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optimization of the Primary Vertex Reconstruction algorithm for the BM@N Experiment with Regard to Topology of Events

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PHYSICS OF ATOMIC NUCLEI 2021年第12期84卷 1947-1951页

作者： Kakhanovskaya, N. E. Merts, S. P. Nemnyugin, S. A. St Petersburg State Univ St Petersburg 199034 Russia Joint Inst Nucl Res Dubna 141980 Moscow Oblast Russia

BM@N (Baryonic Matter at Nuclotron) is the first working experiment performed at the NICA accelerator complex. It is a fixed target experiment. To date, there have been seven runs of the experiment, most of which were technical. In 2018, the first run of the experimental facility with physics data acquisition took place. One of the prerequisites for physics analysis of experimental data is the existence of the primary vertex position estimation. This study describes the proposed algorithm for reconstruction of the primary vertex using the virtual planes method. The results of this algorithm for different targets, beams, and trigger conditions are presented. The sensitivity of the presented method is considered.

关键词： BM@N BmnRoot primary vertex virtual planes method Kalman filter reconstruction of events algorithm optimization

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Improved Branch-and-Bound algorithm for U-Curve optimization

Improved Branch-and-Bound Algorithm for U-Curve Optimization

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IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS)

作者： Atashpaz-Gargari, Esmaeil Braga-Neto, Ulisses M. Dougherty, Edward R. Texas A&M Univ Dept Elect & Comp Engn College Stn TX 77843 USA Translat Genom Res Inst Computat Biol Div Phoenix AZ USA

ISBN: (纸本)9781479934621

The U-curve branch-and-bound algorithm for optimization was introduced recently by Ris and collaborators. In this paper we introduce an improved algorithm for finding the optimal set of features based on the U-curve assumption. Synthetic experiments are used to asses the performance of the proposed algorithm, and compare it to exhaustive search and the original algorithm. The results show that the modified U-curve BB algorithm makes fewer evaluations and is more robust than the original algorithm.

关键词： Branch and bound algorithms exhaustive search algorithms algorithm optimization Donkeys

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Application of heuristic function optimization strategy of A* algorithm in path planning of mobile robot 5

Application of heuristic function optimization strategy of A...

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5th International Conference on Computer Engineering and Application (ICCEA)

作者： Lu, Jiahao Sun, Yuan Shanghai Dianji Univ Sch Mech Engn Shanghai Peoples R China

ISBN: (纸本)9798350386783;9798350386776

Research the application of A* algorithm in path planning. Examine several different optimization strategies for the A* algorithm heuristic function. These strategies aim to improve the search efficiency and path quality of the algorithm. To verify the effectiveness of each strategy, simulations were conducted in two raster map environments with different levels of complexity. The results show that the optimization strategy of the heuristic function can improve the algorithm performance to a certain extent, and the effects of different strategies are related to the complexity of the environment.

关键词： Path Planning A* algorithm Heuristic Function Mobile Robots algorithm optimization

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Application and optimization of the UCT algorithm in Einstein wurfelt nicht! 34

Application and optimization of the UCT algorithm in Einstei...

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34th Chinese Control and Decision Conference (CCDC)

作者： Wang, Tianlong Yang, Zhen Xie, Zhengbo Beijing Inst Technol Sch Comp Sci Beijing 100081 Peoples R China

ISBN: (纸本)9781665478960

Based on the characteristics of Einstein wurfelt nicht!(EWN), this paper puts forward the UCT algorithm applied to EWN, and on its basis, an optimized UCT algorithm with the evaluation function and the dynamic searching rounds is proposed. The evaluation function is used to better evaluate the situation, and the dynamic searching rounds is used to reduce the average cost per game by a decay function. By playing multiple games with the UCT algorithm, the optimized UCT algorithm proved to be effective in improving the strength of the EWN game system.

关键词： Einstein wurfelt nicht Monte Carlo Tree Search UCT algorithm optimization

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Robot Path Planning optimization Based on RRT and APF Fusion algorithm 8

Robot Path Planning Optimization Based on RRT and APF Fusion...

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8th International Conference on Robotics and Automation Sciences (ICRAS)

作者： Fu, Sanli Dept Univ Sanya Sanya 572000 Hainai Peoples R China

ISBN: (纸本)9798350352511;9798350352504

In the current research field, aiming at the problem of robot path planning, this study proposes an optimization strategy combining RRT algorithm and APF method. This strategy aims to achieve more efficient and reliable robot path planning by improving the path search efficiency of RRT algorithm and combining the goal-oriented and obstacle-avoiding capability of APF. Specifically, we optimize the RRT algorithm as follows: First, we introduce an APF-based heuristic strategy, which helps guide the path search process closer to the target point faster;Secondly, in the process of path generation, the APF method is used to smooth the path in real time to reduce the complexity of the path and the energy consumption during execution. After extensive testing in simulation environments, the optimization strategy shows significant improvements in path length, planning time, and obstacle avoidance. Compared with the traditional RRT algorithm, the new strategy not only reduces the path length, but also shows stronger adaptive ability and robustness in the face of complex environment and sudden obstacles. In addition, through the path smoothing process guided by APF, the dynamic response and stability of the robot when executing the path are also improved.

关键词： APF algorithm Local path planning algorithm optimization RRT algorithm Fusion algorithm

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The optimization and Design of the Auto-Exposure algorithm Based on Image Entropy 8

The Optimization and Design of the Auto-Exposure Algorithm B...

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Proceedings 2015 8 International Congress on Image and Signal Processing (CISP)

作者： Ning, Jingyi Lu, Tiejun Liu, Liyan Guo, Liye Jin, Xiaofeng Beijing Microelect Tech Inst 2 Siyingmen N Rd Beijing 100076 Peoples R China

ISBN: (纸本)9781467390989

In order to make the CMOS image sensor exposure automatically and correctly in different environment, this paper presents an improved algorithm based on image entropy. Image entropy is the information measure of image. Thus, with the purpose of getting the most appropriate exposure time, we can search the maximum information entropy. What's more, by using the formula manipulation of image entropy and the piecewise linearization of the log function, the algorithm grasps the overall change rule and avoids the traditional precise calculation, which can save the computing time greatly and reduce the use of the resource. Meanwhile, simulation results demonstrated the effectiveness of the algorithm, which leaves a strong foundation for the hardware realization of the CMOS image sensor auto-exposure.

关键词： auto-exposure image-entropy exposure time algorithm optimization hardware realization

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Research on the optimization algorithm of Urban Road Recognition System based on DM6437 3

Research on the Optimization Algorithm of Urban Road Recogni...

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3rd IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)

作者： Jiang, Libiao Li, Jingxuan Jiang, Zhihui Zhang, Jingyuan South China Univ Technol Sch Mech & Automot Engn Guangzhou Guangdong Peoples R China South China Univ Technol Guangzhou Coll Guangzhou Guangdong Peoples R China

ISBN: (纸本)9781538645093

In order to improve the robustness and real-time performanc e of vehicle safety assistant driving system for identifying the front driving environment, an optimized algorithm for road image processing and lane detection is proposed Aiming at the characteristic structure of road image, we use static partition and image processing in the region of interest. After the grayscale processing, the optimized median filtering algorithm is used to remove the noise. In the process of lane detection and fitting, the Hough algorithm is improved based on the characteristics of lane lines. When Kalman filtering is used to track lane lines, Hough transform and least square method are used to identify lane lines. Finally, the algorithm is transplanted to the DM6437 hardware platform, and the software code is optimized by combining the architecture features of the embedded system. The actual experimental results verify the real-time performance and robustness of the optimized algorithm.

关键词： Road recognition Image processing Hough transform algorithm optimization

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HLS-based optimization of Tau Triggering algorithm for LHC: a case study 18

HLS-based Optimization of Tau Triggering Algorithm for LHC: ...

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18th Baltic Electronics Conference

作者： Cherezova, Natalia Mihhailov, Dmitri Devadze, Sergei Jutman, Artur Tallinn Univ Technol Dept Comp Syst Tallinn Estonia Teston Lab Tallinn Estonia

ISBN: (数字)9781665462952

ISBN: (纸本)9781665462952

With the current increase in the data produced by the Large Hadron Collider (LHC) at CERN, it becomes important to process this data in a corresponding manner. To begin with, to efficiently select events that contain relevant information from a massive flow of data. This is the task of the tau lepton decay triggering algorithm. The implementation is based on the High-Level Synthesis (HLS) approach that allows generating a hardware description of the design from the algorithm written in a high-level programming language like C++. HLS tools are intended to decrease the time and complexity of hardware design development, however, their capabilities are limited. The development of an efficient application requires substantial knowledge of the hardware design and HLS specifics. This paper presents the optimizations introduced to the algorithm that improved latency and area and more importantly solved the problems with the routing, making it possible to implement the algorithm on the FPGA fabric.

关键词： HLS algorithm optimization

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optimization of Sorting Activities in Automatic Storage and Retrieval Systems Based on Improved Artificial Fish Swarm algorithm 3

Optimization of Sorting Activities in Automatic Storage and ...

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3rd International Conference on Robotics and Automation Engineering (ICRAE)

作者： Gao, Xiaoyu Yu, Lei He, Shangyang Wuhan Univ Technol Sch Automat Wuhan Hubei Peoples R China

ISBN: (纸本)9781538695944

For the problem of picking path planning in automatic storage, the traditional artificial fish swarm algorithm is improved to be used to optimize the picking system. In the algorithm, the calculation of dynamic parameters is added, so that the field of view and step size of the algorithm are dynamically changed to adapt to the convergence process of the algorithm;the chaotic model is added for initialization to obtain a better initial individual distribution. Experiments show the improved algorithm is feasible in the sorting activities in automatic storage and retrieval systems.

关键词： picking operation automatic storage artificial fish swarm algorithm travelling salesman problem algorithm optimization

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Research on optimization of Privacy Protection algorithm Based on Federated Learning 10

Research on Optimization of Privacy Protection Algorithm Bas...

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10th International Conference on Big Data and Information Analytics

作者： Jia, Boyu Zhang, Yaohong Bao, Weidong Wang, Ji Zhang, Xiongtao Zhon, Zhenyi Natl Univ Defense Technol Lab Big Data & Decis Changsha Peoples R China

ISBN: (纸本)9798350354638;9798350354621

Faced with the increasing demand and application scenarios for open data sharing in industries such as banking, securities, and insurance, data from different institutions often exhibit high complementarity. However, due to privacy protection and compliance issues, these institutions cannot directly share data. To address this challenge, the article introduces the federated learning optimization algorithm, which enables cross-agency cooperation and allows different institutions to train models without exposing raw data. This approach enhances the effectiveness and accuracy of the models. However, the large-scale implementation of federated learning is hindered by high communication costs, client heterogeneity, low algorithm efficiency, and unstable model performance. Therefore, it is crucial to better apply federated learning algorithms to practical problems and leverage their advantages in data privacy protection and model performance improvement. This article presents a federated learning algorithm specifically designed for optimizing communication costs. Through this optimization algorithm, only one round of communication between the client and server is required. The results demonstrate that, while ensuring accuracy, the amount of communication data is reduced to 1/10 of the Federal Average (FedAvg) algorithm on the dataset, and 1/100 of the FedAvg algorithm on the CIFAR-10 dataset.

关键词： Federated learning Privacy protection algorithm optimization Communication costs

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