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Enhancing the Channel Quality in Cognitive network by Traffic Reduction Method 3

Enhancing the Channel Quality in Cognitive network by Traffi...

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3rd IEEE International conference on Intelligent Technologies, CONIT 2023

作者： Singh, Sanjay Pilania, Urmila Kumar, Manoj Awasthi, Satya Prakash Nelson, Leema Manav Rachna University Dept. of Computer Science & Technology Faridabad India Poornima University Faculty of Computer Engineering Jaipur India Chitkara University Institute of Engineering & Technology Chitkara University Department of Computer Science & Engineering Punjab India

ISBN: (纸本)9798350338607

Cognitive radio (CR) has some specific unique characteristics like flexibility, interoperability and adaptability. Optimal technological candidate is particularly contributed which reduces the challenges towards spectrum scarceness sin multimedia communications. Moreover, this communication over CR networks produces few severe issues like delay-sensitive, bandwidth-hungry, and loss-tolerant service and particularly ensuring quality of service (QoS). Improved Dynamic optimization Algorithm (IDOA) is proposed for spectrum sensing in cognitive radio networks (CRN) where for the Secondary User (SU), data traffic is considered. From the comparison of several works in the literature, it is assumed that SU have no packets to transmit always;but actually data sent per second is considered instead of channel capacity as the possible throughput with which the problem of sensing-throughput tradeoff is reformulated. The parameters such as probability of availability, Signal to Interference Noise Ratio (SINR), Processing time and transmission time are considered to analyze the efficiency of the IDOA approach proposed which is compared with two state of methods namely Medium Access control (MAC) and Dijikstra Algorithm (DA). © 2023 IEEE.

关键词： Cognitive radio

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Research On Topology Mapping Strategy Based On Improved Genetic Algorithm 3

Research On Topology Mapping Strategy Based On Improved Gene...

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3rd International conference on Artificial Intelligence, Automation, and High-Performance Computing, AIAHPC 2023

作者： Yang, Hang Li, Boyan Yang, Zhan Lv, Zhuoheng Zhang, Tao College of Computer and Artificial Intelligence Zhengzhou University Zhengzhou450000 China

ISBN: (数字)9781510666580

ISBN: (纸本)9781510666573

The progress of scientific development requires the use of high-performance computers for large-scale simulations, resulting in a significant communication overhead and thereby constraining the computer's performance. To address this issue, optimizing the topological mapping of application processes to computing nodes is essential for enhancing the communication performance of high-performance computers. However, this topic has not been extensively explored in the literature. In order to reduce the communication overhead of high-performance applications, this study formulates the optimization of topological mapping from application processes to computing nodes as a quadratic allocation problem. The proposed method collects communication features to assess the communication intimacy between processes, and considers the communication relationship between application processes and network topology. To overcome the limitations of traditional genetic algorithms, this study introduces elite learning and adaptive selection into the mutation operator. In this algorithm, individuals undergoing mutation learn from fragments of the best individuals in the current population. Additionally, three functions are selected to control the probability of selecting the elite learning mutation during the mutation process, thereby enhancing the algorithm's efficiency and accuracy. The results of the experiments demonstrate that the suggested methodology yields a noteworthy enhancement in communication performance compared to the widely adopted round-robin approach in NPB test suites. Furthermore, the enhanced genetic algorithm displays superior optimization efficiency in comparison to conventional genetic algorithms and other heuristic approaches. © 2023 SPIE.

关键词： network topology

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Design and Test of Laser Diameter Measurement network System 3

Design and Test of Laser Diameter Measurement Network System

引用

3rd International conference on Machine Learning and Computer Application, ICMLCA 2022

作者： Yin, Huawei Li, Hongda School of Equipment Engineering Shenyang Ligong University Shenyang China

ISBN: (纸本)9781510664814

In recent years, with the development of industrial technology gradually mature, modern industry has carried on the thorough research to the measurement field, put forward higher requirements for accurate measurement and performance optimization in other directions. Therefore, the focus of this paper is to test the networking system based on laser diameter measurement to achieve accurate measurement of cable radius. The measured experimental data can show that the system can show high precision, high efficiency and real-time control for accurate diameter measurement. Through the development of the corresponding measurement data host computer display interface, verify its feasibility, thereby reducing the product development cycle, with strong practicability. © 2023 SPIE.

关键词： Real time control

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Nonlinear control design of grid-connected photovoltaic system through LC filter with ANN based MPPT method 3

Nonlinear control design of grid-connected photovoltaic syst...

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3rd IEEE International conference on Electronics, control, optimization and Computer Science, ICECOCS 2022

作者： El Mezdi, Karim El Magri, Abdelmounime Bahatti, Lhoucine Lajouad, Rachid Watil, Aziz Hassan II University EEIS Laboratory ENSET Mohammedia Casablanca Morocco

ISBN: (数字)9781665457231

ISBN: (纸本)9781665457231

This paper discusses the issue of maximum power point tracking (MPPT) extracted from a photovoltaic module using a DC/AC power energy conversion system. The study targets specifically a solar enrgy conversion system including a PV panel, a PWM DC/AC inverter connected to single-phase grid through LC filter. The following are the primary goals of this work: (i) DC-Link voltage regulation: The voltage of the PV panel must follow a predetermined reference voltage that coincides with the maximum power point. An optimizer based on an artificial neural network (ANN) generates the optimal reference voltage;(ii) PFC requirement: Grid current must be sinusoidal and phase-locked to the voltage network. To do this, a mathematical modeling of the inverter with filter LC was performed. Subsequently, a backstepping controller is developed in order to ensure the control objective. The convergence of closed loop control is formally studied. As result, the injected current has good sinusoidal form and a low total harmonic distortion THD. © 2022 IEEE.

关键词： Electric inverters

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A Multi-Objective optimization Register Clustering Method 3

A Multi-Objective Optimization Register Clustering Method

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3rd International conference on High Performance Computing and Communication Engineering, HPCCE 2023

作者： Liu, Ningzhuang Deng, Hanyu College of Electrical and Control Engineering Xi'an University of Science and Technology Xi'an China

ISBN: (数字)9781510674653

ISBN: (纸本)9781510674646

The clock tree synthesis (CTS) step is critical for the physical design of ultra-large-scale integrated circuits (VLSI). Outstanding CTS results can reduce the skew of clock networks, decrease chip power consumption while improving performance and reliability of the chip. This paper proposes a register clustering method based on the nondominated sorting genetic algorithm II (NSGA-II) algorithm to generate the leaf-level topology of the clock tree, addressing multi-objective optimization issues in integrated circuit physical design. We model register clustering as a multi-objective optimization problem. By analyzing the clock network model and power consumption to design the objective functions, register clustering schemes are encoded. Pareto optimal solutions are obtained through iterative evolution and non-dominated sorting. This method is integrated into the traditional CTS process. Three circuits were selected from the ISCAS89 benchmark circuit for testing and analysis proving its effectiveness. Experimental results show that compared to traditional clock tree synthesis methods, our approach reduces timing skew by more than 5%, maximum clock delay by over 15%, and power consumption by over 10%. Our strategy achieves a balance among multiple physical design objectives, obtaining superior clustering schemes. This paper offers an effective algorithm for multi-objective register clustering. © 2024 SPIE.

关键词： Electric power utilization

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Blockchain-Based Smart Contracts for Supply Chain Management: A Strategic Analysis 3

Blockchain-Based Smart Contracts for Supply Chain Management...

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3rd IEEE International conference on Intelligent Techniques in control, optimization and Signal Processing, INCOS 2024

作者： Santosh, Kathari Dash, Chinmaya Aarif, Mohd Kumar, Yadavalli Suresh Verma, Mrinal Kiranbala, B. Cmr Institute of Technology Department of Mba Bengaluru India St. Claret College Department of Computer Science Bangalore India Global Research Network Noida India Aditya College of Engineering Department of Computer Science & Engineering Andhra Pradesh India Soil School of Business Design Manesar Gurgaon India K.Ramakrishnan College of Engineering Department of Ai and Ds Trichy India

ISBN: (纸本)9798350361186

The supply chain management sector strategic examination of the blockchain relies smart contract technology employs a comprehensive approach, drawing insights from reputable secondary sources to explore performance metrics, transactional flow optimization, consensus mechanisms, and security considerations. The study reveals nuanced performance variations in average throughput and transaction duration, emphasizing the scalability and stability of the blockchain network. The depicted transactional flow showcases enhanced communication and transparency, aligning with strategic goals for supply chain optimization. The introduction of a Proof of Authority (PoA) consensus algorithm underscores the importance of efficient consensus mechanisms for resilience against attacks. By integrating PoA, the proposed blockchain-based smart contracts contribute to a strategic and reliable supply chain management system, enhancing transparency and mitigating potential risks. A robust security analysis demonstrates moderate fault tolerance, high defense mechanisms, and effective security recovery capabilities, aligning with the overarching goals of confidentiality, integrity, and availability of critical supply chain data. Ethereum's Proof of Stake (PoS) mechanism is referenced as an exemplar for improving scalability and security. The comparative analysis highlights the proposed CMBC (Consensus Mechanism with Blockchain) as a standout solution, offering middle-ground high attack diversity, fault tolerance, recovery, and a high attack cost, robust security. CMBC outperforms alternatives, demonstrating superiority in enhancing security and resilience against potential adversarial threats. The proposed CMBC demonstrates notable strengths across key performance indices when compared to Fortified-Chain and SaYoPillow. The proposed method is implemented using python software. The effective standard deviation values, ranging from 9.58 to 25.13, further underscore the system's stability and re

关键词： Smart contract

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Hamiltonian mechanics and neural network technology for high stabilization of Quadrotor UAV on SE(3) 3

Hamiltonian mechanics and neural network technology for high...

引用

3rd IEEE International conference on Electronics, control, optimization and Computer Science, ICECOCS 2022

作者： Mohamed, Benaly Abdelkader, Mezouari Rachid, El Gouri Mohammed, Benbrahim Lamaari, Hlou Ibn Tofail University Faculty of Science Department of Physics Kenitra Morocco Ibn Tofail University National School of Applied Sciences Kenitra Morocco

ISBN: (数字)9781665457231

ISBN: (纸本)9781665457231

The most important feature of expensive drones is that the flight stability is overwhelmingly high. The big expensive drones can fly safely simply due to their big size and heavyweight. The downside of small drones is that the flight is not stable and is easily affected and this is not only due to the wind but also to the nonlinear approaches to be used for flight control systems and the architecture used. In this paper, we propose a new nonlinear dynamic modeling based on Hamiltonian mechanics the most powerful model in modern mechanics for high attitude stabilization of a quadrotor aircraft, a nonlinear controller is developed on the special Euclidean group SE(3). The fly controller is designed by the neural networks (NNs) control algorithm executed on a microprocessor and makes his calculation in a high-speed calculator unite to achieve the desired tracking for the drone. © 2022 IEEE.

关键词： Drones

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Proceedings of QCS 2022: 3rd International Workshop on Quantum Computing Software, Held in conjunction with SC 2022: The International conference for High Performance Computing, networking, Storage and Analysis

Proceedings of QCS 2022: 3rd International Workshop on Quant...

引用

3rd IEEE/ACM International Workshop on Quantum Computing Software, QCS 2022

ISBN: (纸本)9781665475365

The proceedings contain 13 papers. The topics discussed include: wide quantum circuit optimization with topology aware synthesis;Tierkreis: a dataflow framework for hybrid quantum-classical computing;automated quantum memory compilation with improved dynamic range;neural network accelerator for quantum control;rotation-inspired circuit cut optimization;a compiler for universal photonic quantum computers;predicting the optimizability for workflow decisions;automated quantum error mitigation based on probabilistic error reduction;memory-efficient differentiable programming for quantum optimal control of discrete lattices;exploiting in-constraint energy in constrained variational quantum optimization;and stochastic approach for simulating quantum noise using tensor networks.

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A MPGNN-Based Unsupervised Learning Framework for Power control in D2D networks 3rd

A MPGNN-Based Unsupervised Learning Framework for Power Cont...

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3rd International conference on Artificial Intelligence, Robotics, and Communication, ICAIRC 2023

作者： Zhang, Yan He, Yucheng Zhang, Yu Xiamen Key Laboratory of Mobile Multimedia Communications Huaqiao University Xiamen362021 China

ISBN: (纸本)9789819721993

The Internet of Things (IoT) allows physical devices to be connected over wireless networks, and while device-to-device (D2D) communication has become a promising technology for IoT, traditional solutions for D2D resource allocation are often computationally complex and time-consuming. In order to improve the computational efficiency and improve the generalization performance of the algorithm, a large-scale power control unsupervised learning framework algorithm based on Message Passing Graph Neural network (MPGNN) was proposed, which aims to maximize the weighting and rate of all D2D links. To achieve the above goals, we first model the topology of the wireless network as a graph model, define the channel matrix as the graph structure, and then model the objective function of the system as a loss function and train the model parameters in the MPGNN with the help of the unsupervised learning model. After offline training, each D2D link can obtain the optimal power control strategy in a distributed manner according to the channel state information (CSI). Simulation shows that compared with the classic algorithm based on optimization theory, Weighted Minimum Mean Square Error (WMMSE), the computational efficiency of the proposed algorithm is increased by more than 50 times when the number of users is 100 pairs. In addition, compared with the traditional neural network algorithm, deep neural network (DNN), the proposed algorithm improves the generalization ability of the system under the same parameter settings. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Message passing

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Biometric-Based Access control Systems with Robust Facial Recognition in IoT Environments 3

Biometric-Based Access Control Systems with Robust Facial Re...

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3rd IEEE International conference on Intelligent Techniques in control, optimization and Signal Processing, INCOS 2024

作者： Satish Babu, B.V. Manoranjini, J. Changala, Ravindra Aarif, Mohd Mary, S. Suma Christal Raj, I Infant Prasad v Potluri Siddhartha Institute of Technology Department of It Vijayawada India Chaitanya Bharathi Institute of Technology Department of Ai & Ml Hyderabad India Guru Nanak Institutions Technical Campus Department of Information Technology Hyderabad India Associate Editor-Publishing Global Research Network Noida India Panimalar Engineering College Department of Information Technology Poonamalle Chennai India K. Ramakrishnan College of Engineering Department of Computer Science and Engineering Tamil Nadu Trichy India

ISBN: (纸本)9798350361186

The integration of biometric-based access control systems with robust facial recognition technology within Internet of Things (IoT) environments holds paramount significance in addressing contemporary security challenges. The novelty of the research endeavours to contribute to this critical area by investigating and implementing a novel approach, employing Convolutional Neural networks (CNN) for facial classification within the biometric framework. The significance of this study lies in its potential to enhance security measures in IoT environments, ensuring reliable and efficient access control. Previous attempts at integrating facial recognition into IoT have encountered notable challenges, including suboptimal accuracy, vulnerability to adversarial attacks, and scalability issues. This research builds upon these prior issues by introducing CNN for facial classification, leveraging its capabilities in image processing and pattern recognition to achieve enhanced accuracy and resilience against potential security threats. The novelty of the study is underscored by the application of CNN within the biometric context of IoT, offering a cutting-edge solution tailored to the intricacies of interconnected devices. Experiments conducted on benchmark datasets showcase the promising capabilities of the proposed system, with face recognition accuracies reaching an impressive 98%. These results underscore the potential of this research to significantly advance the state-of-the-art in biometric-based access control, particularly within the context of IoT environments. The utilization of CNN introduces a pioneering element, contributing to the evolution of secure and efficient access control solutions in the era of IoT. © 2024 IEEE.

关键词： Biometrics

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