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Research on Digital Classroom Construction in the information Age under Computer Big Data Technology 3

Research on Digital Classroom Construction in the Informatio...

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3rd international conference on Computers, information Processing and Advanced Education, CIPAE 2022

作者： Wang, Shuxin Xin, Zhiyuan Changzhou Vocational Institute of Textile and Garment Jiangsu Changzhou213164 China He University Liaoning Shenyang110163 China

ISBN: (纸本)9781665468121

The data storage consists of three parts: SARM storage, CD-ROM and hard disk. The OLAP server is arranged, and the switch is used to realize the functional integration of front-end tools and applications. Through the personalized data analysis model, the data mining parallelization technology is adopted, the data clustering center is updated through the K-means clustering algorithm and the MapReduce parallel computing framework, the clustering performance index is minimized, and the data in the personalized data source is effectively mined. Analysis, the conclusions after analysis are regularized to generate teaching rules, which are presented to students through human-computer interaction to improve the intelligence and personalization of the teaching system. © 2022 IEEE.

关键词： Data mining

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A Tamper-Proof Smart Contract Metamodel for Blockchain to Optimise Computational Latency 3rd

A Tamper-Proof Smart Contract Metamodel for Blockchain to Op...

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3rd international conference on Computing and Communication Networks, ICCCN 2023

作者： Sengupta, Ratul Srivastava, Ruchika Mishra, Sushruta Abualigah, Laith Kalinga Institute of Industrial Technology Deemed to be University Bhubaneswar India Computer Science Department Prince Hussein Bin Abdullah Faculty for Information Technology Al-Albayt University Mafraq25113 Jordan Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman19328 Jordan MEU Research Unit Middle East University Amman11831 Jordan School of Computer Sciences Universiti Sains Malaysia Pulau Pinang Gelugor11800 Malaysia School of Engineering and Technology Sunway University Malaysia Petaling Jaya27500 Malaysia

ISBN: (纸本)9789819726707

In recent years, blockchain technology has garnered considerable interest on account of its peer-to-peer, distributed consensus, and anonymity functionalities. A smart contract functions as a verifiable, self-executing, and self-validating computing layer. This study seeks to identify the key concepts and associated future research goals pertaining to smart contracts based on the blockchain. Smart contracts enable the implementation of programmable assets, including money, and the automation of business logic processes that were previously executed manually. In response to this disclosure, a comprehensive examination of smart contracts employing blockchain technology is undertaken. In this article, we propose an innovative and practical metamodel for ensuring the integrity of protocols within smart contracts facilitated by blockchain technology. This article begins with an explanation of smart contracts’ operational models, functionalities, and applications. Analysis of the results reveals that the utilisation of the model alleviates the workload associated with numerous measurements. It was determined that the mean response latency, computation time, and overhead were each 1.47, 1.19, and 3.04 s. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Smart contract

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Efficient task-mapping of parallel applications using a space-filling curve 31

Efficient task-mapping of parallel applications using a spac...

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31st international conference on parallel Architectures and Compilation Techniques (PACT)

作者： Kwon, Oh-Kyoung Kang, Ji-Hoon Lee, Seungchul Kim, Wonjung Song, Junehwa Korea Adv Inst Sci & Technol Daejeon South Korea Korea Inst Sci & Technol Informat Daejeon South Korea

ISBN: (纸本)9781450398688

Improving the communication performance of parallel programs is an important but difficult problem in a large-scale distributed memory-based cluster. Efforts to improve parallel scalability often face severe huddles in managing communication overheads. This paper proposes a framework of a space-filing curve(SFC)-based task-remapping for communication intensive parallel applications. An SFC-based mapping, when applied for task-mapping of parallel applications preserves locality in terms of communications and produce a less fragmented task-mapping, reducing communication overheads. The framework also provides tools for performance analysis to see if the proposed task-mapping is appropriate for a given application running on a target system. It further develops a binary classifier as a predictor to decide whether or not to apply the proposed mapping before run-time. We evaluate the framework with three communication intensive applications in Cartesian coordinates: P3DFFT solver and Channel code using 2D domain decomposition model, and Poisson solver using 3D domain decomposition. The evaluation is conducted on a large-scale cluster system of fat-tree topology with up to 1,024 compute nodes. The proposed task-mapping achieves the overall performance improvement ranging from similar to 30% to similar to 66% over the baseline approach depending on the workloads. Also, when used in combination with the binary classifier-based predictor, it achieves the expected performance gains from 4% to 8%.

关键词： Mapping

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Efficient Context-Aware Edge Computing Algorithm in Mobile Cloud 3

Efficient Context-Aware Edge Computing Algorithm in Mobile C...

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3rd international conference on Computer Science and Management Technology, ICCSMT 2022

作者： Chang, Jian Yang, Muchuan Gong, Yan Liu, Jiayu Tian, Yuan Li, Qi State Grid Sichuan Information & Communicatioon Company Chengdu China

ISBN: (纸本)9798350320404

Edge computing provides a feasible technical solution to solve the problem of resource and energy supply constraints in terminal device deep learning applications. By migrating part of the deep learning application computing from the terminal to the cloud edge server, the computing pressure of the terminal device can be greatly relieved, and the energy consumption of the terminal can also be reduced to a certain extent. However, in the process of computing migration, the context switching loss of deep learning applications results in a long delay. This paper studies the problem of minimizing the completion time of deep learning applications under edge computing. We model the deep learning application as a task graph, and consider the constraints such as task switching delay, energy consumption and task dependency. Without changing the structure of the task graph, we transform it into a task scheduling-based application completion time minimization problem. In this paper, we first design a parallel scheduling algorithm based on greedy search. Considering the loss of context switching and the dependence of task data, we can allocate tasks to multiple processors for parallel processing by calculating the expected completion time of tasks, thus reducing the completion time of applications. Based on the experimental results, the greedy scheduling algorithm and comparison algorithm are analyzed and verified to optimize the completion time of different depth learning applications. © 2022 IEEE.

关键词： Energy utilization

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Detecting distributed DoS attacks in autonomous vehicles external environment using Machine Learning Techniques 3

Detecting Distributed DoS attacks in autonomous vehicles ext...

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3rd international conference on distributed Sensing and Intelligent systems, ICDSIS 2022

作者： El-Ghamry, Amir Elhoseny, Mohamed Faculty of Computers and Information Mansoura University Mansoura Egypt University of Sharjah Sharjah United Arab Emirates School of Engineering and Computer Science University of Hertfordshire Global Academic Foundation Egypt Faculty of Computer Science and Engineering New Mansoura University Egypt

ISBN: (纸本)9781839538186

The use of autonomous vehicles rapidly growing, especially iu smart cities. Autonomous vehicles exchange information with an external network through wireless communication, and hence security and privacy challenges become a major challenge for all user of autonomous vehicles. Attackers try to exploit the vulnerabilities in the wireless network that connect autonomous vehicles these by performing different types of attacks such as denial of service attack (DDOS) and injection attacks. To mitigate the catastrophic effect of these attacks, intrusion detection process is a must. In this paper, A novel intrusion-detection method is proposed to detect distributed denial of service attack (DDOS) in the wireless network of autonomous vehicles. In this method, the wireless network intrusion detection system (WNIDS) is applied on "CICDDoS2019" dataset for training and testing our model. First the dataset is cleaned and the most important features are selected using recursive feature elimination method which decrease the number of features to only 8 features. The reduced dataset is tested by two machine learning classifiers (Random Forest (RF) and Stochastic Gradient Descent (SGD)). The evaluation results showed that both RF and SGD classifiers can be used to detect DDOS attack with an accuracy of 99% using only 8 features, which were selected using the proposed feature selection method. Relying only on 8 features only make the proposed method to be applicable to any IoT application such as internet of autonomous vehicles. © IET conference proceedings 2022.

关键词： Denial-of-service attack

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Usability Comparison of Level E-Commerce Platform in Indonesia: A Case Study of Tokopedia, Bukalapak, and Shopee 1

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3rd international conference on Smart Computing and Cyber Security—Strategic Foresight, Security Challenges and Innovation, SMARTCYBER 2023

作者： Rosa, Sri Listia Kadir, Evizal Abdul Apriyani, Cici Evizal, Muhammad Fikri Department of Informatics Engineering Universitas Islam Riau Riau Pekanbaru28284 Indonesia Department of Computer Science and Information Engineering National Dong Hwa University Hualien County974 Taiwan

ISBN: (数字)9789819705733

ISBN: (纸本)9789819705726

E-commerce is a common platform for trading in this era and used online platform where buyer and seller have met the transaction. Usability is the process of optimizing the interaction between the user and the system, which can be done interactively, so that the user gets the correct information or better performs a function in the application. This research aims to analyze how is the usability of e-commerce platform in Indonesia, the most favorite and bigger platform selected for the case study. The comparison of e-commerce usability by distributes an online questionnaire to the user with more than 200 respondents in order to obtain data. The questionnaire was distributed using the likers and comment scale method, namely respondents were asked to complete a questionnaire that required them to indicate their level of agreement with a series of statements. The researcher analyzed and graphed the results obtained from the questionnaire data and tested whether the data was valid or not using the Python programming language, as well as recapitulating the data using Microsoft Excel. Then there are problems in this research, namely what applications provide more convenience to users, what applications are more efficient, and what applications provide better satisfaction to their users. In this work of the level of usability, take case on Tokopedia, Bukalapak and Shopee e-commerce platforms. Results show these three companies of e-commerce platform and the calculations achieve that the usability of application is in higher out of all attributes is Shopee which reaches up to 80% compare to others e-commerce. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Electronic commerce

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A point cloud registration algorithm for the fusion of virtual and real maintainability test prototypes 3

A point cloud registration algorithm for the fusion of virtu...

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3rd international conference on Computing, Networks and Internet of Things, CNIOT 2022

作者： Shen, Xiaolei Ge, Zhexue Gao, Quanqin Sun, Haiyang Tang, Xiaoan Cai, Qingyu Henan University of Science and Technology College of Information Engineering Luoyang China National University of Defense Technology College of Intelligent Sciences Changsha China Changsha College Department of Mechanical and Electrical Engineering Changsha China

ISBN: (纸本)9781665469104

In the virtual-real fusion maintainability test scenario, the point cloud registration of maintenance equipment should meet the online real-time requirements and accuracy requirements, so as to provide a good foundation for virtual-real fusion of equipment. To this end, this paper deeply studies the point cloud registration algorithm based on virtual and real fusion. Firstly, the RGBD depth camera is used to collect depth images and color images of objects (spatial and temporal filtering to remove noise), convert it into point cloud data through the camera's internal parameters, sampling the CAD (computer aided design) model of the test prototype as a model point cloud. Combined with the internal shape descriptor algorithm (ISS) to collect the feature points of the physical point cloud and the CAD model point cloud, using OpenMP multi-core and multi-thread parallel to accelerate the calculation of normal and calculate the unique shape context (USC) descriptor;Then, sample consensus initial aligment algorithm (SAC-IA) is used to coarsely register the virtual and real point clouds to obtain the initial pose;Finally, iterative nearest point (ICP) algorithm based on point-to-surface is used for precise registration. The experimental results prove that the algorithm of this paper has high efficiency, the point cloud coincidence degree after registration is high, and the error is reduced by nearly one order of magnitude compared with other algorithms, which can provide better algorithm support for virtual and real maintenance field. © 2022 IEEE.

关键词： Computer aided design

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GTGR-Net: Graph Attentional-Temporal Network for Surface-Electromyography-Based Gesture Recognition 3

GTGR-Net: Graph Attentional-Temporal Network for Surface-Ele...

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3rd international conference on Computing, Networks and Internet of Things, CNIOT 2022

作者： Jia, Xiaoxu Wang, Hongbo Luo, Jingjing Lai, Zhiping Zhang, Xueze Zhang, Weiqi Tang, Xiuhong Fudan University Academy for Engineering & Technology Shanghai200433 China Yanshan University Parallel Robot and Mechatronic System Laboratory of Hebei Province Qinhuangdao China Intelligent Robot Engineering Research Center Ministry of Education Shanghai200433 China Shanghai Intelligent Robot Engineering Technology Research Center Shanghai200433 China Shanghai Clinical Research Center for Aging and Medicine Shanghai200040 China

ISBN: (纸本)9781665469104

In this process of active rehabilitation assisted by hand rehabilitation robot, the patient's hand motion intention, that is, the patient's gesture recognition, plays an important role. Gesture recognition based on sEMG signal is a hot research topic. Due to the spatial correlation and time non-stationary of sEMG signal, this research topic has many difficulties. In order to solve this problem, we come up with a gesture recognition network GTGR-Net based on sEMG signal, which uses the combination of graph attention network and time convolution network to extract the spatiotemporal information of sEMG signal. We verify the effect of our algorithm on three public data sets and achieve good results, which is better than the other ways. © 2022 IEEE.

关键词： Convolution

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distributed Adaptive Test Monitoring Data Classification Technique Based on Data Fields

Distributed Adaptive Test Monitoring Data Classification Tec...

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Innovations and Development of information Technologies and Robotics (IDITR), international conference on

作者： Jinyi Wei Shiyong Zhang Department of Experimental Training North China Institute of Computing Technology Beijing China

ISBN: (数字)9798350385694

ISBN: (纸本)9798350385700

Aiming at the problem that monitoring data in cross-domain tests face a large amount of data and cross categories, we establish a test monitoring data classification system, study the distributed adaptive data classification technology based on data fields, cut and assign the classification task to nodes at different levels by using a distributed data processing scheme to make the classification modular and low-coupling, and realize fast and accurate classification of cross-domain test monitoring data to achieve the purpose of improving the monitoring efficiency of test data by different test personnel and fast access to key data.

关键词： Technological innovation Adaptive systems distributed databases Data processing Personnel Task analysis information technology

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Physically Based Bidirectional Path Tacing Algorithm on the Tianhe-2 Supercomputer 25

Physically Based Bidirectional Path Tacing Algorithm on the ...

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25th IEEE international conferences on High Performance Computing and Communications, 9th international conference on Data Science and systems, 21st IEEE international conference on Smart City and 9th IEEE international conference on Dependability in Sensor, Cloud and Big Data systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Wu, Yijia Zhang, Congpin Xu, Zhengwei Li, Ligang Chinese Academy of Sciences National Space Science Center Key Laboratory of Electronics and Information Technology for Space System Beijing China School of Computer Science and Technology University of Chinese Academy of Sciences China School of Computer and Information Engineering Henan Normal University Henan Xinxiang China

ISBN: (纸本)9798350330014

Physically based ray tracing is a technique that involves creating a photo-realistic image from a 3D scene description by utilizing the laws of physics to simulate the behavior of light and matter. However, due to the random length of light samples and irregular memory access patterns, it can suffer from low scalability and severe load imbalance. As a result, the development of a framework for multi-node parallelism algorithm in physically based ray tracing is a significant challenge. To tackle these issues, this paper introduces a novel algorithm named distributed parallel physically based bidirectional path tacing algorithm (DP-BDPT). Through analyzing the physical essence of bidirectional path tracing algorithm and the light transport equation, we have devised a framework that carefully divides tasks between inter-compute nodes and intra-compute nodes. To support high scalability, we have developed a physically based architecture. Additionally, we have proposed a hybrid scheduling method to achieve load balancing. To further enhance performance, we have analyzed several key factors that affect rendering performance and implemented adaptive optimization techniques. The experiments conducted on the Tianhe-2 Supercomputer involving typical and challenging 3D scenes, namely the Cornell-box, Veach-bidir, and Teapot-full experiments, have illustrated that DP-BDPT demonstrate near-linear speedups as the number of CPU cores scales from 1200 to 9600, thereby demonstrating their efficiency when operating on a ten-thousand-core system. © 2023 IEEE.

关键词： Ray tracing

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