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检索条件"任意字段=9th International Conference on Algorithms and Architectures for Parallel Processing"

共 2827 条记录，以下是491-500 订阅

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Performance improvement of deep learning architectures for phonocardiogram signal classification using fast fourier transform 9

Performance improvement of deep learning architectures for p...

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9th international conference on Advances in Computing and Communication, ICACC 2019

作者： Gopika, P. Sowmya, V. Gopalakrishnan, E.A. Soman, K.P. Amrita Vishwa Vidyapeetham Center for Computational Engineering and Networking Coimbatore India

ISBN: (纸本)9781728155234

Phonocardiogram known as PCG plays a significant role in the early diagnosis of cardiac abnormalities. Phonocardiogram can be used as initial diagnostics tool in remote applications due to its simplicity and cost effectiveness. Instead of disease specific approach, the proposed work aims for the single architecture that could diagnose different cardiac abnormality from the PCG signals collected from various sources. Our study also shows the effectiveness of using Fast Fourier Transform (FFT) in signal processing applications. It avoids the trivial preprocessing and feature extraction mechanisms with the promising results. © 2019 IEEE.

关键词： Fast Fourier transforms

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9th international conference on Supercomputing, ISUM 2018

9th International Conference on Supercomputing, ISUM 2018

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9th international conference on Supercomputing, ISUM 2018

ISBN: (纸本)9783030104474

the proceedings contain 19 papers. the special focus in this conference is on Supercomputing. the topics include: High performance open source lagrangian oil spill model;fast random cactus graph generation;theoretical calculation of photoluminescence spectrum using DFT for double-wall carbon nanotubes;computational study of aqueous solvation of vanadium (V) complexes;3D image reconstruction system for cancerous tumors analysis based on diffuse optical tomography with blender;sea-surface temperature spatiotemporal analysis for the gulf of California, 1998–2015: Regime change simulation;use of high performance computing to simulate cosmic-ray showers initiated by high-energy gamma rays;data augmentation for deep learning of non-mydriatic screening retinal fundus images;decision support system for urban flood management in the cazones river basin;automatic code generator for a customized high performance microprocessor simulator;use of containers for high-performance computing;generic methodology for the design of parallel algorithms based on pattern languages;a parallelized iterative closest point algorithm for 3D view fusion;Evaluation of orangeFS as a tool to achieve a high-performance storage and massively parallel processing in HPC cluster;many-core parallel algorithm to correct the gaussian noise of an image;amdahl’s law extension for parallel program performance analysis on intel turbo-boost multicore processors;Traffic sign distance estimation based on stereo vision and GPUs.

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Anytime Algorithm for Cell-based DBSCAN by Connecting Randomly Selected Cells

Anytime Algorithm for Cell-based DBSCAN by Connecting Random...

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IIAI international conference on Advanced Applied Informatics (IIAIAAI)

作者： Tatsuhiro Sakai Keiichi Tamura Hajime Kitakami Toshiyuki Takezawa Institute of Science and Engineering Academic Assembly Shimane University Shimane Japan Graduate School of Information Sciences Hiroshima City University Hiroshima Japan

ISBN: (纸本)9781728173986

With the growing interest in big data, speed-up techniques for clustering are required. the density-based spatial clustering of applications with noise (DBSCAN) has been well known in database domains. Since the DBSCAN algorithm was first proposed, several speed-up methods have been introduced. In the previous work, cell-based DBSCAN as a fast DBSCAN algorithm that divides the whole dataset into smaller cells and connects them to form clusters was proposed. In this study we propose a novel clustering algorithm called anytime algorithm for cell-based DBSCAN. the proposed algorithm connects some randomly selected cells and calculates the clustering result at high speed. Next, it repeats this process, which improves the accuracy of clustering, thereby yielding the precise results. Experimental results demonstrated that the proposed algorithm can calculate the clustering results with high accuracy at high speed.

关键词： Clustering algorithms parallel processing Big Data Spatial databases Informatics

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VLSI architectures for 8 bit data comparators for rank ordering image applications 8

VLSI architectures for 8 bit data comparators for rank order...

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8th IEEE international conference on Communication and Signal processing, ICCSP 2019

作者： Sindhu, E. Vasanth, K. Department of VLSI system Design Vidya Jyothi Institute of Technology Telanagana Hyderabad500075 India Vidya Jyothi Institute of Technology Telangana Hyderabad500075 India

ISBN: (纸本)9781538675953

the main objective of the proposed work is to develop a new Data comparator which gives an economical solution for sorting / Rank ordering networks on the basis of speed, power, and area. the proposed work comprises a design of six different comparators for 8 -bit comparison. the performances of these six different comparators were targeted for XCV1000-4bg560 using Xilinx 7.1i compiler tool using VHDL. It was found that Carry select logic based data comparator requires less area and suitable for reduced area applications. the Conventional bit wise logic based data comparator operated with less delay. Hence this architecture can be used for high speed application. the Twos complement using binary to excess one data converter consumes less power. Hence a twos complement based implementation is suitable for low power implementations. the Different architecture for data comparators were applied on parallel and pipelined architecture of modified shear sorting. these three architectures were compared with other existing median finding architectures. It was found that the CSLA based parallel architecture, CBC based pipelined architecture and 2BEC based pipelined architecture were stand out in area, speed and power when compared with conventional median finding algorithms. © 2019 IEEE.

关键词： Comparators (optical)

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Research on Web Service Selection Based on parallel Skyline Algorithm 9

Research on Web Service Selection Based on Parallel Skyline ...

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IEEE 9th international conference on Electronics Information and Emergency Communication (ICEIEC)

作者： Liang Xinmei Luqin Qilu Univ Technol Shandong Acad Sci Sch Comp Sci & Technol Jinan Shandong Peoples R China

ISBN: (纸本)9781728111902

With the continuous development of the Internet, there are many web services with the same functional attributes but different functional attributes. It is urgent to find a web service that can satisfy itself quickly and efficiently from the massive web service data. this paper improves the traditional Skyline algorithm, divides the web service data set into regions, greatly reduces the data points without dominance, and saves memory usage. the improved Skyline algorithm can significantly improve the speed of Web service selection. However, the improved Skyline algorithm will still have insufficient computing resources when processing massive Web service data, resulting in a significant decrease in computing speed and even computer jam. In view of the above situation, this paper will parallelize the improved Skyline algorithm and parallelize the improved Skyline algorithm through the Spark platform. Experiments show that the parallelized Skyline algorithm can better handle massive Web service data.

关键词： Skyline big data Spark Hadoop parallelization

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ctapipe: a low-level data processing framework for the Cherenkov Telescope Array 36

ctapipe: a low-level data processing framework for the Chere...

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36th international Cosmic Ray conference (ICRC)

作者： Kosack, K. Peresano, M. CEA Paris Saclay Astrophys Dept Paris France

the low-level data processing of the Cherenkov Telescope Array (CTA) and indeed all other existing Cherenkov Telescopes can be broken into four general steps: 1) the processing of air-shower event image time-series, 2) the stereo reconstruction of the incident air showers, and 3) the discrimination of gamma-ray induced showers from those from cosmic rays 4) the determination of the overall system response. the final output for science users is a list of reconstructed gamma-ray-like events and their associated parameters, along with a set of instrumental response functions needed for doing astrophysics. We present a python-based framework, ctapipe, for writing the algorithms required for these processing steps along with a reference prototype pipeline. the code is written with a focus on simplicity and usability by developers with a diverse range of skill sets, and leverages existing code from the science community (AstroPy, SciPy/NumPy, SciKit-Learn, etc). this concept is intended to be a prototype for the final CTA low-level data processing pipeline, allowing physicists to quickly explore low-level Cherenkov telescope data and develop new algorithms. thanks to the framework modularity, computer engineers and data scientists will be able to simultaneously optimize the algorithms and parallelize them using modern computing and big-data architectures to support the high data volumes of CTA.

关键词： Gamma rays

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Extended Hierarchical Temporal Memory for Motion Anomaly Detection 9th

Extended Hierarchical Temporal Memory for Motion Anomaly Det...

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9th Annual international conference of the Biologically-Inspired-Cognitive-architectures-Society (BICA) on Biologically Inspired Cognitive architectures (BICA) held as Part of the Joint Multi-conference on Human-Level Artificial Intelligence (HLAI)

作者： Daylidyonok, Ilya Frolenkova, Anastasiya Panov, Aleksandr, I Natl Res Univ Higher Sch Econ Moscow Russia Russian Acad Sci Fed Res Ctr Comp Sci & Control Moscow Russia

ISBN: (纸本)9783319993164;9783319993157

this paper describes the application of hierarchical temporal memory (HTM) to the task of anomaly detection in human motions. A number of model experiments with well-known motion dataset of Carnegie Mellon University have been carried out. An extended version of HTM is proposed, in which feedback on the movement of the sensor's focus on the video frame is added, as well as intermediate processing of the signal transmitted from the lower layers of the hierarchy to the upper ones. By using elements of reinforcement learning and feedback on focus movement, the HTM's temporal pooler includes information about the next position of focus, simulating the human saccadic movements. processing the output of the temporal memory stabilizes the recognition process in large hierarchies.

关键词： Anomaly detection Hierarchical temporal memory Video processing HTM feedback Hierarchical learning

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Implementation of ZYNQ for image defogging

Implementation of ZYNQ for image defogging

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IEEE Joint international Information Technology and Artificial Intelligence conference (ITAIC)

作者： Chao Zhang Shujie Bi Tao Jiang Jing Wang Weiming Mao School of Physics and Electronic Information Yunnan Normal University Kunming China Yunnan Normal University Kunming Yunnan People’s Republic of China

ISBN: (数字)9781728152448

ISBN: (纸本)9781728152455

In this paper, we propose a Zynq-based defogging algorithm for low-light images, firstly, we explain the background and significance of this topic, then we study several algorithms in Retinex, analyze and compare them to get the ideal algorithm. the VDMA module sends data to the 7-inch LCD LCD module (AN070) for control display; then use the mainstream pipeline design, parallel processing for the best FPGA to efficiently implement the Retinex-based image de-fogging algorithm porting, which mainly uses Vivado HLS to generate Retinex algorithm IP cores, including From RGB to HSV color space conversion, linear stretching of the S-space part of the attribute parameters and V-space part of the logarithmic operation, Gaussian fuzzy and other related algorithm modules, and finally download the debugging, optimization and summary of the system de-mist effect of various aspects of the algorithm.

关键词： System performance Pipelines Process control parallel processing Liquid crystal displays Field programmable gate arrays Optimization

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Research and Implementation of High Performance Traffic processing based on Intel DPDK 9

Research and Implementation of High Performance Traffic Proc...

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9th international conference on parallel architectures, algorithms and Programming (PAAP)

作者： Zhu, Wenjun Li, Peng Luo, Baozhou Xu, He Zhang, Yujie Nanjing Univ Posts & Telecommun Sch Comp Sci Nanjing 210003 Jiangsu Peoples R China Nanjing Univ Posts & Telecommun Sch Comp Sci Jiangsu High Technol Res Key Lab Wireless Sensor Nanjing 210003 Jiangsu Peoples R China

ISBN: (纸本)9781538694039

With the rapid development of Internet and the continuous rise of network users, the network traffic in various regions is increasing rapidly. In the face of a large number of high speed and high throughput of the network environment, traditional packet capture methods and processing capabilities cannot reach the corresponding speed, which results in severe packet loss. this paper focuses on a high-performance packet acquisition and distribution method to break through the performance bottleneck of universal servers and network cards. this paper studies a packet capture method based on DPDK platform, and uses the processing of hash value in RSS to improve the efficiency of data packet distribution, which realizes the process from performance acquisition to efficiently multi-core parallel processing. this method can effectively reduce packet loss and improve the data packet processing rate. It can also reduce resource waste and network overhead for traffic capture and distribution. Preliminary experiments show that DPDK-based traffic processing has obvious advantages over PF-RING and Netmap in data processing speed.

关键词： DPDK Traffic processing Distribution Multi-core parallel processing

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Principal Component Analysis with Quantum Whale Optimization Algorithm

Principal Component Analysis with Quantum Whale Optimization...

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IEEE Joint international Information Technology and Artificial Intelligence conference (ITAIC)

作者： Kairui Luo Zan Yang Minhui Ye Yuheng Tang Dan Li Yidan Xing Wei Nai Tongji Zhejiang College Jiaxing China Faculty of Science Tongji Zhejiang College Jiaxing China

ISBN: (数字)9781728152448

ISBN: (纸本)9781728152455

Principal component analysis (PCA) is a classical supervised linear dimension reduction algorithm in machine learning. PCA solves the optimal dimension reduction direction by maximizing the variance of projection points. the classical methods to realize optimization are gradient ascend method or stochastic gradient ascend method depending on gradient information. However, the above methods are easy to fall into the trap of local extremum, which is not conducive to global optimization. In this paper, the quantum whale algorithm is introduced into the optimization part of PCA, which enhances the parallelism and globality of optimization, and gets rid of the dependence on gradient.

关键词： Dimensionality reduction Machine learning algorithms Search methods Whales parallel processing Optimization Principal component analysis

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