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computing Midcurve with Multi-Layer and Convolutional Neural Networks

Computing Midcurve with Multi-Layer and Convolutional Neural...

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

作者： Sreenivasan, Prashanth Kulkarni, Yogesh H. Pune India

ISBN: (纸本)9798331512965

Midcurve computation: the dimension reduction of 2D thin polygon shapes to 1D curves is important for several Computer-Aided Design (CAD) and Computer-Aided Engineering (CAE) applications, particularly in finite element analysis and robot path planning. We advance the state-of-the-art by building on previous work on MidcurveNN, through two new neural architectures: a multi-layer dense network and a CNN-based architecture with skip connections. Through comparative analysis, we demonstrate that while the dense network shows limited improvements, the CNN-based architecture with skip connections achieves a tenfold reduction in average loss compared to existing methods. The proposed approach improves the quality of the generated Midcurves. © 2025 IEEE.

关键词： Convolutional neural networks

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Quantum computing Applications in Financial Modeling and Portfolio Optimization 1

Quantum Computing Applications in Financial Modeling and Por...

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

作者： Mohd, Sharif Dasgupta, Madhumita Akter, Fatema Arunachalam, Mahesh Prabu Sharma, Sakshi Prasanna, Ch.kumari Laxmi NDIM New Delhi Department of Finance Delhi India Amity Business School Amity University Kolkata India Islamia University College Department of Finance & Banking Chattagram Bangladesh Department of IT AustinTX United States University School of Management Kurukshetra University University Institute of Engineering and Technology Kurukshetra and Guest Faculty Kurukshetra India PG College Andhra Pradesh Bhimavaram India

ISBN: (纸本)9798331518578

In this decade the classical computers can surpass the computational power anticipated using quantum computers, bringing transformative advancements across multiple industries, with finance expected to be the first to reap the benefits. Notably, the quantum computer poised in the financial sector leveraging medium and long terms usually but sometimes in short term. The present study involves the quantum computing applications in financial modelling and portfolio optimization using classical convex optimization algorithmthat focus on the current advancement of quantum computationsin financial modelling. The key areas focused by quantum computing includes machine learning optimization and stochastic modelling. It explodes the quantum computing techniques adopted with solutions that can enhance the problem-solving skills in finance sector like fraud detection, natural language processing, portfolio optimization, risk modelling, derivative pricing that improves both efficiency and accuracy. Additionally, we examine the practicality of implementing these algorithms on near-term quantum computers across different hardware architectures and highlight their relevance to a diverse range of financial use cases. © 2025 IEEE.

关键词： Quantum computers

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Sign Language Recognition Using Convolutional Neural Network Based on VGG-16 Deep Learning Approach 5th

Sign Language Recognition Using Convolutional Neural Network...

引用

5th international conference on advances in information communication technology and computing, AICTC 2024

作者： Athish, M.J. Sowmya, S. Lakshaya, E. Preetha, S. Rishiya Shankar, S.U. Sendhil Kumar, K.S. School of Computer Science and Engineering Vellore Institute of Technology Vellore India

ISBN: (纸本)9789819761050

communication is a significant part of our lives, as it facilitates interaction among individuals. Language serves as a mode of communication for all individuals for expressing their thoughts and interpretations. However, hearing-impaired individuals often face hurdles in using spoken language. The technology for recognizing sign language made a commendable effort to improve communication levels among hearing-impaired individuals. In the current era of deep learning, which is a subset of machine learning, Convolutional Neural Network models have been developed and are now in use for gesture recognition. This recognition is based on the CNN model and VGG-16 model. It is used to hone the temporal features. The dataset used here is American Sign Language Dataset (A–Z and 0–9). The focus of this work is to develop a sign language recognition system to fulfill the need for communication of impaired people in society. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

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Function Scheduling with Data Security in Serverless computing Systems 17

Function Scheduling with Data Security in Serverless Computi...

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17th international conference on communication Systems and NETworkS, COMSNETS 2025

作者： Saha, Srestha Pandey, Arvind Addya, Sourav Kanti Brata Nath, Shubha Indian Institute of Information Technology Department of Computer Science and Engineering Guwahati India SRM Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu India National Institute of Technology Karnataka Department of Computer Science and Engineering Surathkal India

ISBN: (纸本)9798331531195

In serverless computing, the service provider takes full responsibility for function management. However, serverless computing has many challenges regarding data security and function scheduling. To address these challenges, we have proposed a system to secure the data of an end-user. We also aim to meet the quality of service (QoS) for the end-user requests. This work presents a Simulated Annealing-based optimization algorithm for function placement. Also, we have Hyperledger Fabric, a blockchain framework in the system architecture for securing the data of an end-user. We have conducted experiments in Amazon Elastic Compute Cloud (EC2) taking virtual machine instances. The experiments in Amazon EC2 indicate that the proposed system secures the data and enhances the end-user's QoS. © 2025 IEEE.

关键词： Simulated annealing

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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...

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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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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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Research and Application of Distribution Network’s Real-Time Line-Transformer Relationship Analysis Method Based on Switch Segment 1

Research and Application of Distribution Network’s Real-Tim...

引用

1st international conference on Intelligent Manufacturing and Cloud computing, ICIMCC 2024

作者： Huang, Shanshan Jiang, Houming Chen, Xingming Nari Information & Communication Technology Company Nanjing China

ISBN: (纸本)9781643685779

This paper presents an innovative real-time line-transformer relationship analysis method for distribution networks, which is based on real-time monitoring and analysis of switch segments. The aim is to overcome the limitations of traditional line-transformer relationship analysis methods in terms of accuracy, real-time performance and flexibility. This method includes six modules: real-time switch quantity acquisition and switch position identification, power and voltage data monitoring of switch segments, real-time analysis and update of line-transformer relationships, user grouping and updating, anomaly detection and alarm modules, system integration and application. By real-time tracking of changes in switch states in the distribution network and combining the response data of switch segments after switching, the line-transformer relationship can be accurately inferred and updated. Applying this method to the line loss calculation business of the grid resource business middle platform system, targeted experiments were conducted based on a designed typical distribution network and divided switch segments. The data shows that this method significantly reduces the packaging rate, makes line loss calculation more accurate and efficient and better meets business needs. © 2025 The Authors.

关键词： Distribution transformers

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Cloud computing in Enhancing the Efficiency and Integration of Alternative Energy Systems 2

Cloud Computing in Enhancing the Efficiency and Integration ...

引用

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

作者： Sahoo, Amiya Kumar Prusty, Sucharita Jayasingh, Suvendra Kumar Swain, Asish Kumar Mohanta, Hemanta Kumar Aryan Institute of Engineering and Technology Odisha Bhubaneswar India Institute of Management and Information Technology BPUT Odisha Cuttack India

ISBN: (纸本)9798331530389

In response to growing environmental concerns and the need for sustainable development, alternative energy systems have emerged as crucial solutions to the problems associated with fossil fuels. This research focuses on the significant role cloud computing plays in improving the efficiency and integration of various alternative energy systems such as solar, wind, hydropower, biomass, geothermal, and tidal/wave energy. The study explores how cloud computing technologies enable real-time data processing, storage, and analysis of the large datasets generated by these renewable energy sources, thus optimizing their performance and integration into the energy grid. Cloud computing provides advanced data management tools that are vital for managing the variable and intermittent nature of renewable energy production. By utilizing cloud-based platforms, energy producers can achieve improved forecasting, load balancing, and energy distribution, which are essential for enhancing efficiency and reliability. Additionally, this research highlights how cloud computing fosters collaboration and innovation by offering a scalable and flexible infrastructure. This infrastructure supports the development of new technologies and applications within the renewable energy sector, promoting continuous advancements and breakthroughs. This research underscores the crucial role of cloud computing in advancing a sustainable energy future. © 2025 IEEE.

关键词： Cloud platforms

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Dynamic Bio-information Image Recognition of Cancel Cell Death based on Parallel Multiple Artificial Intelligence Modules 27

Dynamic Bio-Information Image Recognition of Cancel Cell Dea...

引用

27th international conference on Advanced communications technology, ICACT 2025

作者： Jian, Ming-Shen Ye, Yi-Ling Chung, Wen-Yu Li, Wen-Xuan Lin, Yan-Ting Huang, Bo-Yuan Sikandar, Javeria Chang, Yu-Jung CCIS Lab. Dept. of CSIE National Formosa University Yunlin632 Taiwan Dept. of Biotechnology National Formosa University Yunlin632 Taiwan

ISBN: (纸本)9791188428137

This investigation purpose a unique Dynamic Bio-information Image Recognition System (DBIRS) built for the real-time monitoring of cancer cell apoptosis produced by available medical therapy. Utilizing advances in microscopy, AI-based image recognition, and parallel computing across distributed edge devices, the proposed system dramatically boosts the precision and efficiency of cellular investigation. By deploying numerous AI modules adapted to distinct cellular states, the system provides automatic, high-accuracy recognition of morphological changes in cancer cells, hence minimizing the need on manual procedures. This technique offers remote monitoring and fast data processing via cloud integration, permitting continuous observation and timely intervention. The system's efficiency is proven through trials on K-562 cells, where it attained a recognition accuracy of 97.41%. These outcomes underline the potential of the proposed method to refine cytotoxicity assays, delivering a strong tool for increasing the efficacy and safety of immune cell treatments in clinical and research settings. © 2025 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.

关键词： Diseases

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IoT-Enabled Asthma Trackers for Children with KNN for Improved Breathing Control 5

IoT-Enabled Asthma Trackers for Children with KNN for Improv...

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5th IEEE international conference on advances in Electrical, computing, communication and Sustainable Technologies, ICAECT 2025

作者： Sathyanathan, P. Balachander, K. Pandey, Pramod Srinivasan, V. Prasanna Ganeshbabu, T.R. Muthulekshmi, M. Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Electrical and Electronics Engineering Tamil Nadu Chennai India R.M.K. College of Engineering and Technology Department of Artificial Intelligence and Data Science Tamil Nadu Chennai India Nagpur Campus Maharashtra Pune India R.M.D. Engineering College Department of Information Technology Tamil Nadu Chennai India Department of Electronics and Communication Tamil Nadu Namakkal India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Biomedical Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350356236

Managing asthma in children is a complex task that needs constant vigilance and personalized treatments to get the best potential control. For better respiratory management, an Internet of Things (IoT)-enabled pediatric asthma tracking system that uses machine learning (ML) methods, particularly for K-nearest neighbors (KNN), is presented. The system's integration of wearable sensors, which continuously monitor vital signs and environmental conditions, provides a comprehensive view of the child's respiratory health. Asthma exacerbation causes, and trends may be discovered by analyzing the obtained data using KNN algorithms. Analysis allows for the generation of real-time warnings and feedback, allowing caregivers to take proactive steps in reducing risks and optimizing treatment procedures. Our IoT-enabled method for improving respiratory control and decreasing asthma-related consequences in children is feasible and effective in pilot research, including children with asthma. Our research highlights the promise of IoT devices and ML algorithms to transform how pediatric asthma is treated by providing tailored, evidence-based treatments that lead to better health outcomes. © 2025 IEEE.

关键词： Pediatrics

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