A study on computer viruses attacks and the way to cure them / Shukor Sanim Mohd Fauzi

Many organizations and users are working hard to secure themselves from the growing threats of computer viruses, Trojan horses, worms, and other malicious codes. Computer viruses attacks are problems created by men or women and they are problems that can also be controlled by men or women. In the end, it is basically a war between virus writers and virus fighters. There are bright minds on both sides, and it looks like this fight is not going to end. This research intends to find the pattern of computer viruses attacks and perform a prediction on the next occurrence of virus. Other than that, this research also will propose a new way to cure from computer viruses attacks. The findings of this research are hope be able to shed some light for all of us

The impact of pair programming on students logical thinking : a case study on higher academic institution / Mahfudzah Othman … [et al.]

Pair Programming (PP) is a well-known agile software development technique that has been widely implemented in programming classes. Through PP, students are able to share knowledge and expertise that will contribute to better programming solutions. Nevertheless, how PP can help to improve students’ cognitive abilities has yet to be explored. Therefore, this study’s aim was to investigate the impacts of implementing Pair Programming (PP) on students’ logical thinking. Logical thinking is part of the cognitive ability claimed to be one of the crucial factors that determine the success or failure of novice programmers. To achieve this, 60 students who enrolled in Diploma in Computer Science programme in Universiti Teknologi MARA Perlis Branch, Malaysia, were asked to take the pre-test and post-test of Group Assessment Logical Thinking (GALT) Test in the beginning and at the end of the semester. These students were divided into two main groups; Control and Test in the Test Group, students with low logical ability will be paired with their high logical thinking friends. Meanwhile, in the Control Group, no pair programming or collaborative technique took place. Five programming tasks were assigned to both groups to solve either collaboratively or individually. The results obtained via paired sample t-tests statistical analysis shows significant improvements in students’ logical thinking with p-value <0.05 in the Test Grou

Hierarchical Fuzzy Systems: Interpretability and Complexity

Hierarchical fuzzy systems (HFSs) have been regarded as a useful solution for overcoming the major issues in fuzzy logic systems (FLSs), i.e., rule explosion due to the increase in the number of input variables. In HFS, the standard FLS are reformed into a low-dimensional FLS subsystem network. Moreover, the rules in HFS usually have antecedents with fewer variables than the rules in standard FLS with equivalent functions, because the number of input variables in each subsystem is less. Consequently, HFSs manage to decrease rule explosion, which minimises complexity and improves model interpretability. Nevertheless, the issues related to the question of “Does the complexity reduction of HFSs that have multiple subsystems, layers and different topologies really improve their interpretability?” are not clear and persist. In this paper, a comparison focusing on interpretability and complexity is made between two HFS’ topologies: parallel and serial. A detailed measurement of the interpretability and complexity with different configurations for both topologies is provided. This comparative study aims to examine the correlation between interpretability and complexity in HFS

Designing an IoT-based System to Detect the Out-of-pitch Balls in a Football Match

The incorrect decision making that referee made during a football match is becoming unsatisfied game or biased game. The problem of how a decision made by the referee when coming to an error in football had been issues that being debate. The player or fans did not seem satisfied when referee decide such as a goal or no goal, penalty or no penalty, direct red card, and mistaken identity. Hence, there must be a plan to tackle the problem by using technology, especially in this era. Therefore, as an initial approach, this paper is focusing on developing a design for the ball out detection using the assistants of the IoT (Internet of Things). Correctly, the IoT approach was used for detecting the ball out of play, i.e. from a football match. Note that this proposed design was built based on data obtained from a survey questionnaire conducted with the experts in football and fans of football regarding the ball out of play system. The evaluation of the proposed design suggested that the proposed design promising to improve the decision-making made in the football match.  It is hoped that the study can contribute to the improvement of overall decision making by the referee when coming to ball out or other error that player made

Adaptation of .NET MVC Framework in Developing an Agriculture Sources Inventory System

A viable inventory management system is crucial to an organization, especially those who deals with stock going in and out of their premise. The system should cover several aspects in managing the collection of the available stocks to ensure an efficiency. An inventory management system comprises crucial functions that the goal is to produce accurate information – a minor mis-information could lead to a wrong decision making. Improper system design could lead to the problem; thus, the design of this inventory system is supported by .NET Model View Controller (MVC) Framework as its backbone. The .NET MVC Framework is one of the most widely used framework that is written in C# programming language. By utilizing the MVC Framework, its three main components; data model (Model), user interface (View), and business logic (Controller) can be managed separately without affecting the entire system. Thus, the risk of the system functions to produce inaccurate information is reduced significantly. Moreover, MVC also supports scalability, extend-ability and maintainability which is a very important aspect for an information system with growing needs of new functions

Utilising Target Adjacency Information for Multi-target Prediction

In this paper, we explored how information on the cost of misprediction can be used to train supervised learners for multi-target prediction (MTP). In particular, our work uses depression, anxiety and stress severity level prediction as the case study. MTP describes proposals which results require the concurrent prediction of multiple targets. There is an increasing number of practical applications that involve MTP. They include global weather forecasting, social network users’ interaction and the thriving of different species in a single habitat. Recent work in MTP suggests the utilization of “side information” to improve prediction performance. Side information has been used in other areas, such as recommender systems, information retrieval and computer vision. Existing side information includes matrices, rules, feature representations, etc. In this work, we review very recent work on MTP with side information and propose the use of knowledge on the cost of incorrect prediction as side information. We apply this notion in predicting depression, anxiety and stress of 270,322 anonymous respondents to the DASS-21 psychometric scale in Malaysia. Predicting depression, anxiety and stress based on the DASS-21 fit an MTP problem. Often, a patient experiences anxiety as well as depression at the same time. This is not unusual since it has been discovered that both tend to co-exist at different degrees depending on a patient’s experience. By using existing machine learning algorithms to predict the severity levels of each category (i.e., depression, anxiety and stress), the result shows improved precision with the use of cost matrix as side information in MTP

Towards Designing A Hierarchical Fuzzy System for Early Diagnosis of Heart Disease

Heart disease may represent a range of conditions that affect our heart. Disease under heart diseases umbrella include coronary heart disease, heart attack, congestive heart failure, and congenital heart disease, is the leading cause of death. Mor eover, heart disease not only attacks the elderly. In the present day, lots of younger people might be getting affected by the number of heart diseases. In order to decrease the mortality rate caused by heart disease, it is necessary for the disease, to be diagnosed at an early stage. In this paper, we have proposed the use of hierarchical fuzzy systems (HFSs) for early diagnosis of heart disease. However, to design the HFSs is challenging, especially for the complex system. Therefore, in this paper, we foc us on designing a hierarchical fuzzy system to handle the complex medical application. The designed HFS consists of six key main steps implemented on heart disease. The input variables of heart disease includes shortness of breath, discomfort, pressure, he aviness, or pain in the chest, arm, or below the breastbone, fatigue, nausea, difficulties in climbing stairs, swelling in ankles, difficulty to sleep at night, irregular heartbeats, fullness, sweating, take frequent break during the day, dizzy and depress ed. Additionally, the output of heart disease is to classify whether the patient is healthy or suspecting with heart disease. The study contributes to providing insight into a way of designing the HFSs, particularly for the complex medical application

Mathematical Sciences, Universiti

Abstract—Many companies use Global Software Development (GSD) to access skilled people, reduce costs and utilize around the clock development. GSD has numerous social and technical difficulties, but most literature only examines social difficulties. Few studies concern technical difficulties or address Software Configuration Management (SCM) issues. SCM is widely used, and supports the infrastructure and practices that enable change management and version control. SCM has potential to support more effective GSD, but is more difficult in GSD, because coordination and synchronization are more complex. This paper presents our findings of a systematic mapping study of SCM in GSD. Systematic mapping is a methodology to discover and categorize all research on a topic, and can be used to identify common themes and areas requiring further study. We find most research on SCM in GSD has used case studies, and there has been little empirical validation. The lack of coordination and group awareness causes difficulties for SCM in GSD, but no SCM process has been proposed to address this. More research is required on Software Configuration Control for GSD. Keywords–Global Software Development, Softwar

Developer coordination in software engineering projects

Software development has evolved to become more complex and distributed. This highlights the importance of coordination between developers, which is known to impact development performance. Measuring developer coordination is complex but being able to understand its role in software engineering projects requires an accepted way of measuring it. One approach used to conceptualize and measure coordination is known as ‘Socio-Technical Congruence’ (STC), developed by Cataldo et al. (2006), which is the fit between required coordination and actual coordination measured as the proportion of actual coordination activities that occurred relative to the number of coordination activities that should have taken place (that is, required coordination). Research to-date suggests that STC is a useful predictor of development task performance in software projects. However, STC is relatively new and has been empirically evaluated in only limited software engineering contexts. Also, it has focused on explicit developer coordination. Coordination also happens implicitly and other project contexts may yield additional insights. Therefore, the opportunity and need exists to further investigate STC as a measure of developer coordination in software engineering projects.Consequently, the aims of this dissertation are threefold: 1) to validate the use of STC as a measure of explicit coordination to predict task performance in a contrasting project setting and test out its boundaries; 2) to re-examine developer coordination in the literature, focusing on group awareness as an explicit and implicit coordination mechanism for overcoming challenges of complexity and distribution in software development projects; and, based on this re-examination, 3) to extend and validate the application of STC to measure implicit developer coordination as well as explicit coordination.The first aim was fulfilled by performing a differentiated replication study of Cataldo et al.’s (2006) seminal research to investigate STC in new software engineering contexts, namely in eight open source development projects of different sizes (the original study used a single large in-house commercial project). In contrast to the original study, findings from this research indicated that STC is only effective as a measure of explicit developer coordination in large projects (that is, projects with 50 or more developers). Results for projects smaller than 50 developers showed variable, mostly non-significant results. This unexpected finding is discussed and explained, based on the nature of coordination in different sized groups.The second aim was fulfilled by exploring developer coordination and the role of group awareness in facilitating coordination in the literature. Following an initial overview of prior research on developer coordination, two Systematic Literature Review (SLR) studies were conducted. The first SLR was used to identify coordination issues and causes of coordination difficulty in software engineering projects, particularly in software engineering projects. A key finding of this study related to the role of group awareness in coordination in software engineering projects. Group awareness helps development team members to coordinate explicitly and implicitly. A second SLR study was then conducted to investigate further the role of group awareness as a coordination mechanism. A key finding from this study was that group awareness arises primarily through familiarity of group tasks, group members and the group work context. Together, these studies provided strong theoretical support for using implicit coordination in calculating STC as a measure of development task performance.Finally, the third aim was fulfilled by empirically re-examining the eight open source projects using a measure of implicit developer coordination for STC, motivated by group awareness (in contrast to the explicit coordination measure used in the replication study, following the original study). The study found support for STC as a measure of implicit coordination, not only in the large projects but the small ones as well. In extending application of the STC measure of developer coordination, the results highlight the important role of explicit and implicit coordination as a predictor of task performance and suggest that the relevance of STC may be broader when applied to implicit coordination.This dissertation contributes to the body of knowledge on developer coordination in software engineering. First, it validates and qualifies the use of explicit coordination-based STC as a predictor of development task performance in a replication study in a contrasting setting. Second, it synthesizes current knowledge on coordination challenges and response strategies, and the role of explicit and implicit group awareness as a coordination mechanism in group work contexts. Third, it validates the use of an implicit coordination-based measure of STC as a predictor of development task performance in the same contrasting setting and clarifies the boundaries of STC’s use in projects of different sizes. The studies find that STC is effective as a measure of explicit developer coordination only in large projects, where project complexity makes explicit coordination more relevant