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检索条件"任意字段=International Conference on Teaching and Learning in Computing and Engineering"

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Towards Robust and Efficient Yoga Pose Recognition using Deep learning: A Comprehensive Review 15

Towards Robust and Efficient Yoga Pose Recognition using Dee...

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15th international conference on Advances in computing, Control, and Telecommunication Technologies, ACT 2024

作者： Senthil Kumari, P. Mythili, S. Dept. of Artificial Intelligence PSNA College of Engineering and Technology Dindigul India Dept. of Bio Medical Engineering PSNA College of Engineering and Technology Dindigul India

ISBN: (纸本)9798331300579

Yoga is a popular practice that promotes physical and mental well-being. The lack of regulation and standardization in yoga teaching and learning can lead to unsafe practices and health issues for practitioners, such as injury or exacerbation of pre-existing medical conditions. Accurate classification of yoga postures is essential for effective teaching and learning of yoga. Deep learning (DL) techniques have shown significant potential in automating the process of posture classification, leading to improve accuracy and efficiency. This paper provides a comprehensive review of the use of DL techniques for yoga posture classification. Different DL algorithms, including Convolutional Neural Network (CNN), Recurrent Neural Network (RNN) and Generative Adversarial Network are explored. Additionally, various datasets used for training and testing deep learning models for yoga posture classification are discussed. Challenges involved in yoga posture classification, such as variability in posture performance and the lack of standardized datasets, are also highlighted. A comparison of different DL techniques for yoga posture classification is presented, mentioning their respective strengths and weaknesses. This review emphasizes the potential benefits of DL for accurate yoga posture classification and provides insights into future research directions in this field. © Grenze Scientific Society, 2024.

关键词： Generative adversarial networks

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RSF: Reinforcement learning based hybrid split and federated learning for edge computing environments 32

RSF: Reinforcement learning based hybrid split and federated...

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32nd international conference on Electrical engineering (ICEE)

作者： Soleimani, Alireza Anabestani, Negar Momtazpour, Mahmoud Amirkabir Univ Technol Dept Comp Engn Tehran Iran

ISBN: (纸本)9798350376357;9798350376340

The increasing usage of the Internet of Things (IoT) in various domains, particularly within the realm of artificial intelligence has raised concerns about data privacy. Federated learning has been established to address this issue. However, federated learning faces challenges such as constrained computing resources on IoT devices, fluctuating network bandwidth, and low scalability due to network congestion during the transition of local weights in a large scale. All of these results in a low convergence time, or even failure in the training procedure. This paper presents a reinforcement learning-based dynamic neural network splitting method called RSF to reduce overall training time with a faster partitioning decision time. The reinforcement learning agent dynamically allocates computational tasks across IoT devices, Edge servers, and the cloud, accelerating the training process in edge computing environments. The neural network partitioning adapts iteratively. The agent decides on the neural network partitioning for each IoT device at the start of each training round. Simulation results demonstrate the effectiveness of our proposed method, achieving substantial speed improvements up to 27%, and higher scalability.

关键词： Federated learning Split learning Distributed learning

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Analysis and prediction of student achievement in online teaching based on KNN 3

Analysis and prediction of student achievement in online tea...

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3rd international conference on Intelligent computing and Human-Computer Interaction, ICHCI 2022

作者： Li, Hongmei Zhang, Haihang Anhui Xinhua University China Hefei No. 11 Middle School China

ISBN: (纸本)9781510661301

Using learning analytics technology to mine online learning features can optimize the teaching process. On the basis of collecting students' online learning information, the similarity between features is firstly analyzed;secondly, machine learning algorithm is used to construct a student's learning performance prediction model, and the accuracy and K value of the model are analyzed;The teacher's teaching process reform puts forward the corresponding direction. © 2023 SPIE.

关键词： Data mining

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Research on the Design and Optimization of Russian Spoken Wisdom Education System Based on Recommendation Algorithm

Research on the Design and Optimization of Russian Spoken Wi...

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2024 Asia-Pacific conference on Software engineering, Social Network Analysis and Intelligent computing, SSAIC 2024

作者： Liu, Chunfu Xu, Yanyan Heilongjiang University Of Technology Heilongjiang Jixi158100 China

ISBN: (纸本)9798350393682

Language is the link of excellent civilization exchange and inheritance, all cooperation and integration among all ethnic groups, regions and countries. As two big countries on the international stage, China and Russia play an irreplaceable role in international affairs. With such a large-scale Russian talent training team, its basic teaching mode is worthy of academic thinking and research. Especially since 2019, Russian teachers in colleges and universities across the country have ushered in a new 'big exam'. How to take the initiative to turn crisis into opportunity, do a good job in teaching, improve teaching methods and form a benign teaching reflection is an important mission of Russian teaching. Therefore, how to correctly use different oral testing methods, including using more scientific and objective scoring standards to complete the test, is an important issue that should always be taken seriously and continuously improved in the teaching and testing of relevant courses for each grade of Russian major. The main research direction of this article is to improve the measurement method of user similarity, refine user behavior, and combine factors such as user learning goals to improve recommendation accuracy. This article elaborates in detail on the connotation, methods, platforms, teaching reflection, and promotion of student remote learning models of online teaching, in order to provide reference and guidance for online Russian teaching in China. © 2024 IEEE.

关键词： teaching

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Hobby Based learning for Automata Theory and Computability 2

Hobby Based Learning for Automata Theory and Computability

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2nd IEEE international conference on Intelligent and Innovative Technologies in computing, Electrical and Electronics, ICIITCEE 2024

作者： Pallavi, N. Darshna, A. Naik Manjula, L. Keerthi, P. Ramaiah Institute of Technology Department of Computer Science and Engineering Bangalore India Impact Institute of Technology Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350306415

In the traditional form of instruction, the teacher and pupil converse face to face. The discussion is started by the instructor, who generally discusses the material from the required textbooks. Many students might not find the concepts intriguing, which would reduce their ability to concentrate and pay attention in class. This makes learning challenging. A novel teaching strategy that allows pupils to learn a subject depending on their interests has been implemented in the classroom. With this approach, students apply their own hobbies to the subject they wish to learn. It focuses on interest-driven learn. This method focuses on interest driven learning where students apply their Personal interest to the subject they want to learn. A prime example of interest-driven learning is hobby-based learning. Modelling enthusiasm and making the topics relevant to their hobby would make the classroom student centric learning and interest driven learning where student would learn the topic self-directed, enjoy learning process, gain deeper insight on the topic and also develop their hobbies. Hence hobby-based learning was introduced to the classroom for the subject Automata Theory and Computability. A comparative study was made on analysis and data obtained from classrooms with hobby based learning and conventional learning handled by the same instructor on the subject Automata Theory and Computability where hobby-based learning gave significantly best feedback than conventional learning. © 2024 IEEE.

关键词： Hobby based learning interest driven learning student centric learning

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teaching UML using a RAG-based LLM

Teaching UML using a RAG-based LLM

引用

international Joint conference on Neural Networks (IJCNN)

作者： Ardimento, Pasquale Bernardi, Mario Luca Cimitile, Marta Univ Bari Aldo Moro Dept Comp Sci Bari Italy Univ Sannio Dept Engn Benevento Italy UnitelmaSapienza Univ Dept Law & Econ Rome Italy

ISBN: (纸本)9798350359329;9798350359312

teaching the Unified Modelling Language (UML) is a critical task in the frame of Software engineering courses. Teachers need to understand the students' behavior along with their modeling activities to provide suggestions and feedback to avoid more frequent mistakes and improve their capabilities. This paper presents a novel approach for teaching the UML in Software engineering courses, focusing on understanding and improving student behavior and capabilities during modeling activities. It introduces a cloudbased tool that captures and analyzes UML diagrams created by students during their interactions with a UML modeling tool. The key aspect of the proposal is the integration of a Retrieval Augmented Generation Large Language Model (RAG-based LLM), which generates insightful feedback for students by leveraging knowledge acquired during the modeling process. The effectiveness of this method is demonstrated through an experiment involving a substantial dataset comprising 5,120 labeled UML models. The validation process confirms the performance of the UML RAG-based LLM in providing relevant feedback related to entities and relationships in the students' models. Additionally, a qualitative analysis highlights the user satisfaction, underscoring its potential as a valuable tool in enhancing the learning experience in software modeling education.

关键词： Deep learning Generative AI LLMs computing Education UML Software Modelling

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Revisiting Tech Battles Using Science Fiction: Methodological Implications and First Impressions 15

Revisiting Tech Battles Using Science Fiction: Methodologica...

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15th IEEE Global engineering Education conference (IEEE EDUCON)

作者： Lucchetta, Jessica Carraro, Tommaso Stoycheva, Milena Angeli, Lorenzo Univ Trento Trento Italy Jr Achievement Bulgaria Sofia Bulgaria

ISBN: (纸本)9798350394023;9798350394030

The development of non-technical skills, such as critical thinking and public speaking, is increasingly recognized in computing curricula as essential for computing professionals in the job market. Universities are adopting active learning methods to cultivate these skills, among which are debate-based teaching methods. Previous literature showed that debating is used in many knowledge domains, and can help develop skills of information synthesis, critical thinking, and effective verbal communication. In spite of these benefits, however, debating in computing education is still rare. This work explores a partial redesign of a debates-based teaching method, called Tech Battles, implemented in a 6-ECTS non-technical course at the University of Trento targeted to first-year Master's students in Computer Science with a minor in innovation and entrepreneurship. Battles have been part of the course since 2013, and over the years the teaching team upgraded the methodology, which now foresees a preparatory activity where students read a science fiction short story assigned by the teachers. In this paper, we discuss how this latest modification changes the course and its impacts: how the workflow of each debate evolved, our criteria for selecting short stories, preliminary observations gathered from the field, and the research methods that will be used to more thoroughly validate the updated method.

关键词： debates computing education active learning

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Human-Computer Interaction and Computational Intelligence: Machine learning Approaches

Human-Computer Interaction and Computational Intelligence: M...

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2024 international conference on Sustainable computing and Integrated Communication in Changing Landscape of AI, ICSCAI 2024

作者： Tiwari, Shashank Shekhar Mittal, Tanusha Habelalmateen, Mohammed I. Madhu, P. Nimmalaharathi Bansal, Saloni Kaushik, Rohit Department of Information Technology Dr. Abdul Kalam Technical University REC Ambedkar Nagar U.P Lucknow India Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun India Department of Computers Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq Department of Information Science and Engineering Malnad College of Engineering Karnataka Hassan India Department of EIE School of Engineering Sree Vidyanikethan Engineering College AP India Department of Computer Engineering and Applications GLA University Mathura India Faculty of Management SRM Institute of Science and Technology NCR Campus India

ISBN: (纸本)9798350355338

Machine learning is a field that was established some years ago with the lofty goal of building computational methods to implement various aspects of teaching, Machine learning (ML) has changed materials science fields that have been able to generate large sufficient datasets to use appropriate statistical methods, yet databases for many important types of materials remain intact. Machine learning is an emerging technology that has attracted the attention of academics and business leaders, and it is expected to develop in the near term. Wireless nodes are anticipated to have ubiquitous connectivity due to machine learning methods. IML (Interactive Machine learning) strives to augment subjective experience and intellect by closely combining these abilities with machine computing speed and power. This paper provides a full study and characterization of Interactive Machine learning from the standpoint of interaction design. We present and explain a functional and structural model of a generalized IML system, as well as solution concepts for developing successful IML interactions. © 2024 IEEE.

关键词： Adversarial machine learning

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Adopting an Agile Approach for Reflective learning and teaching 46

Adopting an Agile Approach for Reflective Learning and Teach...

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ACM/IEEE 44th international conference on Software engineering: Software engineering Education and Training (ICSE-SEET)

作者： Leist, Eleanor Lee, Jaejoon Univ East Anglia Norwich Norfolk England

ISBN: (纸本)9798400704987

Software engineering is concerned with how best to create software in ways that promote sustainable development and maximise quality. We have been largely successful at transferring software engineering knowledge into the industry, however, many challenges in software engineering training remain. A key amongst these is how best to teach practical engineering approaches along with the theoretical concepts behind them. This paper describes our experience of adopting an agile approach for reflective learning and teaching within the context of our Software Systems engineering module, aimed at addressing challenges identified with previous efforts to promote reflective practice. Our study attempts to strengthen the use of reflective learning approaches for our current cohort, as well as introducing reflective teaching practices, whereby we examine our teaching approach in order to improve its efficiency and effectiveness. Our analysis of student response to the module shows that it was very well-received by the students, and we were able to collect ample evidence from feedback to support this. Most of our approaches resulted in positive feedback and contributed to improvements in teaching quality, however, we also identified some key aspects in our method that could still benefit from refinement, such as the need for explicit links between learning outcomes and workshop activities, and intuitive design of feedback questions, along with feedback collection frequency. We plan to incorporate these additional updates into the revision of the module for the next academic year, and to continue collecting and analysing feedback data for further enhancement.

关键词： Reflection learning teaching Agile Feedback Ganmification

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Approaches to Foreign Language teaching of Future Engineer-Teachers in the Context of Digitalization and Distance learning 26th

Approaches to Foreign Language Teaching of Future Engineer-T...

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26th international conference on Interactive Collaborative learning (ICL) - Towards a Hybrid, Flexible and Socially Engaged Higher Education / 52nd IGIP international conference on engineering Pedagogy

作者： Trokhymchuk, Sergii Bryntseva, Olena Pasichnyk, Maryna Ukrainian Engn Pedag Acad Kharkiv Ukraine

ISBN: (纸本)9783031526664;9783031526671

The article describes the experience of applying distance digital educational technologies in the process of teaching the discipline "Foreign Language" at higher engineering educational institutions, highlighting both the positive possibilities of the digital format and certain limitations related to the organizational, pedagogical, material and technical conditions of its implementation, and the psychological difficulties of the teaching staff and students in switching to a distance learning format. The results are implemented on the example of bachelors' professional training at the Ukrainian engineering Pedagogics Academy (Kharkiv). The proposed model of organizing a distance learning course in a foreign language for future engineer-teachers allows to develop and implement a combined model of the foreign language educational process: traditional interaction of students and teachers in combination using online courses with synchronous learning in a distance format provided by digital didactics, create a system of control and monitoring of knowledge in all types of foreign language activities;to improve the quality and effectiveness of the distance learning format, as well as to develop the skills of independent work of future engineers-teachers within the distance course in the discipline "A Foreign Language".

关键词： future engineer-teacher foreign language communicative competency distance learning course digital technologies students' independent work

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