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Survey on <i>Essential and Accidental Real-Time Issues</i>in Software Engineering

Journal of Software Engineering and Applications 2017年第3期10卷 245-256页

作者： Furrakh Shahzad dr. maruf pasha dr. Urooj pasha Bushra Majeed Khurram Shahzad Department of Computer Science Pakistan Institute of Engineering and Technology Multan Pakistan Department of Information Technology Bahauddin Zakariya University Multan Pakistan Institute of Management Sciences Bahauddin Zakariya University Multan Pakistan

Software product lines have recently been presented as one of the best promis-ing improvements for the efficient software development. Different research works contribute supportive parameters and negotiations regarding the prob-lems of producing a perfect software scheme. Traditional approaches or recy-cling software are not effective to solve the problems concerning software competence. Since fast developments with software engineering in the past few years, studies show that some approaches are getting extensive attention in both industries and universities. This method is categorized as the software product line improvement;that supports reusing of software in big organizations. Different industries are adopting product lines to enhance efficiency and reduce operational expenses by way of emerging product developments. This research paper is formed to offer in-depth study regarding the software engineering issues such as complexity, conformity, changeability, invisibility, time constraints, budget constraints, and security. We have conducted various research surveys by visiting different professional software development organizations and took feedback from the professional software engineers to analyze the real-time problems that they are facing during the development process of software systems. Survey results proved that complexity is a most occurring issue that most software developers face while developing software applications. Moreover, invisibility is the problem that rarely happens according to the survey.

关键词： Software Engineering Issues Real-Time Software Development Problems Unexpected Issues of S.E

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Survey of Machine Learning Algorithms for Disease Diagnostic

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Journal of Intelligent Learning Systems and Applications 2017年第1期9卷 1-16页

作者： Meherwar Fatima maruf pasha Institute of CS & IT The Women University Multan Multan Pakistan Department of Information Technology Bahauddin Zakariya University Multan Pakistan

In medical imaging, Computer Aided Diagnosis (CAD) is a rapidly growing dynamic area of research. In recent years, significant attempts are made for the enhancement of computer aided diagnosis applications because errors in medical diagnostic systems can result in seriously misleading medical treatments. Machine learning is important in Computer Aided Diagnosis. After using an easy equation, objects such as organs may not be indicated accurately. So, pattern recognition fundamentally involves learning from examples. In the field of bio-medical, pattern recognition and machine learning promise the improved accuracy of perception and diagnosis of disease. They also promote the objectivity of decision-making process. For the analysis of high-dimensional and multimodal bio-medical data, machine learning offers a worthy approach for making classy and automatic algorithms. This survey paper provides the comparative analysis of different machine learning algorithms for diagnosis of different diseases such as heart disease, diabetes disease, liver disease, dengue disease and hepatitis disease. It brings attention towards the suite of machine learning algorithms and tools that are used for the analysis of diseases and decision-making process accordingly.

关键词： Machine Learning Artificial Intelligence Machine Learning Techniques

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