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Information Communication Technologies Conference (ICTC)

作者： Xiaoping Yang Xige Zhang Shaoling Liang Dongyang Wang Zihao Wang Zhaoming Hu Chao Fang Faculty of Information Technology Beijing University of Technology Beijing P.R. China Guangxi Key Laboratory of Digital Infrastructure Nanning P.R. China Beijing Institute of Astronautical Systems Engineering Beijing P.R. China

ISBN: (数字)9798350373523

ISBN: (纸本)9798350373530

To satisfy the differentiated service requirements of delay-sensitive and computing-intensive tasks in unmanned aerial vehicle (UAV) networks, it is urgent to efficiently allocate limited network resources to improve network performance. In this paper, we propose an intelligent task offloading scheme to optimize resource allocation in UAV networks with content caching. Specifically, we formulate the joint optimization of task offloading and resource allocation as a latency minimization model for the caching-assisted UAV system. Then, a new deep reinforcement learning (DRL) algorithm is designed to make offloading and resource allocation decisions based on current network state information, significantly improving resource utilization. Numerical results indicate that the model significantly reduces network latency in comparison to its existing benchmarks in caching-assisted UAV networks.

关键词： Benchmark testing Autonomous aerial vehicles Minimization Deep reinforcement learning Communications technology Numerical models Resource management

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Comparative analysis of preprocessing methods and machine learning models for geographical origin identification in an imbalanced Panax notoginseng dataset with near-infrared spectroscopy

Comparative analysis of preprocessing methods and machine le...

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2024 International Conference on Artificial Intelligence and Machine Learning Research, CAIMLR 2024

作者： Cheng, Xuefeng Buhari, Abudhahir Zhu, Hongmei Cheng, Changyin Liu, Juan Faculty of Engineering Science & Technology Infrastructure University Kuala Lumpur Kajang Malaysia School of Big Data and Information Industry Chongqing City Management College Chongqing China School of Artificial Intelligence Chongqing University of Education Chongqing China Chongqing University Chongqing China Chongqing Institute of Green and Intelligent Technology Chinese Academy of Sciences Chongqing College University of Chinese Academy of Sciences Chongqing China

ISBN: (纸本)9781510691797

Imbalanced sample distributions pose challenges in accurately identifying the geographical origin of Panax notoginseng (P. Notoginseng), impacting machine learning model performance. This study investigates the efficacy of various data preprocessing methods and machine learning models on geographical origin classification accuracy using near-infrared spectroscopy (NIRS) in imbalanced datasets. Results demonstrate that specific combinations of preprocessing methods and models can significantly improve classification accuracy, bridging the gap between imbalanced and balanced datasets. These findings highlight the importance of tailored approaches to mitigate model and evaluation bias, imbalanced sample weights, and decision boundary shifts in P. Notoginseng datasets. Moreover, the insights gleaned from this study have implications for similar analyses in other traditional Chinese medicinal materials. © 2025 SPIE.

关键词： Near infrared spectroscopy

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Block Chain technology Implementations for Secured Financial Transactions using Cloud Environment 1

Block Chain Technology Implementations for Secured Financial...

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1st IEEE International Interdisciplinary Humanitarian Conference for Sustainability, IIHC 2022

作者： Lakshmi, T Vara Raja, Naveen S.M Ramadass, Sudhir Narayanan, Sreekumar Sreenivas, Velagapudi Subramanian, Balambigai Institute of Aeronautical Engineering Department of MBA Hyderabad India Department of Computer Science and Engineering Chilukuru village R R Dist Telangana Moinabad India Sterck Systems Chennai India Botho University Faculty of Engineering and Technology Network Infrastructure and Management Department Gaborone Botswana Dhanekula Institute of Engineering and Technology Department of Computer Science and Engineering Vijajayawada Krishna dt A.P Ganguru India Kongu Engineering College Department of ECE Perundurai638060 India

ISBN: (纸本)9781665456876

The advancement of technology has an influence on consumers' decision to switch from executing your financial information in a conventional way to doing so online. Contracts are encouraged by the use of cloud computers or its key feature of accessibility from everywhere. The enormous amount of data handled by the cloud platform used to facilitate money transfers necessitates maintaining a high degree of security for all those important passwords stored there. Although the conventional authentication methods continue to work well in protecting data in cloud, more sophisticated cyber attacks against cloud-based storage of information still exist. Additionally, using typical cryptographic primitives to secure cloud data requires a significant amount of operation time due to the need to execute verification checks for both valid and illegitimate access control. © 2022 IEEE.

关键词： Authentication

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A Review of Multi-Agent Path Finding Algorithms

A Review of Multi-Agent Path Finding Algorithms

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Information Systems and Computing technology (ISCTech), International Conference on

作者： Mengdie Wu Wenyao Yan Haslin Hasan Robiatul A’Dawiah Jamaluddin School of Data Science and Engineering Xi'an Innovation College of Yan'an University Xi’an Chian Faculty of Creative Media And Innovative Technology Infrastructure University Kuala Lumpur De Centrum City Malaysia Faculty of Business Information and Human Sciences Infrastructure University Kuala Lumpur De Centrum City Malaysia

In the context of Industry 4.0, Autonomous Guided Vehicles (AGVs) and other types of Multi-Agent System (MAS) have been widely used in large-scale warehouses and unmanned factories. Coordination of AGVs in shared space is drawing increasing attention of researchers, especially in the field of Multi-Agent Path Finding (MAPF). The MAPF problem has been studied a lot, and there are many kinds of solutions. Not all kinds of MAPF solvers can be applied in the field of AGV. Few literature focused on which MAPF solutions are suitable for AGV navigation. This review categorized existing MAPF algorithms into five branches, Conflict-Based Search (CBS) algorithms, Rule-Based algorithms, Priority-Based algorithms, Numerical Optimization-based algorithms and Learning-based algorithms. Furthermore, we evaluate these algorithms in terms of their optimality, lifelong property, scalability and computational cost. Finally, we analyzed which MAPF solvers are suitable for AGV navigation.

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Green Task Offloading in Computing STAR-RIS-Aided Wireless Networks

Green Task Offloading in Computing STAR-RIS-Aided Wireless N...

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IEEE Conference on Wireless Communications and Networking

作者： Chao Fang Hang Xu Tianyi Zhang Jining Chen Zhuwei Wang Qingqing Wu Faculty of Information Technology Beijing University of Technology Beijing P.R. China Purple Mountain Laboratories Nanjing P.R. China Guangxi Key Laboratory of Digital Infrastructure Nanning China The Faculty of Information Technology Beijing University of Technology Beijing P.R. China The School of Electronic and Information Engineerin Beihang University Beijing China The Guangxi Key Laboratory of Digital Infrastructure Nanning China The Department of Electronic Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350303582

ISBN: (纸本)9798350303599

A new concept of center processing unit (CPU)-integrated simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) is proposed, namely computing STAR-RIS. Computation-intensive and delay-sensitive tasks from mobile users can be partially processed at the computing STAR-RIS. We aim to minimize the energy consumption of users and the computing STAR-RIS, and formulate a joint task offloading and transmission resource allocation problem. The solution of this problem is affected by the offloading decision and the amplitude and phase-shift of the computing STAR-RIS. To solve the non-convex problem, we decompose it into two subproblems: 1) For the task offloading subproblem, the offloading decision is optimized utilizing the Karush-Kuhn- Tucker (KKT) conditions; and 2) For the transmission resource allocation subproblem, the transmission-reflection coefficient matrix are optimized via successive convex approximation (SCA). Simulation results show that our proposed algorithm can converge faster and have lower energy consumption than the conventional STAR-RIS.

关键词： Energy consumption Wireless networks Simulation Reconfigurable intelligent surfaces Minimization Approximation algorithms Reflection

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Effect of Environment Temperature and Relative Humidity on Thermal Emissivity: Study Case of Mango Fruit

Effect of Environment Temperature and Relative Humidity on T...

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International Symposium on Intelligent Systems and Informatics (SISY)

作者： Panmanas Sirisomboon Jiraporn Sripinyowanich Jongyingcharoen Apiwat Junto Thitima Phanomsophon Cheewanun Dachoupakan Sirisomboon Panan Rerngsamran Dharma Raj Pokhrel Sneha Sharma Jetsada Posom Pimpen Pornchaloempong Anupun Terdwongwarakul Prabhas Chongstitvatana Department of Agricultural Engineering School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Department of Agricultural Engineering School of Engineering and Innovation Rajamangala University of Technology Tawan-Ok Chon Buri Thailand Office of Administrative Interdisciplinary Program on Agricultural Technology School of Agricultural Technology King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Department of Microbiology Faculty of Science Chulalongkorn University Bangkok Thailand Department of Infrastructure Engineering University of Melbourne Victoria Australia Department of Agricultural Engineering Faculty of Engineering Khon Kaen University Khon Kaen Thailand Department of Food Engineering School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Department of Agricultural Engineering Faculty of Engineering at Kanpangsan Kasetsart University Thailand Department of Computer Engineering Chulalongkorn University Bangkok Thailand

ISBN: (数字)9798350385601

ISBN: (纸本)9798350385618

This research was to study the effect of the environment condition during image captured including temperature and relative humidity in the packaging house of the mango exporting factory and in the orchard on the emissivity of mango fruit. The result showed that in the controlled environment of the packaging house in factory, the emissivity was increased (the mango emitted more energy) when the surface temperature was lower and the emissivity of mango is 0.71-0.84 and in the uncontrolled environment of open-air packaging yard in the mango orchard, the different transpiration rates of mango effected mainly by ambient temperature and relative humidity make the morning condition emissivity of 0.44-0.66 and the afternoon condition of 0.72-0.98. There was the effect of the different measured positions on the fruits where the physiology was different and the fluctuated environment in the latter condition made the wide range of emissivity of mangoes. This indicated the shortcoming of thermal imaging of horticultural product if the correct emissivity varied and difficult to set in the thermal camera setting, hence the inaccurate thermogram to be obtained.

关键词： Temperature measurement Transpiration Temperature Humidity Packaging Position measurement Cameras Production facilities Physiology Temperature control

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Preserving Historical Significance: HBIM Implementation for The East Hall of Bandung Institute of technology

Preserving Historical Significance: HBIM Implementation for ...

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IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing technology (AGERS)

作者： Lea Kristi Agustina Agung Budi Harto Deni Suwardhi Ketut Wikantika Iwan Purnama Marcellino Sandro Mahardika Department of Geodesy and Geomatics Engineering Faculty of Earth Science and Technology Institut Teknologi Bandung Bandung Indonesia Department of Geomatics Engineering Faculty of Infrastructure and Regional Technology Institut Teknologi Sumatera Bandung Indonesia Departement of Architecture Sekolah Tinggi Teknologi Cirebon Cirebon Indonesia Faculty of Arts and Design Institut Teknologi Bandung Bandung Indonesia

This research proposes and implements the HBIM model for the ITB East Hall. The HBIM approach combines BIM principles with the unique needs associated with preserving historic buildings. Through detailed mapping and modeling of the building, architectural elements, and building characteristics, HBIM enabled the creation of an accurate and rich digital representation of the physical condition and history of the East Hall. The research methodology involves 3D scanning mapping using the latest laser scanning technology to obtain precise geometric data. The data is then integrated into a BIM software environment, where a three-dimensional building model is generated. Additional information, such as historical changes, materials, and historical construction methods, is also integrated into the HBIM model. This research results in an HBIM model that provides a holistic and accurate digital representation of the ITB East Hall. These models can serve as an important source of information for building preservation, maintenance, and management purposes. HBIM models can also be a valuable educational tool, allowing users to interactively explore the history and architectural complexity of buildings. By applying the HBIM approach to the ITB East Hall, this research provides a real example of how BIM technology can be adapted to preserve cultural heritage buildings. This opens opportunities for similar applications in other cultural heritage buildings, bridging the gap between modern technology and valuable cultural heritage.

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Tracing the transition of Insulating Oil application in Transformers

Tracing the transition of Insulating Oil application in Tran...

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IEEE Students' Conference on Electrical, Electronics and Computer Science (SCEECS)

作者： Raymon Antony Raj Sampath Kumar Venkatachary Sheik Sidthik A Sarathkumar D Leo John Baptist Andrews Annamalai A Sivadasan J Rajeshkanna R Department of Electrical and Electronics Engineering Kongu Engineering College Tamil Nadu India Grant Thornton Gaborone Botswana Department of EEE VSB College of Engineering & Technical Campus Coimbatore Tamil Nadu India Department of Information Technology Faculty of Engineering and Technology Botho University Gaborone Botswana Department of Network and Infrastructure Management Faculty of Engineering and Technology Botho University Gaborone Botswana Department of ECE PSR Engineering College Sivakasi Tamil Nadu India Department of EEE Thamirabarani Engineering College Tirunelveli Tamil Nadu India

This study undertakes a comprehensive investigation to explore strategies for replacing current dielectric liquid understanding in transformers. Understanding existing literature fosters creativity and effective research responses. The review process incorporates data and text analysis. Statistical data from 1978 to 2022 is used to understand prevailing techniques, drawn from an analysis of 80+ research publications. Contributions include Ageing 34 %, blending 20 %, additive addition 17 %, modification 8 %, gas analysis 5 %, critical dielectric testing 5 %, case studies 2 %, and others 8 %. The discussion includes 16 exclusive review papers, highlighting contributions to mixed dielectrics, nanofluids, testing manuals, modifications, and alternative fluids. This advanced study integrates materials, techniques, and standards to explore dielectric liquids, supported by accessible research journal data. The paper provides crucial data for future research.

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Detection and Tracking of Floating Objects Based on Spatial-Temporal Information Fusion

SSRN

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SSRN 2022年

作者： Chen, Renfei Wu, Jian Peng, Yong Yue, Tingxiu Faculty of Infrastructure Engineering Dalian University of Technology Dalian116024 China Artificial Intelligence Institute Dalian University of Technology Dalian116000 China

Floating items on the water surface seriously damage the river landscapes and ecosystems. Implementing visual supervision through cameras to improve the appearance of rivers and lakes has become an essential technical means. However, the detection and tracking of floating objects is still a challenging issue because the river environment is complex and diverse, with many noise problems such as water wave disturbance, dynamic light and shadow, and strong light reflection. In this paper, we propose a floating target detection and tracking method based on deep learning. We improve the network architecture of the Single Shot Multibox Detector (SSD), called SSD-FT, by enhancing the high-resolution layers. In addition, to cope with changes in the target scale of floating objects, we also improve the Kernel Correlation Filter (KCF) by using a pyramidal scale strategy to achieve scale adaptive adjustment based on temporal correlation and motion information. More significantly, a spatial-temporal information fusion strategy is applied to complement detection information with tracking information based on feature comparison. We have evaluated our method over a dataset with 16527 frames of image. The results show that our method has better performance than traditional methods in complex scenes, and achieves an average detection and tracking accuracy of more than 92% with an average running speed of 15.02 FPS, which prove that our method can well complete the detection and tracking task of floating objects. © 2022, The Authors. All rights reserved.

关键词： Object detection

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A Survey of Distance-Based Vessel Trajectory Clustering: Data Pre-processing, Methodologies, Applications, and Experimental Evaluation

arXiv

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arXiv 2024年

作者： Liang, Maohan Liu, Ryan Wen Gao, Ruobin Xiao, Zhe Zhang, Xiaocai Wang, Hua The Department of Civil and Environmental Engineering National University of Singapore Singapore The Hubei Key Laboratory of Inland Shipping Technology School of Navigation Wuhan University of Technology Wuhan China The School of Civil and Environmental Engineering Nanyang Technological University Singapore Institute of High Performance Computing A*STAR Singapore The Department of Infrastructure Engineering Faculty of Engineering and Information Technology University of Melbourne VIC Australia The School of Automotive and Transportation Engineering Hefei University of Technology Hefei China

Vessel trajectory clustering, a crucial component of the maritime intelligent transportation systems, provides valuable insights for applications such as anomaly detection and trajectory prediction. This paper presents a comprehensive survey of the most prevalent distance-based vessel trajectory clustering methods, which encompass two main steps: trajectory similarity measurement and clustering. Initially, we conducted a thorough literature review using relevant keywords to gather and summarize pertinent research papers and datasets. Then, this paper discussed the principal methods of data pre-processing that prepare data for further analysis. The survey progresses to detail the leading algorithms for measuring vessel trajectory similarity and the main clustering techniques used in the field today. Furthermore, the various applications of trajectory clustering within the maritime context are explored. Finally, the paper evaluates the effectiveness of different algorithm combinations and pre-processing methods through experimental analysis, focusing on their impact on the performance of distance-based trajectory clustering algorithms. The experimental results demonstrate the effectiveness of various trajectory clustering algorithms and notably highlight the significant improvements that trajectory compression techniques contribute to the efficiency and accuracy of trajectory clustering. This comprehensive approach ensures a deep understanding of current capabilities and future directions in vessel trajectory clustering. © 2024, CC BY.

关键词： Clustering algorithms

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