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检索条件"任意字段=11th International Conference on Intelligent Data Engineering and Automated Learning"

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Construction of an intelligent Teaching Information Management Cloud Platform Based on Mobile Information Technology 11th

Construction of an Intelligent Teaching Information Manageme...

引用

11th international conference on Applications and Techniques in Cyber Intelligence, ATCI 2023

作者： Li, Qian Liu, Kai Chen, Xiaoning Finance office Shandong Institute of Commerce and Technology Shandong Jinan250031 China

the proposal of student teaching information management conforms to the requirements of the times, which makes cloud platform technology and internet information processing particularly important. In order to keep up with the needs of the public, education and teaching management needs in-depth research. the analysis of student teaching information management can improve the monitoring of students' learning ability and physical and mental health from multiple aspects, contributing to providing a good student talent environment. this article introduced the design of a student teaching information management cloud platform based on mobile internet. this platform utilized cloud computing technology and mobile internet technology to achieve online management and sharing of student teaching information. the platform has functions such as user management, course management, grade management, and online communication, making it easy to manage and analyze students' teaching information, improving the quality and efficiency of school teaching. this article applied experimental and comparative methods to analyze the performance and functionality of the teaching information management system. the experimental data showed that the accuracy of the score query function in the system ranked first, reaching 99.92%, and the availability was 99.54%. © 2024 the Authors. Published by Elsevier B.V.

关键词： Cloud platforms

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Design and Development of a Transformer Condition Diagnosis System Application to Predict Purification Time and Life of a Transformer Based on Machine learning 11

Design and Development of a Transformer Condition Diagnosis ...

引用

11th international conference on Electrical engineering, Computer Science and Informatics, EECSI 2024

作者： Bukit, Ferry R.A. Zulkarnain, Hendra Putra, Andre Yuanda Universitas Sumatera Utara Department of Electrical Engineering Medan Indonesia

ISBN: (纸本)9798350355314

Transformers are equipment in high-voltage engineering that often experience abnormalities originating from internal or external sources. this abnormality causes disturbances, so it is necessary to diagnose faults in the transformer as early as possible so that fault predictions and maintenance actions can be carried out to maintain the quality of work on the transformer. An application was designed to diagnose the transformer's condition and predict purification time and transformer life to maintain the quality of the transformer's work. this application is designed to help make it easier to predict transformer conditions using dissolved gas analysis test results, oil scores, furan, and tap changer. the application design is done using the Python programming language and then converted into a mobile app using the React Native library framework with a simulator using Expo and connected to a database to store user data. the predicted data is for the GT 2.1 Excitation transformer, GT 2.1 Main Transformer, and GT 2.1 UAT transformer. Based on the application design, the test results were 100% successful;the system validated all the tests from the ten tests. the GT 2.1 Excitation transformer oil purification time is predicted to be 5697 days since the last test, and the transformer lifetime is predicted to be more than 15 years. the GT 2.1 Main Trafo transformer oil purification time is predicted to be 2697 days since the last test, and the transformer lifetime is predicted to be more than 15 years. the GT 2.1 Excitation transformer oil purification time is predicted to be 1866 days since the last test, and the transformer lifetime is predicted to be more than 15 years. © 2024 IEEE.

关键词： Electric transformer testing

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Automation of Prediction Method for Supervised learning 11

Automation of Prediction Method for Supervised Learning

引用

11th international conference on Cloud Computing, data Science and engineering (Confluence)

作者： Singh, Irijendra Jaiswal, Rashi Univ Lucknow Dept Comp Sci ICT Res Lab Lucknow Uttar Pradesh India

ISBN: (纸本)9781665414517

data science helps to build the prediction model for decision making through data mining techniques. data Scientists require more time and effort in algorithm selection and data preparation for obtaining more effective results. At the present, a number of existing methods are available for the prediction purpose through supervised learning and unsupervised learning which are based on manual processes. this paper proposed the method for the automation of the prediction process for supervised learning, using prediction type selection methods with the data cleaning process through computing the missing value. It has been illustrated by examples with experimental analysis. this proposed automation methodology makes competitive prediction performance with less effort than the non-automated process.

关键词： data science supervised learning data mining decision making

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PirouNet: Creating Dance through Artist-Centric Deep learning 11th

PirouNet: Creating Dance Through Artist-Centric Deep Learnin...

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11th international conference on Arts and Technologies Interactivity and Game Creation

作者： Papillon, Mathilde Pettee, Mariel Miolane, Nina Univ Calif Santa Barbara Dept Phys Santa Barbara CA 93106 USA Lawrence Berkeley Natl Lab Berkeley CA USA Univ Calif Santa Barbara Dept Elect & Comp Engn Santa Barbara CA USA

ISBN: (纸本)9783031289927;9783031289934

Using Artificial Intelligence (AI) to create dance choreography is still at an early stage. Methods that conditionally generate dance sequences remain limited in their ability to follow choreographer-specific creative direction, often relying on external prompts or supervised learning. In the same vein, fully annotated dance datasets are rare and labor intensive. To fill this gap and help leverage deep learning as a meaningful tool for choreographers, we propose "PirouNet", a semi-supervised conditional recurrent variational autoencoder together with a dance labeling web application. PirouNet allows dance professionals to annotate data with their own subjective creative labels and subsequently generate new bouts of choreography based on their aesthetic criteria. thanks to the proposed semi-supervised approach, PirouNet only requires a small portion of the dataset to be labeled, typically on the order of 1%. We demonstrate PirouNet's capabilities as it generates original choreography based on the "Laban Time Effort", an established dance notion describing a given intention for a movement's time dynamics. We extensively evaluate PirouNet's dance creations through a series of qualitative and quantitative metrics, validating its applicability as a tool for choreographers.

关键词： Deep learning Neural network Semi-supervised Generative Recurrent LSTM VAE Pose Laban

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11th EAI international conference on Game theory for Networks, GameNets 2022

11th EAI International Conference on Game Theory for Network...

引用

11th EAI international conference on Game theory for Networks, GameNets 2022

ISBN: (纸本)9783031231407

the proceedings contain 25 papers. the special focus in this conference is on Game theory for Networks. the topics include: Design and Implementation of Targeted Poverty Alleviation System Based on Blockchain Network;an Intent-Based Routing Scheme in Satellite IoT;interference Management in Terrestrial-Satellite Networks Using Stackelberg Game;optimal Resource Allocation for Computation Offloading in Maritime Communication Networks: An Energy-Efficient Design via Matching Game;game theoretic Analysis of Resource Allocation in Multi-tiered Networks;Energy-Efficient Multi-cell NOMA Design via Coalition Formation Game;the Vaccination Game in Susceptible-Infected-Susceptible (SIS) Networks with Multipopulations;a Stochastic Bandwidth Scanning Game;port Capacity Leasing Games at Internet Exchange Points;multi-service Communication Isolation of Underground Pipe Gallery Based on WiFi6;a Phase Transition in Large Network Games;dynamic Pricing for Tenants in an automated Slicing Marketplace;service Function Chain Placement in Cloud data Center Networks: A Cooperative Multi-agent Reinforcement learning Approach;the Art of Concession in General Lotto Games;providing Slowdown Information to Improve Selfish Routing;budgeted Adversarial Network Resource Utilization Games;MU-PDR: A Method of Fingerprint Passive Positioning for WiFi6 Based on MU-RTS/CTS;the Optimal Layer of User-Specific Reconfigurable intelligent Surfaces Structure for Uplink Communication System;a Sophisticated Anti-jamming Strategy for a Joint Radar and Communication System;power data Credible Decision-Making Mechanism Based on Federated learning and Blockchain;a Service Protection Mechanism of Deterministic Networking Based on Segment Routing;cloud-Edge Collaboration Based Power IoT Scene Perception Mechanism;task Allocation Mechanism of Power Internet of things Based on Edge Routing Optimization.

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Detecting and Mitigating Adversarial Perturbations to Improve E-Commerce Security 11

Detecting and Mitigating Adversarial Perturbations to Improv...

引用

11th IEEE/ACM international conference on Big data Computing, Applications and Technologies, BDCAT 2024

作者： Tariq, Usman Jaafar, Fehmi Malik, Yasir Prince Sattam Bin Abdulaziz University College of Business Administration Dept. of Management Information Systems Saudi Arabia Université du Québec à Chicoutimi Dept. d'Informatique et de mathématique Canada Bishop's University Dept. of Computer Science Canada

ISBN: (纸本)9798350367300

E-commerce platforms face the critical challenge of adversary events, including fraudulent transactions and fake reviews, which can lead to significant financial and reputational damage. Addressing this, our research introduces a hybrid Deep learning model, tailored for the detection of such adversarial activities. this innovative approach leverages spatial and sequential data processing capabilities, enhancing the identification of subtle adversarial manipulations across diverse e-commerce contexts. Our findings indicate a high detection rate of 93 percent for adversarial attacks, with precision, recall, and Matthews Correlation Coefficient metrics underscoring the model's efficacy. this work significantly contributes to e-commerce security by advancing the robustness of detection systems against a spectrum of adversarial threats, including account takeovers and deceptive reviews. While demonstrating a notable improvement over existing methods, our research also acknowledges the potential for evasion by sophisticated attacks, highlighting areas for future work in enhancing model resilience. this balance of innovation and critical insight provides a solid foundation for further advancements in the field of e-commerce security © 2024 IEEE.

关键词： Adversarial machine learning

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data Security Access Control Based on Blockchain and Smart Contracts 23

Data Security Access Control Based on Blockchain and Smart C...

引用

11th international conference on Computer and Communications Management, ICCCM 2023

作者： Yan, Xiaoxue Chen, Meijuan Zhang, Yangxin Pan, Fan School of Communication and Information Engineering Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (纸本)9798400707735

With the development of the Internet and edge computing technology, many industrial Internet applications have emerged, followed by a large amount of data in the Industrial Internet. How to securely store and share this data has become a hot topic in current research. Firstly, a blockchain and IPFS based on-chain and off-chain storage architecture is proposed, which detects data through machine learning algorithms and stores data without anomalies. then, the roles of users were classified and various smart contracts were designed for registering users, deleting users, and managing roles and their permissions. Finally, an experimental platform was built through open-source software to verify the feasibility of the proposed scheme and realize the safe storage and sharing of normal data. © 2023 ACM.

关键词： Smart contract

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Fusing UAV and Ultra-Wideband Technology for Target Visual intelligent Perception Without GNSS 11th

Fusing UAV and Ultra-Wideband Technology for Target Visual I...

引用

11th international conference on Robot Intelligence Technology and Applications, RiTA 2023

作者： Zhao, Zongqing Wei, Junyu Zuo, Zhen Su, Shaojing Guo, Xiaojun Hu, Liushun Tong, Xiaozhong Chen, Wei College of Intelligence Science and Technology National University of Defense Technology Changsha China School of Intelligent Manufacturing Ecosystem Xi’an Jiaotong-Liverpool University Suzhou Jiangsu China School of Energy Science and Power Engineering Central South University Hunan Changsha China

ISBN: (纸本)9783031706837

this paper introduces an innovative framework for target perception by merging Unmanned Aerial Vehicle (UAV) capabilities with Ultra-Wideband (UWB) technology. UAVs are proficient at capturing and analyzing visual data employing intelligent algorithms, while UWB technology excels in providing high-precision positioning information, particularly when Global Navigation Satellite System (GNSS) signals are inaccessible. this study advocates the synergistic integration of UWB technology and UAVs, harnessing their inherent strengths to establish a robust and versatile framework for efficient target perception, which encompasses target detection and localization across diverse scenarios. the presented experimental results showcased in this paper substantiate the effectiveness of our proposed approach in accurately detecting and localizing targets, even in challenging conditions marked by GNSS signal disruptions. this framework not only capitalizes on the amalgamation of UWB technology and UAVs but also offers a resilient and adaptable solution for target detection and localization in a variety of real-world scenarios. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Unmanned aerial vehicles (UAV)

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Research on Optimization Methods for intelligent Industrial Internet Based on Big data Analysis 11

Research on Optimization Methods for Intelligent Industrial ...

引用

11th Joint international Information Technology and Artificial Intelligence conference, ITAIC 2023

作者： Shao, Tsz Hon Maalla, Allam School of Engineering Guangzhou College of Technology and Business Guangdong Guangzhou510850 China

ISBN: (纸本)9798350333664

the advent of the industrial internet has ushered in a transformative era, integrating cutting-edge information and communication technologies with industrial manufacturing, resulting in a novel industrial ecosystem, vital infrastructure, and a revolutionary application model. this research paper delves into the fundamental theories and methodologies underpinning the intelligent industrial internet in the context of big data analysis. the objective is to establish seamless connectivity among all elements, entire industry chains, and complete value chains through secure and reliable interactions between humans, machines, and objects. this technological advancement heralds significant changes in manufacturing production methods and enterprise structures, giving rise to an entirely new industrial production, manufacturing, and service system, propelling the manufacturing industry towards heightened digitization, networking, and intelligence. © 2023 IEEE.

关键词： Big data cutting-edge technologies intelligent industrial internet

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Hebbian learning-Guided Random Walks for Enhanced Community Detection in Correlation-Based Brain Networks 24th

Hebbian Learning-Guided Random Walks for Enhanced Community ...

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24th international conference on intelligent data engineering and automated learning, IDEAL 2023

作者： Sotero, Roberto C. Sanchez-Bornot, Jose M. Department of Radiology and Hotchkiss Brain Institute University of Calgary CalgaryAB Canada Intelligent Systems Research Centre Ulster University Derry Londonderry United Kingdom

ISBN: (纸本)9783031482311

Community detection in complex signed networks is a significant challenge, traditionally addressed using the Louvain method directly applied to the correlation matrix. this study introduces a two-tier approach that integrates a Hebbian learning rule within an adaptive signed random walk (ASRW) framework, then applies the Louvain method to the final weight matrix. this approach refines the network analysis process, providing a new tool for exploring community structure. Tested extensively on synthetic signed networks with defined community structures, our methodology consistently outperformed the traditional Louvain approach, particularly when communities were less clearly demarcated. Further application to resting-state functional MRI data from the ABIDE Preprocessed Initiative highlighted functional connectivity differences between neurotypical individuals and those diagnosed with Autism Spectrum Disorder (ASD). Our approach found key areas of significant difference, including several cerebellum regions, consistent with existing ASD literature. Our findings underscore the potential of the proposed technique to advance community detection in correlation-based networks. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Population dynamics

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