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检索条件"任意字段=International Conference on Information Technology - Coding and Computing"

共 195356 条记录，以下是261-270 订阅

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Enhancing Heart Disease Prediction with GANs in Clinical Decision Support Systems 6

Enhancing Heart Disease Prediction with GANs in Clinical Dec...

引用

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

作者： Periya Nayaki, A. VishwaShree, S.V. Mithra, N. Priyadharshini, C. Thanabal, M.S. Penyameen, K. Department of Information Technology Velammal College of Engineering and Technology Madurai India Department of Computer Science and Engineering PSNA College of Engineering and Technology Dindigul India

ISBN: (纸本)9798331522667

Heart disease remains a leading global cause of mortality, emphasizing the need for innovative diagnostic solutions. Traditional Clinical Decision Support Systems (CDSS) often struggle with limited datasets and imbalances, impacting prediction accuracy. This study proposes a novel approach by integrating Conditional Generative Adversarial Networks (CGANs) into a CDSS framework, enhancing its ability to generate high-quality synthetic data. The augmented dataset is utilized to train a Gradient Boosting model capable of identifying subtle patterns in patient data. This methodology significantly improves prediction precision and addresses limitations of traditional techniques. The results demonstrate the model's superiority inaccurately identifying heart disease risks, making it a valuable tool for early diagnosis and clinical decision-making. By combining advanced machine learning techniques with domain- specific innovations, this research sets a new benchmark in the application of AI for healthcare. © 2025 IEEE.

关键词： Generative adversarial networks

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Regression analysis based on driving schools in Haikou 24

Regression analysis based on driving schools in Haikou

引用

8th international conference on Electronic information technology and Computer Engineering, EITCE 2024

作者： Yang, Darun Yang, Daqing Yang, Dashuai Yang, Dacai College of Information Engineering Hainan Vocational University of Science and Technology Hainan Haikou China Longjie Town Tianqiao Primary School Guizhou Bijie China College of Humanities and Technology Guizhou University for Nationalities Guizhou Guiyang China Guiyang University of Information Technology Guizhou Guiyang China

ISBN: (纸本)9798400710094

With the development of society and the growth of population in Haikou city, the driving school market in Haikou faces a series of challenges such as unreasonable teaching methods, cumbersome registration processes, non-standard training sites, overly long learning periods, delayed handling of student complaints, and lack of supervision. Using univariate regression and ridge regression to analyze the relationship between the number of exam takers and the number of passers, predicting the number of passers with a certain number of exam takers, providing reference for Haikou local undergraduate students and social individuals when registering for driving schools. Also, it aims to provide scientific decision-making basis for driving school managers, decision-makers, and practitioners, and predict future trends. © 2024 Copyright held by the owner/author(s).

关键词： Students

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Delay-Optimized Task Scheduling Based on Deep Reinforcement Learning in computing Power Networks 3rd

Delay-Optimized Task Scheduling Based on Deep Reinforcement ...

引用

3rd international conference on Machine Learning, Cloud computing and Intelligent Mining, MLCCIM 2024

作者： Tang, Qinqin Xu, Deyun Xie, Renchao Feng, Li Chen, Tianjiao Huang, Tao Beijing University of Posts and Telecommunications Beijing China China Mobile Research Institute Beijing China

ISBN: (纸本)9789819624676

With the rapid advancement of information and communication technology, there arises an increasing demand for heightened computing capabilities to facilitate a myriad of intelligent services. The computing power network (CPN) amalgamates an array of resources including cloud and edge devices to enable collaborative sensing, routing, and scheduling. This integration significantly amplifies the utilization of computing network resources while concurrently augmenting service quality. In the realm of multi-node distributed joint computing within CPNs conventional scheduling methodologies frequently neglect the interplay between computing and the network, resulting in suboptimal task scheduling. To address this issue, this study proposes a delay-optimized task scheduling mechanism based on deep reinforcement learning. Simulation results demonstrate that this framework achieves faster convergence speed, particularly under dual-depth networks, outperforming other algorithms in reducing system delays, energy and enhancing scheduling efficiency. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： computing power

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Deep Learning Model for Predicting Basket-Ball Player Injuries Using VGG16

Deep Learning Model for Predicting Basket-Ball Player Injuri...

引用

2025 international conference on computing for Sustainability and Intelligent Future, COMP-SIF 2025

作者： Avula, Sashikanth Reddy Haarika, Annapareddy Raghuram, Mahatee Rahul, S.K. Nitte Meenakshi Institute of Technology Department of Mca Bengaluru India Bms Institute of Technology and Management Department of Information Science and Engineering Bengaluru India

ISBN: (纸本)9798331538538

This growing need for player safety in sports has spurred the creation of newer models for predictive analysis. The project involves predicting the injury risk of basketball players using foot images and image classification techniques. Since VGG16 is a popular Convolutional Neural Network (CNN) whose architecture has been shown to perform well in image recognition, this model is used in this study. The target is to pinpoint and categorize movements more susceptible to inducing injuries and further recommend tactical alterations in training and gameplay. The scheme achieves high accuracy for predicting potential injury risks by finetuning the VGG16 model. The project presents how deep learning can be applied in sports analytics with the objective to reduce injury instances and augment player safety. The discussed methodology predicts the incidence of injury and can be a useful resource to coach- and medial staff to help formulate prevention plans. © 2025 IEEE.

关键词： Convolutional neural networks

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The Emergent Role of Artificial Intelligence as Tool in Conducting Academic Research 16

The Emergent Role of Artificial Intelligence as Tool in Cond...

引用

16th international conference on Society and information Technologies, ICSIT 2025

作者： Ferdousi, Bilquis School of Information Security and Applied Computing College of Engineering and Technology Eastern Michigan University YpsilantiMI United States

ISBN: (纸本)9781950492831

Academic and non-academic research institutes are the two key global sectors that are accomplishing the research agenda. This paper focuses on the implications of using AI tools in academic research. Academic institutions conduct rigorous research to find the impact of different issues on society. Artificial Intelligence (AI) impacts society, organizations, and governance. AI has significantly transformed various domains, including higher education and academic research. Because of its effect on research and education in multidisciplinary fields, there is increasingly significant interest in finding AI's effect on research. In this context, there is a growing concern to find the impact of AI on research in academic institutions. This article aims to engage in a rigorous dialogue on AI’s role in academic research. Conducting a systematic literature review of AI's impact on academic research, this study aims to investigate 1) how AI tools are affecting academic research and 2) ethical dilemmas in using AI in academic research. By exploring the advantages and challenges of using innovative applications of AI tools in academic research, this study will give stakeholders, especially researchers, educators, and students, a comprehensive view of how AI could shape educational and interdisciplinary research practices in the future. © 2025 international conference on Society and information Technologies. All Rights Reserved.

关键词： Academic Research Artificial Intelligence Ethical Concern

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Infrastructure as Code: technology Review and Research Challenges 15

Infrastructure as Code: Technology Review and Research Chall...

引用

15th international conference on Cloud computing and Services Science, CLOSER 2025

作者： Pahl, Claus Gunduz, Niyazi Gokberk Sezen, Övgüm Can Ghamgosar, Ali El Ioini, Nabil Free University of Bozen-Bolzano Bolzano39100 Italy University of Nottingham Semenyih43500 Malaysia

ISBN: (纸本)9789897587474

The quality of software management in infrastructure operations for application software is important as automation in software operations continues to grow. Infrastructure as Code (IaC) refers to a systematic, technology-supported approach to manage deployment infrastructure for software applications. Sample contexts are general software automation, but also cloud and edge and various software-defined networking applications. DevOps (development and operations) practices, which are already applied in the Infrastructure as Code (IaC) context, need to be extended to cover the whole IaC life cycle from code generation to dynamic, automated control. The ultimate objective would range from IaC generation to full self-adaptation of IaC code in an automated setting. We review available IaC technologies based on a comprehensive comparison framework to capture the state-of-the-art. We also introduce an IaC-specific DevOps process. This serves as a basis to identify open research challenges. A discussion of defect categories is at the centre of this process. Copyright © 2025 by SCITEPRESS - Science and technology Publications, Lda.

关键词： Enterprise software

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Analysis of Technological Journey of the Film Industry and Regression Modeling for Predicting Box Office Collection 3

Analysis of Technological Journey of the Film Industry and R...

引用

3rd international conference on Intelligent and Innovative Technologies in computing, Electrical and Electronics, IITCEE 2025

作者： Kawarkhe, Rajnish Khaire, Prajwal Khilari, Sahil Mane, Jaydip Sukte, Chudaman Wankhade, Shalini Vishwakarma Institute of Information Technology Pune India

ISBN: (纸本)9798331515911

In this paper we have analyzed the important technology evolutions that have significantly impacted the film industry. Pre-production of films to post-production, each stage of filmmaking has been greatly enhanced by technological advancements. The journey from silent era and black-and-white pictures to high-defination films has allowed filmmakers to immerse audiences in their stories. This study explores how these innovations have not only reduced the need for extensive human labor but also improved the overall quality of films. Furthermore, the analysis will demonstrate how these advancements have transformed the audience's viewing experience, shaping modern cinema and its future directions. Additionally, the paper will explore the potential innovations that can further bring the revolution in the industry in coming years. Further we have explore this technological evolution with a specific focus on VFX and the formats in which movie was released, by employing linear regression model to predict the box office collection based on these. © 2025 IEEE.

关键词： Animation

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5G Channel Estimation for downlink SISO channels using Convolutional Neural Networks 3

5G Channel Estimation for downlink SISO channels using Convo...

引用

3rd international conference on Intelligent and Innovative Technologies in computing, Electrical and Electronics, IITCEE 2025

作者： Aruna, R. Pushpa Mala, S. Kulkarni, Keerti Dayananda Sagar University Skit India Dayananda Sagar University India Bnm Institute of Technology India

ISBN: (数字)9798331515911

ISBN: (纸本)9798331515911

Channel estimation involves identifying the characteristics of a communication channel, specifically its impulse or frequency response. This information is essential for the receiver to reduce the channel's impact and accurately interpret the transmitted signals. This research presents a deep learning approach developed for channel estimation in a 5G SISO network. The Root Mean Square Error (RMSE) is used as a performance measure to evaluate the effectiveness of the implemented regression model. The outcomes are then contrasted with those from pilot-based linear channel estimation and perfect estimation methods. The findings reveal that the neural network model produces a lower RMSE value (0.022), showcasing its enhanced performance compared to the alternative methods in channel estimation. © 2025 IEEE.

关键词： Convolutional neural networks

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The Microservice Based Architecture for IoT Systems in Agriculture and Aquaculture 24

The Microservice Based Architecture for IoT Systems in Agric...

引用

14th international conference on information Communication and Management, ICICM 2024

作者： Truong, Thai Minh Huynh, Khang Quy Ngo, Thao Thi Thu Luu, Ca Le, Bang Minh College of Communication and Information Technology Can Tho University Can Tho Viet Nam College of Communication and Information Technology Can Tho University Soc Trang Viet Nam College of Communication and Information Technology Can Tho University Tra Vinh Viet Nam College of Communication and Information Technology Can Tho University Vinh Long Viet Nam

ISBN: (纸本)9798400717475

The rapid advancement of Internet of Things (IoT) technologies presents significant opportunities to enhance agriculture and aquaculture practices. This paper proposed a software architecture designed based on microservices to address the complex and evolving requirements of contemporary agriculture and aquaculture systems locations. These systems demand a versatile platform capable of integrating a wide range of functionalities, including environmental monitoring, aquaculture management, and comprehensive record-keeping for crops and aquatic life. The proposed IoT system employs a microservice architecture that ensures modularity, scalability, and flexibility. This approach facilitates the seamless integration of new services and features, easy adaptation to existing systems, and efficient reuse of established components. The microservice-based architecture has been successfully implemented in the TC2 project at Can Tho University under the Japan international Cooperation Agency (JICA) initiative. The project is in remote areas through the deployment of a network of sensor and actuator nodes, supported by a robust backend and user-friendly Front End applications. This implementation demonstrated notable improvements in operational efficiency and resource management. By leveraging edge computing for real-time data processing and integrating cloud-based analytics, the system achieved reduced response times and minimized data transmission costs. The modularity of the microservices architecture also enabled easy scalability and adaptability to change environmental conditions. The success of this implementation highlights the potential of microservices-based IoT solutions to drive innovation and enhance practices in agriculture and aquaculture, laying a strong foundation for future advancements in these fields. © 2024 Copyright held by the owner/author(s).

关键词： Aquaculture

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Thangka Image Object Detection Method Based on Improved YOLOv8 24

Thangka Image Object Detection Method Based on Improved YOLO...

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

作者： Xian, Yukai Zhao, Qijun Yang, Xin Gao, Dingguo School of Information Science and Technology Tibet University Lhasa Tibet China

ISBN: (纸本)9798400717482

This paper explores object detection techniques in Thangka images using an improved YOLOv8 algorithm. To address challenges such as unpredictable occlusions and damages, significant variations in artistic styles, and the difficulty of detecting small objects in Thangka images, this study proposes an enhanced YOLOv8 algorithm. By introducing the Focus Self-Attention mechanism, the algorithm effectively captures long-range dependencies within the images. The paper also introduces the HAFM module, which enhances the model's spatial and channel awareness. The experiments, conducted on a dataset of 3,747 Thangka images, show that the improved algorithm achieves mAP@0.5 and mAP@0.5:0.95 scores of 91.5% and 53.5%, respectively, significantly outperforming traditional methods. The findings demonstrate that the enhanced YOLOv8 algorithm can more accurately identify various objects in Thangka images, offering valuable technical support for the digital preservation and development of Thangka art. © 2024 Copyright held by the owner/author(s).

关键词： Thangka

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