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Improved Synthesis of Nondeterministic Publicly-Known Edit Functions for Opacity Enforcement

IEEE Transactions on Automatic Control 2025年

作者： Liu, Rongjian Hadjicostis, Christoforos N. Chongqing Normal University National Center for Applied Mathematics in Chongqing Chongqing401331 China Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China University of Cyprus Department of Electrical and Computer Engineering Nicosia Cyprus

In this paper, we investigate the synthesis problem of edit functions for opacity enforcement in systems modelled as partially-observed finite-state automata. For better plausible deniability for the edit functions, in cases where the intruder may learn/know their existence, a synthesis problem for nondeterministic edit functions under a publicly-known setting was introduced in the literature, but not yet fully solved. In light of this, we revisit the publicly-known edit mechanism by proposing a sound and complete approach for solving the synthesis problem of nondeterministic publicly-known edit functions. For practical applications, the edit function is assumed to have limited erasure and insertion ability. Our approach is based on a new labelled finite-state structure, and results in wider applicability than previously-proposed in the literature. © 1963-2012 IEEE.

关键词： Discrete event simulation

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Modeling and Simulating more efficient and reliable fuel cell vehicles through enhancing the integration of the 6kW PEM fuel cell stack with DC/DC boost converter and BLDC motor

Modeling and Simulating more efficient and reliable fuel cel...

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Power engineering Conference (SAUPEC), Southern African Universities

作者： Olona Mtumka Senthil Krishnamurthy Department of Electrical Electronic and Computer Engineering Center for Intelligent Systems and Emerging Technologies Cape Peninsula University of Technology Bellville Cape Town South Africa

ISBN: (数字)9798331535162

ISBN: (纸本)9798331535179

This study focuses on enhancing the integration of the PEM fuel cell, DC/DC boost converter, and BLDC motor, which help to develop more efficient and dependable fuel cell vehicles. The development of renewable energy sources for power generation has received much attention due to the depletion of fossil fuel supplies worldwide and economic difficulties. Fuel cells are one of the most efficient and cleanest power generation methods. Polymer electrolyte membrane (PEM) fuel cell is the preferred type of fuel cell for vehicles because of its high energy density, fast start-up, and lack of pollution. This paper aims to model and simulate a PEM fuel cell stack to power a Brushless DC (BLDC) motor for a fuel cell vehicle to reduce emissions in the transportation sectors. A boost converter is implemented to boost the output voltage of the PEM fuel cell stack to 100 V. The paper utilizes the trapezoidal commutation of the BLDC motor to drive the inverter. The trapezoidal commutation uses the six-switching technique to control the inverter's phase currents. The variation of fuel flow rate and drive cycle are included to observe the effect on the operation of the fuel cell stack. The paper presents the modeling and simulation of the PEM Fuel cell stack to improve power conversion, energy management, and vehicle control, helping to make fuel cell vehicles more viable for widespread adoption in the future.

关键词： Renewable energy sources Commutation Hydrogen Fuel cells Transportation Reliability engineering Fuel cell vehicles Inverters Power conversion Power generation

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Predicting Optimal Placement of Electric Vehicle Charge Stations Using Machine Learning: A Case Study in Glasgow, UK

Predicting Optimal Placement of Electric Vehicle Charge Stat...

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Iranian Conference on Renewable Energy and Distributed Generation (ICREDG)

作者： Arash Mousaei Yahya Naderi dept. Computer and Electrical Engineering University of Tabriz Tabriz Iran Sustainable Energy Systems Department Ricardo AEA Glasgow U.K

ISBN: (数字)9798331525132

ISBN: (纸本)9798331525149

Given the reduced costs of establishing Electric Vehicle (EV) charging stations and the need to improve their accessibility, it is essential for EV developers and governments to identify optimized locations for new stations. This study presents a predictive modeling approach using Machine Learning to determine the optimal sites for EV charging stations in Glasgow. While various machine learning methods are available for this purpose, we focus on Linear Regression due to its simplicity and high accuracy. By analyzing a comprehensive dataset of 207 AC charging stations-including factors latitude, longitude, population density, number of kinds of plugs, total number of plugs, price per kWh, traffic conditions, distance to the nearest station, Air Quality Index (AQI), and land value - we aim to provide urban planners and policymakers with actionable insights. The study evaluates the performance of the Linear Regression model in predicting the most suitable locations for charging stations. The results indicate that the proposed model achieved impressive accuracy, with R 2 , Mean Absolute Error (MAE), and Mean Squared Error (MSE) values of 0.89, 0.05, and 0.08, respectively. This research contributes to the ongoing efforts in urban planning for sustainable mobility by offering a data-driven methodology for EV infrastructure development.

关键词： Accuracy Atmospheric modeling Linear regression Machine learning Predictive models Charging stations Electric vehicle charging Indexes Population density Plugs

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An Optimizing Method for FMCW Chirp Linearity Based on Continuous Frequency Step Analysis

An Optimizing Method for FMCW Chirp Linearity Based on Conti...

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IEEE Annual Conference on Wireless and Microwave Technology (WAMICON)

作者： Sheng Sun Chunqi Shi Leilei Huang Jinghong Chen Runxi Zhang Institute of Microelectronic Circuits and Systems East China Normal University Shanghai China Department of Electrical and Computer Engineering University of Houston Houston TX USA

ISBN: (数字)9798331509606

ISBN: (纸本)9798331509613

This paper presents a method for optimizing chirp linearity in frequency-modulated continuous wave (FMCW) signal sources, utilizing continuous frequency step analysis. The study delves into the connection between the phase-locked loop (PLL) loop bandwidth and the chirp slope. Additionally, it examines how variations in frequency step granularity impact the root mean square (RMS) FM error across three distinct radar operational modes: long-range, medium-range, and short-range. Guided by the proposed optimization model, an FMCW signal source has been designed using a 55 nm CMOS process. This design occupies an area of 1.6 mm 2 and consuming 178.4 mW of power. The prototype demonstrates a chirp bandwidth of 5.4 GHz and achieves RMS FM errors of 152.7,167, and 201.3 kHz with the chirp slopes of 13.2,22, and 44 MHz/μs, respectively.

关键词： Semiconductor device modeling Wireless communication Frequency synthesizers Frequency modulation Chirp Software packages Linearity Bandwidth Root mean square Phase locked loops

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A comparison study between Modbus and IEC 61850 MMS Protocols

A comparison study between Modbus and IEC 61850 MMS Protocol...

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Power engineering Conference (SAUPEC), Southern African Universities

作者： Rayner Johnson Senthil Krishnamurthy Haltor Mataifa Mohammed Esmail Department of Electrical Electronic and Computer Engineering Center for Substation Automation and Energy Management Systems Cape Peninsula University of Technology Cape Town South Africa

ISBN: (数字)9798331535162

ISBN: (纸本)9798331535179

The growing adoption of renewable energy primary plants has been seen globally. South Africa has seen a significant development in utility-scale photovoltaic (PV) farms in recent years due to the alleviated regulations stipulated in the latest Electricity Regulation Amendment Act. Connecting the PV plants to the power grid has also undergone a technical evolution by incorporating modern embedded computers known as Intelligent Electronic Devices (IEDs). The International Electrotechnical Committee (IEC) 61850 standard defines a suite of protocols used in modern power systems. This study compares the IEC 61850 Manufacturing Messaging Specification (MMS) with the well-known MODBUS protocol. The comparison is achieved by simulating a solar farm's Power Plant Controller (PPC).

关键词： Photovoltaic systems Renewable energy sources Power engineering Protocols Inverters Regulation Real-time systems Power grids IEC Standards Standards

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Distributed Computation of Source, Target, and Mixed Strongly Connected Components in Multi-agent systems 16th

Distributed Computation of Source, Target, and Mixed Stron...

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16th APCA International Conference on Automatic Control and Soft Computing, CONTROLO 2024

作者： Ramos, Guilherme Pequito, Sérgio Department of Computer Science and Engineering Instituto Superior Técnico University of Lisbon Lisbon1049-001 Portugal Instituto de Telecomunicações Lisbon1049-001 Portugal Department of Electrical and Computer Engineering Instituto Superior Técnico University of Lisbon Lisbon1049-001 Portugal Institute for Systems and Robotics Instituto Superior Técnico University of Lisbon Lisbon1049-001 Portugal

ISBN: (纸本)9783031817236

Strongly Connected Components (SCCs) play a crucial role in understanding the structural properties of directed graphs, with a plethora of applications across various domains including engineering, computer science and social sciences. In this paper, we propose a method for computing both the source SCCs and target SCCs in a distributed fashion. Our method leverages the decentralized nature of distributed systems to efficiently identify SCCs within large-scale graphs. We illustrate the proposed methods with examples. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Distributed computer systems

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A Systematic Design Method Based on Vector Analysis for mmW DCML Divider

A Systematic Design Method Based on Vector Analysis for mmW ...

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IEEE Annual Conference on Wireless and Microwave Technology (WAMICON)

作者： Wangming Liu Wenbo Guo Chunqi Shi Jinghong Chen Runxi Zhang Institute of Microelectronic Circuits and Systems East China Normal University Shanghai China Department of Electrical and Computer Engineering University of Houston Houston TX USA

ISBN: (数字)9798331509606

ISBN: (纸本)9798331509613

The traditional RC delay model and the small-signal model do not suffice for a precise analysis of the dynamic current mode logic (DCML) divider in the millimeter-wave (mmW) frequency band. This paper explores the current vector model and examines the prerequisites for the proper functioning of the DCML, including phase, gain, and amplitude aspects, using expressions and vector diagrams as references. To fulfill the frequency division requirements of mmW ultra-wideband phaselocked loops, a broadband DCML4 divider has been designed based on the aforementioned analysis. Simulation results show that with an input power of -4 dBm, the maximum frequency division range for a single sub-band can reach up to 137.5% (from 5 to 27 GHz). The center frequency is adjusted via biasing, enabling the total frequency coverage to achieve 150% (ranging from 5 to 35 GHz). At a supply voltage of 1.2 V, the average power consumption is only 6.72 mW.

关键词： Wireless communication Analytical models Power demand Systematics Simulation Millimeter wave technology Voltage Frequency conversion Vectors Ultra wideband technology

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Highly Accurate Crow Search Optimized CNN Classifier for Cyclone Prediction

Highly Accurate Crow Search Optimized CNN Classifier for Cyc...

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Data Science, Agents & Artificial Intelligence (ICDSAAI), International Conference on

作者： R. Ramya Kavin K. S R. Anuja A. T. R. Krishna Priya D. Karthikeyan Kiruba Thangam Raja Department of Electronics and Communication Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences (SIMATS) Tamilnadu India Department of Electrical and Electronics Engineering Government College of Engineering Tirunelveli Tamilnadu India Department of Computer Science and Engineering Rohini College of Engineering and Technology Kanyakumari Tamilnadu India Department of Electrical and Electronics Engineering SRM Institute of Science and Technology Chennai India Department of Software and Systems Engineering School of Computer Science Engineering and Information Systems (SCORE) VIT University Vellore

ISBN: (数字)9798331537555

ISBN: (纸本)9798331537562

Accurate and timely prediction of cyclone events is essential for effective disaster management and risk mitigation. This study introduces a highly precise cyclone prediction model that combines Convolutional Neural Networks (CNNs) with the optimization capabilities of the Crow Search Algorithm (CSA). The resulting model, called Crow Search Optimized CNN (CSO-CNN), harnesses the feature extraction and classification strengths of CNNs, while the CSA is used to optimize the hyperparameters of the CNN architecture for optimal performance. The model is trained and validated on a comprehensive dataset that includes satellite imagery and meteorological data from a wide range of cyclone events. The CSO-CNN achieves remarkable classification accuracy, surpassing traditional CNN models and other leading techniques. Its ability to quickly and accurately assess the likelihood of cyclone formation provides crucial decision support for disaster management authorities, enabling timely and effective response strategies. By integrating the CSA optimization technique with the CNN framework, this study presents a novel approach to cyclone prediction. It highlights the potential of combining advanced Machine Learning (ML) algorithms to tackle complex environmental challenges and deepen our understanding of intricate atmospheric phenomena.

关键词： Accuracy Atmospheric modeling Disaster management Predictive models Prediction algorithms Feature extraction Cyclones Satellite images Convolutional neural networks Optimization

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Optimizing Transmit Field Inhomogeneity of Parallel RF Transmit Design in 7T MRI using Deep Learning

Optimizing Transmit Field Inhomogeneity of Parallel RF Trans...

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Medical Imaging 2025: Physics of Medical Imaging

作者： Lu, Zhengyi Liang, Hao Wang, Xiao Yan, Xinqiang Huo, Yuankai Department of Electrical and Computer Engineering Vanderbilt University NashvilleTN United States Vanderbilt University Institute of Imaging Science Vanderbilt University Medical Center NashvilleTN United States Department of Radiology and Radiological Sciences Vanderbilt University Medical Center NashvilleTN United States Computational Science and Engineering Division Oak Ridge National Laboratory Oak RidgeTN United States Department of Computer Science Vanderbilt University NashvilleTN United States

ISBN: (纸本)9781510685888

Ultrahigh field (UHF) Magnetic Resonance Imaging (MRI) provides a higher signal-to-noise ratio and, thereby, higher spatial resolution. However, UHF MRI introduces challenges such as transmit radiofrequency (RF) field (B1+) inhomogeneities, leading to uneven flip angles and image intensity anomalies. These issues can significantly degrade imaging quality and its medical applications. This study addresses B1+ field homogeneity through a novel deep learning-based strategy. Traditional methods like Magnitude Least Squares (MLS) optimization have been effective but are time-consuming and dependent on the patient's presence. Recent machine learning approaches, such as RF Shim Prediction by Iteratively Projected Ridge Regression and deep learning frameworks, have shown promise but face limitations like extensive training times and oversimplified architectures. We propose a two-step deep learning strategy. First, we obtain the desired reference RF shimming weights from multi-channel B1+ fields using random-initialized Adaptive Moment Estimation. Then, we employ Residual Networks (ResNets) to train a model that maps B1+ fields to target RF shimming outputs. Our approach does not rely on pre-calculated reference optimizations for the testing process and efficiently learns residual functions. Comparative studies with traditional MLS optimization demonstrate our method's advantages in terms of speed and accuracy. The proposed strategy achieves a faster and more efficient RF shimming design, significantly improving imaging quality at UHF. This advancement holds potential for broader applications in medical imaging and diagnostics. © 2025 SPIE.

关键词： Neuroimaging

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A Survey on Network Management for xANET: Evolution, Challenges, Future Directions

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IEEE Communications Surveys and Tutorials 2025年

作者： Li, Tong Yang, Chungang Wang, Yao Cai, Lin Anpalagan, Alagan Han, Zhu Xidian University State Key Laboratory of Integrated Services Networks Xi'an710071 China National Key Laboratory of Multi-domain Data Collaborative Processing and Control Xi'an710068 China Hangzhou Institute of Technology of Xidian University Hangzhou311231 China University of Victoria Department of Electrical and Computer Engineering VictoriaBCV8P 5C2 Canada Ryerson University Department of Electrical and Computer Engineering TorontoONM5B 2K3 Canada University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446701 Korea Republic of

The x ad hoc network (xANET) termed as a family of ad hoc networks, including mobile ad hoc network (MANET), vehicular ad hoc network (VANET), flying ad hoc network (FANET) and satellite ad hoc network (SANET), has found a wide range of applications in providing ubiquitous wireless services. Despite its broad utility, the dynamic nature and lack of a centralized controller pose significant challenges to effective and flexible network management for xANET. Conventional network management protocols face challenges such as scalability, security vulnerabilities, configuration complexity, robustness, and performance resilience. Recent efforts have presented different approaches, focusing on policy-based network management (PBNM) and intent-driven network management (IDNM). However, there is no comprehensive survey to clarify their concepts and classifications. This paper presents a survey of the network management evolution for xANET, covering configuration-based, policy-based and the latest intent-driven approaches. We first introduce the characteristics and applications of xANET. Meanwhile, we investigate the network management concepts and challenges. Moreover, we survey the evolution of management protocols for xANET, including simple network management protocol (SNMP), PBNM, and IDNM. Then, we follow the detailed network management of xANET from configuration-based to policy-based and intent-driven approaches. Through comparative analysis, it is found that IDNM employs a more intelligent management protocol, demonstrating higher efficiency and flexibility in handling complex tasks and dynamic network management. This makes it better suited to addressing the challenges of xANET management. Finally, we summarize the remaining challenges and possible future research directions. © 2025 IEEE.

关键词： Vehicular ad hoc networks

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