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检索条件"任意字段=International Conference on Information Technology - Coding and Computing"

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Development of a Gesture Analysis System for Human System Interaction 13

Development of a Gesture Analysis System for Human System In...

引用

Joint 13th international conference on Soft computing and Intelligent Systems and 25th international Symposium on Advanced Intelligent Systems, SCIS and ISIS 2024

作者： Matsumoto, Chifuyu Sone, Yuka Woo, Jinseok Ohyama, Yasuhiro Graduate School of Engineering Tokyo University of Technology Sustainable Engineering Program 1404-1 Katakuracho Hachioji Tokyo192-0982 Japan School of Engineering Tokyo University of Technology Department of Mechanical Engineering 1404-1 Katakuracho Hachioji Tokyo192-0982 Japan

ISBN: (纸本)9798350373332

Recently, Japan has been facing various social issues, and to solve these problems, it is necessary to create a society where diverse people can live comfortably. To build such a society, appropriate support tailored to individuals is required, necessitating the analysis of various types of information to understand the people's needs at any given moment. In particular, analyzing non-verbal elements such as posture, facial expressions, and gestures is crucial, as these naturally indicate a person's condition. Therefore, this study focuses on human gestures, one of the non-verbal elements, and proposes a gesture recognition method using Dynamic Time Warping (DTW) and K-Means. We demonstrated that symbolic gesture recognition is possible by recording arm trajectories from skeletal measurements with an RGB-D camera. © 2024 IEEE.

关键词： Gesture recognition

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Cloud computing as a Key Enabler of Performance and Growth in Small Businesses

Cloud Computing as a Key Enabler of Performance and Growth i...

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2024 international conference on Electrical and Computer Engineering Researches, ICECER 2024

作者： Machera, Rumbidzai Tanya Muchuchuti, Stewart School of Computing and Information Systems Botswana Accountancy College Gaborone Botswana

ISBN: (纸本)9798331539733

Amidst the current digital epoch several Small to Medium-sized Enterprises (SMEs) are incorporating cloud computing technology in their organizations for their day-to-day operations. This research contributes methodologically by examining the improvements within cloud computing technologies, including efficiency refinements and expense refinements, while addressing the resistance and uncertainty some small businesses face regarding cloud-based solutions. This study explores the integration of cloud computing technologies and their impact on performance enhancement and operational effectiveness. In the epoch of Internet of Things (IoT) cloud computing is developing and rising online. Nevertheless, there are still some small businesses who are uncertain of the advantages of cloud-based offerings and some resist to change. Through a systematic review of existing literature, this research synthesizes insights from academic studies and analyses the current state of knowledge in this field to provide a comprehensive understanding of the benefits and challenges of cloud adoption. The paper uniquely identifies gaps in the current research, critically assesses the practical limitations of cloud computing, and highlights emerging trends. This research contributes valuable insights for academia and practitioners, aiming to facilitate informed decision-making and strategic adoption of cloud technologies within the small business sector. © 2024 IEEE.

关键词： Cloud platforms

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An Assessment of Big Data Analysis Technologies for Improved information Delivery 3

An Assessment of Big Data Analysis Technologies for Improved...

引用

3rd international conference on Smart Generation computing, Communication and Networking, SMART GENCON 2023

作者： Chanthati, Sasibhushan Rao Velmurugan, T. Gulati, Neha Kedia, Naresh Akram, Faiz Wegari, Getachew Mamo Harrisburg University of Science and Technology T. Rowe Price United States Srm Institute of Science and Technology Faculty of Management Kattankulathur India Jims Department of It Delhi India Manipal University Jaipur Department of Business Administration Rajasthan Jaipur India Jimma Institute of Technology Jimma University Faculty of Computing and Informatics Oromia Jimma Ethiopia

ISBN: (纸本)9798350319125

Massive information analysis is becoming more and more vital for turning in improved records to the healthcare industry. It has the potential to allow healthcare companies to better apprehend patient information, track affected person results, and improve the general affected person experience. To absolutely comprehend these potentials, healthcare companies have to apprehend the special big statistics evaluation technologies to be had to them and their related strengths and *** this paper, we perform a comprehensive assessment of big data evaluation technologies for improved statistics delivery in the healthcare industry. We check the technology and techniques relevant to the industry and speak their relative strengths and weaknesses. Specially, we consciousness on facts mining, device getting to know, herbal language processing, and fraud detection techniques. We evaluate the blessings and downsides of those technologies in phrases of information accuracy, evaluation speed, and value effectiveness. We conclude that facts mining comprehensive provide the most comprehensive answer for large statistics analysis inside the healthcare industry. © 2023 IEEE.

关键词： comprehensive consciousness techniques technologies weaknesses

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Instant Ambulance Connection Rescue Radar 5

Instant Ambulance Connection Rescue Radar

引用

5th international conference on information Management and Machine Intelligence, ICIMMI 2023

作者： Baskar, M. Kumar, Ankit Bajaj, Khushi Department of Computing Technologies School of Computing College of Engineering and Technology SRM Institute of Science and Technology Tamil Nadu Chengalpattu603203 India Department of Computer Science and Engineering School of Computing College of Engineering and Technology SRM Institute of Science and Technology Tamil Nadu Chengalpattu603203 India

ISBN: (纸本)9798400709418

In the field of emergency medical services, the element of time significantly influences patient outcomes. The groundbreaking Instant Ambulance Connection- Rescue Radar system is introduced to expedite responses to medical emergencies. This research paper explores the system's structure, approach, and potential impact, highlighting its role in providing swift and efficient emergency medical services. The primary objective of this system is to bridge the gap between patients and ambulance services, simplifying ambulance requests and hospital visit scheduling. A user-friendly Android app is central to its functionality, enabling one-tap ambulance requests and harnessing modern technologies like the Internet of Things and the Google Maps API to transmit user information and precise locations to local ambulance drivers rapidly. This system also empowers patients with real-time access to ambulance availability and the ability to track the ambulance's location in real-time. By enhancing communication between patients, ambulance drivers, and healthcare institutions, the system significantly improves the efficiency of the emergency medical response network. © 2023 ACM.

关键词： Location

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A Nonlinear Interval Programming Model based on Fuzzy Neural Networks 2

A Nonlinear Interval Programming Model based on Fuzzy Neural...

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2nd international conference on Distributed computing and Optimization Techniques, ICDCOT 2024

作者： Zhu, Jijin Wu, Qinqin Luo, Chan College of Mechanical and Electrical Engineering Guangdong University of Science and Technology Dongguan China Mathematics Teaching and Research Office Dongguan Guangming Primary School Dongguan China

ISBN: (纸本)9798350382952

Compared to traditional deterministic problem research methods, interval analysis methods have a larger computational load and longer computational time due to the presence of uncertainty. Therefore, for models with complex structures or large scales, there is a lot of uncertain information, which requires a significant amount of computation and reduces the efficiency of the algorithm. The current optimization algorithms also have such shortcomings. In order to improve algorithm efficiency, this article focuses on researching parallel computing methods for interval optimization, designing efficient parallel algorithms, decomposing optimization problems into multiple subtasks that can be parallelized, and analyzing the feasibility and effectiveness of these algorithms in detail. The results indicate that multiple artificial neural network models are used to establish mapping relationships between design variables and uncertain variables, corresponding objective function values, and constraint function values. The objective function and each constraint function are trained with one network each, and a heuristic algorithm is selected as the inner and outer layer optimization solver. © 2024 IEEE.

关键词： Fuzzy neural networks

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Implementation and deployment of the integration of IoT devices in the development of GIS in the cloud platform

Implementation and deployment of the integration of IoT devi...

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international conference on Artificial Intelligence, Blockchain, computing and Security, ICABCS 2023

作者： Krishna Kumari, R. Gireesh, N. Bhavani, R. Sathish, K. Senthil, G.A. Praveena, S. Department of Mathematics Panimalar Engineering College Tamil Nadu Chennai India Department of Electronics and Communication Engineering School of Engineering Mohan Babu University Andhra Pradesh Tirupati India Institute of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Tamil Nadu Chennai India Department of Computer Science and Engineering Madanapalle Institute of Technology and Science Andhra Pradesh Madanapalle India Department of Information Technology Agni College of Technology Tamil Nadu Chennai India Department of Electronics and Communication Engineering Mahatma Gandhi Institute of Technology Telangana Hyderabad India

ISBN: (纸本)9781032669663

The technological infrastructure provided by cloud providers, and used as a deployment platform, allows GIS to take advantage of its high storage and processing capacities;while the use of IoT devices allows the automation of the data collection process. However, the current implementations are carried out in an ad hoc manner, without providing solutions that facilitate their design, implementation and reuse. In this work, we propose a development approach that, based on models that describe at a high level of abstraction, both the system architecture and the interaction between its services and IoT devices, allows guiding the implementation and deployment activities in cloud environments. This has been illustrated with the design and implementation of a GIS application analyse the collected spatial data with air quality sensors and were deployed on the Google Cloud platform. © 2024, CRC Press/Balkema. All rights reserved.

关键词： Air quality

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international Sports Competition Live Streaming System Under Computer Big Data technology

International Sports Competition Live Streaming System Under...

引用

2023 international conference on Applied Physics and computing, ICAPC 2023

作者： Ma, Yongping Xinjiang University Xinjiang Urumqi China

ISBN: (纸本)9798350359244

With the rapid development of information technology, there have been significant changes in the way international sports competitions are broadcasted and the viewing habits of the audience. In the past, traditional live streaming relied on broadcasting methods, with audiences receiving unified content and limited interactivity and personalized experience. But with the integration of big data, AI (artificial intelligence), and cloud computing technology, live streaming systems not only provide high-quality audio-visual experiences, but also personalized content and interactive viewing experiences. Therefore, this article mainly uses computer big data technology to design an international sports live broadcast system, taking football as an example. This article focuses on the application of big data in football and sports live streaming, discussing how to use real-time data analysis to enhance the viewing experience, and briefly analyzing how to optimize live streaming content based on audience preferences and feedback. Finally, simulation and questionnaire survey experiments were conducted, and the results were as follows: the optimized live streaming system improved the accuracy of capturing critical moments by 14.1%, efficiency by 20.8%, and user satisfaction by 9.5 points compared to traditional live streaming systems. © 2023 IEEE.

关键词： Big data

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Depth Estimation Method for Monocular Images Combined with Position Estimation 13

Depth Estimation Method for Monocular Images Combined with P...

引用

13th international conference of information and Communication technology, ICTech 2024

作者： Wang, Hongliang Liu, Xingyu Li, Yang Xing, Guoyang Shenyang Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Liaoning Province Human-Computer Interaction System Engineering Research Center Based on Digital Twin Shenyang China

ISBN: (纸本)9798350376258

—In this paper, we propose a monocular image depth estimation method based on ResNet and bitmap estimation. Traditional monocular depth estimation methods usually utilize convolutional neural networks (CNNs) for end-to-end training, but often require large amounts of labeled data. To overcome the problem of difficult data labeling, we use a competitive cooperative learning approach to jointly train depth estimation networks, camera motion estimation, optical flow estimation, and motion segmentation networks. We use ResNet as the backbone network for depth estimation, which achieves efficient feature transfer through residual concatenation. In addition, we introduce a bit-position estimation module to assist the depth estimation task by estimating camera motion and bit-position information. Experimental results show that our proposed method achieves good performance in the monocular depth estimation task and still achieves satisfactory results in the absence of labeled data. ©2024 IEEE.

关键词： Convolutional neural networks

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Predicting methane adsorption ability of MOFs based on the crystal structural information by convolutional neural network 5

Predicting methane adsorption ability of MOFs based on the c...

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5th international conference on Material Science and technology, ICMST 2025

作者： Lu, Gang Jiang, Xiuyi Yang, Qingyuan Zhao, Zhengyang Gu, Weiwei Li, Ruiqi College of Information Science and Technology Beijing University of Chemical Technology Beijing100029 China State Key Laboratory of Organic-Inorganic Composites Beijing University of Chemical Technology Beijing100029 China

ISBN: (纸本)9781510691742

High-throughput computational screening (HTCS) methods have been widely used in addressing the challenges of screening metal-organic framework (MOF) materials with high performance from large datasets. Accurately predicting the performance of MOFs with hypothetical structures, such as adsorption capacity for methane, can be a great help to HTCS. Traditional molecular dynamics simulation methods are computationally cumbersome and costly. Feature engineering-based machine learning methods have a high reliance on expert experience to extract effective features, some of which can be time-consuming to calculate. Although some classical machine learning models can already achieve good performance, the heavy burden for features computation prior to model training would eventually limit their practical applications, flexibility and generality. In this paper, an approach is proposed for predicting the methane adsorption ability of MOFs directly from their crystal structural information recorded in Crystallographic information File (CIF)-formatted files, without the need for molecular dynamics simulation or calculating any physical or chemical properties. By expressing the structural information in the crystal cells of MOFs as matrices, a deep convolutional neural network model based on residual structure is applied to train an end-to-end model to predict their methane adsorption ability. The experimental results show that the model accomplishes the prediction task with high accuracy, giving the mean square correlation coefficient (R2) as 0.925 and the mean absolute error (MAE) as 22.28 cm3g-1, which demonstrates a good performance over baselines. © 2025 SPIE. All rights reserved.

关键词： Convolutional neural networks

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Quantum security analysis of SM4 algorithm 6

Quantum security analysis of SM4 algorithm

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6th international conference on Wireless Communications and Smart Grid, ICWCSG 2024

作者： Yang, Hao Wang, Chunhong Tang, Xueming Cui, Yongquan Lu, Songfeng Cai, Dunbo Qian, Ling Zhang, Runqing Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan430074 China Wuhan Maritime Communication Research Institute Wuhan430010 China Software Technology Co. Ltd. Suzhou215153 China

ISBN: (纸本)9781510682962

The security of commercial encryption algorithms has always been a focus of attention. The SM4 algorithm, a commercial cryptographic standard, has been recognized by ISO/IEC as an international standard and has shown excellent performance on classical computers. However, with the development of quantum computing, traditional encryption algorithms are facing new challenges. This paper investigates the quantum realization of SM4 algorithm. By applying the Grover algorithm to the SM4 algorithm, we conducted a quantum exhaustive attack and provided an estimation of the required quantum resources. This study offers a novel perspective on the application of quantum computing in breaking commercial encryption algorithms, which holds significant implications for the future development of quantum secure communication and cryptography. © 2024 SPIE.

关键词： Encryption algorithms

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