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检索条件"任意字段=2023 International Conference on Algorithms, Computing and Data Processing, ACDP 2023"

共 6952 条记录，以下是4801-4810 订阅

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Multi-Device data Fusion IoT Monitoring System for Home Safety

Multi-Device Data Fusion IoT Monitoring System for Home Safe...

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2025 international conference on Electrical Automation and Artificial Intelligence, ICEAAI 2025

作者： Ye, Jianying Chen, Hantao Zhang, Lina Peng, Kefeng Tang, Jun Guangzhou Xinhua University School of Information and Intelligence Engineering Guangzhou China

ISBN: (纸本)9798331506797

With the development of technology and the increasing demand for quality of life, home security has become one of the evaluation standards for modern quality of life. This paper proposes a smart home Internet of Things (IoT) monitoring system aimed at enhancing home security. Through real-time detection and automatic response capabilities for fires, gas leaks, and water and electricity usage, the system provides comprehensive security protection for families. The system integrates various sensors and smart home appliances, achieving real-time monitoring and prevention of potential security risks through multi-device data fusion. The system design employs data fusion algorithms capable of timely identification of potential hazards and coordination of device responses, thereby effectively preventing the occurrence of safety incidents. © 2025 IEEE.

关键词： data fusion edge computing intelligent control Internet of Things MQTT Smart home security

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Artificial Intelligence (AI) in the Automotive Industry and the use of Exoskeletons in the Manufacturing Sector of the Automotive Industry

Artificial Intelligence (AI) in the Automotive Industry and ...

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Sustainable computing and data Communication Systems (ICSCDS), international conference on

作者： Jash Minesh Shah N.A. Natraj Giri. G. Hallur Avinash Aslekar Symbiosis Institute of Digital and Telecom Management Symbiosis International (Deemed University) Lavale Pune

Introducing Artificial Intelligence (AI) in the Automotive Industry and developing related technologies will significantly impact the automotive industry. A technological innovation like Autonomous driving entails using artificial intelligence (AI), which represents the future of transportation and applications that will influence the concept of driving. New businesses related to mobility will emerge, and the already existing ones will have to adapt to the necessary shifts. Some security and AI algorithms are used in the vehicle security domain. This research aims to give some idea and understanding about how Artificial Intelligence (AI) is important and impacts the automotive industry. While discussing autonomous vehicles, there is a question to ask or focus on – what about the feasibility of autonomous production? Some light has been thrown on the benefits and requirements for automation of production plants, and its future has been discussed.

关键词： Industries Technological innovation Exoskeletons Transportation Production Manufacturing Security

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Improving Vietnamese Question-Answering system with data Augmentation and Optimization

Improving Vietnamese Question-Answering system with Data Aug...

引用

IEEE international conference on Research, Innovation and Vision for the Future

作者： Nguyen Ba Thanh Bac Nguyen Van Vinh Computer Science Department VNU University of Engineering and Technology Hanoi Vietnam

Extractive question answering (EQA) is one of the most important tasks in natural language processing (NLP) which has both commercial and research value. Recently, methods using neural networks, especially transformer architecture achieved state-of-the-art results in this field. Because of the rise of large language models, datasets need to be more complex to evaluate models strictly. Despite being meticulously fine-tuned on the most cutting-edge and comprehensive datasets available, these models still exhibit a surprising and concerning tendency to struggle with seemingly uncomplicated scenarios. In this paper, we propose a simple and efficient method for Extractive question answering: (1) to augment data to improve question answering task using models and original datasets; (2) we also use deque data structure to enhance post-processing process to guarantee finding the best answer and to decrease complexity to O(n) in there, n is length of context in question answering problem.

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data-Driven Decisions: Exploring the Impact of data Mining in Healthcare

Data-Driven Decisions: Exploring the Impact of Data Mining i...

引用

computing and Big data (ICCBD), international conference on

作者： Jin Wang Pierre-Richard Cornely Department of Applied Mathematics and Physics Valdosta State University Valdosta GA USA College of Science and Mathematics Valdosta State University Valdosta GA USA

ISBN: (数字)9798350317008

ISBN: (纸本)9798350317015

In the healthcare sector, data mining stands as a crucial tool for analyzing vast patient datasets to unearth significant revelations. This manuscript provides a comprehensive exploration of data mining's contributions to healthcare, spanning from pandemic research, treatment efficacy assessment, predictive modeling, insurance fraud detection, medical device optimization, to streamlined hospital management. It delves into various data mining techniques such as clustering, classification, statistical analysis, unsupervised pattern recognition, and web-based data scrutiny, emphasizing their relevance in healthcare contexts. algorithms like the Naïve Bayes Classifier and K-means clustering are underscored for their prevalent use in health-related scenarios. The treatise wraps up by shedding light on the emerging trajectories for healthcare data mining and pinpointing exciting avenues for impending inquiries.

关键词： Statistical analysis Pandemics Prevention and mitigation Medical services Predictive models Prediction algorithms data models

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New Artificial Intelligence System Based on Information processing Technology

New Artificial Intelligence System Based on Information Proc...

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data Analytics, computing and Artificial Intelligence (ICDACAI), international conference on

作者： Ziye Tian School of Information Engineering Shaanxi Institute of International Trade & Commerce Xi'an Shaanxi China

Artificial intelligence (AI) technology is a product of social evolution, an important integration of scientific and technological development, and has a profound impact on people's lives and work. In recent years, countries have increased their attention to AI research. AI is not an isolated technology, and it must be based on the development of information technology. AI encompasses a wider range of knowledge domains, spanning multiple disciplines. The development of AI must be more adaptable to human needs. The networked era continues to develop and must also change. For many people, AI and Knowledge management are interconnected. As information management systems themselves become increasingly complex and contain more and more management content, without intelligent network management as a support, many problems arise in the management process. This article first introduces information processing technology and AI systems, and then explores the construction of a new type of AI system. Finally, through experiments, the power of AI's text recognition function is verified (as long as the data volume is large enough, the recall rate can reach 93.5%, approaching 100%).

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Application of 3D Airborne Electrical Survey data processing in a Distributed computing System when Solving the Problem of Searching for Polymetallic Ores

Application of 3D Airborne Electrical Survey Data Processing...

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international conference on Actual Problems of Electronic Instrument Engineering (APEIE)

作者： Marina G. Persova Yury G. Soloveichik Dmitry S. Kiselev Anastasia P. Sivenkova Daryana A. Leonovich Marina G. Tokareva Department of Applied Mathematics Novosibirsk State Technical University Novosibirsk Russia

An example of the use of 3D processing of airborne electrical survey data in solving the problem of searching for polymetallic ores is presented. data processing is based on solving a 3D inverse problem, in which the field from the geoelectric model and the field of influence of its individual parameters are calculated using finite element 3D modeling. To solve the inverse problem, a heterogeneous distributed computing system is used. It consists of multi-core computers connected by a network. The paper presents the mathematical model used to solve the inverse problem and some features of the implementation of calculations in a distributed system, which are related to taking into account the computational complexity of the subtasks and the load on the computing nodes by other applications. The results of testing the 3D inversion system on airborne electrical survey data obtained at a polymetallic ore deposit are presented. The 3D inversion results show good agreement with the drilling data.

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Improved clustering analysis algorithm for density grid data streams

Improved clustering analysis algorithm for density grid data...

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Electrical Engineering, Big data and algorithms (EEBDA), IEEE international conference on

作者： Fang Bin Zhu Shi Huang Jiahao Li Haozhi Information and Communication Branch of State Grid Hunan Electric Power Company Limited Changsha China State Grid Info-Telecom Great Power Science and Technology Co. Ltd. Fuzhou China

An improved density grid data stream clustering analysis algorithm was proposed to cope with the characteristics of high speed, real-time and continuous real-time data stream. The traditional density grid data clustering method is difficult to popularize because of rough boundary processing, which leads to low clustering accuracy and single grid division. A mesh partitioning method with different grain sizes is proposed to make the boundary mesh and internal mesh more clear. The inner grid adopts coarse-grained clustering method, and the boundary grid adopts fine-grained clustering method. The improved density grid clustering method and the traditional method were respectively used for cluster analysis, and the results show that the proposed method has a fast clustering speed and a high clustering accuracy.

关键词： Grain size Electrical engineering Clustering methods Heuristic algorithms Clustering algorithms Big data Real-time systems

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4th international conference on Applied Technologies, ICAT 2022

4th International Conference on Applied Technologies, ICAT 2...

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4th international conference on Applied Technologies, ICAT 2022

ISBN: (纸本)9783031249846

The proceedings contain 113 papers. The special focus in this conference is on Applied Technologies. The topics include: Automatic Evaluation of Physiotherapy Activities Using Deep Learning Techniques;multivariable Control Approach Applied to the Embryo Incubation Process of Gallus Gallus Domesticus;discovering Visual Deficiencies in Pilots Candidates Using data Mining;an Electronic Equipment for Measuring Color Difference Between Tissues Based on Digital Image processing and Neural Networks;artificial Intelligence-Based Banana Ripeness Detection;U-Net vs. TransUNet: Performance Comparison in Medical Image Segmentation;access Control Through Mask Detection and Estimation of People Capacity in Covered Premises;customer Segmentation in Food Retail Sector: An Approach from Customer Behavior and Product Association Rules;Bibliometric Analysis of Web of Science database STEM Fields in Engineering and Mathematics. Ecuador’s Case Study;smart Antenna Array for Optimal Electromagnetic Energy Capture;image processing Method to Estimate Water Quality Parameter;use of the Student Engagement as a Strategy to Optimize Online Education, Applying a Supervised Machine Learning Model Using Facial Recognition;crime data Analysis Using Machine Learning Models;Gene Therapy as a Solution to Genetic Diseases Through DNA Manipulation;Vulnerability of CAPTCHA Systems Using Bots with Computer Vision Abilities;military Leadership in the Ecuadorian Army;analysis of Key Variables for Ecuadorian Defense Industry Development;the Prioritization of External Security as a Means of Guaranteeing Multidimensional Security and Economic Growth;Comparative Study of Deep Learning algorithms in the Detection of Phishing Attacks Based on HTML and Text Obtained from Web Pages;ground Robot for Search and Rescue Management;virtual Training Module for the Production of Rubber Adhesives Through the Production of Cyclopentenol.

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Direct Transposition Interleaving Technique for DNA data Storage

Direct Transposition Interleaving Technique for DNA Data Sto...

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international conference on Biomedical Engineering and Applications (ICBEA)

作者： Zhengyu Li Kun Bi Xiangwei Zhao Monash University Joint Graduate School Southeast University Suzhou China State Key Laboratory of Bioelectronics School of Biological Science and Medical Engineering Southeast University Nanjing China

Compared to traditional storage media, DNA possesses several advantages; however, it is prone to errors in its base sequence during the storage process. When employing traditional error correction coding algorithms for DNA storage, a substantial number of redundant bases are added to ensure lossless data recovery. This approach results in significant base consumption and is ill-suited for scenarios with extreme error cases. To address these issues, this paper proposes the Direct Transpose Interleaving Code (DTIC), which uses data interleaving technology to distribute potential errors in a sequence across multiple sequences. DTIC can be used in conjunction with traditional error correction coding algorithms to enhance data recovery capabilities. Through theoretical analysis and simulation experiments, this paper demonstrates that lossless data recovery necessitates fewer redundant bases with DTIC processing compared to data without DTIC processing.

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Pairs Trading Strategy Optimization Using Proximal Policy Optimization algorithms

Pairs Trading Strategy Optimization Using Proximal Policy Op...

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international conference on Big data and Smart computing (BIGCOMP)

作者： Yi-Feng Chen Wen-Yueh Shih Hsu-Chao Lai Hao-Chun Chang Jiun-Long Huang Department of Computer Science National Yang Ming Chiao Tung University Hsinchu Taiwan

Pairs trading is a market-neutral quantitative trading strategy which exploits historically correlated stock prices by forming pairs with weighted long and short positions. A pair of opened offsetting positions can profit regardless of positive or negative price trend. Positions are opened when the spread exceeds the trading boundary, and closed when the spread reverts back to the historical mean. In this paper, we adopt proximal policy optimization, which is a deep reinforcement learning algorithm, to determine the trading boundaries as well as stop loss boundaries for maximizing the profit in pairs trading. Besides, we propose to utilize a demonstration butter to pre-train the model for better training efficacy. The experimental results manifest that the proposed method outperforms state-of-the-art strategies in terms of investment return and investment risk in both the Taiwan stock market and the United States stock market.

关键词： Training Deep learning Dairy products Reinforcement learning Big data Market research Stock markets

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