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Journal receives papers in continuous flow and we will consider articles from a wide range of Information Technology disciplines encompassing the most basic research to the most innovative technologies. Please submit your papers electronically to our submission system at http://jatit.org/submit_paper.php in an MSWord, Pdf or compatible format so that they may be evaluated for publication in the upcoming issue. This journal uses a blinded review process; please remember to include all your personal identifiable information in the manuscript before submitting it for review, we will edit the necessary information at our side. Submissions to JATIT should be full research / review papers (properly indicated below main title).

Journal of Theoretical and Applied Information Technology
September 2020 | Vol. 98 No.18

Title:	DESIGN OF COMPOSITE MATERIALS USING INFORMATION TECHNOLOGY
Author:	SERIK ZHUZBAYEV, AKNUR ADILOVA, SHYNAR AKHMETZHANOVA, BAKYT JUZBAYEVA, DIANA SABITOVA
Abstract:	In this article, composite materials are considered, and the explicit difference scheme in solving dynamic problems of elasticity theory was developed on the basis of a combination of the spatial characteristics and the splitting methods, by extending the scope of its application to inhomogeneous linearly deformable bodies. This article discusses the stability of solving non-stationary problems of mechanics as applied to related problems of wave dynamics, and also compares the results of solutions obtained by the spatial characteristics method and the proven method, the algorithm for calculating the voltage at speeds at specific points, the situation at each special point with the interaction of a large number of nodes around her, communication and interaction. The 21st century can be attributed to the age of composite materials. Today, without them, it is almost impossible to imagine the construction of industry, civil and residential complexes. Composites have entered and still enter our life and almost completely replace traditional materials in construction, energy, transport, electronics, etc. Scientific and technical progress in the construction industry involves the usage of new and effective building materials with various complex of properties, different purposes.
Keywords:	Composite Materials, Mathematical Models, Study Area, Conditions, Medium, Difference Equation, Function.Tension, Speed, Numerical Solution
Source:	Journal of Theoretical and Applied Information Technology 30^th September 2020 -- Vol. 98. No. 18 -- 2020
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Title:	CHAOTIC CUCKOO OPTIMIZATION ALGORITHM FOR SOLVING GLOBAL OPTIMIZATION PROBLEMS
Author:	SALWA EL- SAYED, ABD EL-NASSER H. ZAYED, ‎ MAHMOUD ISMAIL
Abstract:	In this paper, three chaotic algorithms based on Cuckoo Optimization Algorithm (COA) are introduced. For avoiding local optima and getting high convergence speed, chaotic theory is used. The first Chaotic Cuckoo Optimization Algorithm (CCOA1) uses chaotic maps to estimate Egg Laying Radius (ELR) coefficient. The second Chaotic Cuckoo Optimization Algorithm (CCOA2) uses chaotic maps to estimate the immigration coefficient (F). In the third Chaotic Cuckoo Optimization Algorithm (CCOA3), chaotic maps are incorporated in the immigration process to the goal point. Ten chaotic maps are applied to determine precisely which map can give the best results for each chaotic algorithm. To verify the efficiency of the proposed algorithms, a set of different types of benchmark problems is selected and tested. Also, Wilcoxon rank-sum test is performed to approve that the results are statistically significant. The results show how the three proposed algorithms can improve COA and also show the ability of CCOA3 to get better results than other compared algorithms. Besides, CCOA3 can achieve high convergence speed than COA and other proposed algorithms. Besides, three chaotic algorithms are tested on two engineering problems and compared with different algorithms from the literature in a fair comparison and results show the ability of the proposed algorithms in getting superior results.
Keywords:	Cuckoo Optimization Algorithm, Chaotic Maps, Metaheuristics, Optimization. Evolutionary Algorithms
Source:	Journal of Theoretical and Applied Information Technology 30^th September 2020 -- Vol. 98. No. 18 -- 2020
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Title:	STATISTICAL MORPHOLOGICAL ANALYSIS BASED SUPERVISED CLASSIFICATION ALGORITHM FOR DIAGNOSING ACUTE LYMPHOBLASTIC LEUKEMIA
Author:	JKC SHYALIKA, PPNV KUMARA, DU KOTTAHACHCHI
Abstract:	Leukemia is a fatal disease of the type â€œBlood Cancerâ€, where the White Blood Cells (WBC) increases in human bone marrow and peripheral blood. Acute Lymphoblastic Leukemia (ALL) is a common types of leukemia that affects young children of below 10 years and adults over 60 years, aroused by accumulation and overproduction of immature and cancerous cells identified as lymphoblasts. At present, the diagnosis of ALL includes measures alike performing a full blood count, bone marrow biopsy, blood picture, immunophenotyping, cytochemical stain and cytogenetics. These medicinal techniques are highly tedious, costly, requires expertise of hematologists and available only in few hospitals especially in developing countries. Hence, as an alternative, use of image processing and machine learning to diagnose ALL would become an effective solution. Even though, several research groups have used image processing to detect and diagnose ALL, recognition and splitting of overlapping Red Blood Cells (RBC) with WBC has however been a challenging issue. This paper is about a research study and an application that includes an image processing and machine learning algorithm to diagnose ALL while attempting to solve the issue of overlapping cells. The research is also extended to detect the quality devastation in blood films in terms of storing them for prolonged period. The inputs for this application include microscopic peripheral blood films of ALL patients and healthy individuals obtained from Department of Pathology Clinic at Faculty of Medicine, University of Colombo, Sri Lanka. This research project has received verification of ethical approval from Faculty of Medicine, General Sir John Kotelawala Defence University, Sri Lanka. In the developed application, segmentation using morphological operations in OpenCV Python and supervised learning based classification using K-Nearest Neighbour implementation has been proposed in detection and diagnosing of ALL. As per the results, the proposed algorithm has led to a high accuracy of 88.8% in diagnosing ALL. The end product includes a Python based QT GUI based development suite that performs main targeted backend functionalities and a PHP based web application that serves hematologists, doctors and patients to perform utility functions.
Keywords:	Acute Lymphoblastic Leukemia, Image Processing, Segmentation and Feature Extraction, Classification, K-Nearest Neighbour, Supervised Learning
Source:	Journal of Theoretical and Applied Information Technology 30^th September 2020 -- Vol. 98. No. 18 -- 2020
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Title:	EFFICIENT VIDEO ENCODING ACCELERATION FOR CLOUD GAMING
Author:	AHMAD A. MAZHAR , MANAR A. MIZHER
Abstract:	Cloud computing is an information technology model that provides access to system resources with higher level of services capability. These resources are considered reliable, flexible and affordable for many types of applications and users. Gaming industry is one filed that gained benefits of cloud computing as new cloud gaming architectures have been introduced. Many advantages of cloud gaming have affected the success of gaming according to the improvements on traditional online gaming. However, cloud gaming suffers from several drawbacks such as the huge amount of required video processing and the computational complexity needed. This paper shows the original system drawbacks and devises a new and novel algorithm for speeding up the encoding process and reducing the computational complexity. Improvements on the video codec led to 41% speeding up on the total encoding time with negligible loss of usersâ€™ satisfactions.
Keywords:	Cloud Gaming, Computational Complexity, Motion Estimation, H.264, Video Encoding
Source:	Journal of Theoretical and Applied Information Technology 30^th September 2020 -- Vol. 98. No. 18 -- 2020
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Title:	CONTEXT-AWARE REASONING MODEL USING DEEP LEARNING AND FOG COMPUTING FOR WASTE MANAGEMENT IN IOTS ENVIRONMENTS
Author:	SHEREEN A. EL-AAL, AHMED A. A. GAD-ELRAB, AFAF A. S. ZAGHROUT, NEVEEN I. GHALI
Abstract:	Recently, Internet of Things (IoTs) influences every aspect of human daily lives through intelligent systems as healthcare, traffic management, and smart building. These IoTs systems depend on contextualization of collecting data through context aware system to gain knowledge by using context reasoning. context reasoning is a way for deducing knowledge and providing better understanding of the collected raw data. Context reasoning is commonly carried out at the cloud due to its high processing capabilities. However, the main challenges of using cloud are high latency time and resource consumption. To meet these challenges, Fog computing is proposed as an intermediate layer between the IoTs devices and the cloud layer to comply IoTs requirements of latency time reduction and resource consumption by deploying services to the fog layer. In this paper a new context reasoning model is proposed based on three previously defined Deep Learning (DL) models which are GoogleNet, ResNet101 and DenseNet201, the results obtained in three cases are compared in cloud and cloud/fog environments. The conducted simulation experiments with fog showed that the proposed cloud/fog model can reduce the time delay, execution time, and energy consumption with good classiﬁcation accuracy which is up to 96%. These reduction values are 4%, 10%, and 94%, respectively, less than values by using cloud layer.
Keywords:	IoTs, Context reasoning, Waste management, Fog computing
Source:	Journal of Theoretical and Applied Information Technology 30^th September 2020 -- Vol. 98. No. 18 -- 2020
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Title:	USING MACHINE LEARNING TO SUPPORT STUDENTSâ€™ ACADEMIC DECISIONS
Author:	AISHA GHAZAL FATEH ALLAH
Abstract:	Making the right decision for students in higher education is vital, as it has a great influence on their study, career, life, and eventually, the whole society. Predicting the future performance of students can inform their choice of majors, concentrations, and courses. It also helps teachers and advisors provide the necessary support to students as needed. While many studies address the issue of predicting studentsâ€™ performance, they mainly predict student performance at only one particular stage of their study. For example, literature has papers on predicting studentâ€™s performance at enrollment, or in a particular course, which is not enough to help students throughout their study journey. This work addresses this gap in literature and proposes a holistic framework for assisting students in their decision throughout their entire study journey, and not only at one point of their study - as currently in literature. First, at enrollment, this work predicts a studentâ€™s GPA in different majors using enrollment data such as high school average, placement test results, and IELTS score. Second, after completing their first year, this work predicts studentâ€™s GPA in different concentrations using grades of Year-1 courses. Third, at any point of time after the student finishes some courses, a user-based collaborative filtering approach using K-Nearest Neighbor is used to predict a studentâ€™s grade in a future course. This approach uses other studentsâ€™ grades to make a prediction. Furthermore, this research tests and compares the performance of Decision Trees, Random Forests, Gradient-Boosted trees, and Deep Learning machine learning regression algorithms to predict student GPA. Gradient Boosted Trees performed the best when predicting studentâ€™s Major GPA, while Deep Learning performed the best for predicting Concentrationâ€™s GPA.
Keywords:	Machine Learning, Educational Data Mining, Decision Trees, Random Forests, Gradient-Boosted Trees, Deep Learning, Regression, Predicting Student GPA, Predicting Student Major GPA, Predicting Course Grade,
Source:	Journal of Theoretical and Applied Information Technology 30^th September 2020 -- Vol. 98. No. 18 -- 2020
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Title:	RESHAPING THE FINANCIAL SERVICES DELIVERY IN SAUDI ARABIA: THE ROLE OF BLOCKCHAIN TECHNOLOGY
Author:	BILAL AHMAD ALI Al-KHATEEB
Abstract:	In respond to the call by the subject matter of this book on management in a context of digital transformation with particular focus on the role of blockchain technology in effective financial services delivery in Saudi Arabia. This chapter examined reshaping the financial services delivery in Saudi Arabia with particular focus on the role of blockchain technology. The financial sector has in the past experience major changes due to the effect of technology and digital era. The new era is geared towards replacing the traditional financial methods in the delivery of financial services, where services are almost done manually. Due to traditional nature of financial methods, service delivery is therefore considered not effective enough to achieve the desire customer satisfactions. Therefore, a new technology has emerged to reshape the financial industry landscape drastically forcing the financial firms to transform and retain their financial stronghold. The study covered 39 employees of 8 banks in Riyadh district, Saudi Arabia through a cross-sectional survey research design with a quantitative survey questionnaire approach. An email survey procedure was employed to distribute and retrieve the copies of questionnaire distributed to the respondents. In all only 39 copies of questionnaire among those returned were usable. A SmartPls analysis technique that deals with reflective constructs was used to analyse the data collected whereby the finding among others revealed overall support on the relationship between blockchain technology and effective financial service delivery (p<0.001 with t value of 13.465). In other words, it shows that blockchain technology affects the financial service delivery, suggesting that effective service delivery in the banking industry is a function of blockchain technology. It draws a conclusion that blockchain technology enhances financial service delivery in the financial industry.
Keywords:	Blockchain technology, Financial service, Service delivery, Financial industry, Saudi Arabia.
Source:	Journal of Theoretical and Applied Information Technology 30^th September 2020 -- Vol. 98. No. 18 -- 2020
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Title:	IMPROVING CUSTOMER CLUSTERING BY OPTIMAL SELECTION OF CLUSTER CENTROIDS IN K-MEANS AND K-MEDOIDS ALGORITHMS
Author:	SHAHLA MOUSAVI , FARSAD ZAMANI BOROUJENI , SAEED ARYANMEHR
Abstract:	Clustering technique is one of the most important tools for knowledge discovery, during which the samples are divided into categories whose members are similar to each other. One of the most common and widely-used clustering solutions is partition-based clustering algorithms such as K-Means and K-Medoids which have attracted a lot of attention in the field of customer clustering. However, in these algorithms, the initial cluster centroids are usually randomly selected from the initial samples, making the final result of the clustering undesirable in most cases. In this research, a solution is proposed for the optimal selection of initial cluster centroids in K-Means algorithm. In the proposed method, the initial cluster centroids are selected based on a heuristic method to provide the input for the clustering algorithm. To evaluate the effectiveness of the proposed method, the K-Means, K-Medoids, and improved K-Means algorithms were tested on a real data set obtained from Central Insurance Company in Iran. According to standard evaluation criteria, the proposed method had a greater impact on improving clustering results than the other two methods.
Keywords:	Partition-Based Clustering, Customer Clustering, Selection of Cluster Centroid, K-Means, K-Medoids
Source:	Journal of Theoretical and Applied Information Technology 30^th September 2020 -- Vol. 98. No. 18 -- 2020
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Title:	CRITICAL FACTORS IN SELECTION OF OFFSHORE SOFTWARE MAINTENANCE OUTSOURCING VENDOR: A SYSTEMATIC LITERATURE REVIEW
Author:	ATIF IKRAM, MASITA ABDUL JALIL, AMIR BIN NGAH, AHMAD SALMAN KHAN
Abstract:	Offshore software maintenance outsourcing (OSMO) is a Global Software Engineering (GSE) paradigm for maintaining high-quality software at very low cost in low-paid countries. From high-paid countries, the client organization contracts out whole software or part of the software maintenance to low-paid countries intending to save money. The main objective of this study is to identify important factors for a client when deciding about the selection of suitable vendors for OSMO. The identification of these factors will make the decision-making process easier for a client to select an appropriate vendor. This paper not only identifies critical factors which are important for OSMO clients but also identifies elements of a process like roles, work product, method and tools in the OSMO context. These elements will help and guide us towards the decision-making process. The research method used to conduct this study is systematic literature review (SLR). The studies included in the SLR were published in the year 2006 to the year 2019. Out of 47 studies, 18 were concerned with the designed research questions. The SLR found 13 critical factors, 13 assessment activities, roles, guidelines, work products, and tools related to the questions. Client organizations can use this information in the decision-making process to select a suitable vendor for successful OSMO.
Keywords:	Offshore software, Maintenance outsourcing, Critical factors, Decision-Making, Systematic Literature Review, Vendor selection
Source:	Journal of Theoretical and Applied Information Technology 30^th September 2020 -- Vol. 98. No. 18 -- 2020
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Title:	INFORMATION SECURITY AWARENESS BEHAVIOR AMONG HIGHER EDUCATION STUDENTS: CASE STUDY
Author:	NAHIL ABDALLAH, ODEH ABDALLA, HAMZAH ALKHAZALEH, AMER IBRAHIM
Abstract:	The exchange of information is a key factor in the daily use of technology. Studies in computer security education, awareness-raising, and training among college students are limited. Most of the research focuses on computer security standards and guidance in organizational contexts. Few studies have analyzed the predictors of the adoption of computer security practices by college students. The objective of this research is to explore information security awareness among higher education students and exam key variables that are influencing this behavior. A total of 180 questionnaires were collected from undergraduate students at Aldar University College and analyzed using the Structural Equation Modelling (SEM) technique. The findings revealed that perceived usefulness, subjective norms, self-efficacy, and the quality of the security system are found to have an important effect on student behavioral awareness of security. The findings of this research will help to develop a clear understanding of the factors that affect studentsâ€™ security awareness behavior. The findings of the study can be used to either refute or strengthen the theories or framework that has been adopted. The findings might also contribute to the literature on security behavior and awareness in general. Findings suggest that the proposed research model is a valuable model for predicting students' attitudes towards information security and that their motivation is influenced by education in security awareness and understanding the severity of such issues. Moreover, the outcome of this research will lead to more awareness programs that can be used to promote privacy and security protection behaviors of information security.
Keywords:	Security Usefulness, Self-Efficacy, Subjective Norms, Security System Quality, Security Awareness.
Source:	Journal of Theoretical and Applied Information Technology 30^th September 2020 -- Vol. 98. No. 18 -- 2020
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Title:	IT FLEXIBILITY, CAPABILITIES AND IT-BUSINESS ALIGNMENT: DO ORGANIZATIONAL CHARACTERISTICS AND CONTEXT MATTER
Author:	DR. WALEED AFANDI
Abstract:	The relationship between IS flexibility, IT capability, and IT-Business alignment is well recognized in both theoretical and practitionerâ€™s literature. However, there is much less understanding upon what factors these relationships might be contingent. At the same time, there is growing evidence that both internal and external factors may be important and influential. Therefore, to enhance the existing IT-Business alignment research, this study presents and empirically tests a moderator framework of IS flexibility, IT capability, and IT-Business alignment. The influence of both endogenous (organizational size, strategic orientation) and exogenous (environmental uncertainty, industry environment) moderators is considered. The research confirmed the positive relationships between IT flexibility, IT capability, and IT-business alignment. System infrastructure, connectivity, and IT relationship to organizational tasks showed individual statistically significant influences. Environmental uncertainty and, to a lesser degree, firmâ€™s strategic orientation demonstrated significant moderating effects. Theoretical and practical implications of the findings are discussed
Keywords:	IT-Business Alignment, IT Flexibility, IT Capability, Environmental Uncertainty, Strategic Orientation
Source:	Journal of Theoretical and Applied Information Technology 30^th September 2020 -- Vol. 98. No. 18 -- 2020
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Title:	THAI EDU SEGMENTATION USING CLUE MARKERS AND SYNTACTIC INFORMATION FROM SHALLOW PARSER
Author:	AUTHAPON KONGWAN , SITI SAKIRA BINTI KAMARUDDIN , FARZANA BINTI KABIR AHMAD
Abstract:	Text is one of the useful knowledge sources of a human. Each element in a text has to be analyzed to identify the piece of information and knowledge. EDU is important for NLP applications that need a smaller unit to process rather than a sentence such as text summarization, information extraction, and question answering. Therefore, EDU can be more appropriated than a sentence to extract knowledge and information from the text. This paper presents a pipeline of the process for Thai EDU segmentation from word segmentation to EDU segmentation. The shallow parser is applied to chunk a non-recursive phrase in a text to reveal partial syntactic information for EDU segmentation. And then, syntactic information is utilized to identify and reconstruct the EDU segmentation in text. From the experiment, the results show that the precision, recall, and F1 score are 0.88865, 0.91577, and 0.90200 respectively.
Keywords:	Word Segmentation, EDU Segmentation, Conditional Random Field, Shallow Parser, Natural Language Processing
Source:	Journal of Theoretical and Applied Information Technology 30^th September 2020 -- Vol. 98. No. 18 -- 2020
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Title:	A NOVEL METHOD TO IDENTIFY HUMAN FINGERPRINTS
Author:	AHMAD SHARADQH
Abstract:	Human fingerprints unique signature among each person. Hence, the requirement for fingerprint identification among a different pattern of human fingers is a crucial security issue. Since fingerprint features are vary from one person to another, a detail of any person can be acquired by recognize the fingerprint features. These features are used as a key to retrieve any information connected to the human. This research proposal will argue the existing fingerprint method, extract fingerprints features and build a data base of the features. The performance issues will be calculated, and the identification process accuracy will be measured. A novel method of fingerprint feature extraction will be proposed, implemented and tested. The obtained experimental results will be compared with other methods results to prove the proposed method advantages.
Keywords:	Fingerprint, identifier, cluster, centroid, WCS, LBP, CSLBP.
Source:	Journal of Theoretical and Applied Information Technology 30^th September 2020 -- Vol. 98. No. 18 -- 2020
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Title:	ANALYSIS OF FLOW ENTRY REPLACEMENT ALGORITHMS IN INTELLIGENT NETWORKS
Author:	HYONGYOUNG KO, YEHOON JANG, NAMGI KIM
Abstract:	In recent years, as Internet services have diversified and grown rapidly, intelligent network environment has dynamically changed with parameters such as traffic patterns and network topologies. To flexibly manage such dynamic changes, SDN (Software Defined Network) technology has emerged. SDN enables more flexible Internet services by dividing the network architecture into a control plane and data plane. By the way, in the SDN, a problem with flow entry replacement may arise owing to flow table size restrictions within the switches. A flow entry replacement problem can increase the packet processing time and degrade the quality of service for the users. Therefore, we need to know exactly the performance of the flow entry replacement algorithms. In order to practically analyze the performance of the flow entry replacement algorithms, we first collect and analyze the actual Internet traffics of famous Internet services such as Instagram, Facebook, Youtube, and Netflex. Then, we analyze the performances of flow entry replacement algorithms by the collected traffic data. Based on the results, the LFU (Least Frequently Used) algorithm exhibits the worst performance, whereas the FIFO (First In First Out), LRU (Least Recently Used), and SFF (Short Flow First) algorithms show relatively better performances.
Keywords:	Intelligent Network, Internet traffic, SDN, Flow Entry Replacement, Flow Table Management
Source:	Journal of Theoretical and Applied Information Technology 30^th September 2020 -- Vol. 98. No. 18 -- 2020
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Title:	INTENTION TO USE ANALYSIS ON TWITTER AS A BANK CUSTOMER CARE IN JABODETABEK
Author:	HADITYA SETIAWAN, NILO LEGOWO
Abstract:	This study examines the interest of using Twitter as a consumer service media in local private banking companies. The purpose of this research is to find out the intention of using Twitter as a customer services media because Twitter considered as a good media for complain. This research is a quantitative study using DeLone & McLean, UTAUT dan TTF methodology that focuses on 3 local private banks which has verified status on their Twitter account and have customer data publications, which is BCA, Permata Bank and Panin Bank as research subjects. The results in this study concluded that the complaint itself is an individual's desire based on the customer services and is not influenced by the social environment. In addition, banking companies also need to build an image of "serving consumers closer" through better services so that customer are interested in making complaints and consulting through social media, especially Twitter.
Keywords:	Intention to Use, Media Sosial, Customer Services, DeLone & McLean, UTAUT.
Source:	Journal of Theoretical and Applied Information Technology 30^th September 2020 -- Vol. 98. No. 18 -- 2020
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Title:	BENCHMARKING OF CONVOLUTIONAL NEURAL NETWORKS FOR FACIAL EXPRESSIONS RECOGNITION
Author:	AHMED HESHAM MOSTAFA, HALA ABDEL-GALIL EL-SAYED, MOHAMED ABDEL-FATTAH BELAL
Abstract:	Facial Expression Recognition (FER) is one of the most interesting problems in computer science due to its potential applications in AI, many studies were proposed for the FER, but it based on traditional machine learning techniques and these techniques do not have the generalizability to classify expressions from unseen images or those that are captured from the wild, so it is still a diﬃcult and a complex problem. Recently, trends of research in various ﬁelds have begun to transfer to deep learning techniques, since it can learn and capture features automatically, robustness to natural variations in the data and generalizability. This work presents a comparative analysis of the popular convolutional neural network (CNN) models based on modular CNN architectures such as ResNet, DenseNet, MobileNet, NASNetMobile, Inception and Xception, applied on FER problem. The purpose of the paper is benchmarking the best architecture models, in order to help researchers to explore and investigate the best architectures for future research in FER based CNN models. For the comparative analysis multiple metrics were used such as Accuracy, Loss, precision, recall, number of parameters and model size, to conduct experiments facial expressions dataset was used from the AffectNet dataset with 287,651 images for training and 4000 images for validation represent eight facial expressions.
Keywords:	Convolutional Neural Network, Deep learning, Emotion Recognition, FER, Facial Expression Recognition
Source:	Journal of Theoretical and Applied Information Technology 30^th September 2020 -- Vol. 98. No. 18 -- 2020
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Title:	MALWARE ANALYSIS BASED ON SMART AGENTS AND IMAGE CLASSIFICATION
Author:	RODOLFO ROMERO-HERRERA, JUAN ANTONIO JIMÃ‰NEZ GARCÃA, VICTOR MANUEL SILVA GARCÃA
Abstract:	Windows-based systems and operating systems in general are significantly damaged, affecting infrastructures. At present, Malware analysis is performed in laboratories that use high costs and resources; so there are few methods of classification of Malware, based on artificial intelligence that consumes few resources. This article provides a system that was developed for the dynamic analysis of malware in Windows and classified using SIFT, SURF, and Bayesian networks. This involves the transformation of infected files into image files that allows the identification and classification of Malware. The samples of malicious software that allows generating a contingency plan were identified. The system was developed using intelligent agents. The analysis of Postal worm malware is presented as an example. When comparing with other malware detection and classification systems, it is observed that the multi-agent-based system is competitive.
Keywords:	Smart agent, classifier, malware, analysis, SIFT, SURF.
Source:	Journal of Theoretical and Applied Information Technology 30^th September 2020 -- Vol. 98. No. 18 -- 2020
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Title:	THE IMPACT OF ICT ON CORONAVIRUS CRISIS MANAGEMENT CASE STUDY: NATIONAL CENTER FOR SECURITY AND CRISES MANAGEMENT IN JORDAN
Author:	HISHAM ALABBADI, SULTAN AL-MASAEED
Abstract:	This research identifies the impact of the ICT dimensions (readiness of ICT infrastructure, human resource skills and knowledge, and financial capabilities) in managing the coronavirus crisis. A quantitative Likert-type questionnaire was administered to all workers in the upper and middle administrative levels who are involved in coronavirus crisis management at the National Center for Security and Crises Management in Jordan. The researchers adopted the descriptive analytical approach using SPSS version 19 for data analysis. The research results show a presence of a statistically significant effect of ICT in the management of the coronavirus crisis in addition to other interesting results about areas that need improvements and attention in crises management centers. Furthermore, the research suggested a number of recommendations that all crisis management centers can benefit from.
Keywords:	ICT, Coronavirus Crisis Management, National Center For Security And Crises Management, Covid-19, Jordan.
Source:	Journal of Theoretical and Applied Information Technology 30^th September 2020 -- Vol. 98. No. 18 -- 2020
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Title:	DEVELOPMENT AND TESTING OF AN ADVANCE SEISMIC MONITORING TO EVALUATE THE PERFORMANCE OF NEW MINI REGION IN THE ONAN GANJANG STATION
Author:	MARZUKI SINAMBELA, MARHAPOSAN SITUMORANG, KERISTA TARIGAN, SYAHRUL HUMAIDI
Abstract:	The new shelter of a mini region station in Onan Ganjang, North Sumatera had been deployed in October 2019 and had been operating in November 2019. The new shelter called ONSM station also includes a solar panel to power the batteries and freestanding communication module transmit real-time data via satellite or internet. The power of solar cell installation could be affected to communicate the waveform availability data at the new shelter. In this case, we design and testing the solar power system for a new mini region station at ONSM station. The result represented the ONSM station in November to December 2019 is unstable with 42.4 % and at beginning of January 2020 will be stable in 70.4 % after installation of the solar power system for the communication module to transmit waveform data. The probabilistic density function (PSDPDF) and data gaps analysis of ONSM station as a new mini region station helped determine seismic station performance and could be useful for the installation of the seismic mini region.
Keywords:	Solar Power System, New Mini Region Station, Waveform, PSDPDF, Performance
Source:	Journal of Theoretical and Applied Information Technology 30^th September 2020 -- Vol. 98. No. 18 -- 2020
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