A specific phobia is a common anxiety-related disorder that can be treated efficiently using diff... more A specific phobia is a common anxiety-related disorder that can be treated efficiently using different therapies including exposure therapy or cognitive therapy. One of the most famous methods to treat a specific phobia is exposure therapy. Exposure therapy involves exposing the target patient to the anxiety source or its context without the intention to cause any danger. One promising track of research lies in VR exposure therapy (VRET) and/or AR exposure therapy (ARET), where gradual exposure to a negative stimulus is used to reduce anxiety. In order to review existing works in this field, a systematic search was completed using the following databases: PubMed, ProQuest, Scopus, Web of Science, and Google Scholar. All studies that present VRET and/or ARET solutions were selected. By reviewing the article, each author then applied the inclusion and exclusion criteria, and 18 articles were selected. This systematic review aims to investigate the previous studies that used either VR ...
Coronavirus (COVID-19) is the most prevalent coronavirus infection with respiratory symptoms such... more Coronavirus (COVID-19) is the most prevalent coronavirus infection with respiratory symptoms such as fever, cough, dyspnea, pneumonia, and weariness being typical in the early stages. On the other hand, COVID-19 has a direct impact on the circulatory and respiratory systems as it causes a failure to some human organs or severe respiratory distress in extreme circumstances. Early diagnosis of COVID-19 is extremely important for the medical community to limit its spread. For a large number of suspected cases, manual diagnostic methods based on the analysis of chest images are insufficient. Faced with this situation, artificial intelligence (AI) techniques have shown great potential in automatic diagnostic tasks. This paper aims at proposing a fast and precise medical diagnosis support system (MDSS) that can distinguish COVID-19 precisely in chest-X-ray images. This MDSS uses a concatenation technique that aims to combine pre-trained convolutional neural networks (CNN) depend on the tr...
For people with Autism Spectrum Disorder (ASD), using technological tools, such as augmented real... more For people with Autism Spectrum Disorder (ASD), using technological tools, such as augmented reality (AR) and serious games remain a new and unexplored option. To attract people with ASD who have communicative, social, emotional and attention deficit disorders to behavioral treatments, an attractive environment is needed that ensures continuity during treatment. The aim of the current work is to efficiently examine systematic reviews and relevant primary studies on ASD solutions from 2015 to 2020, particularly those using the traditional Picture Exchange Communication System (PECS), the application of augmented reality and those that propose serious games, thereby providing an overview of existing evidence and to identify strategies for future research. Five databases were searched for keywords that may be included within the broad Autism Spectrum Disorder ‘ASD’ umbrella term, alongside ‘augmented reality’, ‘serious games’ and ‘PECS’. We screened 1799 titles and abstracts, read, and...
2021 1st International Conference on Emerging Smart Technologies and Applications (eSmarTA), 2021
Birthrates forecasting can help decision-makers to understand population increment patterns, in a... more Birthrates forecasting can help decision-makers to understand population increment patterns, in addition to many issues that support governmental decisions, especially in developing countries as Yemen. Data Mining has important new emerged technologies, support business, and decision-making requirements. Forecasting is one of Artificial Neural Networks (ANN) and Time Series (TS) applications, as data mining techniques. In this paper, birthrates two forecasting models have experimented with. The ANN and TS are used for forecasting Yemeni hospital births data. Monthly birthrates data of four years are processed by each model. The forecasting of monthly next four years had produced, based on each model. Outcomes evaluation is showed the accuracy of forecasting results. Besides, TS outperforms the ANN model, in the context of monthly births data forecasting of Yemeni hospital data.
2019 First International Conference of Intelligent Computing and Engineering (ICOICE), 2019
Harmony search algorithm (HSA) is one of the relatively new metaheuristic algorithms that classif... more Harmony search algorithm (HSA) is one of the relatively new metaheuristic algorithms that classified under population-based search algorithms. Based on literature, hybridizing local-based searching algorithms with population-based algorithms can improve the performance of hybridized algorithms. This research is an extension to our previous work that focus on solving Nurse Rostering Problems (NRP) using hybrid metaheuristic algorithms. One of the improved version of HSA is enhanced harmony search algorithm (EHSA) where it overcomes some of the weaknesses of basic HSA. Slow convergence is noticed in EHSA which encourage us to hybridize it with other metaheuristic algorithms to improve its performance. In this research, EHSA is hybridized with great deluge algorithm (GD) and called Deluged harmony search algorithm (DHSA). DHSA then compared to CHSA (the hybridization of EHSA with Hill climbing (HC)) which developed earlier. To strike the balance between exploration and exploitation, th...
Nurse Rostering Problem (NRP) is a well-known NP-Hard combinatorial optimization problem. The fac... more Nurse Rostering Problem (NRP) is a well-known NP-Hard combinatorial optimization problem. The fact is that coping real-world constraints in allocating the shift duties fairly among the available nurses is still a hard task to accomplish. The problem becomes more serious due to the shortage of nurses. Thus, this work aims to tackle this problem by hybridizing an Enhanced Harmony Search Algorithm (EHSA) with the standard Hill climbing (HC). This hybridization may help to strike the balance between exploration and exploitation in the searching process. The proposed algorithm is called Climbing Harmony Search Algorithm (CHSA) where it applied to solve a real-world NRP dataset, which arises at the Medical Center of Universiti Kebangsaan. The results show that CHSA performs much better than EHSA alone and Basic Harmony Search algorithm (BHSA) in all instances in terms of obtained penalty values (PVs), desirable patterns (DPs) and computational time as well.
2021 1st International Conference on Emerging Smart Technologies and Applications (eSmarTA), 2021
This research reviewed the different steganography techniques used to hide secrets within Arabic ... more This research reviewed the different steganography techniques used to hide secrets within Arabic text. In this paper, we aim to provide an overview of Arabic text steganography techniques from literature and previous studies that used Arabic language. Due to the rapid development in steganography techniques and different medium used to hide secrets and send it over internet, review the Arabic text steganography is important. Hiding text within Arabic language is the art of invisible communication to keep the information confidentiality due to the unique characteristics and features of Arabic language. Arabic text Steganography technique has many benefits that can be further used for Arabic-similar languages or any languages written in Arabic letters such as Pashto language (the official of Afghanistan language), Persian language (the official of Iran language) and Urdu language (the official of Pakistan language). Nevertheless, many Arabic text steganography techniques have been introduced in Arabic, some of which will be covered in this paper.
2019 First International Conference of Intelligent Computing and Engineering (ICOICE), 2019
N-gram distance (N-DIST) was developed by Kondrak's lately to measure the distance between tw... more N-gram distance (N-DIST) was developed by Kondrak's lately to measure the distance between two strings. It was found that, this distance could be computed by a smart dynamic programming procedure. The N-DIST has played important roles in a wide array of applications due to its representational and computational efficiency. To effect a more sensible, distance measure, the normalized edit distance was proposed. Many algorithms and studies have been dedicated along this line with impressive performances in last years. There is, however, a fundamental problem with the original definition of N-DIST that has remained without improved: its context-free nature. In determining the possible actions, i.e., deletion, insertion, transposition and substitution, consider work was given to the local behaviors of the string question that indeed encompass great amount of useful information concerning its content. In this proposed framework, two operations are developed. The original N-DIST algorithm does not consider the transposition operations and the algorithm has fixed the cost of insertion and deletion operations. In addition, the proposed E-N-DIST algorithm computes the costs of substitution and transposition operations is dependent on 2n+1- 1 states while the original N-DIST algorithm has been only dependent on 2n states. In this paper, the experiments carried out show the E-N-DIST algorithm, which gives a sort of results that are more accurate than the algorithms under discussion.
Background Bi-gram distance (BI-DIST) is a recent approach to measure the distance between two st... more Background Bi-gram distance (BI-DIST) is a recent approach to measure the distance between two strings that have an important role in a wide range of applications in various areas. The importance of BI-DIST is due to its representational and computational efficiency, which has led to extensive research to further enhance its efficiency. However, developing an algorithm that can measure the distance of strings accurately and efficiently has posed a major challenge to many developers. Consequently, this research aims to design an algorithm that can match the names accurately. BI-DIST distance is considered the best orthographic measure for names identification; nevertheless, it lacks a distance scale between the name bigrams. Methods In this research, the Soft Bigram Distance (Soft-Bidist) measure is proposed. It is an extension of BI-DIST by softening the scale of comparison among the name Bigrams for improving the name matching. Different datasets are used to demonstrate the efficie...
Nowadays personal names are not the only way to refer to celebrities and experts from different f... more Nowadays personal names are not the only way to refer to celebrities and experts from different fields, instead, they can be referred to by their aliases on the web. Associated aliases have remarkable importance in retrieving information about the personal name from the websites. Therefore, disclosing aliases can have an important role in overcoming many real-world challenges. In this research, the aim is to explore and propose a reliable algorithm that can detect aliases that occurred due to transliteration of Arabic names into English. An extension to the Enhanced N-gram distance algorithm (E-N-DIST) which was previously published is introduced in this paper. The proposed algorithm is called the Extended Enhanced N-gram distance algorithm (E-E-N-DIST). The differences between E-N-DIST and E-E-N-DIST are two main changes in calculating the cost of substitution and transposition. First, E-E-N-DIST is computed based on 2n+1 – 1 states. The second is the use of an edit operation calle...
Decision support systems (DSS) are useful business intelligence (BI) tools as they help managers ... more Decision support systems (DSS) are useful business intelligence (BI) tools as they help managers in large organizations make the best out of many decisions. Decisions are based on various types of raw data, models, documents, knowledge, and past experiences. This paper examines numerous criteria of decision support systems in the educational environment. Two effective methods were discovered and applied in this research, the analytic hierarchy process (AHP) and simple multi-attribute rating technique (SMART). These methods were selected due to their abilities to deal with complex decisional environments in general and widely used in practice for the educational environment in specific. The performance of methods is compared using two datasets called xApi-Education and IPEDS datasets. The obtained results based on the measurement of space complexity showed the level of convergence and similarity between these two methods. However, the experiments show that the Simple Multi-Attribute ...
The widespread usage of social media has led to the increasing popularity of online advertisement... more The widespread usage of social media has led to the increasing popularity of online advertisements, which have been accompanied by a disturbing spread of clickbait headlines. Clickbait dissatisfies users because the article content does not match their expectation. Detecting clickbait posts in online social networks is an important task to fight this issue. Clickbait posts use phrases that are mainly posted to attract a user’s attention in order to click onto a specific fake link/website. That means clickbait headlines utilize misleading titles, which could carry hidden important information from the target website. It is very difficult to recognize these clickbait headlines manually. Therefore, there is a need for an intelligent method to detect clickbait and fake advertisements on social networks. Several machine learning methods have been applied for this detection purpose. However, the obtained performance (accuracy) only reached 87% and still needs to be improved. In addition, ...
A specific phobia is a common anxiety-related disorder that can be treated efficiently using diff... more A specific phobia is a common anxiety-related disorder that can be treated efficiently using different therapies including exposure therapy or cognitive therapy. One of the most famous methods to treat a specific phobia is exposure therapy. Exposure therapy involves exposing the target patient to the anxiety source or its context without the intention to cause any danger. One promising track of research lies in VR exposure therapy (VRET) and/or AR exposure therapy (ARET), where gradual exposure to a negative stimulus is used to reduce anxiety. In order to review existing works in this field, a systematic search was completed using the following databases: PubMed, ProQuest, Scopus, Web of Science, and Google Scholar. All studies that present VRET and/or ARET solutions were selected. By reviewing the article, each author then applied the inclusion and exclusion criteria, and 18 articles were selected. This systematic review aims to investigate the previous studies that used either VR ...
Coronavirus (COVID-19) is the most prevalent coronavirus infection with respiratory symptoms such... more Coronavirus (COVID-19) is the most prevalent coronavirus infection with respiratory symptoms such as fever, cough, dyspnea, pneumonia, and weariness being typical in the early stages. On the other hand, COVID-19 has a direct impact on the circulatory and respiratory systems as it causes a failure to some human organs or severe respiratory distress in extreme circumstances. Early diagnosis of COVID-19 is extremely important for the medical community to limit its spread. For a large number of suspected cases, manual diagnostic methods based on the analysis of chest images are insufficient. Faced with this situation, artificial intelligence (AI) techniques have shown great potential in automatic diagnostic tasks. This paper aims at proposing a fast and precise medical diagnosis support system (MDSS) that can distinguish COVID-19 precisely in chest-X-ray images. This MDSS uses a concatenation technique that aims to combine pre-trained convolutional neural networks (CNN) depend on the tr...
For people with Autism Spectrum Disorder (ASD), using technological tools, such as augmented real... more For people with Autism Spectrum Disorder (ASD), using technological tools, such as augmented reality (AR) and serious games remain a new and unexplored option. To attract people with ASD who have communicative, social, emotional and attention deficit disorders to behavioral treatments, an attractive environment is needed that ensures continuity during treatment. The aim of the current work is to efficiently examine systematic reviews and relevant primary studies on ASD solutions from 2015 to 2020, particularly those using the traditional Picture Exchange Communication System (PECS), the application of augmented reality and those that propose serious games, thereby providing an overview of existing evidence and to identify strategies for future research. Five databases were searched for keywords that may be included within the broad Autism Spectrum Disorder ‘ASD’ umbrella term, alongside ‘augmented reality’, ‘serious games’ and ‘PECS’. We screened 1799 titles and abstracts, read, and...
2021 1st International Conference on Emerging Smart Technologies and Applications (eSmarTA), 2021
Birthrates forecasting can help decision-makers to understand population increment patterns, in a... more Birthrates forecasting can help decision-makers to understand population increment patterns, in addition to many issues that support governmental decisions, especially in developing countries as Yemen. Data Mining has important new emerged technologies, support business, and decision-making requirements. Forecasting is one of Artificial Neural Networks (ANN) and Time Series (TS) applications, as data mining techniques. In this paper, birthrates two forecasting models have experimented with. The ANN and TS are used for forecasting Yemeni hospital births data. Monthly birthrates data of four years are processed by each model. The forecasting of monthly next four years had produced, based on each model. Outcomes evaluation is showed the accuracy of forecasting results. Besides, TS outperforms the ANN model, in the context of monthly births data forecasting of Yemeni hospital data.
2019 First International Conference of Intelligent Computing and Engineering (ICOICE), 2019
Harmony search algorithm (HSA) is one of the relatively new metaheuristic algorithms that classif... more Harmony search algorithm (HSA) is one of the relatively new metaheuristic algorithms that classified under population-based search algorithms. Based on literature, hybridizing local-based searching algorithms with population-based algorithms can improve the performance of hybridized algorithms. This research is an extension to our previous work that focus on solving Nurse Rostering Problems (NRP) using hybrid metaheuristic algorithms. One of the improved version of HSA is enhanced harmony search algorithm (EHSA) where it overcomes some of the weaknesses of basic HSA. Slow convergence is noticed in EHSA which encourage us to hybridize it with other metaheuristic algorithms to improve its performance. In this research, EHSA is hybridized with great deluge algorithm (GD) and called Deluged harmony search algorithm (DHSA). DHSA then compared to CHSA (the hybridization of EHSA with Hill climbing (HC)) which developed earlier. To strike the balance between exploration and exploitation, th...
Nurse Rostering Problem (NRP) is a well-known NP-Hard combinatorial optimization problem. The fac... more Nurse Rostering Problem (NRP) is a well-known NP-Hard combinatorial optimization problem. The fact is that coping real-world constraints in allocating the shift duties fairly among the available nurses is still a hard task to accomplish. The problem becomes more serious due to the shortage of nurses. Thus, this work aims to tackle this problem by hybridizing an Enhanced Harmony Search Algorithm (EHSA) with the standard Hill climbing (HC). This hybridization may help to strike the balance between exploration and exploitation in the searching process. The proposed algorithm is called Climbing Harmony Search Algorithm (CHSA) where it applied to solve a real-world NRP dataset, which arises at the Medical Center of Universiti Kebangsaan. The results show that CHSA performs much better than EHSA alone and Basic Harmony Search algorithm (BHSA) in all instances in terms of obtained penalty values (PVs), desirable patterns (DPs) and computational time as well.
2021 1st International Conference on Emerging Smart Technologies and Applications (eSmarTA), 2021
This research reviewed the different steganography techniques used to hide secrets within Arabic ... more This research reviewed the different steganography techniques used to hide secrets within Arabic text. In this paper, we aim to provide an overview of Arabic text steganography techniques from literature and previous studies that used Arabic language. Due to the rapid development in steganography techniques and different medium used to hide secrets and send it over internet, review the Arabic text steganography is important. Hiding text within Arabic language is the art of invisible communication to keep the information confidentiality due to the unique characteristics and features of Arabic language. Arabic text Steganography technique has many benefits that can be further used for Arabic-similar languages or any languages written in Arabic letters such as Pashto language (the official of Afghanistan language), Persian language (the official of Iran language) and Urdu language (the official of Pakistan language). Nevertheless, many Arabic text steganography techniques have been introduced in Arabic, some of which will be covered in this paper.
2019 First International Conference of Intelligent Computing and Engineering (ICOICE), 2019
N-gram distance (N-DIST) was developed by Kondrak's lately to measure the distance between tw... more N-gram distance (N-DIST) was developed by Kondrak's lately to measure the distance between two strings. It was found that, this distance could be computed by a smart dynamic programming procedure. The N-DIST has played important roles in a wide array of applications due to its representational and computational efficiency. To effect a more sensible, distance measure, the normalized edit distance was proposed. Many algorithms and studies have been dedicated along this line with impressive performances in last years. There is, however, a fundamental problem with the original definition of N-DIST that has remained without improved: its context-free nature. In determining the possible actions, i.e., deletion, insertion, transposition and substitution, consider work was given to the local behaviors of the string question that indeed encompass great amount of useful information concerning its content. In this proposed framework, two operations are developed. The original N-DIST algorithm does not consider the transposition operations and the algorithm has fixed the cost of insertion and deletion operations. In addition, the proposed E-N-DIST algorithm computes the costs of substitution and transposition operations is dependent on 2n+1- 1 states while the original N-DIST algorithm has been only dependent on 2n states. In this paper, the experiments carried out show the E-N-DIST algorithm, which gives a sort of results that are more accurate than the algorithms under discussion.
Background Bi-gram distance (BI-DIST) is a recent approach to measure the distance between two st... more Background Bi-gram distance (BI-DIST) is a recent approach to measure the distance between two strings that have an important role in a wide range of applications in various areas. The importance of BI-DIST is due to its representational and computational efficiency, which has led to extensive research to further enhance its efficiency. However, developing an algorithm that can measure the distance of strings accurately and efficiently has posed a major challenge to many developers. Consequently, this research aims to design an algorithm that can match the names accurately. BI-DIST distance is considered the best orthographic measure for names identification; nevertheless, it lacks a distance scale between the name bigrams. Methods In this research, the Soft Bigram Distance (Soft-Bidist) measure is proposed. It is an extension of BI-DIST by softening the scale of comparison among the name Bigrams for improving the name matching. Different datasets are used to demonstrate the efficie...
Nowadays personal names are not the only way to refer to celebrities and experts from different f... more Nowadays personal names are not the only way to refer to celebrities and experts from different fields, instead, they can be referred to by their aliases on the web. Associated aliases have remarkable importance in retrieving information about the personal name from the websites. Therefore, disclosing aliases can have an important role in overcoming many real-world challenges. In this research, the aim is to explore and propose a reliable algorithm that can detect aliases that occurred due to transliteration of Arabic names into English. An extension to the Enhanced N-gram distance algorithm (E-N-DIST) which was previously published is introduced in this paper. The proposed algorithm is called the Extended Enhanced N-gram distance algorithm (E-E-N-DIST). The differences between E-N-DIST and E-E-N-DIST are two main changes in calculating the cost of substitution and transposition. First, E-E-N-DIST is computed based on 2n+1 – 1 states. The second is the use of an edit operation calle...
Decision support systems (DSS) are useful business intelligence (BI) tools as they help managers ... more Decision support systems (DSS) are useful business intelligence (BI) tools as they help managers in large organizations make the best out of many decisions. Decisions are based on various types of raw data, models, documents, knowledge, and past experiences. This paper examines numerous criteria of decision support systems in the educational environment. Two effective methods were discovered and applied in this research, the analytic hierarchy process (AHP) and simple multi-attribute rating technique (SMART). These methods were selected due to their abilities to deal with complex decisional environments in general and widely used in practice for the educational environment in specific. The performance of methods is compared using two datasets called xApi-Education and IPEDS datasets. The obtained results based on the measurement of space complexity showed the level of convergence and similarity between these two methods. However, the experiments show that the Simple Multi-Attribute ...
The widespread usage of social media has led to the increasing popularity of online advertisement... more The widespread usage of social media has led to the increasing popularity of online advertisements, which have been accompanied by a disturbing spread of clickbait headlines. Clickbait dissatisfies users because the article content does not match their expectation. Detecting clickbait posts in online social networks is an important task to fight this issue. Clickbait posts use phrases that are mainly posted to attract a user’s attention in order to click onto a specific fake link/website. That means clickbait headlines utilize misleading titles, which could carry hidden important information from the target website. It is very difficult to recognize these clickbait headlines manually. Therefore, there is a need for an intelligent method to detect clickbait and fake advertisements on social networks. Several machine learning methods have been applied for this detection purpose. However, the obtained performance (accuracy) only reached 87% and still needs to be improved. In addition, ...
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