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48th Frontiers in Education Conference, FIE 2018

作者： Beck, Phyllis J. Jean Mohammadi-Aragh, M. Archibald, Christopher Jones, Bryan A. Barton, Amy Computer Science and Software Engineering Mississippi State University Mississippi StateMS United States Electrical and Computer Engineering Mississippi State University Mississippi StateMS United States Technical Communication Program Mississippi State University Mississippi StateMS United States

ISBN: (纸本)9781538611739

This is a Work in Progress Research to Practice Category paper. Research has shown that novice programmers struggle with learning introductory concepts and find it difficult to monitor their own progress. Teachers often have hundreds of students and multiple sections of programming courses to teach, making it infeasible to provide the amount of independent feedback each student may need to flourish. With limited instructor feedback, students who can self-monitor and self-assess their programming metacognition have a higher chance of developing a process for solving programming challenges. In this paper, we expand on the literate programming paradigm by using natural language processing and machine learning methods to automatically analyze and classify student programming metacognition levels through their source code comments. Our intent is to ultimately integrate our classification models into an interactive developer environment to provide real-time feedback to students about their metacognition while learning to program. © 2018 IEEE.

关键词： Students

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Influence of blended learning on learning result of algorithm and programming 3

Influence of blended learning on learning result of algorith...

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3rd International Conference on Informatics and Computing, ICIC 2018

作者： Anggrawan, Anthony Ibrahim, Nurdin Suyitno, M. Satria, Christofer Informatics Engineering Study Program of College of Informatics Management and Computer Science Bumigora West Nusa Tenggara Indonesia Education Technology Study Program of Jakarta State University Jakarta Indonesia Education Technology Study Program of Jakarta State University Jakarta Indonesia Visual Communication Design Study Program of College of Informatics Management and Computer Science Bumigora West Nusa Tenggara Indonesia

ISBN: (纸本)9781538669204

The advancement of today's learning technology makes the learning process no longer fully bases on face to face learning, but can achieve by online learning. Online learning is not only useful in overcoming deficiencies in conventional classroom learning, but also a means to meet the learning styles of students who are less fond of and/or dislike face-to-face learning. On the other hand, the main disadvantage of online learning is the lack of face-to-face interaction, while the strength of face-to-face learning is the intensity of student interaction with teachers, the ease of cooperative learning and the clarity of learning materials. In turn, the superiorities on face-to-face learning and online self-learning can be acquired by blended learning. However, blended learning is a learning solution by taking the best advantage of face-to-face classroom learning and online learning. Blended learning has been a learning solution of today's learning. In this study, two blended learning that has different learning content portions between the portion of face-to-face learning materials and online self-learning was conducted to find out which blended learning results produce better pedagogy between two blended learning, and how well the learning outcomes of blended learning are, especially for Algorithm and programming subject. The research results showed the blended learning with 60% face-to-face learning content and 40% online self-learning content delivers learning cognitive competency outcomes worse than 40% face-to-face learning content and 60% online self-learning content. The learning outcome of both blended learning is good, that is greater than 60% from the ideal number. © 2018 IEEE.

关键词： Students

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Uniform scanning model for cognitive communications

Uniform scanning model for cognitive communications

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作者： Liao, Chien-Hsing Woo, Tai-Kuo Yang, Wan-Shing Degree Program of Infornation Technology Fooyin University Taiwan Department of Information Management National Defense Management College Taiwan Department of Computer and Communication Engineering De-Lin Institute of Technology Taiwan

In this paper, in order to capture the spectrum holes with temporal, spatial and frequency variations in sophisticated FHSS radio environments and avoid interference to the existing primary users, a cognitive radio unit (CRU) model with a uniform scanning (U-scanning) technique and cognitive probability ratio (CPR) metric for cognitive communications has been proposed. In this model, real-time spectrum sensing characteristics are coordinated together with system parameters in temporal and frequency domains, e.g., scanning rate and framing processing time, for evaluating the performance of the cognitive radio communications under an elliptic operation scenario. The CPR value is inverse to the hopping rate, and a high CPR value means high spectrum awareness but low coexistence. Moreover, many intriguing numerical results are also illustrated to examine their interrelationships.

关键词： Cognitive radio

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Global mapping of scientific information exchange using altmetric data

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Quality and Quantity 2019年第2期53卷 935-955页

作者： Park, Hyo Chan Youn, Jonghee M. Park, Han Woo Interdisciplinary Program of Digital Convergence Business Yeungnam University Gyeongsan South Korea Department of Computer Engineering Yeungnam University Gyeongsan South Korea Department of Media and Communication Interdisciplinary Program of Digital Convergence Business Cyber Emotions Research Institute Yeungnam University Gyeongsan South Korea

This study seeks to provide new insights into a hidden pattern in the cross-national scholarly network structure from an altmetric perspective. We investigate and visualize the dynamic and complex nature of altmetric-based referrals using a social network algorithm that measures societal use (via Twitter) and scientific impact (via Mendeley). We also use a variety of network indices and a QAP (quadratic assignment procedure) to validate the structural relationships between inter-country sharing networks. Finally, we identify several groups including Asia, Europe, and North America through a transcontinental sharing analysis. The findings suggest that policymakers need to track the international routes of word-of-mouth, which constitute socially mediated data-sharing, regarding scientific publications. © 2018, Springer Nature B.V.

关键词： Altmetrics Big data Global mapping Network analysis Social media

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Writing-to-learn-to-program: Examining the need for a new genre in programming pedagogy 122

Writing-to-learn-to-program: Examining the need for a new ge...

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2015 122nd ASEE Annual Conference and Exposition

作者： Jones, Bryan A. Mohammadi-Aragh, M. Jean Barton, Amy K. Reese, Donna Pan, Hejia Mississippi State University Department of Electrical and Computer Engineering United States Mississippi State University Shackouls Technical Communication Program United States Mississippi State University Computer Science and Engineering Department United States Mississippi State University Mississippi StateMS United States

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Selection decode-and-forward relay networks with rectangular QAM in Nakagami-m fading channels

Selection decode-and-forward relay networks with rectangular...

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IEEE Wireless communications and Networking Conference 2010, WCNC 2010

作者： Al-Qahtani, Fawaz S. Duong, Trung Q. Gurung, Arun K. Bao, Vo Nguyen Quoc National Satellite Technology Program Saudi Arabia Radio Communication Group Blekinge Institute of Technology Sweden School of Electrical and Computer Engineering RMIT University Melbourne VIC Australia Department of Electrical Engineering University of Ulsan Korea Republic of

ISBN: (纸本)9781424463985

In this paper, we investigate the average symbol error probability (SEP) of fixed decode-and-forward relay networks over independent but not identically distributed Nakagami-m fading channels. We have derived closed form expression of SEP for general rectangular quadrature amplitude modulation (QAM) under relay selection scheme where only the best relay forwards message from the source to the destination. The expressions are in terms of hypergeometric series which can be efficiently numerically evaluated. The numerical results are validated with Monte-Carlo simulations. ©2010 IEEE.

关键词： Quadrature amplitude modulation

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Humming-to-Instrument Conversion based on CycleGAN

Humming-to-Instrument Conversion based on CycleGAN

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2021 International Symposium on Intelligent Signal Processing and communication Systems, ISPACS 2021

作者： Lai, Wen-Hsing Wang, Siou-Lin Xu, Zhi-Yao National Kaohsiung University of Science and Technology Dept. of Computer and Communication Engineering Kaohsiung Taiwan National Kaohsiung University of Science and Technology Ph.D. Program In Engineering Science and Technology College of Engineering Kaohsiung Taiwan

ISBN: (纸本)9781665419512

In this research, we propose a humming-to-instrument conversion system based on cycle-consistent adversarial networks (CycleGAN) to convert human humming to the sound of viola. This research adjusts the weight of cycle-consistency loss and identity loss to successfully convert the sound. From the experimental results of objective RMSE, the converted audio is more similar to viola compared to the similarity to humming. From the results of subjective MOS, the quality of the converted sound is fair to listeners. © 2021 IEEE.

关键词： communication systems Signal processing

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Improving the writing-evaluation abilities of graduate teaching assistants in ECE labs

Improving the writing-evaluation abilities of graduate teach...

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2005 ASEE Annual Conference and Exposition: The Changing Landscape of engineering and Technology Education in a Global World

作者： Brocato, John Harden, Jim Chapman, Bill Mississippi State University United States Shackouls Technical Communication Program James Worth Bagley College of Engineering Mississippi State University United States Department of Electrical and Computer Engineering James Worth Bagley College of Engineering Mississippi State University United States

A project conducted by faculty in Bagley College of engineering at Mississippi State University to improve the writing-evaluation of graduate teaching assistants (TAs) in charge of undergraduate laboratories in electrical and computer engineering (ECE). The project began by using writing tutors to work with lab TAs on quality and consistency of their lab-report grading. Results from early exam administrations showed the need for TA support both before and after the exam as well as ongoing performance evaluation. The results show that the every student who took the ESL course performed better on the exam the second time with an average improvement of 57%.

关键词： engineering education

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Image-based food volume estimation

Image-based food volume estimation

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5th International Workshop on Multimedia for Cooking and Eating Activities, CEA 2013

作者： Xu, Chang He, Ye Parra, Albert Delp, Edward Khanna, Nitin Boushey, Carol School of Electrical and Computer Engineering Purdue University West Lafayette IN United States Department of Electronics and Communication Engineering Graphic Era University Dehradun India Cancer Epidemiology Program University of Hawaii Cancer Center Honolulu HI United States

ISBN: (纸本)9781450323925

In this paper, we propose an extension to our previous work on food portion size estimation using a single image and a multi-view volume estimation method. The single-view technique estimates food volume by using prior information (segmentation and food labels) generated from food identification methods we described earlier. For multi-view volume estimation, we use "Shape from Silhouettes" to estimate the food portion size. The experimental results of our volume estimation methods demonstrate our results with respect to accuracy and reliability. © Copyright 2013 ACM.

关键词： Image reconstruction

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AI-Powered Precision: Revolutionizing Skin Cancer Detection with Advanced Machine Learning 6

AI-Powered Precision: Revolutionizing Skin Cancer Detection ...

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6th IEEE Novel Intelligent and Leading Emerging Sciences Conference, NILES 2024

作者： Abd-Elaziz, Mariam M. Elshafie, Basma M. Abdullah, Hagar Gerges, Karen Y. Ghanem, Ingy A. Fouad, Khaled M. El-Ghamry, Amir Moawad, Ibrahim F. El-Metwally, Sara New Mansoura University Faculty of Computer Science and Engineering Dakahlia Egypt Mansoura University New Mansoura University Faculty of Engineering Computer and Communication Program Faculty of Computer Science and Engineering Egypt Benha University Information Systems Faculty of Computers and Artificial Intelligence Egypt Mansoura University New Mansoura University Faculty of Computer and Information Sciences Faculty of Computer Science and Engineering Egypt School of Engineering and Computer Science University of Hertfordshire Gaf Egypt Ain Shams University Faculty of Computer and Information Sciences Cairo Egypt College of Computer Science and Engineering Taibah University Department of Artificial Intelligence Medina42353 Saudi Arabia

ISBN: (纸本)9798350378511

Skin cancer's increasing incidence rates necessitate advanced diagnostic tools. This research uses MobileNet architecture to develop an enhanced system for skin cancer detection. MobileNet's efficient CNN architecture, combined with Keras for model lifecycle management and TensorFlow for real-time inference, forms the foundation of this study. Using 10,015 dermatoscopic pictures from seven different classifications of skin cancer in the HAM10000 dataset, the methodology includes several key stages: image preprocessing to correct illumination and adjust resolution, data augmentation to balance the dataset, and model training using Transfer Learning. The MobileNet model was trained over 50 epochs with a comprehensive architecture incorporating multiple specialized layers. By combining large-scale data analysis and adaptive learning, this methodology demonstrates The revolutionary possibilities of AI and ML in improving skin cancer diagnostics and public health outcomes. Keywords Skin Cancer Detection, Dermatoscopic Images, Machine Learning, Deep Learning © 2024 IEEE.

关键词： Adversarial machine learning

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