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共 294422 条记录，以下是241-250 订阅

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An Efficient Hybrid Deep Learning Model for Detecting Musculoskeletal Abnormalities

An Efficient Hybrid Deep Learning Model for Detecting Muscul...

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2025 ieee international conference on Computational, Communication and Information Technology, ICCCIT 2025

作者： Deo, Arpit Gupta, Priyasha Deveradi, Karnika Patidar, Kashish Kumawat, Ashish Malik, Pankaj Medi-Caps University Department of Computer Science and Engineering Madhya Pradesh Indore453331 India Institute of Engineering & Technology Devi Ahilya Vishwavidyalaya Department of Computer Engineering Madhya Pradesh Indore452017 India

ISBN: (纸本)9798331512965

Deep Convolutional Neural Networks (DCNNs) have made tremendous advances in healthcare, but their limited perceptual capacities make it difficult to capture extensive structural details. To solve this restriction, this study presents a new technique which integrates the benefits of EfficientNet to perform local data extraction with DenseNet201 for processing global characteristics in pictures. The MURA dataset, which contains 40,005 radiographic pictures, is used in the project with the goal of enhancing radiographic image categorization, notably for identifying Musculoskeletal disorders. The goal of the project is to accomplish a more thorough analysis of radiological pictures by successfully collecting global as well as local information via the fusion of EfficientNet and DenseNet201. The proposed approach shows positive outcomes, with the combined approach obtaining an overall accuracy of 96.38% on the test dataset and a sensitivity of 0.90. © 2025 ieee.

关键词： DCNNs DenseNet201 EfficientNet Hybrid Model MURA

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Sampling-Based Density Peaks Clustering for Energy-Aware Industrial IoT Networks

Sampling-Based Density Peaks Clustering for Energy-Aware Ind...

引用

2025 ieee international Students' conference on Electrical, Electronics and computer science, SCEECS 2025

作者： Rajkumar, S. Gopalakrishnan, R. Shreeraksha, T.S. Dhanaraj, S. Kabiyashwanth, V. K. S. Rangasamy College of Technology Computer Science and Engineering 637 215 India K. S. Rangasamy College of Technology Electrical and Electronics Engineering 637 215 India

ISBN: (纸本)9798331529833

In Industrial Internet of Things (IIoT) settings, effective data processing and energy management are essential due to the resource-limited characteristics of the linked equipment. This research introduces a unique Sampling-Based Density Peaks Clustering (SDPC) algorithm designed for energy-efficient clustering in IIoT networks. The suggested method improves classic Density Peak Clustering by incorporating a sampling mechanism that decreases computational burden while preserving excellent clustering precision. SDPC efficiently clusters devices by determining cluster centers through local density and distance parameters, hence reducing communication costs and prolonging the network's operational lifespan. The energy consumption model is integrated into the clustering process, prioritizing devices with greater energy reserves as cluster heads, hence enhancing energy load distribution throughout the network. Simulation results indicate that SDPC realizes substantial enhancements, featuring a 30% decrease in energy usage and a 25% augmentation in network durability relative to leading clustering methods. This method has significant potential for enhancing energy management in IIoT networks, facilitating more sustainable and scalable industrial processes. © 2025 ieee.

关键词： Energy utilization

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Research on Low Frequency Stability of Photovoltaic Connected High Speed Traction Power Supply System in Light Load Scenarios 5

Research on Low Frequency Stability of Photovoltaic Connecte...

引用

5th ieee international conference on Power, Electronics and computer Applications, ICPECA 2025

作者： Yang, Yixia Wang, Ying Li, Jiahao Xie, Ziyun Mu, Xiuqing Wang, Wenwen College of Intelligent Manufacturing Gansu Industry Polytechnic College Tianshui China School of Automation and Electrical Engineering Lanzhou Jiaotong University Lanzhou China

ISBN: (纸本)9798331533694

Low-frequency oscillations are a common issue in traction power supply systems, and the integration of photovoltaic (PV) systems exacerbates the coupling and nonlinearity within these systems, leading to a complex photovoltaic-Train-network coupled system that increases the likelihood of electrical parameter mismatches. This paper investigates the low-frequency stability of the system during the photovoltaic integration process under light-load conditions in a single-Arm traction power system. The study first analyzes the topology and operational principles of integrating photovoltaic systems into the traction power supply system via a back-To-back inverter. Small-signal modeling techniques are then employed to derive the mathematical models of the photovoltaic system, the back-To-back inverter, and the train-network system. Based on the source-load relationship and the equivalent impedances of each subsystem, the coupling matrix of the photovoltaic-Train-network system is established. The low-frequency stability of the system under the light-load scenario is analyzed, and the effects of various control strategies of the photovoltaic system on system stability are assessed using the extended forbidden zone criterion. Finally, the effectiveness of the stability analysis is verified through StarSim HIL semi-physical testing. © 2025 ieee.

关键词： Frequency stability

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Collision Prevention System - Specializing in Animals Equipped with Distance Estimation

Collision Prevention System - Specializing in Animals Equipp...

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2025 ieee international Students' conference on Electrical, Electronics and computer science, SCEECS 2025

作者： Savithri, C.N. Nandhini, R. Harini, R. Lekha, C. Nithya Vishnu, V. Sri Sairam Engineering College Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798331529833

The rising incidence of vehicle-animal collisions poses a serious threat to both human safety and wildlife. This paper presents a comprehensive approach to collision avoidance and animal detection using computer vision techniques, with a specific focus on generic animals. Our system employs a trained convolutional neural network (CNN) model to accurately detect animals in real-time from input video streams. The methodology integrates image processing techniques to identify animals within complex backgrounds and estimate their distance from the vehicle. A distance threshold calculation is incorporated to dynamically evaluate collision risk. Upon detecting an animal within a defined proximity, the system initiates a breaking and alert mechanism to mitigate collision risks. This automated solution not only enhances road safety but also contributes to wildlife conservation efforts. Experimental results demonstrate the system's high detection accuracy and robustness in diverse environments, affirming the potential for scalable implementation in rural and wildlife-prone areas. This study contributes to advancing collision avoidance technology through the integration of AI- driven visual processing and real-time alert systems. © 2025 ieee.

关键词： Invertebrates

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Inclusive Communication for Arabic Notation: Decoding Lebanese Sign Language Using Gesture Recognition

Inclusive Communication for Arabic Notation: Decoding Lebane...

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2025 international conference on Control, automation, and Instrumentation, IC2AI 2025

作者： Abdallah, Ali Abdellatif, Amine Nader, Joelle Said, Jad Al Sultan, Lyne American University of Science and Technology Department of Computer Science Beirut Lebanon

ISBN: (纸本)9798331529604

Effective communication is indispensable for human connection, learning, and social engagement. However, for those with physical disabilities, particularly the deaf and mute community, verbal communication becomes a significant challenge. Expressing thoughts becomes complicated when sign language, a primary mode of communication for this community, is not widely understood. While devices exist to convert sign language into text and speech, they are predominantly designed for English-spoken people. In this work, we focus on identifying the Arabic hand sign language, a unique and regionally distinctive sign language, that has not garnered much attention from foreign recognition systems. We study the characteristics of the above-mentioned sign language and try to convert it into speech and text. We research, investigate, implement, test, and evaluate an online real-time Arabic Sign Language interpreter based on gesture recognition, as an attempt to revolutionize accessibility for the Lebanese deaf and mute, reducing communication barriers in education, healthcare, and various sectors. © 2025 ieee.

关键词： Gesture recognition

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MEIC: Re-thinking RTL Debug automation using LLMs 24

MEIC: Re-thinking RTL Debug Automation using LLMs

引用

43rd international conference on computer-Aided Design, ICCAD 2024

作者： Xu, Ke Sun, Jialin Hu, Yuchen Fang, Xinwei Shan, Weiwei Wang, Xi Jiang, Zhe National Center of Technology Innovation for EDA School of Integrated Circuits Southeast University China Department of Computer Science University of York United Kingdom

ISBN: (纸本)9798400710773

The deployment of Large Language Models (LLMs) for code debugging (e.g., C and Python) is widespread, benefiting from their ability to understand and interpret intricate concepts. However, in the semiconductor industry, utilising LLMs to debug Register Transfer Level (RTL) code is still insufficient, largely due to the underrepresentation of RTL-specific data in training sets. This work introduces a novel framework, Make Each Iteration Count (MEIC), which contrasts with traditional one-shot LLM-based debugging methods that heavily rely on prompt engineering, model tuning, and model training. MEIC utilises LLMs in an iterative process to overcome the limitation of LLMs in RTL code debugging, which is suitable for identifying and correcting both syntax and function errors, while effectively managing the uncertainties inherent in LLM operations. To evaluate our framework, we provide an open-source dataset comprising 178 common RTL programming errors. The experimental results demonstrate that the proposed debugging framework achieves fix rate of 93% for syntax errors and 78% for function errors, with up to 48x speedup in debugging processes when compared with experienced engineers. The Repo. of dataset and code: https://***/SEU-ACAL/reproduce-MEIC-ICCAD. © 2024 Copyright is held by the owner/author(s).

关键词： Program debugging

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K-Gate Lock: Multi-Key Logic Locking Using Input Encoding Against Oracle-Guided Attacks 25

K-Gate Lock: Multi-Key Logic Locking Using Input Encoding Ag...

引用

30th Asia and South Pacific Design automation conference, ASP-DAC 2025

作者： Lopez, Kevin Rezaei, Amin Computer Engineering and Computer Science Department California State University Long Beach United States

ISBN: (纸本)9798400706356

Logic locking has emerged to prevent piracy and overproduction of integrated circuits ever since the split of the design house and manufacturing foundry was established. While there has been a lot of research using a single global key to lock the circuit, even the most sophisticated single-key locking methods have been shown to be vulnerable to powerful SAT-based oracle-guided attacks that can extract the correct key with the help of an activated chip bought off the market and the locked netlist leaked from the untrusted foundry. To address this challenge, we propose, implement, and evaluate a novel logic locking method called K-Gate Lock that encodes input patterns using multiple keys that are applied to one set of key inputs at different operational times. Our comprehensive experimental results confirm that using multiple keys will make the circuit secure against oracle-guided attacks and increase attacker efforts to an exponentially time-consuming brute force search. K-Gate Lock has reasonable power and performance overheads, making it a practical solution for real-world hardware intellectual property protection. © 2025 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.

关键词： Locks (fasteners)

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A Scalable and Secure Facial Recognition Attendance System Leveraging CNN Algorithms for Real-Time Accuracy and Efficiency

A Scalable and Secure Facial Recognition Attendance System L...

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2025 ieee international Students' conference on Electrical, Electronics and computer science, SCEECS 2025

作者： Kumar, Aakash Sharma, Jiya Renjith, P.N. Vellore Institute of Technology School of Computer Science and Engineering India

ISBN: (纸本)9798331529833

The facial recognition attendance system represents a modern approach to attendance tracking, designed to improve efficiency, accuracy, and security in various organizational settings. Advanced biometric technologies are leveraged to capture and encode facial features, creating unique digital identifiers for each individual. The methodology employs cutting-edge facial recognition algorithms powered by convolutional neural networks (CNNs) with a 99.5% recognition accuracy rate. These algorithms extract and encode facial vectors with sub-millisecond latency, which are then compared in real-time against a secure, encrypted database of preregistered individuals. Upon a successful match, the system automatically records the attendance, ensuring an accurate and efficient process. With an intuitive web interface built on ReactJS and a backend supported by *** and MongoDB, the system provides seamless access to attendance records and administrative functionalities. The entire attendance recording process is optimized for speed, typically completing within two seconds per individual. Additionally, advanced anti-spoofing measures and integration support with existing HR management systems redefine traditional attendance management practices with a scalable, robust, and secure solution. (Abstract) © 2025 ieee.

关键词： Efficiency

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Economic And Emission Load Dispatch Using Modified Particle Swarm Optimization

Economic And Emission Load Dispatch Using Modified Particle ...

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2025 ieee international Students' conference on Electrical, Electronics and computer science, SCEECS 2025

作者： Dhurve, Rajesh Kumar Tomar, Shilpi Thakur, Shivendra Singh Sharma, C.S. Samrat Ashok Technological Institute Department of Electrical Engineering M.P Vidisha464001 India

ISBN: (纸本)9798331529833

The modern power system has evolved in complexity, with increasing interconnections and rising power demands. The focus has shifted towards improving performance, enhancing customer satisfaction, and delivering low-cost, reliable, and clean energy. In light of these changes, the scarcity of energy resources, environmental concerns, and rising generation costs have underscored the need for optimal economic dispatch (ED). Since power stations vary in distance from load centers and have differing fuel cost functions, the distribution of load must be optimized to minimize generation costs. This paper presents the economic dispatch problem is addressed for three and six-unit systems using MPSO, with comparisons to conventional methods for cases both with and without transmission losses. Results show that MPSO outperforms traditional optimization methods, which often converge to local optima. © 2025 ieee.

关键词： Clean energy

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A Trapezoidal-Structured Switched-Capacitor Balancing Circuit for Li-ion Battery Energy Storage System

A Trapezoidal-Structured Switched-Capacitor Balancing Circui...

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2025 ieee international Students' conference on Electrical, Electronics and computer science, SCEECS 2025

作者： Sahoo, Abhaya Kumar Sankaranarayanan, V. National Institute of Technology Department of Electrical and Electronics Engineering Tiruchirappalli India

ISBN: (纸本)9798331529833

The existing switched capacitor (SC)-type equalizers are less reliable and inefficient because of their bulkiness and high cost. Therefore, to suppress the drawbacks of existing switched capacitor equalizers (SCEs), a Trapezoidal-Structured SCE (TSSCE) is proposed with optimal cost, compact size, good efficiency, and better equalizing speed. The constructional feature of the proposed equalizer allows it to provide multiple optimal balancing paths with a minimal number of capacitors. An asymptotic relationship of the effective resistance model is presented, which gives an in-depth idea about the behavior of capacitors and switches in slow and fast switching limit regions. A simulation model is made, with four cells connected in series. Simulation analysis ensures the performance of the proposed converter. TSSCE achieves a better equalization speed and efficiency with only n capacitors for n number of cells, making the topology cost-effective and faster than the existing equalizers. © 2025 ieee.

关键词： Capacitor bank

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