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检索条件"任意字段=7th International Conference on Computer and Information Processing Technology, ISCIPT 2022"

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A Comparison of Machine Learning Methods with Feature Extraction for Classification of Patients with Dementia Risk 7

A Comparison of Machine Learning Methods with Feature Extrac...

引用

7th international conference on Digital Arts, Media and technology, DAMT 2022 and 5th ECTI Northern Section conference on Electrical, Electronics, computer and Telecommunications Engineering, NCON 2022

作者： Chaiyo, Yanawut Temdee, Punnarumol Mea Fah Luang Unmversity Computer and Communication Engineering for Capacity Building Research Center School of Information Technology Chiang Rai57100 Thailand Mae Fah Luang University Computer and Communication Engineering for Capacity Building Research Center School of Information Technology Chiang Rai Thailand

ISBN: (纸本)9781665495103

Dementia is becoming more common due to the aging society. It is necessary to identify the patients at risk of dementia early, although the diagnosis of dementia is very difficult, especially at the beginning. A major challenge in classifying patients with dementia is to achieve high accuracy. In this paper, a comparison of machine learning-based classifications of dementia patients is proposed. the open data of Kaggle is used in this paper. Five different classifiers include support vector machine (SVM), decision tree (DCT), random forest (RF), k-nearest neighbors (KNN), and neural networks (NN) are studied. From the comparison, all five classifiers perform well with the deployed data, although the KNN and SVM performed the best in data with and without feature extraction methods. the accuracy rates for all five classifiers are 91.50%, 95.70%,95.70%,95.70%, 95.30%, for DCT, SVM, RF, KNN, respectively. In addition, the accuracy of using the feature extraction method, and setting change feature is 95.70% for SVM, NN, and KNN, respectively. © 2022 IEEE.

关键词： Classification (of information)

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Pre-Activation - Spatial Attention Module for Multiple Catheters and Tubes Classification 7

Pre-Activation - Spatial Attention Module for Multiple Cathe...

引用

作者： Borvornvitchotikarn, thuvanan Yooyativong, thongchai Mae Fah Luang University School of Information Technology Chiang Rai Thailand

ISBN: (纸本)9781665495103

Catheters and tubes are used in emergency departments and intensive care units to keep severely ill patients alive. the proper catheter or tube placement is essential to avoid serious complications. Such issues can be solved if they are found early. the catheters are usually assessed by chest x-rays. Attention modules have recently demonstrated the benefit of improving spatial encoding in multi-label classification tasks on chest X-ray images. In this paper, we propose a Pre-Activation-Spatial Attention (PAc-SA) module. It improves the spatial attention module for multiple catheters and tubes image classification efficiently. In its computation, the proposed module used BN and ReLU as pre-activations. Experiments on the RANCZR-CLiP dataset show that the proposed PAc-SA module achieves better than others, with the best accuracy score of 94.65% and the highest average precision score of 65.18%, respectively, and reduces the network model parameters. © 2022 IEEE.

关键词： Image classification

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Leakage Analysis of Residential Water Supply Network Based on Night Minimum Flow Method and Auto-Regressive Moving Average Model 7

Leakage Analysis of Residential Water Supply Network Based o...

引用

7th international conference on Intelligent Computing and Signal processing, ICSP 2022

作者： Yingzhuo, Xu Jieru, Zhao Jun, Zhou Xi'an Shiyou University School of Computer Science Xi'an China Mountain Range Technology Co. Ltd Xi'an China

ISBN: (纸本)9781665478571

Urban water supply system is an important part of public facilities. the quality of water supply pipe network directly affects the living standard of residents, and the leakage of water supply pipe network will cause a lot of waste of water resources. In this article, the night minimum flow method and the normal distribution model are used to analyze the leakage of the community water supply network and determine the leakage threshold of the community. At the same time, Auto-Regressive Moving Average (ARMA) model is used to predict the state of water supply network, and leakage warning is timely. In this article, the effectiveness of the proposed model is verified by experiments, which provides a method for timely sensing the state of the community water supply pipe network and controlling leakage. © 2022 IEEE.

关键词： Water supply

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Applying Association Rules for Summary Sheet Marketplace 7

Applying Association Rules for Summary Sheet Marketplace

引用

作者： Binchai, Nidjaree Songmuang, Vorameth Worrawat, Kullasatree Chondamrongkul, Nacha Mae Fah Luang University School of Information Technology Thailand

ISBN: (纸本)9781665495103

Enrolling in multiple courses require a student to comprehend contents from all courses. As the examinations approach, some students got difficulty i n p reparation a s they have to manage to read the entire content so choosing what to read wisely is important. the summary sheet is an important reading source that many choose to revive their understanding. As finding a suitable summary sheet is a challenge, we apply the association rules to find t he right summary sheet f or different persons. the association rules are designed to match summary sheets with the demand of students. Our approach serves as a guideline of how to design and develop an application that delivers suitable content to the learners. © 2022 IEEE.

关键词： Association rules

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Smart Story Telling Model with Emotion-Based Enunciation and an Interactive Query Resolver 7

Smart Story Telling Model with Emotion-Based Enunciation and...

引用

7th IEEE international conference for Convergence in technology, I2CT 2022

作者： Bohra, Arushi Sethi, Laksh Nag, Karthik Kanwal, Preet Pes University Dept. of Computer Science and Engineering Bangalore India

ISBN: (纸本)9781665421683

Emotion detection from text is a field of research that involves the recognition of emotions such as anger, disgust, fear, happiness, sadness, and surprise from text. the conversion of text to audio with enunciation based on the detected emotions from text is a contemporary field of study that has short explorations done. the paper presents a methodology and design to classify the emotional affinity of sentences in the narrative domain of children's fairytales using a transformer-based natural language processing technique called the BERT model for subsequent usage in the appropriate expressive rendering of text to speech synthesis using statistical models. the paper also presents a methodology to implement a question-answering system to resolve queries regarding the story by producing an audio clip containing the most appropriate answer extracted through a natural language processing technique called the ALBERT model. the model developed can detect emotions from text with an accuracy of 83%, convert text to audio with emotion-based enunciation with an accuracy of 90%, and the question-answering system produces an accuracy of 80%. the future work will focus on increasing the features taken into consideration for manipulating neutral audio. Detection of sarcasm and handling of complex sentences having multiple emotions will also be included. © 2022 IEEE.

关键词： Machine learning

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A System to Detect Fake Products using Blockchain technology 7

A System to Detect Fake Products using Blockchain Technology

引用

7th international conference on Communication and Electronics Systems, ICCES 2022

作者： Agrawal, Nidhi Kushwaha, Himanshu Shetty, Saujanya Lobo, Vivian Brian St. John College of Engineering and Management Department of Computer Engineering Palghar India

ISBN: (数字)9781665496346

ISBN: (纸本)9781665496346

there are a large number of fake products in the market being manufactured, distributed, sold, and purchased. Here, the meaning of fake products is products that are not from registered or branded sellers and manufacturers. Fake products are actually gaining more importance in the market because of low cost and similarity of them with original products. In this study, genuinity of fake products is determined to help users so that they can distinguish between fake and original products with the help of blockchain technology and cryptocurrency. QR codes will help users to scan and acquire overall information of a product such as basic details, genuinity, ownership, and seller information. © 2022 IEEE.

关键词： Smart contract

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Design and Operation of IoT System and Power Communication with Digital Twin technology 7

Design and Operation of IoT System and Power Communication w...

引用

7th international conference on computer Network, Electronic and Automation, ICCNEA 2024

作者： Lou, Jia Wang, Chaoer Xu, Mengjie He, Le Zhang, Pengjie Information and Telecommunication Branch State Grid Zhejiang Electric Power Co. Ltd Hangzhou China

this paper explores how to integrate digital twin technology into IoT system design to achieve more efficient monitoring and maintenance of power communication networks. By introducing digital twin technology, the real-time performance and accuracy of embedded systems in power communication are enhanced, providing strong data support and simulation environments for predictive maintenance and fault diagnosis. this paper combines theoretical research with practical applications to propose an embedded IoT system design based on the ARM9 platform and verifies its effectiveness in power communication networks. In the testing phase, the ARM9-based IoT system demonstrated a processing speed 15% faster than previous designs, with a latency reduction of 18% in communication processes. these enhancements contribute to the overall efficiency and reliability of power communication networks. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： Predictive maintenance

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Enhancing the Resolution of ChestX-ray Images with SRGAN and Sub-Pixel CNN 7

Enhancing the Resolution of ChestX-ray Images with SRGAN and...

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7th international conference on Image information processing, ICIIP 2023

作者： Reddy, K. Lokeshwar Sudharson, S. Natarajan, B. theetchenya, S. Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science And Engineering Chennai India Computer Science And Engineering Vellore Institute of Technology Chennai India Computer Science And Engineering Sona College of Technology Salem India

ISBN: (纸本)9798350371406

A crucial diagnostic tool for respiratory and heart disorders is chest X-ray imaging. However, the limited resolution of acquired images can hinder accurate interpretation and subsequent treatment decisions. To address this challenge, we employ deep learning-based super-resolution techniques, specifically SRGAN and ESPCN, to enhance the chest X-ray images. In this study, we proposed a modified ESPCN and present our findings on the application of SRGAN and ESPCN for enhancing chest Xray images. the enhanced image resolution enables radiologists to visualize fine details and subtle abnormalities that were previously difficult to discern. this enhancement significantly improves image interpretation and diagnostic accuracy. Moreover, our findings demonstrate the potential of super-resolution techniques for medical education and training. through extensive experimentation, we saw significant visual improvements, as evidenced by PSNR(peak signal-to-noise ratio) of SRGAN and proposed ESPCN are 40.46 and 40.17, and achieved SSIM values 0.84 and 0.71 respectively. In conclusion, our study showcases the efficacy of SRGAN and ESPCN in enhancing chest X-ray imaging. By improving image quality and diagnostic accuracy, these techniques have the potential to revolutionize medical diagnostics, leading to better patient outcomes and a more effective healthcare system. © 2023 IEEE.

关键词： Image resolution

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Sentiment Analysis for IMDb Reviews Using Deep Learning Classifier 7

Sentiment Analysis for IMDb Reviews Using Deep Learning Clas...

引用

7th international conference on Image and Signal processing and their Applications, ISPA 2022

作者： Sabba, Sara Chekired, Nahla Katab, Hana Chekkai, Nassira Chalbi, Mohammed Abdelhamid Mahri University Laboratory of Data Science and Artificial Intelligence Department of Software Technologies and Information Systems Constantine Algeria Abdelhamid Mahri University Department of Software Technologies and Information Systems Constantine Algeria Claude Bernard University Liris Laboratery Lyon France Laboratory of Educational and Psychological Practices Department of Psychology of Educational Sciences and Speech Therapy Constantine Algeria

ISBN: (纸本)9781665480420

Due to the sheer volume of opinion-rich web resources, a lot of current researches are focusing on sentiment analysis. the goal is to create new models that are able to recognize and classify the opinions or sentiments expressed in an electronic text to evaluate and improve a given system. Many solutions have been proposed to deal with this problem, and most of them are based on Machine Learning techniques. Currently, Deep Learning is a rapidly growing field, it has proven its effectiveness to solve many complex problems due to its ability to learn and extract meaningful information from data. therefore, many contributions attempt to adopt this approach in the sentiment analysis area such as that of sentiment classification. In this work, we address the problem of user sentiment analysis by proposing a new solution based on natural language processing and deep convolutional neural network. the proposed solution has been tested on the IMDB dataset containing 50,000 movie reviews. the obtained results were very convincing with an accuracy of 99% in the training phase and 89% in the testing phase. © 2022 IEEE.

关键词： Sentiment analysis

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Escort - Natural Language processing Based University Students Guidance System 7

Escort - Natural Language Processing Based University Studen...

引用

7th international conference on information technology Research, ICITR 2022

作者： Srinivasan, Deepika Uthayakumar, Abarna thiyagalingam, Parathan Ravindran, Shanghavi De Silva, Hansi Kasthururarthna, Dharshana Sri Lanka Institute of Information Technology Department of Software Engineering Colombo Sri Lanka

ISBN: (数字)9798350332032

ISBN: (纸本)9798350332032

Universities play a significant role in students' lives and aim to provide the best education, knowledge, and experience. However, university students face many difficulties during their university life including language, communication issues, and the inability to get proper guidance for education and career improvement. this paper proposes an approach to overcome these issues. With the help of Natural Language processing (NLP), in this paper, several solutions are recommended for the mentioned issues. First, a chatbot helps to communicate with the university administration, where students can ask relevant administrative-related questions. A recommendation system is developed to provide solutions for their psychological issues. Another recommendation system is built for career guidance which will help students to identify the future career of their interest, and the provided mentors will be able to guide them. Another recommendation system identifies the performance of students in each module according to their performance level. the system recommends learning materials to improve their level. With these components, ESCORT - A university students' guidance system, will make students' life easier and more efficient. © 2022 IEEE.

关键词： Students

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