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arXiv 2025年

作者： Aghamiri, Seyyed Ali Sharifnia, Reza Khonsari, Ahmad School of Electrical and Computer Engineering University of Tehran Tehran Iran

With the rapid advancement of blockchain technology, a significant trend is the adoption of Directed Acyclic Graphs (DAGs) as an alternative to traditional chain-based architectures for organizing ledger records. Systems like IOTA, which are specially designed for the Internet of Things (IoT), leverage DAG-based architectures to achieve greater scalability by enabling multiple attachment points in the ledger for new transactions while allowing these transactions to be added to the network without incurring any fees. To determine these attachment points, many tip selection algorithms commonly employ specific strategies on the DAG ledger. Consequently, recent research has moved from chain-based blockchains to Directed Acyclic Graph (DAG)-based blockchains, aiming to reduce transaction confirmation times. Prioritization is a strategy designed to enable faster confirmation of specific transactions. IoT applications can mark the priority level of essential transactions. Transaction prioritization is not considered in the IOTA network, which becomes especially important when network bandwidth is limited. In this paper, we propose an optimization framework designed to integrate a priority level for critical or high-priority IoT transactions within the IOTA network. We evaluate our system using fully based on the official IOTA GitHub repository, which employs the currently operational IOTA node software (Hornet version), as part of the Chrysalis update (1.5). The experimental results show that higher-priority transactions in the proposed algorithm reach final confirmation in less time compared to the original IOTA system. © 2025, CC BY.

关键词： Directed graphs

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Distance Protection of Transmission Lines in Presence of Inverter-Based Resources: A New Earth Fault Detection Scheme during Asymmetrical Power Swings

Distance Protection of Transmission Lines in Presence of Inv...

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作者： Jalilian, Amin Muttaqi, Kashem Sutanto, Danny Robinson, Duane School of Electrical Computer and Telecommunication Engineering University of Wollongong WollongongNSW Australia

Although it is commonly assumed that power swing is symmetrical and will have identical effects on all three-phase voltages and currents, there is another type of power swing, which is asymmetrical and mainly occurs during single-pole tripping (SPT), the impact of which on power systems integrated with the inverter-based resources (IBRs) has not been investigated so far. Since the likelihood of the occurrence of asymmetrical power swing is increasing in today's heavily loaded transmission lines, this article investigates the impact of IBR integration on the performance of distance protection during single-pole tripping. Furthermore, a new scheme is proposed to detect earth faults that occur during asymmetrical power swings to enhance the performance of power swing blocking functions. To do so, the superimposed component of the zero-sequence current during SPT is extracted. Then, the moving average window is used to calculate the average of both zero-sequence current and its superimposed component. Furthermore, to enhance the security of the proposed scheme, a new technique based on the phase angle shift between the three-phase currents is devised to detect the asymmetrical power swing conditions. This article shows that as the penetration level of IBRs increases, the standard reclosing dead-time needs to be revisited otherwise it can create an unstable power swing condition, even during SPT. Moreover, this article shows that the proposed earth fault detection scheme can efficiently detect all single-line-to-ground faults occurring during SPT. © 1972-2012 IEEE.

关键词： Electric lines

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Arbitrary acoustic orbital angular momentum detection using dual-layer metasurfaces

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Science China(Physics,Mechanics & Astronomy) 2024年第6期67卷 106-112页

作者： Zhanlei Hao Haojie Chen Yuhang Yin Shan Zhu Yadong Xu Cheng-Wei Qiu Huanyang Chen Department of Physics College of Physical Science and TechnologyXiamen UniversityXiamen 361005China Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore Department of Mechanical and Electrical Engineering Xiamen UniversityXiamen 361005China Pen-Tung Sah Institute of Micro-Nano Science and Technology Xiamen UniversityXiamen 361005China School of Physical Science and Technology and Jiangsu Key Laboratory of Thin Films Soochow UniversitySuzhou 215006China

Orbital angular momentum(OAM),with its unique physical properties and vast application prospects,has attracted widespread attention in various ***,the development of valid and practical acoustic OAM detection methods continues to be a challenging *** this paper,we propose a novel construction method of dual-layer metasurfaces to achieve a doubleconversion process for the waveform reshaping and differentiated focusing of two-dimensional vortex sources with different ***,by utilizing a concise formula,a one-to-one correspondence is established between the OAM of incident vortex waves and different imaging *** fundamental principle of this special conversion relationship is rigorously constrained by the directional compensation of phase and the material parameters of dual-layer metasurfaces with different quadratic phase *** importantly,the highly consistent results between numerical demonstrations and acoustic experiments further confirm the feasibility and effectiveness of the proposed OAM detection *** work provides a new perspective on the precise manipulation for the phase of vortex fields,holding potential applications in super-resolution imaging and the design of acoustic OAM-based devices.

关键词： arbitrary acoustic OAM detection vortex waves dual-layer metasurfaces waveform reshaping differentiated focusing acoustic experiments

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Verilog-A based implementation of Lorentzian noise spectra in compact models

Verilog-A based implementation of Lorentzian noise spectra i...

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2023 International Conference on Noise and Fluctuations, ICNF 2023

作者： Makris, Nikolaos Chevas, Loukas Bucher, Matthias School of Electrical & Computer Engineering ChaniaGR-73100 Greece Institute of Electronic Structure and Laser HeraklionGR-71110 Greece

ISBN: (纸本)9798350330113

In this paper, a simple Verilog-A implementation of Lorentzian noise spectra is introduced that can be used in compact models for the frequency-domain simulation of low-frequency noise in electronic devices. For this purpose, a thermal noise source is combined with a low-pass filter as realized using laplace nd Verilog-A function to achieve Lorentzian noise behavior. This modeling approach can be implemented in any Verilog-A compact model and provides the means for biasdependent Lorentzian trap modeling. This approach is evaluated in Cadence Spectre simulator. Application examples are provided to demonstrate the capabilities of this approach. © 2023 IEEE.

关键词： Low pass filters

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Impedance Modeling Method for Improving the Grid Stability of Grid-Forming Inverters

Impedance Modeling Method for Improving the Grid Stability o...

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Semiconductor and Electronic Technology (ISSET), International Symposium on

作者： Qiu Li Marloun P. Sejera School of Electrical Electronics and Computer Engineering Mapua University

ISBN: (数字)9798350390285

ISBN: (纸本)9798350390292

In the context of new energy generation, the application proportion of power electronic converters in the power system is constantly increasing, and the inertia and damping of the system are reduced, which leads to stability issues. This article focuses on the control strategy and stability analysis of grid-forming inverters, exploring different modeling and stability analysis methods. On this basis, this article adopts a virtual synchronous generator control strategy to determine the system topology structure of the grid-forming inverter. Then, a sequence impedance model of grid structured inverters based on virtual synchronous generators was established under three different inner loop control schemes, and the model was simplified. Furthermore, based on the established impedance model, stability analysis was conducted on the three-phase inverter grid-connected system.

关键词： Semiconductor device modeling Analytical models Delay effects Power system stability Frequency conversion Stability analysis Synchronous generators Topology Impedance Grid forming

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On the Impact of ISA Extension on Energy Consumption of I-Cache in Extensible Processors

arXiv

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arXiv 2024年

作者： Behboudi, Noushin Kamal, Mehdi Afzali-Kusha, Ali School of Electrical and Computer Engineering University of Tehran Iran

As is widely known, the computational speed and power consumption are two critical parameters in microprocessor design. A solution for these issues is the application specific instruction set processor (ASIP) methodology, which can improve speed and reduce power consumption of the general purpose processor (GPP) technique. In ASIP, changing the instruction set architecture (ISA) of the processor will lead to alter the number and the mean time of accesses to the cache memory. This issue has a direct impact on the processor energy consumption. In this work, we study the impacts of extended ISA on the energy consumption of the extended ISA processor. Also, we demonstrate the extended ISA let the designer to reduce the cache size in order to minimize the energy consumption while meeting performance constraint. Copyright © 2024, The Authors. All rights reserved.

关键词： Cache memory

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Microservice Deployment for Satellite Edge AI Inference via Deep Reinforcement Learning 35

Microservice Deployment for Satellite Edge AI Inference via ...

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35th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2024

作者： Yu, Zhiyong Cheng, Hei Victor Yang, Zhanpeng Liu, Xin Jiang, Yuning Zhou, Yong Shi, Yuanming ShanghaiTech University School of Information Science and Technology Shanghai201210 China Aarhus University Department of Electrical and Computer Engineering Denmark Automatic Control Laboratory Switzerland

ISBN: (纸本)9798350362244

Artificial intelligence (AI) is critical in evolving 5G and developing 6G networks, running on edge devices, and solving resource management challenges. The burgeoning number of edge devices draws attention to the potential of low-earth orbit (LEO) satellite networks with their onboard computing capabilities for edge inference. This paper explores LEO scenarios where multiple remote sensing edge AI inference tasks concurrently process data from a single source. However, due to there being parts with the same functions between different AI applications, traditional monolithic edge AI architecture must be deployed repeatedly and falls short in efficiently harnessing the heterogeneous resources of LEO satellite networks. To solve this problem, we utilize the microservice architecture to decouple a single AI application into several independent microservices to reuse these same functions. However, due to the high latency caused by multiple microservices' communication, we need to design a deployment strategy to fully utilize resources to reduce the service latency. We present a microservice deployment model to minimize the total service latency across all AI applications and meet resource constraints with the constraints of hardware, energy, and memory limitations. This latency optimization problem is rewritten as a Markov decision process (MDP) to effectively deal with the challenge posed by the time-varying transmission rate caused by satellite mobility. To increase the training data utilization, we employ a Proximal Policy Optimization (PPO) based reinforcement learning algorithm to meet the dynamic environment challenge. Finally, we obtain a sub-optimal solution with minimal accuracy loss and an acceptable solution time. © 2024 IEEE.

关键词： Markov processes

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An Improved Affinity Propagation-Based Typical Process Route Discovery Approach Considering Clustering Effectiveness 42

An Improved Affinity Propagation-Based Typical Process Route...

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42nd Chinese Control Conference, CCC 2023

作者： Xu, Binzi Yang, Long Deng, Xiongfeng Tao, Liang Li, Wei Huang, Dengchao Zhang, Yao School of Electrical Engineering Anhui Polytechnic University Wuhu241000 China School of Computer Jiangsu University of Science and Technology Zhenjiang212100 China

ISBN: (纸本)9789887581543

With the increasing development of CAPP (computer Aided Process Planning), an urgent requirement has arisen on how to extract reusable process knowledge effectively. Under this situation, an improved AP (affinity propagation) based clustering approach has been proposed to discover typical process routes from massive historical data under the consideration of clustering effectiveness. Because of the practical requirement of typical process routes, two soft constraints (i.e., quantity constraint and size constraint) have been introduced simultaneously in the clustering process to guarantee the quality and effectiveness of the typical process routes. In doing so, the traditional AP has been improved with two extra function nodes, which represent the two soft constraints mentioned before respectively. Finally, the results of numerical illustrations indicate that the improved AP can find a tradeoff between these two conflicting soft constraints and have better performance compared with commonly used clustering methods for typical process route discovery. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Numerical methods

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Wireless Broadband Ad Hoc network Communication Algorithm Based on IGS Technology 4

Wireless Broadband Ad Hoc Network Communication Algorithm Ba...

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4th IEEE International Conference on Mobile networks and Wireless Communications, ICMNWC 2024

作者： Wang, Haigang Ren, Liming Dai, Chen Jiang, Jiafeng School of Information Science and Technology Tsinghua University Beijing China School of College of Electronic Information and Electrical Engineering Hefei University Anhui Hefei China Nanjing University of Engineering Department of Computer Engineering Jiangsu Nanjing China School of Information Engineering Inner Mongolia University of Science and Technology Inner Mongolia Baotou China

ISBN: (纸本)9798350352931

In response to the problems faced by traditional wireless broadband ad hoc network communication algorithms in dealing with complex and changing network environments, this paper introduces the IGS (Imperfer Gaussian Signaling) technology based on wide linear new waveforms, aiming to improve the transmission efficiency and anti-interference ability of devices. Firstly, the study aims to optimize communication requirements in multiple scenarios of power business;then, the use of IGS technology is studied to convert non-circular signals into Gaussian distribution signals;finally, the study is conducted on intelligent routing algorithms based on wide linear new waveform to optimize path selection between nodes and dynamically adjust topology connections, thereby enhancing the system's self-organization capability and network throughput. As the number of nodes continues to increase to 500, the latency of traditional systems has risen to 33 milliseconds. Wireless broadband self-organizing network communication devices based on IGS technology provide efficient and stable solutions for large-scale self-organizing network applications in the power industry. © 2024 IEEE.

关键词： Ad hoc networks

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Multi-Input Deep Learning Models for Weight Forecasting of Pigs Using Depth Images 36

Multi-Input Deep Learning Models for Weight Forecasting of P...

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36th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2024

作者： Ranjan, Pranjal Ha, Dong Sam Morota, Gota Shin, Sook Bradley Department of Electrical and Computer Engineering Virginia Tech Virginia24061 United States School of Animal Sciences Virginia Tech Virginia24061 United States

ISBN: (纸本)9798331527235

Accurate weight forecasting is essential for optimizing swine farming operations and enhancing animal welfare. This paper introduces a novel approach for pig weight forecasting, employing multi-input deep learning models that harness both depth images and statistical descriptors. The study conducts a comprehensive comparison of traditional machine learning (ML) models, deep learning (DL) models, hybrid ML and DL models, and multi-input models integrating both time-series data and image features. A meticulously curated dataset comprising time-series weight measurements and corresponding depth images of pigs forms the foundation of the study. Image descriptors such as length, width, depth, and volume were extracted from the depth images. The proposed multi-input models, employing architectures based on ResNet, XCeption, LSTM, and GRU layers, are meticulously trained and evaluated using this dataset. The performance evaluation is conducted using mean absolute error (MAE) and mean absolute percentage error (MAPE) metrics. The results underscore the superiority of the multi-input models over traditional ML, DL, and hybrid models. Notably, the best-performing model achieves a test MAE of 1.81 kg and a test MAPE of 5.56 %. This exceptional performance highlights the importance of leveraging both time-series data and image features for precise weight forecasting in pigs. These findings can hold significant implications for improving the efficiency and sustainability of swine farming practices, offering a pathway towards improved decision-making and animal management protocols. © 2024 IEEE.

关键词： Contrastive Learning

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