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检索条件"任意字段=Proceedings of the 3rd International Conference on Parallel and Distributed Information Systems"

共 4571 条记录，以下是51-60 订阅

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Research on Network Security Protection Techniques for the Central Station Side of distributed Power Dispatch and Control systems 3

Research on Network Security Protection Techniques for the C...

引用

2023 IEEE 3rd international conference on Data Science and Computer Application, ICDSCA 2023

作者： Zhang, Xiao Wang, Youhuai Zhang, Wenlu State Grid Hubei Electric Power Co. Ltd. Wuhan China

ISBN: (纸本)9798350341546

This research focuses on the study of network security protection techniques for the central station side of distributed power dispatch and control systems. It covers various aspects such as vulnerability discovery, information interaction security, device management, and threat tracing. The aim is to propose an integrated, multi-dimensional, and multi-level security protection system that combines active and passive data security measures and security analysis methods to ensure the safety and reliability of the distributed power dispatch and control systems. © 2023 IEEE.

关键词： Device Management distributed Power Dispatch and Control System information Interaction Security Network Security Vulnerability Discovery

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Power Generation Performance of distributed Photovoltaic systems Based on Perovskite Solar Cells 3

Power Generation Performance of Distributed Photovoltaic Sys...

引用

3rd international conference on Energy, Power and Electrical Technology, ICEPET 2024

作者： Zhang, Jinxia Li, Xiaolei Yang, Shuo Sun, Peijun Wang, Jixue Tan, Hairen China Electric Power Planning & Engineering Institute Beijing China Nanjing University Nanjing China

ISBN: (纸本)9798350352658

distributed photovoltaic systems are one of the key technologies for achieving China's carbon peaking and carbon neutrality goals, with their continuous development and technological progress being crucial. This study focuses on six representative cities in China, comparing and analyzing the power generation performance of rooftop distributed photovoltaic systems based on perovskite solar cells against those using traditional silicon solar cells. The research found that in all the cities examined, photovoltaic systems employing perovskite solar cells demonstrated higher efficiency compared to systems based on silicon solar cells, with efficiency improvement ranging between 7.0% and 9.9%, especially notable in Haikou and Chongqing with higher annual average temperature or lower light irradiance. This performance advantage mainly stems from the low temperature coefficient and superior performance under low-intensity light irradiance of perovskite solar cells. Additionally, the power generation performance of perovskite cells exhibits lower sensitivity to weather changes, contributing to the overall stability of photovoltaic systems. The widespread application of perovskite photovoltaic technology is expected to further enhance the efficiency and stability of China's distributed photovoltaic systems, providing valuable technical support for China's energy transition. © 2024 IEEE.

关键词： Photovoltaics

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parallel Optimization of Super Pixel Algorithm SLIC 3

Parallel Optimization of Super Pixel Algorithm SLIC

引用

3rd international conference on information Science, parallel and distributed systems, ISPDS 2022

作者： Luo, Xiaoqi Xing, Yuanjie Xu, Senhai Southwest Petroleum University Chengdu China

ISBN: (数字)9781665487474

ISBN: (纸本)9781665487474

Super pixel algorithm SLIC uses K-means mean clustering method to effectively generate super pixels. Compared with other super pixel algorithms, it is more efficient and improves the segmentation performance. In order to further improve its performance, the program is optimized from five major directions: compilation optimization, data structure optimization, loop vectorization, OpenMP parallel optimization and algorithm optimization. © 2022 IEEE.

关键词： K-means clustering

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3rd Southwest Data Science conference, SDSC 2024

3rd Southwest Data Science Conference, SDSC 2024

引用

3rd Southwest Data Science conference, SDSC 2024

ISBN: (纸本)9783031678707

The proceedings contain 15 papers. The special focus in this conference is on Southwest Data Science. The topics include: How Does Normalization Impact Clustering?;quantitative Stock Market Modeling Using Multivariate Geometric Random Walk;disease Similarity and Disease Clustering;composition Analysis and Identification of Ancient Glass Products;data Entropy-Based Imbalanced Learning;analysis of the Changes in Microbial Community During the Fermentation of Feng-Flavour Baijiu;enhanciGraph: Visualizing Enhancer-Gene Interactions;event-Triggered Control for Synchronization of Chaotic Delayed Lur’e systems with Stochastic Cyber-Attacks;in-Game Win Prediction Models for Cricket;finite-Time Outer Average Synchronization Between Two Coupled Heterogeneous Complex Dynamical Networks and Its Application in Secure Communication;Classification of In-Situ Solar Wind Data Measured by Solar Orbiter/SWA-PAS and HIS Using Machine Learning;node Classification with Multi-hop Graph Convolutional Network;pyDaskShift: Automatically Convert Loop-Based Sequential Programs to distributed parallel Programs.

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A Real-Time Adaptive Multi-Stream GPU System for Online Approximate Nearest Neighborhood Search 24

A Real-Time Adaptive Multi-Stream GPU System for Online Appr...

引用

33rd ACM international conference on information and Knowledge Management (CIKM)

作者： Sun, Yiping Shi, Yang Du, Jiaolong Xiaohongshu Inc Shanghai Peoples R China

ISBN: (纸本)9798400704369

In recent years, Approximate Nearest Neighbor Search (ANNS) has played a pivotal role in modern search and recommendation systems, especially in emerging LLM applications like Retrieval-Augmented Generation. There is a growing exploration into harnessing the parallel computing capabilities of GPUs to meet the substantial demands of ANNS. However, existing systems primarily focus on offline scenarios, overlooking the distinct requirements of online applications that necessitate real-time insertion of new vectors. This limitation renders such systems inefficient for real-world scenarios. Moreover, previous architectures struggled to effectively support real-time insertion due to their reliance on serial execution streams. In this paper, we introduce a novel Real-Time Adaptive Multi-Stream GPU ANNS System (RTAMS-GANNS). Our architecture achieves its objectives through three key advancements: 1) We initially examined the real-time insertion mechanisms in existing GPU ANNS systems and discovered their reliance on repetitive copying and memory allocation, which significantly hinders real-time effectiveness on GPUs. As a solution, we introduce a dynamic vector insertion algorithm based on memory blocks, which includes in-place rearrangement. 2) To enable real-time vector insertion in parallel, we introduce a multi-stream parallel execution mode, which differs from existing systems that operate serially within a single stream. Our system utilizes a dynamic resource pool, allowing multiple streams to execute concurrently without additional execution blocking. 3) Through extensive experiments and comparisons, our approach effectively handles varying QPS levels across different datasets, reducing latency by up to 40%-80%. The proposed system has also been deployed in real-world industrial search and recommendation systems, serving hundreds of millions of users daily, and has achieved significant results.

关键词： Real Time Vector Insertion Multi Stream GPU GPU parallel System Approximate Nearest Neighborhood Search

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Gaussian mixture distributed particle filter algorithm for state propagation using ESPT 3

Gaussian mixture distributed particle filter algorithm for s...

引用

3rd international conference on Electronic information Engineering, Big Data, and Computer Technology, EIBDCT 2024

作者： Ding, Yuxuan Zhang, Ying College of Information Engineering Shanghai Maritime University 201306 China

ISBN: (纸本)9781510680449

This article combines the Gaussian mixture model with the extended propagation single particle filtering technique (ESPT) and proposes a Gaussian mixture distributed particle filtering algorithm that uses ESPT for state propagation. The algorithm is implemented through the average consensus algorithm in both distributed and iterative modes to improve computational efficiency. In this algorithm, the posterior probability is approximated as a Gaussian mixture model, and the fusion of the Gaussian mixture is achieved through importance sampling. Meanwhile, the use of ESPT effectively reduces computational complexity. Numerical examples further demonstrate that compared to other distributed particle filtering algorithms, this method also has significant performance advantages © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： State estimation

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Formal Verification of distributed Self-Adaptive systems Under Environmental Uncertainty 3

Formal Verification of Distributed Self-Adaptive Systems Und...

引用

3rd international conference on Artificial Intelligence and Computer information Technology, AICIT 2024

作者： Wang, Zihao Liu, Wei Guo, Kao Xu, Fan School of Computer Science & Engineering Wuhan Institute of Technology Wuhan China

ISBN: (纸本)9798350365443

distributed self-adaptive system is a multi-component collaborative system that automatically adjusts its behavior and structure through adaptive mechanisms to maintain system performance and stability in dynamic environments. The adaptability and robustness of these systems depend on the correctness of self-adaptive decisions in real-world scenarios. However, environmental uncertainty makes it difficult for the systems to accurately perceive their operating environments, which may result in misjudgments and consequently erroneous self-adaptive decisions. To address this issue, we propose a Stochastic Timed Automata-based Adaptive Verification method. By collecting data during system operation and using Bayesian methods to transform it into transition probabilities between system states, a stochastic timed automata model is constructed to simulate the system's operational process. Key properties are verified using statistical model checking to ensure the correctness of self-adaptive decisions. The effectiveness and efficiency of the method are demonstrated by verifying the adaptability and robustness of a multi-roadside unit collaborative system in intelligent transportation vehicle-road coordination. © 2024 IEEE.

关键词： Stochastic systems

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LSTM-MI: Revolutionizing Intrusion Detection Through Adaptive Learning and Mutual information Analysis 3

LSTM-MI: Revolutionizing Intrusion Detection Through Adaptiv...

引用

3rd IEEE international conference on distributed Computing and Electrical Circuits and Electronics, ICDCECE 2024

作者： Archana, J. Aneetha, A.S. Department Of Computer Science Chennai Pallavaram India

ISBN: (纸本)9798350318609

This study introduces two innovative approaches to augment intrusion detection capabilities. The first method employs Principal Component Analysis (PCA) for dimensionality reduction, streamlining the dataset's complexity while retaining crucial features. The second method delves into feature selection using Mutual information (MI), identifying and preserving the most informative attributes crucial for intrusion detection. These selected features are then incorporated into LSTM-based models and it evaluates the efficacy of both PCA and MI alongside LSTM, providing a comparative analysis of their impact on intrusion detection performance. Notably, the LSTM-PCA model exhibits an accuracy of 97.73%, while the LSTM-MI model achieves a higher accuracy of 98.21 %. These results underscore the significance of integrating PCA and MI in conjunction with LSTM, offering nuanced insights into their individual contributions to accurate intrusion detection. Through extensive experimentation on benchmark datasets, the proposed methodologies aim to advance the development of robust intrusion detection systems (IDS). © 2024 IEEE.

关键词： Principal component analysis

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Design and implementation of a dedicated 5G communication terminal for distributed power sources 3

Design and implementation of a dedicated 5G communication te...

引用

3rd international conference on Electronics Technology and Artificial Intelligence, ETAI 2024

作者： Gao, Zunhai Lu, Hongxia Zhou, Kang Yu, Yue School of Information and Artificial Intelligence Nanchang Institute of Science and Technology Nanchang China Economics and Management School Hubei Business College Wuhan China School of Mathematics and Computer Science Wuhan Polytechnic University Wuhan China

ISBN: (纸本)9781510683143

With the increasing integration of renewable energy into the power grid, the demand for efficient communication systems for managing and controlling distributed power sources has become urgent. Here, we introduce the design and implementation of a 5G communication terminal tailored specifically for the unique requirements of distributed power sources. The proposed terminal aims to improve communication reliability, latency, and throughput, thereby optimizing the overall performance of the distribution network, and designs a set of self-feedback fault elimination. The system architecture, key features, and experimental results were discussed in detail, demonstrating the feasibility and effectiveness of the proposed solution. © 2024 SPIE.

关键词： Power distribution networks

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Artificial Intelligence is Used to Identify Tomato Diseases Through Leaf Analysis 3

Artificial Intelligence is Used to Identify Tomato Diseases ...

引用

3rd IEEE international conference on Problems of Informatics, Electronics and Radio Engineering, PIERE 2024

作者： Khujaev, Otabek Djumanazarov, Odamboy Soliyev, Bobur Urgench branch of Tashkent University of Information Technologies named after Muhammad al-Khwarizmi It Department Urgench Uzbekistan

ISBN: (纸本)9798331516321

This paper explores using artificial intelligence in applications to detect tomato leaf diseases. A key issue is how automated systems and artificial intelligence can be used to diagnose and predict disease control, damage, and temporary control of tomato diseases. The paper is based on the study of the benefits of implementing classical and modern artificial intelligence models, their problems, and successful technological solutions in detecting tomato diseases. The article describes in detail how effective distributed artificial intelligence algorithms are in detecting tomato diseases, their application, and their independence in analyzing and accounting for the results. As a result, it is important to use artificial intelligence to detect tomato leaf diseases quickly, and this discovery offers effective methods for faster treatment. Tomato export is considered important for the economy of Uzbekistan, one of the developing agricultural countries today. However, even in this area, there are cases of crop loss, so we created and analyzed a project that detects tomato leaf diseases based on deep learning with transfer learning architectures. © 2024 IEEE.

关键词： Fruits

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