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Integrated Circuits and Communication Systems (ICICACS), IEEE International Conference on

作者： Kiran C H Raj Kumar Gupta Neeraj Kumar Rukmani Devi V. Bhoopathy A. Kathiravan Department of Mechanical Engineering Alva's Institute of Engineering and Technology Mijar (DK) India Department of Physics Sardar Vallabhbhai Patel College Ara India Department of Electrical Engineering Doon Institute of Engineering and Technology Rishikesh India Department of Computer Science Saveetha College of Liberal Arts and Sciences SIMATS Deemed to be University Chennai India Department of Computer Science and Engineering Sree Rama Engineering College Tirupathi India Department of Electrical and Electronics Engineering Rajiv Gandhi College of Engineering and Technology Puducherry India

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

As people rely more on cars for transportation, greenhouse gas emissions and ozone layer depletion rise. For shorter rides, solar-powered e-bikes are affordable and environmentally friendly. This proposed approached a ResLSTM hybrid model with LSTM. The methodology involves preprocessing, feature extraction, and model training. Remove duplicates and missing values before k-means grouping and training. Consistency requires scaling, normalizing, and standardizing features. With an average accuracy of 93.45%, the ResLSTM model surpassed current approaches. The recommended method effectively estimates solar energy and vehicle energy consumption to maximize energy use for solar-powered e-bikes. The results suggest that ResLSTM can provide efficient and eco-friendly transportation options. Resolving data anomalies and ensuring accurate projections helps solar-powered electric bikes become more popular as a sustainable transportation choice.

关键词： Training Photovoltaic systems Accuracy Reviews Transportation Standardization Solar energy Integrated circuit modeling Greenhouse gases Long short term memory

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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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Analyzing the Imitation Behaviors of Gorilla Chest-Beating Based on Human Pose Estimation

Analyzing the Imitation Behaviors of Gorilla Chest-Beating B...

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Cyber Science and technology Congress (CyberSciTech), IEEE

作者： Yu Qi Siyu Xiong Chongyang Zhang Bo Wu Graduate School of Bionics Computer and Media Sciences Tokyo University of Technology Tokyo Japan Department of Information Engineering Hebei Institute of Mechanical and Electrical Technology Xingtai China School of Computer Science Tokyo University of Technology Tokyo Japan

ISBN: (数字)9798331532093

ISBN: (纸本)9798331532109

In animal exercise classes course for acting majors, students enhance their physical flexibility and expressiveness by imitating the behaviors and actions of various animals. The gorilla's chest-beating action is a common exercise in this course. The accuracy of students' body postures when imitating animals often depends on the instructor's experience and personal preferences, leading to students with different levels and physical characteristics not receiving targeted guidance and practice. Human pose estimation technology is already quite mature, and we hope to apply it to animal exercise courses to analyze students' body movements when imitating animals, such as chest-beating. Therefore, this paper utilizes mediapipe technology to detect the elbow joint angles of students imitating the gorilla's chest-beating action, a two-way analysis of variance (ANOVA) was employed to examine the effects of experience and gender on joint angle variations. Additionally, the results of the U-test analyzing the differences between the gorilla and the participants confirmed that male students' elbow joint angles are closer to those of the gorilla than those of female students when mimicking the gorilla's chest-beating action. This has significant implications for improving the precision and personalization of performance training, and it also provides valuable insights for further research and practice in related fields.

关键词： Training Accuracy Animals Pose estimation Standardization Behavioral sciences Elbow Analysis of variance

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Modified Elephant Herd Optimization-Based Advanced Encryption Standard 11th

Modified Elephant Herd Optimization-Based Advanced Encryptio...

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11th International Conference on Frontiers of Intelligent Computing: Theory and Applications, FICTA 2023

作者： Surendiran, R. Chellam, S. Jothin, R. Ahilan, A. Vallisree, S. Jasmine Gnana Malar, A. Sathiamoorthy, J. School of Information Science Annai College of Arts and Science Kumbakonam612503 India Tamil Nadu Madurai625009 India Department of Electronics and Communication Engineering PSN Engineering College Tamil Nadu Tirunelveli India Department of Electronics and Communication Engineering PSN College of Engineering and Technology Tamil Nadu Tirunelveli627152 India Department of Electronics and Communication Engineering Geethanjali College of Engineering and Technology Hyderabad India Department of Electrical and Electronics Engineering PSN College of Engineering and Technology Tamil Nadu Tirunelveli627152 India Department of Computer Science and Engineering R.M.K. Engineering College Tamil Nadu Kavaraipettai601206 India

ISBN: (纸本)9789819967056

Cryptography is commonly employed to ensure secure data transfer via unsecure communication networks. With the rising need for picture transmission confidentiality and privacy, an efficient encryption approach becomes vital. The architectural flow of the newly created technique is implied in the proposal. Based on Cryptographic Method for Digital Picture Security, the design of an efficient Modified Elephant Herd Optimization-based Advanced Encryption Standard (MEHO-AES) is presented. The suggested MEHO-AES approach employs multilevel discrete Cosine transform (DCT) for image decomposition, with the input picture divided into RGB components for examining the fundamental colors of all image sections. Moreover, the AES encryption technology is used throughout the encryption procedure. Additionally, the MEHO method is used to determine the best encryption keys. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Discrete cosine transforms

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Integrated Product-Process Design: Conceptual Framework for Data Driven Manufacturing Resource Selection 2

Integrated Product-Process Design: Conceptual Framework for ...

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2nd International Conference on Digital Futures and Transformative Technologies, ICoDT2 2022

作者： Uz Zaman, Uzair Khaleeq Ghoto, Mujtaba Rafique Siadat, Ali Baqai, Aamer Ahmed Aqeel, Anas Bin Qamar, Usman College of Electrical & Mechanical Engineering National University of Science and Technology Department of Mechatronics Engineering Islamabad44000 Pakistan Arts et Métiers ParisTech - Campus de Metz Laboratoire Conception Fabrication Commande Metz57070 France College of Electrical & Mechanical Engineering National University of Science and Technology Department of Computer & Software Engineering Islamabad44000 Pakistan

ISBN: (纸本)9781665498197

With the extensive development of new technologies and the application of information in the manufacturing industry, immense volumes of distinct data are being generated and collected daily. However, this data is largely unusable as its not meticulously cleaned and processed. The effective utilization of such complex data is the cornerstone of data analytics, as successful analysis leads to useful, relevant, and actionable knowledge, which in the long run can prove to be revolutionary for any field and open new avenues. Although the application of data analytics in areas such as sales & marketing, healthcare, cybersecurity, and climate change is largely prevalent, the implementation of data analysis and its tools for efficient product & process design is an unexplored opportunity with large volumes of data generated by major stakeholders throughout the manufacturing and product-process design activity remaining underutilized. This paper, therefore, defines a novel conceptual framework that applies data analysis to integrated product-process design (IPPD) for weighted data-driven IPPD that amalgamates data generated from multiple streams. Primarily from the user perspective, supply chain network, current & upcoming technological processes, and competitor process and product designs, will be utilized. The proposed framework can be further used to create new products better aligned with customer requirements, enhance the overall quality of the product, improve production efficiency through new technological advancements, support the supply chain network, and give the applicant industry a competitive advantage against its competitors. © 2022 IEEE.

关键词： Big data

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A Design of an Effective Methodology to Detect Glaucoma Disease using Intelligent Learning Strategy 9

A Design of an Effective Methodology to Detect Glaucoma Dise...

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9th IEEE International Conference on Smart Structures and Systems, ICSSS 2023

作者： Shobana, D. Akilarasu, G. Sangeetha, J. Priya, V. Banu Karkuzhali, S. Malathi, P. Rajalakshmi Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Chennai India Lovely Professional University Department of Computer Science and Engineering Punjab India S. A. Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India R.M.K. College of Engineering and Technology Department of Mathematics Tamil Nadu Chennai India R.M.K. Engineering College Department of General Engineering Tamil Nadu Chennai India Saveetha College of Liberal Arts and Sciences Simats Department of Data Analytics Tamil Nadu Chennai India

ISBN: (纸本)9798350384208

Globally, glaucoma is now among the leading causes of blindness. It is a chronic, irreversible illness. Screening for glaucoma and detecting it early are crucial in the fight against this illness. Here, deep learning shows great promise. Two deep learning architectures, the Convolutional Neural Network (CNN) model and the Improved Learning Strategy to Predict Glaucoma (ILSPG) model, have been evaluated in this article. In order to diagnose glaucoma, the DCNN method is utilized. Ultimately, this area of study aims to help doctors diagnose glaucoma by developing methods to spot the disease in retinal fundus pictures. Because glaucoma can have both beneficial and bad effects on the model, the result of the model might be good or bad. Several measures are utilized in the process of evaluating models, including accuracy, precision, specificity, and reliability. In order to determine the accuracy of the proposed model, an additional comparison study is conducted. The results are contrasted with a deep learning-based classification system that uses convolutional neural networks. The results demonstrate, without a doubt, that the proposed system is effective. © 2023 IEEE.

关键词： Convolutional neural networks

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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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An efficient machine learning approach for extracting eSports players distinguishing features and classifying their skill levels using symbolic transfer entropy and consensus nested cross validation

arXiv

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arXiv 2024年

作者： Noroozi, Amin Hasan, Mohammad S. Ravan, Maryam Norouzi, Elham Law, Ying-Ying Department of Digital Technologies and Arts Staffordshire University England Staffordshire United Kingdom Department of Electrical and Computer Engineering New York Institute of Technology New YorkNY United States Department of Computer Engineering Azad University Astara Iran

Discovering features that set elite players apart is of great significance for eSports coaches as it enables them to arrange a more effective training program focused on improving those features. Moreover, finding such features results in a better evaluation of eSports players’ skills, which, besides coaches, is of interest for game developers to design games automatically adaptable to the players’ expertise. Sensor data combined with machine learning have already proved effective in classifying eSports players. However, the existing methods do not provide sufficient information about features that distinguish high-skilled players. In this paper, we propose an efficient method to find these features and then use them to classify players' skill levels. We first apply a time window to extract the players' sensor data, including heart rate, hand activities, etc., before and after game events in the League of Legends game. We use the extracted segments and symbolic transfer entropy to calculate connectivity features between sensors. The most relevant features are then selected using the newly developed consensus nested cross validation method. These features, representing the harmony between body parts, are finally used to find the optimum window size and classify players' skills. The classification results demonstrate a significant improvement by achieving 90.1% accuracy. Also, connectivity features between players’ gaze positions and keyboard, mouse, and hand activities were the most distinguishing features in classifying players' skills. The proposed method in this paper can be similarly applied to sportspeople’s data and potentially revolutionize the training programs in both eSports and sports industries. Copyright © 2024, The Authors. All rights reserved.

关键词： Classification (of information)

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Wearable and interactive multicolored photochromic fiber display

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Light(Science & Applications) 2024年第3期13卷 454-465页

作者： Pan Li Yuwei Wang Xiaoxian He Yuyang Cui Jingyu Ouyang Ju Ouyang Zicheng He Jiayu Hu Xiaojuan Liu Hang Wei Yu Wang Xiaoling Lu Qian Ji Xinyuan Cai Li Liu Chong Hou Ning Zhou Shaowu Pan Xiangru Wang Huamin Zhou Cheng-Wei Qiu Yan-Qing Lu Guangming Tao State Key Laboratory of Material Processing and Die&Mould Technology School of Materials Science and Engineering and Wuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan 430074China Key Laboratory of Vascular Aging(HUST) Ministry of EducationWuhan 430030China School of Optoelectronic Science and Engineering University of Electronic Science and Technology of ChinaChengdu 611731China Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore National Laboratory of Solid State Microstructures Key Laboratory of Intelligent Optical Sensing and ManipulationCollege of Engineering and Applied Sciencesand Collaborative Innovation Center of Advanced MicrostructuresNanjing UniversityNanjing 210023China School of Performing Arts Wuhan Conservatory of MusicWuhan 430060China School of Mechanical Science and Engineering Huazhong University of Science and TechnologyWuhan 430074China School of Architecture and Urban Planning Huazhong University of Science and TechnologyWuhan 430074China School of Fashion Beijing Institute of Fashion TechnologyBeijing 100029China School of Optical and Electronic Information Huazhong University of Science and TechnologyWuhan 430074China Tongji Medical College Huazhong University of Science and TechnologyWuhan 430074China State Key Laboratory for Modification of Chemical Fibers and Polymer Materials College of Materials Science and EngineeringDonghua UniversityShanghai 201620China

Endowing flexible and adaptable fiber devices with light-emitting capabilities has the potential to revolutionize the current design philosophy of intelligent,wearable interactive ***,significant challenges remain in developing fiber devices when it comes to achieving uniform and customizable light effects while utilizing lightweight ***,we introduce a mass-produced,wearable,and interactive photochromic fiber that provides uniform multicolored light *** designed independent waveguides inside the fiber to maintain total internal reflection of light as it traverses the *** impact of excessive light leakage on the overall illuminance can be reduced by utilizing the saturable absorption effect of fluorescent materials to ensure light emission uniformity along the transmission *** addition,we coupled various fluorescent composite materials inside the fiber to achieve artificially controllable spectral radiation of multiple color systems in a single *** prepared fibers on mass-produced kilometer-long using the thermal drawing *** fibers can be directly integrated into daily wearable devices or clothing in various patterns and combined with other signal input components to control and display patterns as *** work provides a new perspective and inspiration to the existing field of fiber display interaction,paving the way for future human–machine integration.

关键词： fiber interactive colored

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Deep Learning Approach to Predict Alzheimer's Disease through Magnetic Resonance Images

Deep Learning Approach to Predict Alzheimer's Disease throug...

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2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Ramadhan, Gilang Titah Pusparani, Yori Farady, Isack Furqon, Elvin Nur Lin, Chih-Yang Chao, Wen-Hung Rani Alex, John Sahaya Aparajeeta, Jeetashree Lung, Chi-Wen Asia University Department of Computer Science and Information Engineering Taichung Taiwan Budi Luhur University Department of Visual Communication Design Jakarta Indonesia Asia University Department of Digital Media Design Taichung Taiwan Mercu Buana University Electrical Engineering Jakarta Indonesia Department of Electrical Engineering Yuan Ze University Chung-Li Taiwan National Central University Department of Mechanical Engineering Taoyuan Taiwan Innovation and Research Vellore Institute of Technology Division of Healthcare Advancement Tamil Nadu India Vellore Institute of Technology School of Electronics Engineering Tamil Nadu India Asia University Department of Creative Product Design Taichung Taiwan

ISBN: (纸本)9798350324174

Alzheimer's disease is the most common type of dementia that causes many of the functions of the human brain to be severely weakened. To date, there has not been a cure for Alzheimer's disease. Therefore, early diagnosis is needed using MRI images with the help of a classification program. Deep learning using the Convolutional Neural Network (CNN) method is receiving increasing attention because of its excellent performance. Its architecture can be modified according to user needs based on the data to be processed and the approach for classifying, detecting, and segmenting visual objects. In this paper, we offer a classification of Alzheimer's disease using one of the architectures on CNN, namely Visual Geometry Group-19 (VGG-19), with a sagittal view of MRI images with an image size of 229 x 229 pixels. The classification accuracy of the described method is 94% for the validation set. © 2023 IEEE.

关键词： Magnetic resonance imaging

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