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arXiv 2023年

作者： Liu, Yinqiu Du, Hongyang Niyato, Dusit Kang, Jiawen Xiong, Zehui Miao, Chunyan Shen, Xuemin Jamalipour, Abbas The School of Computer Science and Engineering Nanyang Technological University Singapore The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The Department of Electrical and Computer Engineering University of Waterloo Canada The School of Electrical and Information Engineering University of Sydney Australia

The rapid development of Artificial Intelligence-Generated Content (AIGC) has brought daunting challenges regarding service latency, security, and trustworthiness. Recently, researchers presented the edge AIGC paradigm, effectively optimize the service latency by distributing AIGC services to edge devices. However, AIGC products are still unprotected and vulnerable to tampering and plagiarization. Moreover, as a kind of online non-fungible digital property, the free circulation of AIGC products is hindered by the lack of trustworthiness in open networks. In this article, for the first time, we present a blockchain-empowered framework to manage the lifecycle of edge AIGC products. Specifically, leveraging fraud proof, we first propose a protocol to protect the ownership and copyright of AIGC, called Proof-of-AIGC. Then, we design an incentive mechanism to guarantee the legitimate and timely executions of the funds-AIGC ownership exchanges among anonymous users. Furthermore, we build a multi-weight subjective logic-based reputation scheme, with which AIGC producers can determine which edge service provider is trustworthy and reliable to handle their services. Through numerical results, the superiority of the proposed approach is demonstrated. Last but not least, we discuss important open directions for further research. © 2023, CC BY.

关键词： Blockchain

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Distributed Optimization with Gradient Descent and Quantized Communication

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IFAC-PapersOnLine 2023年第2期56卷 5900-5906页

作者： Apostolos I. Rikos Wei Jiang Themistoklis Charalambous Karl H. Johansson Division of Decision and Control Systems KTH Royal Institute of Technology SE-100 44 Stockholm Sweden Digital Futures SE-100 44 Stockholm Sweden Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Espoo Finland Department of Electrical and Computer Engineering School of Engineering University of Cyprus Nicosia Cyprus

In this paper, we consider the unconstrained distributed optimization problem, in which the exchange of information in the network is captured by a directed graph topology, thus, nodes can only communicate with their neighbors. Additionally, in our problem, the communication channels among the nodes have limited bandwidth. In order to alleviate this limitation, quantized messages should be exchanged among the nodes. For solving this distributed optimization problem, we combine a gradient descent method with a distributed quantized consensus algorithm (which requires the nodes to exchange quantized messages and converges in a finite number of steps). Specifically, at every optimization step, each node (i) performs a gradient descent step (i.e., subtracts the scaled gradient from its current estimate), and (ii) performs a finite-time calculation of the quantized average of every node's estimate in the network. As a consequence, this algorithm approximately mimics the centralized gradient descent algorithm. We show that our algorithm asymptotically converges to a neighborhood of the optimal solution with linear convergence rate. The performance of the proposed algorithm is demonstrated via simple illustrative examples.

关键词： Distributed optimization quantized communication directed graphs finite-time consensus

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Blockchain-Empowered Lifecycle Management for AI-Generated Content (AIGC) Products in Edge Networks

TechRxiv

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TechRxiv 2023年

关键词： Blockchain

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Design of an Electronically Controlled Biquadratic Filter Using Commercial ICs

Design of an Electronically Controlled Biquadratic Filter Us...

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13th International Electrical engineering Congress, iEECON 2025

作者： Ritnathikul, Somkid Duangmalai, Danupat Kaewdang, Khanittha Kwuanphet, Settasuk Chalermpong, Thanawat Pitaksuttayaprot, Koson Phetchabun Rajabhat University Faculty of Agricultural and IndustrialTechnology Department of Computer Engineering Phetchabun6700 Thailand Ubon Ratchathani University Faculty of Engineering Department of Electrical and Electronic Engineering Ubon Ratchathani34190 Thailand Nakhon Phanom University Faculty of Industrial Technology Department of Electrical Engineering Nakhon Phanom48000 Thailand Phetchabun Rajabhat University Faculty of Agricultural and Industrial Technology Department of Electronics and Automation Systems Engineering Phetchabun6700 Thailand

ISBN: (纸本)9798331543952

This paper presents an electronically controlled biquadratic filter designed for precise frequency selection in applications such as audio processing, telecommunications, and cochlear implants. The design utilizes AD830, AD844, and LM13700 integrated circuits, facilitating high-pass, band-pass, and low-pass responses with improved stability and real-time tunability. PSPICE simulations validate the filter's adaptability and performance, demonstrating its effectiveness in dynamic environments and its suitability for high-frequency applications requiring flexible frequency control. The results indicate a calculated pole frequency of 2.23 MHz, while simulations yield a slightly lower value of 2.0 MHz, affirming the design's practical viability and alignment with theoretical expectations. © 2025 IEEE.

关键词： LSI circuits

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DESIGNING EV CHARGING STATIONS DEPLOYMENT THROUGH HOLISTIC SIMULATIONS: THE SANEVEC PROJECT 5

DESIGNING EV CHARGING STATIONS DEPLOYMENT THROUGH HOLISTIC S...

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5th Conference on Code of Practice for Electric Vehicle Charging Equipment Installation: Charging Ahead, EVI 2023

作者： Guisado-Lizar, José-Luis Jiménez-Moreno, Gabriel Diaz-Del-Rio, Fernando Sevillano-Ramos, J.L. Cagigas-Muñiz, Daniel Morón-Fernández, María José Cascado-Caballero, Daniel Jiménez-Morales, Francisco Cárdenas-Montes, Miguel Wainer, Gabriel A. Ragel-Díaz-Jara, David Rodríguez-Leal, J. Cerezuela-Escudero, E. Montes-Sánchez, J.M. Casanueva-Morato, Daniel Ayuso-Martínez, Alvaro Universidad de Sevilla Avenida Reina Mercedes s/n Sevilla41012 Spain Department of Computer Architecture and Technology Universidad de Sevilla Avenida Reina Mercedes s/n Sevilla41012 Spain Department of Condensed Matter Physics Universidad de Sevilla Avenida Reina Mercedes s/n Sevilla41012 Spain Department of Basic Research Centro de Investigaciones Energéticas Medioambientales y Tecnológicas Madrid Spain Department of Systems and Computer Engineering Carleton University Ottawa Canada

ISBN: (纸本)9781839539848

To determine the optimal location of the large number of urban public charging stations that will have to be deployed in the following years to transition to electric vehicles (EVs) is a challenging task, as it is intimately interconnected with the complexity of urban traffic and electric grid operation. The city is a complex system in which emerging patterns such as traffic jams, and instabilities or even outages in the electric grid are difficult to predict. The layout of charging stations can alter those patterns in traffic and electric grid operation, with consequences to mobility, air quality, and electric system. The present article presents the concept under the research project SANEVEC. It will build a framework for the optimal determination of the location of EV charging stations in a city based on simulation, which will be able to reproduce the feedback effects between all the variables involved: locations of the stations, traffic patterns, characteristics, and operation of the electricity grid, charging fees and air quality in the city. It will employ artificial intelligence methods to find high-quality station location solutions from the simulations and to predict the air quality in the city. © The Institution of engineering & technology 2023.

关键词： Air quality

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Optimized Model Predictive Control for Unmanned Aerial Vehicles with Sensor Uncertainties

Optimized Model Predictive Control for Unmanned Aerial Vehic...

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2022 International Conference on Control, automation and Diagnosis, ICCAD 2022

作者： Taher Azar, Ahmad Serrano, Fernando E. Ahmad Kamal, Nashwa Qureshi, Basit Al Mhdawi, Ammar K. Humaidi, Amjad J. Kasim Ibraheem, Ibraheem Ben Njima, Chakib Prince Sultan University College of Computer and Information Sciences Riyadh Saudi Arabia Benha University Faculty of Computers and Artificial Intelligence Benha Egypt Faculty of Engineering and Architecture Tegucigalpa Honduras Cairo University Faculty of Engineering Egypt Hill University United Kingdom University of Technology Control and Systems Engineering Department Baghdad Iraq Dijlah University College Department of Computer Techniques Engineering Baghdad10001 Iraq University of Sousse Tunisia

ISBN: (数字)9781665497947

ISBN: (纸本)9781665497947

In this paper, a novel control strategy based on model predictive control is proposed for tracking the trajectory of unmanned aerial vehicles (UAV). First, the dynamic model of an unmanned aerial vehicle UAV is established by considering the linear velocities in terms of the analyzed system's attitude angles. The UAV's dynamic model is suitable for kinematic control by using two attitude angles as control inputs. The controller design is made up of an output feedback controller formed by the error variables, which are the difference between the measured output and the reference variables. Then, a model predictive control is established by considering an optimization problem with a performance index and the corresponding constraints. Furthermore, the stochastic properties of the UAV dynamic model are taken into account in this research study. The measured outputs provided by the sensors are constrained by the topological characteristics of the unmanned aerial vehicle to be analyzed. Finally, a numerical experiment and its conclusions are presented, demonstrating that the proposed control strategy provides optimal trajectory tracking. © 2022 IEEE.

关键词： Model predictive control

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Event Graphs: Syntax, Semantics, and Implementation

Event Graphs: Syntax, Semantics, and Implementation

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2023 Winter Simulation Conference, WSC 2023

作者： Gunal, Murat M. Ismail Osais, Yahya Wagner, Gerd Fenerbahce University Faculty of Engineering and Architecture Atatürk Mah. Ataşehir Bulvari Istanbul Ataşehir34758 Turkey Center for Intelligent Secure Systems King Fahd University of Petroleum and Minerals Computer Engineering Department P.O. Box 2244 Dhahran31261 Saudi Arabia Brandenburg University of Technology Konrad-Wachsmann-Allee 5 Cottbus03046 Germany

ISBN: (纸本)9798350369663

This tutorial aims to introduce Event Graphs (EGs), invented 40 years ago by Lee Schruben to allow eventbased modeling of discrete dynamic systems. Their simplicity and naturalness in causality modelling and simulation modelling made EGs popular in research and practice. In a simulation, an event causes state changes in a system as well as other events to happen in the future. EGs provide a parsimonious diagram representation for the Event Scheduling paradigm of Discrete Event Simulation. We first introduce their visual syntax and informal semantics, and then present a recent extension by adding objects to EGs. Our tutorial also includes an introduction to the formal semantics of EGs and a Python implementation for executing EGs. © 2023 IEEE.

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Event Graphs: Syntax, Semantics, and Implementation

Event Graphs: Syntax, Semantics, and Implementation

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Simulation Winter Conference

作者： Murat M. Gunal Yahya Ismail Osais Gerd Wagner Faculty of Engineering and Architecture Fenerbahce University Turkey Computer Engineering Department Center for Intelligent Secure Systems King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia Brandenburg University of Technology Germany

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Hydrogen Supply Infrastructure Planning Method Considering Indirect Network Effects

Hydrogen Supply Infrastructure Planning Method Considering I...

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IEEE Energy Conversion Congress and Exposition, ECCE

作者： Haoran Deng Bo Yang Dafeng Zhu Gang Yao Xinping Guan Dipti Srinivasan Department of Automation Shanghai Jiao Tong University Shanghai China Electric Power and Energy Systems Division KTH Royal Institute of Technology Stockholm Sweden Department of Electrical Engineering Shanghai Jiao Tong University Shanghai China Department of Electrical & Computer Engineering National University of Singapore Singapore

ISBN: (数字)9798350376067

ISBN: (纸本)9798350376074

At the early commercialization stage of hydrogen fuel cell vehicles (HFCVs), there is a strong causal relationship between HFCV parc and hydrogen refueling stations (HRSs) planning, also known as indirect network effects. This is a crucial factor that hasn’t been considered and cannot be ignored in the hydrogen supply infrastructure planning (HSIP) problem. To model the indirect network effects, we quantify the effect of HRS planning on HFCV parc in detail by proposing the calculation method of drivers’ fuel buffer, defining hydrogen refueling convenience, and incorporating coupled constraints between the hydrogen network and transportation network. Further, we characterize the effect of HFCVs on HRS planning by constructing a decision-dependent distributionally robust optimization problem considering the HFCV parc uncertainty. We innovatively quantify the upper bound of the ambiguity set of Wasserstein associated with both the endogenous and exogenous factors. We propose effective linearization methods to deal with the nonlinear constraints in the indirect network effects model and transform the two-stage optimization problem into a solvable MILP problem. The simulation results show that the proposed method can obtain more economical investment decisions and achieve higher energy utilization efficiency. More importantly, in this planning framework, investors can set model parameters more flexibly according to the situation of the HFCV market, thereby promoting the popularization of HFCVs.

关键词： Uncertainty Upper bound Simulation Hydrogen Transportation Transforms Planning Fuels Optimization Investment

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Distributed Learning by Local Training ADMM

Distributed Learning by Local Training ADMM

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IEEE Conference on Decision and Control

作者： Xiaoxing Ren Nicola Bastianello Karl H. Johansson Thomas Parisini Department of Electrical and Electronic Engineering Imperial College London London United Kingdom 2School of Electrical Engineering and Computer Science and Digital Futures KTH Royal Institute of Technology Stockholm Sweden Department of Electronic Systems Aalborg University Denmark Department of Engineering and Architecture University of Trieste Trieste Italy

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

In this paper, we focus on distributed learning over peer-to-peer networks. In particular, we address the challenge of expensive communications (which arise when e.g. training neural networks), by proposing a novel local training algorithm, LTADMM. We extend the distributed ADMM enabling the agents to perform multiple local gradient steps per communication round (local training). We present a preliminary convergence analysis of the algorithm under a graph regularity assumption, and show how the use of local training does not compromise the accuracy of the learned model. We compare the algorithm with the state of the art for a classification task, and in different set-ups. The results are very promising showing a great performance of LT-ADMM, and paving the way for future important theoretical developments.

关键词： Training computer aided instruction Analytical models Accuracy Distance learning Neural networks Classification algorithms Topology Peer-to-peer computing Convergence

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