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Decision Making: Applications in Management and engineering 2024年第1期7卷 494-530页

作者： Suanpang, Pannee Jamjuntr, Pitchaya Department of Information Technology Faculty of Science & Technology Suan Dusit University Bangkok Thailand Department of Electrical Engineering Faculty of Engineering King Mongkut's University of Technology Thonburi Bangkok Thailand

This research proposes a decision-making framework in which the Adaptive Multi-Agent Reinforcement Learning (MARL) model and the concept of Vehicle-to-Grid (V2G) interactivity are employed to improve the effective management of smart grids. The research hypothesis introduces innovations for improving the efficiency and security of power systems in the global south, primarily by controlling the net energy transmission between the defined electric vehicles (EVs) and the grid. Other issues that require attention to ensure the proper functioning of smart grids include demand response, load management, and energy storage optimization. In this instance, these gaps are filled by the system’s proposed framework. With the help of MARL, the system dynamics' autonomous learning aspects allow the system to adapt to the capacity of renewable energy sources and electricity demand, which is also time-dependent. Because of the MARL, the autonomous coordination of decision-making has resulted in very positive changes in the system's effectiveness. In particular, this framework permitted an increase of 13.6% in the total energy exchange between EVs and the grid, and the grid stability index improved from 0.84 to 0.87 compared to what would have been achieved with the conventional methods. Enhanced energy management and pricing rehabs added another 22% to net savings. Further, it is stated that deploying MARL-based V2G systems in developing areas has many benefits, including more robust grid reliability and energy security and better integration of renewable energy resources. Such changes aid in reducing fossil fuel use and greenhouse gas emissions. © 2024 Regional Association for Security and crisis management. All rights reserved.

关键词： Vehicle-to-grid

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Multispectral point cloud superpoint segmentation

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Science China(Technological Sciences) 2024年第4期67卷 1270-1281页

作者： WANG QingWang WANG MingYe ZHANG ZiFeng SONG Jian ZENG Kai SHEN Tao GU YanFeng Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming 650500China Yunnan Key Laboratory of Computer Technologies Application Kunming 650500China School of Electronics and Information Engineering Harbin Institute of TechnologyHarbin 150001China

The multitude of airborne point clouds limits the point cloud processing *** are grouped based on similar points,which can effectively alleviate the demand for computing resources and improve processing ***,existing superpoint segmentation methods focus only on local geometric structures,resulting in inconsistent spectral features of points within a *** feature inconsistencies degrade the performance of subsequent ***,this study proposes a novel Superpoint Segmentation method that jointly utilizes spatial Geometric and Spectral information for multispectral point cloud superpoint segmentation(GSI-SS).Specifically,a similarity metric that combines spatial geometry and spectral information is proposed to facilitate the consistency of geometric structures and object attributes within segmented *** the formation of the primary superpoints,an intersuperpoint pointexchange mechanism that maximizes feature consistency within the final superpoints is *** are conducted on two real multispectral point cloud datasets,and the proposed method achieved higher recall,precision,F score,and lower global consistency and feature classification *** experimental results demonstrate the superiority of the proposed GSI-SS over several state-of-the-art methods.

关键词： multispectral point cloud superpoint segmentation over-segmentation spatial-spectral joint metric

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Optimizing Service Scheduling by Genetic Algorithm Support Decision-Making in Smart Tourism Destinations

Decision Making: Applications in Management and Engineering

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Decision Making: Applications in Management and engineering 2024年第1期7卷 624-650页

Smart tourism destinations are characterised by the integration of advanced technologies and devices to ensure visitors enjoy a seamless and environmentally responsible experience. A key challenge for such destinations lies in efficiently managing and delivering services to meet tourists' expectations while upholding sustainability principles and resource management practices. This study aimed to explore the application of genetic algorithms (GAs) in optimising service scheduling, thereby supporting decision-making processes and enhancing tourism destination services. The research employed a service scheduling methodology that directed the algorithm towards maximising efficiency and customer satisfaction, in contrast to traditional organisational scheduling methods. The methodology centred on the implementation of an algorithmic approach in service delivery management, prioritising operational efficiency and improved customer experience over conventional scheduling techniques. Data collected were systematically analysed, resulting in the development of a theoretical framework based on the findings. The results demonstrated that genetic algorithms significantly enhance service scheduling efficiency when used alongside other methods. The findings underscore the pivotal role of GAs in enabling businesses to achieve time and cost savings while improving customer satisfaction. Furthermore, the study highlights GAs' capacity for adaptability, allowing schedules to be adjusted rapidly in response to changing circumstances, thus providing flexibility and responsiveness to variations in demand. Finally, the research identifies opportunities for innovation and diversification in applying GAs for time scheduling within the tourism sector. It also emphasises the importance of integrating real-time information into scheduling systems to improve service provision at tourist sites. This approach not only enhances the competitiveness of tourism destinations but also adds substantia

关键词： Leisure

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Quasi-static and dynamic compressive behaviour of additively manufactured Menger fractal cube structures

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Defence technology（防务技术） 2024年第7期37卷 39-49页

作者： Damith Mohotti Dakshitha Weerasinghe Madhusha Bogahawaththa Hongxu Wang Kasun Wijesooriya Paul JHazell School of Engineering and Technology UNSWCanberraACT2600Australia School of Civil Mining and Environmental EngineeringFaculty of Engineering and Information SciencesUniversity of WollongongWollongongNSWAustralia

This paper presents the first-ever investigation of Menger fractal cubes'quasi-static compression and impact *** cubes with different void ratios were 3D printed using polylactic acid(PLA)with dimensions of 40 mm×40 mm×40 *** different orders of Menger cubes with different void ratios were considered,namely M1 with a void ratio of 0.26,M2 with a void ratio of 0.45,and M3with a void ratio of ***-static Compression tests were conducted using a universal testing machine,while the drop hammer was used to observe the behaviour under impact *** fracture mechanism,energy efficiency and force-time histories were *** the structured nature of the void formation and predictability of the failure modes,the Menger geometry showed some promise compared to other alternatives,such as foams and *** the increasing void ratio,the Menger geometries show force-displacement behaviour similar to hyper-elastic materials such as rubber and *** third-order Menger cubes showed the highest energy absorption efficiency compared to the other two geometries in this *** findings of the present work reveal the possibility of using additively manufactured Menger geometries as an energy-efficient system capable of reducing the transmitting force in applications such as crash barriers.

关键词： Additive manufacturing Fractal geometries Menger cube Energy absorption Quasi-static

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A Priority-Based Hierarchical Framework for k-Robust Multi-Agent Path Finding

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年第9期9卷 5631-5641页

作者： Zhang, Kaixiang Mao, Jianlin Zhang, Shufan Wang, Ning Kunming University of Science and Technology Faculty of Mechanical and Electrical Engineering Kunming650500 China Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming650500 China

Multi-agent path finding is one of the key problems in the topic of multi-agent system. While some inevitable execution delays resulting from the realistic factors, such as robot faults or avoiding human etc., may make the path plan invalid. Our aim is to effectively find paths with robustness to k-delays for all agents, i.e., each agent can get a k-step margin in its paths without breaking the whole plan, especially for the large-scale systems. We propose a priority-based hierarchical framework for k-robust multi-agent path finding, where the pattern of searching path while avoiding conflict is profit to reduce the burden of conflict handling in k-robust planning. Then, the classification and generation rules of robust constraints are designed to guarantee global k-robustness of prioritized planning. Finally, for the new challenge of k-robust starting predicament, a multi-level key-agent guided priority adjustment mechanism is proposed to improve solution success rate. Experimental results show that the proposed algorithm can effectively reduce the runtime, and averagely maintain a success rate of over 95%. Especially for large-scale problems with hundreds of agents, the runtime can be reduced to a few seconds. In addition, the runtime does not increase dramatically as the k-value grows from 0 to 7. © 2016 IEEE.

关键词： Motion planning

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A review of tracking concept drift detection in machine learning 4th

A review of tracking concept drift detection in machine lear...

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4th Annual International Conference on Data Science, Machine Learning and Blockchain technology, AICDMB 2023

作者： Abdu, Nail Adeeb Ali Basulaim, Khaled Omer Information Technology Department Faculty of Engineering & Computing University of Science and Technology Aden Yemen Information Technology Engineering Department Faculty of Engineering University of Aden

ISBN: (纸本)9781032426853

The availability of time series streaming data has increased dramatically in recent years. Since the last decade, there has been a growing interest in learning from realtime data. While extracting significant information from data streams, online learning faces changes in data distribution. Concept drift refers to hidden data contexts that learning systems are unaware of it. Using previous training instances from the data stream, the classifier categorizes new instances. Hence in this regard, it is obvious to have considerable methods to discover the similarity or diversity status of the present streaming data that compared to the buffered data. This issue is defined and explored in contemporary literature as concept drift. This paper was initiated to identify the constraints of the contemporary methods devised to handle the concept drift in data streams in relation to supervised learning, we also review and categories the concept drift detectors with their key points. Eventually, the article presented observations can provide decision boundary detection at improved levels and discussing open research challenges and possible new research direction. © 2024 The Author(s).

关键词： Machine learning

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Tuning the growth of intermetallic compounds at Sn-0.7Cu solder/Cu substrate interface by adding small amounts of indium

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Journal of Materials Science & technology 2024年第15期182卷 246-259页

作者： Ancang Yang Yaoping Lu Yonghua Duan Mengnie Li Shanju Zheng Mingjun Peng Faculty of Material Science and Engineering Kunming University of Science and TechnologyKunming 650093China College of Physics and Information Engineering Fuzhou UniversityFuzhou 350108China

The void defect in intermetallic compounds(IMCs)layer at the joints caused by inhomogeneous atomic diffusion is one of the most important factors limiting the further development of Sn-based *** this work,the thermodynamic stability of IMCs(high-temperatureη-Cu_(6)Sn_(5)and o-Cu_(3)Sn phases)was improved by adding small amounts of indium(In),and the IMCs layers with moderate thickness,low defect concentrations and stable interface bonding were successfully *** formation order of compounds and the interfacial orientation relationships in IMCs layers,the atomic diffusion mechanism,and the growth tuning mechanism of In onη-Cu_(6)Sn_(5)and Cu_(3)Sn,after In adding,were discussed com-prehensively by combining calculations and *** is the first time that the classic heteroge-neous nucleation theory and CALPHAD data were used to obtain the critical nucleus radius ofη-Cu_(6)Sn_(5)and Cu_(3)Sn,and to explain in detail the main factors affecting the formation order and location of IMCs at joints during the welding process.A novel and systematic growth model about IMCs layers in the case of doping with alloying elements was *** growth tuning mechanism of In doping onη-Cu_(6)Sn_(5)and Cu_(3)Sn was further clarified based on the proposed model using first-principles *** growth model used in this study can provide insights into the development and design of multiele-ment Sn-based solders.

关键词： Sn-0.7Cu solder IMCs Aging Atomic migration barrier Growth tuning

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SELECTED APPLICATIONS OF SATELLITE TECHNOLOGIES IN RAIL TRANSPORT

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Archives of Transport 2024年第3期71卷 91-105页

作者： Chrzan, Marcin Ciszewski, Tomasz Nowakowski, Waldemar Faculty of Transport Electrical Engineering and Information Technology Kazimierz Pulaski University in Radom Radom Poland

Global Navigation Satellite Systems (GNSS) are increasingly being used in various modes of transport, including rail transport. When this technology is applied to railway traffic control, it is essential to ensure a high level of safety and reliability. The approval of a railway traffic control system requires a safety analysis, which includes hazard analysis and risk analysis. This also includes GNSS-based solutions in terms of their compliance with safety integrity require-ments, i.e. THR (Tolerable Hazard Rate) and SIL (Safety Integrity Level) parameters, as defined in normative docu-ments. In the case of railway traffic control systems, the level of dependability of the determined train position, referred to as position integrity, is very important in ensuring safety. Position integrity is affected by many factors, including: errors due to SIS (Signal-In-Space) propagation, multipath errors, signal interference or GNSS receiver errors. In order to improve position integrity, among other things, new data processing methods can be used to improve the accuracy and reliability of measurements. The paper presents the concept of satellite signal processing for precise determination of the position of objects in selected railway systems. The Kalman filter based model of satellite signal filtration and its selected applications, which were tested in the real condition, was presented. The application of Kalman filtration indicated in the paper is a universal method that improves the estimated measurement parameters and can be used in many applications of satellite systems for railway tasks. The applicability of satellite systems to automatic train operation, defect positioning in automatic and manual flaw detection tests, determining track spatial orientation and train integrity control have been considered. The conducted tests confirmed the correctness of the adopted concept and the model of satellite signals filtration developed for this purpose. According to the autho

关键词： Kalman filters

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Cumulative histogram as a feature selection technique for anomaly detection

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Multimedia Tools and Applications 2025年第12期84卷 10095-10107页

作者： Nassar, Mostafa Salama, Rania A. Saleeb, Adel A. El-bahnasawy, Nirmeen A. Ahmed, Hossam Eldin H. Abd El-Samie, Fathi E. Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Department of Information Technology Faculty of Computers and Information Suez University Suez Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University Riyadh11671 Saudi Arabia

The enhancement of Intrusion Detection Systems (IDS) is required to ensure protection of network resources and services. This is a hot research topic, especially in the presence of advanced intrusions and attacks. This paper provides a comparison between Distributed Cumulative Histogram (DCH) as a Feature Selection (FS) technique, information Gain Ratio (IGR) FS and wrapper-based FS in terms of accuracy and Root Mean Square Error (RMSE). The utilization of DCH of the traffic instances in normal and attack cases allows us to compare the traffic charts. We can observe the difference between effective features and less effective ones. We verify the feasibility of using DCH as an FS technique in the field of anomaly detection with just six selected features giving more accurate results with most classifiers compared to the IGR and wrapper-based FS. We applied our experiments on the modern UNSW dataset with the WEKA simulation platform that contains a group of classification, feature reduction and selection techniques. © The Author(s) 2024.

关键词： Anomaly detection

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An optical electric field sensor using two cascaded LiNbO3 crystals with improved sensitivity

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IEEE Sensors Journal 2025年第12期25卷 21377-21385页

作者： Zhang, Jiahong Liu, Baoyong Liu, Xiaoming Li, Yingna Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming China Chengdu Technological University of China Chengdu China School of Information Engineering and Automation Kunming University of Science and technology China

Based on the Pockels effect of lithium niobate LiNbO3 crystals, a high-sensitivity electric field sensor utilizing a dual-crystal configuration of LiNbO3 was designed and fabricated. The sensor internally cascades a LiNbO3 crystal with light propagation along the x-axis and an electric field applied along the z-axis, and another crystal with light propagation along the x-axis and an electric field applied along the y-axis. By utilizing the large electro-optic coefficient γ33 of LiNbO3 along the z-axis, the sensor's sensitivity is significantly enhanced. Consequently, under the condition of identical crystal length, this sensor exhibits higher sensitivity compared to current electric field sensor that employ light propagation along the z-axis. Experimental results indicate that the sensor can accurately measure the time-domain waveforms of electromagnetic pulse (EMP) with rise time on the microsecond and nanosecond scales without distortion. The sensitivity of the sensor is 1.40 mV/(kVm-1), with the minimum and maximum measurable time-domain EMP being 3.6 kV/m and 320.1 kV/m, respectively. When the span of the spectrum analyzer is set to 10 kHz and the resolution bandwidth (RBW) is 10 kHz, the minimum detectable electric field is 2.2 V/m, corresponding to a linear dynamic range of 103.30 dB. Furthermore, from 5 °C to 40 °C, the static output optical power of the sensor fluctuates within ±0.28 dB. © 2001-2012 IEEE.

关键词： Spectrum analyzers

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