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Predicting Mentoring Effectiveness in a Computer Science Program: A Machine Learning Approach [PDF]
2020 IEEE International Conference for Innovation in Technology (INOCON), 2020 Mentoring is a critical academic tool to positively influence students' outcomes. While there is a broad consensus about the benefits of mentoring, still there is a divergence of opinion regarding the attributes based on which student mentees evaluate the effectiveness of a mentoring program. This study has drawn a sample from undergraduate students of
Amit Mittal, Ruchi Mittal, Jaiteg Singh
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A Machine Learning Model for Content-Based Image Retrieval
2023 2nd International Conference for Innovation in Technology (INOCON), 2023With advancement in the modern era, digital data is the new asset. Now making large image datasets is not that laborious task with improvement in image collection and data storage technology.
Kunal +3 more
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Recent Advances in Numerical Methods, Machine Learning, and Computer Science
2021The chapter presents a brief description of chapters that contribute to the recent advances in numerical methods in continuum mechanics, computational physics. Also, this chapter deals with machine learning and computer science. The fourth part of the book presents novel computational methods in continuum mechanics.
Lakhmi C. Jain +4 more
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Distinguishing Human-Written and ChatGPT-Generated Text Using Machine Learning
Systems and Information Engineering Design Symposium, 2023The use of sophisticated Artificial Intelligence (AI) language models, including ChatGPT, has led to growing concerns regarding the ability to distinguish between human-written and AI-generated text in academic and scholarly settings. This study seeks to
Hosam Alamleh +2 more
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Conference on Computer and Communications Security, 2023
Reproducibility is crucial to the advancement of science; it strengthens confidence in seemingly contradictory results and expands the boundaries of known discoveries. Computer Security has the natural benefit of creating artifacts that should facilitate
Daniel Olszewski +8 more
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Reproducibility is crucial to the advancement of science; it strengthens confidence in seemingly contradictory results and expands the boundaries of known discoveries. Computer Security has the natural benefit of creating artifacts that should facilitate
Daniel Olszewski +8 more
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Encoding the atomic structure for machine learning in materials science
WIREs Computational Molecular Science, 2021In recent years, we have witnessed a widespread application of machine learning techniques in the field of materials science, owing to the increased availability of research data and sophisticated algorithms.
Shunning Li +5 more
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Catalyze Materials Science with Machine Learning
ACS Materials Letters, 2021Discovering and understanding new materials with desired properties are at the heart of materials science research, and machine learning (ML) has recently offered special shortcuts to the ultimate goal.
Jaehyun Kim +3 more
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Journal of the American Statistical Association, 2023
He is also Professor of Computer Science at the University of Edinburgh, and a Fellow of Darwin College, Cambridge. In 2004, he was elected Fellow of the Royal Academy of Engineering, in 2007 he was elected Fellow of the Royal Society of Edinburgh, and ...
Chris Nakas +2 more
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He is also Professor of Computer Science at the University of Edinburgh, and a Fellow of Darwin College, Cambridge. In 2004, he was elected Fellow of the Royal Academy of Engineering, in 2007 he was elected Fellow of the Royal Society of Edinburgh, and ...
Chris Nakas +2 more
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Detecting ChatGPT-Generated Code Submissions in a CS1 Course Using Machine Learning Models
Technical Symposium on Computer Science EducationThe emergence of publicly accessible large language models (LLMs) such as ChatGPT poses unprecedented risks of new types of plagiarism and cheating where students use LLMs to solve exercises for them. Detecting this behavior will be a necessary component
Muntasir Hoq +6 more
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The 6th International Conference on Soft Computing and Intelligent Systems, and The 13th International Symposium on Advanced Intelligence Systems, 2012
This paper aims to provide a short review on the application of computational intelligence (CI) and machine learning (ML) in the bioenvironmental sciences. To clearly illustrate the current status, we limit our focus to some key approaches, namely fuzzy systems (FSs), artificial neural networks (ANNs) and genetic algorithms (GAs) as well as some ML ...
Bernard De Baets, Shinji Fukuda
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This paper aims to provide a short review on the application of computational intelligence (CI) and machine learning (ML) in the bioenvironmental sciences. To clearly illustrate the current status, we limit our focus to some key approaches, namely fuzzy systems (FSs), artificial neural networks (ANNs) and genetic algorithms (GAs) as well as some ML ...
Bernard De Baets, Shinji Fukuda
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