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检索条件"任意字段=7th International Conference on Parallel and Distrubuted Computing, Applications and Technologies"

共 233 条记录，以下是11-20 订阅

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Optimized NLP Model with Caching, parallel Processing and Streamlined I/O 7

Optimized NLP Model with Caching, Parallel Processing and St...

引用

7th international conference on Circuit Power and computing technologies, ICCPCT 2024

作者： Rajalakshmi, B. Rani, C Nagamanjula Vijayasekaran, G. Kumar, S Mahesh Hegde, Shabrish B Srikanth, Sai New Horizon College of Engineering Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350372816

this research explores optimization strategies employed within ***, an advanced question generation system driven by natural language processing (NLP) and machine learning (ML) algorithms. the study delves into three pivotal areas of optimization: caching, parallel processing, and streamlining I/O operations. By implementing caching mechanisms using Python's ***-cache, parallelization via *** and multiprocessing modules, and streamlining I/O operations through efficient batching and buffering techniques, significant enhancements in time and space complexity are realized. the effectiveness of these optimization approaches is empirically evaluated, showcasing their profound impact on the efficiency and scalability of the *** platform. this research contributes to the advancement of question generation systems, providing valuable insights into effective optimization strategies for NLP applications, such as question generation, semantic analysis, and language modeling. © 2024 IEEE.

关键词： Semantics

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Synergizing Blockchain with Big Data for Improved Data Integrity and Transparency 7

Synergizing Blockchain with Big Data for Improved Data Integ...

引用

7th international conference on Contemporary computing and Informatics, IC3I 2024

作者： Krishna, M. Hari Raju, Hemanth Jain, Alok Al-Rubaye, Taqi Mohammed Khattab thandra, Nagarjuna Tewari, Preeti Institute of Aeronautical Engineering Department of Computer Science and Engineering Telangana Hyderabad India New Horizon College of Engineering Department of Mechanical Engineering Bangalore India Lovely Professional University Phagwara India The Islamic University College of Medical Technologies Department of Medical Laboratory Technology Najaf Iraq Mlr Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India Lloyd Law College Uttar Pradesh Greater Noida India

ISBN: (纸本)9798350350067

this research offers a novel and complete technique to merge blockchain and big data, solving accuracy, security, and scalability issues. Five algorithms - integrating a decentralized storage solution, automating smart contracts, reaching an agreement (proof-of-work), sharding for scalability, and securely encrypting data for privacy - are advocated. the Decentralized Storage Solution Integration technique secures the system's basis by building up a decentralized storage system, employing cryptographic hashing to ensure stability, and ensuring acceptance through proof-of-work. the technique uses sharding technologies for scaling, parallel processing, redundancy, and fault tolerance. the autonomous storage system and Smart Contract Automation algorithm automate compliance inspections. Clearer deals reduce transaction costs. this strategy is crucial for efficient, transparent, and cost-effective contractual negotiations. the agreement (proof-of-work) approach protects financial transactions with computer problem-solving. thus, the blockchain remains trustworthy, data is consistent, and interactions are visible. the proposed technique has been extensively investigated, and the findings reveal how each program is interconnected and vital to the system. Tables and figures indicate that the recommended strategy outperforms current combinations in all critical areas. the solution is essential because it is extensible, works with other systems, uses resources well, is easy to check, helpful, and cheap. Blockchain technology and big data are proposed as a better solution. It covers the essentials and ensures blockchain systems are secure, open, scalable, and privacy-protecting. © 2024 IEEE.

关键词： Decentralized finance

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Applying Web Crawler technologies for Compiling parallel Corpora as one Stage of Natural Language Processing 7

Applying Web Crawler Technologies for Compiling Parallel Cor...

引用

7th international conference on Computer Science and Engineering, UBMK 2022

作者： Abdurakhmonovaa, Nilufar Alisher, Ismailov Toirovaa, Guli National University of Uzbekistan Uzbek Linguistics Department Tashkent Uzbekistan AAndijan Machine Building Institute Innovative Educational Department Andijan Uzbekistan Bukhara State University Uzbek Linguistics Department Bukhara Uzbekistan

ISBN: (数字)9781665470100

ISBN: (纸本)9781665470100

over the past decade, the amount of information on the internet has increased. A large amount of unstructured data, referred to as big data on the web, has been created. Finding and extracting data on the internet is called information retrieval. In the search for information, there are web crawler tools, which are a program that scans information on the internet and downloads web documents automatically. Search robot applications can be used in various fields, such as news, finance, medicine, etc. In this article, we will discuss the basic principle and characteristics of search engines as an example to build parallel corpora, as well as the classification of modern popular crawlers, strategies and current applications of crawlers. Finally, we will end this article with a discussion of future directions for research on crawlers. © 2022 IEEE.

关键词： Search engines

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Optimized NLP Model with Caching, parallel Processing and Streamlined I/O

Optimized NLP Model with Caching, Parallel Processing and St...

引用

international conference on Circuit, Power and computing technologies (ICCPCT)

作者： B. Rajalakshmi C Nagamanjula Rani G. Vijayasekaran S Mahesh Kumar Shabrish B Hegde Sai Srikanth Computer Science and Engineering New Horizon College Of Engineering Bangalore India

ISBN: (数字)9798350372816

ISBN: (纸本)9798350372823

this research explores optimization strategies employed within ***, an advanced question generation system driven by natural language processing (NLP) and machine learning (ML) algorithms. the study delves into three pivotal areas of optimization: caching, parallel processing, and streamlining I/O operations. By implementing caching mechanisms using Python’s ***_cache, parallelization via *** and multiprocessing modules, and streamlining I/O operations through efficient batching and buffering techniques, significant enhancements in time and space complexity are realized. the effectiveness of these optimization approaches is empirically evaluated, showcasing their profound impact on the efficiency and scalability of the *** platform. this research contributes to the advancement of question generation systems, providing valuable insights into effective optimization strategies for NLP applications, such as question generation, semantic analysis, and language modeling.

关键词： Runtime Computational modeling Scalability Semantics Machine learning parallel processing Question generation

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Implicit-Explicit Error Indicator based on Approximation Order 7

Implicit-Explicit Error Indicator based on Approximation Ord...

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7th international conference on Smart and Sustainable technologies, SpliTech 2022

作者： Jancic, Mitja Strnisa, Filip Kosec, Gregor Parallel and Distributed Systems Laboratory Joief Stefan Institute Joief Stefan International Postgraduate School Ljubljana Slovenia Parallel and Distributed Systems Laboratory Joief Stefan Institute Ljubljana Slovenia

ISBN: (纸本)9789532901160

With the immense computing power at our disposal, the numerical solution of partial differential equations (PDEs) is becoming a day-to-day task for modern computational scientists. However, the complexity of real-life problems is such that tractable solutions do not exist. this makes it difficult to validate the numerically obtained solution, so good error estimation is crucial in such cases. It allows the user to identify problematic areas in the computational domain that may affect the stability and accuracy of the numerical method. Such areas can then be remedied by either h- or p-adaptive procedures. In this paper, we propose to estimate the error of the numerical solution by solving the same governing problem implicitly and explicitly, using a different approximation order in each case. We demonstrate the newly proposed error indicator on the solution of a synthetic two-dimensional Poisson problem with tractable solution for easier validation. We show that the proposed error indicator has good potential for locating areas of high error. © 2022 University of Split, FESB.

关键词： Poisson equation

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A Review on Patients Health Monitoring using IoT and Cloud technologies 7

A Review on Patients Health Monitoring using IoT and Cloud T...

引用

7th international conference on parallel, Distributed and Grid computing, PDGC 2022

作者： Rani, S. Stella Pavan, T. Hemanth Vanathi, A. Devi, B.S. Kiruthika Aditya Engineering College Department of Cse A.P. Surampalem India Cl Educate Ltd New Delhi India

ISBN: (纸本)9781665454018

At present, the population is increasing day by day. Our traditional methods and human efforts are insufficient to meet the needs of every patient. As every patient needs continuous monitoring of their health status. At present, the observation of a patient's health is very important, and this monitored data is connected to a cloud and can alert the doctor by forwarding a message. Physicians can monitor patients' or elderly people's health conditions from a remote area by using the Internet of things (IoT). And also, medical services can be provided to sick people or patients from remote areas based on their daily health status. With the wide range of sensors like pulses, heartbeat, blood pressure, ECG, and temperature sensors along with IoT, such system provides a sophisticated control for continuous monitoring of the health conditions of patients. the goal of this study is to provide a detailed investigation of the IoT health monitoring system that are in the literature. the various existing system is compared and contrasted based on the efficiency and its accuracy. the advantages and disadvantages of the system along with the experimental aspects are available in the comparative results. © 2022 IEEE.

关键词： Internet of things

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Batch Workflow Scheduling Optimization in Cloud Resource Environment

Batch Workflow Scheduling Optimization in Cloud Resource Env...

引用

international conference on Information technologies in Engineering Education (Inforino)

作者： Victor Toporkov Dmitry Yemelyanov Artem Bulkhak Department of Computing Technologies National Research University “MPEI” Moscow Russia

ISBN: (数字)9798350371369

ISBN: (纸本)9798350371376

the constantly evolving cloud ecosystems are promising environments for the execution of science-intensive applications within the framework of the new concept of Workflow-as-a-Service (WaaS). WaaS platforms, being the so-called multitenant environments, provide efficient mechanisms for managing continuous and heterogeneous job-flows in cloud computing. However, in this scenario, along with the complexity of scheduling composite workflows, an additional problem arises to efficiently manage the cloud resources, that is, to determine the start and shutdown times of virtual resources, considering the available economic policy. To handle this problem, we propose a modification to the critical jobs method which has been the basis of the Systems Design course in the Department of computing technologies for over 15 years. the resulting solution combines several heuristics to optimize the cloud resource management for WaaS platforms and largely determined the successful completion of RSF project. Some experiments with the real-world workflows prove the optimization efficiency of the proposed approach.

关键词： Cloud computing Limiting Processor scheduling Genomics parallel processing Scheduling Resource management

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ComFaaS Distributed: Edge computing with Function-as-a-Service in parallel Cloud Environments

ComFaaS Distributed: Edge Computing with Function-as-a-Servi...

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international conference on Information and Computer technologies (ICICT)

作者： Jaden Jinu Lee Judah Nava Hanku Lee Computer Science and Information Systems Minnesota State University Moorhead Moorhead MN

ISBN: (数字)9798350385625

ISBN: (纸本)9798350385632

Function-as-a-Service (FaaS) has emerged as a revolutionary service platform, abstracting the complexities of hardware, operating systems, and web hosting services. this allows developers to focus solely on implementing their service applications, making FaaS an ideal platform for the scalable manipulation of large data sets. Traditionally deployed on the cloud, FaaS now faces a new frontier: the network edge. Leveraging the edge offers several potential benefits, including reduced latency and improved resource utilization, making it a promising approach for efficient FaaS deployment. As the daily volume and complexity of data we handle continues to grow, adopting a parallel computing paradigm has become increasingly important to ensure fast and efficient execution of computational tasks. Addressing this need, ComFaaS Distributed embarks on a comprehensive comparison of the capabilities of parallelized edge and cloud environments for FaaS deployment. Utilizing benchmark programs meticulously crafted to simulate event-triggered scenarios, ComFaaS Distributed aims to provide valuable insights into the performance and potential of FaaS at the edge, paving the way for a future where parallel computing empowers the efficient and scalable processing of ever-growing data volumes.

关键词： Cloud computing Computer architecture parallel processing Benchmark testing Computational efficiency Complexity theory Web sites

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A Subpixel-level parallel Alignment Technology Oriented to EMU Train Undercarriage Image 23

A Subpixel-level Parallel Alignment Technology Oriented to E...

引用

7th international conference on Innovation in Artificial Intelligence, ICIAI 2023

作者： Sun, Peng Zhang, Weijiao Yang, Kai Chen, Yan Institute of Computing Technologies China Academy of Railway Sciences Corporation Limited Beijing China

ISBN: (纸本)9781450398398

In order to realize efficient fault recognition and utilization of the high-speed train (EMU) undercarriage image obtained by detection robot, image alignment technology play an important role. Firstly, research the original image data collection process of the EMU fault detection robot in the practical working site;secondly, perform image enhancement such as gamma transformation and Hanning window adding on the original image;thirdly, compared with the image alignment algorithm based on feature extraction, a Fourier transform-based image alignment algorithm is proposed;finally, the affine processing with global transform parameters acquired from image alignment is given. this paper conducts experimental verification and comparative analysis, and selects a convolutional neural network (CNN) model based on deep residual structure to carry out this experiment. through comparison with three typical image alignment algorithms based on feature extraction, it shows that the Fourier transform-based image alignment algorithm has significantly improved in the accurate alarm rate, mistaken alarm rate, and omitted alarm rate with strong robustness. Based on the intrinsic subpixel-level precision of domain transformation alignment algorithm, and the parallel image processing method proposed in this paper, the on-site image preprocessing, high-precision alignment, and automatic fault recognition can be realized stably and reliably within a reasonable time. © 2023 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Feature extraction

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Strengthening Healthcare Cybersecurity by Optimizing Adversarial Attack Defences in Deep Learning Models using GPU and parallel Processing technologies

Strengthening Healthcare Cybersecurity by Optimizing Adversa...

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international conference on Circuit, Power and computing technologies (ICCPCT)

作者： Hridya Venugopal Mary Subaja Christo Department of Networking and Communications SRM Institute of Science and Technology Kattankulathur Campus Chengalpattu Tamilnadu India

ISBN: (数字)9798350372816

ISBN: (纸本)9798350372823

In healthcare, safeguarding patient data integrity is paramount, necessitating robust deep learning models. this research focuses on bolstering the cyber security defenses of these models, particularly against adversarial attacks, through the application of the Localized Adversarial Feature Attack (LAFEAT) technique. Leveraging Graphics Processing Units (GPU) and the TensorFlow framework, the study explores algorithmic enhancements like the Fast Gradient Sign Method (FGSM) and Model-Agnostic Meta-Learning (MAML). these techniques perturb input data gradients or adapt model parameters, enhancing resilience against adversarial perturbations. Additionally, Particle Swarm Optimization (PSO), a metaheuristic optimization technique, is examined to fortify defense mechanisms further. parallel processing techniques, utilizing parallel GPU or distributed clusters, are implemented to expedite the optimization process, reducing computational burdens and enhancing scalability. Despite advancements, gaps remain in understanding how these models can be optimized for real-world healthcare applications, particularly in terms of balancing computational efficiency and robustness. the research demonstrates tangible benefits, with a significant 10% increase in success rates against adversarial attacks compared to baseline methods. Moreover, parallel processing implementation results in a 30% reduction in optimization time, improving the efficiency of cyber security defenses for deep learning models in healthcare. these numerical enhancements underscore the research’s value in fortifying healthcare systems against adversarial threats, ensuring the security and integrity of patient data while addressing existing gaps in the optimization of adversarial defenses in healthcare applications. the strengths of this research lie in its robust adversarial attack optimization techniques, integration of parallel processing for efficiency, and application to critical healthcare tasks. Comprehensive

关键词： Deep learning Adaptation models Computational modeling Graphics processing units Medical services parallel processing Data models

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