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检索条件"任意字段=International Conference on Advances in Information Communication Technology and Computing"

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A comprehensive survey on client selections in federated learning

A comprehensive survey on client selections in federated lea...

引用

international conference on Innovation and Technological advances for Sustainability, ITAS 2023

作者： Gouissem, A. Chkirbene, Z. Hamila, R. College of Computing and Information Technology University of Doha for Science and Technology Qatar Electrical Engineering Qatar University Qatar

ISBN: (纸本)9781032803722

Federated Learning (FL) is a rapidly growing field in machine learning that allows data to be trained across multiple decentralized devices. The selection of clients to participate in the training process is a critical factor for the performance of the overall system. In this survey, we provide a comprehensive overview of the state-of-the-art client selection techniques in FL, including their strengths and limitations, as well as the challenges and open issues that need to be addressed. We cover conventional selection techniques such as random selection where all or partial random of clients is used for the trained. We also cover performance-aware selections and as well as resource-aware selections for resource constrained networks and heterogeneous networks. We also discuss the usage of client selection in model security enhancement. Lastly, we discuss open issues and challenges related to clients selection in dynamic constrained, and heterogeneous networks. © 2025 The Author(s).

关键词： Federated learning

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AI-Driven Green computing for 6G Network: Improve User Experience and Security 1

AI-Driven Green Computing for 6G Network: Improve User Exper...

引用

1st international conference on advances in Computer Science, Electrical, Electronics, and communication Technologies, CE2CT 2025

作者： Yadav, Rakesh Kumar Harinaiha, Adarsha Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Faculty of Engineering and Technology Department of Mechanical Engineering Karnataka Ramnagar India

ISBN: (纸本)9798331518578

A dynamic Computational Thinking resolution can be likely in a 6G environment by way of Green-IoT and Artificial Intelligence (AI), important parts of computational thinking. This order requires lowering difficult problems to tinier, more controllable parts and recognizing patterns and friendships at intervals in miscellaneous parts. Machine intelligence approaches concentrate on algorithms capable of learning from data, making judgments and predictions, and executing complex tasks beyond explicit programming. To appreciate the far-reaching quantities of data presented by 6G-connected schemes, computational inference and machine intelligence can be used for the Green-IoT. This has the potential to reinforce the computerization of many processes and bring about a smarter and more efficient use of possessions. Computational thinking that combines Green-IoT, AI, and 6G sciences can transform many areas, including education, and reinforce society's lives through the production of brisker, more adept, and more tailor-made uses and services. The research has been started by outlining key limits utilizing Green-IoT-authorized sensor electronics in the framework of 5G and 6G surroundings, as well as Artificial Intelligence, in this place study's review on computational thinking. In the subsequent section, delineate the fundamental structural requirements for a digital thinking paradigm centered on artificial intelligence and the Net of Things, significant aspects of prospective beneficial applications, and evaluate the advantages and disadvantages of each within the context of shared resources. Lastly, several security risks to an AI-based architecture that might compromise the system's ability to provide the computational thinking services that social media platforms need. © 2025 IEEE.

关键词： Economic and social effects

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Performance Improvement: Modulation Recognition Scheme Using CVCNN-LSTM Method 1

Performance Improvement: Modulation Recognition Scheme Using...

引用

1st international conference on advances in Computer Science, Electrical, Electronics, and communication Technologies, CE2CT 2025

作者： Krishnamoorthy, Ramkumar Agarwal, Trapty Department of Computer Science and Information Technology Karnataka Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798331518578

The process for automatic modulation recognition (AMR) is important to industrial cognitive radio Models. Although they have made significant strides in modulation detection, state-of-the-art real-valued CNNs compromise model interpretability and signal phase integrity by treating complicated signal components as distinct actual inputs. The CVCNN-LSTM is a novel AMR technique that is presented in this research. In order to capitalize on the advantages associated with both networks while minimizing their drawbacks, this study intends to use CNNs along with a LSTM. This method improves recognition performance by strengthening the learning for the initial in-phase/quadrature information (I/Q) signal characteristics. The suggested network consists of one LSTM layer and many local features learning unit (LFLUs). Convolutional and average pooling layers, which are the main components of an LFLU, are essential for allowing hierarchical correlation extraction and local correlation learning. Researchers recommend employing end-to-end complex-valued CNN & LSTM for modulation recognition rather than dual-channel real-valued networks as in-phase/quadrature information naturally including complex-valued system. Researchers analyse complex-valued networks via experiments and show that this methodology outperforms the state-of-the-art techniques in AMR area. © 2025 IEEE.

关键词： Convolutional neural networks

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Developing Critical Thinking Skills in Undergraduate Students: A Mapping Study in computing Education

Developing Critical Thinking Skills in Undergraduate Student...

引用

17th international conference on Computer Supported Education, CSEDU 2025

作者： de Andrade Mota, Davy dos Santos, Simone C. Informatic Center Federal University of Pernambuco Pernambuco Recife Brazil

ISBN: (纸本)9789897587467

In the dynamic context of the digital age, academic training in information technology (IT) transcends the mere assimilation of theoretical knowledge, equally requiring the promotion of critical thinking among students. From this perspective, this research proposes a literary approach dedicated to investigating and analysing effective strategies for developing and stimulating critical thinking in IT students. In an environment where technology advances rapidly, it is crucial to equip future professionals in this field not only with solid technical knowledge but also with the intrinsic ability to critically analyse information and conceive innovative solutions in the face of emerging challenges. Thus, this study is motivated by the following research question: "How to develop critical thinking skills in IT undergraduate students?". To conduct this investigation, Kitchenham's systematic mapping studies method and the ChatGPT 4.0 version tool were used as instruments for formatting the extracted data, and visually, generating the charts and graphs. From 72 studies, the main highlighted results were observed, which reference the primary teaching methodologies and frameworks used, the benefits and limitations of these methods, as well as relevant information for understanding the courses in which these methods were applied, class sizes, course durations, and levels of education. Copyright © 2025 by SCITEPRESS - Science and technology Publications, Lda.

关键词： Students

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Enhancing Adaptive Data Management Middleware: Techniques for Federated Cloud Environments 8th

Enhancing Adaptive Data Management Middleware: Techniques fo...

引用

8th IFIP TC 12 international conference on Computer, communication and Signal Processing, ICCCSP 2024

作者： Kolekar, Vikas K. Sakhare, Sachin R. Department of Computer Engineering SMT. Kashibai Navale College of Engineering Pune411041 India Department of Computer Engineering Vishwakarma Institute of Information Technology Pune411048 India

ISBN: (纸本)9783031736162

The adaptive data management middleware is crucial for facilitating efficient and dynamic data management in distributed computing environments. Nevertheless, the widespread adoption of federated cloud environments brings about new complexities and difficulties in data administration, requiring inventive methods to improve the functionalities of current middleware systems. This research paper introduces innovative strategies for enhancing adaptive data management middleware that is especially designed for federated cloud environments. The proposed methodology addresses several fundamental components of adaptive data management middleware. Initially, proposed the methods for dynamically provisioning and allocating resources to enhance the efficiency of data processing and storage across federated cloud environments. In addition, provided the strategies for implementing data governance and enforcing security measures to meet regulatory standards and protect confidential information in federated cloud environments. Furthermore, investigated the techniques for duplicating and synchronization data to improve the accessibility and uniformity of data in federated environments. To evaluate the results of the proposed techniques, we conducted comprehensive experimental evaluations using simulated federated cloud infrastructures. The results demonstrate the substantial enhancements in the performance of data management, utilisation of resources, and capacity to scale when compared to existing methods. Lastly discussed the implications of our findings and emphasised potential areas for further investigation in this rapidly evolving domain. © IFIP international Federation for information Processing 2025.

关键词： Cloud platforms

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Live Audio Recognition and Text Conversion System 2

Live Audio Recognition and Text Conversion System

引用

2nd international conference on Computational Intelligence, communication technology and Networking, CICTN 2025

作者： Sharma, Pratyaksha Gupta, Sumita Bhavya, Boddu Asmitha Sharma, Khushi Dhir, Saru Gambhir, Sapna Department of Computer Science & Engineering Amity School of Engineering & Technology Amity University UP India Department of Information Technology Amity School of Engineering & Technology Amity University UP India Dept. of Computer Science College of Engineering and Computing George Mason University United States

ISBN: (纸本)9798331530389

With the advancement of technologies, different methods are currently being used for converting spoken language into text. These systems offer a hands-free alternative to traditional input methods, especially for individuals with physical disabilities or those requiring efficient documentation of spoken content. The goal of this study is to review recent advancements in this field and highlight gaps in current research, with a focus on accuracy, language adaptability, ease of use, and the integration of various technologies. We also suggest future directions for enhancing and developing this technology further. © 2025 IEEE.

关键词： Hidden Markov models

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A Decentralised Application for Medical Insurance Claim System Using Blockchain technology 5th

A Decentralised Application for Medical Insurance Claim Syst...

引用

5th international conference on computing Science, communication and Security

作者： Joshi, Hrishabh Justine, Sharon Panchami, V. Hrithik, Beeraka IIIT Kottayam CSE Cyber Secur Kottayam 686635 Kerala India

ISBN: (纸本)9783031751691;9783031751707

The medical insurance play a prominent role in healthcare industry by providing financial help in emergency medical condition. However the transparency, security and efficiency of the system should be enhanced to improve the medical insurance process using a decentralized application. The proposed system covers the design and development of a secure and decentralized platform for medical insurance claims. The proposed system enables the patients and insurance companies to easily access and share medical records, which facilitates the insurance claims process and eliminates the need for manual record-keeping. The system is implemented using smart contracts to automate insurance pay-outs, reducing the likelihood of fraud and making the process faster and more reliable. Furthermore the proposed system performance evaluated with different test networks like Mumbai, Sepoli and Goerli to perform a detailed time and cost analysis of different blockchain. Hence the system has the potential to revolutionize the medical insurance industry and improve the overall quality of healthcare services.

关键词： Blockchain technology InterPlanetary File System (IPFS) Smart Contract

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Deep learning based multiple regression analysis approach for designing medical image recognition system 2nd

Deep learning based multiple regression analysis approach fo...

引用

2nd international conference on Next-Generation computing and information Systems, ICNGCIS 2023

作者： Singh, Shweta Jagadish, A.N. Vyas, Bhuman Wasim Bhatt, Mohammed Sameen, Aws Zuhair Degadwala, Sheshang Electronics and Communication Department IES College of Technology Bhopal India Department of Computer Science Bapuji Institute of Engineering and Technology Karnataka Davanagere India Credit Acceptance Canton United States Model Institute of Engineering and Technology J&K Jammu India College of Medical Techniques Al-Farahidi University Baghdad Iraq Department of Computer Engineering Sigma University Gujarat Vadodara India

ISBN: (纸本)9781032738659

Machine learning models are optimization models that make it possible to gather data, evaluate it, and provide the experts and management with the reports they need to make the best decisions. This study uses quantitative research, as it seeks to gather information and analyse it with statistical models such as regression analysis and analysis of variance. Researchers want to use statistical techniques such as descriptive analysis, regression analysis, and ANOVA (analysis of variance) to analyse the hypothesis. The purposive sample technique is used by the authors to choose respondents who work in the healthcare sector. A non-probability sampling technique called purpose sampling is used. The R squared value is 0.744, or 74.4 percent, according to the analysis. According to the investigation, there is a strong correlation between improved picture quality and ML-based techniques in digital image recognition. © 2025 The Author(s).

关键词： Regression analysis

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Benchmarking Indian E-Commerce Giants: Insights from Festive Sales Performance

Benchmarking Indian E-Commerce Giants: Insights from Festive...

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2025 IEEE international conference on Computational, communication and information technology, ICCCIT 2025

作者： Pranav, H. Harshini, Muppavarapu Sri Tarun, Rachuri Radha, D. Amrita School of Computing Dept of Computer Science and Engineering Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331512965

This study presents a comparative analysis of the websites of three major e-commerce platforms in India: during the busy shopping sale of Diwali and Navratri. Using metrics derived from Lighthouse audits, the report evaluates the performance, accessibility, SEO, and adherence to best practices of each site. Key factors such as First Contentful Paint (FCP), Largest Contentful Paint (LCP), Speed Index, and overall user experience are examined. The analysis highlights the strengths and areas for improvement of each platform, with recommendations for enhancing load times, user accessibility, and search engine optimization. This comparison aims to provide actionable insights into optimizing the performance and usability of e-commerce websites. © 2025 IEEE.

关键词： Sales

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Development of a Dynamic Event Hand Tracking System in Mobile Augmented Reality Viewers 24

Development of a Dynamic Event Hand Tracking System in Mobil...

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13th international conference on Networks, communication and computing, ICNCC 2024

作者： Espejon, Kent Tugade Jayoma, Jaymer M. College of Computing and Information Sciences Caraga State University Agusan Del Norte Butuan City Philippines

ISBN: (纸本)9798400717352

This study introduces a dynamic event-handling system designed for hand gesture recognition in mobile augmented reality (AR) viewers. By repurposing low-cost virtual reality (VR) boxes in conjunction with mobile phones, the researchers aimed to facilitate hands-free interaction in AR environments. The system was developed using the Unity 3D game engine and integrated with ManoMotion for real-time gesture recognition, enabling the detection of ten distinct gestures, including Click, Drop, Pick, Grab, Swipe, and Release. Each gesture was mapped to dynamic events that allowed users to engage with virtual objects through natural hand movements, significantly enhancing the AR experience without reliance on physical controllers. The research confirms the viability of an affordable AR system that leverages intuitive hand-based controls while identifying limitations such as reduced gesture accuracy in low-light conditions and ergonomic challenges. The system achieved an impressive hand recognition accuracy of 95.13%. This study contributes to the accessibility of AR technology and lays the groundwork for future enhancements in gesture recognition and user interaction within mobile AR systems. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Augmented reality

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