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Meliponiculture is an activity of raising stingless bees to obtain bee products, mainly honey. Honey production by bees varies depending on various factors which also affect its amount and quality. Meliponiculturists practiced beekeeping... more
Meliponiculture is an activity of raising stingless bees to obtain bee products, mainly honey. Honey production by bees varies depending on various factors which also affect its amount and quality. Meliponiculturists practiced beekeeping in many ways to maximise honey production and its quality such as by considering location of beekeeping, apiary, flowers and plants. Nevertheless, there are many criteria that should be considered in meliponicultures in analysing its importance in producing good quality and quantity of honey. As it involves multiple conflicting criteria, different multi-criteria decision making (MCDM) techniques can be effectively applied to solve such type of problem. Thus, this paper applied MCDM techniques namely as Analytical Hierarchy Process (AHP), Fuzzy Analytical Hierarchy Process (FAHP) and Weighted Sum Method (WSM) to rank the criteria. A set of questionnaires with nine criteria is distributed to meliponiculturists. The criteria were selected based on previous studies of apiculture and opinions from meliponiculture experts from Mardi Alor Setar. The criteria are (1) flowers and plants, (2) water and hydrology, (3) land features, (4) apiary, (5) human activities, (6) pest, (7) wind and humidity, (8) road network, and (9) temperature. The results were analysed based on individual and group ranking. Both individual and group results provide a slightly different ranking by using the MCDM techniques. This study provides an insight on the factors which affect the honey production and its quality in meliponiculture industry which could help optimizing the honey production.
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This paper provides an evaluation of some existing data integrations approaches according to the Patrick Ziegler's ASME criteria for evaluating. These criteria for evaluating identify the characteristics of integrated approaches and... more
This paper provides an evaluation of some existing data integrations approaches according to the Patrick Ziegler's ASME criteria for evaluating. These criteria for evaluating identify the characteristics of integrated approaches and investigate the existing of data integration approaches for their support for user-specific perspectives. Through this review, this paper aims to identify some potential implementation methods and architectures that support for a truly user-specific perspective in the context of the structured, semistructured, and unstructured data integration approaches.
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Heart diseases are serious problem in many countries worldwide. In Malaysia, it has been a major killer since 1980. Many health conditions are closely related to heart disease. However, a large amount of data that medical centers have... more
Heart diseases are serious problem in many countries worldwide. In Malaysia, it has been a major killer since 1980. Many health conditions are closely related to heart disease. However, a large amount of data that medical centers have collected each year is not well-mined to find connections between them that can aid in the prognosis of heart disease. Therefore, the purpose of this study is to propose a predictive model of heart disease based on machine learning for prognosis to help individuals with symptoms to seek early advice and treatment. By following the Knowledge Discovery in Database (KDD) methodology that includes data selection, data pre-processing, data transformation, data mining, and interpretation or evaluation of acquired knowledge, this study has tested a dataset taken from UCI Machine Learning Repository. The classification of Artificial Neural Network and Random Forest was used. They were selected based on their adequacy in the medical field, particularly in the a...
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In the domain of Marine Education and Training (MET), simulators have been utilized for the purpose of training seafarers in the norms for avoiding collisions or for developing the skill of ship manoeuvrability, and even the operation of... more
In the domain of Marine Education and Training (MET), simulators have been utilized for the purpose of training seafarers in the norms for avoiding collisions or for developing the skill of ship manoeuvrability, and even the operation of machinery in the engine room, as well as for conducting research on the subject matter of ship structure, specialized vessel operation, working principle of equipment, and shipboard safety training. These tools are even more important when facing disruptive events such as the COVID-19 pandemic. In MET institutions, full-mission bridge and engine room simulators have been utilized for teaching seafarers for more than a decade. A Systematic Literature Review (SLR) was conducted to identify immersive and non-immersive simulator applications produced over the previous ten years to improve seafarers’ experiential teaching and learning, in the maritime domain. We retrieved 27 articles using the four stages of PRISMA paradigm: Identification, Screening, El...
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Data mining remains as one of the most important research domain in Knowledge Discovery and Database (KDD). Moving deeper, Association Rule Mining (ARM) is one of the most prominent areas in detecting pattern analysis especially for... more
Data mining remains as one of the most important research domain in Knowledge Discovery and Database (KDD). Moving deeper, Association Rule Mining (ARM) is one of the most prominent areas in detecting pattern analysis especially for crucial business decision making. It aims to extract interesting correlations, frequent patterns, association or casual structures among set of items in the transaction databases or other data repositories. Even though most of these data repositories are dealing with flat files, current trend is focusing on using relational Database Management System (DBMS) for the more systematic and structured management of data. In response to the importance of adopting relational database, in this paper we implement MySQL (My Structured Query Language) as our association rule mining database engine in testing benchmark dense datasets which available from Frequent Itemset Mining (FIMI) online repository. Our study is focusing on Eclat algorithm as well as its variants in generating frequent and interesting rule, as a continual from our previous studies. The performance result shows a promising signal as to confirm on the benefits of relational database mechanism in storing any transaction data.
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Non-ideal eye image is a contemporary issue that was attracted many researchers to contribute a solution in iris recognition domain. It consists of iris occlusion, motion blurred, off-angled, and outlier’s situation issues. However it is... more
Non-ideal eye image is a contemporary issue that was attracted many researchers to contribute a solution in iris recognition domain. It consists of iris occlusion, motion blurred, off-angled, and outlier’s situation issues. However it is rarely discussed on outlier’s situation in recognition field related with the ophthalmology domain. Therefore this study was motivated by the outlier’s situation issue in order to prepare a reliable ophthalmology system by using Hough transform segmentation approach. Three frequently used iris databases will be applied in this study to test the segmentation approach and they are CASIA, UBIRIS and UPOL. The result from the conducted testing is to compare and evaluate the accuracy of the approach to the databases. Hence, the consequence from this study is to emphasize the issue that influence the accuracy of the segmentation process.
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Coronavirus often called COVID-19 is a deadly viral disease that causes as a result of severe acute respiratory syndrome coronavirus-2 that needs to be identified especially at its early stages, and failure of which can lead to the... more
Coronavirus often called COVID-19 is a deadly viral disease that causes as a result of severe acute respiratory syndrome coronavirus-2 that needs to be identified especially at its early stages, and failure of which can lead to the further spread of the virus. Despite with the huge success recorded towards the use of the original convolutional neural networks (CNN) of deep learning models. However, their architecture needs to be modified to design their modified versions that can have more powerful feature layer extractors to improve their classification performance. This research is aimed at designing a modified CNN of a deep learning model that can be applied to interpret X-rays to classify COVID-19 cases with improved performance. Therefore, we proposed a modified convolutional neural network (shortened as modification CNN) approach that uses X-rays to classify a COVID-19 case by combining VGG19 and ResNet50V2 along with putting additional dense layers to the combined feature lay...
Raisin grains are among the agricultural commodities that can benefit health. The production of raisin grains needs to be classified to achieve optimal results. In this case, the classification is carried out on two types of grains,... more
Raisin grains are among the agricultural commodities that can benefit health. The production of raisin grains needs to be classified to achieve optimal results. In this case, the classification is carried out on two types of grains, namely Kecimen and Besni. However, inaccurate sample data can affect the performance of the model. In this study, two sampling techniques are proposed: stratified and shuffled. The proposed classification model is RF, GBT, NB, LR, and NN. This study aims to identify the performance of classification models based on sampling techniques. Classification models are applied to the seven-features dataset, and modeling is done by cross-validation. The results of the models were tested with a different amount of test data. The performance of the models was evaluated related to accuracy and AUC. The best outcomes of all models based on stratified sampling were founded on tested data of 40 percent with a mean accuracy of 85.50% and an AUC of 0.921. In comparison, ...
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Sistem pembayaran elektronik merupakan kaedah pembayaran melalui Internet yang semakin digemari oleh masyarakat Malaysia dan dunia amnya. Terdapat pelbagai saluran pembayaran yang memudahkan urusan pembelian antara penjual dengan pembeli... more
Sistem pembayaran elektronik merupakan kaedah pembayaran melalui Internet yang semakin digemari oleh masyarakat Malaysia dan dunia amnya. Terdapat pelbagai saluran pembayaran yang memudahkan urusan pembelian antara penjual dengan pembeli iaitu transaksi tanpa tunai. Keyakinan pengguna semakin menyerlah dengan penambahbaikan keselamatan portal e-dagang dan kesungguhan pihak kewangan seperti institusi kewangan. Objektif penulisan makalah ini adalah untuk menerangkan tentang kelebihan dan kekurangan bagi sistem pembayaran secara elektronik. Kesimpulannya, penggunaan sistem pembayaran secara elektonik ini menjadikan satu perkara yang memudahkan serta lebih selamat yang dipercayai pada masa kini. Pelbagai urus niaga di era COVID-19 pandemik ini telah membudayakan kaedah pembayaran secara elektronik ini.
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F-I-S-Ht is a wonderful discovery on human biometric. Fingerprints are the ridge and furrow patterns on the tip of the finger and its verification is an important biometric technique for personal identification. The quality of the... more
F-I-S-Ht is a wonderful discovery on human biometric. Fingerprints are the ridge and furrow patterns on the tip of the finger and its verification is an important biometric technique for personal identification. The quality of the fingerprint image is the most significant factor in a reliable matching process. Thus, any pre- processing algorithm should aim to enhance the quality of the existing features without creating false features. This scenario brings the idea of the research. The research focus on the segmentation approach in pre-processing images. The purpose of the study is to identify a segmentation approach of fingerprint image by considering several approaches namely Hierarchical technique and Region growing by pixel aggregation technique. The process is vital when to apply next pre-processing stages i.e. thinning, identifying between true and false minutiae and minutiae extraction process. The research is supported by 50 samples of data that is collected through an avail...
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Association Rule Mining (ARM) is one of the most prominent areas in detecting pattern analysis especially for crucial business decision making. With the aims to extract interesting correlations, frequent patterns, association or casual... more
Association Rule Mining (ARM) is one of the most prominent areas in detecting pattern analysis especially for crucial business decision making. With the aims to extract interesting correlations, frequent patterns, association or casual structures among set of items in the transaction databases or other data repositories, the end product of association rule mining is the analysis of pattern that could be a major contributor especially in managerial decision making. Most of previous frequent mining techniques are dealing with horizontal format of their data repositories. However, the current and emerging trend exists where some of the research works are focusing on dealing with vertical data format and the rule mining results are quite promising. One example of vertical rule mining technique is called Eclat which is the abbreviation of Equivalence Class Transformation. In response to the promising results of the vertical format and mining in a higher volume of data, in this study we propose a new model called an Incremental-Eclat adopting via relational database management system, MySQL (My Structured Query Language) that serves as our association rule mining database engine in testing benchmark Frequent Itemset Mining (FIMI) datasets from online repository. The experimental results of our proposed model outperform the traditional Eclat with certain order of magnitude.
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Stingless bee is one of the bees that produce expensive honey because stingless bee only produces less than 1kg honey per year. Due to improper management and security been imposed, stingless beehive is continuously been targeted by thief... more
Stingless bee is one of the bees that produce expensive honey because stingless bee only produces less than 1kg honey per year. Due to improper management and security been imposed, stingless beehive is continuously been targeted by thief for its valuable honey production. The bee farmer also is facing difficulty in tracking and monitoring the number of their beehives that are scattered in certain area in their farm. Taking serious consideration on a good quality of honey production, temperature is the major issues to concern. Honey production can be affected by extreme temperature. When the temperature is too high, the stingless bees become irritable or contradictory, when temperature is too low, the stingless bees become motionless. Therefore, the need for continuously tracking and monitoring of the beehive is crucial to conserve the quality honey production. The objective of the research is to analyze the suitable temperature for bee productivity. Next is to design a system that ...
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Wireless estimation bandwidth is used in path selection for a network environment. To access the internet, a typical user shares the same bandwidth that has been provided by the Internet Service Provider (ISP). The scenario worsens when a... more
Wireless estimation bandwidth is used in path selection for a network environment. To access the internet, a typical user shares the same bandwidth that has been provided by the Internet Service Provider (ISP). The scenario worsens when a few of the users access multimedia content on the Internet which requires high bandwidth at the same time. This research could be enhanced in other different network environments, such as wired and mobile phone environments, and represents an analysis of ready bandwidth using a few wireless bandwidth estimation tools, which are WBest, Pathload, IGI MRTG, PRTG and PTR. This paper attempts to design and develop a detection mechanism for wireless estimation bandwidth to estimate an available bandwidththrough several sending of injection traffic packets to the server. In this paper, we measured available bandwidth with WBest. Then we analysed the estimation measurements prior to 2 simulations done on Wireless Mode 11 Mbps 802.11b and Wireless Mode 54 M...
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The purpose of this research is to develop a battery management system capable of directly reading internal impedance. Currently, many systems used in major markets are based on lead acid batteries (LABs) because of their effectiveness in... more
The purpose of this research is to develop a battery management system capable of directly reading internal impedance. Currently, many systems used in major markets are based on lead acid batteries (LABs) because of their effectiveness in powering such major applications as telecommunication systems, rectifiers, uninterruptable power supplies (UPSs), forklifts, and buggy systems. LABs are easily available at a low cost. But they last only two to five years because of factors that erode performance: depth of discharge (DOD), the lack of any mechanism to prevent excessive charging, extreme temperatures, and the charging algorithm. The popular lithium iron phosphate (LiFeP04) battery has a longer life cycle, higher energy density, and a longer shelf life, and it can provide continuous power over longer periods of time. But because it is expensive, in many contexts it is inadvisable to replace LABs with LiFeP04 batteries. As an alternative, this paper introduces a battery monitoring sys...
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Pattern mining is noticed as a key challenge within the field of data mining and knowledge discovery. Association rule mining is a fundamental step to discover relationships between data in a transactional database or relational... more
Pattern mining is noticed as a key challenge within the field of data mining and knowledge discovery. Association rule mining is a fundamental step to discover relationships between data in a transactional database or relational database. In recent years, there has been an increasing demand for infrequent pattern mining. Finding infrequent patterns plays an essential role in mining associations, correlations and many other interesting relationships among data. As infrequent pattern mining has not been well explored, there is still some fundamental theory that needs to be established especially using ECLAT algorithm. In this paper, we have proposed R-ECLAT algorithms for finding infrequent patterns with the purpose of discovering on how these algorithms can be used to obtain infrequent patterns in a large dataset.
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This article presents data on digital adoption by enterprises in Malaysian industrial sectors during the COVID-19 pandemic. The data were collected during the periods of Conditional Movement Control Order (CMCO) and Recovery Movement... more
This article presents data on digital adoption by enterprises in Malaysian industrial sectors during the COVID-19 pandemic. The data were collected during the periods of Conditional Movement Control Order (CMCO) and Recovery Movement Control Order (RMCO) from October 11 to December 31, 2020. Data collection was completed through an online questionnaire survey conducted among a sample of 432 enterprises from four industrial sectors, namely services, retail, manufacturing, and tourism, in all states in Malaysia. The sample was selected using cluster and systematic random sampling. The questionnaire asked respondents to state whether they used the Internet, computers, phones, web sites, e-payment, and e-commerce to complete their activities relating to finance, production and operations, human resource management, and marketing. The data were analysed using descriptive statistics and cross-tabulation. The data show the extent of digital adoption by Malaysian enterprises during the pandemic in comparison to the situation before the pandemic. The data may be of use to other similar researchers as comparison and to policy makers as guides in devising related policies.
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Data mining is the process of discovering knowledge and previously unknown pattern from large amount of data. The association rule mining (ARM) has been in trend where a new pattern analysis can be discovered to project for an important... more
Data mining is the process of discovering knowledge and previously unknown pattern from large amount of data. The association rule mining (ARM) has been in trend where a new pattern analysis can be discovered to project for an important prediction about any issues. Since the first introduction of frequent itemset mining, it has received a major attention among researchers and various efficient and sophisticated algorithms have been proposed to do frequent itemset mining. Among the best-known algorithms are Apriori and FP-Growth. In this paper, we explore these algorithms and comparing their results in generating association rules based on benchmark dense datasets. The datasets are taken from frequent itemset mining data repository. The two algorithms are implemented in Rapid Miner 5.3.007 and the performance results are shown as comparison. FP-Growth is found to be better algorithm when encountering the support-confidence framework.
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In e-Learning web applications, users interact directly via the web platforms with other users. The learning management system (LMS) is one web platform that has been used to manage the online teaching and learning (T&L). Moodle is an... more
In e-Learning web applications, users interact directly via the web platforms with other users. The learning management system (LMS) is one web platform that has been used to manage the online teaching and learning (T&L). Moodle is an open-sourced LMS that has a widespread adoption in several universities as a virtual learning environment. However, each university does not have any connection with another. Thus, it is difficult for students in one university to enroll in any readily available courses from another. The Malaysian Government has taken the lead to embark on the Massive Open Online Courseware (MOOC) for the Malaysian Public Universities (MPU). This will enable any student from any university to enroll in any courses available in any university. This paper describes a framework called ArmadaNet for a multi-institution collaborative MOOC platform. It covers technical and non-technical issues related to the MOOC implementation. The Moodle LMS has been chosen as the web platform to support this multi-institution MOOC collaboration. The development of ArmadaNet as the model for the collaboration will be given. It is a hub that connects and displays courses hosted in the MOOC. The progress of the implementation is given.
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The amount of all kinds of data that available electronically has increased dramatically in recent years. The data resides in different types, either in structured (SD), semi-structured (SSD) or unstructured data (USD). Data integration... more
The amount of all kinds of data that available electronically has increased dramatically in recent years. The data resides in different types, either in structured (SD), semi-structured (SSD) or unstructured data (USD). Data integration for multiple types of data can be defined as the problem of combining data from heterogeneous sources to one unified structure. A user is unable to view it as a single entity irrespective of the origination or its data type. It involves combining data coming from different sources and providing users with a unified view of these data. In this paper, we propose a diagrammatic representation of a wrapper for multiple types of SSD data extraction using Document Object Model (DOM). We have implemented the automated web extractor, Wrapper for Extraction of Image using DOM (WEID) using the PHP programming language that can extract images from a web page. Experimental results on a web page are encouraging and confirm the feasibility of the approach in extra...
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Recent evolutions in web technology and computer science provide environmental community in expanding resources for data collection and analysis. Today, people are facing challenges to the design of analysis methods, workflows, and... more
Recent evolutions in web technology and computer science provide environmental community in expanding resources for data collection and analysis. Today, people are facing challenges to the design of analysis methods, workflows, and interaction with data sets. Data integration is one of older research fields in database area. It is consists of three types of data; structured data, semi-structured data and unstructured data. Web pages is a part of semi-structured data. In this paper, we briefly introduce the problem of data extraction from web pages focus on images. We also discuss the evolution of extraction images from semi-structured to structured format using WEIDJ (Wrapper for extraction Images using Document Object Model (DOM) and JavaScript Object Notation Data (JSON) approach). An experiment was conducted on same website using different approach JSON and DOM to show the comparison of time performance.
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Dengue is a mosquito-borne viral disease that is surging and becomes worldwide serious issues. Currently, due to lack of specific treatment or vaccine against dengue, many forms of vector control remains a key strategy for dengue fever... more
Dengue is a mosquito-borne viral disease that is surging and becomes worldwide serious issues. Currently, due to lack of specific treatment or vaccine against dengue, many forms of vector control remains a key strategy for dengue fever prevention. In response to the issue, this paper introduces an AedesTech Mosquitoes Home System (AMHS) that is equipped with a special trade secret formulation or also called as Insecticide Growth Regulator (IGR) and combines with Internet of Things (IoT) technology for vector control. An IGR is a pheromone-like liquid formulation that is a chemical that serves to stimulate and have sexually attract the male and female that will attract and lure adult female mosquitoes to lay eggs in them, and the adult mosquitoes will soon die after lying eggs. Those eggs that already laid with the chemical will not hatch or die at an expected of 99% rate, or go beyond the pulp level. Our sustainable approach offers for two (2) novel features. First, to monitor the c...
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Microwave co-pyrolysis was examined as an approach for simultaneous reduction and treatment of environmentally hazardous hospital plastic waste (HPW), lignocellulosic (palm kernel shell, PKS) and triglycerides (waste vegetable oil, WVO)... more
Microwave co-pyrolysis was examined as an approach for simultaneous reduction and treatment of environmentally hazardous hospital plastic waste (HPW), lignocellulosic (palm kernel shell, PKS) and triglycerides (waste vegetable oil, WVO) biowaste as co-feedstock. The co-pyrolysis demonstrated faster heating rate (16-43 °C/min) compared to microwave pyrolysis of single feedstock (9-17 °C/min). Microwave co-pyrolysis of HPW/WVO performed at 1:1 ratio produced a higher yield (80.5 wt%) of hydrocarbon liquid fuel compared to HPW/PKS (78.2 wt%). The liquid oil possessed a low nitrogen content (< 4 wt%) and free of sulfur that could reduce the release of hazardous pollutants during its use as fuel in combustion. In particular, the liquid oil obtained from co-pyrolysis of HPW/WVO has low oxygenated compounds (< 16%) leading to reduction in generation of potentially hazardous sludge or problematic acidic tar during oil storage. Insignificant amount of benzene derivatives (< 1%) was also found in the liquid oil, indicating the desirable feature of this pyrolysis approach to suppress the formation of toxic polycyclic aromatic hydrocarbons (PAHs). Microwave co-pyrolysis of HPW/WVO improved the yield and properties of liquid oil for potential use as a cleaner fuel, whereas the liquid oil from co-pyrolysis of HPW/PKS is applicable in the synthesis of phenolic resin.
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The Internet of Things (IoT) technology is the main contributor in numerous smart applications. The reason is because it offers for 24/7 hours of control and maintenance geographically apart, thus reduces labor or manpower cost... more
The Internet of Things (IoT) technology is the main contributor in numerous smart applications. The reason is because it offers for 24/7 hours of control and maintenance geographically apart, thus reduces labor or manpower cost significantly. The 3 main components for any IoT applications are the source of power (energy), the microcontroller and the sensor (s) involved. Previous issues mainly related to how long the source of power could last for the applications to continue its operation. This paper presents IoT technology for hygiene application to address the utilization of toilet tissue named as Intelligent Tissue Dispenser System (iTDS). The iTDS device relies on the microcontroller and sensor in order to operate the intended task. The microcontroller used is an IoT based device called ESP8266 which is a WiFi-embedded microcontroller that utilized standard everyday WiFi band frequency which is at 2.4 GHz. For the sensor, an ultrasonic distance measurement device is used. The ul...
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Image enhancement is becoming increasingly important with the advancement of space exploration techniques and the technological development of more durable and scientifically sound observatories equipped with more powerful telescopes. The... more
Image enhancement is becoming increasingly important with the advancement of space exploration techniques and the technological development of more durable and scientifically sound observatories equipped with more powerful telescopes. The enhancement of images helps astronomers analyze the results and act toward determining the dates of religious festivals. This work describes a technique known as contrast-limited adaptive histogram equalization (CLAHE) with grayscale contrast enhancement and bilateral filtering. We apply CLAHE on the L component of the CIE-Lab color space to adjust lightness contrast. Subsequently, grayscale contrast enhancement is performed to increase the visibility of the moon crescent. Noise caused by grayscale contrast enhancement is reduced using bilateral filtering. Two quantitative measures are selected (PSNR and MSE) to show the visual improvement achieved by the proposed algorithm.
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Over the decades, Information and Communication Technology (ICT) has become a new trend in the business environment and widely spread in no time at all. Considering all the benefits of ICT, the study utilizes Facebook social media as the... more
Over the decades, Information and Communication Technology (ICT) has become a new trend in the business environment and widely spread in no time at all. Considering all the benefits of ICT, the study utilizes Facebook social media as the electronic business (e-business) and networking platform in marketing the local products of Setiu Wetland women entrepreneurs into wider customer base. This paper presents a case study of rural women entrepreneur in Setiu Wetland, Terengganu, Malaysia from the period of March 2017 until February 2018. To help improve the livelihood through e-business, women entrepreneurs needs to be equipped with entrepreneurship skill explicitly and Information and Communication (ICT) skill implicitly. Through the twelve months' period of tracking the respondent's income, the outcome of this project depicts a 100% achievement with linear proportion of increasing income rate.
Setiu Wetland (SW) is located in Terengganu, Malaysia where it is enriched with vast variety of natural resources. Most SW rural women are doing small medium business with own special skills to help family in their living. They do have... more
Setiu Wetland (SW) is located in Terengganu, Malaysia where it is enriched with vast variety of natural resources. Most SW rural women are doing small medium business with own special skills to help family in their living. They do have skills in utilizing SW resources but lack in proper marketing strategy for their business growth. The paper presents the results of Niche Research Grant Scheme (NRGS) project of UMT for improving the livelihood of Setiu Wetland (SW) rural women entrepreneurship skills through an e-business social innovation model. This project undertakes selected women respondents in giving assistance through the use of social media networking application in marketing of their local products, thus improving their financial stability. The results on income projection in pre and post implementation of the e-business model among SW women shows a significant improvement to their financial growth. It proves that the model has achieved the objective of improving the livelih...
Dengue remains among the major causes of mortality worldwide. Manyresearch and medical institutions are still investigating a treatment or vaccineand vector control that would be a key strategy for dengue fever prevention.We introduce... more
Dengue remains among the major causes of mortality worldwide. Manyresearch and medical institutions are still investigating a treatment or vaccineand vector control that would be a key strategy for dengue fever prevention.We introduce Intelligent Mosquito Spray Dispenser system X’MOS-IOT, aninnovative concept that includes IR4.0 for the cloud storage automation as wellas data analytics and exchange across cyber-physical systems and cognitivecomputing. The X’MOS-IOT provides a solution for spray interval automationusing sensor and battery optimizations with direct Wifi module technology. Thedevice is equipped with X’MOS spray mini aerosol repellent, offering effectiveenvironmentally friendly Aedes mosquito control. This all-in-one systemensures a mosquito-free environment in your home. The implementation showsthe X’MOS-IOT system is able to update the level of each X’MOS in X’MOSIOTdevices, reducing the cost of manual human checking for X’Mos refill.
Conventionally, partial differential equations (PDE) problems are solved numerically through discretization process by using finite difference approximations. The algebraic systems generated by this process are then finalized by using an... more
Conventionally, partial differential equations (PDE) problems are solved numerically through discretization process by using finite difference approximations. The algebraic systems generated by this process are then finalized by using an iterative method. Recently, scientists invented a short cut approach, without discretization process, to solve the PDE problems, namely by using machine learning (ML). This is potential to make scientific machine learning as a new sub-field of research. Thus, given the interest in developing ML for solving PDEs, it makes an abundance of an easy-to-use methods that allows researchers to quickly set up and solve problems. In this review paper, we discussed at least three methods for solving high dimensional of PDEs, namely PyDEns, NeuroDiffEq, and Nangs, which are all based on artificial neural networks (ANNs). ANN is one of the methods under ML which proven to be a universal estimator function. Comparison of numerical results presented in solving the...
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World wide web (www) is a huge information repository and rapidly growing as source of information. Web pages is known as semi-structured data and it contains variety of information such as text, images, audio, video and other various... more
World wide web (www) is a huge information repository and rapidly growing as source of information. Web pages is known as semi-structured data and it contains variety of information such as text, images, audio, video and other various format. The process of extracting information from the web pages is time consuming and requires correct approach and this paper presents an improvised algorithm in extracting images from the web pages efficiently. In this paper, we study the problem of extracting images in efficient manner. This paper presents an improvised algorithm using Document Object Model (DOM) and JavaScript Object Notation (JSON) that accepts web address as input and extracted images information as the output. The experimental evaluation on webpage of real input has been discussed to prove the limitation of existing method. An experiment was conducted on same website using different approach JSON and DOM to show the comparison of time performance.
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Frequent and infrequent itemset mining are trending in data mining techniques. The pattern of Association Rule (AR) generated will help decision maker or business policy maker to project for the next intended items across a wide variety... more
Frequent and infrequent itemset mining are trending in data mining techniques. The pattern of Association Rule (AR) generated will help decision maker or business policy maker to project for the next intended items across a wide variety of applications. While frequent itemsets are dealing with items that are most purchased or used, infrequent items are those items that are infrequently occur or also called rare items. The AR mining still remains as one of the most prominent areas in data mining that aims to extract interesting correlations, patterns, association or casual structures among set of items in the transaction databases or other data repositories. The design of database structure in association rules mining algorithms are based upon horizontal or vertical data formats. These two data formats have been widely discussed by showing few examples of algorithm of each data formats. The efforts on horizontal format suffers in huge candidate generation and multiple database scans ...