Impact of Stress on Software Engineers Knowledge Sharing and Creativity (A Pakistani Perspective)

Software development involves technology as well as human efforts. Software engineering is supportive to create a quality of product by adopting the process of sharing knowledge. A lot of research was conducted on the technical side but human side of software development disregarded. Knowledge and creativity considered major factors for improving the software quality. Currently professionals working in the field of software engineering are under impressive pressure which cause stress for the Software engineers. It is highly desirable to conduct an empirical study on impact of stress on software engineers knowledge sharing & creativity. The major motivation for this study is to investigate the impact of job stress factors which can affect the software engineering knowledge sharing capabilities and creativity. The research is based on industrial assessment. For conducting this study we developed a questionnaire based on Stress Factors. Statistical analyses are performed through SPSS tool. On the basis of the results from the survey, we proposed some strategies for those factors that have high impact on software engineers and try to mitigate their affect. These results highlight stress factors and their impact on software engineers knowledge sharing and creativity, working in Pakistani software industry

Impact of Stress on Software Engineers Knowledge Sharing and Creativity (A Pakistani Perspective)

Software development involves technology as well as human efforts. Software engineering is supportive to create a quality of product by adopting the process of sharing knowledge. A lot of research was conducted on the technical side but human side of software development disregarded. Knowledge and creativity considered major factors for improving the software quality. Currently professionals working in the field of software engineering are under impressive pressure which cause stress for the Software engineers. It is highly desirable to conduct an empirical study on impact of stress on software engineers knowledge sharing & creativity. The major motivation for this study is to investigate the impact of job stress factors which can affect the software engineering knowledge sharing capabilities and creativity. The research is based on industrial assessment. For conducting this study we developed a questionnaire based on Stress Factors. Statistical analyses are performed through SPSS tool. On the basis of the results from the survey, we proposed some strategies for those factors that have high impact on software engineers and try to mitigate their affect. These results highlight stress factors and their impact on software engineers knowledge sharing and creativity, working in Pakistani software industry

Research Article Software Component Selection Based on Quality Criteria Using the Analytic Network Process

Component based software development (CBSD) endeavors to deliver cost-effective and quality software systems through the selection and integration of commercially available software components. CBSD emphasizes the design and development of software systems using preexisting components. Software component reusability is an indispensable part of component based software development life cycle (CBSDLC),which consumes a significant amount of organization’s resources, that is, time and effort. It is convenient in component based software system (CBSS) to select the most suitable and appropriate software components that provide all the required functionalities. Selecting the most appropriate components is crucial for the success of the entire system. However, decisions regarding software component reusability are often made in an ad hoc manner, which ultimately results in schedule delay and lowers the entire quality system. In this paper, we have discussed the analytic network process (ANP) method for software component selection. The methodology is explained and assessed using a real life case study

The Encyclopedia of Neutrosophic Researchers - vol. 1

This is the first volume of the Encyclopedia of Neutrosophic Researchers, edited from materials offered by the authors who responded to the editor’s invitation. The authors are listed alphabetically. The introduction contains a short history of neutrosophics, together with links to the main papers and books. Neutrosophic set, neutrosophic logic, neutrosophic probability, neutrosophic statistics, neutrosophic measure, neutrosophic precalculus, neutrosophic calculus and so on are gaining significant attention in solving many real life problems that involve uncertainty, impreciseness, vagueness, incompleteness, inconsistent, and indeterminacy. In the past years the fields of neutrosophics have been extended and applied in various fields, such as: artificial intelligence, data mining, soft computing, decision making in incomplete / indeterminate / inconsistent information systems, image processing, computational modelling, robotics, medical diagnosis, biomedical engineering, investment problems, economic forecasting, social science, humanistic and practical achievements

De-terminants of entreprneurial career: Experience of polytechnic students

Purpose- This study focuses on the factors influencing students’ choice of selecting entrepreneurship as their career after graduation. The paper aims to gain more understanding of how personality traits, entrepreneurship knowledge-experience and current economic environment affect entrepre-neurial career among polytechnic students in Malaysia. Design/methodology/approach- A theoretical framework based on a literature review is developed. Empirical results were derived from a quantitative approach based on survey method and a cross sectional study. Hypothesis testing were executed where multiple regression analysis utilized to verify the direct relationship between independent variables and dependent variables. Findings- Personality traits and favorable economic environment were proven important in explain-ing students intention to choose entrepreneurial career as their career choice after they graduated from study. Research Implications- The results shall aid polytechnics management in formulating their curricu-lum and programs that fit students’ priorities that they shall choose their future undertaking as an entrepreneur. Malaysian public policy regarding higher education should consider some changes required in higher learning institutions in the country. Annual budget and higher learning institutions entrepreneurship programs shall be revised accordingly after considering the results of the study. Originality/value- Entrepreneurial intention inquiries in Malaysian institutions have been very limited and an established framework need more serious efforts. This study contributes to entrepreneu-rial intention body of knowledge. Research Paper Reference to this paper should be made as follows: Awang, A., Ibrahim, I. I., Ayub, S. A.(2014). ―De-terminants of entreprneurial career: Experience of polytechnic students‖, Journal of Entrepreneur-ship, Business and Economics, Vol. 2, No. 1, pp. 21–40

Manipify: An Automated Framework for Detecting Manipulators in Twitter Trends

The rapid adoption of online social media platforms has transformed the way of communication and interaction. On these platforms, discussions in the form of trending topics provide a glimpse of events happening around the world in real-time. Also, these trends are used for political campaigns, public awareness, and brand promotions. Consequently, these trends are sensitive to manipulation by malicious users who aim to mislead the mass audience. In this article, we identify and study the characteristics of users involved in the manipulation of Twitter trends in Pakistan. We propose “Manipify”—a framework for automatic detection and analysis of malicious users in Twitter trends. Our framework consists of three distinct modules: (1) user classifier, (2) hashtag classifier, and (3) trend analyzer. The user classifier module introduces a novel approach to automatically detect manipulators using tweet content and user behaviour features. Also, the module classifies human and bot users. Next, the hashtag classifier categorizes trending hashtags into six categories assisting in examining manipulators behaviour across different categories. Finally, the trend analyzer module examines users, hashtags, and tweets for hashtag reach, linguistic features, and user behaviour. Our user classifier module achieves 0.92 and 0.98 accuracy in classifying manipulators and bots, respectively. We further test Manipify on the dataset comprising 652 trending hashtags with 5.4 million tweets and 1.9 million users. The analysis of trends reveals that the trending panel is mostly dominated by political hashtags. In addition, our results show a higher contribution of human accounts in trend manipulation as compared to bots

Role of images on World Wide Web readability

As the Internet and World Wide Web have grown, many good things have come. If you have access to a computer, you can find a lot of information quickly and easily. Electronic devices can store and retrieve vast amounts of data in seconds. You no longer have to leave your house to get products and services you could only get in person. Documents can be changed from English to Urdu or from text to speech almost instantly, making it easy for people from different cultures and with different abilities to talk to each other. As technology improves, web developers and website visitors want more animation, colour, and technology. As computers get faster at processing images and other graphics, web developers use them more and more. Users who can see colour, pictures, animation, and images can help understand and read the Web and improve the Web experience. People who have trouble reading or whose first language is not used on the website can also benefit from using pictures. But not all images help people understand and read the text they go with. For example, images just for decoration or picked by the people who made the website should not be used. Also, different factors could affect how easy it is to read graphical content, such as a low image resolution, a bad aspect ratio, a bad colour combination in the image itself, a small font size, etc., and the WCAG gave different rules for each of these problems. The rules suggest using alternative text, the right combination of colours, low contrast, and a higher resolution. But one of the biggest problems is that images that don't go with the text on a web page can make it hard to read the text. On the other hand, relevant pictures could make the page easier to read. A method has been suggested to figure out how relevant the images on websites are from the point of view of web readability. This method combines different ways to get information from images by using Cloud Vision API and Optical Character Recognition (OCR), and reading text from websites to find relevancy between them. Techniques for preprocessing data have been used on the information that has been extracted. Natural Language Processing (NLP) technique has been used to determine what images and text on a web page have to do with each other. This tool looks at fifty educational websites' pictures and assesses their relevance. Results show that images that have nothing to do with the page's content and images that aren't very good cause lower relevancy scores. A user study was done to evaluate the hypothesis that the relevant images could enhance web readability based on two evaluations: the evaluation of the 1024 end users of the page and the heuristic evaluation, which was done by 32 experts in accessibility. The user study was done with questions about what the user knows, how they feel, and what they can do. The results back up the idea that images that are relevant to the page make it easier to read. This method will help web designers make pages easier to read by looking at only the essential parts of a page and not relying on their judgment.Programa de Doctorado en Ciencia y Tecnología Informática por la Universidad Carlos III de MadridPresidente: José Luis Lépez Cuadrado.- Secretario: Divakar Yadav.- Vocal: Arti Jai

Upset or Collapse Detection System for ASD Children Using Smart Watch with Machine Learning Algorithm

ASD is characterised by severe and violent behavioural issues that are referred to as "meltdowns (upset) or tantrums (collapse)" and can include aggression, hyperactivity, intolerance, unpredictability and self-injury. This research work intends to develop and implement a non-invasive real-time Upset or Collapse Detection System (UCDS) for people with ASD. With a certain model of smart watch, the non-invasive biological indications such as Pulse Rate (PR), Skin Temperature (ST), and Galvanic Skin Reaction (GSR) can be artificially captured.  In order to create the UCDS, deep learning algorithms like CNN, LSTM, and the hybrid of CNN-LSTM are given the physiological signals that are captured to a server. The deep learning algorithm could recognise aberrant upset or collapse states from real-time physiological signs after being trained.  Deep learning algorithms including CNN, LSTM, and CNN-LSTM are used to train and test the proposed UCDS system, and it is discovered that hybrid CNN-LSTM beat them all with an average training and testing accuracy of 96% and a low mean absolute error (MAE) of 0.10 for training and 0.04 for testing.  Furthermore, the suggested UCDS system is supported by 93% of the ASD caretakers