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arXiv 2023年

作者： Papa, Lorenzo Russo, Paolo Amerini, Irene Zhou, Luping The Department of Computer Control and Management Engineering Sapienza University of Rome 00185 Italy The School of Electrical and Information Engineering Faculty of Engineering The University of Sydney NSW2006 Australia

Vision Transformer (ViT) architectures are becoming increasingly popular and widely employed to tackle computer vision applications. Their main feature is the capacity to extract global information through the self-attention mechanism, outperforming earlier convolutional neural networks. However, ViT deployment and performance have grown steadily with their size, number of trainable parameters, and operations. Furthermore, self-attention's computational and memory cost quadratically increases with the image resolution. Generally speaking, it is challenging to employ these architectures in real-world applications due to many hardware and environmental restrictions, such as processing and computational capabilities. Therefore, this survey investigates the most efficient methodologies to ensure sub-optimal estimation performances. More in detail, four efficient categories will be analyzed: compact architecture, pruning, knowledge distillation, and quantization strategies. Moreover, a new metric called Efficient Error Rate has been introduced in order to normalize and compare models' features that affect hardware devices at inference time, such as the number of parameters, bits, FLOPs, and model size. Summarizing, this paper firstly mathematically defines the strategies used to make Vision Transformer efficient, describes and discusses state-of-the-art methodologies, and analyzes their performances over different application scenarios. Toward the end of this paper, we also discuss open challenges and promising research directions. © 2023, CC BY.

关键词： computer vision

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Probabilistic Tube-based control Synthesis of Stochastic Multi-Agent Systems under Signal Temporal Logic

Probabilistic Tube-based Control Synthesis of Stochastic Mul...

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IEEE Conference on Decision and control

作者： Eleftherios E. Vlahakis Lars Lindemann Pantelis Sopasakis Dimos V. Dimarogonas Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Computer Science Viterbi School of Engineering University of Southern California Los Angeles CA USA School of Electronics Electrical Engineering and Computer Science Queen’s University Belfast Northern Ireland UK

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

We consider the control design of stochastic discrete-time linear multi-agent systems (MASs) under a global signal temporal logic (STL) specification to be satisfied at a predefined probability. By decomposing the dynamics into deterministic and error components, we construct a probabilistic reachable tube (PRT) as the Cartesian product of reachable sets of the individual error systems driven by disturbances lying in confidence regions (CRs) with a fixed probability. By bounding the PRT probability with the specification probability, we tighten all state constraints induced by the STL specification by solving tractable optimization problems over segments of the PRT, and relax the underlying stochastic problem with a deterministic one. This approach reduces conservatism compared to tightening guided by the STL structure. Additionally, we propose a recursively feasible algorithm to attack the resulting problem by decomposing it into agent-level subproblems, which are solved iteratively according to a scheduling policy. We demonstrate our method on a ten-agent system, where existing approaches are impractical.

关键词： control design Scalability Linearity Probabilistic logic Scheduling Optimization Multi-agent systems

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Energy-Aware Task Allocation for Teams of Multi-mode Robots

arXiv

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arXiv 2025年

作者： Ito, Takumi Funada, Riku Sampei, Mitsuji Notomista, Gennaro Department of Systems and Control Engineering Institute of Science Tokyo Tokyo152-8550 Japan Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada

This work proposes a novel multi-robot task allocation framework for robots that can switch between multiple modes, e.g., flying, driving, or walking. We first provide a method to encode the multi-mode property of robots as a graph, where the mode of each robot is represented by a node. Next, we formulate a constrained optimization problem to decide both the task to be allocated to each robot as well as the mode in which the latter should execute the task. The robot modes are optimized based on the state of the robot and the environment, as well as the energy required to execute the allocated task. Moreover, the proposed framework is able to encompass kinematic and dynamic models of robots alike. Furthermore, we provide sufficient conditions for the convergence of task execution and allocation for both robot models. Copyright © 2025, The Authors. All rights reserved.

关键词： Constrained optimization

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Cooperative control Strategy for Virtual Inertia Based on Fuzzy control 8

Cooperative Control Strategy for Virtual Inertia Based on Fu...

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8th International Conference on control Science and Systems engineering, ICCSSE 2022

作者： Gao, Zhimin Cao, Yongji Zhang, Hengxu Qin, Hao Zhang, Xiaoning Li, Changgang Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education Shandong University Jinan China Technical University of Denmark Department of Electrical Engineering Kgs. Lyngby Denmark School of Control and Computer Engineering North China Electric Power University Beijing China

ISBN: (纸本)9781665484138

The large-scale integration of renewable energies brings about low inertia characteristics to the power system, and the frequency security faces greater challenges. The existing inertia research lacks the synergy between different types of inertia sources and different control methods, and the inertia response capability of power system still can be improved. In this paper, with the aim of proposing a virtual inertia cooperative control strategy for the power system with high penetration of renewable energies, we analyze the virtual inertia mechanisms of wind power, PV units and energy storage system (ESS), and propose control methods for wind power and PV units to participate in inertia response. Considering the reason of limited inertia response capability of renewable energy units, the fuzzy control is used to make the ESS participate in inertia compensation to improve the frequency response capability. Finally, case study is carried out to verified the effectiveness of the proposed control strategy. © 2022 IEEE.

关键词： Fuzzy control

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Vr-Hmt: Virtual Reality-Driven Human Motion Tracking System via Mask Rcnn for Real-Time Monitoring

Vr-Hmt: Virtual Reality-Driven Human Motion Tracking System ...

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Advancement in Computation & computer Technologies (InCACCT), International Conference on

作者： Kannan R Suguna T Sivasubramanian R Bhuvanesh A Vemulapalli Sri Lakshmi Harshitha Kulwant Singh Chellam S Ahilan Appathurai Department of Electrical and Electronics Engineering Nehru Institute of Engineering and Technology Coimbatore India Department of Information Technology Government College of Technology Coimbatore Tamil Nadu India Department of AIML Malla Reddy University Dulapally Hyderabad India Department of Electrical and Electronics Engineering PSN College of Engineering and Technology Tirunelveli India Department of BE Computer Science and Design Rmk Engineering College (An Autonomous College) Kavaraipettai Tamil Nadu India Yadavindra Department of Engineering Electronics And Communication Engineering Punjabi University Guru Kashi Campus Department of Electrical and Electronics Engineering Velammal College of Engineering and Technology Madurai Tamil Nadu India Department of Electronics and Communication Engineering PSN College of Engineering and Technology Tirunelveli Tamilnadu India

ISBN: (数字)9798331543891

ISBN: (纸本)9798331543907

Human motion tracking (HMT) is capturing and analyzing the movement of individuals and objects, focusing on their location, speed, and acceleration. It is used in various fields including filmmaking, animation, sports analysis, robotics, and augmented reality. Unauthorized physical access to facilities presents significant challenges for organizations as it can result in theft, sabotage, and data breaches, these incidents lead to financial losses, and compromised sensitive information. To overcome these challenges, a novel virtual reality (VR) based XXX system has been proposed for tracking human motion to identify any suspicious activity within an organization. The system uses various sensors such as cameras and motion sensors to capture real-world activity in a monitored space. These sensors capture continuous video, which has been converted into frames for further processing. The bilateral filter is used as a pre-processing step to minimize sound while maintaining edges in the frames. The Mask R-CNN model is used for HMT from the frames assigns bounding boxes around each detected human and predicts segmentation masks on each detected frame. The tracking data is stored in a database server and displayed on a large screen to observe the environment. The processed data is further transferred to an application server which serves as a control unit for managing the data and coordinating with the central platform. According to the result, the proposed model attains a 98.45% accuracy rate for human motion tracking. The proposed XXX model achieves an overall accuracy of 2.18%, 8.99%, and 1.47% compared to the existing method such as DBSCAN, cluster segmentation, and k-fold cross-validation.

关键词： Solid modeling Accuracy Tracking Motion segmentation Organizations Predictive models Sensor systems Sensors Servers Monitoring

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Quantitative Inertia Estimation Method for Wind Farm Based on AFF-RLS 8

Quantitative Inertia Estimation Method for Wind Farm Based o...

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8th International Conference on control Science and Systems engineering, ICCSSE 2022

作者： Qin, Hao Cao, Yongji Zhang, Hengxu Gao, Zhimin Zhang, Xiaoning Li, Changgang Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education Shandong University Jinan China Technical University of Denmark Kgs. Department of Electrical Engineering Lyngby Denmark School of Control and Computer Engineering North China Electric Power University Beijing China

ISBN: (纸本)9781665484138

In order to guarantee the frequency security and stability of the power system with high proportional of wind generation, virtual inertia control techniques are gradually being promoted and applied. However, there is still a lack of methods and techniques to accurately estimate the equivalent virtual inertia of wind farms in real time, which makes it difficult to quantitatively evaluate the effect of virtual inertia control and to dynamically monitor the inertia level of power systems. Therefore, in this paper, an AR model with eXogenous input is applied to the time-varying characteristics of the virtual inertia of wind farm, and a recursive least squares identification algorithm based on a fuzzy control algorithm with an adaptive forgetting factor is proposed to estimate the virtual inertia of wind farms online. The proposed identification model and solution algorithm have superior tracking ability and good convergence. All that is required is to obtain perturbation data on the frequency and active power of the point of common coupling from the phasor measurement unit. A case study is carried out to verify the effectiveness of the proposed method. © 2022 IEEE.

关键词： Least squares approximations

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Impurity Monitoring using IOT

Impurity Monitoring using IOT

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Energy, Materials and Communication engineering (ICEMCE), International Conference on

作者： Sarathkumar D Srinivasan Murugesan P Sukumar Raymon Antony Raj Sampath Kumar Venkatachary Leo John Baptist Andrews Dishore Shunmugham Vanaja Department of Electrical and Electronics Engineering Kongu Engineering College Tamilnadu India Department of Computer Science and Engineering Nandha Engineering College (Autonomous) Erode Tamilnadu Grant Thornton Gaborone Botswana Department of Information Technology Faculty of Engineering and Technology Botho University Gaborone Botswana Department of Electrical and Electronics Engineering MarBaselios College of Engineering and Technology Thiruvananthapuram Kerala India

Today, the Internet of Things (IoT) technique is applied in a variety of study fields to observe, collect, and analyze data from remote locations. The quality of water has significantly declined as a result of the massive increase in global industrial output, the move from rural to urban areas, and the over exploitation of land and marine resources. Impurities can be found in the dying chamber's output water. Repeatedly, the same water is controlled in the ETP chamber and fed to the death chamber. The impact of the various physical water contaminations created during the hydrologic cycle and/or bacterial colonization relies on the unique circumstances of the water consumer. The different contaminants must be identified and calculated in order to examine the demand for treatment and the suitable technology. The most common application of qualitative differentiating is to describe the aesthetic or visual quality of water. Water that is turbid contains suspended particles that give it a murky look. These particles scatter and submerge light, giving the impression of clouds. Organic or inorganic particles may be suspended. The pH of a fluid is used to determine its relative acidic or basic level. Calculating the hydrogen ion concentration in water results in pH. For the additional treatment step, the waste water's temperature is measured. The degree of pollution present in the waste water can be identified and appropriately handled by measuring the pH, turbidity, temperature, and humidity.

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Sentiment Summarization Generation Based on Multi Instance Learning and Graph Convolution on Social Media

Sentiment Summarization Generation Based on Multi Instance L...

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International Conference on computer Supported Cooperative Work in Design

作者： Bingshu Shi Meiling Liu Jiyun Zhou Kaiqun Fu School of Computer and Control Engineering Northeast Forestry University Harbin China Lieber Institute Johns Hopkins University Baltimore USA Department of Electrical Engineering and Computer Science South Dakota State University Brookings USA

ISBN: (数字)9798350349184

ISBN: (纸本)9798350349191

Sentiment summary generation task is very valuable in social media, which can extract different aspects from people’s evaluation of products or services, such as the quality of products, and generate summarized opinionated sentiment summaries. And nowadays, sentiment summarization still suffers from insufficient contextual information capture and incorrect and comprehensive aspect extraction. In this paper, we propose a new strategy to solve the above problems: firstly, MILNET is used to automatically identify aspects related to a product or service from a large number of user reviews, and then the results are inputted into GCN, which is used to enhance the importance of contextual words close to the aspect; meanwhile, E-MABA is utilized for further optimization of the model on aspect extraction. By conducting a large number of experiments on the OPOSUM dataset and comparing the existing state-of-the-art methods, it is found that our method achieves better performance than other methods, proving the feasibility and effectiveness of our proposed strategy.

关键词： Analytical models Vocabulary Sentiment analysis Social networking (online) Reviews Predictive models Data mining

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PrivShape: Extracting Shapes in Time Series under User-Level Local Differential Privacy

arXiv

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arXiv 2024年

作者： Mao, Yulian Ye, Qingqing Hu, Haibo Wang, Qi Huang, Kai Department of Computer Science and Engineering Southern University of Science and Technology China Department of Electrical and Electronic Engineering The Hong Kong Polytechnic University Hong Kong Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology China School of Computer Science and Engineering Macau University of Science and Technology China

Time series have numerous applications in finance, healthcare, IoT, and smart city. In many of these applications, time series typically contain personal data, so privacy infringement may occur if they are released directly to the public. Recently, local differential privacy (LDP) has emerged as the state-of-the-art approach to protecting data privacy. However, existing works on LDP-based collections cannot preserve the shape of time series. A recent work, PatternLDP, attempts to address this problem, but it can only protect a finite group of elements in a time series due to ω-event level privacy guarantee. In this paper, we propose PrivShape, a trie-based mechanism under user-level LDP to protect all elements. PrivShape first transforms a time series to reduce its length, and then adopts trie-expansion and two-level refinement to improve utility. By extensive experiments on real-world datasets, we demonstrate that PrivShape outperforms PatternLDP when adapted for offline use, and can effectively extract frequent shapes. Copyright © 2024, The Authors. All rights reserved.

关键词： Time series

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Data Analysis and Visualization of the Industrial IoT Based on the Big Data Approach

Data Analysis and Visualization of the Industrial IoT Based ...

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International conference of Electronics, Communication and Aerospace Technology (ICECA)

作者： R. Ganesan Chandrima Roy Ramiya R Hemambujavalli S R. Vijayakumar Department of Electrical and Electronics Engineering Meenakshi College of Engineering India Department of Computer Science and Engineering Adamas University Kolkata West Bengal Department of Electronics and Communication Engineering Periyar Maniammai Institute of Science and Technology Thanjavur Department of Electronics and Communication Engineering Mahendra Engineering College (Autonomous) Namakkal

The present work proposes a solution for the visualization of temperature and pressure data from plastic injection machines. From the collected data., an analysis of these data is carried out., to present the data in the clearest possible way. This data is sent to a local database., which then must be visualized in the form of graphs in real time. For further queries of the data., a dashboard is also developed for these data., divided by time intervals., in which the maximum., average., and minimum data of temperature and pressure are visualized., in the form of line and circular graphs. The solution intends to be used not only in a web environment., but also on the production line in low-cost single-board systems., such as RaspberryPI., allowing real-time visualization.

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