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检索条件"任意字段=2023 International Conference on Computer Science and Automation Technology, CSAT 2023"

共 68880 条记录，以下是1461-1470 订阅

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Personalized Secure E-Identity Card Using Block Chain

Personalized Secure E-Identity Card Using Block Chain

引用

2023 international conference on computer Communication and Informatics, ICCCI 2023

作者： Burugari, Vijay Kumar Kanmani, P. Selvaraj, Prabha Potluri, Varun Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering K L Deemed to Be University Vaddeeswaram Andhra Pradesh India SRM Institute of Science and Technology Kattankulathur Department of DSBS Chengalpattu India VIT-AP University Amaravati School of Computer Science and Engineering Andhra Pradesh India University of Texas Dallas Richardson Master of Science in Computer Science TX United States

ISBN: (纸本)9798350348217

Blockchain technology is a new technology in digital platforms for making transactions in a decentralized manner. Blockchain is used for last some year for bitcoin. The preceding block's cryptographic hash, a timestamp, and a transaction are all included in every block in the blockchain. As a result, it is noticeable for security on an identity card. Implementation of blockchain technology for digital identity card maintains a secure network for the user. Identity card has personal information and some important information included. Individual person identity cards are stored in file with encryption method which will hacked by hackers. So a system using blockchain technology for identity card is proposed. In distribute file system, data security for information exchange and storage is provided using blockchain and IPFS (Interplanetary File System) for storing and communicating data securely. © 2023 IEEE.

关键词： Blockchain

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Discussion on the Optimization and Integration of computer Application Intelligent Computing technology and Information Digitization 2

Discussion on the Optimization and Integration of Computer A...

引用

2nd international conference on Data Analytics, Computing and Artificial Intelligence, ICDACAI 2023

作者： Chen, Lijuan Shandong University of Political Science and Law Shandong Jinan250014 China

ISBN: (纸本)9798350339765

Under the background of the era of network information, the optimization and integration of computer application technology and information management has an important value significance in providing guarantee for enterprise information security, optimizing the function of enterprise information management system, and improving the effectiveness and quality of enterprise information *** paper introduces relevant concepts, analyzes the integration of computer application technology and information management, and proposes the optimization and integration strategy of computer application technology and information management. © 2023 IEEE.

关键词： Information management

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Body-Focused Expression Analysis: A Conceptual Framework 17th

Body-Focused Expression Analysis: A Conceptual Framework

引用

17th international conference on Universal Access in Human-computer Interaction (UAHCI) part of the 25th international conference on Human-computer Interaction (HCI)

作者： Rodrigues, Joao M. F. Cardoso, Pedro J. S. Univ Algarve LARSyS P-8005226 Faro Portugal Univ Algarve ISE P-8005226 Faro Portugal

ISBN: (纸本)9783031358968;9783031358975

Humans are prepared to comprehend others' emotional expressions from subtle body movements or facial expressions, and they change the way they communicate in the function of those interactions/responses. Emotions influence sentiment and sentiment influences emotions. To transition from the traditional human-computer interaction to a human-machine collaboration, where the machine delivers relevant information and functionalities in a timely and appropriate manner, machines, user interfaces, and robots need to be equipped with such capabilities. The current state-of-the-art in methods and models for body emotion and sentiment classification, as well as existing datasets, are reviewed in this position paper. In this context, it also suggested the creation of a database for body expression analysis and a framework for emotion and sentiment prediction.

关键词： Affective Computing Human-Centred AI Body Emotions Body Expression computer Vision

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The Performance Evaluation of Static Obstacle Recognition by Underwater Pressure Characteristics for Underwater Spherical Robot 20

The Performance Evaluation of Static Obstacle Recognition by...

引用

20th IEEE international conference on Mechatronics and automation, ICMA 2023

作者： Li, Ao Guo, Shuxiang The Key Laboratory of Convergence Biomedical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology Beijing Institute of Technology Beijing100081 China Southern University of Science and Technology The Department of Electronic and Electrical Engineering Guangdong Shenzhen518055 China

ISBN: (纸本)9798350320831

Underwater spherical robots are flexible and often perform tasks in narrow, dark and complex environments. The artificial lateral line system inspired by the lateral line system of fish can recognize obstacles. However, currently, the recognition of obstacles under the artificial lateral line system is mainly based on the vibration characteristics of obstacles. Based on the blank recognition of static obstacles, this paper analyzes the feasibility of recognition static obstacles. A polynomial regression model is proposed to detect static obstacles (walls) by moving robots. Finally, the effectiveness of obstacle recognition is verified by experiment and simulation. © 2023 IEEE.

关键词： Regression analysis

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A Survey on Mapping of Urban Green Spaces within Remote Sensing Data Using Machine Learning & Deep Learning Techniques 15

A Survey on Mapping of Urban Green Spaces within Remote Sens...

引用

15th international conference on computer and automation Engineering, ICCAE 2023

作者： Burrewar, Smita Sunil Haque, Mazharul Haider, Tanwir Uddin National Institute of Technology Patna Architecture & Planning Department Bihar Patna India National Institute of Technology Patna Computer Science & Engineering Department Bihar Patna India

ISBN: (纸本)9798350396225

For environmental protection, urban planning, monitoring, and management of the urban ecosystem, mapping urban green spaces is a crucial undertaking. A vital source of information for United Nations Sustainable Development Goal 11.7 could come from urban green space mapping. The standard method of mapping urban green spaces requires field measurements and takes a lot of time. It is also important to update urban green space maps periodically because urban green spaces can change quickly over time due to development. With the advent of high-resolution satellite sensors like Sentinel-1 and Sentinel-2, a large number of remote sensing images may be gathered, providing quick and precise information over urban areas. This work intends to offer a new perspective on how crowd sourced geospatial big data and remote sensing may be combined to enhance the mapping of urban green spaces, including time optimization and accurate information through machine learning and deep learning. For the revitalization of cities, this data will be valuable. Remote sensing imagery data can be classified using machine learning techniques like Support vector machines (SVM), Random forests (RF), and Naive Bayes (NB). In deep learning techniques such as Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), K Nearest Neighbor (KNN), Generative Adversarial Networks (GAN), and Recurrent Neural Networks (RNN) can be used to classify remote sensing images. © 2023 IEEE.

关键词： Remote sensing

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An inverse kinematic solution for redundant robotic arms based on a combination of analytical and geometric methods 9

An inverse kinematic solution for redundant robotic arms bas...

引用

9th international conference on Mechanical Engineering, Materials, and automation technology, MMEAT 2023

作者： Pan, Chengshan Zhao, Yongguo Wang, Peng Xiao, Yongfei Institute of Automation Qilu University of Technology Shandong Academy of Sciences Shandong Provincial Key Laboratory of Robot and Manufacturing Automation Technology Jinan China

ISBN: (纸本)9781510668584

Seven-degree-of-freedom redundant robotic arms with linkage offsets are suitable for complex tasks and have obvious geometric significance. However, the redundancy of degrees of freedom also increases the complexity of the spatial configuration, which makes the kinematic solution slow, computationally intensive and subject to iterative cumulative errors. This paper proposes an inverse kinematic solution method based on a combination of analytical and geometric methods to avoid self-collision by limiting the joints. This allows the redundant robot arm to reach the target position quickly and stably with an optimal attitude. Finally, kinematic simulations using Rviz and Gazebo in ROS demonstrate the high accuracy of the method. This provides an accurate, real-time, complete and stable solution for the kinematic solution of the redundant robotic arm and can be effectively applied to related research and development work in the field of robotics. © 2023 SPIE.

关键词： Robotic arms

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A review of research on super-resolution image reconstruction based on deep learning 8

A review of research on super-resolution image reconstructio...

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8th international conference on Intelligent Informatics and Biomedical sciences, ICIIBMS 2023

作者： Yu, Wanjun Liang, Xiayan Shanghai University of Applied Technology School of Computer Science and Information Engineering Shanghai China

ISBN: (纸本)9798350369564

Currently, Super-resolution image reconstruction (SRIR or SR) is a research hotspot in the field of computer vision and image processing. With the development of deep learning, The technology of super-resolution image reconstruction based on deep learning has achieved some research results. In this paper, the concept of super resolution image reconstruction and typical deep network models of super resolution image reconstruction are described first, and then the advantages and disadvantages of different models are compared and analyzed. On this basis, the future of super-resolution image reconstruction methods based on deep learning is forecasted. © 2023 IEEE.

关键词： Generative adversarial networks

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Estimation of Minimum Miscibility Pressure in Impure/Pure N2Based Enhanced Oil Recovery Process: A Comparative Study of Statistical and Machine Learning Algorithms 6

Estimation of Minimum Miscibility Pressure in Impure/Pure N2...

引用

6th international conference on Robotics, Control and automation Engineering, RCAE 2023

作者： Zhu, Xiuli Damarla, Seshu Kumar Huang, Biao University of Shanghai for Science and Technology Department of Control Shanghai China University of Alberta Department of Chemical and Materials Engineering AB Canada

ISBN: (纸本)9798350315301

Minimum miscibility pressure (MMP) prediction plays an important role in design and operation of nitrogen based enhanced oil recovery processes. In this work, a comparative study of statistical and machine learning methods used for MMP estimation is carried out. These methods include weighted k-nearest neighbors, wavelet neural network, general regression neural network, extreme learning machine, regression trees (RTs), random forest, bagging RTs, boosting RTs and Gaussian process regression. Most of the predictive models developed in this study exhibited superior performance over predictive models reported in literature. © 2023 IEEE.

关键词： Nitrogen

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Temperature Prediction for Ultra-Low Temperature Measurement System Based on Improved Extreme Learning Machine Algorithm 3

Temperature Prediction for Ultra-Low Temperature Measurement...

引用

3rd international conference on Electronic Information Engineering and computer Communication, EIECC 2023

作者： Zhang, Zhenyu Dong, Xiang Xue, Yufei Jiang, Man Cao, Huibin School of Electrical Engineering and Automation Anhui University Anhui Hefei230601 China Institutes of Physical Science and Information Technology Anhui University Anhui Hefei230601 China Hefei Institutes of Physical Science Chinese Academy of Sciences Anhui Hefei230601 China

ISBN: (纸本)9798350359961

Temperature monitoring is essential to ensure the operational safety of fusion devices in the ultra-low temperature liquid helium region. However, the unavoidable errors caused by environmental effects severely hinder the accuracy of its temperature measurement. Considering that traditional methods are not accurate enough to predict the temperature at low temperatures, for the first time, this work proposes an algorithm based on the SSA-PSO-ELM network for constructing a prediction model of the cryogenic measurement system. By this method, the initial number of hidden layer nodes is first randomly generated, then the network is trained with weight thresholds, and finally a quadratic optimization search is performed to determine the best network prediction model. Compared with the traditional algorithm, our algorithm effectively reduces the prediction error, improve the accuracy, and realize more accurate temperature monitoring in ultra-low temperature environment. © 2023 IEEE.

关键词： Extreme Learning Machine Particle swarm arithmetic Sparrow algorithm Temperature prediction Ultra-low temperature measurement system

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Post Diagnosis Digital Routine Monitoring System for Patients of Skin Diseases 5

Post Diagnosis Digital Routine Monitoring System for Patient...

引用

5th IEEE international conference on Electrical, computer and Communication Technologies, ICECCT 2023

作者： Bhadula, Shuchi Sharma, Sachin Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India

ISBN: (纸本)9781665493604

The system for post-diagnosis digital routine monitoring of patients with skin diseases is suggested in this research. The system tracks changes in the patterns of skin diseases and categorizes them according to their severity. The classification levels lead to the creation of monitoring graphs that the dermatologist may take into account for enhancing the diagnostic procedure. Once a skin condition is identified, this device enables remote patients to communicate with skin specialists from their home location. This strategy puts a monitoring tool in the hands of people with skin diseases and their doctors. The technology can monitor and treat skin diseases with the aid of machine learning algorithms, assisting clinicians with further prescriptions and testing. In each follow-up plan for each ailment, recovery charts based on severity levels are also provided. The suggested method of application can be used as part of a skin treatment and monitoring program, and a doctor can be consulted to diagnose and assess the patient more swiftly. In order to provide historical health data for future prevention and control, the system is being built to collect patient data and photographs. For the detection and treatment of skin diseases, automation based on machine learning is used. © 2023 IEEE.

关键词： Diagnosis

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