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Real-time Dynamic Trajectory Planning for Intelligent Vehicles Based on Quintic Polynomial

Real-time Dynamic Trajectory Planning for Intelligent Vehicl...

引用

IEEE international Symposium on parallel and distributed Processing with Applications and IEEE international conference on Ubiquitous computing and Communications (ISPA/IUCC)

作者： Zefu Tan Jian Wei Nina Dai School of Electronics and Information Engineering Chongqing Three Gorges University Chongqing China

The trajectory planning of intelligent vehicles is the focus of the research field of intelligent vehicles. In this paper, the vehicle state is analyzed during the lane change process, the trajectory of the intelligent vehicle is planned by using the quintic polynomial, the trajectory optimization function is introduced, the objective function of integrated lane change time and maximum acceleration to improve comfort and passage efficiency is constructed, the lane change trajectory is optimally selected based on particle swarm algorithm, and the lane change trajectory is referenced according to the real-time information provided by the Vehicle to Everything to realize real-time data update in order to the data is updated in real-time to provide timely feedback to the information processing center for re-planning the path when there is an unexpected situation ahead. The simulation results show that the lane change trajectory planning method can solve the problems caused by the change of speed of surrounding vehicles and the sudden intrusion of vehicles in the process of lane change, and can significantly improve the smoothness and safety of the process of lane change.

关键词： Trajectory planning Simulation Ubiquitous computing Real-time systems Safety Reliability Vehicle dynamics

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Research on Optimization Control of Deep Hole Machining Based on Capuchin Search Algorithm to Optimize Fuzzy PID

Research on Optimization Control of Deep Hole Machining Base...

引用

IEEE international Symposium on parallel and distributed Processing with Applications and IEEE international conference on Ubiquitous computing and Communications (ISPA/IUCC)

作者： Chang Qin Hongzhi Hu HuaiZhi Chen BaoXian Yan Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou University Wuzhou China Guangxi Key Laboratory of Automatic Testing Guilin University of Electronic Science and Technology Guilin China School of Electronic Engineering and Automation Guilin University of Electronic Science and Technology Guilin China

A small deep hole drilling control system based on the capuchin search algorithm to optimize fuzzy PID is proposed to improve the efficiency of small deep hole drilling. Based on the difference between the actual axial force and the expected axial force, the system adaptively adjusts the quantization factor and scale factor of the fuzzy PID controller by using the capuchin search algorithm and adjusting the parameters of the controller in real-time to improve the system performance. The experimental results show that the CapSA-optimized fuzzy PID algorithm achieves the shortest stabilization time and slight overshoot. When the algorithm is applied to actual machining, the proposed algorithm has a faster response speed and more stable axial force. It can be adaptive to Change the PID drilling parameters to meet the production requirements of intelligent manufacturing..

关键词： Drilling PI control System performance Simulation Force Process control Ubiquitous computing

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An Experimental Consideration of High-Order Harmonic Resonance Phenomenon Caused by grid-Connected Inverter in parallel Operation

An Experimental Consideration of High-Order Harmonic Resonan...

引用

CIRED 2021 - The 26th international conference and Exhibition on Electricity Distribution

作者： K. Fukushima N. Okada Central Research Institute of Electric Power Industry Yokosuka-city Japan

Harmonic disturbances caused by the high-order harmonics of grid-connected inverters are observed in the medium-voltage distribution systems with a large number of distributed generations. It has been demonstrated with the one inverter that a large harmonic voltage is observed when the switching frequency of the inverter becomes equal to the series resonance frequency of the grid-side impedance. In real distribution systems, multiple inverters are connected in parallel for the large power capacity. It is required to clarify the mechanism of the harmonic disturbance in parallel-operating conditions. This paper considers the harmonic voltage characteristics in parallel-operating conditions by the experimental results.

关键词： distributed power generation power system harmonics invertors power grids

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A Blockchain-Based Multi-Cloud Storage Data Consistency Verification Scheme

A Blockchain-Based Multi-Cloud Storage Data Consistency Veri...

引用

IEEE international conference on Big Data and Cloud computing (BdCloud)

作者： Feiyu Wang Jian-tao Zhou Hao Wang Xu Guo College of Computer Science Inner Mongolia University Hohhot China Inner Mongolia Engineering Laboratory for Cloud Computing and Service Software Inner Mongolia Key Laboratory of Social Computing and Data Processing Inner Mongolia Engineering Laboratory for Big Data Analysis Technology Engineering Research Center of Ecological Big Data Ministry of Education National & Local Joint Engineering Research Center of Intelligent Information Processing Technology for Mongolian China

Users worldwide widely use cloud storage because of its efficiency, convenience, and high availability. Multi-cloud storage is usually selected to ensure the high availability of data. Unfortunately, when data is migrated and replicated between multi-cloud data centers, it is not easy to guarantee data con-sistency. This paper proposes an efficient, secure, and new data consistency verification scheme using blockchain technology. In order to reduce the computation and communication overhead in the verification process, our scheme uses encrypted tags to build Merkle hash tree to generate unique and lightweight verification proofs and does not use third-party auditors. The final theoretical and experimental analysis shows that our scheme has higher security and a faster verification process in multi-cloud storage.

关键词： Cloud computing Data centers Costs Blockchains Behavioral sciences

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Aware: Adaptive distributed Training with Computation, Communication and Position Awareness for Deep Learning Model

Aware: Adaptive Distributed Training with Computation, Commu...

引用

IEEE international conference on High Performance computing and Communications (HPCC)

作者： Yan Zeng Guangzheng Yi Yuyu Yin Jiyang Wu Meiting Xue Jilin Zhang Jian Wan Yunquan Zhang School of Computer Science and Technology Hangzhou Dianzi University Hangzhou China School of Cyberspace Hangzhou Dianzi University Hangzhou China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China

The accuracy of the neural networks can usually be improved by increasing the size of the dataset and the layers or operators of the network, as it has strong composability. But, it makes a challenge to train these models efficiently, due to the limited resources of a single device, such as memory, computational resource and so on. For this challenge, it has become an inevitable trend to automatically implement model parallelism across multiple devices. This paper proposes Aware, an adaptive distributed parallel training method, to search distributed parallel strategy automatically for deep learning model. It firstly proposes an operator fusion strategy with computation and communication awareness to simplify the computational graph of deep learning model. And then, it introduces position-aware graph embedding algorithm to extract the structural features of models, which can make the searched parallel strategies to transplant to other networks with similar structures. On this basis, we use reinforcement learning algorithm to search distributed parallel strategy automatically. This paper makes experiments with neural networks such as Inception V3, NMT, GNM, NasNet and ResNet, and uses CIFAR10 and PTB datasets to compare the two methods of Hierarchical and Placeto. The results show that compared with Placeto, Aware achieves up to 5% reductions in runtime. Aware achieves more than 8% reductions in runtime compared with Hierarchical. Moreover, it has better transplantation and generalization capabilities, and supports pre-training for large-scale network parallel strategy search and accelerates convergence.

关键词： Deep learning Training Adaptation models Runtime Computational modeling Neural networks Reinforcement learning

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FLY: A Domain-Specific Language for Scientific computing on FaaS 25th

FLY: A Domain-Specific Language for Scientific Computing on ...

引用

25th international conference on parallel and distributed computing (Euro-Par)

作者： Cordasco, Gennaro D'Auria, Matteo Negro, Alberto Scarano, Vittorio Spagnuolo, Carmine Univ Campania Dipartimento Psicol Caserta Italy Univ Salerno Dipartimento Informat Fisciano Italy

ISBN: (纸本)9783030483401;9783030483395

Cloud computing is widely recognized as distributed computing paradigm for the next generation of dynamically scalable applications. Recently a novel service model, called Function-as-a-Service (FaaS), has been proposed, that enables users to exploit the computational power of cloud infrastructures, without the need to configure and manage complex computations systems. FaaS paradigm represents an opportunity to easily develop and execute extreme-scale applications as it allows fine-grain decomposition of the application with a much more efficient scheduling on cloud provider infrastructure. We introduce FLY, a domain-specific language for designing, deploying and executing scientific computing applications by exploiting the FaaS service model on different cloud infrastructures. In this paper, we present the design and the language definition of FLY on several computing (local and FaaS) back-ends: Symmetric multiprocessing (SMP), Amazon AWS Lambda, Microsoft Azure Functions, Google Cloud Functions, and IBM Bluemix/Apache OpenWhisk. We also present the first FLY source-to-source compiler, publicly available on GitHub, which supports SMP and AWS back-ends.

关键词： Domain-Specific Languages Scientific computing parallel computing distributed computing Serverless computing Functions as a Service (FaaS)

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Application Management Practice of Investment Statistics Business Based on Blockchain Technology

Application Management Practice of Investment Statistics Bus...

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2020 international conference on New Energy Technology and Industrial Development, NETID 2020

作者： Ma, Lei Che, Jiachen Qian, Xiao Song, Hongfang Wen, Geping Jiang, Hao Cui, Qinyue Wen, Fan Development Planning Department State Grid Zhejiang Electric Power Co. Ltd Hangzhou Zhejiang Province China Strategy and Development Research Center State Grid Zhejiang Economic Research Institute Hangzhou Zhejiang Province China

As a new decentralized infrastructure and distributed computing paradigm, blockchain is of great significance to break through the mutual trust problem between statistical specialty and basic data providing departments, and between the upper and lower levels of statistical data reporting units, and further improve the quality of statistical work. This paper first briefly analyzes the problems existing in the current investment statistics business, and introduces the basic principles and characteristics of blockchain technology. This paper studies the idea and process optimization of the application of blockchain technology in investment statistics business, and expounds the specific application schemes of blockchain technology in different links, such as automatic data collection, automatic data verification, automatic report generation, and automatic index release. Finally, the expected effect of the application of blockchain technology in investment statistics business is analyzed. © The Authors, published by EDP Sciences, 2021.

关键词： Blockchain

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Handwritten Chinese Character Recognition Based on Convolutional Neural Networks and TrueType Font Template Matching

Handwritten Chinese Character Recognition Based on Convoluti...

引用

IEEE international Symposium on parallel and distributed Processing with Applications and IEEE international conference on Ubiquitous computing and Communications (ISPA/IUCC)

作者： Yue Chen Guangyao Pang Xiaoying Zhu Baoxing Pu Jihong Huang Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou University Wuzhou China Guangxi Colleges and Universities Key Laboratory of Industry Software Technology Wuzhou University Wuzhou China

Convolutional neural networks(CNN) have made significant advances in offline handwritten Chinese character recognition, CNN recognize characters based on local feature but not making use of the overall topology of the character to improve recognition accuracy. In this paper, we propose a method for handwritten Chinese character recognition by using CNN combined with TrueType font template matching. Firstly, a trained CNN is used to recognize the handwritten Chinese character, the output Top-N are selected as the candidate characters, and then the handwritten Chinese character is linearly transformed and matched with the TrueType font templates of the candidate characters respectively, the best matching candidate character is selected as the result. The experiments show that the method can combine the speed of CNN and the accuracy of template matching effectively, has higher accuracy than conventional CNN, especially for specific types of handwritten Chinese characters recognition.

关键词： Handwriting recognition Network topology Neural networks Stroke (medical condition) Ubiquitous computing Topology Convolutional neural networks

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Design of Hybrid Architecture Cloud Center of Service-Oriented Aerospace TC Application Integration System

Design of Hybrid Architecture Cloud Center of Service-Orient...

引用

2021 IEEE international conference on Computer Science, Electronic Information Engineering and Intelligent Control Technology, CEI 2021

作者： Chen, Hongyan Wang, Sihong Wan, Junwei Li, Wensu Beijing Institute of Tracking and Telecommunicaitons Technology China

ISBN: (纸本)9780738146492

In view of the deficiencies in the current situation of various types of system centers in the field of aerospace measurement, transportation and control, especially the in-depth analysis and summary of the inadaptability of the existing system architecture, combined with the actual needs of my country's satellite applications in the development of industrialization, ubiquity and democratization, this article puts forward the design idea of a service-oriented hybrid architecture integrated measurement, operation and control cloud center. By building a cloud platform and a distributed service-oriented software architecture, use a hybrid software interaction model of 'centralization' and 'decentralization', adopt service-oriented and hybrid architecture software systems and other technologies, The parallel task execution capabilities and resource scheduling and management capabilities of the Aerospace TC System Center are improved, so as to improve the timeliness and accuracy of the system response to meet the actual needs of a large number of users for real-time service response. It has certain guiding and reference significance for the follow-up construction of related aerospace measurement and control centers. © 2021 IEEE.

关键词： Cloud computing architecture

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Modeling pre-Exascale AMR parallel I/O Workloads via Proxy Applications

Modeling pre-Exascale AMR Parallel I/O Workloads via Proxy A...

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IEEE international Symposium on parallel and distributed Processing Workshops and Phd Forum (IPDPSW)

作者： William F Godoy Jenna Delozier Gregory R Watson Computer Science and Mathematics Division Oak Ridge National Laboratory Oak Ridge TN USA College of Computing Georgia Institute of Technology Atlanta GA USA

ISBN: (数字)9781665497473

ISBN: (纸本)9781665497480

The present work investigates the modeling of preexascale input/output (I/O) workloads of Adaptive Mesh Refinement (AMR) simulations through a simple proxy application. We collect data from the AMReX Castro framework running on the Summit supercomputer for a wide range of scales and mesh partitions for the hydrodynamic Sedov case as a baseline to provide sufficient coverage to the formulated proxy model. The non-linear analysis data production rates are quantified as a function of a set of input parameters such as output frequency, grid size, number of levels, and the Courant-Friedrichs-Lewy (CFL) condition number for each rank, mesh level and simulation time step. Linear regression is then applied to formulate a simple analytical model which allows to translate AMReX inputs into MACSio proxy I/O application parameters, resulting in a simple “kernel” approximation for data production at each time step. Results show that MACSio can simulate actual AMReX nonlinear “static” I/O workloads to a certain degree of confidence on the Summit supercomputer using the present methodology. The goal is to provide an initial level of understanding of AMR I/O workloads via lightweight proxy applications models to facilitate autotune data management strategies in anticipation of exascale systems.

关键词： Analytical models Adaptation models Time-frequency analysis Production Machine learning Predictive models Hydrodynamics

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