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20th IEEE International Conference on Intelligence and Security Informatics, ISI 2023

作者： McGuan, Colman Yu, Chansu Lin, Qin Cleveland State University Department of Electrical Engineering and Computer Science 2121 Euclid Avenue ClevelandOH44115 United States

ISBN: (纸本)9798350337730

The protection of Industrial control Systems (ICS) that are employed in public critical infrastructures is of utmost importance due to catastrophic physical damages cyberattacks may cause. The research community requires testbeds for validation and comparing various intrusion detection algorithms to protect ICS. However, there exist high barriers to entry for research and education in the ICS cybersecurity domain due to expensive hardware, software, and inherent dangers of manipulating real-world systems. To close the gap, built upon recently developed 3D high-fidelity simulators, we further showcase our integrated framework to automatically launch cyberattacks, collect data, train machine learning models, and evaluate for practical chemical and manufacturing processes. On our testbed, we validate our proposed intrusion detection model called Minimal Threshold and Window SVM (MinTWin SVM) that utilizes unsupervised machine learning via a one-class SVM in combination with a sliding window and classification threshold. Results show that MinTWin SVM minimizes false positives and is responsive to physical process anomalies. Furthermore, we incorporate our framework with ICS cybersecurity education by using our dataset in an undergraduate machine learning course where students gain hands-on experience in practicing machine learning theory with a practical ICS dataset. All of our implementations have been open-sourced. © 2023 IEEE.

关键词： Students

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Out-of-focus Noise Elimination by Tunable Focusing in Optical Scanning Holography

Out-of-focus Noise Elimination by Tunable Focusing in Optica...

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Digital Holography and Three-Dimensional Imaging, DH 2024

作者： Yao, Yongwei Zhang, Yaping Poon, Ting-Chung Kunming University of Science and Technology Yunnan Kunming650500 China Bradley Department of Electrical and Computer Engineering Virginia Tech BlacksburgVA24061 United States

We propose an out-of-focus noise elimination method in optical scanning holography by tunable focusing. Numerical simulation results are presented to demonstrate the visibility of the proposed method. © 2024 The ... 详细信息

关键词： Optical recording

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Improving Resources in Internet of Vehicles Transportation Systems Using Markov Transition and TDMA Protocol

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IEEE Transactions on Intelligent Transportation Systems 2023年第11期24卷 13050-13067页

作者： Miri, Farimasadat Javadpour, Amir Ja'Fari, Forough Sangaiah, Arun Kumar Pazzi, Richard Faculty of Business and Information Technology OshawaL1H 7K4 Canada Harbin Institute of Technology Department of Computer Science and Technology Shenzhen150001 China Instituto Politécnico de Viana Do Castelo ADiT-Lab Electrical and Telecommunications Department Viana do Castelo4900-347 Portugal Sharif University of Technology Department of Computer Engineering Tehran14588-89694 Iran National Yunlin University of Science and Technology International Graduate Institute of Ai Yunlin64002 Taiwan Lebanese American University Department of Electrical and Computer Engineering Byblos1102 Lebanon

In today's world, interconnected Vehicular ad-hoc networks (VANET) and intelligent transportation systems have become more popular. Although IoV can bring many benefits for the smart cities and provide comforts for the passengers, however, the increasing needs for keeping the QoS and QoE at an acceptable level in time sensitive applications seems crucial and needs to be investigated deeply. Also, allocating the right number of resources to avoid congestions and fill the deficiencies in a distributed manner is a challenging issue. So, with the increase in users, attention must be given to Quality of Service (QoS) and resource allocation. As the vehicle network provides information to provide safety, comfort, and entertainment to drivers and passengers, they are one of the most compelling research topics in intelligent transportation systems. TDMA protocol is used in this study to increase the efficiency of the network and the quality of service it provides. To solve the synchronization problem, the Markov method predicts the size of slots and frames. The scenario field is used in the Markov application section to better predict TDMA gaps on solving the synchronization problem. Accordingly, the higher the quality of service, the lower the latency of the network, and the better the allocation of resources. Optimizing allocation and quality of service is further motivated by reducing collision between packets. In terms of its implementation, this method is divided into two components, the first being the database proposal for constructing the Markov matrix and the second being the simulation on VanetMobisim and implementation of the network in NS2. The proposed method performed better in different scenarios in terms of computational complexity, PDF, latency, and overhead, as shown in the results section. © 2000-2011 IEEE.

关键词： Quality of service

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Utilizing hybrid faradaic mechanism via catalytic and surface interactions for high-performance flexible energy storage system

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Journal of Energy Chemistry 2023年第8期83卷 541-548,I0013页

作者： Dong-Gyu Lee Hyeonggeun Choi Yeonsu Park Min-Cheol Kim Jong Bae Park Suok Lee Younghyun Cho Wook Ahn A-Rang Jang Jung Inn Sohn John Hong Young-Woo Lee Department of Energy Engineering Soonchunhyang UniversityAsan 31538Republic of Korea Division of Physics and Semiconductor Science Dongguk University-SeoulSeoul 04620Republic of Korea Jeonju Centre Korea Basic Science InstituteJeonju 54907Republic of Korea Division of Electrical Electronic and Control EngineeringKongju National UniversityCheonan 31080Republic of Korea School of Materials Science and Engineering Kookmin UniversitySeoul 02707Republic of Korea

Improving the capacitance and energy density is a significant challenge while developing practical and flexible energy storage system(ESS).Redox mediators(RMs),as redox-active electrolyte additives,can provide additional energy storing capability via electrochemical faradaic contribution on electrodes for high-performance flexible ***,determining effective material combinations between electrodes and RMs is essential for maximizing surface faradaic redox reactions for energy-storage *** this study,an electrode-RM system comprising heterostructured hybrid(carbon fiber(CF)/MnO_(2)) faradaic electrodes and iodine RMs(I-RMs) in a redox-active electrolyte is *** CF/MnO_(2)with the 1-RMs(CF/MnO_(2)-I) induces dominant catalytic faradaic interaction with the I-RMs,significantly enhancing the surface faradaic kinetics and increasing the overall energy-storage *** CF/MnO_(2)-I ESSs show a 12.6-fold(or higher) increased volumetric energy density of 793.81 mWh L^(-1)at a current of 10 μA relative to ESSs using CF/MnO_(2)without I-RMs(CF/MnO_(2)).Moreover,the CF/MnO_(2)-I retains 93.1% of its initial capacitance after 10,000 cycles,validating the excellent ***,the flexibility of the ESSs is tested at different bending angles(180° to 0°),demonstrating its feasibility for flexible and high-wear ***,CF/MnO_(2)electrodes present a practical material combination for high-performance flexible energy-storage devices owing to the catalytic faradaic interaction with I-RMs.

关键词： Energy storage system Redox mediators Faradaic electrodes Catalytic interactions Mechanical stability

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An assessment of the effectiveness of deep learning techniques for allocating resources in 5G networks 15

An assessment of the effectiveness of deep learning techniqu...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Pandey, Arvind Kumar Dadhich, Atul Bekal, Shruthi K. Arka Jain University Department of Computer Science & It Jharkhand Jamshedpur India Vivekananda Global University Department of Electrical Engineering Jaipur India Jain Deemed to be University Department of Management School of Management - Ug Karnataka Bangalore India

ISBN: (纸本)9798350370249

This paper evaluates the efficiency of deep learning strategies for aid allocation in 5G networks. 5G networks have annoying requirements, which include high statistics charge, low latency, reliability, and flexibility. Deep learning is a powerful technical device for optimizing aid allocation in 5G networks, as it can help to expect the modifications in statistics needs and examine the underlying patterns of the residents' visitors. For you to examine the efficiency of deep getting-to-know techniques in 5G networks, the authors conducted simulations in a laboratory-scale testbed with the ability to regulate records site visitors and surroundings. The assessment covers metrics consisting of the normalized throughput, implied squared error, signal-to-noise ratio, and resource utilization. The authors determined that the usage of deep mastering techniques caused improvements in the normalized throughput and the mean squared error. The deep mastering approaches did not impact the signal-to-noise ratio and resource usage. The authors have stated that in 5G networks, resource allocation can be performed very well by using various strategies with deep knowledge, which were identified as powerful enough to apply and fulfil the requirements of resource scheduling for future generation five G networks. © 2024 IEEE.

关键词： Allocation Efficiency Knowledge Networks Simulations Strategies

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Poisoned ChatGPT Finds Work for Idle Hands: Exploring Developers’ Coding Practices with Insecure Suggestions from Poisoned AI Models

Poisoned ChatGPT Finds Work for Idle Hands: Exploring Develo...

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IEEE Symposium on Security and Privacy

作者： Sanghak Oh Kiho Lee Seonhye Park Doowon Kim Hyoungshick Kim Department of Electrical and Computer Engineering Sungkyunkwan University Republic of Korea Department of Electrical Engineering and Computer Science University of Tennessee USA

ISBN: (数字)9798350331301

ISBN: (纸本)9798350331318

AI-powered coding assistant tools (e.g., ChatGPT, Copilot, and IntelliCode) have revolutionized the software engineering ecosystem. However, prior work has demonstrated that these tools are vulnerable to poisoning attacks. In a poisoning attack, an attacker intentionally injects maliciously crafted insecure code snippets into training datasets to manipulate these tools. The poisoned tools can suggest insecure code to developers, resulting in vulnerabilities in their products that attackers can exploit. However, it is still little understood whether such poisoning attacks against the tools would be practical in real-world settings and how developers address the poisoning attacks during software development. To understand the real-world impact of poisoning attacks on developers who rely on AI-powered coding assistants, we conducted two user studies: an online survey and an in-lab study. The online survey involved 238 participants, including software developers and computer science students. The survey results revealed widespread adoption of these tools among participants, primarily to enhance coding speed, eliminate repetition, and gain boilerplate code. However, the survey also found that developers may misplace trust in these tools because they overlooked the risk of poisoning attacks. The in-lab study was conducted with 30 professional developers. The developers were asked to complete three programming tasks with a representative type of AI-powered coding assistant tool (e.g., ChatGPT or IntelliCode), running on Visual Studio Code. The in-lab study results showed that developers using a poisoned ChatGPT-like tool were more prone to including insecure code than those using an IntelliCode-like tool or no tool. This demonstrates the strong influence of these tools on the security of generated code. Our study results highlight the need for education and improved coding practices to address new security issues introduced by AI-powered coding assistant tools.

关键词： Surveys Codes Chatbots Encoding Software Security Task analysis

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Scheduling of Electric Vehicle Charging in a Solar-Wind Powered Microgrid Using Machine Learning

Scheduling of Electric Vehicle Charging in a Solar-Wind Powe...

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2024 IEEE International Women in engineering (WIE) Conference on electrical and computer engineering, WIECON-ECE 2024

作者： Rahman, Motinur Saha, Subrata Hasan, Mahmudul Alam, Mahbub Dadon, Saikot Hossain Suki, Tahmid Tamrin College of Ecs Arkansas State University Department of Electrical Engineering JonesboroAR United States Institute of Electronics Bangladesh Atomic Energy Commission Dhaka Bangladesh Institute of Computer Science Bangladesh Atomic Energy Commission Dhaka Bangladesh Bangladesh University of Professionals Department of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798331535476

The future of power generation lies in renewable energy, and solar and wind power are major contributors to meeting the ever-increasing energy demand brought on by the development of new technologies like electric vehicles (EVs). To address the rising energy demand, a machine learning-based approach has been explored in this research, which predicts the most practical hour for EV charging using renewable energy sources. Power generation throughout the year has been predicted using wind-solar power generation datasets. The research was conducted in two stages: applying machine learning algorithms and time series analysis. We have compared the R-squared value, correlation, and various types of errors using five machine-learning algorithms. With an R-squared value of 0.9574, the XGB Regressor model outperformed the other four machine learning algorithms in predicting solar wind power generation for EV charging demand management. On the other hand, our time series study reveals that when the sum of these two powers (solar, wind) reaches its peak between 8 AM and 8 PM over 24 hours, EV charging demand stays at its peak, suggesting the demand handling capacity of EVs by renewable energy sources. © 2024 IEEE.

关键词： demand flexibility electric vehicle machine learning microgrid regression renewable energy solar power wind power

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Automatic generation of repair suggestions for overall I&C architecture represented with an ontology 28

Automatic generation of repair suggestions for overall I&C a...

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28th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2023

作者： Ovsiannikova, Polina Pakonen, Antti Vyatkin, Valeriy VTT Technical Research Centre of Finland Ltd. Espoo Finland Aalto University Department of Electrical Engineering and Automation Espoo Finland Luleiå Tekniska Universitet Department of Computer Science Computer and Space Engineering Sweden

ISBN: (纸本)9798350339918

We present an approach for suggesting possible fixes to an overall I&C nuclear architecture during its design phase. Despite the I&C architecture, in our case, being represented with an ontology, we do not aim to change the properties of an ontology per se. Instead, we focus on the subset of ABox triples that do not contain terminological elements in either subject, predicate, or object parts. Such a subset we call the design artifacts. When the ontology is filled with the design artifacts, the analyst runs the check of non-functional requirements using SPARQL queries. The requirements associated with the queries that returned results do not hold. The goal of the current work is to provide support for the next stage when the analyst has to change the design artifacts so that the queries no longer return results. Our method is based on representing the results of queries as graphs, intersecting them, and finding the minimal changes that prevent the results from being mapped on their (or other) queries. © 2023 IEEE.

关键词： Ontology

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Structural and functional connectivity of the whole brain and subnetworks in individuals with mild traumatic brain injury:predictors of patient prognosis

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Neural Regeneration Research 2024年第7期19卷 1553-1558页

作者： Sihong Huang Jungong Han Hairong Zheng Mengjun Li Chuxin Huang Xiaoyan Kui Jun Liu Department of Radiology The Second Xiangya HospitalCentral South UniversityChangshaHunan ProvinceChina Department of Computer Science Aberystwyth UniversityAberystwythCeredigionUK Shenzhen Institutes of Advanced Technology Chinese Academy of SciencesShenzhenGuangdong ProvinceChina School of Computer Science and Engineering Central South UniversityChangshaHunan ProvinceChina Department of Radiology Quality Control Center of Hunan ProvinceChangshaHunan ProvinceChina Clinical Research Center for Medical Imaging of Hunan Province ChangshaHunan ProvinceChina

Patients with mild traumatic brain injury have a diverse clinical presentation,and the underlying pathophysiology remains poorly *** resonance imaging is a non-invasive technique that has been widely utilized to investigate neuro biological markers after mild traumatic brain *** approach has emerged as a promising tool for investigating the pathogenesis of mild traumatic brain injury.G raph theory is a quantitative method of analyzing complex networks that has been widely used to study changes in brain structure and ***,most previous mild traumatic brain injury studies using graph theory have focused on specific populations,with limited exploration of simultaneous abnormalities in structural and functional *** that mild traumatic brain injury is the most common type of traumatic brain injury encounte red in clinical practice,further investigation of the patient characteristics and evolution of structural and functional connectivity is *** the present study,we explored whether abnormal structural and functional connectivity in the acute phase could serve as indicators of longitudinal changes in imaging data and cognitive function in patients with mild traumatic brain *** this longitudinal study,we enrolled 46 patients with mild traumatic brain injury who were assessed within 2 wee ks of injury,as well as 36 healthy ***-state functional magnetic resonance imaging and diffusion-weighted imaging data were acquired for graph theoretical network *** the acute phase,patients with mild traumatic brain injury demonstrated reduced structural connectivity in the dorsal attention *** than 3 months of followup data revealed signs of recovery in structural and functional connectivity,as well as cognitive function,in 22 out of the 46 ***,better cognitive function was associated with more efficient ***,our data indicated that small-worldness in the acute sta

关键词： cognitive function cross-section follow-up functional connectivity graph theory longitudinal study mild traumatic brain injury prediction small-worldness structural connectivity subnetworks whole brain network

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Sliding mode control rotor flux MRAS based speed sensorless induction motor traction drive control for electric vehicles

AIMS Electronics and Electrical Engineering

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AIMS Electronics and electrical engineering 2023年第4期7卷 354-379页

作者： Rind, Saqib J. Javed, Saba Rehman, Yawar Jamil, Mohsin Department of Automotive & Marine Engineering NED University of Engineering & Technology University Road Karachi Pakistan Department of Electronics Engineering NED University of Engineering & Technology University Road Karachi Pakistan Department of Electrical & Computer Engineering Faculty of Engineering and Applied Science Memorial University of Newfoundland 240 Prince Phillip Drive St. John'sNLA1B 3X5 Canada

Climate change has highlighted a need to transition to more sustainable forms of transportation. Electric vehicles (EVs) and hybrid electric vehicles (HEVs) offer a promising alternative to conventional gasoline powered vehicles. However, advancements in power electronics and advanced control systems have made the implementation of high performance traction drives for EVs and HEVs easy. In this paper, a novel sliding mode control model reference adaptive system (SMC-MRAS) speed estimator in traction drive control application is presented. However, due to the unpredictable operational uncertainties of the machine parameters and unmodelled non-linear dynamics, the proportional-integral (PI)-MRAS may not produce a satisfactory performance. The Proposed estimator eliminates the PI controller employed in the conventional MRAS. This method utilizes two loops and generates two different error signals from the rotor flux and motor torques. The stability and dynamics of the SMC law are obtained through the Lyapunov theory. The potential of the proposed SMC-MRAS methodology is simulated and experimentally validated for an electric vehicle application. Matlab-Simulink environment is developed and proposed scheme is employed on indirect vector control method. However, for the experimental validation, the dSPACE 4011 R & D controller board was utilized. Furthermore, the SMC-MRAS performance is differentiated with PIMRAS for speed regulation performance, tracking and estimation error, as well as the fast minimization of the error signal. The results of the proposed scheme illustrate the enhanced speed estimation, load disturbance rejection ability and fast error dynamics. © 2023 the Author(s).

关键词： Sliding mode control

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