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检索条件"任意字段=1st International Conference on Parallel, Distributed and Grid Computing for Engineering"

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Proceedings of the 1st international conference on parallel, distributed and grid computing for engineering, PARENG 2009

Proceedings of the 1st International Conference on Parallel,...

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1st international conference on parallel, distributed and grid computing for engineering, PARENG 2009

ISBN: (纸本)9781905088270

The proceedings contain 44 papers. The topics discussed include: parallel moving particle calculations using the immersed boundary method;tuning a cluster system for high performance computing in engineering;OOFEM: a parallel finite element toolkit;balancing domain decomposition with nonlinear relocalization: parallel implementation for laminates;an iterative substructuring solver for the stokes equations;one- and two-level domain decomposition methods for nonlinear problems;grid computing applied to the boundary element method;unified kernel and user space distributed tracing for message passing analysis;a framework for parallel adaptive finite element computations with dynamic load balancing;implementation of a parallel fluid-structure interaction problem;solution of multibody system dynamics problems on client-server architectures with pipe data interchange;and generic design of a distributable class for integrated earthquake simulation.

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20th international conference on grid, Cloud, and Cluster computing, GCC 2024, 3rd international conference on Quantum Technologies, ICEQT 2024, and 21st international conference on Modeling, Simulation and Visualization Methods, MSV 2024, held as part of the World Congress in Computer Science, Computer engineering and Applied computing, CSCE 2024

20th International Conference on Grid, Cloud, and Cluster Co...

引用

20th international conference on grid, Cloud, and Cluster computing, GCC 2024, 3rd international conference on Quantum Technologies, ICEQT 2024, and 21st international conference on Modeling, Simulation and Visualization Methods, MSV 2024, held as part of the World Congress in Computer Science, Computer engineering and Applied computing, CSCE 2024

ISBN: (纸本)9783031858833

The proceedings contain 20 papers. The special focus in this conference is on grid, Cloud, and Cluster computing. The topics include: Scientific Workflow Provenance Management: System Requirements and a Reference Architecture;Enhancing Data Security with Decentralized Cloud storage: An IPFS Approach;learning Robust Observable to Address Noise in Quantum Machine Learning;evaluating Cost-Effective Reconfigurable Hardware for Quantum Simulation;an Efficient Quantum Solver for Multidimensional Partial Differential Equations;explaining the Design of the Quantum Fourier Transform;Optimizing Depth of Quantum Circuit for Generating GHZ states;a Comparative Analysis of Hybrid-Quantum Classical Neural Networks;NRQNN: The Role of Observable Selection in Noise-Resilient Quantum Neural Networks;studying the Impact of Quantum-Specific Hyperparameters on Hybrid Quantum-Classical Neural Networks;Eclipse Qrisp QAOA: Description and Preliminary Comparison with Qiskit Counterparts;federal Cloud computing Adoption Case study: A Retrospective Analysis as a Precursor to Optimized Quantum Adoption Methodologies;integrating Secure Quantum Digital Signature into Quantum Communications;methodology to Accelerate Federal Agency Adoption of Quantum Technologies;understanding Public Policy Effects on Alcohol-Related Behaviors and Outcomes Using System Dynamics;Performance Investigation of Small UAV Attitude Control Based on Optimized Nonlinear Dynamic Inversion;Prediction of 1st Year Registration Renewal of General-Use JP Domain Names with the Use of Machine Learning;data Clustering and Visualization with Recursive Max k-Cut Algorithm.

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Electric Vehicle Charging strategies for Solar Integrated Office Parking Lots 1

Electric Vehicle Charging Strategies for Solar Integrated Of...

引用

1st international conference on Sustainable Energy Technologies and Computational Intelligence, SETCOM 2025

作者： Verma, Hitesh Kumar Gupta, Nikhil Agrawal, Praveen Kumar Niazi, K.R. Swarnkar, Anil Mnit Department of Electrical Engineering Jaipur India

ISBN: (纸本)9798331520540

The environmental issues motivated the widespread usage of electric vehicles (EVs) across the world. However, the high penetration of EVs has also brought numerous operational, technical, and financial challenges. These issues can be resolved by using distributed energy resources such as solar energy for charging EVs. Moreover, a well-structured EV charging strategy can effectively utilize energy resources and reduce the charging burden on the grid. In this context, the study proposed three charging strategies for grid-connected solar-integrated office parking lots to align the EV charging demand with solar generation to reduce grid dependency, considering the seasonal variation of solar production. Further, the proposed strategies are compared with uncontrolled charging in terms of annual peak demand and energy imported and exported to the grid across all seasons. © 2025 IEEE.

关键词： distributed energy

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Intelligent Energy Management strategies for Renewable Energy Sources 1

Intelligent Energy Management Strategies for Renewable Energ...

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1st international conference on AIML-Applications for engineering and Technology, ICAET 2025

作者： Patil, Sangita Deotale, Disha Mali, Ramesh MIT School of Computing MIT ADT University Department of Electrical & Electronics Engineering Pune412201 India MIT School of Computing MIT ADT University Department of Computer Science & Engineering Pune412201 India

ISBN: (纸本)9798350355611

There have been several developments in renewable resources, standby sources of energy, and storage technologies. Because renewable sources are inconsistent, the best method to ensure supply continuity is to combine them with traditional energy to serve mini-grids or the isolated loads that are not linked to the main grid. In hybrid power system, many different energy sources are blended. Every time, effective and efficient Energy Management strategies (EMS) are necessary when more than a source of energy is employed to supply a given load. This strategy directs the energy flow via the supply chain. This is necessary not just for standalone hybrid systems, but for hybrid power system that are linked to the main network. The intelligent control of hybrid MG has been the subject of a large number of serious research projects. A comprehensive assessment of the approaches used by a number of writers in their research work on applying energy management approaches is conducted. standalone hybrid energy systems and the hybrid systems those are linked to the electrical grids are examples of these solutions. The aim of this paper is to give summary of various energy management schemes utilized in sustainable hybrid systems. Brief study is conducted for a number of freestanding and grid-linked hybrid system designs in order to make sure and find that which energy management technique that works well and will be applied for one renewable source is not always the best for another. © 2025 IEEE.

关键词： Hybrid power

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A Review Summary on Recent Trends in Application of Li-ion Battery in Power Delivery System 1

A Review Summary on Recent Trends in Application of Li-ion B...

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1st international conference on Sustainable Energy Technologies and Computational Intelligence, SETCOM 2025

作者： Samantaray, Soumyakanta Kayal, Partha Srivastava, Dev National Institute of Technology Electrical Engineering Department Assam Silchar India C.V. Raman Global University Electrical Engineering Department Bhubaneswar India

ISBN: (纸本)9798331520540

Electrical energy generation by conventional methods, their transportation to the load end, and the distribution among the electric consumers becomes complex day by day due to unscheduled insertion of generated power by distributed energy resources (DER). As most of the distributed generations are integrated into the distributed system (DS), the variability in power generation and consumption increases, and the DS operation becomes more vulnerable. The generation and injection of electricity from DER during the peak generation to the DS may not match the peak demand hours, which is a big challenge for the distribution operator in managing the power. Due to uncertain availability and power injection, the power purchased from the grid by the utility becomes irregular and adversely affects the DS economy. To address the said problem a detailed survey has been performed in this paper and the research opportunities are demonstrated considering the minimization of different attributes like SADPL, SADD, and SAENS by the optimal operation of the electric energy storage system like Li-ion BES. This study can lend a helping hand to researchers to investigate the electrical power distribution system's (PDS) techno-economic performance improvement with a reliable power supply, which could be a win-win solution for both utility and needy electric consumers. © 2025 IEEE.

关键词： distributed energy

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1st international conference on grid Services engineering and Management, GSEM 2004

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1st international conference on grid Services engineering and Management, GSEM 2004 held in conjunctionwith 5th international conference on Net.ObjectDays, NODE2004 and European conference on Web Services, ECOWS 2004

ISBN: (纸本)3540233016

The proceedings contain 11 papers. The special focus in this conference is on Architecture and Composition. The topics include: An early implementation of web services actors, programming a grid application to access astronomical databases;a scalable entry-level architecture for computational grids based on web services;enhancing java grid computing security with resource control;an approach to flexible application composition in a diverse software landscape;an ontology-based framework for semantic grid service composition;towards a metamodeling based method for representing and selecting grid services;towards a flexible trust model for grid environments;the AspectIX approach for a flexible and secure grid environment;a specification for security services on computational grids;grid service management by using remote maintenance shell and the grid-occam project.

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Kinematic Analysis of a Novel 3-UPrU parallel Mechanism 1

Kinematic Analysis of a Novel 3-UPrU Parallel Mechanism

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1st international conference on Intelligent Manufacturing and Cloud computing, ICIMCC 2024

作者： Liu, Jingfang Liu, Yao Tian, Shuai College of Mechanical and Energy Engineering Beijing University of Technology Beijing100124 China ZTE Corporation Tianjin300300 China

ISBN: (纸本)9781643685779

To meet the needs of the remote center-of-motion (RCM) in minimally invasive surgery, a novel 3-UPrU parallel mechanism is proposed that allows for two rotations around the incision site and movement in the direction of the incision point. The screw theory is used to solve the degree-of-freedom(DOF) of the mechanism, utilizing the limit boundary method solve the workspace of the mechanism. The research in this paper demonstrates that the mechanism has RCM motion properties, which can suit the needs of minimally invasive surgery implying that the mechanism has some application potential. © 2025 The Authors.

关键词： Degrees of freedom (mechanics)

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Fault-Tolerant Architectures for distributed Big Data Analytics 1

Fault-Tolerant Architectures for Distributed Big Data Analyt...

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1st international conference on Advances in Computer Science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Sudhakaran, Sunil Shah, Samarth Mishra, Manas Kumar Natarajan, Vignesh Bhatt, Jay Goel, Om Mahatma Gandhi University Kerala Kottayam India University at Albany AlbanyNY12222 United States G.L. Bajaj Institute of Technology and Management Department of Computer Science and Engineering Greater Noida201306 India Arizona State University AZ United States Northeastem University BostonMA United States ABES Engineering College U.P. Ghaziabad India

ISBN: (纸本)9798331518578

It has created challenges in the processing of data and analysis, which need to go beyond the traditional centralized architecture to solve the current data volume, speed, and types. To address these challenges, fault-tolerant architectures have become one of the keys to meeting the needs of distributed big data analytics. Failure is a normal part of systems;these architectures are meant to accommodate failures of individual components so that the entire system does not need to stop working or, worse, give false results. They make use of several nodes to operate and retain data in a distributed fashion, which supplies excessive scalability and fault tolerance. This means that even if some nodes fail, a fault-tolerant architecture can still provide redundancy by replicating data across many nodes, giving the system redundancy. Fault-tolerant architectures also utilize efficient data processing techniques like partitioning and data parallel processing, to achieve high performance. This allows real-time and near-real-time analysis of streaming data. © 2025 IEEE.

关键词： Data Analytics

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Electrical Energy Forecasting of Industrial Feeder from Rural Area Using Different Regression Techniques 1

Electrical Energy Forecasting of Industrial Feeder from Rura...

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1st international conference on AIML-Applications for engineering and Technology, ICAET 2025

作者： Patil, Rahul R. Gupta, Mukesh Kumar Bhadane, Kishor V. Suresh Gyan Vihar University Department of Electrical Engineering Jaipur India Amrutvahini College of Engineering Sangamner Department of Electrical Engineering Maharashtra India

ISBN: (纸本)9798350355611

We are aware about the role of machine learning in engineering domain increasing day by day to ease the life of human being. Now a day's population, globalization and industrialization are increasing which lead to increasing electrical consumption and due to this challenges for existing energy infrastructure increased. Entire world looking for the cheap, smooth, easily available and reliable energy resources to fulfill this challenges in efficient way at local level so energy generation and consumption will match to each other. To minimize carbon and other contaminant emissions, there is combination of renewable and clean distributed generation energy is increasing continuously. But integrating these energy into the grid may increase in electrical demand consumption enhance instability. With the help of Electrical load forecasting;we can reduce the grid instability and enhances the strength of power quality. Electrical energy forecasting by referring a historical data modelling plays a major role in base, peak electrical energy consumption, generation balancing;but forecasting an accurate electrical energy data is very tough work due to variation and nonlinearity in load nature. Machine Learning has different forecasting methods based on the previous data set. In this study a dataset is gathered from Industrial Feeder in Nasik rural district, Maharashtra state, India. The aim of this real time case study is to design a model to forecast the electrical energy consumption by using different regression techniques like LR, SVM, LstM, KNN, Bi-layered NN etc. A best fitted model using KNN is identified based on the evaluation parameters values. © 2025 IEEE.

关键词： Electrical energy consumption Evaluation Matrix Forecasting Machine Learning Regression

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Optimizing Fog computing Performance: A Machine Learning-Based Task Scheduling Approach Using Fuzzy Logic and Clustering 1

Optimizing Fog Computing Performance: A Machine Learning-Bas...

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1st international conference on Advances in Computer Science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Dbritto, Ceres Lopes, Joel Oli, Sanjay Joshi, Maulik S Singh, Aniket Rayal, Ashish St Louis United States Redmond United States Dayananda Sagar College of Engineering Department of Mathematics Bangalore560078 India Gujarat Power Engineering and Research Institute GTU Department of Humanity and Science Gujarat India Veer Madho Singh Bhandari Uttarakhand Technical University Department of Computer Science and Engineering Pithoragarh Campus India School of Applied and Life Sciences Uttaranchal University Department of Mathematics Dehradun248007 India

ISBN: (纸本)9798331518578

The ability to deliver results promptly has become crucial for analytical frameworks due to the swift increase in data volumes. Complex algorithms are needed to schedule data processing activities on distributed compute clusters efficiently. Because it is impractical to create and fine-tune a scheduling policy for every task, current systems rely on basic, generic heuristics and neglect workload peculiarities. Effective task scheduling is essential for optimising the performance of fog computing systems. Fog nodes are dynamic, heterogeneous, and resource-constrained, and traditional task scheduling techniques, which were largely created for centralised cloud settings, frequently cannot accommodate these characteristics. We provide a cutting-edge machine learning (ML) based solution that adjusts job assignment to the evolving needs of the Fog environment in order to get beyond these restrictions. Fuzzy logic, a reliable unsupervised learning method, is used with the K-Means clustering algorithm in our method to effectively group. We have used Python to model and assess our suggested method. The simulation findings validate the effectiveness of our scheduling method, demonstrating notable improvements in response time, reduced network usage, and execution time reduction in comparison to other ML and non-ML based scheduling techniques available in the Python framework. © 2025 IEEE.

关键词： Fog computing

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