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Pneumonia Detection in X-Ray Chest Images Based on Convolutional Neural Networks and Data Augmentation Methods 11

Pneumonia Detection in X-Ray Chest Images Based on Convoluti...

引用

11th international conference on Information and communication technologies for Ageing Well and e-Health, ICT4AWE 2025

作者： Dardouri, Samia Department of Computer Science College of Computing and Information Technology Shaqra University Saudi Arabia InnoV'COM Laboratory-Sup'Com University of Carthage Tunisia

ISBN: (纸本)9789897587436

Pneumonia, a widespread lung ailment, stands as a leading global cause of mortality, particularly affecting vulnerable demographics such as children under five, the elderly, and individuals with underlying health conditions. Accounting for a significant portion of childhood fatalities, at 18%, pneumonia remains a critical health concern. Despite advancements in imaging diagnostic methods, chest radiographs remain pivotal due to their cost-effectiveness and rapid results. The proposed model, trained on data sourced from a readily available Kaggle database, consists of two primary stages: image preprocessing and feature extraction/image classification. Utilizing a CNN model, the framework achieves remarkable performance metrics, with precision, recall, F1-score, and accuracy reaching 93%, 96%, 94%, and 96%, respectively. These results underscore the CNN model's effectiveness in pneumonia detection, showcasing superior consistency and accuracy compared to other pretrained deep learning models. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Adam Optimizer CNN Deep Learning Early Detection Feature Extraction Image Data Augmentation Pneumonia Infection

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Job Generator for Evaluating and Comparing Scheduling Algorithms for Modern GPU Clouds 15

Job Generator for Evaluating and Comparing Scheduling Algori...

引用

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

作者： Konopa, Michal Fesl, Jan Beránek, Ladislav Department of Data Science and Computing Systems Faculty of Agriculture and Technology University of South Bohemia České Budějovice Czech Republic

ISBN: (纸本)9789897587474

The steep technological and performance advances in GPU cards have led to their increasing use in data centers in the recent years, especially in machine learning jobs. However, high hardware performance alone does not guarantee (sub) optimal utilization of computing resources, especially when the cost associated with power consumption also needs to be increasingly considered. As consequence of these realities, various job scheduling algorithms have been and are being developed to optimize the power consumption in data centers with respect to defined constraints. Unfortunately, there is still no known, widely used, parametrizable dataset that serves as a de facto standard for simulating scheduling algorithms and the resulting ability to compare their performance against each other. The goal of this paper is to describe a simple job set generator designed to run on modern GPU architectures and to introduce the newly created data set suitable for evaluation the scheduling algorithms. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Scheduling algorithms

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SSL400 - A Comprehensive Word Level Dataset for Sinhala Sign Language Recognition 5

SSL400 - A Comprehensive Word Level Dataset for Sinhala Sign...

引用

5th international conference on advanced Research in computing, ICARC 2025

作者： Abhishek, Yohan Sumanathilaka, T.G.D.K. Informatics Institute of Technology School of Computing Colombo006 Sri Lanka

ISBN: (纸本)9798331530983

In the context of increasing digital accessibility and the need for inclusive communication technologies, the demand for automated sign language recognition has grown significantly. However, Sinhala Sign Language (SSL), used by the Sri Lankan deaf community, remains underexplored due to the lack of labelled datasets and the challenges of developing recognition models for low-resource languages. This study addresses this gap by introducing an SSL dataset, specifically curated to support real-time recognition of 384 commonly used words in daily and work-related contexts. The methodology for dataset creation involved expert consultations, a structured data collection process, and multi-step labelling. These steps ensured the accurate labeling of video data, which can be used for machine learning tasks like gesture recognition, sentence formation, and speech translation. The proposed dataset lays the foundation for SSL recognition models that are fast, lightweight, and optimized for low-resource environments. Additionally, we explore the performance of initial recognition models using this dataset, demonstrating its applicability in real-world scenarios. The dataset and research outcomes provide valuable resources for the development of inclusive AI-driven communication tools for the Sinhala-speaking deaf community. This contribution addresses the pressing need for better technological support for underrepresented languages in the field of sign language recognition and processing. © 2025 IEEE.

关键词： Multi-task learning

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AIAS: Experimental Evaluation of Spectrum Utilization Over Cognitive Radio Networks Using Artificial Intelligence (AI) Assisted Adaptive Searching Algorithm 5

AIAS: Experimental Evaluation of Spectrum Utilization Over C...

引用

5th IEEE international conference on Advances in Electrical, computing, communication and Sustainable technologies, ICAECT 2025

作者： Bharathi, P. Shyamala Shankar, A. Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798350356236

The AI-Assisted Adaptive Searching Algorithm (AIAS) enhances spectrum utilization in Cognitive Radio Networks (CRNs) by predicting and dynamically allocating available frequency bands to secondary users. Using the Kaggle Spectrum Dataset, AIAS employs supervised learning to forecast spectrum availability with a 91.3% average accuracy, outperforming traditional searching methods by approximately 13%. Additionally, reinforcement learning enables real-time decision-making for optimal frequency allocation, achieving an average spectrum utilization efficiency of 92.5% and interference-free allocations up to 95.1%. Compared to conventional algorithms, AIAS reduces latency by an average of 50%, achieving allocation times of approximately 15.2 milliseconds. These improvements demonstrate AIAS's capability to adapt in spectrum-dense environments, ensuring minimal interference with primary users and higher spectrum utilization efficiency. This study highlights the potential of AIAS to address the limitations of static allocation in CRNs and underscores the advantages of machine learning in dynamic spectrum management. Future research could focus on integrating advanced AI models, such as deep learning, to further optimize prediction accuracy and enhance the robustness of adaptive spectrum utilization in increasingly complex network environments. © 2025 IEEE.

关键词： Reinforcement learning

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Literature Review on Cloud-Based Service-Oriented Architecture for IEC 61499 Distributed control Systems 15

Literature Review on Cloud-Based Service-Oriented Architectu...

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

作者： Torres, Tomás Gonçalves, Gil Pinto, Rui Department of Informatics Engineering Faculty of Engineering University of Porto Porto Portugal SYSTEC ARISE Faculty of Engineering University of Porto Porto Portugal

ISBN: (纸本)9789897587474

The 4th Industrial Revolution has driven innovations in integrating Information technologies (IT) with Operations technologies (OT). This integration is essential for developing Cyber-Physical Production Systems (CPPS), which enhance distributed automation and optimize industrial production processes. The IEC 61499 standard facilitates this integration through its modularity, reusability, and interoperability, making it crucial for distributed control and system automation. Despite its advantages, IEC 61499’s application is predominantly at the Edge layer, limiting its functionality in higher layers such as the Cloud. To address this gap, Cloud-based Service-Oriented Architectures (SoA) have emerged as a key study area, offering modular, reusable, and scalable services extending beyond the Edge layer. This paper presents a comprehensive literature review focused on expanding the IEC 61499 applications to reconfigure CPPS, by integrating Cloud layer services through SoA. The review highlights advancements, challenges, and future directions in achieving greater modularity, interoperability, scalability, and abstraction within distributed control systems. By synthesizing current research, this work provides insights into the potential enhancements of CPPS using a Cloud-based SoA approach. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Service oriented architecture (SOA)

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Generating Accessibility: Using AI to Improve Higher Education for the Visually Impaired 17

Generating Accessibility: Using AI to Improve Higher Educati...

引用

17th international conference on Computer Supported Education, CSEDU 2025

作者： Schauer, Sophie Simbeck, Katharina Schüßler, Leon School of Computing Communication and Business HTW University of Applied Sciences Berlin Wilhelminenhofstraße Berlin Germany

ISBN: (纸本)9789897587467

Visually impaired students face many obstacles in higher education, including access to adapted course material. While accessibility is a legal requirement in many countries, its implementation is linked to practical challenges for educators. In this paper, we discuss the adaptation of existing course materials for blind students in a case study and propose using generative Artificial Intelligence to facilitate the creation of accessible educational materials, contributing to a more inclusive learning environment. We introduce and evaluate the tool TRAIL to generate accessible textual descriptions of lecture slides. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Students

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Edge computing and big data analysis integration framework in smart grid edge gateway

Edge computing and big data analysis integration framework i...

引用

2024 international conference on Physics, Photonics, and Optical Engineering, ICPPOE 2024

作者： Liu, Yuan Zhang, Wei Liu, Liguo Li, Xuehua Yang, Chenjie Wang, Yukui State Grid Information & Telecommunication Co. Ltd. Beijing branch Beijing China

ISBN: (数字)9781510689121

ISBN: (纸本)9781510689114

This study aims to enhance the data processing efficiency, real-time performance, and system reliability of smart grids by integrating edge computing and big data analysis in smart grid edge gateways. This study shows how advanced technologies like edge devices, edge computing nodes, big data analytics modules, and control systems can be utilized in a real grid setting to enhance operational efficiency and grid prediction ability through a comprehensive architecture design and implementation. In the research, we concentrated on data real-time processing, transmission mechanism, and system architecture design, and we validated the framework's efficiency with real cases. Studies indicate that the integration of edge computing and big data analysis in an organic manner can enhance the data processing abilities of the power grid, decrease delays, and offer robust backing for optimal power grid management. This framework is capable of satisfying the requirements of current smart grids, as well as possessing strong scalability and adaptability, providing a robust groundwork for the advancement of future smart grids. © 2025 SPIE.

关键词： Mobile edge computing

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A Greedy Dynamic Task Offloading and Service Management in V2V Networks 11

A Greedy Dynamic Task Offloading and Service Management in V...

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11th international conference on Vehicle Technology and Intelligent Transport Systems, VEHITS 2025

作者： Xing, Hanyang Chengdu China

ISBN: (纸本)9789897587450

This paper introduces an advanced framework for optimizing task offloading and service caching in Vehicle-to-Vehicle (V2V) communication networks. The proposed approach leverages a greedy algorithm to address key challenges such as offloading latency, energy consumption, and system overhead. By incorporating practical factors such as task size, server storage capacity, and task popularity, the framework efficiently allocates tasks, thereby reducing computational delays and enhancing network performance. The effectiveness of the algorithm is validated through comprehensive simulations that demonstrate significant improvements in both time efficiency and resource utilization compared to existing methodologies. The results underscore the potential for future advancements in V2V networks, particularly in enhancing network stability under high-speed conditions and developing robust communication systems that maximize the use of roadside computational resources. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Decision Tree Game Theory Knapsack Algorithm Vehicle-to-Vehicle communication

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Voice over Internet Protocol: Custom SIP Server with QoS Optimization for Real-Time communication 3

Voice over Internet Protocol: Custom SIP Server with QoS Opt...

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3rd international conference on Intelligent Data communication technologies and Internet of Things, IDCIoT 2025

作者： Dinesh Krishna, B.V. Yogendrasai, P. Rajeev, S. Rajagopal, Shinu M. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

VoIP is a revolutionary technology for transmission of voice over internet protocol than from plain telephony systems. But current VoIP solutions have some important issues which are packet loss, latency, and jitter especially when the network is in motion. This work outlines the design, implementation and performance of a locally developed VoIP system which includes a SIP Server Node, Sender Node and a Receiver Node. The SIP Server Node was designed nearly from the ground up to handle session initiation, packet forwarding, and adaptive QoS control. Both Sender and Receiver Nodes had facilities to record, compress and playback audio. The system’s performance was evaluated in a LAN environment, achieving significant improvements in Quality of Service (QoS) metrics: achieving low latency under 150 ms, 95% packet recovery and achieving a good audio quality with the MOS of 4.2. Evaluating the obtained results, it can be concluded that the proposed system is efficient in handling the issues of the packet-switched network and providing high-quality real time voice communication. © 2025 IEEE.

关键词： Packet loss

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A Comprehensive End-to-End Solution for Web Security with Cryptography, Multi-Factor Authentication, and Secure communication 3

A Comprehensive End-to-End Solution for Web Security with Cr...

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3rd international conference on Intelligent Data communication technologies and Internet of Things, IDCIoT 2025

作者： Kumar, Kanderi Johith Sai, Kandlapalli Aravind Reddy, Adapala Dharshan Reddy, Chinthamreddy Pranay Daiwik Rajagopal, Shinu M. Dept. of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

In today’s digital landscape, securing sensitive information has become an essential priority in the modern digital era for both individuals and organizations. This project introduces a comprehensive web application that integrates advanced encryption and decryption functionalities alongside multifactor authentication (MFA) and secure payment processing. The application supports various cryptographic algorithms, including AES, DES, Triple DES, Blowfish, etc., allowing users to securely encrypt and decrypt data through dedicated routes accessed over secure HTTPS connections. To further enhance security, robust multifactor authentication mechanisms, such as OTP-based challenge-response and QR-code-enabled 2FA, have been implemented to prevent unauthorized access to sensitive operations. The platform also incorporates PGP encryption powered by Keybase, enabling users to securely exchange encrypted emails. Additionally, a secure payment gateway is integrated using Stripe, ensuring sensitive payment data is encrypted and handled safely. With a strong focus on data integrity, user privacy, and modern web security standards, this project delivers an all-encompassing solution for safeguarding sensitive information and facilitating secure communication. By addressing common vulnerabilities and security risks, the platform stands as a reliable and scalable tool for data protection. © 2025 IEEE.

关键词： Authentication Protocol

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