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2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022

作者： Kiani, Saad Hassan Rafique, Umair Alibakhshikenari, Mohammad Falcone, Fransisco Dalarsson, Mariana IIC University of Technology Department of Electrical Engineering Phnom Penh Cambodia Sapienza University Department of Information Engineering Electronics and Telecommunications Rome00184 Italy Universidad Carlos III de Madrid Department of Signal Theory and Communications Leganés28911 Spain Public University of Navarre Electric Electronic and Communication Engineering Department Pamplona31006 Spain Public University of Navarre Institute of Smart Cities Pamplona31006 Spain KTH Royal Institute of Technology School of Electrical Engineering and Computer Science StockholmSE 100-44 Sweden

ISBN: (数字)9781665496582

ISBN: (纸本)9781665496582

In this paper, a simple planar plow-shaped wideband antenna is presented for mm-wave 5G devices. The proposed antenna is designed on a thin substrate with an overall size of 10×12 mm2. The results show that the antenna offers 49.5% fractional bandwidth ranging from 22.2 GHz to 36.8 GHz. Moreover, the radiation efficiency of the antenna is >90% throughout the operating bandwidth, with a peak gain of 3.3 dBi. Through its simple structure and high performance characteristics, it can be observed that the proposed antenna can be termed as a potential candidate for future mm-wave 5G communication devices. © 2022 IEEE.

关键词： Radiation efficiency

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ENHANCING SITUATIONAL AWARENESS IN SURVEILLANCE: LEVERAGING DATA VISUALIZATION TECHNIQUES FOR MACHINE LEARNING-BASED VIDEO ANALYTICS OUTCOMES

arXiv

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arXiv 2023年

作者： Ardabili, Babak Rahimi Yao, Shanle Pazho, Armin Danesh Bourque, Lauren Tabkhi, Hamed Department of Public Policy University of North Carolina at Charlotte CharlotteNC28223 United States Department of Electrical and Computer Engineering University of North Carolina at Charlotte CharlotteNC28223 United States

The pervasive deployment of surveillance cameras produces a massive volume of data, requiring nuanced interpretation. This study thoroughly examines data representation and visualization techniques tailored for AI surveillance data within current infrastructures. It delves into essential data metrics, methods for situational awareness, and various visualization techniques, highlighting their potential to enhance safety and guide urban development. This study is built upon real-world research conducted in a community college environment, utilizing eight cameras over eight days. This study presents tools like the Occupancy Indicator, Statistical Anomaly Detection, Bird's Eye View, and Heatmaps to elucidate pedestrian behaviors, surveillance, and public safety. Given the intricate data from smart video surveillance, such as bounding boxes and segmented images, we aim to convert these computer vision results into intuitive visualizations and actionable insights for stakeholders, including law enforcement, urban planners, and social scientists. The results emphasize the crucial impact of visualizing AI surveillance data on emergency handling, public health protocols, crowd control, resource distribution, predictive modeling, city planning, and informed decision-making. Copyright © 2023, The Authors. All rights reserved.

关键词： Data visualization

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Humans and robots are nearly ethically equivalent

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AI and Ethics 2024年 1-10页

作者： Jorgenson, Corinne Willems, Jurgen Ozkes, Ali I. Vanderelst, Dieter Department of Psychology University of Cincinnati Cincinnati USA Institute for Public Management and Governance WU Vienna University of Economics and Business Vienna Austria SKEMA Business School GREDEG Universite Cote d’Azur Suresnes France Department of Biological Sciences Department of Electrical and Computer Engineering Department of Mechanical and Materials Engineering University of Cincinnati Cincinnati USA

Social care robots are increasingly used in health care. As the autonomy of these machines continues to increase, they will likely require some capacity for ethical reasoning. Current efforts to imbue robots with ethical decision-making capabilities tend to assume that people perceive robots and human actors as ethically equivalent entities. That is, it is assumed that the ethical behavior of a robot can be modeled based on what is considered ethical human behavior. Despite its ubiquity, this assumption is a hypothesis that warrants empirical investigation. In this article, we partially replicate earlier work that tested this hypothesis. We run two online experiments assessing the ethical equivalence of robots and humans. In addition, we present a new analysis of the data of as reported by Hidalgo et al. (How Humans Judge Machines, MIT Press, 2021). We compare the current (and previous) data with these authors’ work to summarize the tenability of the ethical equivalence hypothesis. Generally, respondents tend to rate robot actions as slightly less ethical than those performed by humans. However, the differences are minor and depend on the scenario. Therefore, we conclude that people treat humans and robots as nearly ethically equivalent. This implies that ethical rules for robots can be derived from existing frameworks and guidelines to regulate human behaviors.

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Emergency Load Shedding to Enhance Resiliency Considering Operator and Customer Equity

Emergency Load Shedding to Enhance Resiliency Considering Op...

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IEEE Green Technologies Conference (IEEE-Green)

作者： Nirasha Bataduvaarachchi Demy Alexander Visvakumar Aravinthan Al Tamimi Department of Electrical and Computer Engineering Wichita State University Wichita Kansas USA Transmission Planning & Policy Sunflower Electric Corporation Wichita Kansas USA

Recent high impact low frequency events have caused significant concerns on reliability and resiliency of electrical grid. Transmission operators might enforce load curtailment during such events to preserve the integrity of the power network and to prevent catastrophic system failures and long-lasting outages. Although load-shedding procedures employed by system operators are reviewed and constraints are highlighted throughout most hazardous incidents, such mechanisms are not evaluated to ensure consumer fairness and system impacts are addressed. This study was conducted at the transmission level in order to propose a new curtailment algorithm that addresses the limitations of the load shedding mechanism of the Southwest Power Pool. The study was motivated by the North American winter storm occurred in February 2021. The performance of the proposed algorithm is tested and compared with Southwest Power Pool's curtailment model via IEEE RTS-96 test system.

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Minimising cybersecurity risk exposures in industrial control system environments: a techno-human vulnerability analysis approach

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Journal of Cyber Security Technology 2024年

作者： Ani, Uchenna Daniel Watson, Jeremy He, Hongmei Radanliev, Petar Epiphaniou, Gregory School of Computer Science and Mathematics Keele University Staffordshire United Kingdom Department of Science Technology Engineering and Public Policy University College London London United Kingdom School of Science Engineering and Environment University of Salford Salford United Kingdom Department of Computer Science University of Oxford Oxford United Kingdom Coventry United Kingdom

Organisations operating IoT-enabled industrial control systems (ICSs) are concerned about growing cybersecurity risks and impacts to their systems. Cyber-attacks on ICSs demonstrate that technology alone is neither a problem nor a solution to the growing cybersecurity issues affecting these systems. As socio-technical systems, ICSs encompass the functions and interactions of social and technological system elements to enable and/or sustain industrial processes. Thus, a more effective cybersecurity risk management process needs to consider human and technology factors, especially for high-value industrial process targets. Combining critical reviews and gap analysis of existing vulnerability assessment methods with conceptual modelling, a Vulnerability Analysis Critical Impact Point Process (VACIP) methodology is proposed which considers both human and technological vulnerabilities within a cyber-physical system environment to inform an improved insight about attack criticality and impacts. VACIP is validated using a simulated industrial mini testbed;showing that it can enable practicable support for security vulnerability discovery, impact criticality analysis, weak link identification, and prioritised controls. Its novelty is demonstrated in its combination of technology and human vulnerability evaluations in the minimisation of system security exposures. It provides a useful guide for adopting effective cybersecurity risk assessment and exposure reduction strategies. © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

关键词： Risk analysis

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Dynamic Load Frequency Control for Small Signal Stability Analysis in Steam Plant with Reheater 21

Dynamic Load Frequency Control for Small Signal Stability An...

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21st IEEE International Symposium on Intelligent Systems and Informatics, SISY 2023

作者： Shahgholian, Ghazanfar Fathollahi, Arman Mosavi, Amirhosein Islamic Azad University Smart Microgrid Research Center Najafabad Branch Najafabad Iran Aarhus University Department of Electrical and Computer Engineering Aarhus Denmark John von Neumann Faculty of Informatics Budapest Hungary Ludovika University of Public Service Budapest Hungary

ISBN: (纸本)9798350343366

Steam energy plants are the fundamental source of electricity in the world, which has a large share of renewable energy. Load changes impact the frequency of electrical networks. Frequency stabilization is very important based on the boosting influence of renewable power sources in energy systems. The main task of load frequency control is to keep the system frequency according to the determined nominal value and to maintain the correct amount of exchange energy between the control areas. Maintaining the output power and actual frequency of the interconnected energy system and controlling the variation in power along the connection link between control areas are the central objectives of load frequency control (LFC). In this work, the purpose is to analyze and investigate load frequency control in a two-area energy system. Each area contains a steam turbine with a reheater. The system equations are expressed in state space and analyzed in MATLAB software. The simulation outcomes demonstrate the impact of changes in the gain parameters of the equivalent power system model and high-pressure coefficient in an area. © 2023 IEEE.

关键词： Thermoanalysis

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Enhanced Multiclass Brain Tumor Detection in MRI Using Similarity-Navigated Graph Neural Networks with Banyan Tree Growth Optimization

Enhanced Multiclass Brain Tumor Detection in MRI Using Simil...

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Ubiquitous Computing and Intelligent Information Systems (ICUIS), International Conference on

作者： Babu Rao K Pallavi Singh Gargi Shankar Verma L. Mohana Kannan Swaraj Kadam Department of Computer Science and Engineering Mangalore Institute of Technology & Engineering Mijar Karnataka India Department of Public Health Dentistry Saraswati Dental College & Hospital Lucknow Uttar Pradesh India Department of Computer Science and Engineering Krishna's Vikash Institute of Technology Raipur Chhattisgarh India Department of Biomedical Engineering Erode Sengunthar Engineering College Perundurai Tamil Nadu India Department of Electrical Engineering Dr. D Y Patil Institute of Technology Pune Maharashtra India

ISBN: (数字)9798331529635

ISBN: (纸本)9798331529642

The diagnosis of brain tumors is admittedly difficult because of their varied and complicated nature. Therefore, one has to get the right diagnosis and categorization for it to be treated well. This is a situation where identification of multiple classes such as; meningioma, pituitary, glioma and no tumor is crucial in taking the right course of action. Therefore, a new deep learning architecture is suggested in this work to increase the specificity between different types of tumors by detecting brain tumors with high accuracy in MRI scans. The proposed methodology starts with the Cumulative Curve Fitting Approximation (CCFA) preprocessing algorithm to improve the quality of MRI images. Preprocessed images are used as inputs for feature extraction based on geometric algebra transformers. These transformers include geometric relationships within the data, ensuring more distinctive selection. The categorization is further carried out with assistance of a Similarity-Navigated Graph Neural Network (SNGNN) incorporating the Banyan Tree Growth Optimizer (BTGO) model, which is constructed for efficient detection of the subtlest patterns and their connection between classes of brain tumors. It integrates very well in terms of the accuracy shown by its performance metrics. It shows effectiveness in a multiclass scenario of detecting brain tumors, which helps in the precise and early diagnosis and even tailors proper treatment plans.

关键词： Accuracy Algebra Magnetic resonance imaging Brain tumors Brain modeling Transformers Feature extraction Approximation algorithms Graph neural networks Curve fitting

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UAV weaknesses against deauthentication based hijacking attacks

UAV weaknesses against deauthentication based hijacking atta...

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International Symposium on Applied Machine Intelligence and Informatics (SAMI)

作者： Brúnó Krasnyánszki Sándor Tihamér Brassai András Németh Under Graduate Student in Computer Science Engineering Óbuda University Budapest Hungary Department of Electrical Engineering Sapientia Hungarian University of Transylvania Corunca Romania Department of Electronic Warfare National University of Public Service Budapest Hungary

Unmanned Aerial Vehicles (UAVs) and Unmanned Aerial Systems (UAS) are more important than ever before and we’re using it daily for agriculture, photo making, film industry, Search & Rescue, long range cable quality control, Geo Informatics, cartography, and state use (including border protection, disaster recovery and the military). Most of the UAV/UAS devices are using digital communication protocols nowadays, especially the IEEE 802.11 Wireless Local Area of Network for the cheaper and middle price UAV/UAS. Unfortunately, the protocols specified by the previously mentioned IEEE standard are vulnerable against some attacks. This research paper proposes a method that can interrupt the normal operation of the UAV/UAS that are using the IEEE 802.11 protocol and hijack the interrupted UAV/UAS permanently. For this method, deauthentication attack has been performed against the UAV/UASs. The attack vector is capable of denying the communication between the UAV and the control station. With sufficient prior knowledge it is possible to hijack the UAV that communicates on a 802.11 based protocol. Deauthentication based attacks are much more sophisticated than for example traditional electronic jamming, because the target can be precisely chosen and the attack will not interrupt other devices using the same communication method. The research has unfortunately some limitations in equipment, measurements conducted only in three different types of UAVs from three price categories, but in the future the authors would like to extend the range of UAVs. From this three UAVs two are hijackable by this method and the third should also be hijackable with some modifications. This research could be a base later for UAV/UAS counter measure systems for the safety of all of us.

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Overcoming Hurdles: A Comprehensive Analysis of Renewable Energy in Bangladesh

Overcoming Hurdles: A Comprehensive Analysis of Renewable En...

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Computational Intelligence for Green and Sustainable Technologies (ICCIGST), International Conference on

作者： Md Ashraful Islam Khusbu Rahman M M Naushad Ali Mashfiq Ahasan Hridoy Suribabu Golla Taha Selim Ustun Valisher Sapayev Odilbek Uglu Abdullayev Abdulla Fayzulla Ugli Ahmed Al Mansur Department of Electrical and Electronic Engineering Green University of Bangladesh Bangladesh Doermer School of Business Purdue University Fort Wayne USA Centre for Policy Dialogue (CPD) Dhaka Bangladesh Civil Engineering Department SRKR Engineering College India Department of Electrical and Computer Engineering Carnegie Mellon University United States Department of social-humanitarian and exact specific sciences Tashkent state University of Economy Uzbekistan

ISBN: (数字)9798350381887

ISBN: (纸本)9798350381894

This study addresses the critical aspects of renewable energy development in Bangladesh, identifying challenges and offering practical solutions. It recommends revising and enhancing renewable energy policies to establish realistic and inclusive targets over short, medium, and long terms. Financial support is advocated through the introduction of incentives and subsidies, particularly to overcome economic barriers hindering widespread solar technology adoption, with a focus on rural areas. The proposal includes combining feedin tariff and net metering, removing the limit in net metering, and offering tax exemptions for early-stage independent power producers. Additionally, the study underscores the need for integrated institutional and capacity development, emphasizing the establishment of an institute for skill building and technology innovation. Collaboration is a key theme, urging synergies between academia, government, and industries to bridge the gap between expertise, policies, and applications, ultimately contributing to a sustainable energy future in Bangladesh.

关键词： Industries Renewable energy sources Technological innovation Green buildings Government Buildings Collaboration Tariffs Propulsion Proposals

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Implementation of Robots in Autism Spectrum Disorder Research: Diagnosis and Emotion Recognition and Expression

Implementation of Robots in Autism Spectrum Disorder Researc...

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International Conference on Modern Circuits and Systems Technologies (MOCAST)

作者： Konstantinos-Filippos Kollias Luis Miguel Maia Marques Torres E Silva Panagiotis Sarigiannidis Christine K. Syriopoulou-Delli George F. Fragulis Department of Electrical and Computer Engineering University of Western Macedonia Kozani Greece Faculty of Engineering University of Porto Porto Portugal Department of Educational and Social Policy University of Macedonia Thessaloniki Greece

Early Autism Spectrum Disorder (ASD) diagnosis and intervention with state-of-the-art instruments, such as Artificial Intelligence and Robots is a rather challenging and promising research area which can optimise outcomes regarding the quality of life of ASD individuals and their families. Autistic individuals tend to show, among others, deficits in emotion recognition and expression. The present review study, aiming to review the literature concerning the contribution of Robotics to ASD research, found 27 review studies conducted from 2016 to February 2023 on PubMed and Web of Science databases in which robots were either employed in ASD diagnosis, or emotion recognition and expression. Results pointed out beneficial effects of robots’ employment as far as ASD diagnosis and emotion recognition and expression are concerned. Limitations and recommendations for future research are also involved, i.e., studies combining the Internet of Things (IoT) and Robotics with an aim to early ASD diagnosis, assessment, intervention, and inclusion.

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