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24th IEEE International Conference on High Performance computing and Communications, 8th IEEE International Conference on Data Science and Systems, 20th IEEE International Conference on Smart City and 8th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Application, HPCC/DSS/SmartCity/DependSys 2022

作者： Wang, Weiqiang Chen, Haiyang Zhang, Xingzhou Zhou, Wei Shi, Weisong Engineering Research Center of Cyberspace Yunnan University Kunming650091 China School of Software Yunnan University Kunming650091 China Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100190 China University of Delaware Department of Computer and Information Sciences NewarkDE19716 United States

ISBN: (纸本)9798350319934

Unmanned aerial vehicle (UAV) system plays an important role in new edge scenarios such as disaster relief, situational awareness, and so on. In order to improve efficiency, computing tasks such as object detection are carried out on the drone-mounted computing unit. However, there is a trade-off between flight altitude and mission accuracy. Higher altitudes result in smaller images, which influence the accuracy. In comparison, shorter altitudes reduce the difficulty of detection while decreasing the recognition range, which affects user experience. Therefore, this paper proposes an airborne altitude adaptive UAV System, Aprus, which selects the most suitable object detection models based on a self-adaptation strategy at different altitudes. The selection strategy is based on a purpose-related evaluation indicator, PEI. It comprehensively considers the model's accuracy, recall, and inference speed at the current altitude according to the user's purpose. Moreover, Aprus sends the original image to a divider instead of scaling the image before pushing it to the model, thus ensuring that the original picture information will not be lost. To evaluate the system, we build a high-resolution UAV dataset with altitude, UDWA, which contains 46037 images. From the experiments, Aprus obtained 58.52% mAP, 94.17%mAP50, 66.17%mAR, 1.61FPS results on DJI Manifold 2G when the purpose is set to Balance mode, and the system can be adjusted by multiple preset purposes or according to the user customs. © 2022 IEEE.

关键词： Edge computing

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Deep-learning assisted Cross-Layer Routing in Multi-hop Wireless Network 7

Deep-learning assisted Cross-Layer Routing in Multi-hop Wire...

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7th IEEE World Forum on Internet of Things, WF-IoT 2021

作者： Regis, Paulo Alexandre Bhunia, Suman Patra, Amar Nath Sengupta, Shamik Southeastern Louisiana University Department of Computer Science HammondLA United States Miami University Department of Computer Science and Software Engineering OxfordOH United States Radford University School of Computing and Information Sciences RadfordVA United States University of Nevada Department of Computer Science and Engineering RenoNV United States

ISBN: (纸本)9781665444316

Wireless ad hoc networks rely on exchanging information among the nodes to find a feasible route between source and destination. Routing protocols require periodically flooding the entire system with the updated state of the network. Routing protocols define the rules and semantics of how this information is spread throughout the network and can be classified into proactive and reactive protocols, both of which eventually sends out control packets to the network. However, with the increase of the scale of the network, the amount of packets exchanged uses resources that could be otherwise used for application messages. In this paper, we explore the use of machine learning techniques to restrict the flooding radius of control packets. We define the problem objective as a regression problem and use neural networks to model it. The model can be used in networks that share similar attributes, suggesting that transfer learning can be used to re-purpose the initial model. The results show that using machine learning reduces the amount of resources used to maintain the network state up to date, which could be subsequently used to improve the overall performance of the networked system. We anticipate machine learning to be the starting point for more sophisticated models of cross-layer routing mechanisms. © 2021 IEEE.

关键词： Routing protocols

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Twitter Sentiment Analysis in Covid-19 Pandemic 12

Twitter Sentiment Analysis in Covid-19 Pandemic

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12th IEEE Annual Information Technology, Electronics and Mobile Communication Conference, IEMCON 2021

作者： Madanian, Samaneh Airehrour, David Samsuri, Nabilah Ahmad Cherrington, Marianne Auckland University of Technology Department of Computer Science and Software Engineering Auckland New Zealand School of Applied Business Unitec Institute of Technology Auckland New Zealand Auckland University of Technology Department of Mathematical Sciences Auckland New Zealand School of Computing and Engineering University of Huddersfield Huddersfield United Kingdom

ISBN: (纸本)9781665400664

We have yet to realise the full capability of social media as an innovative information platform during emergencies and crisis response and management. Sentiment analysis can systematically identify, extract, and scrutinise emotional states and subjective information in social media data. Exploring reactions and perceptions to response messaging is invaluable and proved especially useful for a pandemic response as it can demonstrate general population reaction to the pandemic and governments response actions. This can be further analysed to identify the gap between government response actions and communications and citizens' perceptions. In this paper, an analysis of Twitter data explores population reaction towards COVID-19 health messaging. A Natural Language Processing Python tool is known as TextBlob was used to discover general data sentiment. Data were divided into three sentiments and text extraction of health messages was conducted to explore subsequent tweets in predefined categories. Our findings show the outcome of Tweets analysis could help us to identify the general population concerns and their reactions to COVID-19 to give a better understanding of the situation to governments and support them in implementing appropriate policies. © 2021 IEEE.

关键词： Sentiment analysis

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Video-Based Jump Height Estimation in Athletic Performance Testing

Video-Based Jump Height Estimation in Athletic Performance T...

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Sport, Technology and Research (STAR), IEEE International Workshop on

作者： Ivan Lokas Matea Vasilj Sven Skender Vlatko Vučetić Hrvoje Mihaldinec Hrvoje Dzapo Software development Ultrax Technologies Zagreb Croatia Human Performance Laboratory Faculty of Kinesiology Zagreb Croatia Hardware development Ultrax Technologies Zagreb Croatia Department of Electronic Systems and Information Processing Faculty of Electrical Engineering and Computing Zagreb Croatia

Jump height estimation is well-studied problem in sports science with a variety of methods proposed over the years. This paper introduces a portable, simple-to-setup and a cost-effective video-based jump height estimation method, and compares it with existing traditional methods that use expensive and specialized equipment. To enable more accurate comparison between different systems, a custom-designed Inertial Measurement Unit (IMU) was used as an additional sensor input. The analysis was performed on eleven female physically active handball players. The dataset consists of three most common vertical jump variations: squat jump, counter-movement jump and counter-movement jump with free arms. The analysis show that our video-based approach achieves comparable results to the traditional methods.

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LightOcean: A Lightweight And Efficient Network For Real-time UAV Tracking 19

LightOcean: A Lightweight And Efficient Network For Real-tim...

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2022 IEEE SmartWorld, 19th IEEE International Conference on Ubiquitous Intelligence and computing, 2022 IEEE International Conference on Autonomous and Trusted Vehicles Conference, 22nd IEEE International Conference on Scalable computing and Communications, 2022 IEEE International Conference on Digital Twin, 8th IEEE International Conference on Privacy computing and 2022 IEEE International Conference on Metaverse, SmartWorld/UIC/ATC/ScalCom/DigitalTwin/PriComp/Metaverse 2022

作者： Chen, Haiyang Wang, Weiqiang Zhang, Xingzhou Zhou, Wei Shi, Weisong Yunnan University Engineering Research Center of Cyberspace Kunming650091 China Yunnan University School of Software Kunming650091 China Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100190 China University of Delaware Department of Computer and Information Sciences NewarkDE19716 United States

ISBN: (纸本)9798350346558

Siamese-based trackers have significantly advanced in visual object tracking over the past years. However, most of these trackers emphasize tracking accuracy over efficiency, which limits their real-world deployment on edge platforms with widespread applications such as unmanned aerial vehicles (UAVs). In this paper, we propose LightOcean, a lightweight and efficient aerial tracker. Specifically, we design a dynamic template feature update module and a pixel-level cross-correlation module to improve the robustness and adaptability of the tracker without additional model computation. The former allows the tracker to capture additional space-time information during the tracking process to adapt to the appearance changes of the object. The latter utilizes pixel-level cross-correlation and attention mechanisms to generate similarity maps, improving the accuracy of predicted boundaries. By combining the lightweight and efficient backbone network and the prediction head, LightOcean significantly increases the tracking speed while maintaining accuracy. By running three common UAV benchmarks on Jetson Nano, a typical edge-embedded device, LightOcean presents better performance. The tracking speed is 4x faster than the state-of-the-art tracker, Ocean, while the energy consumption and memory usage are reduced by 80% and 12%. What's more, the accuracy remained stable, and the precision of LightOcean is 78.6%, which is 2.7% higher than Ocean. © 2022 IEEE.

关键词： Antennas

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An innovation analysis of LZ77 and LZ78 Compression Algorithms for Data Compression & Source Coding

An innovation analysis of LZ77 and LZ78 Compression Algorith...

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International Conference on computing and Networking Technology (ICCNT)

作者： Rakesh Kumar Giri Abhinav Mishra Aruna Sri Rongali Laxmi A. Bewoor R Raghavendra M. S. Kavitha Department of Computer Science & Engineering Sunrise University Alwar India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of Information Technology Emphasis/Technology Software Engineer Ph.D University of The Cumberlands US Department of Computer Engineering Vishwakarma Institute of Technology Pune INDIA College of Computing Sciences And Information Technology Jain (deemed to be) University Bangalore Karnataka India Department of ECER. M. K. Engineering College RSM Nagar Kavaraipettai

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

This paper evaluates innovation on two of the most widely used compression algorithms — the LZ77 and the LZ78 algorithms — for information compression and supply coding programs. A detailed assessment of these algorithms presents insights approximately their design philosophy, technical traits, and performance metrics. Additionally, the studies offer a complete overview of their packages and implementations. The paper investigates the prominent considerations for implementing compression algorithms and analyzes their relative blessings and downsides. An exploration of the constraints of every algorithm is likewise undertaken. Furthermore, the research explores distinctive design elements of the algorithms, such as data structure, compression engine, and set of rules optimization. Eventually, the paper assesses the algorithms by reading the exchange-offs between their performance and complexity. This study facilitates practitioners and developers to apprehend the results of using those algorithms for diverse compression and supply coding applications. It can assist practitioners in identifying the first-class compression set of rules for their unique application needs. This paper gives an innovative evaluation of the LZ77 and LZ78 Compression Algorithms. These algorithms are algorithms designed for statistics compression and source coding. They’re used to take a given series of characters (or bits) and encode them right into an area-green representation. The innovation evaluation presents a valuable perception of how the algorithms improve compression ratios and shop area. It also discusses the effect of positive parameters such as window length, repeat cycle, and buffer size on compression efficiency. ultimately, the paper will speak to future studies’ challenges in this region and the capability packages of those algorithms.

关键词： Measurement Technological innovation Image coding Codes Philosophical considerations Source coding Green products Approximation algorithms Compression algorithms Optimization

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Privacy-aware Data Fusion and Prediction for Smart City Services in Edge computing Environment 15

Privacy-aware Data Fusion and Prediction for Smart City Serv...

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2022 IEEE Congress on Cybermatics: 15th IEEE International Conferences on Internet of Things, iThings 2022, 18th IEEE International Conferences on Green computing and Communications, GreenCom 2022, 2022 IEEE International Conference on Cyber, Physical and Social computing, CPSCom 2022 and 8th IEEE International Conference on Smart Data, SmartData 2022

作者： Qi, Lianyong Chi, Xiaoxiao Zhou, Xiaokang Liu, Qi Dai, Fei Xu, Xiaolong Zhang, Xuyun School of Computer Science Qufu Normal University China Faculty of Data Science Shiga University Japan Riken Center for Advanced Intelligence Project Japan School of Computer and Software Nanjing University of Information Science and Technology China School of Big Data and Intelligence Engineering Southwest Forestry University China Department of Computing Macquarie University Australia

ISBN: (数字)9781665454179

ISBN: (纸本)9781665454179

With fast development of Cyber Physical System, the variety and volume of data generated from different edge servers are fairly considerable. Mining and exploiting the data would definitely bring huge advantages. However, there are two major issues exposed in the process. First, utilizing the data with high efficiency is challenging in edge computing environment. Second, data from multiple edge servers often contain sensitive information such as user preferences, which will give rise to privacy breach risks when using the data. Locality-Sensitive Hashing and amplified technology are utilized for dealing with two problems. In this paper, we propose a novel privacy-protection approach named SRchain-LSH in edge computing environment which is based on amplified Locality-Sensitive Hashing technique. In order to verify high accuracy and efficiency of our proposal, large sets of experiments are conducted. According to experimental results, our proposal shows better performance than those of comparative methods in terms of MAE , RMSE and time costs. For our method, the best value of MAE is about 0.41 and time cost is about 0.1 seconds, which are more accurate and efficient than comparative methods. © 2022 IEEE.

关键词： Smart city

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Automatic Video Segmentation Based on Information Centroid and Optimized SaliencyCut

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Journal of Computer Science & Technology 2020年第3期35卷 564-575页

作者： Hui-Si Wu Meng-Shu Liu Lu-Lu Yin Ping Li Zhen-Kun Wen Hon-Cheng Wong College of Computer Science and Software Engineering Shenzhen UniversityShenzhen 518060China Department of Computing The Hong Kong Polytechnic UniversityHong Kong 999077China Faculty of Information Technology Macao University of Science and TechnologyMacao 999078China

We propose an automatic video segmentation method based on an optimized SaliencyCut equipped with information centroid(IC)detection according to level balance principle in physical *** the existing methods,the image information of another dimension is provided by the IC to enhance the video segmentation ***,our IC is implemented based on the information-level balance principle in the image,and denoted as the information pivot by aggregating all the image information to a *** effectively enhance the saliency value of the target object and suppress the background area,we also combine the color and the coordinate information of the image in calculating the local IC and the global IC in the *** saliency maps for all frames in the video are calculated based on the detected *** applying IC smoothing to enhance the optimized saliency detection,we can further correct the unsatisfied saliency maps,where sharp variations of colors or motions may exist in complex ***,we obtain the segmentation results based on IC-based saliency maps and optimized *** method is evaluated on the DAVIS dataset,consisting of different kinds of challenging *** with the state-of-the-art methods are also conducted to evaluate our *** visual results and statistical comparisons demonstrate its advantages and robustness for automatic video segmentation.

关键词： automatic video segmentation information centroid saliency detection optimized SaliencyCut

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Age of Information in Digital Twin Migration

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IEEE Transactions on Vehicular Technology 2025年

作者： Noroozi, Kiana Todd, Terence D. Zhao, Dongmei Karakostas, George McMaster University Department of Electrical and Computer Engineering HamiltonON Canada McMaster University Department of Computing and Software HamiltonON Canada

A Digital Twin (DT) is a virtual representation of a real physical system (PS) that interacts with other objects on its behalf. In these interactions, the Age of Information (AoI) is a key performance measure that is dependent on the DT's current network server placement. To maintain acceptable AoI performance as the system evolves, the DT location may have to be moved, which is referred to as Digital Twin migration. In this paper we consider the problem of DT migration in a vehicular system, focusing on minimizing the time-averaged AoI. In this type of system, it is difficult to maintain acceptable AoI performance due to the speed of the vehicles, which can result in frequent abrupt handoffs between different cellular domains. This makes the question of when to initiate DT migration an important one. The problem is formulated as a Markovian stopping problem and an optimal online algorithm is proposed using dynamic programming and the statistics of vehicular motion. A more computationally intensive adaptive version of this algorithm is also proposed where the dynamic programming tables are recomputed at each time step. A best-in-expectation algorithm is introduced that gives sub-optimal AoI performance but is more computationally efficient than in the optimal version. These algorithms are also compared to heuristics that do immediate migration and migration at handoff. An offline algorithm is formulated that provides a lower bound on the average AoI that is attainable. Performance results show that the proposed algorithm can significantly improve the efficiency of Digital Twin migrations compared to the other approaches while guaranteeing the minimized time-averaged AoI. © 1967-2012 IEEE.

关键词： Dynamic programming

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Weighted Poisson-disk Resampling on Large-Scale Point Clouds 39

Weighted Poisson-disk Resampling on Large-Scale Point Clouds

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Jiao, Xianhe Lv, Chenlei Zhao, Junli Yi, Ran Wen, Yu-Hui Pan, Zhenkuan Wu, Zhongke Liu, Yong-Jin College of Computer Science and Technology Qingdao University China College of Computer Science and Software Engineering Shenzhen University China Department of Computer Science and Engineering Shanghai Jiao Tong University China School of Computer Science & Technology Beijing Jiaotong University China School of Artificial Intelligence Beijing Normal University China Department of Computer Science and Technology MOE-Key Laboratory of Pervasive Computing Tsinghua University China

ISBN: (纸本)157735897X

For large-scale point cloud processing, resampling takes the important role of controlling the point number and density while keeping the geometric consistency. However, current methods cannot balance such different requirements. Particularly with large-scale point clouds, classical methods often struggle with decreased efficiency and accuracy. To address such issues, we propose a weighted Poisson-disk (WPD) resampling method to improve the usability and efficiency for the processing. We first design an initial Poisson resampling with a voxel-based estimation strategy. It is able to estimate a more accurate radius of the Poisson-disk while maintaining high efficiency. Then, we design a weighted tangent smoothing step to further optimize the Voronoi diagram for each point. At the same time, sharp features are detected and kept in the optimized results with isotropic property. Finally, we achieve a resampling copy from the original point cloud with the specified point number, uniform density, and high-quality geometric consistency. Experiments show that our method significantly improves the performance of large-scale point cloud resampling for different applications, and provides a highly practical solution. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Geometry

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