- India
- Computer Engineering, Bioinformatics, Algorithms, Database Systems, Data Mining, Dependable Computing, and 107 moreDistributed Computing, Parallel Computing, Power Quality Signal Analysis Using DSP, Digital Signal Processing, Image Processing, Embedded Systems, Games, Grid Computing, Data Intensive Scalable Computing, 16. Intelligent information systems, Database Management Systems, Mobile Technology, Ubiquitous Computing, Modelling and simulation, Multimedia, Computer Networks, Communication, Web Technologies, Semantic Web, Databases, Artificial Intelligence, Signal Processing, Social Networking, Wireless Sensor Networks, Network Security, Software, Software Development, Software Testing, Internet of Things (IoT), Big Data, Datamining, Data Warehousing, Digital Image Processing, Machine Learning, Deep Learning, Computer Vision, Pakistan drone attacks policy, Software Quality Engineering, Software Measurement, Computer Science, Information Technology, Wireless Networks (Computer Science), Computer Science & IT, Internet Computing, Information Technology and Computer Science, Information and Communication Technology,computer Science, Coupled Human and Natural Systems, Computer Architecture and Real time Systems, Computer science & Information Technology, Computer Science and Technology, Intelligent Information & Database Systems, Information Security, Assurance and Audit, Soft Computing, Information Techmology, Computer Security, Informatics, Computer Science and Engineering, Cloud Computing, Education, Human Computer Interaction, Information Systems, E-learning, Internet of Things, Software Engineering, Parallel & Distributed Computing, Information Security, High Performance Computing, Scheduling, Computational Biology, Data Structures, Evolutionary algorithms, Operating Systems, Natural Language Processing, Cyber Physical Systems, Semantic Computing, Distributed Information Systems, Text Mining, Web Applications, Web 2.0, Web Design, Software Architecture, Software Quality, Agile software development, Pattern Recognition, Computer Graphics, Artificial Neural Networks, Robotics, Information Systems (Business Informatics), Wireless networks, Mobile Ad Hoc Networks, Computer Science and IT, Developing Conversation and Vocabulary Skills, Ethical Hacking and Information Security, Wireless Network Security, Computer Science and Information Technology, Fuzzy Logic, Intelligent Systems, Fuzzy Control, Support Vector Machines, Hybrid Systems, Multi Agent Systems and Technologies, Civil Engineering, Science and Technology Studies, Science, Technology and Society, Computer Scince, Open Distance Learning, and Ultimate Bearing Capacityedit
- International Journal of Computer Science & Information Technology (IJCSIT)--H Index 51
INSPEC,WJCI Indexededit
Clouds provide a powerful computing platform that enables individuals and organizations to perform variety levels of tasks such as: use of online storage space, adoption of business applications, development of customized computer... more
Clouds provide a powerful computing platform that enables individuals and organizations to
perform variety levels of tasks such as: use of online storage space, adoption of business
applications, development of customized computer software, and creation of a “realistic”
network environment. In previous years, the number of people using cloud services has
dramatically increased and lots of data has been stored in cloud computing environments. In the
meantime, data breaches to cloud services are also increasing every year due to hackers who are
always trying to exploit the security vulnerabilities of the architecture of cloud. In this paper,
three cloud service models were compared; cloud security risks and threats were investigated
based on the nature of the cloud service models. Real world cloud attacks were included to
demonstrate the techniques that hackers used against cloud computing systems. In addition,
counter measures to cloud security breaches are presented.
perform variety levels of tasks such as: use of online storage space, adoption of business
applications, development of customized computer software, and creation of a “realistic”
network environment. In previous years, the number of people using cloud services has
dramatically increased and lots of data has been stored in cloud computing environments. In the
meantime, data breaches to cloud services are also increasing every year due to hackers who are
always trying to exploit the security vulnerabilities of the architecture of cloud. In this paper,
three cloud service models were compared; cloud security risks and threats were investigated
based on the nature of the cloud service models. Real world cloud attacks were included to
demonstrate the techniques that hackers used against cloud computing systems. In addition,
counter measures to cloud security breaches are presented.
Research Interests:
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in... more
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
Research Interests:
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in... more
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
Research Interests:
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in... more
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
Research Interests:
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in... more
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
Research Interests: Computer Science, Ontology, Web 2.0, Teaching English as a Second Language, Information Security, and 14 moreWeb Design, Machine Learning, Semantics, The big five, Computer Security, Big Dams, Inforamation Technology, Big Five Personality Traits, Big Data, Big Data Analytics, Big Data / Analytics / Data Mining, Big Data Visualisation, Machine Learning Big Data, and Big Data Technologies
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in... more
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
Research Interests: Information Systems, Computer Science, Information Technology, Web 2.0, Ubiquitous Computing, and 15 moreNetwork Security, International Security, Computer Networks, Wireless Sensor Networks, Computer Security, Semantic Web, Mobile Communication, Cloud Computing, Computational Linguistics & NLP, Bigdata, Chatbot, Big Data / Analytics / Data Mining, Natural Language Processing(NLP), Bigdata Hadoop, and ChatGPT
. Image segmentation and classification tasks in computer vision have proven to be highly effective using neural networks, specifically Convolutional Neural Networks (CNNs). These tasks have numerous practical applications, such as in... more
. Image segmentation and classification tasks in computer vision have proven to be highly effective using neural networks, specifically Convolutional Neural Networks (CNNs). These tasks have numerous
practical applications, such as in medical imaging, autonomous driving, and surveillance. CNNs are capable
of learning complex features directly from images and achieving outstanding performance across several
datasets. In this work, we have utilized three different datasets to investigate the efficacy of various preprocessing and classification techniques in accurssedately segmenting and classifying different structures
within the MRI and natural images. We have utilized both sample gradient and Canny Edge Detection
methods for pre-processing, and K-means clustering have been applied to segment the images. Image
augmentation improves the size and diversity of datasets for training the models for image classification.
This work highlights transfer learning’s effectiveness in image classification using CNNs and VGG 16 that
provides insights into the selection of pre-trained models and hyper parameters for optimal performance.
We have proposed a comprehensive approach for image segmentation and classification, incorporating preprocessing techniques, the K-means algorithm for segmentation, and employing deep learning models such
as CNN and VGG 16 for classification.
practical applications, such as in medical imaging, autonomous driving, and surveillance. CNNs are capable
of learning complex features directly from images and achieving outstanding performance across several
datasets. In this work, we have utilized three different datasets to investigate the efficacy of various preprocessing and classification techniques in accurssedately segmenting and classifying different structures
within the MRI and natural images. We have utilized both sample gradient and Canny Edge Detection
methods for pre-processing, and K-means clustering have been applied to segment the images. Image
augmentation improves the size and diversity of datasets for training the models for image classification.
This work highlights transfer learning’s effectiveness in image classification using CNNs and VGG 16 that
provides insights into the selection of pre-trained models and hyper parameters for optimal performance.
We have proposed a comprehensive approach for image segmentation and classification, incorporating preprocessing techniques, the K-means algorithm for segmentation, and employing deep learning models such
as CNN and VGG 16 for classification.
Research Interests:
The security of Electric Vehicle (EV) charging has gained momentum after the increase in the EV adoption in the past few years. Mobile applications have been integrated into EV charging systems that mainly use a cloud-based platform to... more
The security of Electric Vehicle (EV) charging has gained momentum after the increase in the EV adoption
in the past few years. Mobile applications have been integrated into EV charging systems that mainly use a
cloud-based platform to host their services and data. Like many complex systems, cloud systems are
susceptible to cyberattacks if proper measures are not taken by the organization to secure them. In this
paper, we explore the security of key components in the EV charging infrastructure, including the mobile
application and its cloud service. We conducted an experiment that initiated a Man in the Middle attack
between an EV app and its cloud services. Our results showed that it is possible to launch attacks against
the connected infrastructure by taking advantage of vulnerabilities that may have substantial economic and
operational ramifications on the EV charging ecosystem. We conclude by providing mitigation suggestions
and future research directions.
in the past few years. Mobile applications have been integrated into EV charging systems that mainly use a
cloud-based platform to host their services and data. Like many complex systems, cloud systems are
susceptible to cyberattacks if proper measures are not taken by the organization to secure them. In this
paper, we explore the security of key components in the EV charging infrastructure, including the mobile
application and its cloud service. We conducted an experiment that initiated a Man in the Middle attack
between an EV app and its cloud services. Our results showed that it is possible to launch attacks against
the connected infrastructure by taking advantage of vulnerabilities that may have substantial economic and
operational ramifications on the EV charging ecosystem. We conclude by providing mitigation suggestions
and future research directions.
Research Interests:
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in... more
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
Research Interests:
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in... more
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
Research Interests: Computer Science, Ontology, Web 2.0, Information Security, Web Design, and 11 moreNetwork Security, International Security, Web Technologies, Computer Security, Semantic Web, Web Services and SOA, Web Programming, Final Year Project of Computer Science Student, Computer Science Engineering, COMPUTER SCIENCE & ENGINEERING, and Computer Science and Engineering
In this research, we have focused on the most challenging issue that Web Services face, i.e. how to secure their information. Web Services security could be guaranteed by employing security standards, which is the main focus of this... more
In this research, we have focused on the most challenging issue that Web Services face, i.e. how to secure
their information. Web Services security could be guaranteed by employing security standards, which is the
main focus of this search. Every suggested model related to security design should put in the account the
securities' objectives; integrity, confidentiality, non- repudiation, authentication, and authorization. The
proposed model describes SOAP messages and the way to secure their contents. Due to the reason that
SOAP message is the core of the exchanging information in Web Services, this research has developed a
security model needed to ensure e-business security. The essence of our model depends on XML encryption
and XML signature to encrypt and sign SOAP message. The proposed model looks forward to achieve a
high speed of transaction and a strong level of security without jeopardizing the performance of
transmission information.
their information. Web Services security could be guaranteed by employing security standards, which is the
main focus of this search. Every suggested model related to security design should put in the account the
securities' objectives; integrity, confidentiality, non- repudiation, authentication, and authorization. The
proposed model describes SOAP messages and the way to secure their contents. Due to the reason that
SOAP message is the core of the exchanging information in Web Services, this research has developed a
security model needed to ensure e-business security. The essence of our model depends on XML encryption
and XML signature to encrypt and sign SOAP message. The proposed model looks forward to achieve a
high speed of transaction and a strong level of security without jeopardizing the performance of
transmission information.
Research Interests:
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in... more
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
Research Interests:
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in... more
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
Research Interests:
The AIRCC’s International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a peer-reviewed scientific journal published in electronic form as... more
The AIRCC’s International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
Research Interests: Information Systems, Computer Science, Artificial Intelligence, Information Technology, Ontology, and 12 moreWeb 2.0, Information Security, Computer Engineering, Web Design, Semantics, Information Communication Technology, Semantic Web, Web Programming, Big Data, Big Data / Analytics / Data Mining, Computer Science Engineering, and Computer Science and Engineering
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in... more
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
Research Interests: Computer Science, Human Computer Interaction, Information Technology, Ontology, Teaching English as a Second Language, and 12 moreSecond Language Acquisition, Information Security, Computer Engineering, Web Design, Semantics, Network Security, Computer Networks, Ontology (Computer Science), Computer Security, Semantic Web, Cloud Computing, and Syntactic and Semantic Knowledge
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in... more
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
Research Interests:
Interpretation of image contents is one of the objectives in computer vision specifically in image processing. In this era it has received much awareness of researchers. In image interpretation the partition of the image into object and... more
Interpretation of image contents is one of the objectives in computer vision specifically in image
processing. In this era it has received much awareness of researchers. In image interpretation the partition
of the image into object and background is a severe step. Segmentation separates an image into its
component regions or objects. Image segmentation t needs to segment the object from the background to
read the image properly and identify the content of the image carefully. In this context, edge detection is a
fundamental tool for image segmentation. In this paper an attempt is made to study the performance of
most commonly used edge detection techniques for image segmentation and also the comparison of these
techniques is carried out with an experiment by using MATLAB software.
processing. In this era it has received much awareness of researchers. In image interpretation the partition
of the image into object and background is a severe step. Segmentation separates an image into its
component regions or objects. Image segmentation t needs to segment the object from the background to
read the image properly and identify the content of the image carefully. In this context, edge detection is a
fundamental tool for image segmentation. In this paper an attempt is made to study the performance of
most commonly used edge detection techniques for image segmentation and also the comparison of these
techniques is carried out with an experiment by using MATLAB software.
Research Interests:
Practicing the secure software development lifecycle (SSDLC) requires a team of application security experts and a proper management structure. Software developers usually lack application security expertise but are often responsible for... more
Practicing the secure software development lifecycle (SSDLC) requires a team of application security
experts and a proper management structure. Software developers usually lack application security
expertise but are often responsible for software security when management undervalues software security,
or the SSDLC is too expensive to practice. Software developers must have adequate application security
self-efficacy (SE) to execute software security activities and processes effectively. To improve software
developers’ SE, the factors that impact their SE must be identified. A sample of 200 software developers
based in the United States was surveyed for their SE. The relationship between the factors and SE was
analyzed using Spearman’s rho correlation. Application security awareness, the presence of an application
security team, and education level all correlated with software developers’ SE. Security training and
performing multiple application securities did not correlate with software developers’ SE. The results
have practical implications for improving software security.
experts and a proper management structure. Software developers usually lack application security
expertise but are often responsible for software security when management undervalues software security,
or the SSDLC is too expensive to practice. Software developers must have adequate application security
self-efficacy (SE) to execute software security activities and processes effectively. To improve software
developers’ SE, the factors that impact their SE must be identified. A sample of 200 software developers
based in the United States was surveyed for their SE. The relationship between the factors and SE was
analyzed using Spearman’s rho correlation. Application security awareness, the presence of an application
security team, and education level all correlated with software developers’ SE. Security training and
performing multiple application securities did not correlate with software developers’ SE. The results
have practical implications for improving software security.
Research Interests:
Clouds provide a powerful computing platform that enables individuals and organizations to perform variety levels of tasks such as: use of online storage space, adoption of business applications, development of customized computer... more
Clouds provide a powerful computing platform that enables individuals and organizations to perform variety levels of tasks such as: use of online storage space, adoption of business applications, development of customized computer software, and creation of a “realistic” network environment. In previous years, the number of people using cloud services has dramatically increased and lots of data has been stored in cloud computing environments. In the meantime, data breaches to cloud services are also increasing every year due to hackers who are always trying to exploit the security vulnerabilities of the architecture of cloud. In this paper, three cloud service models were compared; cloud security risks and threats were investigated based on the nature of the cloud service models. Real world cloud attacks were included to demonstrate the techniques that hackers used against cloud computing systems. In addition, countermeasures to cloud security breaches are presented.
Research Interests: Computer Science, Human Computer Interaction, Communication, Computer Engineering, Semantics, and 12 moreCognitive Semantics, Information Communication Technology, Lexical Semantics, Semantic Web technology - Ontologies, Semantic Web, Semantics/Pragmatics interface, Semantic Search Engine, Computational Linguistics & NLP, Big Data, Linguistics. Word-formation. Morphology. Lexicology. Semantics., Inofrmation Techology, and Syntactic and Semantic Knowledge
Interpretation of image contents is one of the objectives in computer vision specifically in image processing. In this era it has received much awareness of researchers. In image interpretation the partition of the image into object and... more
Interpretation of image contents is one of the objectives in computer vision specifically in image processing. In this era it has received much awareness of researchers. In image interpretation the partition of the image into object and background is a severe step. Segmentation separates an image into its component regions or objects. Image segmentation t needs to segment the object from the background to read the image properly and identify the content of the image carefully. In this context, edge detection is a fundamental tool for image segmentation. In this paper an attempt is made to study the performance of most commonly used edge detection techniques for image segmentation and also the comparison of these techniques is carried out with an experiment by using MATLAB software.
Research Interests: Computer Science, Human Computer Interaction, Web 2.0, Teaching English as a Second Language, Information Security, and 12 moreComputer Engineering, Web Design, Semantics, Network Security, Security, Web Technologies, Computer Security, Cloud Computing, Computational Mathematics, Web Services and SOA, Web Programming, and Tutoriales De Desarrollo Web
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in... more
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
Research Interests:
The advent of Big Data has seen the emergence of new processing and storage challenges. These challenges are often solved by distributed processing. Distributed systems are inherently dynamic and unstable, so it is realistic to expect... more
The advent of Big Data has seen the emergence of new processing and storage challenges. These challenges are often solved by distributed processing. Distributed systems are inherently dynamic and unstable, so it is realistic to expect that some resources will fail during use. Load balancing and task scheduling is an important step in determining the performance of parallel applications. Hence the need to design load balancing algorithms adapted to grid computing. In this paper, we propose a dynamic and hierarchical load balancing strategy at two levels: Intrascheduler load balancing, in order to avoid the use of the large-scale communication network, and interscheduler load balancing, for a load regulation of our whole system. The strategy allows improving the average response time of CLOAK-Reduce application tasks with minimal communication. We first focus on the three performance indicators, namely response time, process latency and running time of MapReduce tasks.
Research Interests:
Interpretation of image contents is one of the objectives in computer vision specifically in image processing. In this era it has received much awareness of researchers. In image interpretation the partition of the image into object and... more
Interpretation of image contents is one of the objectives in computer vision specifically in image processing. In this era it has received much awareness of researchers. In image interpretation the partition of the image into object and background is a severe step. Segmentation separates an image into its component regions or objects. Image segmentation t needs to segment the object from the background to read the image properly and identify the content of the image carefully. In this context, edge detection is a fundamental tool for image segmentation. In this paper an attempt is made to study the performance of most commonly used edge detection techniques for image segmentation and also the comparison of these techniques is carried out with an experiment by using MATLAB software.
Research Interests:
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in... more
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
Research Interests: Computer Science, Web 2.0, Computer Engineering, Web Design, Semantics, and 7 moreInformation Communication Technology, Semantic Web technology - Ontologies, Semantic Web, Syntactic and Semantic Knowledge, Big Data / Analytics / Data Mining, Informaton Technology, and Computer Science and Engineering
Clouds provide a powerful computing platform that enables individuals and organizations to perform variety levels of tasks such as: use of online storage space, adoption of business applications, development of customized computer... more
Clouds provide a powerful computing platform that enables individuals and organizations to perform variety levels of tasks such as: use of online storage space, adoption of business applications, development of customized computer software, and creation of a-realistic‖ network environment. In previous years, the number of people using cloud services has dramatically increased and lots of data has been stored in cloud computing environments. In the meantime, data breaches to cloud services are also increasing every year due to hackers who are always trying to exploit the security vulnerabilities of the architecture of cloud. In this paper, three cloud service models were compared; cloud security risks and threats were investigated based on the nature of the cloud service models. Real world cloud attacks were included to demonstrate the techniques that hackers used against cloud computing systems. In addition, counter measures to cloud security breaches are presented.
Research Interests:
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in... more
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
Research Interests: Computer Science, Human Computer Interaction, Information Technology, Web 2.0, Computer Engineering, and 12 moreWeb Design, Semantics, Cognitive Semantics, Web Technologies, Information Communication Technology, Lexical Semantics, Semantic Web, Semantics/Pragmatics interface, Web Services and SOA, Ontogeny, Tutoriales De Desarrollo Web, and Computer Science and Engineering
Clouds provide a powerful computing platform that enables individuals and organizations to perform variety levels of tasks such as: use of online storage space, adoption of business applications, development of customized computer... more
Clouds provide a powerful computing platform that enables individuals and organizations to perform variety levels of tasks such as: use of online storage space, adoption of business applications, development of customized computer software, and creation of a-realistic‖ network environment. In previous years, the number of people using cloud services has dramatically increased and lots of data has been stored in cloud computing environments. In the meantime, data breaches to cloud services are also increasing every year due to hackers who are always trying to exploit the security vulnerabilities of the architecture of cloud. In this paper, three cloud service models were compared; cloud security risks and threats were investigated based on the nature of the cloud service models. Real world cloud attacks were included to demonstrate the techniques that hackers used against cloud computing systems. In addition, counter measures to cloud security breaches are presented.
Research Interests: Computer Science, Human Computer Interaction, Information Security, Web Design, Semantics, and 8 moreCognitive Semantics, Information Communication Technology, Lexical Semantics, Semantic Web technology - Ontologies, Semantic Web, Cloud Computing, Web Services and SOA, and Computer Science and Engineering
Interpretation of image contents is one of the objectives in computer vision specifically in image processing. In this era it has received much awareness of researchers. In image interpretation the partition of the image into object and... more
Interpretation of image contents is one of the objectives in computer vision specifically in image processing. In this era it has received much awareness of researchers. In image interpretation the partition of the image into object and background is a severe step. Segmentation separates an image into its component regions or objects. Image segmentation t needs to segment the object from the background to read the image properly and identify the content of the image carefully. In this context, edge detection is a fundamental tool for image segmentation. In this paper an attempt is made to study the performance of most commonly used edge detection techniques for image segmentation and also the comparison of these techniques is carried out with an experiment by using MATLAB software.
Research Interests:
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in... more
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
Research Interests: Computer Science, Information Technology, Ontology, Information Security, Machine Learning, and 13 moreCognitive Semantics, Ubiquitous Computing, Digital Signal Processing, Wireless Sensor Networks, Lexical Semantics, Semantic Web technology - Ontologies, Semantic Web, Computational Linguistics & NLP, Big Data / Analytics / Data Mining, Signals and Systems, Embedded System, Computer Science and Engineering, and Blockchain Technologies
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in... more
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
Research Interests: Computer Science, Information Technology, Information Security, Machine Learning, Electronics, and 9 moreSemantic Web technology - Ontologies, Semantic Web, Arabic NLP, Final Year Project of Computer Science Student, Big Data / Analytics / Data Mining, Computer Science Engineering, Signals and Systems, Embedded System, and Computer Science and Engineering
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in... more
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
Research Interests:
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in... more
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
Research Interests: Computer Science, Human Computer Interaction, Machine Learning, Data Mining, Semantics, and 9 moreCognitive Semantics, Digital Signal Processing, Lexical Semantics, Semantic Web, Web Services and SOA, ECG Signal processing, Big Data / Analytics / Data Mining, Signals and Systems, and Computer Science and Engineering
Interpretation of image contents is one of the objectives in computer vision specifically in image processing. In this era it has received much awareness of researchers. In image interpretation the partition of the image into object and... more
Interpretation of image contents is one of the objectives in computer vision specifically in image processing. In this era it has received much awareness of researchers. In image interpretation the partition of the image into object and background is a severe step. Segmentation separates an image into its component regions or objects. Image segmentation t needs to segment the object from the background to read the image properly and identify the content of the image carefully. In this context, edge detection is a fundamental tool for image segmentation. In this paper an attempt is made to study the performance of most commonly used edge detection techniques for image segmentation and also the comparison of these techniques is carried out with an experiment by using MATLAB software.
Research Interests: Computer Science, Machine Learning, Ubiquitous Computing, Information Communication Technology, Digital Signal Processing, and 9 moreSemantic Web technology - Ontologies, Semantic Web, Electrical, Web Services and SOA, ECG Signal processing, Big Data / Analytics / Data Mining, Computer Science Engineering, Cloud Computing and Virtualization, and Computer Science and Engineering
Clouds provide a powerful computing platform that enables individuals and organizations to perform variety levels of tasks such as: use of online storage space, adoption of business applications, development of customized computer... more
Clouds provide a powerful computing platform that enables individuals and organizations to perform variety levels of tasks such as: use of online storage space, adoption of business applications, development of customized computer software, and creation of a-realistic‖ network environment. In previous years, the number of people using cloud services has dramatically increased and lots of data has been stored in cloud computing environments. In the meantime, data breaches to cloud services are also increasing every year due to hackers who are always trying to exploit the security vulnerabilities of the architecture of cloud. In this paper, three cloud service models were compared; cloud security risks and threats were investigated based on the nature of the cloud service models. Real world cloud attacks were included to demonstrate the techniques that hackers used against cloud computing systems. In addition, counter measures to cloud security breaches are presented.
Research Interests: Information Systems, Electrical Engineering, Computer Science, Human Computer Interaction, Information Technology, and 14 moreWeb 2.0, Computer Engineering, Web Design, Web Technologies, Web Development, Semantic Web, Web Services and SOA, Web Designing, Web Programming, Bigdata, Computer Science and Engineering, Bigdata Analytics, Blockchains, and Blockchain Technologies
Research Interests:
Interpretation of image contents is one of the objectives in computer vision specifically in image processing. In this era it has received much awareness of researchers. In image interpretation the partition of the image into object and... more
Interpretation of image contents is one of the objectives in computer vision specifically in image processing. In this era it has received much awareness of researchers. In image interpretation the partition of the image into object and background is a severe step. Segmentation separates an image into its component regions or objects. Image segmentation t needs to segment the object from the background to read the image properly and identify the content of the image carefully. In this context, edge detection is a fundamental tool for image segmentation. In this paper an attempt is made to study the performance of most commonly used edge detection techniques for image segmentation and also the comparison of these techniques is carried out with an experiment by using MATLAB software.
Research Interests:
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in... more
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
Research Interests: Computer Science, Algorithms, Software Engineering, Information Technology, Communications/DSP, and 10 moreComputer Engineering, Data Mining, Distributed Cognition, The Internet of Things, Applications of Machine Learning, Computational Linguistics & NLP, Parallel & Distributed Computing, Deep Learning, Blockchains, and Web and Internet Computing
Clouds provide a powerful computing platform that enables individuals and organizations to perform variety levels of tasks such as: use of online storage space, adoption of business applications, development of customized computer... more
Clouds provide a powerful computing platform that enables individuals and organizations to perform variety levels of tasks such as: use of online storage space, adoption of business applications, development of customized computer software, and creation of a-realistic‖ network environment. In previous years, the number of people using cloud services has dramatically increased and lots of data has been stored in cloud computing environments. In the meantime, data breaches to cloud services are also increasing every year due to hackers who are always trying to exploit the security vulnerabilities of the architecture of cloud. In this paper, three cloud service models were compared; cloud security risks and threats were investigated based on the nature of the cloud service models. Real world cloud attacks were included to demonstrate the techniques that hackers used against cloud computing systems. In addition, counter measures to cloud security breaches are presented.
Research Interests:
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in... more
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
Research Interests: Bioinformatics, Parallel Computing, Software Engineering, Data Mining, Ubiquitous Computing, and 15 moreMultimedia, Genetic Algorithms, Soft Computing, The Internet of Things, Applications of Machine Learning, Opinion Mining (Data Mining), Software Quality Engineering, Business and Management, DSP, Parallel & Distributed Computing, Deep Learning, Natural Language Processing(NLP), Parallel and Distributed Systems, Geographic Information Systems (GIS), and Blockchain
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in... more
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
Research Interests: Software Engineering, Data Mining, Ubiquitous Computing, Genetic Algorithms, The Internet of Things, and 10 moreData Intensive Scalable Computing, Applications of Machine Learning, NLP, Databases, Software Quality Engineering, Computational Linguistics & NLP, Deep Learning, Big Data, Natural Language Processing(NLP), and Blockchain
Interpretation of image contents is one of the objectives in computer vision specifically in image processing. In this era it has received much awareness of researchers. In image interpretation the partition of the image into object and... more
Interpretation of image contents is one of the objectives in computer vision specifically in image processing. In this era it has received much awareness of researchers. In image interpretation the partition of the image into object and background is a severe step. Segmentation separates an image into its component regions or objects. Image segmentation t needs to segment the object from the background to read the image properly and identify the content of the image carefully. In this context, edge detection is a fundamental tool for image segmentation. In this paper an attempt is made to study the performance of most commonly used edge detection techniques for image segmentation and also the comparison of these techniques is carried out with an experiment by using MATLAB software.
Research Interests: Bioinformatics, Computer Science, Information Technology, Computer Science Education, Image Processing, and 14 moreGenetic Algorithms, Database And Data Mining, DSP, Information and Technology, Engineering and Computer Science, Computer science & Information Technology, Computer Sciencee, COMPUTER SCIENCE & ENGINEERING, Information Technology and System Integration, Automatic Control Electronics and Computer Science, Electronic Engineering and Computer Science, Off-grid Electricity, Game and software engineering, and Grid and Scalable Computing
Clouds provide a powerful computing platform that enables individuals and organizations to perform variety levels of tasks such as: use of online storage space, adoption of business applications, development of customized computer... more
Clouds provide a powerful computing platform that enables individuals and organizations to perform variety levels of tasks such as: use of online storage space, adoption of business applications, development of customized computer software, and creation of a-realistic‖ network environment. In previous years, the number of people using cloud services has dramatically increased and lots of data has been stored in cloud computing environments. In the meantime, data breaches to cloud services are also increasing every year due to hackers who are always trying to exploit the security vulnerabilities of the architecture of cloud. In this paper, three cloud service models were compared; cloud security risks and threats were investigated based on the nature of the cloud service models. Real world cloud attacks were included to demonstrate the techniques that hackers used against cloud computing systems. In addition, counter measures to cloud security breaches are presented.
Research Interests:
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in... more
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
Research Interests:
Clouds provide a powerful computing platform that enables individuals and organizations to perform variety levels of tasks such as: use of online storage space, adoption of business applications, development of customized computer... more
Clouds provide a powerful computing platform that enables individuals and organizations to perform variety levels of tasks such as: use of online storage space, adoption of business applications, development of customized computer software, and creation of a "realistic" network environment. In previous years, the number of people using cloud services has dramatically increased and lots of data has been stored in cloud computing environments. In the meantime, data breaches to cloud services are also increasing every year due to hackers who are always trying to exploit the security vulnerabilities of the architecture of cloud. In this paper, three cloud service models were compared; cloud security risks and threats were investigated based on the nature of the cloud service models. Real world cloud attacks were included to demonstrate the techniques that hackers used against cloud computing systems. In addition,countermeasures to cloud security breaches are presented.
Research Interests:
Clouds provide a powerful computing platform that enables individuals and organizations to perform variety levels of tasks such as: use of online storage space, adoption of business applications, development of customized computer... more
Clouds provide a powerful computing platform that enables individuals and organizations to perform variety levels of tasks such as: use of online storage space, adoption of business applications, development of customized computer software, and creation of a "realistic" network environment. In previous years, the number of people using cloud services has dramatically increased and lots of data has been stored in cloud computing environments. In the meantime, data breaches to cloud services are also increasing every year due to hackers who are always trying to exploit the security vulnerabilities of the architecture of cloud. In this paper, three cloud service models were compared; cloud security risks and threats were investigated based on the nature of the cloud service models. Real world cloud attacks were included to demonstrate the techniques that hackers used against cloud computing systems. In addition, countermeasures to cloud security breaches are presented.
Research Interests: Computer Science, Information Technology, Machine Learning, Classification (Machine Learning), Soft Computing, and 9 moreThe Internet of Things, Modeling and Simulation, Big Data, Internet of Things (IoT), Big Data Analytics, COMPUTER SCIENCE & ENGINEERING, Information Technology and System Integration, Natural Language Processing(NLP), and Data Communications and Networking
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in... more
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
Research Interests:
The research project of the World Journal Clout Index Catalogue (2020 STM) is supported by China Association for Science and Technology. The project team consists of the evaluation and research departments of China Academic Journals (CD... more
The research project of the World Journal Clout Index Catalogue (2020 STM) is supported by China Association for Science and Technology. The project team consists of the evaluation and research departments of China Academic Journals (CD Edition) Electronic Publishing House Co., Ltd., Institute of Scientific and Technical Information of China, Tsinghua
University Library, Society of China University Journals, and Wanfang Data Co., Ltd.
University Library, Society of China University Journals, and Wanfang Data Co., Ltd.
Research Interests:
Computer Science & Information Technology (CS & IT) is an open access-Computer Science Conference Proceedings (CSCP) series that welcomes conferences to publish their proceedings / post conference proceedings. This series intends to focus... more
Computer Science & Information Technology (CS & IT) is an open access-Computer Science Conference Proceedings (CSCP) series that welcomes conferences to publish their proceedings / post conference proceedings. This series intends to focus on publishing high quality papers to help the scientific community furthering our goal to preserve and disseminate scientific knowledge. Conference proceedings are accepted for publication in CS & IT - CSCP based on peer-reviewed full papers and revised short papers that target international scientific community and latest IT trends. Our mission is to provide the most valuable publication service. More. . .
Research Interests:
Clouds provide a powerful computing platform that enables individuals and organizations to perform variety levels of tasks such as: use of online storage space, adoption of business applications, development of customized computer... more
Clouds provide a powerful computing platform that enables individuals and organizations to perform variety levels of tasks such as: use of online storage space, adoption of business applications, development of customized computer software, and creation of a "realistic" network environment. In previous years, the number of people using cloud services has dramatically increased and lots of data has been stored in cloud computing environments. In the meantime, data breaches to cloud services are also increasing every year due to hackers who are always trying to exploit the security vulnerabilities of the architecture of cloud. In this paper, three cloud service models were compared; cloud security risks and threats were investigated based on the nature of the cloud service models. Real world cloud attacks were included to demonstrate the techniques that hackers used against cloud computing systems. In addition,countermeasures to cloud security breaches are presented.
Research Interests: Information Systems, Computer Science, Information Technology, Computer Science Education, Information Security, and 11 moreData Mining, Computer Networks, Clouds, Computer Security, Cloud Computing, Computer and Information Technology, Information and Technology, Cloud Computing Security, COMPUTER SCIENCE & ENGINEERING, Cloud Computing and Virtualization, and Computer Science and Engineering
11th International Conference on Foundations of Computer Science & Technology (CST 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Computer Science &... more
11th International Conference on Foundations of Computer Science & Technology (CST 2024)
will provide an excellent international forum for sharing knowledge and results in theory,
methodology and applications of Computer Science & Technology. The goal of this Conference is to
bring together researchers and practitioners from academia and industry to focus on understanding
Modern Computer Science & Technology concepts and establishing new collaborations in these areas.
will provide an excellent international forum for sharing knowledge and results in theory,
methodology and applications of Computer Science & Technology. The goal of this Conference is to
bring together researchers and practitioners from academia and industry to focus on understanding
Modern Computer Science & Technology concepts and establishing new collaborations in these areas.
Research Interests: Logic And Foundations Of Mathematics, Algorithms, Quantum Physics, Quantum Chemistry, Evolutionary algorithms, and 14 moreMachine Learning, Quantum Information, Foundations of Quantum Mechanics, Genetic Algorithms, Design and Analysis of Algorithms, Graph/Network Algorithms, Data Structures and Algorithms, Seismic soil-structure interaction (pile foundations), Social Foundations of Education, Bio and Nature Inspired Algorithms, Educational Foundations and Leadership, Datastructures and Algorithms, Bachelor of Education - Foundations of Educations, and Soil Foundations
3 rd International Conference on Machine Learning, NLP and Data Mining (MLDA 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Machine Learning, Natural... more
3
rd International Conference on Machine Learning, NLP and Data Mining (MLDA 2024) will
provide an excellent international forum for sharing knowledge and results in theory, methodology and
applications of Machine Learning, Natural Language Computing and Data Mining.
rd International Conference on Machine Learning, NLP and Data Mining (MLDA 2024) will
provide an excellent international forum for sharing knowledge and results in theory, methodology and
applications of Machine Learning, Natural Language Computing and Data Mining.
Research Interests: Mining Engineering, Machine Learning, Data Mining, Classification (Machine Learning), Text Mining, and 14 moreApplications of Machine Learning, Statistical machine learning, Mining, Computational Linguistics & NLP, Arabic NLP, Mining Law, Machine Learning and Pattern Recognition, Mining method selection, MAchine Learning Algorithms, Big Data / Analytics / Data Mining, Natural Language Processing(NLP), Machine Learning Big Data, Applied Machine Learning, and Machine Learning in Python
8 th International Conference on Electrical & Computer Engineering (E& C 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications impacts and challenges of Electrical &... more
8
th International Conference on Electrical & Computer Engineering (E& C 2024) will
provide an excellent international forum for sharing knowledge and results in theory,
methodology and applications impacts and challenges of Electrical & Computer Engineering.
The conference documents practical and theoretical results which make a fundamental
contribution for the development of Electrical & Computer Engineering. The aim of the
conference is to provide a platform to the researchers and practitioners from both academia as
well as industry to meet and share cutting-edge development in the field.
th International Conference on Electrical & Computer Engineering (E& C 2024) will
provide an excellent international forum for sharing knowledge and results in theory,
methodology and applications impacts and challenges of Electrical & Computer Engineering.
The conference documents practical and theoretical results which make a fundamental
contribution for the development of Electrical & Computer Engineering. The aim of the
conference is to provide a platform to the researchers and practitioners from both academia as
well as industry to meet and share cutting-edge development in the field.
Research Interests: Electrical Engineering, Computer Engineering, Electrical, Electrical and Electronics, Electrical Circuit Theory, and 11 moreElectrical Drives, Electrical Engineering Technology, Electrical Circuit Analysis, Computer Science Engineering, COMPUTER SCIENCE & ENGINEERING, Electrical Power Engineering, Electrical and Computer Engineering (ECE), Computer Science and Engineering, Electrical And Electronic Engineering, Electrical and Computer Engineering, and Electrical and Electronics Engineering
9 th International Conference on Education (EDU 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications impacts and challenges of education. The conference documents... more
9
th International Conference on Education (EDU 2024) will provide an excellent
international forum for sharing knowledge and results in theory, methodology and
applications impacts and challenges of education. The conference documents practical and
theoretical results which make a fundamental contribution for the development of
Educational research. The goal of this conference is to bring together researchers and
practitioners from academia and industry to focus on Educational advancements and
establishing new collaborations in these areas. Original research papers, state-of-the-art
reviews are invited for publication in all areas of Education.
th International Conference on Education (EDU 2024) will provide an excellent
international forum for sharing knowledge and results in theory, methodology and
applications impacts and challenges of education. The conference documents practical and
theoretical results which make a fundamental contribution for the development of
Educational research. The goal of this conference is to bring together researchers and
practitioners from academia and industry to focus on Educational advancements and
establishing new collaborations in these areas. Original research papers, state-of-the-art
reviews are invited for publication in all areas of Education.
Research Interests: Music Education, Education, Educational Technology, Teacher Education, Science Education, and 12 moreChemistry Education, Higher Education, Mathematics Education, Educational Psychology, Educational Research, Early Childhood Education, ICT in Education, Bilingual Education, Physics Education, Physical Education, English Education, and Educations
Research Interests: Computer Science, Algorithms, Computational Linguistics & NLP, Science Computer, Computer Sciencee, and 10 moreFinal Year Project of Computer Science Student, Computer Science Engineering, COMPUTER SCIENCE & ENGINEERING, Computer Science and Engineering, Blockchains, Blockchain, Blockchain Technologies, Blockchains Technology and Creative Industries, Blockchain technology in financial sector, and Blockchain Law
Computer Science & Engineering: An International Journal (CSEIJ) is a bi-monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Computer Science & Computer Engineering. The... more
Computer Science & Engineering: An International Journal (CSEIJ) is a bi-monthly open access
peer-reviewed journal that publishes articles which contribute new results in all areas of the
Computer Science & Computer Engineering. The journal is devoted to the publication of high
quality papers on theoretical and practical aspects of computer science and computer Engineering
peer-reviewed journal that publishes articles which contribute new results in all areas of the
Computer Science & Computer Engineering. The journal is devoted to the publication of high
quality papers on theoretical and practical aspects of computer science and computer Engineering
Research Interests: Computer Science, Robotics (Computer Science), Computer Science Education, Science Computer, Computer Sciencee, and 7 moreFinal Year Project of Computer Science Student, Computer Science and Information Technology, Computer Science Engineering, COMPUTER SCIENCE & ENGINEERING, Computer Science and Engineering, Electrical Engineering and Computer Science, and International Journal of Computer Science Engineering and Information Technology Research (IJCSEITR)
In this paper, we examine the use of Bayesian Hierarchical Models (BHMs) for multi-level credit risk assessment while focusing on their advantages compared to conventional valuation approaches of single-level models. Unlike most... more
In this paper, we examine the use of Bayesian Hierarchical Models (BHMs) for multi-level credit risk assessment while focusing on their advantages compared to conventional valuation approaches of single-level models. Unlike most traditional methodologies, which consider events either separately or condition on an aggregate measure, each of the BHMs systematically incorporates data from different levels — loan or obligor level and institution level — to provide a more holistic view of credit risk under numerous uncertainties and dependencies. The paper reviews basic theoretical underpinnings of BHMs, such as Bayesian inference and hierarchical Modeling, while giving examples on how these mechanisms work in practice within the context of estimating default risk. In addition, the paper outlines computational challenges, highlights the role of prior distributions, and explains that BHMs could potentially be combined with machine learning for dynamic risk assessments. The paper highlights a real-world application, and provides detailed insights into how BHMs can help improve both the accuracy and interpretability of credit risk assessments.
Research Interests:
Colors possess extraordinary ability to evoke feelings, memories and even influence the processes of enactment decisions. This interdisciplinary study brings together elements of psychology, the human psyche and art as science. From the... more
Colors possess extraordinary ability to evoke feelings, memories and even influence the processes of enactment decisions. This interdisciplinary study brings together elements of psychology, the human psyche and art as science. From the soothing embrace of the cold blue color to the energetic liveliness of warm red, each color carries its own psychological weight, capable of shaping our mood and affect the way we interpret the world around us. It all starts when light enters the eye and passes through the photoreceptor cells in the retina, during which refraction occurs, where the magic of color perception happens. The brain then seamlessly integrates these signals, allowing us to perceive colors that make it up visible spectrum. Objects we see around us do not have real color and colors exist, but only as a visual sensation in our brain. The actual color of objects that our brain sees depends on the amount of light that will be received or reflected from the surface of objects. In this exploration of color psychology in this paper I will decode the language of shades, to discover the subtle and profound ways in which color will shape our perceptions and how they influence in decision making.
Research Interests:
The percentage of unpredictable renewable power in the power grid will dramatically rise as a result of the present trend in energy , development. The power system's stability could be impacted by this. Therefore, one of the major... more
The percentage of unpredictable renewable power in the power grid will dramatically rise as a result of the
present trend in energy , development. The power system's stability could be impacted by this. Therefore,
one of the major technologies for the development of green energy is the battery-based Energy Storage
System (ESS) with quick reaction control capabilities. In this thesis, a method for determining the best ESS
capacity is suggested. It is based on estimates of the lithium iron phosphate battery's lifetime for various
converter topologies. Two goal functions are taken into consideration in order to get the best capacity and
prevent overinvestment
present trend in energy , development. The power system's stability could be impacted by this. Therefore,
one of the major technologies for the development of green energy is the battery-based Energy Storage
System (ESS) with quick reaction control capabilities. In this thesis, a method for determining the best ESS
capacity is suggested. It is based on estimates of the lithium iron phosphate battery's lifetime for various
converter topologies. Two goal functions are taken into consideration in order to get the best capacity and
prevent overinvestment
Research Interests:
Blockchain is revolutionizing the field of financial services by presenting a secure and decentralized framework that enhances efficiency and trust. This framework spans the entire spectrum of finance and financial services, from simple... more
Blockchain is revolutionizing the field of financial services by presenting a secure and decentralized
framework that enhances efficiency and trust. This framework spans the entire spectrum of finance and
financial services, from simple transfers to complex management and regulation. This technology has the
potential to reduce the need for intermediaries while also lowering the cost of doing business and potential
fraud avenues and fostering greater express transactions. The very design of this open, shared record
ensures that all networks have access to the same document, which cannot be altered. Blocks validate
transactions, and users have a say over it. Smart contracts provide the most convenient transaction process
by eliminating human error and spike earnings. Furthermore, the integration of blockchain in the financial
sector confronts several problems. Some of those are dependency, variation, and stability. Nevertheless,
this technology makes financial markets more secure, effective, and open which results in new goods and
business environments.
framework that enhances efficiency and trust. This framework spans the entire spectrum of finance and
financial services, from simple transfers to complex management and regulation. This technology has the
potential to reduce the need for intermediaries while also lowering the cost of doing business and potential
fraud avenues and fostering greater express transactions. The very design of this open, shared record
ensures that all networks have access to the same document, which cannot be altered. Blocks validate
transactions, and users have a say over it. Smart contracts provide the most convenient transaction process
by eliminating human error and spike earnings. Furthermore, the integration of blockchain in the financial
sector confronts several problems. Some of those are dependency, variation, and stability. Nevertheless,
this technology makes financial markets more secure, effective, and open which results in new goods and
business environments.
Research Interests:
Home security is of paramount importance in today's world, where we rely more on technology, home security is crucial. Using technology to make homes safer and easier to control from anywhere is important. Home security is important for... more
Home security is of paramount importance in today's world, where we rely more on technology, home
security is crucial. Using technology to make homes safer and easier to control from anywhere is
important. Home security is important for the occupant’s safety. In this paper, we came up with a low cost,
AI based model home security system. The system has a user-friendly interface, allowing users to start
model training and face detection with simple keyboard commands. Our goal is to introduce an innovative
home security system using facial recognition technology. Unlike traditional systems, this system trains
and saves images of friends and family members. The system scans this folder to recognize familiar faces
and provides real-time monitoring. If an unfamiliar face is detected, it promptly sends an email alert,
ensuring a proactive response to potential security threats.
security is crucial. Using technology to make homes safer and easier to control from anywhere is
important. Home security is important for the occupant’s safety. In this paper, we came up with a low cost,
AI based model home security system. The system has a user-friendly interface, allowing users to start
model training and face detection with simple keyboard commands. Our goal is to introduce an innovative
home security system using facial recognition technology. Unlike traditional systems, this system trains
and saves images of friends and family members. The system scans this folder to recognize familiar faces
and provides real-time monitoring. If an unfamiliar face is detected, it promptly sends an email alert,
ensuring a proactive response to potential security threats.
Research Interests:
In the era of data-driven warfare, the integration of big data and machine learning (ML) techniques has become paramount for enhancing defence capabilities. This research report delves into the applications of big data and ML in the... more
In the era of data-driven warfare, the integration of big data and machine learning (ML) techniques has become paramount for enhancing defence capabilities. This research report delves into the applications of
big data and ML in the defence sector, exploring their potential to revolutionize intelligence gathering, strategic decision-making, and operational efficiency. By leveraging vast amounts of data and advanced
algorithms, these technologies offer unprecedented opportunities for threat detection, predictive analysis, and optimized resource allocation. However, their adoption also raises critical concerns regarding data
privacy, ethical implications, and the potential for misuse. This report aims to provide a comprehensive understanding of the current state of big data and ML in defence, while examining the challenges and
ethical considerations that must be addressed to ensure responsible and effective implementation.
big data and ML in the defence sector, exploring their potential to revolutionize intelligence gathering, strategic decision-making, and operational efficiency. By leveraging vast amounts of data and advanced
algorithms, these technologies offer unprecedented opportunities for threat detection, predictive analysis, and optimized resource allocation. However, their adoption also raises critical concerns regarding data
privacy, ethical implications, and the potential for misuse. This report aims to provide a comprehensive understanding of the current state of big data and ML in defence, while examining the challenges and
ethical considerations that must be addressed to ensure responsible and effective implementation.
Research Interests:
Cloud Computing, being one of the most recent innovative developments of the IT world, has been instrumental not just to the success of SMEs but, through their productivity and innovative contribution to the economy, has even made a... more
Cloud Computing, being one of the most recent innovative developments of the IT world, has been
instrumental not just to the success of SMEs but, through their productivity and innovative contribution to
the economy, has even made a remarkable contribution to the economic growth of the United States. To
this end, the study focuses on how cloud computing technology has impacted economic growth through
SMEs in the United States. Relevant literature connected to the variables of interest in this study was
reviewed, and secondary data was generated and utilized in the analysis section of this paper. The findings
of this paper revealed that there have been meaningful contributions that the usage of virtualization has
made in the commercial dealings of small firms in the United States, and this has also been reflected in the
economic growth of the country. This paper further revealed that as important as cloud-based software is,
some SMEs are still skeptical about how it can help improve their business and increase their bottom line
and hence have failed to adopt it. Apart from the SMEs, some notable large firms in different industries,
including information and educational services, have adopted cloud computing technology and hence
contributed to the economic growth of the United States. Lastly, findings from our inferential statistics
revealed that no discernible change has occurred in innovation between small and big businesses in the
adoption of cloud computing. Both categories of businesses adopt cloud computing in the same way, and
their contribution to the American economy has no significant difference in the usage of virtualization.
instrumental not just to the success of SMEs but, through their productivity and innovative contribution to
the economy, has even made a remarkable contribution to the economic growth of the United States. To
this end, the study focuses on how cloud computing technology has impacted economic growth through
SMEs in the United States. Relevant literature connected to the variables of interest in this study was
reviewed, and secondary data was generated and utilized in the analysis section of this paper. The findings
of this paper revealed that there have been meaningful contributions that the usage of virtualization has
made in the commercial dealings of small firms in the United States, and this has also been reflected in the
economic growth of the country. This paper further revealed that as important as cloud-based software is,
some SMEs are still skeptical about how it can help improve their business and increase their bottom line
and hence have failed to adopt it. Apart from the SMEs, some notable large firms in different industries,
including information and educational services, have adopted cloud computing technology and hence
contributed to the economic growth of the United States. Lastly, findings from our inferential statistics
revealed that no discernible change has occurred in innovation between small and big businesses in the
adoption of cloud computing. Both categories of businesses adopt cloud computing in the same way, and
their contribution to the American economy has no significant difference in the usage of virtualization.
Research Interests:
Energy-constrained Wireless Sensor Networks (WSNs) have garnered significant research interest in recent years. Multiple-Input Multiple-Output (MIMO), or Cooperative MIMO, represents a specialized application of MIMO technology within... more
Energy-constrained Wireless Sensor Networks (WSNs) have garnered significant research interest in
recent years. Multiple-Input Multiple-Output (MIMO), or Cooperative MIMO, represents a specialized
application of MIMO technology within WSNs. This approach operates effectively, especially in
challenging and resource-constrained environments. By facilitating collaboration among sensor nodes,
Cooperative MIMO enhances reliability, coverage, and energy efficiency in WSN deployments.
Consequently, MIMO finds application in diverse WSN scenarios, spanning environmental monitoring,
industrial automation, and healthcare applications.
recent years. Multiple-Input Multiple-Output (MIMO), or Cooperative MIMO, represents a specialized
application of MIMO technology within WSNs. This approach operates effectively, especially in
challenging and resource-constrained environments. By facilitating collaboration among sensor nodes,
Cooperative MIMO enhances reliability, coverage, and energy efficiency in WSN deployments.
Consequently, MIMO finds application in diverse WSN scenarios, spanning environmental monitoring,
industrial automation, and healthcare applications.
Research Interests:
With growing, Car parking increases with the number of car users. With the increased use of smartphones and their applications, users prefer mobile phone-based solutions. This paper proposes the Smart Parking Management System (SPMS) that... more
With growing, Car parking increases with the number of car users. With the increased use of smartphones
and their applications, users prefer mobile phone-based solutions. This paper proposes the Smart Parking
Management System (SPMS) that depends on Arduino parts, Android applications, and based on IoT. This
gave the client the ability to check available parking spaces and reserve a parking spot. IR sensors are
utilized to know if a car park space is allowed. Its area data are transmitted using the WI-FI module to the
server and are recovered by the mobile application which offers many options attractively and with no cost
to users and lets the user check reservation details. With IoT technology, the smart parking system can be
connected wirelessly to easily track available locations.
and their applications, users prefer mobile phone-based solutions. This paper proposes the Smart Parking
Management System (SPMS) that depends on Arduino parts, Android applications, and based on IoT. This
gave the client the ability to check available parking spaces and reserve a parking spot. IR sensors are
utilized to know if a car park space is allowed. Its area data are transmitted using the WI-FI module to the
server and are recovered by the mobile application which offers many options attractively and with no cost
to users and lets the user check reservation details. With IoT technology, the smart parking system can be
connected wirelessly to easily track available locations.
Research Interests:
Computer-Assisted Language Learning (CALL) are computer-based tutoring systems that deal with linguistic skills. Adding intelligence in such systems is mainly based on using Natural Language Processing (NLP) tools to diagnose student... more
Computer-Assisted Language Learning (CALL) are computer-based tutoring systems that deal with
linguistic skills. Adding intelligence in such systems is mainly based on using Natural Language
Processing (NLP) tools to diagnose student errors, especially in language grammar. However, most such
systems do not consider the modeling of student competence in linguistic skills, especially for the Arabic
language. In this paper, we will deal with basic grammar concepts of the Arabic language taught for the
fourth grade of the elementary school in Egypt. This is through Arabic Grammar Trainer (AGTrainer)
which is an Intelligent CALL. The implemented system (AGTrainer) trains the students through different
questions that deal with the different concepts and have different difficulty levels. Constraint-based student
modeling (CBSM) technique is used as a short-term student model. CBSM is used to define in small grain
level the different grammar skills through the defined skill structures. The main contribution of this paper
is the hierarchal representation of the system's basic grammar skills as domain knowledge. That
representation is used as a mechanism for efficiently checking constraints to model the student knowledge
and diagnose the student errors and identify their cause. In addition, satisfying constraints and the number
of trails the student takes for answering each question and fuzzy logic decision system are used to
determine the student learning level for each lesson as a long-term model. The results of the evaluation
showed the system's effectiveness in learning in addition to the satisfaction of students and teachers with its
features and abilities.
linguistic skills. Adding intelligence in such systems is mainly based on using Natural Language
Processing (NLP) tools to diagnose student errors, especially in language grammar. However, most such
systems do not consider the modeling of student competence in linguistic skills, especially for the Arabic
language. In this paper, we will deal with basic grammar concepts of the Arabic language taught for the
fourth grade of the elementary school in Egypt. This is through Arabic Grammar Trainer (AGTrainer)
which is an Intelligent CALL. The implemented system (AGTrainer) trains the students through different
questions that deal with the different concepts and have different difficulty levels. Constraint-based student
modeling (CBSM) technique is used as a short-term student model. CBSM is used to define in small grain
level the different grammar skills through the defined skill structures. The main contribution of this paper
is the hierarchal representation of the system's basic grammar skills as domain knowledge. That
representation is used as a mechanism for efficiently checking constraints to model the student knowledge
and diagnose the student errors and identify their cause. In addition, satisfying constraints and the number
of trails the student takes for answering each question and fuzzy logic decision system are used to
determine the student learning level for each lesson as a long-term model. The results of the evaluation
showed the system's effectiveness in learning in addition to the satisfaction of students and teachers with its
features and abilities.
Research Interests:
This research aims to further understanding in the field of continuous authentication using behavioural biometrics. We are contributing a novel dataset that encompasses the gesture data of 15 users playing Minecraft with a Samsung Tablet,... more
This research aims to further understanding in the field of continuous authentication using behavioural
biometrics. We are contributing a novel dataset that encompasses the gesture data of 15 users playing
Minecraft with a Samsung Tablet, each for a duration of 15 minutes. Utilizing this dataset, we employed
machine learning (ML) binary classifiers, being Random Forest (RF), K-Nearest Neighbors (KNN), and
Support Vector Classifier (SVC), to determine the authenticity of specific user actions. Our most robust
model was SVC, which achieved an average accuracy of approximately 90%, demonstrating that touch
dynamics can effectively distinguish users. However, further studies are needed to make it viable option
for authentication systems. You can access our dataset at the following
link:https://github.com/AuthenTech2023/authentech-repo
biometrics. We are contributing a novel dataset that encompasses the gesture data of 15 users playing
Minecraft with a Samsung Tablet, each for a duration of 15 minutes. Utilizing this dataset, we employed
machine learning (ML) binary classifiers, being Random Forest (RF), K-Nearest Neighbors (KNN), and
Support Vector Classifier (SVC), to determine the authenticity of specific user actions. Our most robust
model was SVC, which achieved an average accuracy of approximately 90%, demonstrating that touch
dynamics can effectively distinguish users. However, further studies are needed to make it viable option
for authentication systems. You can access our dataset at the following
link:https://github.com/AuthenTech2023/authentech-repo
Research Interests:
This paper discusses the capabilities and limitations of GPT-3 (0), a state-of-the-art language model, in the context of text understanding. We begin by describing the architecture and training process of GPT-3, and provide an overview of... more
This paper discusses the capabilities and limitations of GPT-3 (0), a state-of-the-art language model, in the context of text understanding. We begin by describing the architecture and training process of GPT-3, and provide an overview of its impressive performance across a wide range of natural language processing tasks, such as language translation, question-answering, and text completion. Throughout this research project, a summarizing tool was also created to help us retrieve content from any types of document, specifically IELTS (0) Reading Test data in this project. We also aimed to improve the accuracy of the summarizing, as well as question-answering capabilities of GPT-3 (0) via long text.
Research Interests:
In the realm of computer security, the importance of efficient and reliable user authentication methods has become increasingly critical. This paper examines the potential of mouse movement dynamics as a consistent metric for continuous... more
In the realm of computer security, the importance of efficient and reliable user authentication methods has
become increasingly critical. This paper examines the potential of mouse movement dynamics as a
consistent metric for continuous authentication. By analysing user mouse movement patterns in two
contrasting gaming scenarios, "Team Fortress" and "Poly Bridge," we investigate the distinctive
behavioral patterns inherent in high-intensity and low-intensity UI interactions. The study extends beyond
conventional methodologies by employing a range of machine learning models. These models are carefully
selected to assess their effectiveness in capturing and interpreting the subtleties of user behavior as
reflected in their mouse movements. This multifaceted approach allows for a more nuanced and
comprehensive understanding of user interaction patterns. Our findings reveal that mouse movement
dynamics can serve as a reliable indicator for continuous user authentication. The diverse machine
learning models employed in this study demonstrate competent performance in user verification, marking
an improvement over previous methods used in this field. This research contributes to the ongoing efforts to
enhance computer security and highlights the potential of leveraging user behavior, specifically mouse
dynamics, in developing robust authentication systems.
become increasingly critical. This paper examines the potential of mouse movement dynamics as a
consistent metric for continuous authentication. By analysing user mouse movement patterns in two
contrasting gaming scenarios, "Team Fortress" and "Poly Bridge," we investigate the distinctive
behavioral patterns inherent in high-intensity and low-intensity UI interactions. The study extends beyond
conventional methodologies by employing a range of machine learning models. These models are carefully
selected to assess their effectiveness in capturing and interpreting the subtleties of user behavior as
reflected in their mouse movements. This multifaceted approach allows for a more nuanced and
comprehensive understanding of user interaction patterns. Our findings reveal that mouse movement
dynamics can serve as a reliable indicator for continuous user authentication. The diverse machine
learning models employed in this study demonstrate competent performance in user verification, marking
an improvement over previous methods used in this field. This research contributes to the ongoing efforts to
enhance computer security and highlights the potential of leveraging user behavior, specifically mouse
dynamics, in developing robust authentication systems.
Research Interests:
This paper describes the outcome of an attempt to implement the same transitive closure (TC) algorithm for Apache MapReduce running on different Apache Hadoop distributions. Apache MapReduce is a software framework used with Apache... more
This paper describes the outcome of an attempt to implement the same transitive closure (TC) algorithm
for Apache MapReduce running on different Apache Hadoop distributions. Apache MapReduce is a
software framework used with Apache Hadoop, which has become the de facto standard platform for
processing and storing large amounts of data in a distributed computing environment. The research
presented here focuses on the variations observed among the results of an efficient iterative transitive
closure algorithm when run against different distributed environments. The results from these comparisons
were validated against the benchmark results from OYSTER, an open source Entity Resolution system. The
experiment results highlighted the inconsistencies that can occur when using the same codebase with
different implementations of Map Reduce.
for Apache MapReduce running on different Apache Hadoop distributions. Apache MapReduce is a
software framework used with Apache Hadoop, which has become the de facto standard platform for
processing and storing large amounts of data in a distributed computing environment. The research
presented here focuses on the variations observed among the results of an efficient iterative transitive
closure algorithm when run against different distributed environments. The results from these comparisons
were validated against the benchmark results from OYSTER, an open source Entity Resolution system. The
experiment results highlighted the inconsistencies that can occur when using the same codebase with
different implementations of Map Reduce.
Research Interests:
In the ever-changing field of software testing and automation, this study brings attention to the frequently underestimated yet crucial role of test design. By highlighting its significant influence on the success of automation... more
In the ever-changing field of software testing and automation, this study brings attention to the frequently
underestimated yet crucial role of test design. By highlighting its significant influence on the success of
automation initiatives, this investigation aims to reveal the fundamental principles that serve as the basis of
effective testing strategies. Going beyond the surface, the study explores the complexities of test design,
uncovering its strategic impact on optimizing the creation of test cases, enhancing test coverage, and
ultimately improving the efficiency and dependability of automated testing processes. Through the use of
real-life examples and practical insights, this study strives to elucidate the methods by which professionals
can harness the strategic potential of test design, leading to a shift in the way automation is understood
and implemented. As we delve into the various layers of this foundational element, a deeper comprehension
emerges, empowering testing experts to strategically employ test design for comprehensive and influential
automation endeavors.
underestimated yet crucial role of test design. By highlighting its significant influence on the success of
automation initiatives, this investigation aims to reveal the fundamental principles that serve as the basis of
effective testing strategies. Going beyond the surface, the study explores the complexities of test design,
uncovering its strategic impact on optimizing the creation of test cases, enhancing test coverage, and
ultimately improving the efficiency and dependability of automated testing processes. Through the use of
real-life examples and practical insights, this study strives to elucidate the methods by which professionals
can harness the strategic potential of test design, leading to a shift in the way automation is understood
and implemented. As we delve into the various layers of this foundational element, a deeper comprehension
emerges, empowering testing experts to strategically employ test design for comprehensive and influential
automation endeavors.
Research Interests:
This study proposes a method for consolidating various program accreditations into a unified accreditation process for a single academic program. The primary challenge lies in harmonizing the diverse requirements of multiple... more
This study proposes a method for consolidating various program accreditations into a unified
accreditation process for a single academic program. The primary challenge lies in harmonizing the
diverse requirements of multiple accreditations. In the context of academic technology programs in Saudi
Arabia, this research focuses on the integration of NCAAA and ABET accreditations, with a specific
application to the Information Systems at King Abdulaziz university. The core methodology employed in
this study involves applying Bloom's taxonomy of learning to identify the synergies between the
accreditation criteria of ABET and NCAAA. To ascertain the alignment of learning outcome measurement
based on both accreditations, a questionnaire was administered to faculty members within the College of
Computer Science and Information Technology at renowned universities in the Kingdom of Saudi Arabia.
This article is intended for researchers specializing in the quality of education in computing and
engineering, as well as professionals, developers, and officials with an interest in academic accreditations.
Furthermore, this research seeks to establish a foundation for the seamless dissemination of educational
content through websites and digital applications, adhering to the standards and principles of academic
accreditation.
accreditation process for a single academic program. The primary challenge lies in harmonizing the
diverse requirements of multiple accreditations. In the context of academic technology programs in Saudi
Arabia, this research focuses on the integration of NCAAA and ABET accreditations, with a specific
application to the Information Systems at King Abdulaziz university. The core methodology employed in
this study involves applying Bloom's taxonomy of learning to identify the synergies between the
accreditation criteria of ABET and NCAAA. To ascertain the alignment of learning outcome measurement
based on both accreditations, a questionnaire was administered to faculty members within the College of
Computer Science and Information Technology at renowned universities in the Kingdom of Saudi Arabia.
This article is intended for researchers specializing in the quality of education in computing and
engineering, as well as professionals, developers, and officials with an interest in academic accreditations.
Furthermore, this research seeks to establish a foundation for the seamless dissemination of educational
content through websites and digital applications, adhering to the standards and principles of academic
accreditation.
Research Interests:
In the software industry, two software engineering development best practices coexist: open-source and closed-source software. The former has a shared code that anyone can contribute, whereas the latter has a proprietary code that only... more
In the software industry, two software engineering development best practices coexist: open-source and
closed-source software. The former has a shared code that anyone can contribute, whereas the latter has a
proprietary code that only the owner can access. Software reliability is crucial in the industry when a new
product or update is released. Applying meta-heuristic optimization algorithms for closed-source software
reliability prediction has produced significant and accurate results. Now, open-source software dominates
the landscape of cloud-based systems. Therefore, providing results on open- source software reliability - as
a quality indicator - would greatly help solve the open-source software reliability growth- modelling
problem. The reliability is predicted by estimating the parameters of the software reliability models. As
software reliability models are inherently nonlinear, traditional approaches make estimating the
appropriate parameters difficult and ineffective. Consequently, software reliability models necessitate a
high- quality parameter estimation technique. These objectives dictate the exploration of potential
applications of meta- heuristic swarm intelligence optimization algorithms for optimizing the parameter
estimation of nonhomogeneous Poisson process-based open-source software reliability modelling. The
optimization algorithms are firefly, social spider, artificial bee colony, grey wolf, particle swarm, moth
flame, and whale. The applicability and performance evaluation of the optimization modelling approach is
demonstrated through two real open-source software reliability datasets. The results are promising.
closed-source software. The former has a shared code that anyone can contribute, whereas the latter has a
proprietary code that only the owner can access. Software reliability is crucial in the industry when a new
product or update is released. Applying meta-heuristic optimization algorithms for closed-source software
reliability prediction has produced significant and accurate results. Now, open-source software dominates
the landscape of cloud-based systems. Therefore, providing results on open- source software reliability - as
a quality indicator - would greatly help solve the open-source software reliability growth- modelling
problem. The reliability is predicted by estimating the parameters of the software reliability models. As
software reliability models are inherently nonlinear, traditional approaches make estimating the
appropriate parameters difficult and ineffective. Consequently, software reliability models necessitate a
high- quality parameter estimation technique. These objectives dictate the exploration of potential
applications of meta- heuristic swarm intelligence optimization algorithms for optimizing the parameter
estimation of nonhomogeneous Poisson process-based open-source software reliability modelling. The
optimization algorithms are firefly, social spider, artificial bee colony, grey wolf, particle swarm, moth
flame, and whale. The applicability and performance evaluation of the optimization modelling approach is
demonstrated through two real open-source software reliability datasets. The results are promising.
Research Interests:
This paper describes an architecture for predicting the price of cryptocurrencies for the next seven days using the Adaptive Network Based Fuzzy Inference System (ANFIS). Historical data of cryptocurrencies and indexes that are considered... more
This paper describes an architecture for predicting the price of cryptocurrencies for the next seven days
using the Adaptive Network Based Fuzzy Inference System (ANFIS). Historical data of cryptocurrencies
and indexes that are considered are Bitcoin (BTC), Ethereum (ETH), Bitcoin Dominance (BTC.D), and
Ethereum Dominance (ETH.D) in adaily timeframe. The methods used to teach the data are hybrid and
backpropagation algorithms, as well as grid partition, subtractive clustering, and Fuzzy C-means
clustering (FCM) algorithms, which are used in data clustering. The architectural performance designed
in this paper has been compared with different inputs and neural network models in terms of statistical
evaluation criteria. Finally, the proposed method can predict the price of digital currencies in a short time
using the Adaptive Network Based Fuzzy Inference System (ANFIS). Historical data of cryptocurrencies
and indexes that are considered are Bitcoin (BTC), Ethereum (ETH), Bitcoin Dominance (BTC.D), and
Ethereum Dominance (ETH.D) in adaily timeframe. The methods used to teach the data are hybrid and
backpropagation algorithms, as well as grid partition, subtractive clustering, and Fuzzy C-means
clustering (FCM) algorithms, which are used in data clustering. The architectural performance designed
in this paper has been compared with different inputs and neural network models in terms of statistical
evaluation criteria. Finally, the proposed method can predict the price of digital currencies in a short time
Research Interests:
Creating 3D vehicle model is complex process that requires basic knowledge of polygonal modeling. In this research, environment map is used as lighting with HDRI image.The final process of converting 3D scene to 2D image is called... more
Creating 3D vehicle model is complex process that requires basic knowledge of polygonal modeling. In
this research, environment map is used as lighting with HDRI image.The final process of converting 3D
scene to 2D image is called rendering. Image data will be obtained in four ways with various toolsets used
in 3ds Max. They are: Scaneline, V-Ray, Mental Ray and Corona Renderer. At final step was made critical
analysis on all of these techniques on the same computer system and excellent results were obtained
this research, environment map is used as lighting with HDRI image.The final process of converting 3D
scene to 2D image is called rendering. Image data will be obtained in four ways with various toolsets used
in 3ds Max. They are: Scaneline, V-Ray, Mental Ray and Corona Renderer. At final step was made critical
analysis on all of these techniques on the same computer system and excellent results were obtained
Research Interests:
Multiple sclerosis disease is a main cause of non-traumatic disabilities and one of the most common neurological disorders in young adults over many countries. In this work, we introduce a survey study of the utilization of machine... more
Multiple sclerosis disease is a main cause of non-traumatic disabilities and one of the most common
neurological disorders in young adults over many countries. In this work, we introduce a survey study of
the utilization of machine learning methods in Multiple Sclerosis early genetic disease detection methods
incorporating Microarray data analysis and Single Nucleotide Polymorphism data analysis and explains in
details the machine learning methods used in literature. In addition, this study demonstrates the future
trends of Next Generation Sequencing data analysis in disease detection and sample datasets of each
genetic detection method was included .in addition, the challenges facing genetic disease detection were
elaborated.
neurological disorders in young adults over many countries. In this work, we introduce a survey study of
the utilization of machine learning methods in Multiple Sclerosis early genetic disease detection methods
incorporating Microarray data analysis and Single Nucleotide Polymorphism data analysis and explains in
details the machine learning methods used in literature. In addition, this study demonstrates the future
trends of Next Generation Sequencing data analysis in disease detection and sample datasets of each
genetic detection method was included .in addition, the challenges facing genetic disease detection were
elaborated.
Research Interests:
Business intelligence systems are highly complex systems that senior executives use to process vast amounts of information when making decisions. Business intelligence systems are rarely used to their full potential due to a poor... more
Business intelligence systems are highly complex systems that senior executives use to process vast
amounts of information when making decisions. Business intelligence systems are rarely used to their full
potential due to a poor understanding of the factors that contribute to system success. Organizations using
business intelligence systems frequently find that it is not easy to evaluate the effectiveness of these
systems, and researchers have noted that there is limited scholarly and practical understanding of how
quality factors affect information use within these systems. This quantitative post positivist research used
the information system (IS) success model to analyze how information quality and system quality influence
information use in business intelligence systems. This study was also designed to investigate the
moderating effects of maturity constructs (i.e., data sources and analytical capabilities) on the
relationships between quality factors and information use.
amounts of information when making decisions. Business intelligence systems are rarely used to their full
potential due to a poor understanding of the factors that contribute to system success. Organizations using
business intelligence systems frequently find that it is not easy to evaluate the effectiveness of these
systems, and researchers have noted that there is limited scholarly and practical understanding of how
quality factors affect information use within these systems. This quantitative post positivist research used
the information system (IS) success model to analyze how information quality and system quality influence
information use in business intelligence systems. This study was also designed to investigate the
moderating effects of maturity constructs (i.e., data sources and analytical capabilities) on the
relationships between quality factors and information use.
Research Interests:
A variety of goods and services in the contemporary world requires evolutionary improvement of services e-commerce platform performance and optimization of costs. Contemporary society is deeply integrated with delivery services,... more
A variety of goods and services in the contemporary world requires evolutionary improvement of services
e-commerce platform performance and optimization of costs. Contemporary society is deeply integrated
with delivery services, purchasing of goods and services online, that makes competition between service
and good providers a key selection factor for end-user.. As long as logistic, timely, and cost-effective
delivery plays important part authors decided to analyse possible ways of improvements in the current
field, especially for regions distantly located from popular distribution canters and drop-ship delivery
networks. Considering both: fast and lazy delivery the factor of costs is playing an important role for each
end-user. The work proposes a simulation that analyses the current cost of delivery for e-commerce orders
in the context of delivery by the Supplier Fleet, World-Wide delivery service fleet, and possible vendor
drop-ship and checks of the alternative ways can be used to minimize the costs. Special attention is given to
Drop-Ship networks as the factor of possible costs decrease. The main object of investigation is focused
around mid and small companies living far from big distribution canters, in the rural areas but actively
using e-commerce solutions for their daily activities.
e-commerce platform performance and optimization of costs. Contemporary society is deeply integrated
with delivery services, purchasing of goods and services online, that makes competition between service
and good providers a key selection factor for end-user.. As long as logistic, timely, and cost-effective
delivery plays important part authors decided to analyse possible ways of improvements in the current
field, especially for regions distantly located from popular distribution canters and drop-ship delivery
networks. Considering both: fast and lazy delivery the factor of costs is playing an important role for each
end-user. The work proposes a simulation that analyses the current cost of delivery for e-commerce orders
in the context of delivery by the Supplier Fleet, World-Wide delivery service fleet, and possible vendor
drop-ship and checks of the alternative ways can be used to minimize the costs. Special attention is given to
Drop-Ship networks as the factor of possible costs decrease. The main object of investigation is focused
around mid and small companies living far from big distribution canters, in the rural areas but actively
using e-commerce solutions for their daily activities.
Research Interests:
In many decision situations, decision-makers face a kind of complex problems. In these decision-making problems, different types of fuzzy numbers are defined and, have multiple types of membership functions. So, we need a standard form to... more
In many decision situations, decision-makers face a kind of complex problems. In these decision-making
problems, different types of fuzzy numbers are defined and, have multiple types of membership functions.
So, we need a standard form to formulate uncertain numbers in the problem. Shadowed fuzzy numbers are
considered granule numbers which approximate different types and different forms of fuzzy numbers. In
this paper, a new ranking approach for shadowed fuzzy numbers is developed using value, ambiguity and
fuzziness for shadowed fuzzy numbers. The new ranking method has been compared with other existing
approaches through numerical examples. Also, the new method is applied to a hybrid multi-attribute
decision making problem in which the evaluations of alternatives are expressed with different types of
uncertain numbers. The comparative study for the results of different examples illustrates the reliability of
the new method.
problems, different types of fuzzy numbers are defined and, have multiple types of membership functions.
So, we need a standard form to formulate uncertain numbers in the problem. Shadowed fuzzy numbers are
considered granule numbers which approximate different types and different forms of fuzzy numbers. In
this paper, a new ranking approach for shadowed fuzzy numbers is developed using value, ambiguity and
fuzziness for shadowed fuzzy numbers. The new ranking method has been compared with other existing
approaches through numerical examples. Also, the new method is applied to a hybrid multi-attribute
decision making problem in which the evaluations of alternatives are expressed with different types of
uncertain numbers. The comparative study for the results of different examples illustrates the reliability of
the new method.
Research Interests:
This paper examines emotion intensity prediction in dialogs between clients and customer support representatives occurring on Twitter. We focus on a single emotion type, namely, frustration, modelling the user's level of frustration while... more
This paper examines emotion intensity prediction in dialogs between clients and customer support
representatives occurring on Twitter. We focus on a single emotion type, namely, frustration, modelling the
user's level of frustration while attempting to predict frustration intensity on the current and next turn,
based on the text of turns coming from both dialog participants. A subset of the Kaggle Customer Support
on Twitter dataset was used as the modelling data, annotated with per-turn frustration intensity ratings.
We propose to represent dialog turns by binary encoded bags of automatically selected keywords to be
subsequently used in a machine learning classifier. To assess the classification quality, we examined two
different levels of accuracy imprecision tolerance. Our model achieved a level of accuracy significantly
higher than a statistical baseline for prediction of frustration intensity for a current turn. However, we did
not find the additional information from customer support turns to help predict frustration intensity of the
next turn, and the reason for that is possibly the stability of user’s frustration level over the course of the
conversation, in other words, the inability of support’s response to exert much influence to user’s initial
frustration level.
representatives occurring on Twitter. We focus on a single emotion type, namely, frustration, modelling the
user's level of frustration while attempting to predict frustration intensity on the current and next turn,
based on the text of turns coming from both dialog participants. A subset of the Kaggle Customer Support
on Twitter dataset was used as the modelling data, annotated with per-turn frustration intensity ratings.
We propose to represent dialog turns by binary encoded bags of automatically selected keywords to be
subsequently used in a machine learning classifier. To assess the classification quality, we examined two
different levels of accuracy imprecision tolerance. Our model achieved a level of accuracy significantly
higher than a statistical baseline for prediction of frustration intensity for a current turn. However, we did
not find the additional information from customer support turns to help predict frustration intensity of the
next turn, and the reason for that is possibly the stability of user’s frustration level over the course of the
conversation, in other words, the inability of support’s response to exert much influence to user’s initial
frustration level.
Research Interests:
This article presents a comprehensive and in-depth analysis of the intricate relationship that underlies selfesteem and depression, two crucial aspects in the field of mental health. Study aims not only to scrutinize the existing... more
This article presents a comprehensive and in-depth analysis of the intricate relationship that underlies selfesteem and depression, two crucial aspects in the field of mental health. Study aims not only to scrutinize
the existing relationship between self-esteem and depression but also to do so innovatively by leveraging
the analytical and data visualization capabilities offered by two cutting-edge tools: Power BI [3], [4] and
Weka [1], [2]. These platforms, widely recognized in the realm of data science, allow for not only
exploring the relationship between these two fundamental variables but also presenting their findings in an
accessible and enlightening manner for both specialized and general audiences. Thus, our study represents
a comprehensive and multidisciplinary effort to unravel the complex relationship between self-esteem and
depression. Through the synergy between advanced data analysis carried out with Weka and the powerful
visualization provided by Power BI, the aim is not only to broaden the understanding of this crucial
relationship but also to lay the groundwork for future research and approaches in the field of mental
health. In a world where mental health takes center stage in socio-health concerns, this study aspires to
contribute valuable insights that can inform and enrich the care, treatment, and policies related to
depression and self-esteem.
the existing relationship between self-esteem and depression but also to do so innovatively by leveraging
the analytical and data visualization capabilities offered by two cutting-edge tools: Power BI [3], [4] and
Weka [1], [2]. These platforms, widely recognized in the realm of data science, allow for not only
exploring the relationship between these two fundamental variables but also presenting their findings in an
accessible and enlightening manner for both specialized and general audiences. Thus, our study represents
a comprehensive and multidisciplinary effort to unravel the complex relationship between self-esteem and
depression. Through the synergy between advanced data analysis carried out with Weka and the powerful
visualization provided by Power BI, the aim is not only to broaden the understanding of this crucial
relationship but also to lay the groundwork for future research and approaches in the field of mental
health. In a world where mental health takes center stage in socio-health concerns, this study aspires to
contribute valuable insights that can inform and enrich the care, treatment, and policies related to
depression and self-esteem.
Research Interests:
This systematic literature review examines the effectiveness of user-generated content (UGC) in ecommerce marketing, specifically focusing on its impact on customer trust, engagement, and purchase behavior. The review identifies key... more
This systematic literature review examines the effectiveness of user-generated content (UGC) in ecommerce marketing, specifically focusing on its impact on customer trust, engagement, and purchase
behavior. The review identifies key determinants of UGC effectiveness by analyzing multiple studies,
including source credibility, message relevance, and social influence. The findings confirm the positive
association between UGC and customer trust, highlighting the potential of UGC as a marketing tool for ecommerce businesses. However, gaps in the literature, such as limited exploration of demographic and
cultural differences, indicate the need for further research in this area. The findings from this systematic
literature review will help e-commerce businesses improve their marketing plans by utilizing usergenerated content to win over customers' trust and engagement.
behavior. The review identifies key determinants of UGC effectiveness by analyzing multiple studies,
including source credibility, message relevance, and social influence. The findings confirm the positive
association between UGC and customer trust, highlighting the potential of UGC as a marketing tool for ecommerce businesses. However, gaps in the literature, such as limited exploration of demographic and
cultural differences, indicate the need for further research in this area. The findings from this systematic
literature review will help e-commerce businesses improve their marketing plans by utilizing usergenerated content to win over customers' trust and engagement.
Research Interests:
Trust is a big part of how well e-commerce works and it is also a big part of how people decide what to buy. As more and more business is done online, companies that want to build customer loyalty and involvement must understand the... more
Trust is a big part of how well e-commerce works and it is also a big part of how people decide what to
buy. As more and more business is done online, companies that want to build customer loyalty and
involvement must understand the complex relationship between trust and e-commerce. This study paper
looks at the many distinct aspects of trust in e-commerce and how it affects people’s actions. By looking at
the various aspects and causes of trust and how to build and keep trust, this study shows how businesses
can create a trustworthy online environment that makes customers happier and leads to long-term success.
buy. As more and more business is done online, companies that want to build customer loyalty and
involvement must understand the complex relationship between trust and e-commerce. This study paper
looks at the many distinct aspects of trust in e-commerce and how it affects people’s actions. By looking at
the various aspects and causes of trust and how to build and keep trust, this study shows how businesses
can create a trustworthy online environment that makes customers happier and leads to long-term success.
Research Interests:
Cloud computing is regarded as the next generation of computing. It is progressively being used as a launching pad for digital innovation and organizational agility. Cloud computing is frequently used by private and public organizations... more
Cloud computing is regarded as the next generation of computing. It is progressively being used as a launching pad for digital innovation and organizational agility. Cloud computing is frequently used by
private and public organizations due to its flexibility, collaboration, cost-effectiveness, and scalability. These characteristics make cloud computing indispensable for individuals and businesses such as higher
education institutes. Several prior studies covered the technological facets of cloud-based contexts,
including cloud security, scalability, and virtualization. However, it is contend that the main barrier to
cloud computing isn't technical but cognitive or behavioural, and in particular attitudinal. Thus, this
research aims to study higher education’ students’ attitudes and their intention to adopt cloud computing, with a specific concentration on the effect of trust, peer influences, perceived usefulness and ease of use in
order to investigate the factors influencing the adoption of cloud computing in higher educational environment in Saudi Arabia.
private and public organizations due to its flexibility, collaboration, cost-effectiveness, and scalability. These characteristics make cloud computing indispensable for individuals and businesses such as higher
education institutes. Several prior studies covered the technological facets of cloud-based contexts,
including cloud security, scalability, and virtualization. However, it is contend that the main barrier to
cloud computing isn't technical but cognitive or behavioural, and in particular attitudinal. Thus, this
research aims to study higher education’ students’ attitudes and their intention to adopt cloud computing, with a specific concentration on the effect of trust, peer influences, perceived usefulness and ease of use in
order to investigate the factors influencing the adoption of cloud computing in higher educational environment in Saudi Arabia.
Research Interests:
Cyberbullying includes the repeated and intentional use of digital technology to target another person with threats, harassment, or public humiliation. One of the techniques of Cyberbullying is sharing bullying memes on social media,... more
Cyberbullying includes the repeated and intentional use of digital technology to target another person with
threats, harassment, or public humiliation. One of the techniques of Cyberbullying is sharing bullying
memes on social media, which has increased enormously in recent years. Memes are images and texts
overlapped and sometimes together they present concepts that become dubious if one of them is absent.
Here, we propose a unified deep neural model for detecting bullying memes on social media. In the
proposed unified architecture, VGG16-BiLSTM, consists of a VGG16 convolutional neural network for
predicting the visual bullying content and a BiLSTM with one-dimensional convolution for predicting the
textual bullying content. The meme is discretized by extracting the text from the image using OCR. The
perceptron-based feature-level strategy for multimodal learning is used to dynamically combine the features
of discrete modalities and output the final category as bullying or nonbullying type. We also create a
“bullying Bengali memes dataset” for experimental evaluation. Our proposed model attained an accuracy
of 87% with an F1 score of 88%. The proposed model demonstrates the capability to detect instances of
Cyberbullying involving Bengali memes on various social media platforms. Consequently, it can be utilized
to implement effective filtering mechanisms aimed at mitigating the prevalence of Cyberbullying.
threats, harassment, or public humiliation. One of the techniques of Cyberbullying is sharing bullying
memes on social media, which has increased enormously in recent years. Memes are images and texts
overlapped and sometimes together they present concepts that become dubious if one of them is absent.
Here, we propose a unified deep neural model for detecting bullying memes on social media. In the
proposed unified architecture, VGG16-BiLSTM, consists of a VGG16 convolutional neural network for
predicting the visual bullying content and a BiLSTM with one-dimensional convolution for predicting the
textual bullying content. The meme is discretized by extracting the text from the image using OCR. The
perceptron-based feature-level strategy for multimodal learning is used to dynamically combine the features
of discrete modalities and output the final category as bullying or nonbullying type. We also create a
“bullying Bengali memes dataset” for experimental evaluation. Our proposed model attained an accuracy
of 87% with an F1 score of 88%. The proposed model demonstrates the capability to detect instances of
Cyberbullying involving Bengali memes on various social media platforms. Consequently, it can be utilized
to implement effective filtering mechanisms aimed at mitigating the prevalence of Cyberbullying.
Research Interests: Computer Science, Distributed Computing, Grid Computing, Parallel Computing, Information Technology, and 15 moreComputer Engineering, Wireless Communications, Database Systems, Information Communication Technology, Wireless Sensor Networks, Wireless networks, Wireless Networks (Computer Science), Computing, Mobile Computing, Cloud Computing, Databases, WSN (Wireless sensor network), Bigdata, Wireless Computing, and Information Technology and System Integration
This paper analyses ChatGPT 3.5 Turbo, the latest free version of the ChatGPT service. By using ChatGPT to create theoretical papers on itself, further insights are gained into the potential of ChatGPT and other generative artificial... more
This paper analyses ChatGPT 3.5 Turbo, the latest free version of the ChatGPT service. By using
ChatGPT to create theoretical papers on itself, further insights are gained into the potential of ChatGPT and other generative artificial intelligence services as well as their weaknesses. Through this analysis
presented, potential future avenues of research are suggested alongside necessary changes if services like ChatGPT wish to be used as a tool in academic works.
ChatGPT to create theoretical papers on itself, further insights are gained into the potential of ChatGPT and other generative artificial intelligence services as well as their weaknesses. Through this analysis
presented, potential future avenues of research are suggested alongside necessary changes if services like ChatGPT wish to be used as a tool in academic works.
Research Interests:
Climate services involve the timely production, translation, and delivery of useful climate data, information and knowledge for societal decision making. In order to create climate services for farmers that are truly integrated with... more
Climate services involve the timely production, translation, and delivery of useful climate data, information
and knowledge for societal decision making. In order to create climate services for farmers that are truly
integrated with user-centric design into the development process in an African context, the study has
finished an important and crucial step by conducting a literature review and designing a prototype for the
application. The goal of this study was to create climate services for farmers in an African context that are
genuinely integrated with user-centric design. This led to the co-design and development and integration
of a mobile application that provide climate and weather information as well as agricultural
information for the main crops such millet, maize and sorghum. The research applied using qualitative
research using interview with 3 farmers in the field using random sampling with the approach to inform
the study. A survey has been administered to find out how people understand climate services, Agro
meteorology and help enhance the mobile application’s user experience. A Results shows that farmers are
determined and ready to use and excited with the application. These innovations helped farmers to reduce
the cost, increase crop capacity and profit. A hypothesis was set that there is a need forintegrating AI into
a farmer’s application for making farming process more progressive and efficient farming and the
integration of Market Place (MP) for farmer’s application to market and sell their product the integration
of notification system that allows farmers to receive real-time data and IOT for real-time data. The data
collected and the survey results demonstrated that the research objectives were being met. The study aims
to develop the application that would be scalable, durable and fault tolerant for farmers to use the
application successfully
and knowledge for societal decision making. In order to create climate services for farmers that are truly
integrated with user-centric design into the development process in an African context, the study has
finished an important and crucial step by conducting a literature review and designing a prototype for the
application. The goal of this study was to create climate services for farmers in an African context that are
genuinely integrated with user-centric design. This led to the co-design and development and integration
of a mobile application that provide climate and weather information as well as agricultural
information for the main crops such millet, maize and sorghum. The research applied using qualitative
research using interview with 3 farmers in the field using random sampling with the approach to inform
the study. A survey has been administered to find out how people understand climate services, Agro
meteorology and help enhance the mobile application’s user experience. A Results shows that farmers are
determined and ready to use and excited with the application. These innovations helped farmers to reduce
the cost, increase crop capacity and profit. A hypothesis was set that there is a need forintegrating AI into
a farmer’s application for making farming process more progressive and efficient farming and the
integration of Market Place (MP) for farmer’s application to market and sell their product the integration
of notification system that allows farmers to receive real-time data and IOT for real-time data. The data
collected and the survey results demonstrated that the research objectives were being met. The study aims
to develop the application that would be scalable, durable and fault tolerant for farmers to use the
application successfully
Research Interests: Computer Science, Ontology, Web 2.0, Teaching English as a Second Language, Second Language Acquisition, and 10 moreInformation Security, Computer Engineering, Web Design, Semantics, Network Security, International Security, Web Technologies, Computer Security, Web Services and SOA, and Web Programming
"The paper introduces confidential computing approaches focused on protecting hierarchical data within edge-cloud network. Edge-cloud network suggests splitting and sharing data between the main cloud and the range of networks near the... more
"The paper introduces confidential computing approaches focused on protecting hierarchical data within edge-cloud network. Edge-cloud network suggests splitting and sharing data between the main cloud and
the range of networks near the endpoint devices. The proposed solutions allow data in this two-level hierarchy to be protected via embedding traditional encryption at rest and in transit while leaving the
remaining security issues, such as sensitive data and operations in use, in the scope of trusted execution environment. Hierarchical data for each network device are linked and identified through distinct paths between edge and main cloud using individual blockchain. Methods for data and cryptographic key splitting between the edge and the main cloud are based on strong authentication techniques ensuring the
shared data confidentiality, integrity and availability.
the range of networks near the endpoint devices. The proposed solutions allow data in this two-level hierarchy to be protected via embedding traditional encryption at rest and in transit while leaving the
remaining security issues, such as sensitive data and operations in use, in the scope of trusted execution environment. Hierarchical data for each network device are linked and identified through distinct paths between edge and main cloud using individual blockchain. Methods for data and cryptographic key splitting between the edge and the main cloud are based on strong authentication techniques ensuring the
shared data confidentiality, integrity and availability.
Research Interests:
Vulnerability exploitation is the key to obtaining the control authority of the system, posing a significant threat to network security. Therefore, it is necessary to discover exploitation from traffic. The current methods usually only... more
Vulnerability exploitation is the key to obtaining the control authority of the system, posing a significant threat to network security. Therefore, it is necessary to discover exploitation from traffic. The current methods usually only target a single stage with an incomplete causal relationship and depend on the payload content, causing attacker easily avoids detection by encrypting traffic and other means. We propose a traffic traceback method of vulnerability exploitation to solve the above problems based on session relation. First, we construct the session relationship model using the session correlation of different stages during the exploit. Second, we build a session diagram based on historical traffic. Finally, we traverse the session diagram to find the traffic conforming to the session relationship model. Compared with Blatta, a method detecting early exploit traffic with RNN, the detection rate of our method is increased by 50%, independent of traffic encryption methods.
Research Interests:
In the field of enterprise architecture (EA), qualitative scenarios are used to understand the qualitative characteristics better. In order to reduce the implementation cost, scenarios are prioritized to be able to focus on the higher... more
In the field of enterprise architecture (EA), qualitative scenarios are used to understand the qualitative characteristics better. In order to reduce the implementation cost, scenarios are prioritized to be able to focus on the higher priority and more important scenarios. There are different methods to evaluate enterprise architecture including architecture Trade-off Analysis Method (ATAM).Prioritizing qualitative scenarios is one of the main phases of this method. Since none of the recent studies meet the prioritizing qualitative scenarios requirements, considering proper prioritizing criteria and reaching an appropriate speed priority, non-dominated sorting genetic algorithms is used in this study (NSGA-II). In addition to previous research standards more criteria were considered in the proposed algorithm, these sets of structures together as gene and in the form of cell array constitute chromosome. The proposed algorithm is evaluated in two case studies in the field of enterprise architecture and architecture software. The results showed the accuracy and the more appropriate speed comparing to the previous works including genetic algorithms.
Research Interests:
The importance of health sector in Colombia is notorously growing. In this article one of the major issues concerning the field is addressed, the interoperability of heath history. Due to the stablishment of standards , Colombia must... more
The importance of health sector in Colombia is notorously growing. In this article one of the major issues
concerning the field is addressed, the interoperability of heath history. Due to the stablishment of
standards , Colombia must begin a process to accomplish such an important necesity to offer an efficient
and high quality health service. In this context, the standar FHIR is an example of successfull
implementation of electronic health history in public sector. It's tought to be gradually implemented first in
the beneficiary institution Rubén Cruz Vélez Hospital and further in ther health institutions in the country.
concerning the field is addressed, the interoperability of heath history. Due to the stablishment of
standards , Colombia must begin a process to accomplish such an important necesity to offer an efficient
and high quality health service. In this context, the standar FHIR is an example of successfull
implementation of electronic health history in public sector. It's tought to be gradually implemented first in
the beneficiary institution Rubén Cruz Vélez Hospital and further in ther health institutions in the country.
Research Interests:
The airport collaborative decision-making (A-CDM) network brings together airports, airlines, and air navigation service providers to share timely and accurate information in order to facilitate optimal decision-making, plan operations... more
The airport collaborative decision-making (A-CDM) network brings together airports, airlines, and air navigation service providers to share timely and accurate information in order to facilitate optimal decision-making, plan operations and improve air traffic management. Research found that aviation service quality can be improved by integrating the A-CDM network and SERVQUAL together with Kano's model to enhance service quality and improve network operational efficiency. The theory and methods of the A-CDM network combined with information technology and process innovation can maximise the serviceability of the aviation industry to improve network operation at the airport concerned.
Research Interests:
Acritical process in a software project life-cycle is risk assessment and mitigation. Risks exist in every software project and recognizing and evaluating risks and uncertainties is a challenging process for practitioners with little... more
Acritical process in a software project life-cycle is risk assessment and mitigation. Risks exist in every
software project and recognizing and evaluating risks and uncertainties is a challenging process for
practitioners with little historical data. In our study, by using a survey data, we identify and provide a
relatively wider coverage of risks and ratings of software project. The risk register and evaluations are
useful for practitioner of small organizations at initial phase of risk identification and assessment. There
are 128 risks in this study which are analyzed. Furthermore, the study provides a top risk list according to
this study alongside a highly cross correlatedrisks table. Additionally, previous studies have also provided
top risks lists regarding the corresponding surveys. This study extends previous studies to provide a recent
risk study. Outcomes are also compared to previous works in discussion.
software project and recognizing and evaluating risks and uncertainties is a challenging process for
practitioners with little historical data. In our study, by using a survey data, we identify and provide a
relatively wider coverage of risks and ratings of software project. The risk register and evaluations are
useful for practitioner of small organizations at initial phase of risk identification and assessment. There
are 128 risks in this study which are analyzed. Furthermore, the study provides a top risk list according to
this study alongside a highly cross correlatedrisks table. Additionally, previous studies have also provided
top risks lists regarding the corresponding surveys. This study extends previous studies to provide a recent
risk study. Outcomes are also compared to previous works in discussion.
Research Interests:
To mine out relevant facts at the time of need from web has been a tenuous task. Research on diverse fields are fine tuning methodologies toward these goals that extracts the best of information relevant to the users search query. In the... more
To mine out relevant facts at the time of need from web has been a tenuous task. Research on diverse fields are fine tuning methodologies toward these goals that extracts the best of information relevant to the users search query. In the proposed methodology discussed in this paper find ways to ease the search complexity tackling the severe issues hindering the performance of traditional approaches in use. The proposed methodology find effective means to find all possible semantic relatable frequent sets with FP Growth algorithm. The outcome of which is the further source of fuel for Bio inspired Fuzzy PSO to find the optimal attractive points for the web documents to get clustered meeting the requirement of the search query without losing the relevance. On the whole the proposed system optimizes the objective function of minimizing the intra cluster differences and maximizes the inter cluster distances along with retention of all possible relationships with the search context intact. The major contribution being the system finds all possible combinations matching the user search transaction and thereby making the system more meaningful. These relatable sets form the set of particles for Fuzzy Clustering as well as PSO and thus being unbiased and maintains a innate behaviour for any number of new additions to follow the herd behaviour's evaluations reveals the proposed methodology fares well as an optimized and effective enhancements over the conventional approaches.
Research Interests:
This paper proposes development of an android app to improve the transportation services for bus rental companies that lift Taibah University students. It intends to reduce the waiting time for bus students, thereby to stimulate sharing... more
This paper proposes development of an android app to improve the transportation services for bus rental companies that lift Taibah University students. It intends to reduce the waiting time for bus students, thereby to stimulate sharing of updated information between the bus drivers and students. The application can run only on android devices. It would inform the students about the exact time of arrival and departure of buses on route. This proposed app would specifically be used by students and drivers of Taibah University. Any change in the scheduled movement of the buses would be updated in the software. Regular alerts would be sent in case of delays or cancelation of buses. Bus locations and routes are shown on dynamic maps using Google maps. The application is designed and tested where the users assured that the application gives the real time service and it is very helpful for them.
Research Interests:
The present manuscript proposes a comparison between two types of shift registers; the first one, a traditional one with a linear feedback (LFSR); on the other corner, a register designed one register with genetically-controlled feedback... more
The present manuscript proposes a comparison between two types of shift registers; the first one, a
traditional one with a linear feedback (LFSR); on the other corner, a register designed one register with
genetically-controlled feedback loop (NLFGR). Being more traditional, the linear feedbacked register
works as reference to offer comparison metrics, meanwhile the NLFGR is our research focus, since our
proposal relies in its good features to replicate certain behaviours, with shorter parsing time than linear
feedback shift register.
traditional one with a linear feedback (LFSR); on the other corner, a register designed one register with
genetically-controlled feedback loop (NLFGR). Being more traditional, the linear feedbacked register
works as reference to offer comparison metrics, meanwhile the NLFGR is our research focus, since our
proposal relies in its good features to replicate certain behaviours, with shorter parsing time than linear
feedback shift register.
Research Interests:
International Journal of Computational Science and Information Technology (IJCSITY) focuses on Complex systems, information and computation using mathematics and engineering techniques. This is an open access peer-reviewed journal will... more
International Journal of Computational Science and Information Technology (IJCSITY) focuses on Complex systems, information and computation using mathematics and engineering techniques. This is an open access peer-reviewed journal will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the area of Computation theory and applications. It will also serve to facilitate the exchange of information between researchers and industry professionals to discussthelatestissuesandadvancementintheareaofadvancedComputationanditsapplications.
Research Interests:
Culling newly hatched male chicks in industrial hatcheries poses a serious ethical problem. Both laying and broiler breeders need males, but it is a problem because they are produced more than needed. Being able to determine the sex of... more
Culling newly hatched male chicks in industrial hatcheries poses a serious ethical problem. Both laying
and broiler breeders need males, but it is a problem because they are produced more than needed. Being
able to determine the sex of chicks in the egg at the beginning or early stage of incubation can eliminate
ethical problems as well as many additional costs. When we look at the literature, the methods used are
very costly, low in applicability, invasive, inadequate in accuracy, or too late to eliminate ethical problems.
Considering the embryo's development, the earliest observed candidate feature for sex determination is
blood vessels. Detection from blood vessels can eliminate ethical issues, and these vessels can be seen
when light is shined into the egg until the first seven days. In this study, sex determination was made by
morphological analysis from embryonic vascular images obtained in the first week when the light was
shined into the egg using a standard camera without any invasive procedure to the egg.
and broiler breeders need males, but it is a problem because they are produced more than needed. Being
able to determine the sex of chicks in the egg at the beginning or early stage of incubation can eliminate
ethical problems as well as many additional costs. When we look at the literature, the methods used are
very costly, low in applicability, invasive, inadequate in accuracy, or too late to eliminate ethical problems.
Considering the embryo's development, the earliest observed candidate feature for sex determination is
blood vessels. Detection from blood vessels can eliminate ethical issues, and these vessels can be seen
when light is shined into the egg until the first seven days. In this study, sex determination was made by
morphological analysis from embryonic vascular images obtained in the first week when the light was
shined into the egg using a standard camera without any invasive procedure to the egg.
Research Interests:
Practicing the secure software development lifecycle (SSDLC) requires a team of application security experts and a proper management structure. Software developers usually lack application security expertise but are often responsible for... more
Practicing the secure software development lifecycle (SSDLC) requires a team of application security experts and a proper management structure. Software developers usually lack application security expertise but are often responsible for software security when management undervalues software security, or the SSDLC is too expensive to practice. Software developers must have adequate application security self-efficacy (SE) to execute software security activities and processes effectively. To improve software developers' SE, the factors that impact their SE must be identified. A sample of 200 software developers based in the United States was surveyed for their SE. The relationship between the factors and SE was analyzed using Spearman's rho correlation. Application security awareness, the presence of an application security team, and education level all correlated with software developers' SE. Security training and performing multiple application securities did not correlate with software developers' SE. The results have practical implications for improving software security.
Research Interests:
This study intends to investigate the mate selection criteria and weights of unmarried female junior high school teachers in Taiwan. This study used the Delphi method to clarify mate selection criteria. The primary assessment criteria... more
This study intends to investigate the mate selection criteria and weights of unmarried female junior high school teachers in Taiwan. This study used the Delphi method to clarify mate selection criteria. The primary assessment criteria included 4 items: social condition, personal condition, emotional condition, and family background. The secondary assessment criteria included 24 items. This study used AHP to determine that, among the primary assessment criteria, the order of importance is, as follows: emotional condition, personal condition, social condition, and family background. Among the secondary assessment criteria, the order of importance of the top 10 is, as follows: carefulness and meticulousness, tenderness and thoughtfulness, sense of safety, parents are alive and healthy, health status, conviction record, birth order, monthly income, sense of humor, and value.
Research Interests:
Personalized web is used in all functional domains. Personalized web consists of private pages and pages which personalize the content, data and information based on user's context and preferences. Personalization engines use users'... more
Personalized web is used in all functional domains. Personalized web consists of private pages and pages which personalize the content, data and information based on user's context and preferences. Personalization engines use users' implicit and explicit feedback to personalize the user experience and information. While the personalization drives the user satisfaction levels, it also has performance side effects. Traditional web performance optimization methods fall short of improving the performance of personalized web due to privacy and security concerns and due to the dynamic nature of the data. In this paper we have tried to address this crucial issue by discussing various aspects of personalized performance optimization algorithms. We have discussed a novel approach using "Personalization performance Optimization" (PPO) framework that has resulted in 30% increase in page response times and 35% increase in cache hit ratio during our experiments.
Research Interests: Computer Science, Human Computer Interaction, Ontology, Second Language Acquisition, Information Security, and 13 moreComputer Engineering, Semantics, Cognitive Semantics, Network Security, International Security, Computer Networks, Security, Lexical Semantics, Computer Security, Semantic Web, Cloud Computing, Semantic Search Engine, and Syntactic and Semantic Knowledge
The paper emphasizes the human aspects of cyber incidents concerning protecting information and technology assets by addressing behavioral analytics in cybersecurity for digital forensics applications. The paper demonstrates the human... more
The paper emphasizes the human aspects of cyber incidents concerning protecting information and
technology assets by addressing behavioral analytics in cybersecurity for digital forensics applications.
The paper demonstrates the human vulnerabilities associated with information systems technologies and
components. This assessment is based on past literature assessments done in this area. This study also
includes analyses of various frameworks that have led to the adoption of behavioral analysis in digital
forensics. The study's findings indicate that behavioral evidence analysis should be included as part of the
digital forensics examination. The provision of standardized investigation methods and the inclusion of
human factors such as motives and behavioral tendencies are some of the factors attached to the use of
behavioral digital forensic frameworks. However, the study also appreciates the need for a more
generalizable digital forensic method.
technology assets by addressing behavioral analytics in cybersecurity for digital forensics applications.
The paper demonstrates the human vulnerabilities associated with information systems technologies and
components. This assessment is based on past literature assessments done in this area. This study also
includes analyses of various frameworks that have led to the adoption of behavioral analysis in digital
forensics. The study's findings indicate that behavioral evidence analysis should be included as part of the
digital forensics examination. The provision of standardized investigation methods and the inclusion of
human factors such as motives and behavioral tendencies are some of the factors attached to the use of
behavioral digital forensic frameworks. However, the study also appreciates the need for a more
generalizable digital forensic method.
Research Interests:
Nowadays, we remark that breakthroughs in the field of Artificial Intelligence (AI) suggesting its similarity with human beings, tremendous diversity of subfields and terminologies implied in the AI discipline, huge diversity of AI... more
Nowadays, we remark that breakthroughs in the field of Artificial Intelligence (AI) suggesting its similarity with human beings, tremendous diversity of subfields and terminologies implied in the AI discipline, huge diversity of AI techniques, mistakes of AI and hype could lead to confusion about a clear understanding of the field (due to multiplicity of elements, brilliant successes, and senseless failures at the same time). In some cases, misunderstanding about AI led to hype, firing, and rude criticism even among many senior experts of the AI domain. Therefore, we detected the need for a short and very comprehensive overview of the whole and very vast AI field (as a good and useful reference) for providing fast insights leading to a better contextual understanding. And all of this by putting all aspects of AI together in few pages, based on practical and realistic (empirical) studies. Indeed, as only long training paths based on several outstanding books can fully cover all aspects of the AI discipline in several years, a short AI approach with shallow technical aspects would be suitable for everybody no matter their fields of activity, and so would contribute to avoiding misunderstandings about AI.
Research Interests: Computer Science, Human Computer Interaction, Computer Vision, Teaching English as a Second Language, Information Security, and 14 moreComputer Engineering, Semantics, Cognitive Semantics, Network Security, Computer Networks, Lexical Semantics, Semantic Web technology - Ontologies, Semantic Web, Cloud Computing, Computational Mathematics, Semantic Search Engine, Computational Linguistics & NLP, Syntactic and Semantic Knowledge, and Computer Science and Engineering
The normal method for analyzing technology is formulating many search queries to extract patent datasets and filter the data physically. The purpose of filtering the collected data is to remove noise to guarantee accurate information... more
The normal method for analyzing technology is formulating many search queries to extract patent datasets and filter the data physically. The purpose of filtering the collected data is to remove noise to guarantee accurate information analysis. With the advancement in technology and machine learning, the work of physical analysis of the patent can be programmed so the system can remove noise depending on the results based on the previous data. Microsoft team generates a new artificial intelligence model that provides solutions on how individuals respond to speakers. Microsoft team, workplace, Facebook, and Google collected data from many active users hence developing artificial intelligence to minimize distracting background noise, barking and typing during the call.
Research Interests:
Anemia is a state of poor health where there is presence of low amount of red blood cell in blood stream. This research aims to design a model for prediction of Anemia in children under 5 years of age using Complete Blood Count reports.... more
Anemia is a state of poor health where there is presence of low amount of red blood cell in blood stream. This research aims to design a model for prediction of Anemia in children under 5 years of age using Complete Blood Count reports. Data are collected from Kanti Children Hospital which consist of 700 data records. Then they are preprocessed, normalized, balanced and selected machine learning algorithms were applied. It is followed by verification, validation along with result analysis. Random Forest is the best performer which showed accuracy of 98.4%. Finally, Feature Selection as well as Ensemble Learning methods, Voting, Stacking, Bagging and Boosting were applied to improve the performance of algorithms. Selecting the best performer algorithm, stacking with other algorithms, bagging it, boosting it are very much crucial to improve accuracy despite of any time issue for prediction of anemia in children below 5 years of age.
Research Interests:
The Fintech industry is no stranger to transformation and disruption. With the emergence of new technologies such as Big Data and the Metaverse, finance companies are quickly leveraging these technologies to revolutionize the virtual... more
The Fintech industry is no stranger to transformation and disruption. With the emergence of new technologies such as Big Data and the Metaverse, finance companies are quickly leveraging these technologies to revolutionize the virtual fintech sector. Big data transforms how financial institutions gather, analyze, and utilize data. The sheer amount of data available has opened up countless opportunities for better customer understanding and insight into business operations. Companies can use this data to create predictive models that identify emerging trends in customer behavior, market activity, and other aspects of their business. By utilizing these insights, companies can make smarter decisions about products, services, marketing strategies, and more. The Metaverse is another technology with massive potential for disrupting the Fintech sector. The Metaverse enables businesses to offer virtual goods and services without physical stores or retail outlets. This makes it easier for companies to scale their operations across multiple regions and gives customers more options when choosing a financial service provider. Additionally, using digital currencies like Bitcoin helps reduce transaction costs significantly while increasing security compared to traditional payment methods like credit cards or PayPal.