A Study on Reuse-based Requirements Engineering by Utilizing Knowledge Pattern

Software development has become an essential part of many industries over the past decade. The use of software has become an essential element for the organization to support its operation and business. Some software has certain features in common, which allow its requirements to be used repetitively in the requirement engineering phase. This paper presents a study on knowledge patterns for reuse-based requirements engineering. Reuse-based requirements engineering is saving the effort to conduct the process and, at the same time maintaining the standard since reused requirements come with its properties as well.  Software development is an iterative process itself and so does the knowledge it holds in every iteration. When analysts perform many iterations of elicitation processes, it is often the case that a significant amount of requirements is recurring and similar software system will likely benefit from them. This research adopted a literature review method to investigate and to present current studies on knowledge pattern for the purpose of reuse. Knowledge reuse by utilizing knowledge pattern is becoming a significant method in software requirements engineering as it safes the effort of developing requirements from scratch. The study found that a specific pattern is required to develop good requirements specification. A proposed prototype to deploy reuse-based requirements engineering is also presented and evaluated. Experts’ judgment method is used for evaluation by adapting the Technology Acceptance Model (TAM). The results showed that reusing knowledge pattern expedites the requirements elicitation process and improves the requirements quality.

Privacy, Ethics, And Security On Social Media: An Islamic Overview

Privacy is one of the most critical fields in recent years since the presence of social media that is increasingly eroding the fundamental human right to privacy. This phenomenon raises many people's concerns about the future o privacy. Commonly discussed by many people are privacy, ethics, and security, including the extent to which they are being taken seriously by designers and users social media. The discussion is not only from the perspective of western culture but also from the religious point of view. The purposes ot this paper is to investigate the privacy, ethics, and security concerns in social media from an Islamic overview. Towards this, we begin by introducing the Qur'an and Sunnah as the life guidelines for humanity. We then highlight the mention of privacy, ethics, and security in both these guidelines. Then we explain it in sequence in each section accompanied by the existing problems in social media. Finally, we discuss the future of privacy in social media

Survey On Nudity Detection: Opportunities And Challenges Based On ‘Awrah Concept In Islamic Shari’a

The nudity or nakedness which known as awrah in Islam is part of the human body which in principle should not be seen by other people except those qualified to be her or his mahram or in an emergency or urgent need.Nudity detection technique has long been receiving a lot of attention by researchers worldwide due to its importance particularly to the global Muslim community. In this paper, the techniques were separated into four classifications namely methods based on body structure, image retrieval, the features of skin region, and bag-of-visual-words (BoVW). All of these techniques are applicable to some areas of skin on the body as well as on the sexual organs that should be visible to determine nude or not. While the concept of nakedness in Islamic Shari'a has different rules between men and women, such as the limit of male ‘awrah is between the navel and the knees, while the limit of female ‘awrah is the entire body except the face and hands which should be closed using the hijab. In general, existing techniques can be used to detect nakedness concerned bythe Islamic Shari'a. The selection ofhese techniques are employed based on the areas of skin on the body as well as or the sexual organs to indicate whether it falls to thenude category or not. While in Islamic Shari'a, different 'awrah rules are required for men and women such as the limit 'awrah, the requirements of clothes as cover awrah, and kinds of shapes and shades of Hijabs in various countries (for women only). These problems are the opportunities and challenges for the researcher to propose an ‘awrah detection technique in accordance with the Islamic Shari'a

Shopping Assistant App For People With Visual Impairment: An Acceptance Evaluation

Visual impairment refers to when someone lose part or all of the ability to see. People with visual impairment has many limitations including the freedom of doing grocery shopping independently. They will have difficulty to read ingredients or dietary information which usually returned in small font letters on the products. This information is deemed important to make informed decision in order to purchase products. Therefore, this research is conducted to investigate the need of grocery shopping assistant app for people with visual impairment and their acceptance level. An empirical investigation method is adapted and data was collected based on Technology Acceptance Model (TAM). The evaluation results indicate that the people with visual impairment positively inclined towards utilizing shopping assistant app caused by the technology is easy to use and therefore they can obtain benefit from the app, concluding that Perceived Ease of Use is a better indicator for the attitude towards using the shopping assistant app

Shopping Assistant App For People With Visual Impairment: An Acceptance Evaluation

Visual impairment refers to when someone lose part or all of the ability to see. People with visual impairment has many limitations including the freedom of doing grocery shopping independently. They will have difficulty to read ingredients or dietary information which usually returned in small font letters on the products. This information is deemed important to make informed decision in order to purchase products. Therefore, this research is conducted to investigate the need of grocery shopping assistant app for people with visual impairment and their acceptance level. An empirical investigation method is adapted and data was collected based on Technology Acceptance Model (TAM). The evaluation results indicate that the people with visual impairment positively inclined towards utilizing shopping assistant app caused by the technology is easy to use and therefore they can obtain benefit from the app, concluding that Perceived Ease of Use is a better indicator for the attitude towards using the shopping assistant app

Exam timetabling using graph colouring approach

Timetabling at large covering many different types of problems which have their own unique characteristics. In education, the three most common academic timetabling problems are school timetable, university timetable and exam timetable. Exam timetable is crucial but difficult to be done manually due to the complexity of the problem. The main problem includes dual academic calendar, increasing student enrolments and limitations of resources. This study presents a solution method for exam timetable problem in centre for foundation studies and extension education (FOSEE), Multimedia University, Malaysia. The method of solution is a heuristic approach that include graph colouring, cluster heuristic and sequential heuristic

STATISTICS WITH SPSS FOR RESEARCH

This book consists of five chapters: Correlation, Regression, t – Test, ANOVA and Crosstabs Procedure with worked examples and review exercises. For the purpose of helping students to master the skills of this subject, step by step easy approach has been designed and adopted by the authors of this book. This is deemed as the best approach when the design of the content is structured and well-organized. Furthermore, a large part of the syllabus involves the mastery of manual mathematical calculation and step by step, direct instruction is the best approach in order to obtain an answer. In addition, for students who are not so good in math-logic reasoning and dealing with numbers, this method may enable them a sure way of obtaining the correct answer by following a set of given guidelines. Assessment is the process of evaluating the extent to which students have developed their knowledge, understanding and abilities. It involves determining what does the student know, understand, and can do with the knowledge gained from the lessons. For the purpose of evaluating whether the students have achieved the objectives of the chapters, exercises in form of assessments based on theory was used. In order to maximize the student’s learning capability, the authors took effort in providing extra exercises that cover the manual calculation and SPSS calculation for all different chapters. The Step by Step Leaning SPSS would also work as a good guide book that enhance the level of understanding of the concepts and enable students to execute the appropriate steps in coming up with the correct interpretation

An Intelligent Crisis-Mapping Framework For Flood Prediction

This paper proposes a new framework for crisis-mapping with flood prediction model based on the crowdsourcing data. Crisis-mapping is still at infancy stage development and offers opportunities for exploration. In fact, the application of the crisis-mapping gives fast information delivery and continuous updates for crisis and emergency evacuation using sensors. However, current crisis-mapping is more to the information dissemination of flood-related information and lack of flood prediction capability. Therefore, this paper applied artificial neural network for flood prediction model in the proposed framework. Sensor data from the crowdsourcing platform can be used to predict the flood-related measures to support continuous flood monitoring. In addition, the proposed framework makes used of the unstructured data from the Twitters to support the flood warnings dissemination to locate flood area with no sensor installation. Based on the results of the experiment, the fitted model from the optimization process gives 90.9% of accuracy performance. The significance of this study is that we provide a new alternative in flood warnings dissemination that can be used to predict and visualized the flood occurrence. This prediction is significant to agencies and authorities to identify the flood risk before its occurrence and crisis-maps can be used as an analytics tool for future city planning

An improved LSTM technique using three-point moving gradient for stock price forecasting

Everybody desires to see the future. The understanding of the time ahead can create enormous prospects, clout and fortune. For soothsayers who can predict the future financial developments, they are be able to command immense fortune. Therefore, predicting the financial stock market is always a great attraction with financiers and opportunists. Massive finance and equipment have been devoted into exploring the stock prices movements, hoping of realizing the best method to hit paydirt in this endervour. Analysts utilize numerous methodologies as well as employ a variety of hypotheses to solve this artful task, but not any has accomplished with a satisfactory margin of errors. The need to make informed choices causes correct and accurate information to be a desired and highly valued commodity. One encouraging Artificial Intelligence technique is the Long Short-Term Memory (LSTM) technique. Although LSTM is excellent in recognizing patterns, it places no considerable importance to the intense relationship that connects the past and its ensuing values within a time series. It does not take into account the association between the past and the later values. This research offers an optional LSTM method which contemplates the past, current and subsequent prices by predicting the Three-Point Moving Gradient of the stock market prices. The precise forecast price can be calculated with adequate accuracy by employing reversed Linear Regression (LR) and its mean price. The results is just as precise as the conventional LSTM method

Application of multi-step time series prediction for industrial equipment prognostic

The use of prognostics is critically to be implemented in industrial. This paper presents an application of multi-step time series prediction to support industrial equipment prognostic. An artificial neural network technique with sliding window is considered for the multi-step prediction which is able to predict the series of future equipment condition. The structure of prognostic application is presented. The feasibility of this prediction application was demonstrated by applying real condition monitoring data of industrial equipment