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

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Assembly Line Balancing with Collaborative Robots Under Uncertainty of Human processing Times

Assembly Line Balancing with Collaborative Robots Under Unce...

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international conference on Control, Decision and Information Technologies (CoDIT)

作者： Ilhem Slama Taha Arbaoui Amir Nourmohammadi Masood Fathi LIST3N Université de Technologie de Troyes Troyes France Division of Intelligent Production Systems University of Skövde Skövde Sweden Division of Industrial Engineering and Management Uppsala University Uppsala Sweden

this paper studies the assembly line balancing problem with collaborative robots in light of recent efforts to implement collaborative robots in industrial production systems under random processing time. A stochastic version with uncertain human processing time is considered for the first time. the issue is defined by the potential for simultaneous human and robot task execution at the same workpiece, either in parallel or in collaboration. We provide stochastic mixed-integer programming based on Monte Carlo sampling approach for the balancing and scheduling of collaborative robot assembly lines for this novel issue type. In order to minimise the line cost including fixed workstation operating costs and resource costs caused by exceeding cycle time, the model determines both the placement of collaborative robots at stations and the distribution of work among humans and robots.

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parallel Identification of Unique Sequences in Nuclear Structure Calculations 1

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14th international conference on parallel processing and Applied Mathematics, PPAM 2022

作者： Langr, Daniel Dytrych, Tomáš Faculty of Information Technology Czech Technical University in Prague Thákurova 9 Praha16000 Czech Republic Nuclear Physics Institute Czech Academy of Sciences Řež 130 Řež25068 Czech Republic Department of Physics and Astronomy Louisiana State University Baton RougeLA70803 United States

ISBN: (数字)9783031304453

ISBN: (纸本)9783031304446

Reducing the set of sequences into the set of sequences that are unique can save a lot of memory space in computer programs. We study this problem on the symmetry-adapted no-core shell model (SA-NCSM) nuclear structure calculations, where duplicated sequences of different kinds naturally emerge in the data of the basis of the Hilbert space physically relevant to a given nucleus. For a fast solution of this problem on multicore architectures, we propose and present a multithreaded algorithm suitable for high performance computing (HPC) environments. Furthermore, we provide an experimental evaluation of this algorithm and show that, in practice, it can significantly reduce the time required to identify unique sequences in a real-world application. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Software architecture

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Experimental Research of Wideband Robust Capon Beamforming Based on Focusing Transform for Circular Array

Experimental Research of Wideband Robust Capon Beamforming B...

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IEEE international conference on Signal and Image processing (ICSIP)

作者： Yue Liu Le Cheng BingBing Zhang Zhengliang Hu College of Meteorology and Oceanology National University of Defense Technology Changsha China School of Information Science and Technology Southwest Jiaotong University Chengdu China

ISBN: (数字)9798350350920

ISBN: (纸本)9798350350937

the circular array is widely used for wideband acoustic source localization due to its 360° isotropic azimuthal response. Adaptive beamformer may degrade significantly in practical scenarios because of array steering vector (ASV) mismatches and snapshot deficiency. In this study, the wideband robust Capon beamforming (WBRCB) approach combined the robust Capon beamforming (RCB) with focusing transform is presented. It is found that the WBRCB converges in a shorter time due to the higher statistical degree of freedom of the focusing cross-spectral density matrix. Meanwhile, WBRCB has a lower computational complexity. Experimental results show the effectiveness of the presented beamforming approach on circular array.

关键词： Location awareness Array signal processing Focusing Transforms Interference parallel processing Lakes

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Species Classification and Counter for Mixed-Species Bird Flock Using ResNet9 Network and YOLOv5 Object Detection Algorithm

Species Classification and Counter for Mixed-Species Bird Fl...

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international conference on Business and Industrial Research (ICBIR)

作者： Ma. Christina R. Navarro Ivan Andrei A. Abalos Jemyr Ann P. Prado Gleizel C. Bautista Jerome T. Alvez Gene Justine P. Rosales Kristin Gel V. Santos Computer Science Department Adamson University Manila Philippines IT and IS Department Adamson University Manila Philippines

Bird9;s population is essential to ecology and conservation initiatives. However, proper categorization and counting in mixed-species flocks presents significant challenges because of the complexity due to increasi... 详细信息

ISBN: (数字)9798350383027

ISBN: (纸本)9798350383034

Bird's population is essential to ecology and conservation initiatives. However, proper categorization and counting in mixed-species flocks presents significant challenges because of the complexity due to increasing number of different species with diverse looks. Deep learning and computer vision techniques are used to automate the procedure to overcome these obstacles. this paper discusses the method to develop a graphic analyzing system for detection, classifying of bird species and counting, leveraging the ResNet9 network and YOLOv5 algorithm. Convolutional neural network (CNN) is also utilized for image classification process wherein a pre trained architectures named ResNet9 to identify the bird species. It improves its network feature extraction ability by overcoming the vanishing gradient as it skips the convolutional layer and can stack hundreds of layers. the models were trained using images collected from ***. Pre-processing of the ResNet9 model involves oversampling and image augmentation techniques to handle imbalanced data. A recall of 97.67% for the YOLOv5 and 98.12% and 95.34% for the validation and testing of ResNet9, show how well the network and algorithm are applied to accurately classify bird species and provide counts of the bird species within flocks. With this, the study will be useful in a bird monitoring environment.

关键词： YOLO Graphics Biological system modeling Birds Image augmentation Classification algorithms Convolutional neural networks Monitoring Testing Image classification

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GPU-Accelerated Matrix Exponent for Solving 1D Time-Dependent Schrödinger Equation 9th

GPU-Accelerated Matrix Exponent for Solving 1D Time-Depende...

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9th Russian Supercomputing Days international conference, RuSCDays 2023

作者： Choi, Yea Rem Stegailov, Vladimir HSE University Moscow Russia Joint Institute for High Temperatures of RAS Moscow Russia

ISBN: (纸本)9783031494314

Non-adiabatic electron-ion quantum dynamics is still an area of many unresolved problems even for such simple systems as the H 2+ molecular ion. Mathematical modelling based on time-dependent Schrödinger equation (TDSE) is an important method that can provide better understanding of these phenomena. In this work, we present TDSE solution for 1D TDSE that describes non-adiabatic electron-ion quantum dynamics for the simplified H 2+ model. For solving TDSE, we use the real-space representation and the matrix exponent method that is quite computationally expensive but is free from usual symmetry-based simplifications. For this purpose, we make use of the very high performance of modern Nvidia V100/A100 GPUs and deploy our parallel multi-GPU matrix multiplication algorithm. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Graphics processing unit

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Design and Analysis of Proposed Smartphone-based Distributed parallel processing System

Design and Analysis of Proposed Smartphone-based Distributed...

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international Engineering conference (IEC)

作者： Nashma Taha Muhammed Zryan Najat Rashid Subhi R. M. Zeebaree Yousif Sufyan Jghef Rowaida Khalil Ibrahim Teba Mohammed Ghazi Sami IT Department Sulaimani Polytechnic University Sulaymani Iraq Computer Network Department Sulaimani Polytechnic University Sulaymani Iraq Energy Eng. Department Duhok Polytechnic University Duhok Iraq Computer Eng. Department Knowledge University Erbil Iraq Computer Science Department University of Zakho Duhok Iraq

Online storage and use of digital assets and applications are both aspects of cloud computing. through a computer network, distributed information systems store and transmit data. Data and effort have both grown for studying and keeping track of outcomes. Cloud-based parallel processing techniques must be improved. Our research hastens the resolution of interactive composite jobs. In this innovative architecture, cell phones act as servers for distributed parallel processing and cloud computing. Users with restricted availability could find the update useful for completing challenging jobs. the recommended strategy is supported by cloud computing, which may expand to infinity servers (webserver). Servers between clients and servers are automatically registered by web servers. Cloud storage and client-side matrices (web server). To ensure timely completion, the server distributes matrix algebra assignments to all subscribed workstations. Before transmitting results to the user, the server uploads them to the cloud. A large number of sets of two-dimensional matrices were requested from the user, and the responses were compared to the total number of servers that were available.

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parallel solvers comparison for an inverse problem in fractional calculus 14

Parallel solvers comparison for an inverse problem in fracti...

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14th IADIS international conference Computer Graphics, Visualization, Computer Vision and Image processing 2020, CGVCVIP 2020 and 5th IADIS international conference Big Data Analytics, Data Mining and Computational Intelligence 2020, BigDaCI 2020 and 9th IADIS international conference theory and Practice in Modern Computing 2020, TPMC 2020, Part of the 14th Multi conference on Computer Science and Information Systems, MCCSIS 2020

作者： De Luca, Pasquale Galletti, Ardelio Marcellino, Livia Department of Computer Science University of Salerno Fisciano Italy Department of Science and Technology University of Naples Parthenope Napoli Italy

ISBN: (纸本)9789898704214

High-Performance Computing (HPC) is a fundamental tool for improving the performance of many algorithms in terms of time, especially for large-scale problems. In the last years, various HPC architectures have been developed to quickly process data in many research areas and at the same time the HPC tools has become very important. In addition, the development of scientific libraries for parallel computing plays a key role in achieving better performance. In particular, thanks to the computational power of Graphic processing Units, themost popular and inexpensive accelerators, the parallel computing field has become almost a standard process for datamanagement. Hence, the porting of many standard numerical libraries on these architectures produced excellent results. In this work, we deal with a two-dimensional time fractional diffusion problem. More in detail, we analyze the performance of some parallel codes, specifically designed to solve it, implemented in different architectures. Moreover, a further GPU version is proposed and compared with the above implementations. © Proceedings of the 14th IADIS international conference Computer Graphics, Visualization, Computer Vision and Image processing 2020, CGVCVIP 2020 and Proceedings of the 5th IADIS international conference Big Data Analytics, Data Mining and Computational Intelligence 2020, BigDaCI 2020 and Proceedings of the 9th IADIS international conference theory and Practice in Modern Computing 2020, TPMC 2020 - Part of the 14th Multi conference on Computer Science and Information Systems, MCCSIS 2020. All rights reserved.

关键词： Graphics processing unit

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parallel Channel Separate Attention Network for Concealed Object Detection in Millimeter-Wave Images

Parallel Channel Separate Attention Network for Concealed Ob...

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6th international conference on Intelligent Computing and Signal processing (ICSP)

作者： Tang Li Zhenhong Chen Xin Wen Liang Chen Shengkang Zhang School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Institute of Radio Metrology and Measurement Beijing China

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

the active millimeter-wave scanner plays an increasingly pivotal role in public safety by employing a non-contact method to detect contraband concealed beneath human clothing. However, millimeter-wave images encounter challenges such as low signal-to-noise ratio, limited resolution, and suspicious targets being small in size, when compared to optical images. To address these challenges and improve detection performance, this paper introduces a parallel Channel Separate Attention (PCSA) method. Specifically, we propose a parallelized and channel-separated attention module to enhance the extraction ability of features pertaining to minute targets. this module is integrated into the YOLOv8 backbone network, namely PC SA-YOLO. Moreover, we incorporate high-frequency information from the original image into the network input to provide preliminary guidance. Extensive experiments conducted on millimeter-wave datasets demonstrate that our proposed method outperforms existing state-of-the-art detection techniques.

关键词： Integrated optics Millimeter wave technology Object detection Feature extraction Optical imaging Public security Spatial resolution Optical signal processing Signal resolution Signal to noise ratio

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A Fire Smoke Segmentation Method Based on Dual Path Encoder and Edge Enhancement

A Fire Smoke Segmentation Method Based on Dual Path Encoder ...

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6th international conference on Intelligent Computing and Signal processing (ICSP)

作者： Hui Wang College of Computer Science and Technology Zhengzhou University of Light Industry Zhengzhou China

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

Smoke production is a precursor to fire, and smoke is more valuable to study than flames in disaster monitoring and prevention. Smoke segmentation is important for the study of smoke characteristics, based on the traditional method of smoke segmentation accuracy is limited and susceptible to the influence of the scene. Deep learning-based segmentation models usually rely on a large classification backbone network, which ignores the local details and global contrast information that are relatively important for smoke segmentation when implementing deeper architectures, and the segmentation of smoke is not satisfactory. In this article, a dual-encoder and edge-enhanced fire smoke segmentation method is proposed based on U 2 -Net, which extracts and fuses contextual and multi-scale information to realize the segmentation of smoke body, and at the same time, uses the edge-enhanced network to realize the extraction and enhancement of smoke edge information, which makes the model get a huge enhancement in the segmentation accuracy, segmentation precision, and edge segmentation. Test results indicate the model's mIoU peaks at 91.18% and stabilizes at 91.09%, mPA reaches 96.96%, MAE drops to 0.02, and MaxF1 attains 94.37%, surpassing existing smoke segmentation models. this novel method excels in fire smoke segmentation, vital for smoke characterization research.

关键词： Measurement Accuracy Fuses Prevention and mitigation Fires Production Signal processing Feature extraction Data mining Monitoring

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30th international conference on parallel and Distributed processing Techniques, PDPTA 2024, held as part of the World Congress in Computer Science, Computer Engineering and Applied Computing, CSCE 2024

30th International Conference on Parallel and Distributed Pr...

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30th international conference on parallel and Distributed processing Techniques, PDPTA 2024, held as part of the World Congress in Computer Science, Computer Engineering and Applied Computing, CSCE 2024

ISBN: (纸本)9783031856372

the proceedings contain 24 papers. the special focus in this conference is on parallel and Distributed processing Techniques. the topics include: parallel N-Body Performance Comparison: Julia, Rust, and More;REFT: Resource-Efficient Federated Training Framework for Heterogeneous and Resource-Constrained Environments;An Efficient Data Provenance Collection Framework for HPC I/O Workloads;using Minicasts for Efficient Asynchronous Causal Unicast and Byzantine Tolerance;a Comparative Study of Two Matrix Multiplication algorithms Under Current Hardware architectures;Is Manual Code Optimization Still Required to Mitigate GPU thread Divergence? Applying a Flattening Technique to Observe Performance;towards Automatic, Predictable and High-Performance parallel Code Generation;Attack Graph Generation on HPC Clusters;analyzing the Influence of File Formats on I/O Patterns in Deep Learning;inference of Cell–Cell Interactions through Spatial Transcriptomics Data Using Graph Convolutional Neural Networks;natural Product-Like Compound Generation with Chemical Language Models;improved Early–Modern Japanese Printed Character Recognition Rate with Generated Characters;Improved Method for Similar Music Recommendation Using Spotify API;Reconfigurable Virtual Accelerator (ReVA) for Large-Scale Acceleration Circuits;Building Simulation Environment of Reconfigurable Virtual Accelerator (ReVA);vector Register Sharing Mechanism for High Performance Hardware Acceleration;Efficient Compute Resource Sharing of RISC-V Packed-SIMD Using Simultaneous Multi-threading;introducing Competitive Mechanism to Differential Evolution for Numerical Optimization;hyper-heuristic Differential Evolution with Novel Boundary Repair for Numerical Optimization;jump Like a Frog: Optimization of Renewable Energy Prediction in Smart Gird Based on Ultra Long Term Network;vision Transformer-Based Meta Loss Landscape Exploration with Actor-Critic Method;Fast Computation Method for Stopping Condition of Range Restricted

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