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Development and study of the impacts of automated walking aids on the elderly 20

Development and study of the impacts of automated walking ai...

20th International Conference on Electrical Engineering/Electronics, computer, Telecommunications and Information technology, ECTI-CON 2023

作者： Tangjitjetsada, Maleeya Thianthong, Tawan Rakluea, Chawalit Loedhammacakra, Wisit Rakluea, Paitoon Tangthong, Nipont Mahatthanajatuphat, Chatree Chudpooti, Nonchanutt Rajamangala University of Technology Suvarnabhumi Faculty of Engineering and Architecture Department of Electronics and Telecommunication Engineering Nonthaburi Thailand Siam Airport Ground Services Co. Ltd Bangkok Thailand Rajamangala University of Technology Thanyaburi Faculty of Engineering Department of Electronics and Telecommunication Engineering Pathum Thani Thailand King Mongkut's University of Technology North Bangkok Faculty of Engineering Department of Electrical and Computer Engineering Bangkok Thailand King Mongkut's University of Technology North Bangkok Faculty of Applied Science Department of Industrial Physics and Medical Instrumentation Bangkok Thailand

ISBN: (纸本)9798350310467

Since Thailand has now completely stepped into an aged society there are more than 20% of the population aged 60 years and over. There was also an increase in those who had problems with their balance. One of the main difficulties for these people is walking on their own. This paper presents an automatic walking aid for people with balance or walking problems. A specially designed automatic walking aid can be adjusted to six levels of height. It has an anti-collision warning system at a distance of up to 40 centimeters and displays GPS coordinates via SMS when falling. The experimental results of the prototype automatic walking aid showed that the walking aid could work as designed and could help people with balance problems walk more comfortably. © 2023 IEEE.

关键词： Walking aids

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A Non-contact Microwave Sensor System for Characterizing a Binary-liquid Mixed Concentration

A Non-contact Microwave Sensor System for Characterizing a B...

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2023 International Electrical Engineering Congress, iEECON 2023

作者： Seewattanapon, Somporn Namsang, Apirada Lerdwanittip, Reungyot Akkaraekthalin, Prayoot Rakluea, Chawalit Duangrit, Nattapong Rajamangala University of Technology Suvarnabhumi Faculty of Engineering and Architecture Nonthaburi Thailand Civil Aviation Training Center Aeronautical Engineering Division Bangkok Thailand King Mongkut's University of Technology North Bangkok Faculty of Engineering Department of Electrical and Computer Engineering Bangkok Thailand Rajamangala University of Technology Thanyaburi Department of Electronics and Telecommunication Engineering Pathumthani Thailand National Astronomical Research Instituite of Thailand Centre of Observatory Operation and Engineering Chiangmai Thailand

ISBN: (纸本)9798350332360

This research presents a design and analysis of an open-loop microstrip resonator which is integrated with a microwave sensor system. It is used for measuring a binary-liquid mixed concentration of sodium chloride (NaCl) and DI-water to detect salinity level. The open-loop resonator is designed to provide a band-stop bandwidth of 1 GHz, which has operated from 2 GHz to 3 GHz. The proposed microwave sensor system consists of a microwave synthesizer, a voltage detector, and an open-loop resonator that is designed to operate at 3 GHz to characterize the salinity level of the sample liquid mixture. A liquid mixture samples of NaCl and Distill-water with 5 different concentration levels of 0%, 2%, 5%, 10%, and 20% were used to assess the salinity level for the proposed microwave sensor system. © 2023 IEEE.

关键词： Sodium chloride

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Brain Cortical Surface Can Predict Fiber Trajectories

Brain Cortical Surface Can Predict Fiber Trajectories

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IEEE International Symposium on Biomedical Imaging

作者： Tianle Han Yifan Lv Mengshen He Yiheng Liu Tianming Liu Bao Ge School of Physics & Information Technology Shaanxi Normal University Xi'an China Department of Computer Science and Bioimaging Research Center Cortical Architecture Imaging and Discovery Lab The University of Georgia GA USA

ISBN: (数字)9798350313338

ISBN: (纸本)9798350313345

Gray matter and white matter are fundamental constituents of the brain, and exploring the relationship between them is for gaining insights into the intricate architecture of the brain. This study utilizes information extracted from the gray matter surface of the brain to predict the trajectories of white matter fibers. Specifically, it predicts the coordinates of fiber trajectories by utilizing both fiber endpoints and reference points on the cortical surface. Both qualitative analysis and extensive quantitative experiments confirm that information derived from the brain's cortical surface can be employed to predict fiber trajectories. Furthermore, this conclusion remains robust across diverse fiber tracking and surface reconstruction techniques. The study introduces a novel perspective, elucidating the fundamental principles of fiber connectivity and the intricate relationship between gray matter and white matter.

关键词： Surface reconstruction Brain Pathology Nerve fibers Magnetic resonance imaging Grey matter Streaming media

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ERS: a novel comprehensive endoscopy image dataset for machine learning, compliant with the MST 3.0 specification

arXiv

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arXiv 2022年

作者： Cychnerski, Jan Dziubich, Tomasz Brzeski, Adam Department of Computer Architecture Gdańsk University of Technology Narutowicza 11/12 Gdańsk Poland

The article presents a new multi-label comprehensive image dataset from flexible endoscopy, colonoscopy and capsule endoscopy, named ERS. The collection has been labeled according to the full medical specification of'Minimum Standard Terminology 3.0' (MST 3.0), describing all possible findings in the gastrointestinal tract (104 possible labels), extended with an additional 19 labels useful in common machine learning applications. The dataset contains around 6000 precisely and 115,000 approximately labeled frames from endoscopy videos, 3600 precise and 22,600 approximate segmentation masks, and 1.23 million unlabeled frames from flexible and capsule endoscopy videos. The labeled data cover almost entirely the MST 3.0 standard. The data came from 1520 videos of 1135 patients. Additionally, this paper proposes and describes four exemplary experiments in gastrointestinal image classification task performed using the created dataset. The obtained results indicate the high usefulness and flexibility of the dataset in training and testing machine learning algorithms in the field of endoscopic data analysis. © 2022, CC BY-SA.

关键词： Image recognition

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Decomposition of the unit test generation task for parallel computations 16

Decomposition of the unit test generation task for parallel ...

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16th IEEE International Conference on computer Science and Information Technologies, CSIT 2021

作者： Bazylevych, Roman Czarnul, Pawel Franko, Andrii Lviv Polytechnic National University Department of Software Lviv Ukraine Gdansk University of Technology Faculty of Electronics Telecommunications and Informatics Department of Computer Architecture Gdansk Poland

ISBN: (纸本)9781665442572

A decomposition of unit test generation task for symbolic execution has been considered. The process has been divided into the subtasks: code parsing, paths generation, path analysis, constraints analysis and test generation. The code parsing and path generation time have been investigated. The dependency between time and input size is close to be linear on code parsing and test path generation. It has been shown that path generation takes almost three times larger time than code parsing. The results will be used for load-balancing of unit test generators based on symbolic execution. © 2021 IEEE.

关键词： Regression analysis

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Joint Prediction of SOH and RUL for Lithium Batteries Considering Capacity Self Recovery and Model Drift

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IEEE Internet of Things Journal 2025年第12期12卷 22187-22196页

作者： Jia, Zhen Li, Zhifei Wang, Zhengdong Liu, Zhenbao Vong, Chi-Man Xi'an University of Architecture and Technology School of Mechanical and Electrical Engineering Xi'an710055 China Northwestern Polytechnical University School of Civil Aviation Xi'an710072 China University of Macau Department of Computer and Informa tion Science Macau999078 China

Accurate monitoring of the state of health (SOH) and remaining useful life (RUL) of lithium batteries is a key technology to realize their stable and economic operation. The current data-driven methods have problems such as local prediction errors caused by capacity self-recovery effect, model drift phenomenon, and inaccurate trend prediction caused by complex degradation process. In this paper, we propose a joint SOH and RUL forecasting based on the fusion of Kolmogorov-Arnold Network (KAN), Deep Bidirectional Long Short-Term Memory Network (DBLSTM) and adaptive mechanism method (KAN-HDBLSTM-AM). The method innovatively introduces an adaptive mechanism that considers the capacity degradation trend for different prediction steps, suppresses the accumulation of errors in the model prediction process, and further improves the prediction accuracy by combining the nonlinear approximation capability of KAN and the mastery of data temporal characteristics of DBLSTM. Experimental validation shows that the proposed method can effectively overcome the prediction errors caused by capacity self-recovery and model drift, and can retain sufficient accuracy under long prediction steps, with the prediction trend being more in line with the actual change trend and the prediction error being smaller compared with other methods. © 2014 IEEE.

关键词： Prediction models

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Improving Genetic Algorithms Performance via Deterministic Population Shrinkage

arXiv

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arXiv 2024年

作者： Laredo, Juan Luis Jiménez Fernandes, Carlos Merelo, Juan Julián Gagné, Christian Department of Architecture and Computer Technology University of Granada Spain LASEEB-ISR/IST University of Lisbon Portugal Laboratoire de vision et systèmes numériques Laval University Canada

Despite the intuition that the same population size is not needed throughout the run of an Evolutionary Algorithm (EA), most EAs use a fixed population size. This paper presents an empirical study on the possible benefits of a Simple Variable Population Sizing (SVPS) scheme on the performance of Genetic Algorithms (GAs). It consists in decreasing the population for a GA run following a predetermined schedule, configured by a speed and a severity parameter. The method uses as initial population size an estimation of the minimum size needed to supply enough building blocks, using a fixed-size selectorecombinative GA converging within some confidence interval toward good solutions for a particular problem. Following this methodology, a scalability analysis is conducted on deceptive, quasi-deceptive, and non-deceptive trap functions in order to assess whether SVPS-GA improves performances compared to a fixed-size GA under different problem instances and difficulty levels. Results show several combinations of speed-severity where SVPS-GA preserves the solution quality while improving performances, by reducing the number of evaluations needed for success. © 2024, CC BY.

关键词： Genetic algorithms

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Radio spectrum awareness using deep learning: Identification of fading channels, signal distortions, medium access control protocols, and cellular systems

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Intelligent and Converged Networks 2021年第1期2卷 16-29页

作者： Yu Zhou Hatim Alhazmi Mohsen H.Alhazmi Alhussain Almarhabi Mofadal Alymani Mingju He Shengliang Peng Abdullah Samarkandi Zikang Sheng Huaxia Wang Yu-Dong Yao Department of Electrical and Computer Engineering Stevens Institute of TechnologyHobokenNJ 07030USA the College of Information Science and Engineering Huaqiao UniversityXiamen 361021China the College of Engineering Architecture and TechnologyOklahoma State UniversityStillwaterOK 74078-1010USA

Radio spectrum awareness,including understanding radio signal activities,is crucial for improving spectrum utilization,detecting security vulnerabilities,and supporting adaptive *** tasks include spectrum sensing,identifying systems and terminals,and understanding various protocol *** this paper,we investigate various identification and classification tasks related to fading channel parameters,signal distortions,Medium Access Control(MAC)protocols,radio signal types,and cellular ***,we utilize deep learning methods in those identification and classification *** evaluations demonstrate the effectiveness of deep learning in those radio spectrum awareness tasks.

关键词： cellular system deep learning signal classification spectrum awareness Convolutional Neural Network(CNN)

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Potential implementation of EVs - Features, Challenges and User perspective

Potential implementation of EVs - Features, Challenges and U...

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2021 IEEE Green Energy and Smart Systems Conference, IGESSC 2021

作者： Alotaibi, Saleh Omer, Siddig Aljarallah, Sulaiman Su, Yuehong University Of Nottingham Faculty Of Engineering Department Of Architecture And Built Environment Nottingham United Kingdom Zulfi College Of Technology Department Of Computer Science Riyadh Saudi Arabia

ISBN: (纸本)9781665434560

Sustainable transportation has become an important consideration for countries seeking to reduce carbon emissions. Electric vehicles (EVs) are seen as a cornerstone of the transformation toward sustainability within the transportation sector;however, research on large-scale EVs' implementation to aid carbon emission reduction is sparse. Doubts have been raised concerning the effectiveness of EVs in satisfying sustainability in all of its dimensions: economic, social and environmental. Since achieving balanced sustainability requires an understanding of end-users' requirements, a mixed-methods empirical study surveyed end-users' perceptions of the desirable characteristics of EVs, using Saudi Arabia as a case study. Data gathered from 1012 respondents were analyzed to examine and rank their preferences, allowing the identification of a set of key features likely to influence Saudi citizens' utilization of EVs. Quantitative findings indicate that the features perceived as most significant were availability of charging stations and EV travelling distance. Other features which are also found important include aesthetics, maintenance costs, and charging cost, whereas end-users had low concern for branding and resale value. Thematic analysis of qualitative data shows that the most significant themes were security, localization of the EVs industry, charging energy sources, and self-driving. These results may serve as a framework to replicate the study in other countries, taking relevant inherent factors into account. © 2021 IEEE.

关键词： Sustainable development

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THE EFFECT OF LIMITED MOBILITY ON THE EXPERIENCED SEGREGATION OF FOREIGN-BORN MINORITIES

arXiv

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arXiv 2024年

作者： Liao, Yuan Gil, Jorge Yeh, Sonia Pereira, Rafael H.M. Alessandretti, Laura Department of Space Earth and Environment Chalmers University of Technology Gothenburg Sweden Department of Architecture and Civil Engineering Chalmers University of Technology Gothenburg Sweden - Brazil Data Science Division Brazil Department of Applied Mathematics and Computer Science Technical University of Denmark Lyngby Denmark

Segregation is a key challenge in promoting more diverse and inclusive cities. Research based on large-scale mobility data indicates that segregation between majority and minority groups persists in daily activities beyond residential areas, like visiting shops and restaurants. Aspects including lifestyle differences, homophily, and mobility constraints have been proposed as drivers of this phenomenon, but their contributions remain poorly quantified. Here, we elucidate how different mechanisms influence segregation outside home, looking at the distinctive segregation experienced by native and foreign-born individuals. Our study is based on the movement of ∼320,000 individual smartphone devices collected in Sweden, where immigration creates profound divides. We find that while day-to-day activities lead to mixing for native-born individuals, foreign-born individuals remain segregated in their out-of-home activities. Using counterfactual simulations, we show that this heterogeneous effect of mobility on experienced segregation results mainly from two mechanisms: homophily and limited travel, i.e. foreign-born individuals (i) tend to visit destinations visited by similar individuals, and (ii) have limited mobility ranges. We show that homophily, as represented by destination preference, plays a minor role, while limited mobility, associated with reduced transport access, limits opportunities for foreign-born minorities to diversify their encounters. Our findings suggest that enhancing transport accessibility in foreign-born concentrated areas could reduce social segregation. © 2024, CC BY-SA.

关键词： Smartphones

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