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Research on Seismic Security Evaluation Model and Route Reconfiguration Algorithm for Public Communication Networks

Research on Seismic Security Evaluation Model and Route Reco...

引用

International Conference on Communication Technology (ICCT)

作者： Mingchao Han Guoliang Sun Xiangping Li Xuezhong Zhang Shuqiang Ji China Telecommunication Technology Labs China Academy of Information and Communications Technology Baoding China

ISBN: (数字)9798350363760

ISBN: (纸本)9798350363777

Seismic disaster would cause overall performance degradation or even failure of public communication networks. To analyze the security performance of networks responding to seismic disasters scenarios, a nodes-lines evaluation model is proposed based on graph theory and Monte Carlo method, which clarifies the mathematical probability relationship between seismic parameter and performance of the networks. And then, we present a post-disaster route reconfiguration algorithm with optimal recovery time as objective function considering social dimensions. Finally, two cases analysis are given which verify the feasibility of the proposed evaluation model and route algorithm respectively. This research provides effective methodologies for seismic security evaluation and rapid post-disaster recovery of public communication networks.

关键词： Disasters Evaluation models Reconstruction algorithms linear programming Routing Graph theory Communication networks Security Optimization Electronics packaging

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Three-Dimensional Magnetic Target Inversion and Simulation

Three-Dimensional Magnetic Target Inversion and Simulation

引用

China Instrument and Control Society (ACCIS), Academic Conference of

作者： Lu Yin Xiaoyan Zhao Tianyao Zhang Jianmei Guo Fan Song Lei Han Liang Liang Zhaohui Zhang School Of Automation And Electeical Engineering University of science and Technology Beijing Beijing China

ISBN: (数字)9798350350326

ISBN: (纸本)9798350350333

Susceptibility inversion of near-field magnetic sources has played an increasingly important role in the field of magnetic target detection in recent years. In this paper, the GBO algorithm, an objective optimization algorithm that combines Newton's iterative method with genetic algorithm, is used to find the optimal objective function. At the same time, we improved the setup conditions for the initial populations so that their priori information could be more fully utilized. In this study, the simulation software was used to generate the magnetic anomaly data for four models, which were then inverted with promising results, demonstrating the significant role of the GBO optimization algorithm in the physical inversion of magnetic targets. Finally, an experimental platform is built to realistically measure the magnetic target to be measured, proving the effectiveness of the GBO algorithm in magnetization rate inversion.

关键词： Magnetization Instruments Software algorithms Object detection linear programming Software Iterative methods Optimization Magnetic susceptibility Genetic algorithms

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Deployment of Airborne Distributed MIMO Radar for Task Reinforcement

Deployment of Airborne Distributed MIMO Radar for Task Reinf...

引用

IEEE National Conference on Radar

作者： Chuhan Wang Xiaolong Li Mingxing Wang Zhao Zhang Guolong Cui School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9798350329209

ISBN: (纸本)9798350329216

Airborne radar deployment optimization signifi-cantly enhances the utilization ratio of resources such as flight loss and strengthens the target detection capability. This article investigates a deployment optimization method of airborne dis-tributed multiple input multiple output (MIMO) radar for task reinforecement. In order to improve detection ability and reduce flight loss, we use effective coverage rate and total flight cost as objective functions and develop a multi-objective optimization model. Considering that the problem has more than one objective and dimension, we propose a multi-objective particle swarm optimization with dynamic weight relative crowding distance (MOPSO-DWRCD) algorithm. Compared to traditional MOPSO, MOPSO-DWRCD exhibits better performance in global optimal solution selection in each iteration. Finally, simulation results are provided to verify the effectiveness of the proposed algorithm.

关键词： Costs Heuristic algorithms MIMO radar Simulation Airborne radar Radar detection linear programming

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A New Optimization Approach to Solve the Optimal Reactive Power Dispatch Problem for Real Power Loss Minimization, Voltage Deviation Minimization and Voltage Stability Enhancement

A New Optimization Approach to Solve the Optimal Reactive Po...

引用

International Conference on Advanced Electrical Engineering (ICAEE)

作者： Abdallah Chanane Messaoud Belazzoug Laboratoire des systérnes électriques et télécornmande Faculté de Technologie Université Blida 1 Soumaa Blida Algerie

ISBN: (数字)9798350349351

ISBN: (纸本)9798350349368

This study proposes a novel method based on K-means and the Logistic Chaotic JAYA algorithm (LCJAYA) to resolve the ORPD problem for real power loss minimization, voltage deviation minimization and voltage stability enhancement. Firstly, the K-means method is introduced to cluster the setting of control variables including the generation voltage magnitude, the tap changing transformers and the reactive power of the compensation devices. Then, the LCJAYA is used to determine the cluster centers. The proposed algorithm uses at first, a Logistic Chaotic to enhance the population diversity and to improve the exploration search areas. Then, a chaotic mutation strategy to improve the exploration and the exploitation. IEEE 57 Bus system is used to validate the proposed algorithm. The optimization algorithm is general and can be used to solve other power system optimization problems

关键词： Electrical engineering Reactive power Clustering algorithms Power system stability Minimization Transformers linear programming Voltage control Optimization Logistics

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Multi-Infeed SCR Margin Evaluation Method Considering DC Terminal Location Selection

Multi-Infeed SCR Margin Evaluation Method Considering DC Ter...

引用

HVDC (HVDC), International Conference on

作者： Zhijuan Zhang Xiaowei Yu Minxiao Han Hongmei Luo School of Electrical and Electronic Engineering North China Electric Power University Beijing China Central China Branch of State Grid Corporation of China State Grid Corporation of China Wuhan China Power System Department China Electric Power Research Institute Beijing China

ISBN: (数字)9798350387759

ISBN: (纸本)9798350387766

Multi-infeed short circuit ratio (MISCR) is an important index for evaluating the AC system capability interconnecting HVDC systems. With a view to analyzing the influence of the margin of MISCR on DC access, based on the MISCR established by the multi-infeed interaction factor (MIIF) based on the reduced Jacobian matrix. First, proposes the multi-infeed SCR margin index and the multi-infeed SCR margin interference index. Then, based on the method of constructing a weighted objective function, a method for evaluating multi-infeed SCR margin with consideration of DC terminal location selection is presented, and the procedure for applying this method to select the DC terminal location is provided. Ultimately, the proposed method's effectiveness is confirmed through simulation analysis of a 3-infeed 11-bus system. The findings indicate that the assessment approach suggested in this paper has the capability to quantitatively evaluate the multi-infeed SCR margin of the system and can be effectively applied to the selection of DC terminal location.

关键词： Jacobian matrices HVDC transmission Integrated circuit interconnections Interference linear programming Power grids Indexes

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ORIENT: A Priority-Aware Energy-Efficient Approach for Latency-Sensitive Applications in 6G

ORIENT: A Priority-Aware Energy-Efficient Approach for Laten...

引用

IEEE International Conference on Communications (ICC)

作者： Masoud Shokrnezhad Tarik Taleb Oulu University Oulu Finland Ruhr University Bochum Bochum Germany

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

Anticipation for 6G's arrival comes with growing concerns about increased energy consumption in computing and networking. The expected surge in connected devices and resource-demanding applications presents unprecedented challenges for energy resources. While sustainable resource allocation strategies have been discussed in the past, these efforts have primarily focused on single-domain orchestration or ignored the unique requirements posed by 6G. To address this gap, we investigate the joint problem of service instance placement and assignment, path selection, and request prioritization, dubbed PIRA. The objective function is to maximize the system's overall profit as a function of the number of concurrently supported requests while simultaneously minimizing energy consumption over an extended period of time. In addition, end-to-end latency requirements and resource capacity constraints are considered for computing and networking resources, where queuing theory is utilized to estimate the Age of Information (AoI) for requests. After formulating the problem in a non-linear fashion, we prove its NP-hardness and propose a method, denoted ORIENT. This method is based on the Double Dueling Deep Q-Learning (D3QL) mechanism and leverages Graph Neural Networks (GNNs) for state encoding. Extensive numerical simulations demonstrate that ORIENT yields near-optimal solutions for varying system sizes and request counts.

关键词： 6G mobile communication Energy consumption Q-learning NP-hard problem Numerical simulation linear programming Information age

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Enhanced Security-based Energy-aware Routing for RPL in IoT Network

Enhanced Security-based Energy-aware Routing for RPL in IoT ...

引用

International Conference on Circuits, Communication, Control and Computing

作者： Poornima M R Vimala H S Shreyas J Dept. of CSE UVCE Bengaluru India Dept. IT MAHE Manipal Institute of Technology Manipal India

ISBN: (数字)9798331528539

ISBN: (纸本)9798331528546

The rapid growth of Low-Power and Lossy Networks (LLN s) in the Internet of Things (IoT) has brought significant advancements in connectivity and automation, particularly in environments with constrained resources and unstable communication links. However, this widespread adoption also exposes LLN s to various security threats, including rank, version number, and neighbor attacks, which can severely disrupt network operations and compromise data integrity. This paper proposes an Intrusion Detection System (IDS) tailored for Routing Protocol for Low-Power and Lossy Networks (RPL), aimed at detecting and mitigating these specific attacks. The proposed hybrid-trust-based IDS (H-TIDS) employs a multi-faceted approach, incorporating enhanced rank verification mechanisms within the energy-efficient Objective Function (OF) and utilizing version numbers and timestamps to ensure the freshness and integrity of routing information. The IDS effectively identifies and neutralizes malicious activities by monitoring and analyzing the consistency of rank values, detecting anomalies in version number updates, and validating the authenticity of neighboring nodes. Extensive simulations demonstrate the efficacy of the proposed work in maintaining efficiency, network stability, and security, thereby reinforcing the resilience of RPL-based LLNs against sophisticated attacks. The performance of the proposed approach is analyzed and compared with existing work in terms of energy efficiency and increased network throughput. The results show that the proposed approach outperforms the existing methods.

关键词： Routing Throughput linear programming Energy efficiency Stability analysis Routing protocols Security Internet of Things Monitoring Resilience

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CAD-Informed Uncertainty-Aware Sequence and Motion Planning for Robotic Assembly

CAD-Informed Uncertainty-Aware Sequence and Motion Planning ...

引用

IEEE International Conference on Automation Science and Engineering (CASE)

作者： Takuya Kiyokawa Ismael Rodriguez Korbinian Nottensteiner Peter Lehner Thomas Eiband Maximo A. Roa Kensuke Harada Department of Systems Innovation Graduate School of Engineering Science Osaka University Osaka Japan Institute of Robotics and Mechatronics German Aerospace Center (DLR) Oberpfaffenhofen Weßling Germany Industrial Cyber-Physical Systems Research Center The National Institute of Advanced Industrial Science and Technology (AIST) Tokyo Japan

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

This study addresses a multi-objective optimization problem in the planning of an uncertainty-aware sequence and motion for mechanical products with intricate structures and numerous contact areas. To generate an optimized sequence and motion that satisfies multiple conditions under mandatory requirements, we use a multi-objective optimization algorithm inspired by Non-Dominated Sorting Genetic Algorithm III, along with contact-rich robotic assembly-oriented constraints and objective functions. The proposed pipeline takes as input the CAD models of robot hardware, workspace, and assembled parts, conducts 3D geometrical and physical simulations of assembly motions, and then optimizes the assembly plan, including parts order, object placement pose, state transition, grasp, and trajectory for the real robot to execute. To obtain the uncertainty-aware sequence and motion, we incorporated a Contingent Contact-Exploring Rapidly-exploring Random Trees (ConCERRT)-based state transition planner and an objective function to evaluate the uncertainty in the multi-objective optimization algorithm. Our experiments on assembly planning for a chainsaw product demonstrated that the proposed method can generate constraint-satisfied assembly plans with a success rate of 99.2% while lowering the uncertainty in the simulations.

关键词： Robotic assembly Solid modeling Uncertainty linear programming Planning Trajectory Mechanical products Robots Optimization Assembly

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Constant Modulus IRS-Assisted Secure Beamforming for Massive MIMO

Constant Modulus IRS-Assisted Secure Beamforming for Massive...

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IEEE International Conference on Communications Workshops, ICC

作者： Weijie Xiong Yuhan Zhang Jingran Lin Kai Zhong Jinfeng Hu University of Electronic Science and Technology of China Chengdu China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing China

ISBN: (数字)9798350304053

ISBN: (纸本)9798350304060

The physical layer (PHY) security is a key technology for constant modulus (CM) massive MIMO systems. In this paper, we consider using an intelligent reflecting surface (IRS) to provide the system with additional degrees of freedom, thus enhancing its performance. We approach the problem from an optimization perspective, aiming to maximize the security rate. The optimization problem presents significant challenges due to highly coupled variables, non-convex constraints and the non-concave objective function. To tackle these challenges, we propose an efficient alternating optimization (AO) method. This method guarantees convergence to a Karush-Kuhn-Tucker (KKT) point and separately optimizes the CM beamforming and phase shift coefficients at the IRS as two sub-problems. Both sub-problems are solved using similar frameworks of the Dinkelbach method and the alternating direction method of multipliers (ADMM). Simulation results show that the proposed method outperforms many other related methods.

关键词： Array signal processing Simulation Conferences Massive MIMO Physical layer linear programming Convex functions

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Investigation and Solution of One Class of Nonlinear Optimization Problems

Investigation and Solution of One Class of Nonlinear Optimiz...

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Problems of Logistics, Management and Operation in the East-West Transport Corridor (PLMO), International Conference on

作者： Kamil Aida-zade Azer Baghirov Laboratory of recognition identification and methods of optimal solutions Institute of Control Systems Baku Azerbaijan

ISBN: (数字)9798350353099

ISBN: (纸本)9798350353105

This paper examines a special class of nonlinear programming problems. The problem is characterized by 1) nonlinearity of the objective function and functions defining constraints of the equality type; 2) large dimension of optimized variables; 3) sparseness of the Jacobian matrix of equality type constraints. By applying graph theory to the problem of obtaining constructive formulas for the gradient of the objective function. The obtained formulas made it possible to propose a gradient projection method for a numerical solution.

关键词： Jacobian matrices Optimization methods Optimal control programming linear programming Raw materials Mathematical models Numerical models MATLAB Logistics

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