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检索条件"任意字段=International Conference on Engineering of Reconfigurable Systems and Algorithms"

共 90344 条记录，以下是281-290 订阅

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Optimization of Automated Driving systems for Electric Vehicles

Optimization of Automated Driving Systems for Electric Vehic...

引用

2024 international conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Kumar, Sunil Rengarajan, A. Acharjya, Kalyan College of Engineering Teerthanker Mahaveer University Uttar Pradesh Moradabad India Department of Computer Science and Information Technology Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798350383348

Automated riding structures for electric-powered vehicles have been an increasing number of researched regions due to the growing call for sustainable transportation. The main objective of these systems is to maximize efficiency so that it will lessen emissions and enhance the gasoline economy. Optimizing the management of computerized systems is a complicated challenge due to the several factors that ought to be taken into consideration: pace, acceleration, road situations, and many others. To optimize those systems, various techniques and algorithms were developed to automate the procedure and improve efficiency. Those algorithms hire an iterative optimization process so that you can determine the foremost trajectory and speed for the car. The resulting most appropriate trajectories are then combined in an effort to limit gasoline consumption, emissions, and time. Moreover, sensors and device-getting-to-know algorithms have been utilized to enhance the accuracy of the gold standard trajectory. Furthermore, distinct manipulation techniques, such as feedforward and remarks manipulation, have been hired to decorate the overall performance and accuracy of computerized driving. The improvement of those optimization techniques has helped to improve the performance of electric cars, at the same time affording a smoother and greater dependable driving enjoyment. © 2024 IEEE.

关键词： algorithms Feedforward Manipulation Optimization Researched Transportation

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Multi-Functional RIS-Aided Anti-Jamming Communication in Semantic Integrated Satellite-Ground Networks 16

Multi-Functional RIS-Aided Anti-Jamming Communication in Sem...

引用

16th international conference on Wireless Communications and Signal Processing, WCSP 2024

作者： Sun, Yifu An, Kang He, Yuanzhi Cao, Haotong Zhong, Xudong Guo, Kefeng Zhu, Hongbo Sixty-third Research Institute National University of Defense Technology Nanjing China Institute of Systems Engineering Academy of Military Sciences Beijing China College of Telecommunications and Information Engineering Nanjing University of Posts and Telecommunications Nanjing China School of Space Information Space Engineering University Beijing China

ISBN: (纸本)9798350390643

Integrated satellite-ground network (ISGN) emerges as a promising key component of the sixth-generation (6G) wireless networks due to its potential capabilities in providing ubiquitous connectivity for global coverage and reliable services. However, the inevitable existences of high-volume data, uncontrollable propagation environment, and malicious jamming attacks pose three significant bottlenecks for enabling efficient ISGN. With these focuses, we propose a novel framework of multi-functional reconfigurable intelligent surface (MF-RIS) aided semantic anti-jamming communication in ISGN. Under this framework, a semantic transceiver exhibits inherent robustness and data compression capability, and MF-RIS can customize the full-space wireless environment by leveraging its signal reflection, refraction, amplification, and energy harvesting functions, thereby achieving substantial global coverage, reliable connectivity, and high-rate transmission. Based on our proposed framework, we formulate a total semantic rate maximization problem considering the impacts of jammer's channel state information (CSI) imperfection, while maintaining the semantic similarity requirement, semantic rate target, and MF-RIS's self-sustainability. Then, by transforming the imperfect CSI into a worst-case one by exploiting a discretization method, we propose a fast-converging monotonic optimization algorithm that is combined with decoupling second-order cone programming to obtain a globally optimal solution with fewer feasibility evaluations. Numerical simulations demonstrate the superiority of our proposed framework and algorithms compared to various benchmarks. © 2024 IEEE.

关键词： Satellite communication systems

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Uncovering the Impact of Untreated Diabetes via Machine Learning Approach

Uncovering the Impact of Untreated Diabetes via Machine Lear...

引用

2024 international conference on Intelligent algorithms for Computational Intelligence systems, IACIS 2024

作者： Yadav, Avinash Gourisaria, Mahendra Kumar Dwivedi, Nitish Bandyopadhyay, Anjan Singh, Jay Prakash Mishra, Soumya Ranjan Kiit Deemed to be University School of Computer Engineering Odisha Bhubaneswar India Kiit Deemed to be University School of Computer Engineering Bhubaneswar India Manipal University Jaipur Dept of Computer Science & Engineering Jaipur India

ISBN: (纸本)9798350360660

Determining the impact of untreated diabetes poses challenges with an estimated one in four cases remaining undiagnosed. Diabetes mellitus, a group of metabolic disorders, arises when blood glucose levels or blood sugar are elevated due to insufficient insulin production, cellular response or both. We have diagnosed untreated diabetes to predict the level of diabetes in this paper. In this paper we tested various machine learning algorithms to improve the precision of disease prediction while automating health care systems. The classifier and boosting techniques include Ada Boost, Logistic Regression, Decision Tree, Extreme Gradient Boosting, Gaussian Naive Bayes, Support Vector Machine, Random Forest, and Cat Boost. Decision Tree emerged as the top-performing algorithm, achieving an accuracy of 0.8306 in classifying diabetes health markers, followed by Logistic Regression having 82.97. It's common to evaluate the performance of machine learning models using multiple metrics to get a comprehensive understanding of their effectiveness. © 2024 IEEE.

关键词： Support vector machines

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Automatic Timetable Generation using Neural Networks Trained by Genetic algorithms 18

Automatic Timetable Generation using Neural Networks Trained...

引用

18th international conference on Open Source systems and Technologies, ICOSST 2024

作者： Abbas, Shaheer Maaz, Ahmad Ali, Raja Hashim Khan, Talha Ali Ahmed, Iftikhar University of Europe for Applied Sciences Department of Business Think Campus Potsdam14469 Germany GIK Institute of Engineering Sciences & Technology Faculty of Computer Science & Engineering Topi23460 Pakistan

ISBN: (纸本)9798331508692

Scheduling is a crucial task in various real-life situations, including educational institutions where creating a feasible timetable is a complex challenge due to numerous constraints. The educational timetable scheduling problem is NP-hard, making it a difficult problem to solve optimally within reasonable time frames. Traditional methods like Genetic algorithms (GAs) and Evolutionary algorithms (EAs) have been applied to this problem with varying degrees of success. In this paper, we introduce a novel approach for automatic timetable generation using neural networks trained by genetic algorithms. Our method leverages the strengths of neural networks in pattern recognition and GAs in optimization to effectively handle the constraints and complexities of timetable scheduling. Experimental results demonstrate a significant improvement in scheduling accuracy and computational efficiency. We compare the performance of our proposed method with traditional GAs and demonstrate that the neural network approach trained by GAs achieves superior results in terms of speed and solution quality. This research paves the way for more efficient and intelligent scheduling systems in educational environments. © 2024 IEEE.

关键词： Genetic algorithms

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Automated Detection of Encryption algorithms Using AI Techniques 5

Automated Detection of Encryption Algorithms Using AI Techni...

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5th international conference on IoT Based Control Networks and Intelligent systems, ICICNIS 2024

作者： Chidambaranathan, Senthilnathan Santhanaraj, M. Ajitha, E. Syed Fiaz, A.S. Suchithra, B. Kathirvel, T. Virtusa Corporation NJ United States Kongunadu College of Engineering and Technology Department of IT Tamil Nadu Trichy India St. Joseph's Institute of Technology Computer Science and Engineering India Sona College of Technology Department of Information Technology Salem India Sri Eshwar College of Engineering Department of CSE Coimbatore India

ISBN: (纸本)9798331518097

In today's digital era, cryptographic algorithms play a vital role in safeguarding sensitive information, maintaining confidentiality, and defending against cyberattacks. With the growing variety of encryption methods and modes, identifying the specific algorithm used to generate a ciphertext has become increasingly challenging. To address this, we propose a machine learning solution that automatically identifies cryptographic algorithms using the Random Forest classifier. The system processes a vast dataset called 'encrypted-data,' which contains 39 different algorithms and modes, by extracting essential features like byte frequency and entropy from the ciphertexts. These features form a 257-dimensional Feature vector used for classification. Random Forest models are trained with these data. During testing, models are loaded is used to predict the encryption algorithm for a given ciphertext. Our method offers a scalable and efficient approach to cryptographic identification, surpassing traditional techniques. © 2024 IEEE.

关键词： Encryption algorithms

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Intelligent Beamforming for Enhanced Secrecy and Performance in reconfigurable Intelligent Surfaces 3

Intelligent Beamforming for Enhanced Secrecy and Performance...

引用

3rd international conference on Electrical, Electronics, Information and Communication Technologies, ICEEICT 2024

作者： Sivasankar, S. Markkandan, S. Vellore Institute of Technology School of Electronics Engineering Chennai India

ISBN: (数字)9798350369083

ISBN: (纸本)9798350369083

Intelligent Reflecting Surfaces (IRS) are pivotal in enhancing wireless communication systems by shaping the propagation environment. This study introduces a customized beamforming algorithm for reconfigurable Intelligent Surface (RIS) setups, aiming to enhance wireless communication security by refining beamforming and IRS configurations. The process involves initializing system parameters, optimizing beamforming vector w and IRS reflection matrix Θ to maximize secrecy rate Rs, while adhering to power and phase shift constraints. Through gradient ascent, the optimization boosts signal strength at the user equipment (UE) while minimizing eavesdropping risks. Simulations demonstrate significant secrecy rate improvements with more reflecting elements, surpassing traditional Physical Layer Security (PLS) and backscatter methods. The proposed scheme effectively counters eavesdropping threats and optimizes resource allocation in multi-user scenarios, providing a robust solution for secure wireless communications. © 2024 IEEE.

关键词： Beamforming

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High Performance VLSI Architecture of FIR Filter for Seismic Signal Processing 3

High Performance VLSI Architecture of FIR Filter for Seismic...

引用

3rd international conference on Advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2023

作者： Karunakaran, S. Electronics and Communication Engineering Vardhaman College of Engineering Hyderabad India

ISBN: (纸本)9781665494007

As a primary requirement, FIR filters(Finite Impulse response)used in real-time seismic alert systems are required to be low complexity, fast, and re-configurable. The CSE technique is commonly used to abate hardware complexity in digital FIR filters by decreasing logic operators and logic depths. In this paper, we present a new LO and LD minimization matrix grouped CSE algorithm that outperforms existing CSE algorithms. Additionally, the suggested design With low complexity and reduced truncation error, we developed a new biased-based rounding method that includes half units, as well as to lessen critical-path delay, use the cut-set retiming technique. This paper presents two hardware-efficient FIR filter topologies (I and II) that employ cut-set retiming, HUB rounding, and the canonical signed digit based MCSE algorithm. Additionally, architecture II implements a reconfigurable FIR filter in a hardware- efficient manner. FPGA and ASIC platforms are used to implement the architectures on the hardware side. Comparing the hardware implementation of proposed architectures, we mooted decrease of LOs, CPD, effective latency, area-delay product (ADP), and power- delay product using cutting-edge CSE- based architectures by a factor of 2 more than 35%, 47 %, 36 %, 34 %, and 29 %,*** comparison to the *** reconfigurable architecture II has an approximately 46 %, 10 %, and 11 % less in PDP, ADP and CPD. © 2023 IEEE.

关键词： FIR filters

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Subspace-based DOA Estimation Method for Coherent Signals Assisted by Transformer 16

Subspace-based DOA Estimation Method for Coherent Signals As...

引用

16th international conference on Signal Processing systems, ICSPS 2024

作者： Mao, Wei Xi, Feng School of Electronic and Optical Engineering Nanjing University of Science and Technology China

ISBN: (纸本)9781510689251

Direction of Arrival (DOA) estimation plays a crucial role in array signal processing, with broad applications across various fields. Traditional Model-Based (MB) DOA estimation algorithms, however, are constrained by their reliance on prior knowledge and tend to perform poorly in non-ideal conditions, such as when dealing with coherent sources or limited snapshot numbers. In contrast, Data-Driven (DD) approaches using deep learning offer novel insights and capabilities for enhancing DOA estimation. This paper introduces a novel hybrid MB-DD framework for estimating the DOAs of multiple coherent narrowband signals captured by Uniform Linear Arrays (ULA). Specifically, the proposed method, TransSubNet, employs an autoencoder module centered around a Transformer Encoder to generate a proxy covariance matrix, which is then fed into classical subspace algorithms, such as root-MUSIC, to estimate the DOAs of the received signals. By integrating the strengths of both MB and DD methods, TransSubNet utilizes the Transformer-based network to improve the covariance matrix estimation process, enhancing the robustness and accuracy of subspace-based DOA algorithms. Our architecture achieves high-precision DOA estimation even under challenging conditions, such as low snapshot numbers, low Signal-to-Noise Ratios (SNRs), and 1-bit quantized signals. Experimental results show that TransSubNet outperforms existing algorithms in the domain, delivering superior performance across a range of scenarios. © 2025 SPIE.

关键词： Covariance matrix

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Application and optimization of adaptive control algorithm in optical communication 5

Application and optimization of adaptive control algorithm i...

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5th international conference on Telecommunications, Optics, and Computer Science, TOCS 2024

作者： Zhang, Zhihao School of Electrical Automation and Information Engineering Tianjin University Tianjin China

ISBN: (纸本)9781510691667

In the context of rapidly evolving communication technologies, there is an urgent need for dynamic systems capable of adapting to fluctuating environmental conditions to ensure reliable signal transmission. This article delves into the application and optimization of adaptive control algorithms in optical communication systems, which are pivotal for adjusting system parameters in real-time. We introduce the fundamentals of optical communication and adaptive control algorithms, then proceed to analyze their critical roles in channel equalization, pattern recognition, and signal recovery. Our methodology encompasses a detailed analysis of algorithm performance through experimental setups, parameter adjustments, and structural optimizations. Key findings indicate significant improvements in signal quality and data transmission reliability, particularly through the optimization of algorithm parameters and the fusion of different adaptive control techniques. Ultimately, our research concludes that adaptive control algorithms are indispensable for enhancing the performance and reliability of optical communication systems, offering a robust framework for future technological advancements in this field. © 2025 SPIE.

关键词： Self adjusting control systems

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Authentication and Access Control in Software Defined Network-Internet of Things: A Security Perspective

Authentication and Access Control in Software Defined Networ...

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2024 international conference on Intelligent algorithms for Computational Intelligence systems, IACIS 2024

作者： Sahana, D.S. Gopala Krishnan, C. Gitam School of Technology Department of Computer Science and Engineering Bengaluru India

ISBN: (数字)9798350360660

ISBN: (纸本)9798350360660

The study's primary goal is to prevent unauthorized people and systems from accessing protected resources in a way that goes beyond their permissions. It aims to provide an overview of authentication and access control methods while showcasing current research developments in the SDN-IoT space. The review discusses current Authentication and Access Control approaches and technologies, including security difficulties, risks, and numerous technological innovations. Finally, it also covers the various authentication and access control existing mechanisms and how technology might be incorporated into a network's architecture plan. © 2024 IEEE.

关键词： Authentication Protocol

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