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International Conference on Advanced computer Information Technologies (ACIT)

作者： Viktor Satsyk Oleksandr Reshetylo Lyudmila Markina Nataliia Khrystynets Nataliia Bahniuk Yuliia Melnychuk Automation and Computer-Integrated Technologies Department Lutsk National Technical University Lutsk Ukraine Department of Automation and Computer-Integrated Technologies Lutsk National Technical University Lutsk Ukraine Computer Engineering and Cyber Security Department Lutsk National Technical University Lutsk Ukraine Department of Computer Engineering and Cyber Security Lutsk National Technical University Lutsk Ukraine Department of Digital Educational Technologies Lutsk National Technical University Lutsk Ukraine

ISBN: (数字)9798350350043

ISBN: (纸本)9798350350050

in the article we develop modeling and creating a prototype of improved solar power plant for economical power supply systems for consumers which require simple autonomous inexpensive practical energy solutions. On the basis of Arduino Uno microcontroller board, a software-hardware complex for controlling the angle of the solar panel has been developed, which allows to follow the position of sun and automatically turn the solar panel in its direction. With aid of developed Android application on a smartphone screen, it is possible to monitor the amount of voltage produced by the solar panel at current time moment, and to analyze the dynamics of its change over time and, accordingly, to plan effective use the generated energy.

关键词： Power supplies Power system dynamics Prototypes Solar energy Universal Serial Bus Software Solar panels Sun Power generation Monitoring

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Skeleton-Based Multi-Stream Adaptive Graph Convolutional Network for Indoor Scene Action Recognition

Skeleton-Based Multi-Stream Adaptive Graph Convolutional Net...

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2023 China automation Congress, CAC 2023

作者： Li, Jiazhuo Chen, Luefeng Li, Min Wu, Min Pedrycz, Witold Hirota, Kaoru The School of Automation The Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems The Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China University of Geosciences Wuhan430074 China The Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 2R3 Canada The Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland The Department of Computer Engineering Istinye University Sariyer Istanbul34396 Turkey The Tokyo Institute of Technology Tokyo226-8502 Japan

ISBN: (纸本)9798350303759

With the rapid advances in computer vision, human action recognition has gradually received attention, but the current methods still exhibit some problems in indoor environments. The human skeleton, as the framework of human motion, contains high-quality actional feature information, and the skeleton-based action recognition method effectively avoid the interference of interior background noise and has advantages in indoor action recognition. The outstanding effect of graph convolutional networks on graph structure data processing has led to its rapid development and wide application in skeleton-based action recognition. Second-order skeletal information also contains a large number of actional features but is not effectively utilized. The artificial predefined topology of the human skeleton map has limitations, and cannot reflect the interaction between limbs. To solve the above problems, this article designs an adaptive weighted multi-stream graph convolutional network (AM-GCN) based on skeletal information, using an attention mechanism to enhance the network's ability to extract actional features, and an adaptive layer to make the construction graph more flexible, incorporating second-order skeletal features through a dual-stream architecture. In this article, the NTU-RGB+D dataset has been used for the experiments, the results show that the method in this article has good results. © 2023 IEEE.

关键词： Convolution

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Recursive Broadcasting Approach

Recursive Broadcasting Approach

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Euromicro Conference on Parallel, Distributed and Network-Based Processing

作者： Hovhannes A. Harutyunyan Narek Hovhannisyan Department of Computer Science and Software Engineering Concordia University Montreal QC Canada NAS RA Institute for Informatics and Automation Problems Yerevan Armenia

ISBN: (数字)9798331524937

ISBN: (纸本)9798331524944

Broadcasting is one of the fundamental information dissemination primitives in interconnection networks, where a message is passed from one node (called originator) to all other nodes in the network. Following the increasing interest in interconnection networks, extensive research was dedicated to broadcasting. Two main research goals of this area are finding inexpensive network structures that maintain efficient broadcasting and finding the broadcast time for well-known and widely used network topologies. In the scope of this study, we will mainly focus on determining the broadcast time and nearoptimal broadcasting schemes in networks. Determination of the broadcast time of any node in an arbitrary network is known to be NP-hard. Polynomial time solutions are known only for a few network topologies. There also exist various heuristic and approximation algorithms for different network topologies. In this study, we consider the broadcast time problem on graphs that comprise some recursive structures. We initiate a novel direction to designing broadcasting algorithms on recursively defined graphs. We provide a theoretical foundation for future broadcasting studies, as well as discuss several practical applications of the approach we introduce.

关键词： Multicast algorithms Network topology Multiprocessor interconnection Heuristic algorithms Broadcasting Approximation algorithms Polynomials Topology

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Islanding Protection scheme based on IEC61850 GOOSE application for 11kV network with distributed energy resources

Islanding Protection scheme based on IEC61850 GOOSE applicat...

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Power engineering Conference (SAUPEC), Southern African Universities

作者： Abuyile Mpaka Senthil Krishnamurthy Department of Electrical Electronics and Computer Engineering Centre for Substation Automation and Energy Management Systems (CSAEMS) Cape Peninsula University of Technology South Africa

ISBN: (数字)9798331535162

ISBN: (纸本)9798331535179

This study focuses on islanding protection for a microgrid operating at 11kV. The literature provides novel algorithms developed for islanding protection schemes. However, there is a lack of validation and test the IEC61850 GOOSE message application for the islanding protection scheme. The paper's significant contribution is to address the literature gap by comparing legacy islanding protection with the IEC 61850 GOOSE message application. The research utilizes simulation techniques in the DigSilent and Hardware-in-the-Loop (HIL) simulations using RTDS to assess the performance of the Islanding protection scheme. Four test scenarios were conducted, which include undervoltage, overvoltage, underfrequency, and overfrequency protection functionalities. The simulation validation results from these four scenarios confirm that the modeled distribution system meets the required protection criteria for both legacy (hardwired) and modern IEC61850 GOOSE message applications. The simulation results show that the GOOSE message application for the Islanding protection scheme operates faster than the legacy scheme.

关键词： Islanding Hardware-in-the-loop simulation Microgrids Standardization Reliability Protection Voltage control Monitoring Testing Resilience

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Price Prediction of Digital Currencies using Machine Learning 10

Price Prediction of Digital Currencies using Machine Learnin...

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10th IEEE International Conference on Data Science and Advanced Analytics, DSAA 2023

作者： Dwivedi, Ashutosh Dhar Dutta, Subhayu Adhikary, Subhrangshu Pedersen, Jens Myrup Aalborg University Cyber Security Group Department of Electronic Systems Copenhagen Denmark Dr. B.C. Roy Engineering College Department of Computer Science & Engineering West Bengal Durgapur713206 India Spiraldevs Automation Industries Pvt. Ltd. Department of Research & Development West Bengal Raiganj733123 India

ISBN: (纸本)9798350345032

Cryptocurrencies have gained immense significance and popularity in recent times. With thousands of digital currencies available, selecting the right one can be challenging for users. In the financial sector, accurately predicting future prices is crucial for profitable investments in digital currencies. However, price prediction in this realm poses unique challenges, as it lacks physical goods or services as the basis, unlike stock prices. Machine learning emerges as a pivotal tool for addressing this challenge and plays a vital role in price prediction. This research analyzes five prominent currencies - Monero, Bitcoin, Ethereum, IOTA, and Zcash - employing five models: SVR, LRG, Huber, RANSAC, MLP, and AdaBoost. The experimental results demonstrate promising outcomes, showcasing the ability to predict digital currency prices with an impressive R2 score of 1.0 for specific machine learning algorithms. This advancement opens new avenues for informed decision-making and profitable ventures in the dynamic world of digital currencies. © 2023 IEEE.

关键词： Forecasting

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AI Integrated Dialogic Alphabet Zone Board for Kids in Pre-childhood Education

AI Integrated Dialogic Alphabet Zone Board for Kids in Pre-c...

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International Conference on Electrical, computer and Communication engineering (ECCE)

作者： Asif Mahmud Tahsin Faisal M. Akhtaruzzaman Jamal Uddin Tanvin Sachitra Halder Fahim Shahryer Department of Computer Science and Engineering Military Institute of Science and Technology Dhaka Bangladesh Quantum Robotics and Automation Research Group (QRARG) Dhaka Bangladesh

ISBN: (数字)9798350357509

ISBN: (纸本)9798350357516

The smart Dialogic Alphabet Zone Board (DAZ-Board) aims to address the issue of learning process for pre-childhood education among the children. It is importance to facilitate a healthy and effective environment for early childhood education in shaping a child’s cognitive development, language acquisition, and literacy skills. Traditional teaching methods often fail to engage young learners effectively, leading to limited understanding and retention. On the other hand, dependencies on mobile devices raise the physical and mental health issues. This study introduces an interactive, auditory, and multisensory game board providing a wonderful and healthy experiences in tailoring the developmental needs of children. The objective of this research is to design and develop an interactive alphabet board with necessary sensors, electronics, and controller modules. Moreover, designing a Machine Learning (ML) model for voice-based alphabet recognition is one of the important contributions of this research. Among the results of different ML models, Naïve Bayes Classifier outperforms the most with accuracy ≈ . %. The proposed system will facilitate the preschoolers to learn in modern and interactive way, while keeping away from being addicted to the mobile devices.

关键词： Pediatrics Visualization Accuracy Scalability Education Games Speech recognition Sensors Smart phones Systematic literature review

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ArbiTrack: A Novel Multi-Object Tracking Framework for a moving UAV to Detect and Track Arbitrarily Oriented Targets

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IEEE Transactions on Multimedia 2025年

作者： Chen, Yuqing Wang, Jiayu Zhou, Qianchen Hu, Huosheng Dalian Maritime University Department of Automation College of Marine Electrical Engineering Dalian116026 China University of Essex School of Computer Science and Electronic Engineering ColchesterCO43SQ United Kingdom

The operation of traditional multi-object trackers on a moving unmanned aerial vehicle (UAV) faces many difficulties due to the irregular motion of UAV, the occlusion problem, and in particular arbitrarily oriented targets that are densely distributed with complex backgrounds. To solve these difficulties, this paper proposes a novel multi-object tracking framework, namely ArbiTrack, for a moving UAV to effectively detect and track arbitrarily oriented targets on the grounds. The proposed framework consists of an oriented object detection module to capture ground objects, a multi-scale context aggregation (MCA) module to improve the detection accuracy of small objects, and an adaptive motion switching (AMS) module to deal with the nonlinear complexity among UAV and ground objects. Historical information from multiple moments is used in this framework to learn the spatio-temporal characteristics so that the occlusion problem can be solved effectively. Experiments are conducted by using our OriDrone dataset and the public dataset UAVDT dataset. Results demonstrate that the proposed method achieves state-of-the-art tracking performance. © 2025 IEEE.

关键词： Object tracking

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Adaptive Resource Allocation with SVM-based Multi-hop Video Packet Delay Bound Violation Modeling

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Chinese Journal of Electronics 2023年第2期20卷 261-267页

作者： Yunsheng Zhang Yongfei Zhang Shixin Sun Shiyin Qin Zhihai He School of Computer Science and Engineering University of Electronic Science and Technology Chengdu China School of Automation Science and Electrical Engineering Beihang University Beijing China Department of Electrical and Computer Engineering University of Missouri Columbia MO U.S.A

In this work, we develop a multi-hop packet delay bound violation model using Support vector machines (SVM) to predict the packet loss probability and end-to-end distortion for video streaming over multi-hop networks. Based on this model, we formulate the resource allocation into a non-convex optimization problem which aims to minimize the overall video distortion while maintaining fairness between sessions. We solve this optimization problem using Lagrangian duality methods. Extensive experimental results demonstrate that, with this widely-used offline-training-online-estimation mechanism, the proposed model is potentially applicable to almost all network conditions and can provide fairly accurate estimation results as compared with other models with a given sample data set. The proposed optimization algorithm achieves more efficient resource allocation than existing schemes.

关键词： Support vector machines Adaptation models Computational modeling Spread spectrum communication Streaming media Predictive models Distortion

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Deep Learning Meets Mechanism Design: Key Results and Some Novel Applications

arXiv

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arXiv 2024年

作者： Sankar, V. Udaya Rao, Vishisht Srihari Narahari, Y. Department of Electronics and Communicatin Engineering SRM University A.P. Guntur India Department of Computer Science and Automation Indian Institute of Science Bangalore India

Mechanism design is essentially reverse engineering of games and involves inducing a game among strategic agents in a way that the induced game satisfies a set of desired properties in an equilibrium of the game. Desirable properties for a mechanism include incentive compatibility, individual rationality, welfare maximisation, revenue maximisation (or cost minimisation), fairness of allocation, etc. It is known from mechanism design theory that only certain strict subsets of these properties can be simultaneously satisfied exactly by any given mechanism. Often, the mechanisms required by real-world applications may need a subset of these properties that are theoretically impossible to be simultaneously satisfied. In such cases, a prominent recent approach is to use a deep learning based approach to learn a mechanism that approximately satisfies the required properties by minimizing a suitably defined loss function. In this paper, we present, from relevant literature, technical details of using a deep learning approach for mechanism design and provide an overview of key results in this topic. We demonstrate the power of this approach for three illustrative case studies: (a) efficient energy management in a vehicular network (b) resource allocation in a mobile network (c) designing a volume discount procurement auction for agricultural inputs. Section 6 concludes the paper. © 2024, CC BY-NC-ND.

关键词： Deep learning

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Plate Shape Prediction Based on Data-Driven in Roll Quenching Process

Plate Shape Prediction Based on Data-Driven in Roll Quenchin...

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2023 China automation Congress, CAC 2023

作者： Hu, Liu Chen, Luefeng Hu, Jie Wu, Min Pedrycz, Witold Hirota, Kaoru School of Automation Ministry of Education China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems The Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6R 2G7 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Istinye University The Department of Computer Engineering Istanbul Sariyer34396 Turkey Tokyo Institute of Technology Tokyo Yokohama226-8502 Japan

ISBN: (纸本)9798350303759

In the process of steel plate production, predicting the plate shape is of great significance for producing high-quality and consistently stable plate shapes. This paper presents a model that predicts both the defect types and flatness of the plate, providing theoretical support for setting process parameters in roller quenching production. First, the parameters of the quenching process are analyzed to identify their characteristics. Then, the K-Means clustering algorithm and correlation analysis are employed to process the quenching process parameters. A gradient boosting decision tree (GBDT) model is used to predict the defect types and flatness of the steel plates. Finally, industrial production data is utilized for experimental validation. The obtained experimental results verify the reliability of the proposed method. © 2023 IEEE.

关键词： Decision trees

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