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检索条件"任意字段=International Conference on Multimedia, Software Engineering and Computing"

共 66536 条记录，以下是91-100 订阅

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Design of an airborne electromechanical interface unit with lightweight and extendable functions 5

Design of an airborne electromechanical interface unit with ...

引用

5th international conference on Mechanical engineering and Materials, ICMEM 2024

作者： Jing, Li-Xiong Wang, Peng-Bo Luo, De-Jie School of Computer Science Northwestern Polytechnical University Shaanxi Xi'an710072 China Xi'an Institute of Computing Technology Aviation Industry Shaanxi Xi'an710065 China

ISBN: (数字)9781510688971

ISBN: (纸本)9781510688964

This paper introduces a lightweight, configurable interface, bus can be cascaded expansion of the airborne electromechanical interface unit. The device is applied to the electrical control system of small and medium-sized UAV, which has the advantages of lightweight, low cost, strong versatility and extendable function. In the design of the electromechanical interface unit, the distributed processing idea applied in the large passenger aircraft is used for reference. The main feature is that the device has greater flexibility, can adapt to the interface characteristics of various sensors and actuators, and has the ability of configurable input and output interfaces and extensible bus communication nodes. The software design of the electromechanical interface unit adopts an open architecture, modular and componentized design, and the table driving technology is applied in the design, which can flexibly configure the software functions, quickly realize the function iteration of the software, and has a certain health management ability. © 2025 SPIE.

关键词： Photons

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Emerging Trends in software engineering: Implications for Development and Efficiency 5

Emerging Trends in Software Engineering: Implications for De...

引用

5th international conference on Emerging Systems and Intelligent computing, ESIC 2025

作者： Chhatria, Bhubaneswar Dharua, Himansu Tarai, Sushanta Kumar Panda, Snigdharani Kiss Du Department of Economics Bhubaneswar India Kiss Du Department of Commerce Bhubaneswar India

ISBN: (纸本)9798331522100

This study explores recent advancements in software engineering, focusing on methods and practices that enhance development efficiency, security, and innovation. The originality of this research lies in its comprehensive analysis of the latest trends, such as Agile methodologies, and the integration of machine learning, which are revolutionizing the software development landscape. The primary objective is to assess the effectiveness of these trends in optimizing software development processes and improving end-user experiences. This research applies quantitative analysis, using time-series data and survey responses from software development teams to evaluate key performance indicators associated with each trend. The analysis, conducted using SPSS software, examines correlations between the adoption of modern methodologies and outcomes such as reduced development time, enhanced security, and overall software quality. Findings indicate that Agile and DevOps practices contribute significantly to faster deployment cycles, while machine learning integration aids in predictive analysis, improving error detection and reducing maintenance needs. The practical implications of this study emphasize the value of embracing emerging methodologies to foster innovation, enhance project success rates, and ensure robust software products. These insights aim to support software companies and developers in adopting strategic trends for sustainable and effective engineering solutions. © 2025 IEEE.

关键词： DevOps

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Enhancing Data Security and Privacy in Cloud computing: A Survey of Modern Techniques 3

Enhancing Data Security and Privacy in Cloud Computing: A Su...

引用

3rd international conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Suganya, N. Gouthami, P. Sathiya, R. Sivaranjani, S. Murugesan, M. Department of Computer Science and Business Systems Dr. N.G.P. Institute of Technology Coimbatore India Department of Information Technology Thangavelu Engineering College Chennai India Departement of Electrical and Electronics Engineering Sri Krishna College of Engineering and Technology Coimbatore India Departement of Electrical and Electronics Engineering Karpagam Institute of Technology Coimbatore India

ISBN: (纸本)9798331527549

A computing system that is based on the internet and offers users all resources as on-demand services. Servers, storage, databases, software, and networking are among these on-demand services. Usually, the user must pay for the use of the resources;they are not their property. The number of people using this technology is increasing dramatically as a result of these features. Although it has benefits, cloud computing poses certain security and privacy risks. The authorized user’s data can be stolen easily. This current research thoroughly investigates modern strategies to these problems, highlighting identity management protocols, effective encryption and blockchain-based solutions. The article identifies research gaps, focuses attention to the inadequacies of current approaches, and recommends the possible ways to improve the efficiency, scalability and trustworthiness. © 2025 IEEE.

关键词： Cloud security

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Improving Federated Learning Efficiency with PruneFL: A Healthcare Perspective 24

Improving Federated Learning Efficiency with PruneFL: A Heal...

引用

13th international conference on computing and Pattern Recognition, ICCPR 2024

作者： Shahid, Alvina Arshad, Muhammad Muneeb Azam, Farooque Anwar, Muhammad Waseem Shafi, Imran Department of Computer and Software Engineering EME College National University of Sciences and Technology Punjab Islamabad Pakistan School of Interdisciplinary Engineering and Sciences National University of Sciences and Technology Punjab Islamabad Pakistan

ISBN: (纸本)9798400717482

In healthcare, accessing diverse and large datasets for machine learning poses challenges due to data privacy concerns. Federated learning (FL) addresses this by training models on decentralized data while preserving privacy. We propose PruneFL, a FL paradigm that leverages model pruning to reduce complexity and enhance efficiency. PruneFL strikes a balance between model accuracy and efficiency by reducing parameters, accelerating convergence, and minimizing communication overhead. Our approach addresses critical FL challenges and demonstrates efficacy in resource-constrained environments like healthcare. © 2024 Copyright held by the owner/author(s).

关键词： Federated learning

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Design and Development of IoT Smart Driving Protocol for Unmanned Ground Vehicles 6

Design and Development of IoT Smart Driving Protocol for Unm...

引用

6th international conference on Mobile computing and Sustainable Informatics, ICMCSI 2025

作者： Seelam, Santhosh Kumar Nagakishore Bhavanam, S. Midasala, Vasujadevi Reddy, Edara Sreenivasa Department of Computer Science and Engineering University College of Engineering and Technology Acharya Nagarjuna University Andhra Pradesh Guntur India Jabalpur Madhya Pradesh Barela India Department of Computer Science and Engineering VIT-AP University Andhra Pradesh Amaravati India

ISBN: (纸本)9798331522667

UGVs have enormous potential in industries such as defense, agriculture, and autonomous transportation. Efficiency and effectiveness can be achieved by UGVs through the sophistication of their control systems, mainly with regard to navigation and decision-making. In this study, a new IoT-based smart direction control system is proposed for UGVs. The system presented herein integrates state-of-the-art sensor fusion techniques against the backdrop of a robust and adaptive communication framework for enhanced navigation accuracy and reduced latency, with the overall goal of improving system efficiency. Equipped with GPS, IMU, and LiDAR sensors, our system provides accurate environmental perception and real-time adaptability to various terrains. The heart of this device is a high-performance, military-grade microcontroller, which ensures the reliability and handling of numerous data streams simultaneously with minimal latency. On the software side, modular design makes use of edge computing and machine learning algorithms to facilitate adaptive control and real-time decision-making. The performance was verified by rigorous testing in simulated environments and real-world field trials. The results show an improvement in the navigation accuracy and system responsiveness compared to previous solutions. A comparative deep analysis shows the superiority of our approach to hardware design, software integration, and prototype testing. © 2025 IEEE.

关键词： Adaptive control systems

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Education and Teaching Research of IoT Embedded Subject under the National Vocational and Technical Skills Standards 6

Education and Teaching Research of IoT Embedded Subject unde...

引用

6th international conference on Mobile computing and Sustainable Informatics, ICMCSI 2025

作者： Yanglu Wang, Xingchen Yadav, Amit Shah, Abhishek Pratap College of Computer and Software Chengdu Neusoft University Chengdu China College of Engineering IT and Environment Charles Darwin University Darwin Australia School of Management Science and Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9798331522667

This research study analyzes six key factors in the education and teaching of IoT embedded direction: training objectives (which direction to teach), curriculum system (what to teach), teaching organization (how to teach), faculty team (who teaches), and teaching evaluation (how well the teaching is) under the current status of embedded teaching on the Internet of Things (IoT) engineering discipline. Guided by the latest National Occupational Technical Skill Standards for IoT engineering professionals and in accordance with the educational philosophy of Chengdu Neusoft University, here we propose a design for teaching system for IoT embedded talent courses, clarified the key elements and formulated new ideas for the current development of talents in this direction to assist improvement and perfection of related curriculum systems, and to promote the establishment and operation of practical and technological activity platforms. It aims to provide practical references for the construction of professionalism in education and teaching standards of IoT. © 2025 IEEE.

关键词： Curricula

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Metrics-Based Refactoring Prediction Using Boosting Algorithm 5

Metrics-Based Refactoring Prediction Using Boosting Algorith...

引用

5th international conference on Emerging Systems and Intelligent computing, ESIC 2025

作者： Patnaik, Archana Padhy, Neelamadhab Kumar, Lov Panigrahi, Rasmita Giet University Department of Computer Science and Engineering Gunupur India Nit Kurukshetra Department of Computer Science and Engineering Kurukshetra India

ISBN: (纸本)9798331522100

software quality enhancement can be done by identifying the refactoring scope of the existing open-source projects in real time. The refactoring mechanism alters the internal structure of the code base without changing the external result. Objectives: In this work, we have assured the project quality by considering different source code metrics as input that helps to evaluate the refactoring score. Methodology: software metrics used are NOI, SLOC, LOC, WMC, and CCL are considered as input parameters and implemented five different types of boosting algorithms. Result Analysis: As there are many extra features, we have selected 20 relevant features out of 115 using Recursive Feature Elimination (RFE). It is observed that Extreme Gradient Boosting (XGB) is best suitable for identifying refactoring opportunities with an accuracy of 99%.Conclusion: A comparison of projects is performed and Titan projects highly required refactoring as it contains more dirty code. © 2025 IEEE.

关键词： software quality

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Integrating AI into software engineering: A Critical Review and Future Directions

Integrating AI into Software Engineering: A Critical Review ...

引用

2025 international conference on Intelligent Control, computing and Communications, IC3 2025

作者： Aditya Pai, H. Sharath, K.R. Babalad, Kavita Guru Prasad, M.S. Chandrappa, S. Kumar, Pratik Mit School of Computing Mit Art Design and Technology University Pune India Department of Computer Science and Engineering Dehradun India School of Computing and Information Technology Reva University Bangalore India Bengaluru India Department of Computer Applications Dehradun India

ISBN: (纸本)9798331527495

The field of Artificial Intelligence (AI) has been witnessing a huge demand in the field of research, tools development, and applications of deployment. There are multiple software companies which are shifting their focus to developing AI systems, many are also deploying the AI paradigms to their current system. Correspondingly, the academic research community has also used AI paradigms to solve the traditional software engineering problems. AI has become very useful to the software engineering community. The paper also uses a survey of the most commonplace methods of using AI into the software engineering, that covers the methods for SE phases such as Requirements, Design, Development, Testing, Release, and Maintenance. The paper also aims in answering to the sufficient intelligence in the SE lifecycle, this evaluates the overlapping of the SE and AI domains, and challenge the current conventional wisdom of the state-of-the-art. © 2025 IEEE.

关键词： software testing

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Empowering Future Engineers: Unveiling Personalized Flipped Classrooms in Basic Programming Education 17

Empowering Future Engineers: Unveiling Personalized Flipped ...

引用

17th international conference on Computer Supported Education, CSEDU 2025

作者： Aldalur, Iñigo Markiegi, Urtzi Sagarna, Xabier Electronics and Computing Department Mondragon Unibertsitatea Arrasate-Mondragon Spain San Sebastian Spain

ISBN: (纸本)9789897587467

In the evolving educational landscape of the 21st century, innovative pedagogical methods like the Flipped Classroom (FC) and Personalized Learning (PL) have increased renown. The FC methodology revolutionizes traditional teaching by moving initial concept exposure outside the classroom, allowing in-class time for interactive and practical activities. This approach increases a dynamic learning environment, enhancing critical thinking, problem-solving, and collaboration skills. Successful FC implementation involves comprehensive educational experiences utilizing digital resources and active classroom interactions. PL adapts teaching to individual student needs, recognizing diverse learning speeds and cognitive styles. By leveraging technology, PL provides customized educational experiences that increase learner autonomy and motivation, leading to deeper understanding and engagement. A case study on teaching C programming using a Personalized Flipped Classroom (PFC) approach illustrates the practical application of these methodologies. The course design includes structured planning, multimedia resources, and continuous evaluation, promoting effective learning. Students engage with instructional videos and practical exercises, promoting autonomy and active participation. The course covers fundamental programming concepts, with a thematic progression that balances foundational understanding and advanced topics. Despite challenges like increased workload and digital competency gaps, the PFC approach demonstrates significant potential in enhancing student performance and skill development. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： engineering education

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FreqSense: Universal and Low-Latency Adversarial Example Detection for Speaker Recognition with Interpretability in Frequency Domain

FreqSense: Universal and Low-Latency Adversarial Example Det...

引用

2025 IEEE international conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Huang, Yihuan Li, Yuanzhe Ren, Yanzhen Tu, Weiping Yang, Yuhong Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of Education China School of Cyber Science and Engineering Wuhan University China National Engineering Research Center for Multimedia Software School of Computer Science Wuhan University China

ISBN: (纸本)9798350368741

Speaker recognition (SR) systems are particularly vulnerable to adversarial example (AE) attacks. To mitigate these attacks, AE detection systems are typically integrated into SR systems. To overcome the limitations of low detection accuracy, poor generalization, and high latency in existing schemes, this paper proposes FreqSense, an AE detection scheme based on frequency distribution features. FreqSense detects a variety of unknown AE attacks with low latency, and provides interpretability in its detection process. The basic idea of FreqSense is that AE typically introduce carefully designed noise in specific frequency bands that are associated with highly distinctive speaker identities. Therefore, leveraging the distributional variations in these frequency bands can effectively distinguish between AE and benign audio. FreqSense models frequency distribution features by integrating time-frequency transformation technology with a self-attention mechanism and employs a neural network-based classifier to distinguish between AE and benign audio. Experimental results show that FreqSense achieves an overall detection accuracy of 99.2%, surpassing state-of-the-art (SOTA) schemes by 27.2%. When confronting unknown AE attacks, FreqSense achieves a detection accuracy of 98.3% with a latency of just 0.0014 seconds. © 2025 IEEE.

关键词： Adversarial Attack Adversarial Example Detection Speaker Recognition

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