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2023 International Conference on Integrated Intelligence and Communication Systems, ICIICS 2023

作者： Mao, Pandi Liao, Xiaowen Xu, Daolian School of Electrical Engineering and Intelligent Manufacturing Chongqing Metropolitan College of Science and Technology hongqing Yongchuan China School of Arts and Media Chongqing Metropolitan College of Science and Technology Chongqing Yongchuan China Chongqing University College of Optoelectronic Engineering Chongqing Shapingba China

ISBN: (纸本)9798350315455

In order to meet the current training, employment and regulatory needs, the Hong Kong government will launch a comprehensive training program. The system consists of the main arm controller, sensor module, adjustable camera and image acquisition and processing system. The system has the advantages of high precision and reasonable price, and has broad market prospects. In this paper, the problem of autonomous motion control for tracking target is studied, and an active tracking control method for serial action output target is proposed. The learning strategy utilizes visual perception and depth improvement to make decisions, using consecutive frames' visual image as continuous control model for input state and output action. The system has the advantages of high precision and reasonable price, and has broad market prospects. Target tracking is an important application in video surveillance and a new research field in image processing. Video surveillance uses cameras to identify moving or multiple objects, widely used in human-computer interaction, security, traffic control, airports, subway stations, and mass activities. As a result, MUSIC obtained 96% of accuracy, 95% of precision, 94% of f-measure, and 91% of recall. © 2023 IEEE.

关键词： Ace image Face Image Processing sensor module Target tracking technology

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IoT and Peer-to-peer Signal Notification Methods Reduce the Time Needed to Detect Wildfire Heat Points 7

IoT and Peer-to-peer Signal Notification Methods Reduce the ...

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7th International Conference on Green technology and Sustainable Development, GTSD 2024

作者： Panlawan, Nattawat Somsak, Teerasak Thongpron, Jutturit Muangjai, Worrajak Ngaodet, Montri Assanavijit, Visut Thanin, Phiched Sungkham, Suriyon Oranpiroj, Kosol Patcharaprakiti, Noppom Somsak, Peeraya Nakaiam, Kan Program in Electrical Engineering Faculty of Engineering Rmutl Chiang Mai Thailand College of Integrated Science and Technology Rmutl Chiang Mai Thailand Research and Development Institute Rmutl Chiang Mai Thailand Faculty of Business Administration and Liberal Arts Rmutl Chiang Mai Thailand

ISBN: (纸本)9798350386073

The issue of dust and smoke resulting from forest fires in northern Thailand. This is caused by people burning the forest to get forest products. Individuals can start forest fires by intentionally burning the forest to extract forest resources. Deforestation negatively affects the well-being of vulnerable patients and has repercussions on public health. The decrease in tourist numbers impacts the economy. Individuals setting fire to the forest to gather forest resources impact government and public sector connections. The education sector has implemented many strategies to educate and mitigate forest fires. There is a fire suppression system. Remove garbage, leaves, and branches that are flammable. However, forest fires remain a concern. Collaboration among three entities in the community can aid in preventing unauthorized forest fires through communal procedures. From multiple ministries, the local organization department, and the central government Collaborating to safeguard Forest fire suppression and afforestation This study is a component of the forest fire surveillance division. If the forest fire's location is not clearly indicated, participating in combined operations will lead to issues because of the overlap in operational responsibilities. Previously, thermal imaging satellites were utilized for coordinate determination. If the satellite completes two orbits each day and identifies a hot location, it initiates a forest fire. Firefighters cannot reach the area to put out forest fires;thus, they need to enter from a nearby, accessible location. Joining the forest fire prevention volunteer organization is challenging and will require approximately 24 to 25 hours. This study aims to conserve energy by utilizing an loT system that transmits peer-to-peer signals. Individuals are prepared to dismantle this system. The villagers can develop it themselves due to its modest cost of $10. During a forest fire (temperature exceeding 50 degrees Celsius), specific oper

关键词： Fire extinguishers

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Deep Attention Network for Pneumonia Detection Using Chest X-Ray Images

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Computers, Materials & Continua 2023年第1期74卷 1673-1691页

作者： Sukhendra Singh Sur Singh Rawat Manoj Gupta B.K.Tripathi Faisal Alanzi Arnab Majumdar Pattaraporn Khuwuthyakorn Orawit Thinnukool Department of Information Technology JSS Academy of Technical EducationNoidaIndia JSS Academy of Technical Education NoidaIndia Department of Electronics and Communication Engineering JECRC University JaipurRajasthanIndia Harcourt Butler Technological University Kanpur India Department of Electrical Engineering Prince Sattam Bin Abdulaziz UniversityCollege of EngineeringAl Kharj16278Saudi Arabia Faculty of Engineering Imperial College LondonLondonSW72AZUK College of Arts Media and TechnologyChiang Mai UniversityChiang Mai50200Thailand

In computer vision,object recognition and image categorization have proven to be difficult *** have,nevertheless,generated responses to a wide range of difficult issues from a variety of *** Neural Networks(CNNs)have recently been identified as the most widely proposed deep learning(DL)algorithms in the *** have unquestionably delivered cutting-edge achievements,particularly in the areas of image classification,speech recognition,and video ***,it has been noticed that the CNN-training assignment demands a large amount of data,which is in low supply,especially in the medical industry,and as a result,the training process takes *** this paper,we describe an attentionaware CNN architecture for classifying chest X-ray images to diagnose Pneumonia in order to address the aforementioned *** provide attention-aware properties to the Attention *** attentionaware features of various modules alter as the layers become *** a bottom-up top-down feedforward structure,the feedforward and feedback attention processes are integrated into a single feedforward process inside each attention *** the present work,a deep neural network(DNN)is combined with an attention mechanism to test the prediction of Pneumonia disease using chest X-ray *** produce attention-aware features,the suggested networkwas built by merging channel and spatial attentionmodules in DNN *** this network,we worked on a publicly available Kaggle chest X-ray *** testing was carried out to validate the suggested *** the experimental results,we attained an accuracy of 95.47%and an F-score of 0.92,indicating that the suggested model outperformed against the baseline models.

关键词： Attention network image classification object detection residual networks deep neural network

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Hybrid Models for Breast Cancer Detection via Transfer Learning Technique

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Computers, Materials & Continua 2023年第2期74卷 3063-3083页

Currently,breast cancer has been amajor cause of deaths in women worldwide and the World Health Organization(WHO)has confirmed *** severity of this disease can be minimized to the large extend,if it is diagnosed properly at an early stage of the ***,the proper treatment of a patient having cancer can be processed in better way,if it can be diagnosed properly as early as possible using the better ***,it has been currently observed that the deep neural networks have delivered remarkable performance for detecting cancer in histopathological images of breast *** address the above said issues,this paper presents a hybrid model using the transfer learning to study the histopathological images,which help in detection and rectification of the disease at a low *** dataset experiments were carried out to validate the suggested hybrid model in this *** experimental results show that the proposed model outperformed the baseline methods,with F-scores of 0.81 for DenseNet+Logistic Regression hybrid model,(F-score:0.73)for Visual Geometry Group(VGG)+Logistic Regression hybrid model,(F-score:0.74)for VGG+Random Forest,(F-score:0.79)for DenseNet+Random Forest,and(F-score:0.79)for VGG+Densenet+Logistic Regression hybrid model on the dataset of histopathological images.

关键词： Histopathological deep neural network machine learning breast cancer binary classification transfer learning

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Tactile Displays Driven by Projected Light

arXiv

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arXiv 2024年

作者： Linnander, Max Goetz, Dustin Reardon, Gregory Kumar, Vijay Hawkes, Elliot Visell, Yon Department of Mechanical Engineering United States Department of Bioengineering United States Media Arts & Technology Program United States Department of Electrical and Computer Engineering University of California Santa Barbara United States

Tactile displays that lend tangible form to digital content could transform computing interactions. However, achieving the resolution, speed, and dynamic range needed for perceptual fidelity remains challenging. We present a tactile display that directly converts projected light into visible tactile patterns via a photomechanical surface populated with millimeter-scale optotactile pixels. The pixels transduce incident light into mechanical displacements through photostimulated thermal gas expansion, yielding millimeter scale displacements with response times of 2 to 100 milliseconds. Employing projected light for power transmission and addressing renders these displays highly scalable. We demonstrate optically driven displays with up to 1,511 addressable pixels – several times more pixels than any prior tactile display attaining comparable performance. Perceptual studies confirm that these displays can reproduce diverse spatiotemporal tactile patterns with high fidelity. This research establishes a foundation for practical, versatile high-resolution tactile displays driven by light. Copyright © 2024, The Authors. All rights reserved.

关键词： Light transmission

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Exploring Electromagnetic Time-Reversal as a Method to Monitor Cable Temperature in Medium-Voltage Networks 10

Exploring Electromagnetic Time-Reversal as a Method to Monit...

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10th International Conference on Condition Monitoring and Diagnosis, CMD 2024

作者： Ragusa, Antonella Wouters, Peter A. A. F. Sasse, Hugh Duffy, Alistair Rachidi, Farhad Rubinstein, Marcos De Montfort University Faculty of Computing Engineering and Media Leicester United Kingdom Eindhoven University of Technology Department of Electrical Engineering Eindhoven Netherlands School of Engineering École Polytechnique Fédérale de Lausanne Lausanne Switzerland Institute for Information and Communication Technologies University of Applied Sciences and Arts Western Switzerland Yverdon-les-Bains Switzerland

ISBN: (纸本)9788986510225

The paper addresses the research question of whether the electromagnetic time reversal (EMTR) technique can be used to estimate the propagation speed of a signal on power cables. This value changes in the long term due to ageing of the cable insulation and in the short term due to the cable temperature variation. A first numerical investigation of the EMTR effectiveness in estimating the propagation speed in a simple cable system is described showing that EMTR is a promising technique to be used also for the monitoring of power cable temperature. Future research will be directed to implementation of the methodology in more complex networks. © 2024 The Korean Institute of electrical Engineers (KIEE).

关键词： Power cables

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Crops Leaf Diseases Recognition:A Framework of Optimum Deep Learning Features

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Computers, Materials & Continua 2023年第1期74卷 1139-1159页

作者： Shafaq Abbas Muhammad Attique Khan Majed Alhaisoni Usman Tariq Ammar Armghan Fayadh Alenezi Arnab Majumdar Orawit Thinnukool Department of Computer Science HITEC UniversityTaxilaPakistan Computer Sciences Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh 11671Saudi Arabia College of Computer Engineering and Science Prince Sattam Bin Abdulaziz UniversityAl-Kharaj11942Saudi Arabia Department of Electrical Engineering College of EngineeringJouf UniversitySakakahSaudi Arabia Faculty of Engineering Imperial College LondonLondonSW72AZUK College of Arts Mediaand TechnologyChiang Mai UniversityChiang Mai50200Thailand

Manual diagnosis of crops diseases is not an easy process;thus,a computerized method is widely *** couple of years,advancements in the domain ofmachine learning,such as deep learning,have shown substantial ***,they still faced some challenges such as similarity in disease symptoms and irrelevant features *** this article,we proposed a new deep learning architecture with optimization algorithm for cucumber and potato leaf diseases *** proposed architecture consists of five *** the first step,data augmentation is performed to increase the numbers of training *** the second step,pre-trained DarkNet19 deep model is opted and fine-tuned that later utilized for the training of fine-tuned model through transfer *** features are extracted from the global pooling layer in the next step that is refined using Improved Cuckoo search *** best selected features are finally classified using machine learning classifiers such as SVM,and named a few more for final classification *** proposed architecture is tested using publicly available datasets–Cucumber National Dataset and Plant *** proposed architecture achieved an accuracy of 100.0%,92.9%,and 99.2%,*** with recent techniques is also performed,revealing that the proposed method achieved improved accuracy while consuming less computational time.

关键词： Crops diseases preprocessing convolutional neural network features optimization machine learning

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Design of Digital Film and Television Projection System Based On Blockchain technology

Design of Digital Film and Television Projection System Base...

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2022 IEEE International Conference on Knowledge engineering and Communication Systems, ICKES 2022

作者： Liao, Xiaowen Mao, Pandi Xu, Daolian School of Arts and Media Chongqing Metropolitan College of Science and Technology Chongqing402167 China School of Electrical Engineering and Intelligent Manufacturing Chongqing Metropolitan College of Science and Technology Chongqing402167 China College of Optoelectronic Engineering Chongqing University Chongqing40030 China

ISBN: (纸本)9781665456371

Digital Rights Management (DRM) is widely used to protect digital content and has made a major contribution to protecting digital content. However, traditional DRM technology has shortcomings, such as centralized and opaque copyright and transaction information. In order to solve the security problem of centralized management of digital movies, a digital movie distribution system architecture based on blockchain technology is proposed. Provide authenticity and traceability of data and business logic in film trading, license certification, projection control and other fields. It is developed through the decentralized consensus mechanism and decentralized IPFS storage mechanism using smart contract scripts in the blockchain. Create efficient and accurate implementation and reduce manual intervention and authorization to ensure traffic control throughout the working day. Our mechanism allows rights holders to set prices for different content usage rules according to their own wishes. Customers have the flexibility to choose the usage rules they want to purchase. We have also developed a licensing framework based on blockchain, which is close to the current DRM standard and easy to promote. © 2022 IEEE.

关键词： Copyrights

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A Dynamic Model for Pauses in the Synthesized Speech of Mathematical Expressions in MathML 14

A Dynamic Model for Pauses in the Synthesized Speech of Math...

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14th International Conference on Education technology and Computers, ICETC 2022

作者： Souza, Adriana Freitas, Diamantino Bahia Federal Institute of Education Science and Technology Porto Seguro Bahia Brazil Doctoral Program in Digital Media Faculty of Engineering Faculty of Engineering of University of Porto Porto Portugal Department of Electrical and Computer Engineering Faculty of Engineering of University of Porto Porto Portugal

ISBN: (纸本)9781450397766

Voice synthesizers still present several challenges in the speech of mathematical content, as spoken mathematics has quite peculiar rules. In the synthesized speech, pauses help blind and visually impaired students identify the limits of mathematical operators and subexpressions. However, most studies on pauses define them uniformly or use simple punctuation marks to force the synthesizer to introduce pauses in certain parts of the expression. Speech is a dynamic process and pauses in expressions also need to be dynamic to make the synthetic speech of expressions more natural, as this can help in memorizing this type of content. This work proposed a dynamic model of pauses for mathematical expressions. Collected math expressions spoken by teachers were used to create the model. These expressions were useful for identifying patterns and creating a linear regression model. Blind and visually impaired students evaluated the model. Some improvements were observed when we compared the synthesized mathematical expressions with the model and Audiomath, the parameter tool used in this study. © 2022 ACM.

关键词： Dynamic models

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Towards the Improvement of the Cognitive Process of the Synthesized Speech of Mathematical Expression in MathML: An Eye-Tracking 2

Towards the Improvement of the Cognitive Process of the Synt...

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2nd International Conference on Interactive media, Smart Systems and Emerging Technologies, IMET 2022

作者： Souza, Adriana Freitas, Diamantino Bahia Federal Institute of Education Science and Technology Bahia Brazil Doctoral Program in Digital Media Faculty of Engineering of the University of Porto Porto Portugal Faculty of Engineering of the University of Porto Speech Processing Laboratory Electrical and Computer Engineering Department Porto Portugal

ISBN: (数字)9781665470162

ISBN: (纸本)9781665470162

Being one essential part of the solutions we are developing to provide accessibility for blind persons, synthesized speech of mathematical content, although having evolved in naturalness in recent years, still keeps a characteristic of generating very long outputs, which makes it difficult for a person who uses a screen reader to memorize. Eye-gaze tracking has been useful for studying cognitive processes and student's effort in performing tasks therefore it seems attractive as a means to understand how people analyze, process, and break down extensive math expressions into smaller ones. This understanding can help to build a similar model of auditory rendering of MathML capable of avoiding cognitive overload. Therefore, we carried out an experiment to do a gaze-based analysis of reading and memorizing mathematical expressions. Our sample consisted of fourteen participants, and seven mathematical expressions were used in the experiment. The results showed that the computed complexity of the expressions and the average duration of eye-gaze fixations have a strong and significant relationship. Therefore, we conclude that the complexity variable must always be considered in the speech synthesis process of mathematical expressions. However, when considering why participants requested the repetition of an expression with not larger complexity during the memorization process, a tentative interpretation based on the number of MathML tree nodes and the computed complexity of the expressions was not enough to explain it, indicating that other factors need to be investigated. Although some answers to the research questions were not yet conclusive, we consider this research relevant because it points to directions for the work in order to minimize the cognitive processing and mental load of the synthesized speech rendering of mathematical expressions. © 2022 IEEE.

关键词： Eye tracking

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