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检索条件"任意字段=4th International Multi-Conference on Computing in the Global Information Technology"

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4th international conference on Advances in information Communication technology and computing, AICTC 2022

4th International Conference on Advances in Information Comm...

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4th international conference on Advances in information Communication technology and computing, AICTC 2022

ISBN: (纸本)9789811998874

the proceedings contain 51 papers. the special focus in this conference is on Advances in information Communication technology and computing. the topics include: Internet of things and Retail Performance in an Emerging Market: A Qualitative Analysis;the Impact of Social Media on Consumer Purchase Behaviour;the Contribution of the Internet of things to Enhance the Brands of Small and Medium-Sized Enterprises in Iraq;trust Chain for Managing Trust in Blockchain-Associated IoT-Enabled Supply-Chains;supply Chain Management Using Blockchain Security Enhancement;a Novel Image Encryption Algorithm Using Logistic and Henon Map;an Analysis of Data Sparsity Resolution Algorithms Used in Recommender Systems;recent Trends for Practicing Machine Learning in Brain Tumors: A Survey;voice-Based Intelligent Virtual Assistant;the Impact of IT Capabilities on Competitive Advantage;Identification of Autism Spectrum Disorder from Functional MRI Using Deep Learning;conversion of Sign Language to Text and Audio Using Deep Learning Techniques;security Attacks and Key Challenges in Blockchain technology: A Survey;advancing from Manual to Automatic Telecast of News for Deaf;study of Nutrition-Based Recommender System for Diabetes and Cardiovascular Patients Based on Various Machine Learning Techniques: A Systematic Review;comparing Fish Finding Techniques using Satellite and Indigenous Data based on Different Machine Learning Algorithms;implementation of E-Governance Framework for Rural Areas of India;opinion Summarization from Online Mobile Phone Reviews Using Feature Based Association Rule Mining;unconventional to Automated Attendance Marking Using Image Processing;synthetic Animations Based Dictionary for Indian Sign Language;start of Telemedicine in Uzbekistan. Technological Availability;review of Feature Extraction Techniques for Fake News Detection.

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Proceedings - 2021 20th international conference on Ubiquitous computing and Communications, 2021 20th international conference on Computer and information technology, 2021 4th international conference on Data Science and Computational Intelligence and 2021 11th international conference on Smart computing, Networking, and Services, IUCC/CIT/DSCI/SmartCNS 2021

Proceedings - 2021 20th International Conference on Ubiquito...

引用

20th international conference on Ubiquitous computing and Communications, 20th international conference on Computer and information technology, 4th international conference on Data Science and Computational Intelligence and 11th international conference on Smart computing, Networking, and Services, IUCC/CIT/DSCI/SmartCNS 2021

ISBN: (纸本)9781665466677

the proceedings contain 80 papers. the topics discussed include: back-imaging scheme in RF-powered passive camera system;proactive attack detection at the edge through an ensemble deep learning model;a secure federated learning mechanism for data privacy protection;OFDM signal design based on electrode-based through-the-earth communication;spiking mean field multi-agent reinforcement learning for dynamic resources allocation in D2D networks;joint optimization of latency and reward for offloading dependent tasks in mobile edge computing;energy-efficient power control and resource allocation based on deep reinforcement learning for d2d communications in cellular networks;a fuzzy Bayesian network based on fault tree for vaccine safety risks analysis;a reinforcement learning-based task classification mechanism for privacy-enhanced mobile crowdsensing strategy;a mobile crowd sensing ecosystem based on fog computing infrastructure;preserving privacy for edge weights in communication networks;and design and implementation of anti-wireless electricity rubbing system.

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Self-Supervised multi-Label Classification with global Context and Local Attention 24

Self-Supervised Multi-Label Classification with Global Conte...

引用

4th Annual international conference on multimedia Retrieval (ICMR)

作者： Chen, Chun-Yen Yeh, Mei-Chen Natl Taiwan Normal Univ Taipei Taiwan

ISBN: (纸本)9798400706028

Self-supervised learning has proven highly effective across various tasks, showcasing its versatility in different applications. Despite these achievements, the challenges inherent in multi-label classification have seen limited attention. this paper introduces GAELLE, a novel self-supervised multi-label classification framework that simultaneously captures image context and object information. GAELLE employs a combination of global context and local attention mechanisms to discern diverse levels of semantic information in images. the global component comprehensively learns image content while local attention eliminates object-irrelevant nuances by aligning embeddings with a projection head. the integration of global and local features in GAELLE effectively captures intricate object-scene relationships. To further enhance this capability, we introduce a global and local swap prediction technique, facilitating the nuanced interplay between various objects and scenes within images. Experimental results showcase GAELLE's state-of-the-art performance in self-supervised multi-label classification tasks, highlighting its effectiveness in uncovering complex relationships between multiple objects and scenes in images.

关键词： multi-label classification Self-supervised learning Attention

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Application of the Blockchain Sharding Model to Improve the Efficiency of a global-Scale Drug Supply Chain System Based on Blockchain technology 4

Application of the Blockchain Sharding Model to Improve the ...

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4th international conference on Ubiquitous computing and Intelligent information Systems, ICUIS 2024

作者： Inayatulloh Juwitasary, Hanny School of Information system Bina Nusantara University Information Systems Department Jakarta11480 Indonesia

ISBN: (纸本)9798331529635

the drug supply chain involves several parties with different roles. Several global pharmaceutical companies, such as drug manufacturers, sell and distribute their products to hospitals and drug distributors in several countries. Several pharmaceutical companies already have a system that supports the drug supply chain. Several studies offer the adoption of blockchain technology to improve the transparency and validity of drug supply chain information. But the application of peer-to-peer validation is not efficient for the drug supply chain, which involves actors spread across several countries with many transactions. So, this research aims to improve the efficiency of the global drug supply chain system based on blockchain technology with blockchain sharding. the Hyperledger framework is used to test the resulting prototype. the research output is a blockchain sharding adoption model to increase the efficiency of blockchain technology implementation in the global pharmaceutical supply chain. © 2024 IEEE.

关键词： Drug discovery

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Design and Implementation of Energy Data multi-party Privacy Query Scheme Based on Privacy information Retrieval 4

Design and Implementation of Energy Data Multi-party Privacy...

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4th IEEE international conference on information technology, Big Data and Artificial Intelligence, ICIBA 2024

作者： Sheng, Liu Hangxuan, Song Fang, Shang Ze, Yuan Xiaoyu, Wang Yingying, Wang Xinyue, Shi State Grid Heilongjiang Electric Power Research Institute Harbin China

ISBN: (纸本)9798350363586

With the development of energy Internet, the privacy protection of energy data has become an important issue. In this paper a multi-party privacy query scheme for energy data based on privacy information retrieval (PIR) technology is proposed, aiming at solving the privacy leakage problem in the process of energy data sharing. By analyzing the current demand of energy data privacy protection, a complete business process is designed in this paper, including data collection, preprocessing, analysis model construction and output. For different privacy requirements, this paper discusses three PIR schemes based on oblivious transfer (OT), homomorphic encryption and keyword PIR, and compares their technical characteristics, communication overhead and computational overhead. Simulation experiments verify the feasibility of the proposed scheme. the results show that the proposed scheme can effectively protect query privacy. the research in this paper provides technical support for the sustainable development of new power systems and is of great significance to promote the safe sharing of energy data. © 2024 IEEE.

关键词： Differential privacy

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Study on Railway Informatization Optimization Based on Intelligent Fusion Algorithm 4

Study on Railway Informatization Optimization Based on Intel...

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4th international conference on Neural Networks, information and Communication Engineering, NNICE 2024

作者： Bai, Ping China Academy of Railway Sciences Group Co. Ltd Institute of Electronic Computing Technology Beijing100081 China

ISBN: (纸本)9798350394375

this research introduces a QoS model for fundamental grid railway information services and a QoS model for composite grid railway information services to assess the efficacy of the railway information service composition within a grid environment. the study utilizes the weighted sum method to convert multi-objective optimization problems into single-objective optimization problems and devises a genetic annealing fusion algorithm for the global optimization model. Subsequently, using ticketing services as an illustration, the study validates the rationality of the QoS-based grid railway information service combination optimization model and confirms the accuracy of the genetic annealing hybrid algorithm. © 2024 IEEE.

关键词： information services

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Design and Implementation of Power Tax Data Query Tool Based on Private information Retrieval 4

Design and Implementation of Power Tax Data Query Tool Based...

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4th IEEE international conference on information technology, Big Data and Artificial Intelligence, ICIBA 2024

作者： Sheng, Liu Fang, Shang Xiaoyu, Wang Haijiao, Yu Shibao, Han Xiang, Yu Baiyu, Yang State Grid Heilongjiang Electric Power Research Institute Harbin China State Grid Heilongjiang Electric Power Company Limited Harbin China

ISBN: (纸本)9798350363586

Design and implementation of a power tax data query tool based on Private information Retrieval (PIR) technology is presented in this paper, aimed at enabling power companies to securely obtain tax data without revealing the privacy of their queries, thereby more accurately estimating the electricity usage of enterprises. With the development of the digital economy and the instability of economic operations, the tax-electricity index, as a new government tool, is of great significance for monitoring the quality and efficiency of economic operations. By employing Secure multi-Party Computation (MPC) technology, the MASCOT protocol, and PIR technology, this paper designs and implements a method that protects the security of tax-electricity private data while improving data utilization efficiency. Simulation results demonstrate that the tool can effectively assist power companies in using tax data to optimize enterprise electricity services, providing support for high-quality economic development. © 2024 IEEE.

关键词： Data Security Power Tax Data Private information Retrieval Secure multi-Party Computation

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multi-objective optimization of aluminum electrolysis based on improved SHAP value 4

Multi-objective optimization of aluminum electrolysis based ...

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4th IEEE international conference on information technology, Big Data and Artificial Intelligence, ICIBA 2024

作者： Du, Zhaowei North China University of Technology School of Information Technology Beijing China

ISBN: (纸本)9798350363586

Aiming at the problem that many parameters affecting each other in the process of aluminum electrolysis make it difficult to improve the current efficiency and unable to reach the expected production index, the multi-objective optimization idea is proposed to optimize the current efficiency as the primary objective, and optimize the other important parameters that have a large impact on the current efficiency and affect each other as the secondary objective. Firstly, the variance threshold and the improved SHAP value method are used to extract the important features such as aluminum level and electrolyte level. then the prediction model and MOTROA multi-objective optimization algorithm are used to establish a multi-objective optimization model for the aluminum electrolysis production process to obtain the optimal ranges of parameters such as aluminum level, electrolyte temperature, and so on, and to achieve the goal of improving the current efficiency. the experimental results show that these important parameters are located in the optimal range while the current efficiency is increased. © 2024 IEEE.

关键词： multiobjective optimization

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Research on Intelligent Agent technology and Applications Based on Large Models 4

Research on Intelligent Agent Technology and Applications Ba...

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4th IEEE international conference on information technology, Big Data and Artificial Intelligence, ICIBA 2024

作者： Liu, Wenfu Chang, Wentai Shi, Chuan Wang, Yajing Hu, Ran Zhang, Caikun Ouyang, Haibo State Key Lab. of Complex Electromagnetic Environment Effects on Electronics and Information System China

ISBN: (纸本)9798350363586

With the rapid growth of available data, the continuous improvement of computing power, and the increasing maturity of large model technology, AI Agents based on large models are gradually becoming the core of AI research and applications. AI Agents possess characteristics such as learning ability, decision-making capability, adaptability, and initiative, enabling them to automatically make choices and take actions to achieve specified goals. Moreover, by integrating large-scale pre-trained model technology, AI Agents can continuously improve their performance based on interactions. this paper will review the background, concepts, and characteristics of AI Agents, focusing on the analysis of the core capabilities and implementation paradigms of large model-based intelligent agents. In line with industry demands, it constructs an electromagnetic target analysis and recognition intelligent agent application framework based on multi-modal large models, providing a reference for readers interested in the research and development of large model intelligence agents. © 2024 IEEE.

关键词： AI agent ETAR agent large model large model Agent

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multi-Scale Vision Transformer with Local-global Attention 4

Multi-Scale Vision Transformer with Local-Global Attention

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4th international conference on Industrial Automation, Robotics and Control Engineering, IARCE 2024

作者： Zhang, Ruomiao Du, Shengdong Hu, Jie Zhao, Xiaole Yang, Yan School of Computing and Artificial Intelligence Southwest Jiaotong University Chengdu China

ISBN: (纸本)9798350380323

the extraction of multi-scale features from input images is crucial for computer vision tasks. However, some backbone networks based on visual transformers lack the ability to effectively extract multi-scale features or use relatively simplistic methods to do so. this paper proposes a novel multi-scale visual transformer, called multi-Scale Extraction Transformer (MSET), designed to proficiently tackle a range of downstream visual tasks. MSET incorporates innovative concepts of multi-Scale feature extraction Embedding (MS Embedding) and Local-global self-attention (LGSA). MS Embedding uses a unique architecture convolutional layer method that constructs hierarchical residual-like connections, allowing for the extraction of multi-scale features at finer granularity levels. Meanwhile, LGSA integrates local and global dependencies within the self-attention module, reducing computational complexity while facilitating connections between the global and local features of the image. the importance of position information in the embeddings and the impact of amplitude on model performance are also considered, allowing MSET to handle position bias information of variable size in the input image and to ensure stability during training. Numerous experiments have demonstrated the significant advantages of MSET over most existing state-of-the-art backbone networks across various visual tasks, including image classification, object detection, instance segmentation, and semantic segmentation tasks. © 2024 IEEE.

关键词： Semantic Segmentation

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