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检索条件"任意字段=3rd International Conference on Wireless Algorithms, Systems and Applications"

共 12570 条记录，以下是61-70 订阅

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A Paradigm Shift in Real-Time Detection: The YOLOv7 Approach to Trainable Freebie Optimization 3

A Paradigm Shift in Real-Time Detection: The YOLOv7 Approach...

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3rd international conference on Electronics and Renewable systems, ICEARS 2025

作者： Vinitha, A. Jeevitha, S. Kumar, N.B. Mahesh Sathish Kumar, L. Saravanan, D. Karpagam Academy of Higher Education Department of Computer Applications Tamilnadu Coimbatore India Kalasalingam Academy of Research and Education Department of Computer Science and Information Technology Krishnankoil Tamilnadu Virudhunagar India Hindusthan Institute of Technology Computer Science and Engineering Tamil Nadu Coimbatore India Madhya Pradesh Sehore India

ISBN: (纸本)9798331509675

Significant progress has been made in real-time object detection, with YOLOv7 emerging as a state-of-the-art model that achieves the highest levels of accuracy and speed. This study combines Bag-of-Freebies (BoF) strategies with YOLOv7 to improve performance without incurring extra computational expenses. Our tests show that adding BoF preserves real-time inference capabilities while increasing mAP@0.5 by 3.5%. The accuracy and FPS of YOLOv7 with BoF are superior to those of the current YOLO-based models (YOLOv4, YOLOv5, YOLOv6). According to the results, YOLOv7 with BoF sets a new standard for real-time object detection by achieving a mAP@0.5 of 55.3% and 83 FPS on the COCO dataset. © 2025 IEEE.

关键词： Contrastive Learning

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Minimization of Energy Consumption Using Optimum Resource Allocation Scheme in D2D Communication for IoT applications 3rd

Minimization of Energy Consumption Using Optimum Resource Al...

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3rd international conference on Machine Vision and Augmented Intelligence, MAI 2023

作者： Pandey, Krishna Chandra, Saurabh Sharma, Vipin Arya, Rajeev Wireless Sensor Network Lab Department of Electronics and Communication Engineering National Institute of Technology Bihar Patna800005 India

ISBN: (纸本)9789819743582

D2D communication plays a vital role in the Internet of Things within the framework of 5G technology. Within D2D communication, resource allocation stands out as a critical research area aimed at enhancing the capabilities of 5G communication for IoT applications. In our proposed work, we begin by establishing a mathematical framework designed to minimize energy consumption in the allocation of frequency bands, utilizing a novel algorithm. Subsequently, we harness the core principles of this algorithm through the application of three distinct optimization methods: (i) the genetic algorithm, (ii) the simulated annealing approach, and (iii) the coalition game theory technique. The analysis and results derived from these methodologies shed light on the individual contributions of these optimization techniques and allow us to conduct a comparative analysis, focusing on convergence patterns. The proposed work provides insights for researchers in domain of the D2D system to facilitate decision-making regarding optimization strategies. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Genetic algorithms

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Digital Evidence Management: Modern Techniques in Digital Forensics 3

Digital Evidence Management: Modern Techniques in Digital Fo...

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3rd international conference on Electronics and Renewable systems, ICEARS 2025

作者： Venkataramanan, N. Jayalakshmi, V. Anitha, S. Ganesan, R. Jenifer, V. Drbccc Hindu College Department of Computer Applications Pattabiram Chennai600072 India Department of Computer Science and Applications Ramapuram600089 India Anna University St. Joseph's College of Engineering Department of Artificial Intelligence and Machine Learning Chennai600119 India Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai600062 India Department of Computer Science and Applications Ramapuram Campus 600089 India

ISBN: (纸本)9798331509675

This research study reviews the significance of digital forensic analysis in modern criminal investigations, highlighting the way it complements conventional methods of inquiry and the difficulties it encounters in the information era. To solve crimes effectively, investigators must combine digital knowledge with traditional forensic techniques. This will enable them to use evidence from many different types of digital and physical sources. The specific intricacies of digital crime scenes need specialized methods for the proper storage and analysis of digital evidence to identify criminal intent and patterns of conduct. To propose Modern Techniques for Digital Evidence Management [MT-DEM] based Digital Forensics Service. Multidisciplinary teams and cutting-edge technology are becoming necessities in digital forensic investigation as the field adjusts to new threats like data encryption and massive amounts of data. The admissibility of evidence in the legal world depends on digital forensic procedures being transparent and adhering to set criteria. Digital forensic analysis has become an indispensable tool for contemporary investigators with the rise of digital evidence. © 2025 IEEE.

关键词： Forensic science

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Role of IoT in Smart Cities: A Review, applications, Open Challenges and Solutions 3

Role of IoT in Smart Cities: A Review, Applications, Open Ch...

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3rd international conference on Electronics and Renewable systems, ICEARS 2025

作者： Vivek, Kolla Swetha, Gurrala Kumar M, V. T. Ram Pavan Veni, Anusuri Krishna Praveen, Neti Kale, Masthan Rao Dept. of Cse Andhra Pradesh Ongole India Dept. of Cse Telangana India Kakaraparti Bhavanarayana College Dept. of Computer Science Andhra Pradesh Vijayawada India Madanapalle Institute of Technology & Science Dept. of Computer Science & Engineering - Data Science Andhra Pradesh Madanapalle517325 India Srkr Engineering College Dept. of Computer Science and Design Andhra Pradesh Bhimavaram India Dept. of Cse Andhra Pradesh Ongole India

ISBN: (纸本)9798331509675

Smart cities have emerged as a response to the fast expansion of metropolitan areas;these places strive to improve the lives of their residents while simultaneously promoting environmentally responsible growth. To maximize urban services, the Internet of Things (IoT) is an essential technology that allows for the seamless integration of sensors, devices, and systems. This allows smart cities to become a reality. With an emphasis on smart transportation, energy management, healthcare, environmental monitoring, and public safety, this paper explores the critical role of IoT in smart cities. Data security, privacy, scalability, and interoperability are some of the problems that arise when smart cities use IoT, despite the revolutionary potential it has. These obstacles are thoroughly examined in this work, along with possible solutions to these problems. This study gives a thorough overview of the IoT and its impact on smart city development, innovation, and urban resilience by focusing on the present situation, applications, and unanswered questions. © 2025 IEEE.

关键词： Digital Technology Drainage Monitoring Fire detection Smart City Waste Management

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CNTFET-RMGDI based Full swing BCD to Seven Segment Display for Low Power applications 3

CNTFET-RMGDI based Full swing BCD to Seven Segment Display f...

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3rd international conference on Electronics and Renewable systems, ICEARS 2025

作者： Lavanya, Parsa Lakshmi Subramanyam, M.V. Rambabu, S. Santhiram Engineering College Dept. of Ece AP Nandyal India Santhiram Engineering Dept. of Ece AP Nandyal India

ISBN: (纸本)9798331509675

The majority of gadgets, including radios, digital clocks, calculators, washing machines, and others, use seven-segment displays to display the letters and numbers. This seven-segment display allows the binary value to be seen as a decimal. A Full-Swing BCD to Seven-Segment Decoder based on CNTFETs and improved by Resistive based RMGDI approaches is presented in this article. The proposed design uses CNTFET-RMGDI to conquer the speed, power consumption, and voltage flip limitations of traditional CMOS circuits. Partial output voltage swing problems are eliminated using the RMGDI approach, which guarantees a full voltage swing over the seven-segment display. In regards to space, power usage, delays, and PDP, the proposed architecture is significantly better than CMOS segment decoders when executed in the CADENCE Tool with 32 nm technology. According to experimental results, the CNTFET-RMGDI-based BCD segments decoder uses 55% less area, 96% less power, and 78% less PDP than traditional CMOS-based seven segment decoders. According to the findings, the suggested decoder is perfect for low-power, high-performance applications, especially in handheld devices, since it improves the rate of switching while reducing transistor count, PDP, and energy use. © 2025 IEEE.

关键词： CMOS integrated circuits

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Integrating Big Data Analytics in Soil Quality Assessment: Techniques, Challenges, and applications 3

Integrating Big Data Analytics in Soil Quality Assessment: T...

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

作者： Mohammed, Shehu Singh, Arun Hanif, Md Abu Lovely Professional University Department of Computer Applications Phagwara India Lovely Professional University Department of Computer Science and Engineering Phagwara India Department of Computer Science 365 5th Ave New YorkNY110016 United States

ISBN: (纸本)9798331515911

This review paper investigates the application of Big Data analytics, focusing on soil quality assessment, with an emphasis on the innovative benefits offered by modern data-driven techniques for improved soil management. With world food demands rising, the importance for real-time and exact soil quality monitoring has increased. Although still useful, traditional approaches to modeling are limited in their ability to capture the spatial and temporal variability of soil properties. Big Data analytics sits as the answer to the above by facilitating extensive and large volume data processing resulting in better, on-demand and scalable soil quality assessment. In the paper, we describe machine learning algorithms, remote sensing and geospatial analysis as key techniques to mine soil data at scales and resolutions unprecedented so far. We also critically evaluate the challenge of data integration (heterogeneity, scalability and multi-disciplinarity). These analytics are scalable for assessment and decision-making in precision agriculture, sustainable land management and environmental conservation. Thus, this paper synthesizes current research and practical implications in support of the need for Big Data analytics within soils and soil sciences to cover also future challenges. Future research directions are also highlighted, including the importance of improved data acquisition and algorithmic advances as well greater synergy between Big Data and conventional soil science practices.. © 2025 IEEE.

关键词： Data quality

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Implementing Encryption algorithms for the Protection of wireless Networks 5th

Implementing Encryption Algorithms for the Protection of Wir...

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5th international conference on Data Science, Machine Learning and applications, ICDSMLA 2023

作者： Ahmad, Naseem Madhura, K. Agarwal, Trapty Zaidi, Taskeen Department of Computer Science and Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bangalore India

ISBN: (纸本)9789819780426

The use of encryption algorithms is more and more turning into a crucial issue of defensive wireless networks. Encryption algorithms may be used to cozy facts that is transferred over a Wi-Fi network while also presenting authentication and integrity protocols for the systems connected to the network. This paper discusses the significance of enforcing encryption algorithms for the safety of a wireless community. It describes the distinct encryption algorithms and protocols which are available, and the criteria for selecting the proper algorithm for exclusive varieties of Wi-Fi networks. It additionally provides unique implementation eventualities based totally on numerous sorts of Wi-Fi community structure in addition to the vast security threats in Wi-Fi networks that may be averted by imposing encryption algorithms. Finally, this paper offers guidelines on selecting and imposing the perfect encryption set of rules for safety of wireless networks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Encryption algorithms

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Performance Analysis of Optimized Improved Controller using BLDC Motor for E-Auto applications 3

Performance Analysis of Optimized Improved Controller using ...

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3rd international conference on Electronics and Renewable systems, ICEARS 2025

作者： Dhineshkumar, K. Mythili, R. Dhanush Bharathi, S. Shivaani, S.T. Roslin Gnana Grace, E. KIT-Kalaignarkarunanidhi Institute of Technology Department of Electrical and Electronics Engineering Coimbatore India

ISBN: (纸本)9798331509675

This paper explores the performance of an optimized Proportional-Integral (PI) controller applied to Brushless DC (BLDC) motors for electric automotive (E-auto) applications, with a focus on minimizing rotor speed fluctuations under varying load conditions. The primary aim of this paper is to reduce rotor speed fluctuations that occur when the motor is subjected to varying load conditions, which is a common challenge in electric vehicle systems. To achieve this, the PI controller parameters were carefully optimized through a systematic trial-and-error method, ensuring that the motor exhibited improved responsiveness and stability under load variations. System performance was enhanced by the optimization, which modified the proportional and integral gains of the PI controller to strike a compromise between quick response time and little overshoot. The dynamic response of the motor under various load circumstances was assessed using MATLAB/Simulink simulations. The settling time was significantly reduced to 0.025 seconds, according to the results, guaranteeing faster stabilization following disturbances. This demonstrates how the improved controller performs better. Additionally, the torque ripple, a key factor in motor smoothness and efficiency, was significantly reduced to 0.029 Nm. These findings demonstrate that the optimized PI controller not only improves the motor's response time but also minimizes the mechanical vibrations and inefficiencies caused by torque ripple, thereby ensuring a smoother operation. Furthermore, the controller's ability to maintain stability and consistent performance across different load conditions highlights its effectiveness in real- world applications, where electric vehicles are often subjected to fluctuating demands. © 2025 IEEE.

关键词： Brushless DC motors

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TriBoost and Beyond: Advanced Machine Learning Approaches for Diabetes Risk Prediction 3

TriBoost and Beyond: Advanced Machine Learning Approaches fo...

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3rd international conference on Electronics and Renewable systems, ICEARS 2025

作者： Katlariwala, Soham Biren Gandhi, Vaibhav C. Patel, Nirav Parmar, Devendra Desai, Ayushi Indian Institute of Technology Madras B.S. Data Science and Applications Chennai India University Department of Computer Engineering Mbit Anand India Parul University Parul Institute of Technology Vadodara India

ISBN: (纸本)9798331509675

Diabetes is a tremendous world health issue and, in its management, and complications prevention, proper screening is vital. This paper examines the improvement of accurate diabetes risk prediction by some advanced machine learning methods. The study compares various models such as;Random Forest, AdaBoost, Support Vector Machine, CatBoost, Decision Tree, LS-SVM, Logistic Regression, Naïve Bayes, k-Nearest Neighbors, LightGBM, XGBoost, and neural networks. Most emphasis is put on TriBoost that is a novel ensemble model which integrates XGBoost, CatBoost, and LightGBM. Lastly, the effectiveness of a model is determined using measures such as ROC AUC and accuracy. Evaluation of the results has shown that the proposed TriBoost had the highest accuracy at 94% and ROC AUC of 91% thereby outcompeting the use of individual classifiers as well as other ensemble methods. The results of the study confirm adequacy and possibilities of ensemble learning to enhance predictive precision and stability and their applicability for early detection of diabetes in clinics. Further work shall seek to increase the variability of the dataset, integrate fresh clinical data, and increase computational effectiveness for practical use. © 2025 IEEE.

关键词： Adversarial machine learning

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Wordle-Based Text Analysis: applications of Intelligent algorithms Such as XGBoost and Char-CNN 3rd

Wordle-Based Text Analysis: Applications of Intelligent Algo...

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

作者： Ye, Huicheng Su, Qifeng Chen, Shuang Xu, Dan Yu, Hongqi National University of Defense Technology Hunan Changsha410000 China School of Systems Science and Engineering Sun Yat-sen University Guangzhou510006 China

ISBN: (纸本)9789819624676

In this paper, the application of intelligent algorithms such as XGBoost and Char-CNN is verified by establishing the analysis model of the game Wordle. The three models established can perform the tasks of fitting and predicting the number of players, analyzing the number of attempts, and classifying the difficulty of the game. In the first model, XGBoost optimizes the classical SIR Model to improve output accuracy and analysis efficiency. In the second model, this paper designs an innovative two-dimensional code word coding method concerning machine language, which effectively reduces the redundancy of Char-CNN. In the third model, the classical Bayesian algorithm is used to classify the difficulty of a large word set, proving its usability. In addition to helping Wordle editors identify more appealing puzzles, the process of analyzing text with intelligent algorithms is also valuable for scholars who study the text features. In the era of big data, the model-building method in this paper may also give some enlightenment to the field of artificial intelligence. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Char-CNN Wordle XGBoost

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