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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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A Survey of Multipath Load Balancing Based on Network Stochastic Model in MANET 23

A Survey of Multipath Load Balancing Based on Network Stocha...

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23rd International Conference on Advanced Communication Technology, ICACT 2021

作者： Hui, Zhang Lingli, Zhang Yonghang, Yan Linlin, Ci School of Computer Science Technology Beijing Institute of Technology Beijing China Beijing Aerospace Automatic Control Institute Beijing China School of Computer and Information Engineering Henan University Kaifeng China

ISBN: (纸本)9791188428069

Mobile Ad Hoc Network (MANET) is a special kind of network that differs from traditional communication network. It consists of multiple wireless nodes within an area, with each device assuming responsibility for assisting in forwarding packets and being free to move around the area to change the wireless connection at any time. The network's wireless topology may change rapidly and unpredictably, and MANET has no centralized control for distribution of load properly, so load balancing becomes one of the most important issue in MANET. When a network transmits a large number of packets, if there is no load balancing, the network's life and performance will be affected due to congestion, high latency and data loss caused by overloading the network. Load balancing can improve network life and performance by distributing the load on a per-node basis. With development of the research, multipath routing protocols are more popular than single-path routing protocols, and multi-path routing protocols have shown superiority in their ability to improve packet rates, increase transmission reliability, and handle network congestion and busy traffic on time. This paper examines some multi-path load-balanced routing schemes in MANET networks and provides the relative advantages and disadvantages of the protocols so that we can identify future directions for research. © 2021 Global IT Research institute (GiRI).

关键词： Routing protocols

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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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Global scale solar energy harnessing: An advanced intra-hourly diffuse solar irradiance predicting framework for solar energy projects

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Neural Computing and Applications 2024年第18期36卷 10585-10598页

作者： El-kenawy, El-Sayed M. Bailek, Nadjem Bouchouicha, Kada Zerouali, Bilel Hassan, Muhammed A. Kuriqi, Alban Jamil, Basharat Colak, Ilhami Khalil, Adel Ibrahim, Abdelhameed Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Mansoura35111 Egypt Laboratory of Mathematics Modeling and Applications Department of Mathematics and Computer Science Faculty of Sciences and Technology Ahmed Draia University of Adrar Adrar01000 Algeria Energies and Materials Research Laboratory Faculty of Sciences and Technology University of Tamanghasset Tamanrasset10034 Algeria MEU Research Unit Middle East University Amman Jordan Adrar01000 Algeria Vegetal Chemistry-Water-Energy Laboratory Faculty of Civil Engineering and Architecture Department of Hydraulic Hassiba Benbouali University of Chlef Ouled Fares Chlef02180 Algeria Mechanical Power Engineering Department Faculty of Engineering Cairo University Giza12613 Egypt School of Architecture University of Waterloo 7 Melville St S CambridgeONN1S 2H4 Canada CERIS Instituto Superior Tecnico Universidade de Lisboa Lisbon Portugal Civil Engineering Department University for Business and Technology PristinaKosovo10000 High Temperature Processes Unit IMDEA Energy Institute Av. Ramón de La Sagra 3 Móstoles Madrid28935 Spain Faculty of Engineering and Architectures Nisantasi University Istanbul Turkey Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura35516 Egypt

Diffuse horizontal irradiance (DHI) forecasts are critical for adopting solar photovoltaic technology. Yet, they can lack reliability given the limited and uncertain meteorological data available for desert areas. This research develops a new sine cosine dipper throated optimization (SCDTO) technique, targeting DHI prediction even given such data constraints. SCDTO uniquely hybridizes sine cosine metaheuristics, adept at exploration, with dipper throat optimization, providing focused exploitation. This hybridization aims to create a robust ensemble model capable of delivering reliable DHI predictions despite climatic uncertainty. The ensemble model, employing various input combinations, was rigorously evaluated across multiple meteorological stations. The SCDTO algorithm exhibited remarkable performance improvements, yielding substantial reductions exceeding 93% in root mean squared error and 98% in mean absolute error at key stations in Morocco, including Tan-Tan, Zagora, Erfoud, and Oujda. Comparative analyses against established optimization algorithms consistently underscored the superior predictive capabilities of SCDTO. Visualizations, including box plots and histograms, demonstrated SCDTO’s efficacy in minimizing prediction errors, particularly for Tan-Tan, Zagora, and Erfoud stations. Also, statistical validation through one-way analysis of variance (ANOVA) further affirmed the significance of the proposed SCDTO method. Therefore, this hybrid metaheuristic optimization enables more accurate DHI predictions from limited meteorological data. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Solar energy

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Concept for composition of hybrid flying multi-rotor platforms with distributed load and its experimental justification 19

Concept for composition of hybrid flying multi-rotor platfor...

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19th International Conference on Aviation and Cosmonautics, AviaSpace 2020

作者： Chemodanov, V. Gavrilin, K. Klimov, I. Kotelnikova, A. Faculty of Control Systems Computer Science and Power Engineering Moscow Aviation Institute 4 Volokolamskoe highway Moscow125993 Russia

This paper discusses the main approaches to the development and construction of hybrid flying multi-rotor platforms with separation of lift control functions and angular stabilization functions, called by the authors "distributed load". A significant factor that limits flight time for majority of multi-rotor platforms is the energy density limit of lithium polymer batteries, which are most commonly used. To solve this problem we analyzed possible ways to increase flight time: replacing the main type of energy carrier for a more energy-intensive one and use of hybrid systems with combination of popular lithium-polymer batteries and a more energy-intensive energy carrier. The analysis was supported by experimental data. © Published under licence by IOP Publishing Ltd.

关键词： Lithium-ion batteries

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A Review of Gateway Load Balancing Methods in Connecting MANET into Internet 23

A Review of Gateway Load Balancing Methods in Connecting MAN...

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23rd International Conference on Advanced Communication Technology, ICACT 2021

ISBN: (纸本)9791188428069

Interconnection of wired Internet and Mobile Ad hoc Network (MANET), called Integrated Internet-MANET can expand the network coverages and services. In this type of networks, the gateway acts as a bridge between MANET and wired Internet. As all data packets must pass through gateway, which is likely to be congested due to uneven traffic distribution. Thus, gateway load balancing become one of the most important issues in MANET. When the gateway is transmitting a large number of packets, load Balancing is the process of improving the performance of a network through a distribution of load among different gateways. If a gateway is heavily loaded without any load balancing capability, it degrades the performance by causing congestion, delay and resource loss in network. Recently, the key issue of gateway load balancing has been addressed by researchers in various ways, but now there aren't systematic analysis and comparison among different strategies. This paper provides the complete survey on load balancing solutions and proposes a gateway load balancing strategy comparison framework. © 2021 Global IT Research institute (GiRI).

关键词： Mobile ad hoc networks

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Network Traffic Co-Movement Assessment via Oriented Basis Signal Processing and Ensemble Decision Trees 27

Network Traffic Co-Movement Assessment via Oriented Basis Si...

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27th IEEE International Conference on Intelligent Transportation Systems, ITSC 2024

作者： Mohebbi, Mohammad Reza Hassan Zada, Mohammad Javad Rostami-Shahrbabaki, Majid Doller, Mario Yamnenko, Iuliia University of Applied Sciences Josef Ressel Center Vision2Move Project Tirol Kufstein Austria University of Passau Department of Computer Science Germany Technical University of Munich Traffic Engineering and Control Germany National Technical University of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Department of Electronic Devices and Systems Kyiv Ukraine

ISBN: (纸本)9798331505929

Accurate short-term network-wide traffic prediction is essential to guarantee high service quality in urban traffic control systems. Nevertheless, traffic state time series represent network-scale spatiotemporal co-movement patterns and location-specific features. Therefore, hybrid statistical machine learning (ml) algorithms could be utilized to accommodate the aforementioned characteristics. In this paper, a hybrid random forest (rf) and extreme gradient boosting tree (XGBoost) model is introduced for network-wide traffic prediction. Moreover, a multi-noise oriented basis wavelet transform (OBT) filter is employed to pre-process the original time series, and improve the predictive accuracy. The RF model captures the traffic co-movements and the XGBoost extracts the local information. Comparative analysis of the hybrid algorithm and deep learning-based benchmarks indicate better performance of the proposed methodology in hourly traffic state prediction of 30 loop detectors, located in the paris city center. Hence, the hybrid decision-tree-based mechanism is a useful framework for real-time network traffic forecasting offering fewer trainable (hyper-)parameters, and thus, lower computational cost. © 2024 IEEE.

关键词： Time series

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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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A heuristic mixed real-time task allocation of virtual utilization in multi-core processor

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Journal of Information and Intelligence 2023年第2期1卷 156-177页

作者： Hongbiao Liu Mengfei Yang Tingyu Wang Chenghao Song Shenghui Zhu Xi Chen School of Computer Science and Technology Xidian UniversityXi'an 710071China China Academy of Space Technology Beijing 100094China Beijing Institute of Control Engineering Beijing 100190China

Multi-core processor is widely used as the running platform for safety-critical real-time systems such as spacecraft,and various types of real-time tasks are dynamically added at *** order to improve the utilization of multi-core processors and ensure the real-time performance of the system,it is necessary to adopt a reasonable real-time task allocation method,but the existing methods are only for single-core processors or the performance is too low to be *** at the task allocation problem when mixed real-time tasks are dynamically added,we propose a heuristic mixed real-time task allocation algorithm of virtual utilization VU-WF(Virtual Utilization Worst Fit)in multi-core ***,a 4-tuple task model is established to describe the fixedpoint task and the sporadic task in a unified ***,a VDS(Virtual Deferral Server)for serving execution requests of fixed-point task is constructed and a schedulability test of the mixed task set is ***,combined with the analysis of VDS's capacity,VU-WF is proposed,which selects cores in ascending order of virtual utilization for the schedulability *** show that the overall performance of VU-WF is better than available algorithms,not only has a good schedulable ratio and load balancing but also has the lowest runtime *** a 4-core processor,compared with available algorithms of the same schedulability ratio,the load balancing is improved by 73.9%,and the runtime overhead is reduced by 38.3%.In addition,we also develop a visual multi-core mixed task scheduling simulator RT-MCSS(open source)to facilitate the design and verification of multi-core scheduling for *** the high performance,VU-WF can be widely used in resource-constrained and safety-critical real-time systems,such as spacecraft,self-driving cars,industrial robots,etc.

关键词： Mixed real-time task set Multi-core scheduling Task dynamical adding Virtual utilization Scheduling simulator

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Classification of Wind Turbine Defects based on the SqueezeNet Neural Network 19

Classification of Wind Turbine Defects based on the SqueezeN...

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19th IEEE International Conference on computer Science and Information Technologies, CSIT 2024

作者： Dubchak, Lesia Sachenko, Anatoliy Wolff, Carsten Vasylkiv, Nadiia Bernas, Zenovii West Ukrainian National University Department of Computer Engineering Ternopil Ukraine West Ukrainian National University Research Institute for Intelligent Computer Systems Ternopil Ukraine Kazimierz Pulaski University of Technology and Humanities in Radom Department of Tele-Informatics Radom Poland Dortmund University of Applied Science and Arts Dortmund Germany West Ukrainian National University Department of Information Computer Systems and Control Ternopil Ukraine

ISBN: (纸本)9798331542627

The article presents a study on classifying wind turbine defects using the SqueezeNet neural network. Wind turbines are critical for renewable energy, but defects such as corrosion, erosion, and cracks can significantly reduce their efficiency. The study proposes using image classification techniques with neural networks, particularly SqueezeNet, to automate defect detection. The compact nature of SqueezeNet makes it suitable for real-time applications with limited computing resources. Through training and testing, the network achieved an accuracy of 89%, demonstrating its potential to improve wind turbine maintenance and reduce operational costs. © 2024 IEEE.

关键词： defect detection image classification neural network SqueezeNet wind turbine

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