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检索条件"任意字段=3rd International Conference on Intelligent Data Engineering and Automated Learning"

共 20250 条记录，以下是4621-4630 订阅

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An intelligent Technique for the Effective Prediction of Monkeypox Outbreak 3

An Intelligent Technique for the Effective Prediction of Mon...

引用

3rd IEEE international conference on Artificial Intelligence, ICAI 2023

作者： Mir, Azka Rehman, Attique Ur Javaid, Sabeen Ali, Tahir Muhammad University of Sialkot Department of Software Engineering Sialkot Pakistan GULF University for Sciences and Technology Department of Computer Science Mubarak Al-Abdullah Kuwait

ISBN: (纸本)9798350322125

Monkey pox is a viral disease that spreads from animals especially monkey to human beings. Monkey pox outbreak has been increasing at a concerning rate. The outbreak of monkey pox has infected several people around the world. The extent and intensity of the disease can be determined by the occurrence of the symptoms. The objective of this paper is to predict monkeypox virus so that outbreak can be administered before monkeypox looms as a viral health hazard. The monkeypox case has been classified as confirmed, discarded and suspected. This paper uses a supervised machine learning model to predict the status of monkey pox case. To diagnose monkeypox virus case, clinical parameters are required. The selected dataset contains the parameters of monkey pox virus from April 2022 onwards. It is necessary to predict the monkey pox outbreak before it effects more valuable lives. For the purpose of this paper, supervised machine learning techniques have been used to determine the performance of the dataset through experimental analysis. The experiment has been performed using various classifiers such as Decision tree, Naïve Bayes etc. to compare the accuracy rate. After the comparative analysis of the resulting accuracy percentage of different classifiers, we have proposed the model with the classifier with the highest accuracy. Our proposed model has achieved an accuracy rate of 93.51% using K-NN classifier with k=5 neighbors. Rapid miner platform is used for the application of the machine learning tools and techniques for the purpose of this research. This paper highlights the effective machine learning steps for the development of highly accurate model using machine learning techniques on monkey pox outbreak dataset. © 2023 IEEE.

关键词： Viruses

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intelligent Overcurrent and Distance Relay Coordination in Power Networks 3

Intelligent Overcurrent and Distance Relay Coordination in P...

引用

3rd IEEE international conference on Sustainable Energy and Future Electric Transportation, SeFet 2023

作者： Majhi, Abhilash Asit Kumar Singh, Manohar Ray, Papia Veer Surendra Sai University of Technology Department of Electrical Engineering Burla Sambalpur India Punjab Engineering College Deemed University Chandigarh Department of Electrical Engineering India

ISBN: (纸本)9798350319972

The increased deployment of distributed generators (DGs) in distribution networks has brought new challenges to power system protection coordination. With multiple generation sources supplying the distribution network, the conventional protective devices that were designed for centralized generation may not be sufficient to ensure proper protection coordination in case of fault. This research provides an overview of the impact of distributed generations (DGs) on protection coordination in distribution networks, as well as an analysis of the different approaches that can be used to select and coordinate protection systems in the presence or absence of DGs. The proposed approach for selecting the optimal overcurrent (O/C) relays for protection coordination takes into account various relay characteristics and uses the Teaching learning Based Optimization (TLBO) algorithm to determine the best combination of relays for achieving optimal coordination. Optimization of the zones of distance relays is also done and proper coordination time interval (CTI) of 0.2s or more is maintained. The optimization results are tested and validated in Electrical Transient Analyzer Program (ETAP). The effectiveness of the proposed method for achieving optimal coordination in practical power system networks like IEEE-9 bus test system is demonstrated through simulation results, which show that the method can produce feasible and effective solutions. © 2023 IEEE.

关键词： Distributed power generation

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RIS-Assisted Indoor Visible Light Positioning Based on Sparse Bayesian learning 3

RIS-Assisted Indoor Visible Light Positioning Based on Spars...

引用

3rd international conference on intelligent Communications and Computing, ICC 2023

作者： Wang, Yuhao Wu, Sifan Yu, Lisu Xu, Chuan Wang, Zhenghai Cai, Xiangxiang School of Information Engineering Nanchang University Jiangxi Nanchang330031 China Digital Technology Application Industry College Shangrao Normal University Jiangxi Shangrao334001 China School of Mathematics and Computer Science Nanchang University Jiangxi Nanchang330031 China

ISBN: (纸本)9798350308327

Visible light communication (VLC) relies heavily on the line of sight (LoS). Once the LoS link is blocked, the communication efficiency will be greatly reduced. The indoor environment is complex, and it is inevitable that the LoS link will be blocked. In order to solve such problem, we have integrated the reconfigurable intelligence surface (RIS) into the indoor visible light positioning (VLP) system to enhance the positioning accuracy when the LoS link is blocked. We have proposed a sparse Bayesian learning (SBL)-Based algorithm to solve the formulated joint-optimization problem of estimated position, noise variance, and sparsity. This algorithm uses Bayesian reconstruction theory and conditional probability expressions to calculate the mean and covariance matrix of the formula, and further obtain the updated noise variance value and sparsity value, thereby finally attain the accurate position. From the simulation results, the positioning accuracy can reach 0.41m when the cascade channel length is 10m. © 2023 IEEE.

关键词： Covariance matrix

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Classification of Green Tea Samples Based on Epigallocatechin-3-Gallate Content Using Molecular Imprinting Polymerization Technique 3

Classification of Green Tea Samples Based on Epigallocatechi...

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3rd IEEE international conference on Control, Instrumentation, Energy and Communication, CIEC 2024

作者： Modak, Angiras Das, Debangana Roy, Runu Banerjee Jadavpur University Dept. of Instrumentation and Electronics Engineering Kolkata India Silicon Institute of Technology Dept. of Electronics and Communication Engineering Bhubaneshwar India

ISBN: (纸本)9798350313703

The proposed system implements a machine learning based approach to classify samples of green tea based on the EGCG (Epigallocatechin-3-Gallate) content. The EGCG content in green tea samples are estimated by using the synthesized molecularly imprinted polymer (MIP) electrode. The voltametric responses were obtained using a three-electrode set-up. The data was recorded and pre-processed. The responses obtained after pre-processing are fed for feature selection using UMAP (Uniform Manifold Approximation and Projection) algorithm, in which the number of features is reduced to generate optimized output. Further, the selected features are processed with K-means clustering method, to distinguish the green tea samples. The classification of green tea samples is performed by using XGBoost (Extreme Gradient Boost) algorithm. The use of XGBoost provides fast converging with limited steps, direct route to the least error and simplified calculations to lower computational costs and improve speed. Finally, the efficacy of the proposed system is calculated based on metrics namely, Calinski Harabasz Score, Distortion score and Silhouette score for K-means clustering technique. The efficiency of the introduced XGBoost method is calculated based on the metrics such as accuracy, AUC (Area under Curve), Recall, Precision, F1-score, Kappa and MCC (Matthews Correlation Coefficient) with outcomes of 0.96, 0.99, 0.96, 0.96, 0.96, 0.94 and 0.95. Thus, the outcome of the proposed method denotes the effective performance in classifying the green tea samples. © 2024 IEEE.

关键词： Polymerization

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Traffic Sign Recognition Based on Improved VGG16 Algorithm 3

Traffic Sign Recognition Based on Improved VGG16 Algorithm

引用

3rd international conference on Computer Vision and Pattern Analysis, ICCPA 2023

作者： Wang, Jianxia Jiang, Shan Zhou, Wanzhen School of Information Science and Engineering Hebei University of Science and Technology Shijiazhuang China

ISBN: (纸本)9781510667563

The detection and recognition of traffic signs acts an extremely crucial role in driverless technology and assisted driving systems. In view of the low recognition rate of traffic signs, this paper improves the neural network based on the existing VGG16 network architecture, including adding BN layer, adopting batch normalization algorithm and adding attention mechanism. The GTSRB data set is enhanced by scaling and random rotation. The data is preprocessed by image graying and image normalization. In this paper, the model recognition rate reached 99.34%, which is of great value to enhance the recognition accuracy of traffic signs and promote the development of intelligent transportation. © 2023 SPIE.

关键词： Traffic signs

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Annular gap width measurement based on sub-pixel edge fitting 3

Annular gap width measurement based on sub-pixel edge fittin...

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3rd international conference on Electronic Information engineering and data Processing, EIEDP 2024

作者： Zhang, Jiawei Xu, Yongli Liu, Mingyang Liu, Yufeng Du, Guangrong School of Information Science and Engineering Shenyang University of Technology Shenyang110870 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China Northwest Industries Group Co. Ltd. Xi’an710043 China

ISBN: (纸本)9781510680531

To address the difficulty in measuring the annular joint gap structure with structured light, a detection method based on sub-pixel edge fitting is proposed. Firstly, the centerline is extracted by combining the directional template method with the gray centroid method, and then the laser groups are positioned accordingly. Secondly, The Zernike moment method is used to detect the sub-pixel contours of each pair of laser lines. Subsequently, the sub-pixel feature points of the light pattern are obtained by sliding the feature circle along the centerline. Finally, the gap value is determined by calculating the average distance between the fitted straight lines of the sub-pixel feature points. A single annular gap is selected for both visual measurement and manual feeler gauge measurement. The measurement results show that the error between the final measurement value of the proposed method and the manual feeler gauge measurement is no greater than 0.05mm. This indicates that this detection method exhibits good accuracy and high stability. This visual measurement method can meet the requirements for the measurement accuracy of annular joint gap widths. © 2024 SPIE.

关键词： Method of moments

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Automatic Bug Triaging Analysis using Machine learning Techniques: A Review 3

Automatic Bug Triaging Analysis using Machine Learning Techn...

引用

3rd international conference on Issues and Challenges in intelligent Computing Techniques, ICICT 2022

作者： Sirohi, Rishabh Singh, Priya Delhi Technological University Department of Software Engineering Delhi India

ISBN: (纸本)9781665482684

As technology is exponentially expanding day by day, the developers and testing team give their best to resolve issues as earliest as possible so that they can deliver the product to customer on time. Generally, in micro organizations, identifying the relevant developer to resolve a particular bug is easy and not much time consuming but for big organization it is still challenging to locate the right developer having the potential to resolve the bug on time which is one of the major task of bug triaging. In this review, we would be analyzing various techniques that will help in performing Automatic bug triaging and will try to find the best technique on the basis of some set of Research Questions, which will help in knowing the statistical analysis of these techniques. © 2022 IEEE.

关键词： Machine learning

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Design and Development of a Chatbot for Personalized learning in Higher Education 3rd

Design and Development of a Chatbot for Personalized Learnin...

引用

3rd international conference on Computer Vision, High Performance Computing, Smart Devices, and Networks, CHSN 2022

作者： Algabri, Hayder Kareem Kamat, Rajanish K. Kharade, Kabir G. Muppalaneni, Naresh Babu Department of Computer Science Shivaji University Maharashtra Kolhapur India Dr. Homi Bhabha State University Maharashtra Mumbai India Department of CSE Indian Institute of Information Technology Design and Manufacturing Andhra Pradesh Kurnool518008 India

ISBN: (纸本)9789819966899

Technology now plays a more significant role in our everyday lives, impacting how students learn and gain knowledge. The use of artificial intelligence allows educators to provide students with a personalized learning environment. Systematically detecting whether or not students are grasping the material has been created. Based on the feedback, we can also determine the student’s starting point. Conversational agents or chatbots could be used to supplement teacher instruction and reduce the costs of informal education. The development and training of an intelligent conversational agent have long been a goal of humanity and a significant challenge for scientists and programmers. It was still just a dream until recently. On the other hand, language teachers have a new hope thanks to cutting-edge technologies like deep learning and neural networks, which provide intelligent chatbots that can learn through communication just like humans. His research aims to create an emotionally realistic chatbot system using artificial intelligence to improve the chatbot’s believability. This study aims to create a chatbot that can be integrated into a personalized teaching–learning process. The goal of the study is to determine the efficacy of the developed chatbot in personalized learning. Its developed system enables it to provide a suitable personalized learning solution. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Students

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VR-based Silent Reading and Rosenberg Tests: Machine-learning Approach to Identify learning Disorders 3

VR-based Silent Reading and Rosenberg Tests: Machine-Learnin...

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3rd IEEE international conference on Metrology for eXtended Reality, Artificial Intelligence and Neural engineering, MetroXRAINE 2024

作者： Materazzini, Michele Morciano, Gianluca Alcalde-Llergo, José Manuel Yeguas-Bolivar, Enrique Zingoni, Andrea Taborri, Juri University of Tuscia Dept. of Economics Engineering Society and Business Organization Viterbo Italy University of Córdoba Córdoba Spain

ISBN: (纸本)9798350378009

This study explores the intersection of self-esteem assessment, specific learning disorders (SLDs), and emerging technologies, particularly virtual reality (VR) and machine learning (ML). Through this scope, the research involved the development of novel VR-based tools for administering silent reading and Rosenberg tests, designed to simulate real-world academic challenges and social interactions. A sample of 40 Italian university students, including those diagnosed with SLDs and a control group, participated in the study. data collected from VR were analyzed using ML algorithms, with a focus on dyslexia detection. The findings underscored the critical role of self-esteem in academic performance and overall well-being for individuals with SLDs. ML models, particularly support vector machines (SVM), demonstrated efficacy in identifying dyslexic tendencies based on data from VR. This multidisciplinary approach contributes to advancing personalized intervention strategies for individuals with SLDs, emphasizing early diagnosis and targeted support systems. © 2024 IEEE.

关键词： Adversarial machine learning

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Bitcoin Prediction using Convolutional Neural Network 3

Bitcoin Prediction using Convolutional Neural Network

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3rd international conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023

作者： Dhanushwar, M. Gokul Krishnan, K. Gopinath, M. Vinod, S.A. Lincy, R. Babitha Sri Eshwar College of Engineering Department of CCE Coimbatore India

ISBN: (纸本)9798350343632

This research study addresses the challenging issue of predicting the highly volatile price of Bitcoin, which exhibits significant fluctuations. Surprisingly, despite their successful applications in various engineering and scientific domains, Convolutional Neural Networks (CNNs) have been largely neglected in the context of financial time series modeling. Therefore, the primary emphasis of this study is on exploring the potential of CNNs for improving Bitcoin price prediction. Our model harnesses the capabilities of CNN to extract crucial features from historical Bitcoin transaction data, revealing underlying patterns and trends. Subsequently, LSTM is employed to analyze and predict Bitcoin price movements based on these learned features. To bolster prediction accuracy, we integrate external factors, including macroeconomic variables and investor sentiments, with the historical Bitcoin data. The model's performance is rigorously evaluated on a comprehensive real-world dataset, assessing its effectiveness in predicting Bitcoin's price direction and magnitude. The results demonstrate promising prediction accuracy, surpassing conventional models and showcasing the potential of leveraging artificial intelligence in cryptocurrency price forecasting. © 2023 IEEE.

关键词： Artificial Intelligence Bitcoin prediction Convolutional Neural Network (CNN) Deep learning

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