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30th International Scientific Conference Electronics, ET 2021

作者： Mecheva, Teodora A. Kakanakov, Nikolay R. Faculty of Electronics and Automation Technical University of Sofia Department of Computer Systems and Technologies Plovdiv4000 Bulgaria

ISBN: (纸本)9781665445184

Simulation models are vital in the process of design, evaluation, and predicting modern traffic systems. The selection of appropriate data and their adaptation to the simulator is one of the toughest tasks in transport simulation. The article presents a simple two-step model for traffic flow generation based on real data from road cameras. The privilege of the presented model in comparison to classic four-step model is its simplicity and the ability to operate with a small amount of data. The model is implemented over an area of three main intersections in the central Plovdiv. In the first step the origin and destination flows are calculated via Python. At the second step the road network and the calculated flows are set up to AIMSUN traffic simulator. The generated traffic flow is compared to the data from real measurements. The evaluation of the data shows that additional adjustment of the model is required. Directions for improvement are proposed: data purification before calculating traffic demand, investigation of model applicability with data from alternative measurements, and setting the traffic lights in dynamic mode. © 2021 IEEE.

关键词： Python

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Multi-Blockchain Based Data Trading Markets With Novel Pricing Mechanisms

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IEEE/CAA Journal of Automatica Sinica 2023年第12期10卷 2222-2232页

作者： Juanjuan Li Junqing Li Xiao Wang Rui Qin Yong Yuan Fei-Yue Wang IEEE the State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China the College of Computer Science and Engineering Shandong University of Science and TechnologyQingdao 266590China the School of Artificial Intelligence Anhui UniversityHefei 266114 the Qingdao Academy of Intelligent Industries Qingdao 230031China the School of Mathematics Renmin University of ChinaBeijing 100872China the State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 the Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China

In the era of big data,there is an urgent need to establish data trading markets for effectively releasing the tremendous value of the drastically explosive *** security and data pricing,however,are still widely regarded as major challenges in this respect,which motivate this research on the novel multi-blockchain based framework for data trading markets and their associated pricing *** this context,data recording and trading are conducted separately within two separate blockchains:the data blockchain(DChain) and the value blockchain(VChain).This enables the establishment of two-layer data trading markets to manage initial data trading in the primary market and subsequent data resales in the secondary ***,pricing mechanisms are then proposed to protect these markets against strategic trading behaviors and balance the payoffs of both suppliers and ***,in regular data trading on VChain-S2D,two auction models are employed according to the demand scale,for dealing with users’ strategic *** incentive-compatible Vickrey-Clarke-Groves(VCG)model is deployed to the low-demand trading scenario,while the nearly incentive-compatible monopolistic price(MP) model is utilized for the high-demand trading *** temporary data trading on VChain-D2S,a reverse auction mechanism namely two-stage obscure selection(TSOS) is designed to regulate both suppliers’ quoting and users’ valuation ***,experiments are carried out to demonstrate the strength of this research in enhancing data security and trading efficiency.

关键词： Auction data trading markets multi-blockchain pricing mechanisms

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Detection of Detonators in Baggage Using Deep CNN Architecture: A Comparative Study of Contrast Enhancement and Feature Extraction Methods 8

Detection of Detonators in Baggage Using Deep CNN Architectu...

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8th IEEE International Conference on Image and Signal Processing and their Applications, ISPA 2024

作者： Lynda, Oulhissane Mostefa, Merah Moldovanu, Simona Moraru, Luminita LSS Faculty of Science and Technology Abdelhamid Ibn Badis University Laboratory of Signals and Systems Mostaganem Algeria Faculty of Automation Computers Electrical Engineering and Electronics Dunarea de Jos University of Galati Modelling & Simulation Laboratory MSlab Department of Computer Science and Information Technology Galati Romania Faculty of Sciences and Environment Modelling & Simulation Laboratory Dunarea de Jos University of Galati MSlab Department of Chemistry Physics & Environment Galati Romania

ISBN: (纸本)9798350309249

Visual inspection of dual-energy X-ray radiographic images of cabin baggage requires high performance, but is hindered by various challenges such as low target prevalence, variability in target visibility, possible presence of multiple targets, and security personnel fatigue and inattention. Artificial intelligence (AI) techniques, particularly deep convolutional neural networks (CNNs), have shown promise in improving the automatic detection of explosives, even with low-resolution radiographic images, especially in high baggage throughput scenarios. In this paper, we focus on the detection of detonators as components of improvised explosive devices. The proposed approach involves comparing two experiments implemented in a deep CNN architecture using TensorFlow and Keras libraries. In the first experiment, raw dual-energy radiographic images without any enhancement were used. The second experiment includes three methods for contrast enhancement and feature extraction: the Contrast Limited Adaptive Histogram Equalization (CLAHE) method, the wavelet transform-based method, and the mixed CLAHE RGB-Wavelet method. In the latter two methods, Haar, Db2, Coif2, and Sym2 mother wavelet functions at two levels (HH and HL) were employed. The analysis of results focuses on a comparative study of performance measures such as accuracy, precision, recall, and F1 score. It was found that the preprocessing methods used in experiment 2, for the two evaluated classes (detonator and no detonator), achieved higher accuracy compared to the raw radiographic images used in experiment 1 (98.08%). The highest accuracies in experiment 2, with a value of 100%, were obtained with the CLAHE method (green channel in grayscale, blue channel in grayscale, and RGB channels) and the wavelet transform method with Haar mother wavelet at two levels HL © 2024 IEEE.

关键词： Feature extraction

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Aspects of Data Transfer and Synchronization for Vulnerable Road Users Emergency Scenarios Based on Blockchain Technology in ITS

Aspects of Data Transfer and Synchronization for Vulnerable ...

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2024 systems of Signal Synchronization, Generating and Processing in Telecommunications, SYNCHROINFO 2024

作者： Pomogalova, A.V. Donskov, E.A. Elagin, V.S. Vladyko, A.G. The Bonch-Bruevich Saint-Petersburg State University of Telecommunications Infocommunication Systems Department Saint Petersburg Russia St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences Laboratory of Computer Security Problems Department St. Petersburg Russia Saint-Petersburg State University of Telecommunications Faculty of Infocommunication Networks and Systems the Bonch-Bruevich Saint Petersburg Russia Saint-Petersburg State University of Telecommunications Faculty of Fundamental Training the Bonch-Bruevich Saint Petersburg Russia

ISBN: (纸本)9798350373448

The paper presents a study of response scenarios in an intelligent transport system, in which pedestrians are participants, to emergency situations and their prevention. Pedestrians are included in the VRU (Vulnerable Road Users) category within the general ITS architecture and are most susceptible to accidents due to the lack of movement control. Scenarios for interaction with such traffic participants may include not only rules for responding and providing assistance as soon as possible, but also identifying the initiator of the incident for the purpose of further control and prevention of situations of a similar nature. The authors of the work propose the use of blockchain technology to ensure data safety, as well as the option of building an ITS architecture with a module for monitoring incident data and timely response. The paper provides mathematical calculations of the possibility of using blockchain technology within the framework of the proposed concept and modeling. © 2024 IEEE.

关键词： blockchain distributed ledger technology emergency scenario Intelligent Transport System ITS V2X Vehicle-to-Everything VRU

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On Security And Privacy In Smart Metering systems 7

On Security And Privacy In Smart Metering Systems

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7th International Conference on Smart and Sustainable Technologies, SpliTech 2022

作者： Bacnar, David Leytner, Lolita Prenc, Rene Jardas, Veljko Lerga, Jonatan University of Rijeka Faculty of Engineering Department of Computer Engineering Rijeka Croatia University of Rijeka Faculty of Engineering Department of Electric Power Systems Rijeka Croatia University of Angers Polytech Angers/Automation and Computer Engineering Department Angers France Jatro D.o.o. Rijeka Croatia

ISBN: (纸本)9789532901160

Smart meters are modernizing the electrical energy systems, solving numerous problems of the classical systems, and introducing new functionalities to the grid. This paper aims to give an insight into these systems in terms of their security and privacy aspects. Special attention is paid to the energy theft problem (meter tampering, physical anti-tampering measures, and theft detection methods). We, next, address other security issues present in remote metering (attack types, risks, and threats to the system). Also, necessary security requirements and signature-based, anomaly-based, and specification-based Intrusion Detection systems (IDS) are defined. We conclude by listing privacy concerns arising due to the remote meters and advanced metering infrastructures (AMI) being installed more and more. © 2022 University of Split, FESB.

关键词： Advanced metering infrastructures

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Hybrid Machine Learning and Deep Learning CNN Models for Apple Trees Leaves Pathologies Classification

Hybrid Machine Learning and Deep Learning CNN Models for App...

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computer Science (COMSCI), International Scientific Conference on

作者： Petar Iavorov Matov Milena Kirilova Lazarova Simona Kirilova Filipova-Petrakieva Ina Taralova Department of Computer Systems Faculty of Computer Systems and Technologies Technical University of Sofia Sofia Bulgaria Department of Theoretical Electrical Engineering Faculty of Automation Technical University of Sofia Sofia Bulgaria LS2N UMR CNRS 6004 Ecole Centrale de Nantes Nantes France

ISBN: (数字)9798350392166

ISBN: (纸本)9798350392173

Agricultural development in recent years has been based entirely on smart management. Leaves diseases on apple trees is a very common problem. The present work is a continuation of previous research of the author's team to solve it. The recently proposed apple leaves pathology prediction model based on deep learning convolutional neural network (CNN) is extended to hybrid models. The latter are a combination of a deep learning CNN and classical machine learning techniques. To increase the classification accuracy two hybrid models are proposed: CNN+SVM (Support Vector Machines) and CNN+RF (Random Forest). The CNN is based on modified DenseNet architecture and SVM and RF models are integrated as CNN output is fed to SVM and RF models respectively to ensure higher classification accuracy. The suggested hybrid models are evaluated on a data set that comprises 1800 images of pathologies in apple trees’ leaves. The experimental results prove the higher accuracies of the hybrid deep + machine learning models compared to the deep learning CNN model.

关键词： Deep learning Support vector machines Radio frequency Pathology Accuracy Computational modeling computer architecture Predictive models Convolutional neural networks Random forests

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The effect of graph complexity in an energy-based FDI approach

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IFAC-PapersOnLine 2024年第4期58卷 622-627页

作者： Jan H. Smith George van Schoor Kenneth R. Uren Thomas Schäfer School of Electrical Electronic and Computer Engineering Faculty of Engineering North-West University South Africa Unit for Energy and Technology Systems Faculty of Engineering North-West University Institute for Process Technology Process Automation and Measurement Technology Zittau/Görlitz Germanuy

This paper introduces a structured approach for creating node signature graphs in energy graph-based visualization for industrial systems, focusing on anomaly detection. It examines the relationship between graph cardinality and the singular value decomposition analysis applied in the energy graph-based visualization method. The results reveal a trade-of between graph complexity and singular value resolution. The study highlights how graph structure affects energy flow monitoring and anomaly detection. It notably enables fault detection in components not represented as nodes, enhancing the methodology in energy-based system monitoring.

关键词： Fault detection isolation Graph reduction Graph matching Hybrid FDI Industrial process Thermal flow process Graph-based anomaly detection

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A Parallel and Asynchronous Blob Shape Descriptor Implemented in CMOS Technology 33

A Parallel and Asynchronous Blob Shape Descriptor Implemente...

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33rd IEEE International Conference on Microelectronics, MIEL 2023

作者： Bogacki, P. Dlugosz, M. Talaska, T. Dlugosz, R. Aptiv Services Poland Kraków30-399 Poland Agh University of Science and Technology Institute of Telecommunications Faculty of Computer Science Electronics and Telecommunications Kraków30-059 Poland Poznan University of Technology Faculty of Control Robotics and Electrical Engineering Institute of Automation and Robotics Division of Signal Processing and Electronic Systems Poznan60-965 Poland Bydgoszcz University of Science and Technology Faculty of Telecommunication Computer Science and Electrical Engineering Bydgoszcz85-796 Poland

ISBN: (纸本)9798350347760

The paper presents a family of novel light blob shape descriptors for use in selected active safety algorithms used in Advanced Driver Assistance systems (ADAS). One of the motivations was to obtain a descriptor that would ensure low computational complexity. This makes it easy to implement both in software and hardware. One assumption is that the location of the center of a given light spot is approximately known. The principle of its operation is then to count white pixels in selected directions, starting from this central point. A key issue here is an efficient way of determining indexes of particular pixels belonging to the image patch, as well as the location of points representing places where the white area turns into black. In the case of a hardware implementation, this can be done using a parallel circuit operating in asynchronous mode, without the need for a control clock. © 2023 IEEE.

关键词： Pixels

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Integrating Variable Reduction Strategy With Evolutionary Algorithms for Solving Nonlinear Equations systems

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IEEE/CAA Journal of Automatica Sinica 2022年第1期9卷 75-89页

作者： Aijuan Song Guohua Wu Witold Pedrycz Ling Wang School of Traffic and Transportation Engineering Central South UniversityChangsha 410075China Department of Electrical and Computer Engineering University of AlbertaEdmontonAB T6G 2V4Canada Department of Electrical and Computer Engineering Faculty of EngineeringKing Abdulaziz UniversityJeddah 21589Saudi Arabia Systems Research Institute Polish Academy of SciencesWarsaw 01447Poland Department of Automation Tsinghua UniversityBeijing 100084China

Nonlinear equations systems(NESs)are widely used in real-world problems and they are difficult to solve due to their nonlinearity and multiple *** algorithms(EAs)are one of the methods for solving NESs,given their global search capabilities and ability to locate multiple roots of a NES simultaneously within one ***,the majority of research on using EAs to solve NESs focuses on transformation techniques and improving the performance of the used *** contrast,problem domain knowledge of NESs is investigated in this study,where we propose the incorporation of a variable reduction strategy(VRS)into EAs to solve *** VRS makes full use of the systems of expressing a NES and uses some variables(i.e.,core variable)to represent other variables(i.e.,reduced variables)through variable relationships that exist in the equation *** enables the reduction of partial variables and equations and shrinks the decision space,thereby reducing the complexity of the problem and improving the search efficiency of the *** test the effectiveness of VRS in dealing with NESs,this paper mainly integrates the VRS into two existing state-of-the-art EA methods(i.e.,MONES and DR-JADE)according to the integration framework of the VRS and EA,*** results show that,with the assistance of the VRS,the EA methods can produce better results than the original methods and other compared ***,extensive experiments regarding the influence of different reduction schemes and EAs substantiate that a better EA for solving a NES with more reduced variables tends to provide better performance.

关键词： Evolutionary algorithm(EA) nonlinear equations systems(ENSs) problem domain knowledge variable reduction strategy(VRS)

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Strong Stabilization of the Acrobot at the Down–Up Equilibrium Point ⋆

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IFAC-PapersOnLine 2023年第2期56卷 9167-9172页

作者： Ziyu Wang Xin Xin Yannian Liu School of Automation Southeast University and Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing 210096 China Faculty of Computer Science and Systems Engineering Okayama Prefectural University Okayama 719-1197 Japan

In this paper, the strong stabilization of the Acrobot at the Down-Up equilibrium point is addressed, with the first link being downward and the second link being upright. By converting the strong stabilization of the Acrobot at the Down–Up equilibrium point equivalently to the existence and design of a stable stabilizing controller for a fourth-order single-input single-output linear plant with adjustable zeros, a pair of poles on the imaginary axis, and a pair of real poles located symmetrically with respect to the origin, this paper has three main contributions. Firstly, the existence of a stable stabilizing controller for any Acrobot which is linearly controllable at the Down–Up equilibrium point is proved by showing the range of the adjustable zero via adjusting a parameter of the output signal. Secondly, a necessary and sufficient condition on the mechanical parameters of the Acrobot is provided to guarantee the existence of a second-order stable stabilizing controller for the Acrobot around its Down– Up equilibrium point. Thirdly, a direct method is presented to design a second-order stable controller, whose transfer function is preset with three parameters. By utilizing the Liénard– Chipart criterion for a fourth-order polynomial, the necessary and sufficient conditions on these parameters for achieving the strong stabilization are obtained, which are expressed in a cascade form for obtaining these parameters conveniently. A numerical example is presented to validate the effectiveness of the proposed method.

关键词： Robust control strong stabilization underactuated mechanical systems reduced-order controller linear systems

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