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25th International Arab Conference on Information Technology, ACIT 2024

作者： Alsalem, Gheed M. Sarhan, Noor Hammad, Mustafa Zawaideh, Bayan University of Jordan Counseling and Special Education Department Amman Jordan University of Bahrain Department of Computer Science Sakheer Bahrain Mutah University Department of Software Engineering Alkarak Jordan Luminus Technical College University Foundation and Support Programs Amman Jordan

ISBN: (纸本)9798331540012

This paper presents students' performance prediction model based on Machine Learning (ML) classifiers. The used dataset provides three groups of features that may affect students' performance. Features selection approaches have been applied to the dataset. Several well-known ML classifiers including Neural Network (ANN), Bayes Network (Bayes Net), and Decision Tree (DT). Along with the original approach, hyper approach is applied using boosting, bagging, and voting classifiers. The performance of these algorithms is examined and compared using a confusion matrix. Results show that behavioral features have a major impact on students' performance and ML algorithms can be used effectively to build students' performance prediction model. © 2024 IEEE.

关键词： Prediction models

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Predicting Students’ Performance using Machine Learning Classifiers

Predicting Students’ Performance using Machine Learning Cla...

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Information Technology (ACIT)

作者： Gheed M. Alsalem Noor Sarhan Mustafa Hammad Bayan Zawaideh Counseling and Special Education Department University of Jordan Amman Jordan Department of Computer Science University of Bahrain Sakheer Bahrain Department of Software Engineering Mutah University Alkarak Jordan Foundation and Support Programs Luminus Technical College University Amman Jordan

ISBN: (数字)9798331540012

ISBN: (纸本)9798331540029

This paper presents students’ performance prediction model based on Machine Learning (ML) classifiers. The used dataset provides three groups of features that may affect students’ performance. Features selection approaches have been applied to the dataset. Several well-known ML classifiers including Neural Network (ANN), Bayes Network (Bayes Net), and Decision Tree (DT). Along with the original approach, hyper approach is applied using boosting, bagging, and voting classifiers. The performance of these algorithms is examined and compared using a confusion matrix. Results show that behavioral features have a major impact on students’ performance and ML algorithms can be used effectively to build students’ performance prediction model.

关键词： Hands Machine learning algorithms Neural networks Predictive models Prediction algorithms Feature extraction Classification algorithms Bayes methods Information technology Bagging

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Foreword

Proceedings of the 2016 International Conference on Image Pr...

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Proceedings of the 2016 International Conference on Image Processing, computer Vision, and Pattern Recognition, IPCV 2016 2016年

作者： Abd-Wahab, Mohd Helmy Al-Bakry, Abbas Al-Holou, Nizar Arabnia, Hamid R. Bhattacharya, Mahua Martinez Castillo, Juan Jose Daimi, Kevin Deligiannidis, Leonidas Djoudi, Lamia Atma Duong, Trung Eshaghian-Wilner, Mary Mehrnoosh Gravvanis, George A. Huang, Ruizhu Jandieri, George Kim, Byung-Gyu Kim, Tai-hoon Korovin, Iakov Lai, Guoming Lee, Hyo Jong Bin Mansor, Muhammad Naufal Marsh, Andrew Mostafaeipour, Ali Park, James J. Patil, Shashikant Ponalagusamy, R. Schaefer, Gerald Singh, Akash Solo, Ashu M.G. Swee, Sim Kok Thomas, Jaya Tinetti, Fernando G. Vladimir, Hahanov Wang, Shiuh-Jeng Yang, Mary Yoe, Hyun You, Jane Zhao, Wenbing Department of Computer Engineering University Tun Hussein Onn Malaysia Malaysia University of IT and Communications Baghdad Iraq Electrical and Computer Engineering Department IEEE/SEM-Computer Chapter University of Detroit Mercy DetroitMI United States University of Georgia United States ABV Indian Institute of Information Technology and Management MHRD Government of India India Acantelys Alan Turing Nikola Tesla Research Group and GIPEB Universidad Nacional Abierta Venezuela Computer Science and Software Engineering Programs Department of Mathematics Computer Science and Software Engineering University of Detroit Mercy DetroitMI United States Department of Computer Information Systems Wentworth Institute of Technology BostonMA United States Synchrone Technologies France Rutgers University State University of New Jersey New Jersey United States University of Southern California California United States Electrical Engineering University of California Los Angeles Los Angeles [UCLA CA United States Advanced Scientific Computing Applied Math and Applications Research Group Applied Mathematics and Numerical Computing and Department of ECE School of Engineering Democritus University of Thrace Xanthi Greece Texas Advanced Computing Center University of Texas AustinTX United States Georgian Technical University Tbilisi Georgia Institute of Cybernetics Georgian Academy of Science Georgia Multimedia Processing CommunicationsLab.[MPCL Department of Computer Science and Engineering College of Engineering SunMoon University Korea Republic of School of Information and Computing Science University of Tasmania Australia Southern Federal University Russia Computer Science and Technology Sun Yat-Sen University Guangzhou China Center for Advanced Image and Information Technology Division of Computer Science and Engineering Chonbuk National University Korea Republic of Faculty of Engineering Technology Kampus Uniciti Alam Universiti Malaysia Perlis UniMAP Malaysi

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Rainbow: engineering support for self-healing systems

Rainbow: Engineering support for self-healing systems

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SBES 2009 - 23rd Brazilian Symposium on software engineering

作者： Garlan, David Software Engineering Professional Programs School of Computer Science Carnegie Mellon University United States

ISBN: (纸本)9780769538440

An increasingly important requirement of modern software-based systems is continuous operation even in the face of environmental changes, shifting user requirements, and unanticipated faults. One approach to address this requirement is to make systems self-adaptive: when problems are detected the system "heals" itself. In this talk I describe the Rainbow System, which allows engineers to add self-healing capabilities to existing systems. The key ideas behind Rainbow are (a) the use of architectural models;(b) a new language for specifying self-healing strategies;and (c) the ability to customize the self-healing mechanisms to the domain.

关键词： C (programming language)

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software architectures for task-oriented computing 08

Software architectures for task-oriented computing

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7th IEEE/ACIS International Conference on computer and Information science, IEEE/ACIS ICIS 2008

作者： Garlan, David Department of Computer Science Carnegie Mellon University Department of Computer Science Software Engineering Professional Programs School of Computer Science Carnegie Mellon University

ISBN: (纸本)9780769531311

Recent advances in ubiquitous computing, autonomic computing, and artificial intelligence have led to a desire to better support user-oriented tasks by placing more intelligence In the computing infrastructure. This infrastructure helps mediate between computing resources and legacy applications on the one hand, and a user's high-level goals on the other hand. In this talk I survey recent research in developing software architectures to support these new capabilities. Key features of these architectures are the ability to interface with legacy applications, but still add considerable support for user tasks;the ability to incorporate machine learning so that the system adapts to the user over time;and the ability to cope with resource variability and user mobility. I outline some of the consequent software engineering challenges that arise in this setting. © 2008 IEEE.

关键词： software architecture

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Exporting Studio: Critical Issues to Successfully Adopt the software Studio Concept

Exporting Studio: Critical Issues to Successfully Adopt the ...

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Conference on software engineering Education & Training (CSEE&T)

作者： David Root Mel Rosso-Llopart Gil Taran Master of Software Engineering Programs Institute for Software Research School of Computer Science Carnegie Mellon University Pittsburgh PA USA

ISBN: (纸本)9780769531441

In 1989 the professional masters of software engineering (MSE) program at Carnegie Mellon initiated a new approach to graduate level software projects: the software development studio. In 2002 the studio concept was first exported under a cooperative program to teach software engineering at an international partner university. However, CMU quickly determined that student projects, at this partner, lacked progress compared to their CMU counterparts. This paper will focus on the critical lessons that were learned from this ldquoexportrdquo that not only has helped this partnership but also others that are just starting.

关键词： software engineering Programming Educational programs Project management software systems computer science education Gas insulated transmission lines computer science History software development management

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Proposal Based Studio Projects: How to Avoid Producing "Cookie Cutter" software Engineers

Proposal Based Studio Projects: How to Avoid Producing "C...

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Conference on software engineering Education & Training (CSEE&T)

作者： David Root Mel Rosso-Llopart Gil Taran Master of Software Engineering Programs Institute for Software Research School of Computer Science Carnegie Mellon University Pittsburgh PA USA

ISBN: (纸本)9780769531441

The proposal based studio is a method to teach software engineers best practices without developing a "cookie cutter" environment. It teaches students how to get projects done in the fixed time of a degree program without relying on a dogmatic, fixed "recipe" process. This paper discusses how students are provided a template with six general process areas for which they must "propose" solutions. These proposed solutions are unique to each 4 to 5 member Master of software engineering team and are continuously reviewed by the faculty throughout the project.

关键词： Proposals software engineering computer science education Educational programs Gas insulated transmission lines computer science Best practices computer industry software development management Programming

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Continuing Challenges in Selecting Industry Projects for Academic Credit: Points to Consider and Pitfalls to Avoid

Continuing Challenges in Selecting Industry Projects for Aca...

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Conference on software engineering Education & Training (CSEE&T)

作者： Gil Taran Dave Root Mel Rosso-Llopart Master of Software Engineering Programs Institute for Software Research School of Computer Science Carnegie Mellon University Pittsburgh PA USA

ISBN: (纸本)9780769531441

Many academic programs use industrial projects within their teaching curriculum. These provide an exposure to real customers, challenging problems currently faced by industry and the opportunity to interact with working professionals in a situation driven by quality, schedules, and users. Selecting projects that fit todaypsilas academic environment, is a constant challenge. This paper presents how at Carnegie Mellon we have refined our project selection criteria to provide a better fit between our needs and those of our industrial partners. Criteria, issues to consider and pitfalls to avoid in the project selection process will be discussed.

关键词： software engineering computer industry Industrial training Risk management Industrial relations computer science education Continuing education Educational programs Gas insulated transmission lines computer science

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Meeting the Information Assurance Crisis in the U.S. Now

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EDPACS 2006年第6期28卷 1-14页

作者： Corey Schou Deborah Frincke Charles Reynolds James Frost The Associate Dean of Information Systems Programs at Idaho State University (ISU) in Pocatello and the director of the Center for Decision Support. Currently he serves as the Chair of the National Colloquium on Information System Security Education. Schou also directs the ISU National Center of Excellence in Information Assurance Education and the ISU Technology Innovation Center. Contact Corey Schou one of the authors of this article and the Chair of the NCISSE by email at Schou@*** for help in finding additional ways to address the issues raised in this article. A member of the University of Idaho College of Engineering faculty. She graduated from the University of California at Davis. Frincke is the co-director and co-founder of the university's Center for Secure and Dependable Software (CSDS). She was the program chair for the 2nd International Workshop on Recent Advances in Intrusion Detection (RAID). A professor of Computer Science at the College of Integrated Science and Technology at James Madison University in Harrisonburg Virginia. He holds a Ph.D. in computer science from the University of Texas at Austin and a BA in philosophy from the University of Houston. Reynolds is the Director of Information System Security Education at James Madison University. Since 1997 Reynolds has led the development of the first remote Internet-based curriculum that leads to an M.S. degree in computer science with a concentration in information security. Thus far 160 students have completed this program. A professor of computer information systems at Idaho State University and the manager of its Simplot Decision Support Center.

T he only difference etween evolution and revolution is the speed at which each occurs.

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Assessing the ripple effect of CS1 language choice

Journal of Computing Sciences in Colleges

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Journal of Computing sciences in Colleges 2000年第2期16卷

作者： John G. Meinke Adair Dingle Carol Zander Maryland in Europe Graduate Programs Computer Science & Software Engineering Seattle Univeristy Seattle WA Computing and Software Systems University of Washington Bothell WA

Java has reinvigorated the debate on the `best' language to use for CS1. Much of the controversy centers on the goals of CS1, specific language constructs that either hinder or support the first formal introduction to programming, and, even, `real-world' relevance. Missing from typical discussions is the effect of the language choice in CS1 on CS2 and subsequent courses in the CS curriculum. In all such dialogues, it is important to note the characteristics of the department at hand. While many programs can afford to choose a language (such as Scheme) purely for pedagogical reasons, others (if not most), due to pressure from students, industry, advisory boards, select a language with some market appeal. Small departments that serve students who expect an immediate transition to a professional job typically choose a traditional procedural language like C, Pascal, Modula-2, or a popular OO language like C++, Java, Ada95, or Visual Basic. Hence, we focus here on the choice of one of these languages, and the resulting effects on students' progression in the CS curriculum.

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