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arXiv 2023年

作者： Foszner, Pawel Szczęsna, Agnieszka Ciampi, Luca Messina, Nicola Cygan, Adam Bizon, Bartosz Cogiel, Michal Golba, Dominik Macioszek, Elżbieta Staniszewski, Michal Department of Computer Graphics Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland Institute of Information Science and Technologies National Research Council Pisa Italy QSystems.pro sp. z o.o. Mochnackiego 34 Bytom41-907 Poland Blees sp. z o.o. Zygmunta Starego 24a/10 Gliwice44-100 Poland Department of Transport Systems Traffic Engineering and Logistics Faculty of Transport and Aviation Engineering Silesian University of Technology Katowice Poland

Generally, crowd datasets can be collected or generated from real or synthetic sources. Real data is generated by using infrastructure-based sensors (such as static cameras or other sensors). The use of simulation tools can significantly reduce the time required to generate scenario-specific crowd datasets, facilitate data-driven research, and next build functional machine learning models. The main goal of this work was to develop an extension of crowd simulation (named CrowdSim2) and prove its usability in the application of people-tracking algorithms. The simulator is developed using the very popular Unity 3D engine with particular emphasis on the aspects of realism in the environment, weather conditions, traffic, and the movement and models of individual agents. Finally, three methods of tracking were used to validate generated dataset: IOU-Tracker, Deep-Sort, and Deep-TAMA. © 2023, CC BY.

关键词： Deep learning

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Refresh Method for the Weights of the Analogue Synapses

Refresh Method for the Weights of the Analogue Synapses

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International Conference on System Theory, control, and Computing (ICSTCC)

作者： Mircea Hulea Alexandru Bârleanu Faculty of Automatic Control and Computer Engineering Gheorghe Asachi Technical University of Iasi Iasi Romania

ISBN: (数字)9781728198095

ISBN: (纸本)9781728198101

The analogue implementation of spiking neural networks have the critical advantage of parallel operation and information transmission. The implementation in hardware of the synaptic weights and learning mechanisms represents a challenging task. A cheap and efficient method to store the weights of analogue SNN which benefits from real time adjustment represents the capacitors. However, the main disadvantage of this method represents the leakage currents which make the synaptic weights volatile. This paper proposes and evaluates experimentally a method for refreshing the weights of the analogue synapses by rhythmic activation of the neurons. The results show that the long term memory of analogue neurons improves significantly if the neurons are activated at certain periods of time. Moreover, in order to obtain non-volatile memory the refresh rate can be determined as a function of the initial value and the variation of the synaptic weights.

关键词： Neurons Synapses Capacitors Depression Hardware Random access memory Information processing

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Novel Image Steganography Algorithm Using Two Hidden Thresholds

Novel Image Steganography Algorithm Using Two Hidden Thresho...

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International Conference on System Theory, control, and Computing (ICSTCC)

作者： Alexandru-Gabriel Tudorache Vasile Manta Simona Caraiman Faculty of Automatic Control and Computer Engineering "Gheorghe Asachi" Technical University Iași Romania

ISBN: (数字)9781728198095

ISBN: (纸本)9781728198101

This paper describes a novel image steganography algorithm, with the central idea being the use of two hidden thresholds. By implementing the described method, various types of information (sub-images, numbers, symbols) can be hidden inside a usual image. The article presents how to apply this procedure for a gray image: after recovering the two threshold values, hidden inside the least significant bit of each of the first 16 pixels on the edges, an image can be processed by comparing the gray level to the threshold levels (making sure the gray level is between the thresholds) and thus reveal the secret message. The algorithm can be extended to different types of data and image representations and could also suggest another method of embedding metadata inside an image, such as the time of download, the original website from where it was downloaded or information on its author, etc.

关键词： Image edge detection Gray-scale Protocols Image color analysis computer science Indexes Image representation

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Optimization of Methodology for Identifying Partial Discharges in Insulating Liquids through Optical Radiation Analysis Using Machine Learning

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Koziol, Michal Boczar, Tomasz Jancarczyk, Daniel Bernas, Marcin Opole University of Technology Faculty of Electrical Engineering Automatic Control and Informatics Opole45-758 Poland University of Bielsko-Biala Department of Computer Science and Automatics Bielsko-Biala43-309 Poland

The emission of optical radiation is associated with electrical discharges in high-voltage power systems. Detecting, measuring, and analyzing this radiation can enable the identification of the type of electrical discharge and the determination of its source. The article presents the results of measurements and analysis of optical spectra in the context of their application for recognizing different forms of electrical discharges in selected insulating liquids. Optical radiation in the ultraviolet, visible light, and near-infrared range, emitted by electrical discharges in insulating liquids commonly used in electrical engineering, such as mineral oil, natural ester, and synthetic ester, was analyzed. As part of the research, an innovative methodology for measuring and analyzing optical radiation emitted by electrical discharges was proposed, utilizing machine learning tools for precise analysis and interpretation of measurement data. The research results enrich current knowledge with new parameters and measurement indicators, representing another stage in the development of diagnostic methods that can be used to build expert systems and new diagnostic techniques for high-voltage insulation systems. © 1963-2012 IEEE.

关键词： Electric insulation

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A Supervised Generative Model for Efficient Rendering of Medical Volume Data

A Supervised Generative Model for Efficient Rendering of Med...

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E-Health and Bioengineering Conference (EHB)

作者： Marius Gavrilescu Faculty of Automatic Control and Computer Engineering “Gheorghe Asachi” Technical University of Iasi Iasi Romania

ISBN: (数字)9781728188034

ISBN: (纸本)9781728188041

Complex 3D and multidimensional medical data require significant computational resources to render high-quality, high-resolution images which provide useful information from the originating data set. As an alternative to traditional on-the-fly ray-casting-based generation of such images from volume data, we propose a generative model based on a deep neural network which is continually trainable from data dynamically generated by a GPU-based renderer. When properly trained, the model is capable of independently generating images similar to ones produced by a dedicated renderer, using control parameters commonly encountered in volume rendering engines. The network takes over the task of generating images from such parameters, thereby alleviating the need for high-capability computational resources while at the same time providing images without requiring access to the original data sets. Our model allows the user to generate high-resolution images on low-spec hardware without the need for a GPU-based renderer, and without access to sensitive or protected patient data. Also, the model is exploitable in a manner which allows the fully-interactive exploration of complex volume data sets and the efficient generation of representations of the data using limited computational resources.

关键词： Isosurfaces Rendering (computer graphics) Neural networks Training Data models Task analysis Biomedical imaging

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Trends and Challenges of Sustainable Agriculture in the Iraqi Environment

Trends and Challenges of Sustainable Agriculture in the Iraq...

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Blockchain, Smart Healthcare and Emerging Technologies (SmartBlock4Health), IEEE International Conference on

作者： Hanan Hussein Al-asadi Maria Goga Haider Abdullah Ali Ramona Cristina Popa Awodele Oludele Faculty of Automatic Control and Computers University POLITEHNICA of Bucharest Bucharest Romania University of Technology-Iraq Baghdad Iraq UTCB Department for Training of Teaching Personnel Technical University of Civil Engineering of Bucharest Bucharest Romania Madenat Alelem University College Baghdad Iraq Faculty of Engineering in Foreign Languages University POLITEHNICA of Bucharest Bucharest Romania computer science department Babcock University Ogun State Nigeria

ISBN: (纸本)9781665460156

The use of Agriculture Intelligent Systems (AISs) in Iraq has become popular among farmers. The greenhouse is a solution for plant growth, which uses an effective microclimate to simulate seasons and to use alternative energy sources like solar, thermal, and photovoltaic systems for microclimate control. Greenhouses are considered a successful solution with developments and achievements in the technology of this field. However, problems like high costs, difficulties in installation and maintenance, or the need for some procedures should be considered. Because Iraq is close to the equator (3669 km), it receives sufficient solar power. It also has large areas available for the building of solar greenhouse systems. The farmers need an affordable and functional smart greenhouse to enable and encourage them to use the environment efficiently. We intend to develop low-cost, accurate, and easy-to-use greenhouse systems controlled by artificial intelligence algorithms. Farmers will be able to control the greenhouse by using simple commands. Machine learning algorithms provide real-time and effective analysis that could support farmers in decision-making and provide relevant data for researchers and policymakers. AISs algorithms can lead to a sustainable and productive agriculture system. The system can be used in Iraq with sufficient government support and subsidy.

关键词： Smart agriculture Machine learning algorithms Costs Green buildings Soil control systems Agriculture

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Distributed Model Predictive control Algorithm with Communication Delays for a Cooperative Adaptive Cruise control Vehicle Platoon

Distributed Model Predictive Control Algorithm with Communic...

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Mediterranean Conference on control and Automation (MED)

作者： Anca Maxim Corneliu Lazar Constantin F. Caruntu Faculty of Automatic Control and Computer Engineering “Gheorghe Asachi” Technical University of Iasi Iasi Romania

ISBN: (数字)9781728157429

ISBN: (纸本)9781728157436

This paper proposes a distributed model predictive control (DMPC) strategy with known delays in the communication network. The algorithm is suitable for a vehicle platooning application in the cooperative adaptive cruise control (CACC) framework. All the platoon vehicles are connected in a uni-directional wireless communication network. The simulation results for a five-vehicle platoon show that the DMPC optimization problem can successfully accommodate for the communication delays, while a velocity-dependent inter-vehicle spacing-policy for the follower vehicles is used.

关键词： Delays Optimization Trajectory Mathematical model Computational modeling Cruise control Current measurement

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A sliding mode controller design for thermal comfort in buildings

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engineering Transactions 2019年第4期67卷 475-489页

作者： Skruch, Pawel Dlugosz, Marek AGH University of Science and Technology Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering Department of Automatic Control and Robotics Al. Mickiewicza 30 Kraków30-059 Poland

One of the factors determining comfort in buildings is the indoor air temperature of the rooms. A control system, part of the home automation system, should stabilise air temperature to the desired level, despite various disturbances such as the presence of random or occasional sources of heat. Inaccurate models of the dynamics of air temperature changes in buildings prescribe the use of robust control methods, a type of which is the sliding mode controller. This article presents the application of a sliding mode controller (SMC) to home automation systems, designed to control air temperature inside a building. The sliding-mode controller makes use of sliding surfaces, which are defined by the assumed trajectory and the system output. The control law is designed in such a way that the trajectory of the system tends to the sliding surface from any initial point and remains on it after reaching the sliding surface. In this article, a model at air temperature change dynamics inside a building is presented. The modelling approach relies on the lumped-parameter methodology, in which distributed physical properties are represented by lumped parameters (such as thermal capacity or resistance). The model takes into account the loss of heat through conduction and ventilation, as well as internal heat gain. The parameters of the model can be obtained easily from the thermal properties of the construction materials. Theoretical considerations were applied in simulation experiments and the results of these experiments confirm the performance improvement achieved by the proposed solutions. © 2019, Polish Academy of Sciences. All rights reserved.

关键词： Atmospheric temperature

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Hard hat wearing detection based on head keypoint localization

arXiv

引用

arXiv 2021年

作者： Wójcik, Bartosz Zarski, Mateusz Ksiązek, Kamil Miszczak, Jaroslaw A. Skibniewski, Miroslaw J. Faculty of Civil Engineering Silesian University of Technology Poland Institute of Theoretical and Applied Informatics Polish Academy of Sciences Poland Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Poland Department of Civil & Environmental Engineering University of Maryland College Park United States

In recent years, a lot of attention is paid to deep learning methods in the context of vision-based construction site safety systems. However, still there is no reliable way to establish the relationship between supervised construction workers and their basic personal protective equipment, like hard hats. To address this problem, a novel deep learning method combining object detection, keypoint localization, and simple rule-based reasoning is proposed in this article. In tests, this solution surpassed the previous methods based on the relative bounding box position of different instances, as well as direct detection of hard hat wearers and non-wearers. Achieving MS COCO style overall AP of 67.5% compared to 66.4% and 66.3% achieved by the above-mentioned approaches, with class specific AP for hard hat non-wearers of 64.1% compared to 63.0% and 60.3%. The results show that the conjunction of deep learning methods with humanly-interpretable rule-based algorithm is better suited for detection of hard hat non-wearers. Code is available at barwojcik/hard-hats. © 2021, CC BY.

关键词： Object detection

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Securing isosceles triangular formations under heterogeneous sensing and mixed constraints

arXiv

引用

arXiv 2021年

作者： Chan, Nelson P.K. Jayawardhana, Bayu de Marina, Hector Garcia Engineering and Technology Institute Groningen University of Groningen Nijenborgh 4 Groningen9747AG Netherlands Department of Computer Architecture and Automatic Control Faculty of Physics Universidad Complutense de Madrid Madrid28040 Spain

This paper focuses on securing a triangular shape (up to translation) for a team of three mobile robots that uses heterogeneous sensing mechanism. Based on the available local information, each robot employs the popular gradient-based control law to attain the assigned individual task(s). In the current work, robots are assigned either distance and signed area task(s) or bearing task(s). We provide a sufficient condition on the gain ratio RAd between the signed area and the distance control term such that the desired formation shape, an isosceles triangle, is reached from all feasible starting positions. Numerical simulations are provided to support the theoretical *** Codes 93D99 © 2021, CC BY-NC-SA.

关键词： Robots

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