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Abacus: a service-oriented programming language for grid applications

Abacus: a service-oriented programming language for grid app...

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IEEE international conference on Services computing (SCC)

作者： Xiaoning Wang Lijuan Xiao Wei Li Haiyan Yu Zhiwei Xu Graduate School of Chinese Academy of Sciences Beijing China Institute of Computing Technology Chinese Academy and Sciences Beijing China

This paper presents Abacus, a service-oriented programming language designed for the development of grid applications. Abacus considers that all the grid resources constitute a unified logical address space, where each memory cell holds a resource in the form of a service, and a grid application solves a problem by operating on these memory cells. Abacus allows programmers to concentrate on the logic of their applications, such as service implementation logic, service invocation logic, and glue logic. Low-level details such as resource distribution, resource binding, and service deployment are supported by the compiler and the runtime system. With such virtualization techniques, Abacus helps to enhance the productivity of programmers in developing grid applications.

关键词： Computer languages Logic programming Programming profession grid computing Programming environments Writing Resource management Application virtualization Productivity Collaboration

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Hybrid EEMD-WOA-LSTM model for enhanced power load prediction

Hybrid EEMD-WOA-LSTM model for enhanced power load predictio...

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2024 international conference on Algorithms, High Performance computing, and Artificial Intelligence, AHPCAI 2024

作者： Chen, Yuwei Zhou, Jing Lin, Shuang Yao, Wenxu State Grid Corporation of China Fuzhou350108 China Fujian Power Co. Ltd Electric Power Research Institute Fuzhou350108 China

ISBN: (纸本)9781510685840

This paper investigates power load forecasting models and introduces an advanced method that integrates Ensemble Empirical Mode Decomposition (EEMD), Whale Optimization Algorithm (WOA), and Long Short-Term Memory neural network (LSTM). The proposed EEMD-WOA-LSTM model is validated through experiments, demonstrating superior prediction accuracy and efficiency compared to traditional methods, particularly in managing nonlinear and non-stationary data. The model outperforms traditional LSTM and WOA-LSTM models in various evaluation metrics, showing a closer alignment with actual values when handling complex load data. Additionally, the paper discusses future research directions, such as model optimization, multi-source data fusion, real-time prediction systems, and extending applications to broader areas. This study not only highlights the significant potential of the EEMD-WOA-LSTM model in power load forecasting but also offers valuable technical references for the intelligent transformation of the power industry, aiming to develop more advanced and practical solutions for smart grids and related fields. © 2024 SPIE.

关键词： Smart power grids

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Validity Detection of Kernel Address of Embedded Operating System in Intelligent Electricity Meter 5

Validity Detection of Kernel Address of Embedded Operating S...

引用

5th IEEE international conference on Power, Intelligent computing and Systems, ICPICS 2023

作者： Wang, Zhiqiang Du, Jun Wang, Xiang Zang, Zhicheng Liu, Na Yi, Ling Beijing Smartchip Microelectronics Technology Co. Ltd. Beijing China State Grid Corporation of China Beijing China

ISBN: (纸本)9798350333442

Currently, the business applications of smart electricity meters are developed based on the interfaces provided by the operating system. According to different business divisions, smart energy meters have developed multiple business application apps. When developing each app, the operating system automatically assigns addresses based on the corresponding configuration information, which not only protects the security of the operating system but also ensures that different apps do not affect each other. However, the automatic address assignment function for the energy meter operating system is mainly tested indirectly through business development, and no targeted and systematic testing method has been formed. Therefore, this paper proposes a detection method applicable to the validation of addresses in the embedded operating system kernel of smart electricity meters. This method detects whether the running address of a single app goes out of range, effectively avoiding system crashes caused by a single app and thereby improving the stability, reliability, and robustness of the micro-kernel operating system. © 2023 IEEE.

关键词： Electric measuring instruments

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The Role of National Research and Education Networks Providing Connectivity and Advanced Network Services to Virtual Communities in Collaborative R&E Projects. CUDI: The Mexican Case Part 1 6th

The Role of National Research and Education Networks Providi...

引用

6th international conference on Supercomputing in Mexico (ISUM)

作者： Jalife Villalon, Salma Leticia Lopez Hermosa, Carlos Casasus Corp Univ Desarrollo Internet AC Red Nacl Invest & Educ Mexico Mexico City DF Mexico

ISBN: (纸本)9783319322438;9783319322421

This paper describes the role of National Research and Education Networks (NRENs) and their aim to provide a seamless, large scale, high-speed, low-latency network to accelerate scientific and education discovery for national, regional or global collaborative projects that are dependent on the use of modern high performance distributed computing systems (HPDCS) to process mathematical models, produce new knowledge and drive innovation when resolving complex problems. NRENs have become the mainstream of communication and collaboration to integrate the efforts of large geographically distributed teams of Virtual Communities (VC) that - train, teach and learn-, -create, use and share-knowledge, data, information and communications technology resources (e.g. computer and information systems, middleware, tools, instruments, data sets, repositories, applications and services) building e-infrastructures necessary to meet the collaborative projects' goals. The paper focuses on the current status of the Mexican NREN: CUDI, its future organization and political support, necessary to provide seamless, large scale, high-speed, low latency and secure national backbone and international links providing connectivity, advanced network services and technical support to VCs and their e-infrastructures in collaborative R&E projects within the country, the LAC region and worldwide.

关键词： National Research and Education Networks NREN HPDCS grid computing High Performance computing Cloud computing e-infrastructures

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international conference on computing, Intelligence and Data Analytics, ICCIDA 2022

International Conference on Computing, Intelligence and Data...

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international conference on computing, Intelligence and Data Analytics, ICCIDA 2022

ISBN: (纸本)9783031270987

The proceedings contain 44 papers. The special focus in this conference is on computing, Intelligence and Data Analytics. The topics include: Preface;Priority-Based Pollution Management ITS;security Issues for Banking Systems;smart Autonomous Bike Hardware Safety Metrics;demand Side Management Based Cost-Centric Solution for a grid Connected Microgrid System with Pico-Hydro Storage System;impact of Multimodal Model Complexity on Classification of Diabetic Retinopathy Level;secure Image Data Encryption Scheme for 5G Internet of Things applications;Symptom Based Health Status Prediction via Decision Tree, KNN, XGBoost, LDA, SVM, and Random Forest;Multiband Microstrip Elliptical Monopole Antenna Design with Mushroom-Like Loadings for DCS, 5G and Ku-Band applications;an IoT-Based Modular Avionics and Electrical System for Nanosatellite Systems;reinforcement Learning for Intrusion Detection;comparison of Small-Sized Deep Neural Network Models for Hyperspectral Image Classification;autonomous Mobile Robot Mapping and Exploration of an Indoor Environment;time-Sensitive Embedding for Understanding Customer Navigational Behavior in Mobile Banking;do Lunar Cycles Affect Bitcoin Prices?;Stock Price Prediction in Response to US Dollar Exchange Rate Using Machine Learning Techniques;A Service of RSU Communication in Internet of Vehicles (IoV) in Urban Environment;a Comparative Study on Subdural Brain Hemorrhage Segmentation;deep Learning Based Spectrum Sensing Method for Cognitive Radio System;Colour Image Encryption Based on HACS and Knuth-Durstenfeld Algorithm;Turkish Sign Language Recognition by Using Wearable MYO Armband;effects of Different Parameters on Sleep Quality;predictive Maintenance on Industrial Data Using Soft Voted Ensemble Classifiers;Medical Image Transmission Using a Secure Cryptographic Approach for IoMT applications;volume Forecasting in Supply Chain: A Mixed Study of Boosting and Prophet Algorithms;blockchain-Based System for Traceability of Counterfeit Med

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An evaluation of partitioners for parallel SAMR applications 7

引用

7th European conference on Parallel computing, Euro-Par 2001

作者： Chandra, Sumir Parashar, Manish TASSL/ECE Department Rutgers The State University of New Jersey 94Bret t Road PiscatawayNJ08854 United States

ISBN: (纸本)3540424954

This paper presents an experimental evaluation of a suite of dynamic partitioning/load-balancing techniques for adaptive grid hierarchies that underlie parallel structured adaptive mesh refinement applications. Partitioners evaluated include those included in popular software libraries such as GrACE, Vampire, and ParMetis. The overall goal of the research presented in the paper is an application-centric characterization of the partitioners as a function of the number of processors, problem size, and partitioning granularity. © Springer-Verlag Berlin Heidelberg 2001.

关键词： Computers

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A Multimodal Named Entity Recognition Model for Power Equipment Based on Deep Neural Network 3

A Multimodal Named Entity Recognition Model for Power Equipm...

引用

3rd international conference on Applied Mathematics, Modeling and Computer Simulation, AMMCS 2023

作者： Zhang, Qiang Song, Bochuan Zhao, Changwei Liu, Tongyang Zhang, Fengda Li, Zhuangzhuang State Grid Laboratory of Grid Advanced Computing and Applications State Grid Smart Grid Research Institute Co. Ltd. Beijing China State Grid Anhui Electric Power Research Institute Anhui China State Grid Shandong Electric Power Research Institute Jinan China

ISBN: (纸本)9781643684581

Digital empowerment of China's power energy sector is a key factor in increasing its economic and social benefits, and named entity recognition technology is the most fundamental and core task of information extraction technology in the digital empowerment process. Therefore, we propose a multimodal named entity recognition model PE-MNER for power equipment based on deep neural networks. Compared to text multimodality, text and image multimodality can use image information to supplement missing information in the text, thus enabling more accurate entity extraction. The model first obtains a BERT neural network through incremental training, and then extracts Chinese character features through the network. Then, a hierarchical visual prefix fusion network is used to fuse image information. From the comparative experimental results, it can be seen that the proposed model has the best performance compared to the benchmark model, with an improvement of 4.08%~7.20% in the F1 score compared to the benchmark model. © 2023 The Authors.

关键词： Deep neural networks

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Multi-preconditioned Domain Decomposition Methods in the Krylov Subspaces 6th

Multi-preconditioned Domain Decomposition Methods in the Kry...

引用

6th international conference on Numerical Analysis and applications (NAA)

作者： Ilin, Valery P. Novosibirsk State Univ Inst Computat Math & Math Geophys SB RA S Novosibirsk Russia

ISBN: (纸本)9783319570990;9783319570983

We consider the algebraic and geometric issues of the advanced parallel domain decomposition methods (DDMs) for solving very large non-symmetric systems of linear algebraic equations (SLAEs) that arise in the finite volume or the finite element approximation of the multi-dimensional boundary value problems on the non-structured grids. The main approaches in question for DDM include the balancing decomposition of the grid computational domain into parameterized overlapping or non-overlapping subdomains with different interface conditions on the internal boundaries. Also, we use two different sructures of the contacting the neigbour grid subdomains: with definition or without definition of the node dividers (separators) as the special grid subdomain. The proposed Schwarz parallel additive algorithms are based on the "total-flexible" multi-preconditioned semi-conjugate direction methods in the Krylov block subspaces. The acceleration of two-level iterative processes is provided by means of aggregation, or coarse grid correction, with different orders of basic functions, which realize a low-rank approximation of the original matrix. The auxiliary subsystems in subdomains are solved by direct or by the Krylov iterative methods. The parallel implementation of algorithms is based on hybrid programming with MPI-processes and multi-thread computing for the upper and the low levels of iterations, respectively. We describe some characteristic features of the computational technologies of DDMs that are realized within the framework of the library KRYLOV in the Institute of Computational Mathematics and Mathematical Geophysics, SB RAS, Novosibirsk. The technical requirements for this code are based on the absence of the program constraints on the degree of freedom and on the number of processor units. The conceptions of the creating the unified numerical envirement for DDMs are presented and discussed.

关键词： Multi-dimensional boundary value problems Domain decomposition Krylov subspaces Multi-preconditioning Coarse grid corection Scalable parallelism Hybrid programming Hierarchical memory

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Disparity estimation method of electric inspection robot based on lightweight neural network 6

Disparity estimation method of electric inspection robot bas...

引用

6th IEEE international conference on Intelligent computing and Signal Processing, ICSP 2021

作者： Yu, Hong Shen, Feng Electric Power Research Institute Yunnan Power Grid Co. Ltd Kunming China School of Instrument Science and Engineering Harbin Institute of Technology Harbin China

ISBN: (纸本)9780738143705

The image depth information can be used to understand the geometric relationship of image scenes, and has important applications in robots, scene understanding, three-xdimensional reconstruction and other fields. Recent work has proved that depth estimation from stereo RGB image pairs can be realized by convolution neural network. However, the mainstream depth estimation deep learning algorithms rely on patch-based Siamese networks, which lacks the ability to comprehensively utilize the context information and the environment texture information, and their performance is poor in complex regions and illposed regions. The working environment of electric inspection robot is complex and the occlusion problem is serious, so the classical methods are difficult to be directly applied. In addition, the real-time performance of neural network is very important for electric inspection robot. In this paper, a disparity estimation neural network for electric inspection robot is proposed, which consists of two main parts: PSMNet module and lightweight cutting module. Experiments show that the proposed method can be effectively applied to electric inspection robot. © 2021 IEEE.

关键词： Learning algorithms

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11th international conference on High-Performance computing Systems and Technologies in Scientific Research, Automation of Control and Production, HPCST 2021

11th International Conference on High-Performance Computing ...

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11th international conference on High-Performance computing Systems and Technologies in Scientific Research, Automation of Control and Production, HPCST 2021

ISBN: (纸本)9783030941406

The proceedings contain 32 papers. The special focus in this conference is on High-Performance computing Systems and Technologies in Scientific Research, Automation of Control and Production. The topics include: Mathematical Simulation of Coupled Elastic Deformation and Fluid Dynamics in Heterogeneous Media;numerical Modeling of Electric and Magnetic Fields Induced by External Source in Frequency Domain;improving the Heterogeneous computing Node Performance of the Desktop grid When Searching for Orthogonal Diagonal Latin Squares;visual Metamodeling with Verification Based on Surrogate Modeling for Adaptive computing;recognition Algorithms Based on the Selection of 2D Representative Pseudo-objects;applied Interval Analysis of Big Data Using Linear Programming Methods;parallel computing in Problems of Classification of Teenagers Based on Analysis of Digital Traces;identification of Key Players in a Social Media Based on the Kendall-Wei Ranking;using Time Series and New Information Technologies for Forecasting Sugarcane Production Indicators;Calculation of Activation Functions in FPGA-Based Neuroprocessors Using the Cordic Algorithm;software and Methodology for the Design of System Dynamics Models Based on the Situation-Activity Approach;architecture of an Intelligent Network Pyrometer for Building Information-Measuring and Mechatronic Systems;implementation of a Network-Centric Production Storage System in Distributed High-Performance computing Systems;internet of Things for Reducing Commercial Losses from Incorrect Activities of Personnel;method of Constructing the Assigned Trajectory of a Multi-link Manipulator Based on the "Programming by Demonstration" Approach;developing a Microprocessor-Based Equipment Control Panel for Rifle Sports Complexes;methods for Domain Adaptation of Automated Systems for Aspect Annotation of Customer Review Texts;testing Methods for Blockchain applications.

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