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Innovative Research on the Prevention Path of Athletic Injuries under Digital technology 8

Innovative Research on the Prevention Path of Athletic Injur...

引用

8th international conference on Image, Vision and computing, ICIVC 2023

作者： Lei, Miaowen Chen, Fang Academy of Arts Wuhan Institute of Physical Education Wuhan China

ISBN: (纸本)9798350335231

Integration of computer vision technology and artificial intelligence presents a potential method for treating sports injuries in the digital age. Traditional imaging techniques have limitations when it comes to identifying sports injuries, such as delays and an inability to provide early warnings. Through a review of the literature and case studies, MediaPipe video feedback is exceptionally useful for accurately tracking human joints and capturing movement. Real-time surveillance of relevant node data during physical activities can provide early warnings and prompt diagnosis of sports injuries in order to prevent sports injuries. This serves to reduce the risk of 'secondary injuries' resulting from missing the 24-hour critical acute phase. In addition, the convergence of artificial intelligence and injury prevention in sports creates new opportunities. Utilizing artificial intelligence can result in innovative approaches and enhanced methods for treating and preventing sports injuries. © 2023 IEEE.

关键词： Sports

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Finite-Time Three-Dimensional Cooperative Guidance Law for Moving Target with Line-of-Sight Angle Constraint

Finite-Time Three-Dimensional Cooperative Guidance Law for M...

引用

2023 international conference on Neuromorphic computing, ICNC 2023

作者： Zhu, Huatian Wang, Linan Wang, Yujun Wang, Xinhe Yin, Qiyu Southeast University School of Mathematics Nanjing211189 China School of Automation Beijing Institute of Technology Beijing100081 China Southeast University School of Cyber Science and Engineering Nanjing211189 China

ISBN: (纸本)9798350316889

A new kind of finite-time three-dimensional cooperative guidance laws with Line-of-sight (LOS) that guarantees the intercept of moving targets is proposed in this paper. Firstly, through careful and rigorous analysis of the cooperative guidance systems, a finite-time observer is designed to observer states of the moving target. Then, a cooperative guidance law via the finite-time control theory is proposed to intercept the target under the user-defined LOS angle constraint. Finally, simulation studies are provided to illustrate the advantages of the proposed guidance law. © 2023 IEEE.

关键词： cooperative guidance law finite-time convergence line-of-sight angle constraint

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A STABLE, FAST, AND FULLY AUTOMATIC LEARNING ALGORITHM FOR PREDICTIVE CODING NETWORKS 12

A STABLE, FAST, AND FULLY AUTOMATIC LEARNING ALGORITHM FOR P...

引用

12th international conference on Learning Representations, ICLR 2024

作者： Salvatori, Tommaso Song, Yuhang Yordanov, Yordan Millidge, Beren Emde, Cornelius Xu, Zhenghua Sha, Lei Bogacz, Rafal Lukasiewicz, Thomas VERSES AI Research Lab Los AngelesCA90016 United States MRC Brain Network Dynamics Unit University of Oxford United Kingdom Department of Computer Science University of Oxford United Kingdom School of Health Sciences and Biomedical Engineering Hebei University of Technology China Institute of Logic and Computation Vienna University of Technology Austria Fractile Ltd. London United Kingdom

Predictive coding networks are neuroscience-inspired models with roots in both Bayesian statistics and neuroscience. Training such models, however, is quite inefficient and unstable. In this work, we show how by simply changing the temporal scheduling of the update rule for the synaptic weights leads to an algorithm that is much more efficient and stable than the original one, and has theoretical guarantees in terms of convergence. The proposed algorithm, which we call incremental predictive coding (iPC), is also more biologically plausible than the original one, as it is fully automatic. In an extensive set of experiments, we show that iPC constantly performs better than the original formulation on a large number of benchmarks for image classification, as well as for the training of both conditional and masked language models, in terms of test accuracy, efficiency, and convergence with respect to a large set of hyperparameters. © 2024 12th international conference on Learning Representations, ICLR 2024. All rights reserved.

关键词： Bayesian networks

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An Improved Dung Beetle Optimizer for Random Forest Optimization 6

An Improved Dung Beetle Optimizer for Random Forest Optimiza...

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6th international conference on Frontier Technologies of Information and Computer, ICFTIC 2024

作者： Tan, Lianghao Liu, Xiaoyi Liu, Dong Liu, Shubing Wu, Weixi Jiang, Huangqi W. P. Carey School of Business Arizona State University Tempe United States Ira A. Fulton Schools of Engineering Arizona State University Tempe United States Yale University Department of Computer Science New Haven United States University of North Carolina at Chapel Hill Department of Computer Science Chapel Hill United States Tandon School of Engineering New York University New York United States College of Computing Georgia Institute of Technology Atlanta United States

ISBN: (纸本)9798331541750

To improve the convergence speed and optimization accuracy of the Dung Beetle Optimizer (DBO), this paper proposes an improved algorithm based on circle mapping and longitudinal-horizontal crossover strategy (CICRDBO). First, the Circle method is used to map the initial population to increase diversity. Second, the longitudinal-horizontal crossover strategy is applied to enhance the global search ability by ensuring the position updates of the dung beetle. Simulations were conducted on 10 benchmark test functions, and the results demonstrate that the improved algorithm performs well in both convergence speed and optimization accuracy. The improved algorithm is further applied to the hyperparameter selection of the Random Forest classification algorithm for binary classification prediction in the retail industry. Various combination comparisons prove the practicality of the improved algorithm, followed by SHapley Additive exPlanations (SHAP) analysis. © 2024 IEEE.

关键词： Random forests

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Multi-Level and Multi-Swarm Particle Swarm Optimization Algorithm

Multi-Level and Multi-Swarm Particle Swarm Optimization Algo...

引用

2023 international conference on Algorithms, computing and Data Processing, ACDP 2023

作者： Long, Junwei Yi, Xiangbo School of Computer Science and Artificial Intelligence Wuhan University of Technology Wuhan China

ISBN: (纸本)9798350326680

Inspired by the mechanism of batch processing systems, this paper proposes a multi-level and multi-swarm particle swarm optimization (MMPSO) algorithm to alleviate the performance degradation caused by imbalances in exploration and exploitation within the swarm. The algorithm constrains the learning behavior of different swarms by dividing the swarm into multi-level and multi-swarm. Swarms of different levels are grouped into various to perform different tasks. The small-scale in top-level swarm is responsible for exploiting the global optimal position. The large-scale in bottom-level swarm uses the Levy flight strategy based on the improvement rate to explore unknown areas, effectively improving the exploration ability. The middle-level swarm is divided into multi-swarm to explore and exploit local locations and design an internal and external comprehensive learning strategy. A lifting mechanism is proposed to improve the information exchangeability of swarms at different levels. Experimental results on the 30-D of the CEC2017 benchmark optimization problems show that the MMPSO algorithm exhibits the best convergence accuracy on most benchmark functions due to the balance of exploration and exploitation. Furthermore, the algorithm combine with BP Neural Networks (BPNN) shows the best convergence accuracy on the application problem of developing force-field parameters (FFPs). © 2023 IEEE.

关键词： Swarm intelligence

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Integration of Quantum computing Techniques in MIMO System Optimization

Integration of Quantum Computing Techniques in MIMO System O...

引用

2023 international conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Durga, C.S.L. Vijaya Anandhi, R.J. Suman, Bashetty Ritika Singh, Navdeep Naser, Zamen Latef Institute of Aeronautical Engineering Hyderabad Dundigal India New Horizon College of Engineering Department of Information Science Engineering Bangalore India Mlr Institute of Technology Department of Information Technology Telangana Hyderabad India G.L. Bajaj Institute of Technology and Management Dept. of It Gr. Noida India Lovely Professional University Phagwara India College of Engineering Technology National University of Science and Technology Dhi Qar Iraq

ISBN: (纸本)9798350357769

The rapid advancement of quantum computing provides unprecedented opportunities for the optimization of multiple-input, multiple-output (MIMO) systems. This paper investigates the efficacy of harnessing quantum algorithms, particularly the Quantum Approximate Optimization Algorithm (QAOA) and Grover's algorithm, for the optimization of MIMO systems. The paper establishes a theoretical framework that maps MIMO optimization problems onto quantum circuits, ensuring a reduction in computational complexity compared to classical algorithms. The proposed methodology is validated through a series of numerical simulations. Notable improvements are observed in both convergence speed and the quality of the optimized solutions. Furthermore, the synergy of quantum computing and MIMO presents new frontiers for reducing interference, enhancing throughput, and ensuring robustness against environmental uncertainties. These results affirm the potential of integrating quantum computing techniques in MIMO system optimization, heralding a transformative era for wireless communication paradigms. © 2023 IEEE.

关键词： Grover's Algorithm Interference Minimization. Top of Form MIMO Systems Quantum Approximate Optimization Algorithm (QAOA) Quantum computing

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Resilience-Centric Trust Evaluation in Cloud computing: A Comparative Assessment of Cloud Trust Evaluation Methods Using the RAA Metric

Resilience-Centric Trust Evaluation in Cloud Computing: A Co...

引用

2024 international conference on Smart Electronics and Communication Systems, ISENSE 2024

作者： John, Jomina John Singh, K. School of Computer Science Engineering and Information Systems Vellore Institute of Technology Tamil Nadu Vellore632014 India

ISBN: (数字)9798331528126

ISBN: (纸本)9798331528126

In cloud computing environments, trust evaluation models are critical for assessing the reliability and security of cloud service providers. The accuracy of trust evaluations may be impacted by the failure of traditional trust measurements to take resilience under dynamic settings into consideration. In order to assess the flexibility and resilience of trust assessment models in cloud computing, this research presents a new metric called the Resilience-Aware Assessment. The Risk Assessment offers a thorough assessment of trust models in a variety of cloud environments by taking into account elements including system performance during high stress, reaction to malevolent activity, and recovery time following interruptions. In order to compare various trust evaluation models already in use, this study evaluates them using the RAA in addition to other traditional criteria like accuracy, scalability, and convergence time. The findings show that the RAA metric, especially in situations with uncertainty and volatility, successfully draws attention to trust model strengths and shortcomings that are missed by traditional metrics. The integration of the RAA metric into multi-criteria decision-making frameworks for cloud service selection is also covered in the article, offering a more adaptable and robust method for evaluating trust. Future research will examine how the RAA measure can be used to improve autonomous trust management systems in edge-cloud contexts as well as how it can be applied in real-time cloud orchestration. © 2024 IEEE.

关键词： Cloud security

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Enhanced Fog-based Smart Parking System with 5G 3

Enhanced Fog-based Smart Parking System with 5G

引用

3rd international conference on Intelligent computing, Communication and convergence, ICI3C 2023

作者： Roy, Swati Sucharita Sahu, Bharat J. R. Dash, Shatarupa Iter Siksha 'O' Anusandhan University Dept. of Comp. Sc. & Engineering Bhubaneswar India

ISBN: (纸本)9798350343922

The rapid growth of population and urbanization leads to substantial growth in vehicular traffic. Most city planning authorities focus on smart parking systems to automate vehicle parking and reduce traffic congestion. Thus, the smart city and Internet of Things (IoT) data traffic is growing tremendously. Moreover, cloud and fog computing are becoming well-known for IoT traffic. As a result, the cloud becomes congested. To manage parking system communication, we proposed an efficient fog-based parking system with 5G wireless communication technology to allow low latency and green communication, reduce overloading, and make faster real-time computation. Each parking lot is connected with fog nodes, Road Side Units (RSU), cloud through 5G base station, and capillary connections (Wi-Fi, ZigBee) for parking-related services like vacant parking space searching, best possible slot allocation, parking slot reservation and nearest optimal parking lot identification concerning driver's destination location and preferences. Overall service delay, possible slot vacancies prediction, and parking cost estimation are three significant issues in this article. We simulated and compared the response time of the proposed model with the legacy models. The simulation results show the benefits of using fog computing over the cloud. © 2023 IEEE.

关键词： Fog computing

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A Survey on Vehicular Edge computing Architectures 13

A Survey on Vehicular Edge Computing Architectures

引用

13th international conference on Information and Communication technology convergence, ICTC 2022

作者： Lee, Jaehwan Na, Woongsoo Kongju National University Department of Computer Science and Engineering Korea Republic of Kongju National University Department of Software Korea Republic of

ISBN: (数字)9781665499392

ISBN: (纸本)9781665499392

With the recent development of intelligent transportation system (ITS), vehicular applications are being actively studied including autonomous driving, vehicle platooning, that require real-time and high-performance processing resources. Accordingly, various system architectures are being studied to satisfy the high-performance computing requirements. Although the mobile cloud computing architecture provides large-scale computing resources, it is not suitable for vehicular environment that requires real-time processing due to the structure in which the edge node and the computing resources are geographically distant. The mobile edge computing (MEC) architecture places computing resources around edge devices. However, it does not consider edge devices moving at a high speed in a limited service area. Vehicular edge computing (VEC) and vehicular fog computing paradigm have emerged to address the latency requirement with the development of vehicular communications. In this paper, such a computation offloading architecture is presented and analyzed. © 2022 IEEE.

关键词： Computer architecture

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QIGA: Quantum-Inspired Genetic Algorithm for Dynamic Scheduling in Mobile Edge computing 29

QIGA: Quantum-Inspired Genetic Algorithm for Dynamic Schedul...

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29th international Computer conference, Computer Society of Iran, CSICC 2025

作者： Galavani, Sadra Younesi, Abolfazl Ansari, Mohsen Department of Computer Engineering Sharif University of Technology Tehran Iran

ISBN: (纸本)9798331523114

This paper introduces a Quantum-Inspired Genetic Algorithm (QIGA) for efficient scheduling in a Mobile Edge computing (MEC) environment. Inspired by the principles of quantum computing, it enhances solution diversity and convergence in the MEC landscape with heterogeneous resources and dynamic tasks. In this work, the QIGA framework is applied to an optimization problem with multiple conflicting objectives: makespan, energy consumption, and resource utilization. Extensive evaluations demonstrate the effectiveness of our proposed method, which shows improvement over three state-of-the-art scheduling methods in varied burst MEC scenarios in energy consumption about 15.7% on average and up to 39%, 20.5% in makespan, 27.5% in resource utilization, and latency up to 69.9%. © 2025 IEEE.

关键词： Qubits

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