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2023 IEEE 66th International Midwest Symposium on Circuits and Systems, MWSCAS 2023

作者： Wolters, Christopher Taylor, Brady Hanson, Edward Yang, Xiaoxuan Schlichtmann, Ulf Chen, Yiran Duke University Department of Electrical and Computer Engineering DurhamNC United States Institute for Electronic Design Automation Technical University of Munich Munich Germany

ISBN: (纸本)9798350302103

Movement of model parameters from memory to computing elements in deep learning (DL) has led to a growing imbalance known as the memory wall. Neuromorphic computation-in-memory (CIM) is an emerging paradigm that addresses this imbalance by performing computations directly in analog memory. However, sequential backpropagation of error through a network in DL prevents efficient parallelization. A novel method, direct feedback alignment (DFA), resolves layer dependencies by directly passing the error from the output to each layer. This work explores the interrelationship of implementing a bio-plausible learning algorithm like DFA in-situ on neuromorphic CIM hardware, emphasizing energy, area, and latency constraints. Using the DNN+NeuroSim benchmarking framework, we investigate the impact of hardware nonidealities and quantization on algorithm performance, as well as how network topologies and algorithm-level design choices scale latency, energy, and area consumption of a chip. While standard backpropagation learns more accurate models when faced with hardware imperfections, DFA enables significant speedup through parallelization, reducing training time by a factor approaching N for N-layer networks. © 2023 IEEE.

关键词： Compute-in-memory deep neural network direct feedback alignment hardware/software co-design

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Enhancing detection of SSVEP-based surround suppression using canonical correlation analysis 23

Enhancing detection of SSVEP-based surround suppression usin...

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2023 International Conference on computer, Vision and Intelligent Technology, ICCVIT 2023

作者： Chen, Sicong Hu, Wen Zhang, Xin Huang, Qiyun School of Automation Science and Engineering South China University of Technology Guangzhou China Research Center for Brain-Computer Interface Pazhou Lab Guangzhou China

ISBN: (纸本)9798400708701

Canonical correlation analysis (CCA), a method for assessing inter-signal correlation that is widely used to enhance the performance of brain-computer interfaces (BCIs), can play an effective role in detecting steady-state visual evoked potentials (SSVEPs) in response to target flicker stimuli. However, it remains unclear whether CCA-based measurements can enhance the quantification of a visual perceptual process that related to human psychophysics. In this study, we used SSVEP to achieve quantitative measurements of the surround suppression effect, a visual perceptual process related to the excitation-inhibition balance in the central nervous system based on electroencephalogram (EEG). The CCA method was compared with two traditional methods for SSVEP quantifications: the power spectral density (PSD) and the signal-to-noise ratio (SNR). Our results demonstrated that CCA had the highest sensitivity among the three to enhance the quantification of SSVEP-based surround suppression effect. Thus, our work confirmed that CCA is an outstanding method for SSVEP measurements, compared to the two other commonly used SSVEP detection methods mentioned below, not only in the field of artificial intelligence, such as the development of BCIs, but also can facilitate vision studies in cognitive and perceptual neuroscience. © 2023 ACM.

关键词： Brain computer interface

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Topology Maintenance Optimization Algorithm Based on Deep Reinforcement Learning in High Dynamic Flying Ad-Hoc Networks 2

Topology Maintenance Optimization Algorithm Based on Deep Re...

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2nd International Conference on Signal Processing, computer Networks and Communications, SPCNC 2023

作者： Li, Liheng Qiu, Xiulin Song, Bo Ke, Yaqi Yang, Yuwang School of computer Science and Engineering Nanjing University of Science and Technology Nanjing China School of Automation Jiangsu University of Science and Technology Jiangsu Zhenjiang China

ISBN: (纸本)9798400716430

In the realm of high-dynamic-flight self-organizing networks, traditional proactive and reactive routing protocols confront challenges arising from the delayed and inflexible determination of the validity of neighbour nodes. An untimely assessment of node validity may lead to an escalated overall network packet loss rate, consequently causing a proportional decrease in throughput. To mitigate this issue, this paper introduces a Reinforcement Learning based Topoloty Maintenance Algorithm (RLTM). This algorithm integrates the mobility characteristics and remaining energy of neighbour nodes into a stability metric for these nodes. By conceptualizing the validity of neighbour nodes in topology maintenance as a Markov process and incorporating the stability metric as a dimension in the state space, the model undergoes training via Proximal Policy Optimization (PPO) to generate decisions for establishing the effective time of neighbour nodes. Simulation results demonstrate that, in comparison to other topology maintenance optimization algorithms, the proposed algorithm amplifies the average packet delivery rate and throughput of unmanned aerial vehicle (UAV) nodes in high-speed mobility scenarios. © 2023 ACM.

关键词： Reinforcement learning

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Energy and Time-Optimized Task Scheduling with Simulated-Annealing-Based Firefly Algorithm in Hybrid Cloud Edge Computing

Energy and Time-Optimized Task Scheduling with Simulated-Ann...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Bi, Jing Zhou, Xinmin Yuan, Haitao Zhang, Jia Zhou, MengChu College of Computer Beijing University of Technology Beijing100124 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Southern Methodist University Dept. of Computer Science DallasTX75275 United States New Jersey Institute of Technology Dept. of Electrical and Computer Engineering NewarkNJ07102 United States

ISBN: (纸本)9781665410205

In a cloud-edge system, data analysis, processing, and storage can be performed in edge servers, avoiding transferring data to more distant cloud servers. This greatly improves the efficiency of data processing, saves network bandwidth and cloud resources, and reduces operating and maintenance costs. However, it is a challenge of how to perform task scheduling. It is difficult to schedule tasks for joint optimization of the total energy consumption and completion time of a task sequence within a limited time in a resource-constrained cloud-edge system. The work proposes an improved Simulated-Annealing-based Firefly Algorithm with Linear position update, called SAFAL for short. SAFAL incorporates a simulated annealing mechanism and an efficient position update strategy into the firefly algorithm, enabling fireflies to find the optimal solution more quickly and avoid getting trapped in local optima. SAFAL adopts a probabilistic mapping operator to map the position of each firefly to a task scheduling sequence, thus linking the firefly space and the task space. Several test instances in cloud-edge systems are designed to validate the superiority of SAFAL over the firefly algorithm, simulated annealing, and firefly algorithm with a self-adaptive strategy. Results show that the weighted cost of total energy consumption and completion time of SAFAL is reduced by 16.32%, 17.62%, and 14.21%, respectively, with 20 tasks. © 2024 IEEE.

关键词： Simulated annealing

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Node-Decomposition Privacy-Preserving for Finite-Time Secondary Control of DC Microgrids

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IEEE Transactions on Smart Grid 2025年第4期16卷 3295-3304页

作者： Wu, Han Zhu, Si-Min Chai, Li Zhu, Zhen-Hua Tian, Yu-Chu Wuhan University of Science and Technology Engineering Research Center of Metallurgical Automation and Measurement Technology School of Artificial Intelligence and Automation Wuhan430081 China Zhejiang University State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Hangzhou310027 China Huzhou Institute of Industrial Control Technology Huzhou China Queensland University of Technology School of Computer Science BrisbaneQLD4001 Australia

In the distributed secondary control of DC microgrids, achieving both rapid convergence and robust information security is critical for enhancing control performance and maintaining power quality. However, current privacy-preserving approaches often compromise either control performance or privacy preservation performance. To address this challenge, this paper presents a node-decomposition privacy-preserving (NDPP) method for fully distributed, finite-time secondary control in DC microgrids. By splitting each node in the communication graph into multiple sub-nodes, the method enhances both convergence speed and privacy preservation without sacrificing control accuracy. Sub-nodes communicate within groups, and the topology of the generated graph is concealed from malicious nodes and eavesdroppers. Theoretical analysis is provided to prove finite-time voltage regulation and current sharing with privacy preservation against malicious nodes and external eavesdroppers. Simulations are conducted to verify the effectiveness of the method in maintaining control performance and power quality. © 2010-2012 IEEE.

关键词： Privacy by design

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Computationally Efficient Core Losses Calculation and Thermal Evaluation Using the VBR-Based Finite Element Model of Induction Motors

Computationally Efficient Core Losses Calculation and Therma...

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2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023

作者： Valipoor, Zahra Koti, Hossein Nejadi Demerdash, Nabeel A. O. Marquette University Electrical and Computer Engineering Department Milwaukee United States Rockwell Automation Inc. Motion Control Team Mequon United States

ISBN: (纸本)9798350316445

Accuracy of the simulation results obtained from the FEA analysis of electric motors is highly dependent on the quality of the motor performance metrics such as motor steady state temperatures and losses. In addition such FEA analysis is typically computationally burdensome and demanding. Improving the computational burden and accuracy of core losses calculation and thermal evaluation in Time-Stepping Finite Element (TS-FE) models of induction motors is addressed in this paper. The Virtual Blocked Rotor (VBR)-based Time-Stepping Finite Element (TS-FE) technique is utilized to mitigate the numerical transient response of the induction motor FE model. The motor core losses have been calculated through the harmonic based core loss calculation that assumes variable loss coefficients as a function of magnetic flux density. In addition, the motor estimated losses, including the calculated core losses are fed to a thermal network model to estimate the temperature of different motor components. © 2023 IEEE.

关键词： Core Losses Induction Motor Temperature Thermal Calibration VBR-based FEA

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Enhancing Predictive Maintenance with AI: Applications and Impact

Enhancing Predictive Maintenance with AI: Applications and I...

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Mobile Computing and Sustainable Informatics (ICMCSI), International Conference on

作者： Chitranjanjit Kaur Anurag Sharma dept. School of Engineering Design and Automation (Computer Science and Engineering) GNA University Phagwara India

ISBN: (数字)9798331522667

ISBN: (纸本)9798331522674

Industrial maintenance is crucial for companies due to its significant impact on operational costs and efficiency. Many industrial firms find that a substantial portion of their expenses stems from equipment breakdowns, failures, or suboptimal performance over time. These costs can sometimes account for up to 50% of overall expenditures. Additionally, companies face various losses, including downtime from breakdowns, challenges in inventory and purchase management, and potential risks of injuries. The objective of this writing is to investigate how Predive maintenance is a footstep towards industry 5.0 where automation of predictive maintenance is evolved to autonomy in maintenance. In addition to it various machine learning algorithms are suggested to identify between healthy and poor data of a machine which is first step in Predictive maintenance then Deep learning algorithms to construct XAI (Explainable artificial Intelligence). Predictive maintenance, production scheduling, problem detection, predictive quality, and increased energy efficiency are highlighted in the typical use cases of the selected AI applications. Data from the real environment is transmitted to be virtually recreated. Efficient industrial maintenance helps mitigate these costs by reducing downtime, improving equipment reliability, and lowering the need for emergency repairs. By implementing a well-designed and optimized maintenance strategy, production plants can ensure their equipment operates as reliably as possible, minimizing disruptions and enhancing overall operational efficiency. Machine Learning (ML) methods have been appeared as a crucial tool in Predictive Maintenance (PdM) applications to prevent failures in equipment that make up the production lines. However, the performance of PdM applications depends on the appropriate choice of the ML method. To save expenses, find inefficiencies, duplicate tool tracking systems, and do other tasks, Digital Twin evaluates material utilization

关键词： Adaptation models Costs Machine learning algorithms Electric breakdown Stacking Companies Writing Vectors Maintenance Predictive maintenance

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Accumulating Priority Queue for Charging of Unmanned Aerial Vehicles in Cognitive Radio Networks 6

Accumulating Priority Queue for Charging of Unmanned Aerial ...

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6th International Symposium on Autonomous Systems, ISAS 2023

作者： Li, Yuran Zhai, Xiangping Bryce Wang, Ran Zhu, Jing Yao, Chenghua Nanjing University of Aeronautics and Astronautics College of Computer Science and Technology Nanjing China Nanjing University of Aeronautics and Astronautics College of Automation Engineering Nanjing China

ISBN: (纸本)9798350316155

The combination of cognitive radio networks and unmanned aerial vehicles (UAVs) can overcome the scarcity of spectrum for wireless networks and provide important benefits for large-scale deployment of UAVs. However, energy constraint is an inevitable challenge for UAV communication. In order to prolong the lifetime of UAVs, we apply the accumulating priority queue (APQ) discipline for the first time to the queuing charging process of UAVs in cognitive radio networks. The APQ is based on the classic priority queue with the accumulation rate added to it, which means that the priority of a user is a function of the waiting time. By analyzing the values for different arrival rates and priorities, we discuss the factors that affect the average waiting times and key performance indicators. We also consider the related optimization problem and propose an improved bisection algorithm. According to the requirements of different classes of users, we can adjust the accumulation rates and arrival rates to meet the performance indicators. © 2023 IEEE.

关键词： Wireless networks

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Tracking Control of Unmanned Surface Vessels Based on Fully Actuated System Approaches

Tracking Control of Unmanned Surface Vessels Based on Fully ...

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2023 China automation Congress, CAC 2023

作者： Li, Zijing Zhu, Jing Zhai, Xiangping College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing China College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China

ISBN: (纸本)9798350303759

Considering the complication and high requirements of controller design in unmanned surface vessels (USVs) from the perspective of under-actuated model, this paper investigates the tracking control of USVs in terms of fully actuated system approaches (FASA). We firstly propose a high-order fully actuated (HOFA) model of USV for path tracking. Then, using the idea and method of FASA controller design, a control law is proposed to make the closed-loop system obtain the dynamic characteristics we expect and decouple it into two linear systems, which can be achieved with simple and easy computation. The proposed USV path tracking control law achieves global asymptotic stability without continuous angular and forward velocity excitations. The effectiveness of this method is verified through MATLAB simulation. © 2023 IEEE.

关键词： MATLAB

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Securing Mobile Robots Multi-Party Authentication Technique Using Modified Elliptic Curve Cryptography

Securing Mobile Robots Multi-Party Authentication Technique ...

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2023 International Conference on Advanced Computing and Communication Technologies, ICACCTech 2023

作者： Haldar, Bilas Jha, Prabin Kumar The Neotia University Computer Science & Engineering West Bengal Sarisha743368 India The Neotia University Robotics & Automation West Bengal Sarisha743368 India

ISBN: (纸本)9798350380880

Mobile robots continue to play a pivotal role in various industries, safeguarding their operations against unauthorized access and cyber-attacks becomes increasingly critical. The burgeoning adoption of ubiquitous services across a variety of sectors has led to an exponential rise in mobile robot users. In this scenario, the authentication of mobile robots becomes a crucial requirement for ensuring data security and confidentiality. To protect the authenticity of confidential information it is necessary to provide strong authentication systems as these robots become key participants for providing a range of services. This work proposed an innovative approach to enhance the security of mobile robots by implementing Multi-Part Authentication (MP A) techniques using a modified Elliptic Curve Cryptography (ECC) algorithm. Traditional authentication methods often prove insufficient when it comes to the unique challenges faced by mobile robots, including remote control vulnerabilities, data integrity concerns, and the potential for physical tampering. The present work is a novel, efficient, and robust cryptography technique for generating keys using modified ECC and arithmetic greatest common divisor for multi-party communications. Additionally, the proposed work also presented a novel methodology of encryption and decryption techniques for the distribution of the authentication keys using a modified ECC algorithm. The results of the work show that the proposed technique ensures that only authorized users are able to control mobile robots as well as provide protection against attacks. © 2023 IEEE.

关键词： Authentication

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