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7th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2023

作者： Kaushal, Rajanish Kumar Jain, Shubhi Shankar Rao, R Gowri Thirumalaimuthu, Babu Rawat, Ruchira Natrayan, L. Chandigarh University Department of Electrical Engineering Punjab Mohali Gharuan India Swami Keshvanand Institute of Technology Management and Gramothan Department of Electronics and Communication Rajasthan Jaipur302018 India Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Physics Tamil Nadu Chennai600062 India St. Joseph's College of Engineering Department of Instrumentation and Control Engineering Tamil Nandu Chennai600119 India Graphic Era Deemed to Be University Department of Computer Science & Engineering Uttarakhand Dehradun248002 India Saveetha School of Engineering Simats Department of Mechanical Engineering Tamil Nadu Chennai602105 India

ISBN: (纸本)9798350341485

The popularity of vehicles based on electricity is increasing as they are considered a sustainable mode of transportation. The charging infrastructure for electric vehicles are suffering various issues. There are limited availability of public charging stations, the high costs associated with installing private charging stations, and the high variability of electricity prices. The peer-to-peer (P2P) energy stability will be seen as a potential solution to facilitate electric vehicle (EV) charging in a manner that is both cost-effective and environmentally sustainable. The paper presents a novel system energy trading and charging payment for electric vehicles (EVs). The desired system enables EV owners to exchange surplus electricity with other EV owners in their location. The system being proposed utilizes blockchain technology to guarantee secure and transparent transactions. Additionally, it incorporates a smart contract to automate the trading and charging process. The system utilizes a dynamic pricing mechanism that adjusts in real-time to reflect the current electricity prices. This feature is designed to encourage electric vehicle owners to engage in energy stabilization during maximum usage hours. The Optimistic results shows that the described system has the efficacy on minimising the cost of vehicle charging and to decrease peak demand on the grid. Additionally, the system encourages the utilization of renewable energy sources. © 2023 IEEE.

关键词： Electric vehicles

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High Efficiency Dual-Active-Bridge Converter with Triple-Phase-Shift control for Battery Charger of Electric Vehicles

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Energies 2024年第2期17卷 354页

作者： Kuo, Shih-Hao Chiu, Huang-Jen Chiang, Che-Wei Huang, Ta-Wei Chang, Yu-Chen Bachman, Serafin Piasecki, Szymon Jasinski, Marek Turzyński, Marek Department of Electronic and Computer Engineering National Taiwan University of Science and Technology Taipei106 Taiwan Institute of Control and Industrial Electronics Warsaw University of Technology Warsaw00-662 Poland Faculty of Electrical and Control Engineering Gdańsk University of Technology Gdansk80-233 Poland

An optimal modulation scheme with triple-phase-shift (TPS) control could increase the efficiency in the entire load range for a dual-active-bridge (DAB) converter under wide output voltage range conditions. Therefore, this study proposes a convergent approach to TPS mode selection, coupled with an optimal modulation scheme, ensuring the circuit’s efficiency over the entire range in the realm of a high-power and high-efficiency battery charger for electric vehicles. The convergent approach to TPS mode selection also reduces the numerous cases for small-signal analysis through general average modeling. After verifying the small-signal models under various voltage transfer ratios and load conditions to verify the stability, a converter prototype with a rated power of 15 kW is built and tested. Thus, a peak efficiency of 97.7% can be achieved. © 2024 by the authors.

关键词： Charging (batteries)

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RBP-Former: Joint Prediction of RNA-protein Binding Sites on Full-length RNA Transcripts for Multiple RBPs

RBP-Former: Joint Prediction of RNA-protein Binding Sites on...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Li, Yichong Liu, Xiaojian Cheng, Fan Pan, Xiaoyong Yang, Yang Shanghai Jiao Tong University Department of Computer Science and Engineering Shanghai200240 China Shanghai Jiao Tong University Institute of Image Processing and Pattern Recognition Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai200240 China

ISBN: (纸本)9798350386226

RNA-binding proteins (RBPs) are essential for gene expression, and the complex RNA-protein interaction mechanisms require analysis of global RNA information. Therefore, accurate prediction of RBP binding sites on full-length RNA transcripts is crucial for understanding these mechanisms and their roles in diseases. While machine learning methods can predict RBP binding to RNA fragments, extending this to full-length transcripts presents challenges due to sequence length and data imbalance. In this paper, we introduce RBP-Former, a binding site joint prediction model designed specifically for full-length RNA transcripts that can be used for multiple RBPs. This model processes information at both coarse and fine-grained levels to fully exploit sequence data and its interactions with multiple RBPs. We develop multi-level imbalance learning strategies, achieving favorable results on imbalanced data. Our method outperforms existing methods in predicting binding sites on full-length RNA transcripts for multiple RBPs, demonstrating its effectiveness in handling imbalanced label and sample distributions. © 2024 IEEE.

关键词： Binding sites

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Two-Player Incomplete Games of Resilient Multiagent Systems

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IFAC-PapersOnLine 2023年第2期56卷 258-263页

作者： Yurid E. Nugraha Tomohisa Hayakawa Hideaki Ishii Ahmet Cetinkaya Quanyan Zhu Department of Electrical Engineering Institut Teknologi Sepuluh Nopember Surabaya 60111 Indonesia Department of Systems and Control Engineering Tokyo Institute of Technology Tokyo 152-8552 Japan Department of Computer Science Tokyo Insitute of Technology Yokohama 226-8502 Japan Department of Functional Control Systems Shibaura Institute of Technology Tokyo 135-8548 Japan Department of Electrical and Computer Engineering New York University Brooklyn NY 11201 USA

Evolution of agents’ dynamics of multiagent systems under consensus protocol in the face of jamming attacks is discussed, where centralized parties are able to influence the control signals of the agents. In this paper we focus on a game-theoretical approach of multiagent systems where the players have incomplete information on their opponents’ strength. We consider repeated games with both simultaneous and sequential player actions where players update their beliefs of each other over time. The effect of the players’ optimal strategies according to Bayesian Nash Equilibrium and Perfect Bayesian Equilibrium on agents’ consensus is examined. It is shown that an attacker with incomplete knowledge may fail to prevent consensus despite having sufficient resources to do so.

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Low-Complexity control for a Class of Uncertain MIMO Nonlinear Systems under Generalized Time-Varying Output Constraints (extended version)

arXiv

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arXiv 2024年

作者： Mehdifar, Farhad Lindemann, Lars Bechlioulis, Charalampos P. Dimarogonas, Dimos V. Division of Decision and Control Systems KTH Royal Institute of Technology Stockholm Sweden Thomas Lord Department of Computer Science University of Southern California Los AngelesCA United States Division of Systems and Control Department of Electrical and Computer Engineering University of Patras Patra Greece

This paper introduces a novel control framework to address the satisfaction of multiple time-varying output constraints in uncertain high-order MIMO nonlinear control systems. Unlike existing methods, which often assume that the constraints are always decoupled and feasible, our approach can handle coupled time-varying constraints even in the presence of potential infeasibilities. First, it is shown that satisfying multiple constraints essentially boils down to ensuring the positivity of a scalar variable, representing the signed distance from the boundary of the time-varying output-constrained set. To achieve this, a single consolidating constraint is designed that, when satisfied, guarantees convergence to and invariance of the time-varying output-constrained set within a user-defined finite time. Next, a novel robust and low-complexity feedback controller is proposed to ensure the satisfaction of the consolidating constraint. Additionally, we provide a mechanism for online modification of the consolidating constraint to find a least violating solution when the constraints become mutually infeasible for some time. Finally, simulation examples of trajectory and region tracking for a mobile robot validate the proposed approach. Copyright © 2024, The Authors. All rights reserved.

关键词： Feedback control

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Deep Learning for Improved Aircraft Identification in Shared Airspace

SSRN

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SSRN 2024年

作者： Ahmed, Aisha Sir Elkhatem Engin, Seref Naci Malik, Zainab Abdalgadir, Shahd Aeronautical Engineering Department Sudan University of Science and Technology Khartoum407 Sudan Computer Engineering Department Yildiz Technical University Istanbul34220 Turkey Department of Electrical and Electronics Engineering Sakarya University of Applied Science Sakarya54050 Turkey Control and Automation Engineering Department Yildiz Technical University Istanbul34220 Turkey

Ensuring accurate identification of approaching aircraft is a crucial task for Air Traffic control (ATC) systems. This is essential to prevent misidentification accidents, occurring especially in shared airspace. Misidentification incidents may occur due to "Mistaken Identity" and a system malfunction that results in the aircraft crew being unable to respond to a radar control sector call, as well as radio signal problems due to bad weather. While military Identification Friend or Foe (IFF), and Automatic dependent surveillance-broadcast (ADS-B) systems have traditionally served this purpose, their reliability diminishes in cases where stealthy aircraft, during extreme weather conditions and spacious oceanic regions, are involved. In addition, radio signal- based surveillance systems are reliance on aircraft transponders. Under certain circumstances, this may pose a serious problem for the ATC. This paper introduces a novel approach utilizing deep Convolutional Neural Networks (CNN) for the identification of a type of approaching aircraft as either military or civilian, specifically applied to remote-sensing satellite imagery. The objective is to robustly and accurately determine the type of aircraft whether hostile or friendly to enhance radio signal-based surveillance systems detectability. Experimental evaluation incorporates three distinct datasets: noise-free datasets, noisy datasets, and images affected by varying illumination conditions. The experimental results reveal a remarkably high identification accuracy, averaging 99.50%, across both noise-free and augmented datasets. The introduction of noisy datasets is accomplished through the application of a median filter. However, the results also point out an intrinsic challenge posed by illumination variations that affect CNN classification accuracy. © 2024, The Authors. All rights reserved.

关键词： Air traffic control

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Multi-Agent Coordination for a Partially Observable and Dynamic Robot Soccer Environment with Limited Communication

arXiv

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arXiv 2024年

作者： Affinita, Daniele Volpi, Flavio Spagnoli, Valerio Suriani, Vincenzo Nardi, Daniele Bloisi, Domenico D. Department of Computer Control and Management Engineering Antonio Ruberti Sapienza University of Rome Italy Faculty of Political Science and Sociopsychological Dynamics UNINT University Rome Italy

RoboCup represents an International testbed for advancing research in AI and robotics, focusing on a definite goal: developing a robot team that can win against the human world soccer champion team by the year 2050. To achieve this goal, autonomous humanoid robots’ coordination is crucial. This paper explores novel solutions within the RoboCup Standard Platform League (SPL), where a reduction in WiFi communication is imperative, leading to the development of new coordination paradigms. The SPL has experienced a substantial decrease in network packet rate, compelling the need for advanced coordination architectures to maintain optimal team functionality in dynamic environments. Inspired by market-based task assignment, we introduce a novel distributed coordination system to orchestrate autonomous robots’ actions efficiently in low communication scenarios. This approach has been tested with NAO robots during official RoboCup competitions and in the SimRobot simulator, demonstrating a notable reduction in task overlaps in limited communication settings. © 2024, CC BY.

关键词： Human resource management

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The influence of coordinated behavior on toxicity

arXiv

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arXiv 2023年

作者： Loru, Edoardo Cinelli, Matteo Tesconi, Maurizio Quattrociocchi, Walter Department of Computer Control and Management Engineering Sapienza University of Rome Italy Department of Computer Science Sapienza University of Rome Italy Institute of Informatics and Telematics National Research Council

In the intricate landscape of social media, genuine content dissemination may be altered by a number of threats. Coordinated Behavior (CB), defined as orchestrated efforts by entities to deceive or mislead users about their identity and intentions, emerges as a tactic to exploit or manipulate online discourse. This study delves into the relationship between CB and toxic conversation on X (formerly known as Twitter). Using a dataset of 11 million tweets from 1 million users preceding the 2019 UK general election, we show that users displaying CB typically disseminate less harmful content, irrespective of political affiliation. However, distinct toxicity patterns emerge among different coordinated cohorts. Compared to their non-CB counterparts, CB participants show marginally higher toxicity levels only when considering their original posts. We further show the effects of CB-driven toxic content on non-CB users, gauging its impact based on political leanings. Our findings suggest that CB only has a limited impact on the toxicity of digital discourse. Please cite published version: https://***/10.1016/***.2024.100289 © 2023, CC BY.

关键词： Tweets

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Behavioural Swarm Optimisation for Stable Slung-Load Aerial Transportation

Behavioural Swarm Optimisation for Stable Slung-Load Aerial ...

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Congress on Evolutionary Computation

作者： Jingyu Chen John Oyekan Department of Automatic Control and Systems Engineering The University of Sheffield Sheffield United Kingdom Department of Computer Science University of York York United Kingdom

Collaboration of agents in a natural swarm enables the accomplishment of tasks that would be difficult or impossible for a single agent to complete alone. For example, a swarm of autonomous Unmanned Aerial Vehicles (UAVs) enables the collaborative sensing of bulky loads for transportation over impassable terrains when the load weighs several times more than each UAV. In this work, we propose a hierarchical algorithmic architecture that supports the search and coverage of various unknown payload profiles for subsequent transportation. The grasping formation of UAVs over the payload emerges from the synthetic behaviours in the architecture without any path planning. Experiments show that our proposed design can be successfully applied in searching and coverage of various loads and has been validated in the real world through the use of Crazyflie micro-UAVs. Furthermore, the proposed grasping formation satisfies static equilibrium thereby reducing orientation changes in the load-swarm system during transportation.

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control-oriented modeling and passivity analysis of thermal dynamics in a multi-producer district heating system

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IFAC-PapersOnLine 2023年第1期56卷 175-180页

作者： Saeed Ahmed Juan E. Machado Michele Cucuzzella Jacquelien M.A. Scherpen Jan C. Willems Center for Systems and Control ENTEG Faculty of Science and Engineering University of Groningen 9747 AG Groningen The Netherlands Department of Electrical Computer and Biomedical Engineering University of Pavia Italy

Climate change and geopolitics have led to the conception of plans for reducing greenhouse gas emissions and improving the sustainability of existing fossil-based energy systems. In this respect, district heating has been identified as an indispensable player for its potential to integrate seamlessly environmentally-friendly heat sources. To improve the efficiency of these district heating systems, optimal operation schemes can be devised and enforced through control systems. To this end, we present a control-oriented nonlinear ODE-based model of temperature dynamics in a multi-producer district heating system. The model features a modular design and comprises the thermal dynamics of heat exchangers of producers and consumers interconnected by a distribution network of meshed topology. Then, we establish passivity properties and zero-state detectability for the modeled temperature dynamics that could be exploited for controller design and solving constrained optimization problems.

关键词： District heating thermal dynamics Krasovskii passivity shifted passivity zero-state detectability

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