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IEEE International Conference on Consumer Electronics (ICCE)

作者： Chang-Ming Yang Shu-Cing Wu Rally Kao Kuo-Cheng Liao Ze-We Wu Shih-Hung Chen Chi-Chun Chen Ming Young Biomedical Corp Miaoli Taiwan Program Prospective Technology of Electrical Engineering and Computer Science National Chin-Yi University of Technology Taichung Taiwan Bonanza Biotechnology Co.Ltd Dept. of Computer Science and Information Engineering National Chin-Yi University of Technology Taichung Taiwan Dept. of Electronic Engineering National Chin-Yi University of Technology Taichung Taiwan

With the rapid advancement of electronic textiles, the design and integration of connectors have emerged as pivotal challenges. This study emphasizes the development of a connection solution that amalgamates miniaturization, efficiency, and reliability, specifically tailored for Flexible Conductive Silicone Circuits. A diversified connection scheme is proposed, incorporating elements such as snaps, Pogo pins, and conductive hook-and-loop fasteners, thereby achieving an innovative and pragmatic design. Through meticulous manufacturing processes, including the utilization of hot-melt adhesive, PET films, conductive fabric, and other multilayer materials, a connection system with low impedance and commendable conductivity was successfully engineered. Impedance test outcomes have indicated that the resistance at each connection point is less than 0.7 ohms, substantiating its superior electrical properties. In terms of assembly, this research demonstrates the precise interconnection of the controller and conductive fabric circuit, ensured by metal pin technology, leading to connection stability. This solution not only furnishes appropriate connection technology for specific application scenarios but also opens new avenues and directions for connection design within the domain of electronic textiles.

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An Improved Particle Swarm Approach for Energy-Aware Location-Aided Routing in Mobile Ad-Hoc Network

An Improved Particle Swarm Approach for Energy-Aware Locatio...

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International Conference on Contemporary Computing and Informatics (IC3I)

作者： Sandeep Kumar Khemraj Sharma P. M. Ashok Kumar Arpit Jain Sukesh Kumar Bhagat Pranita Singh Tula’s institute Dehradun U.K India Department of Business Administration Doctoral Program in Management Sciences Nanhua University Dalin Chiayi R.O.C Department of Computer Science Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram AP India Department of Computer Science & Engineering Uttaranchal University Dehradun Uttarakhand India Department of Computer Science and Engineering Roorkee Institute of Technology Roorkee Uttarakhand India

ISBN: (数字)9798350350067

ISBN: (纸本)9798350350074

A network with no infrastructure, multiple hops, and dispersed nodes called a MANET. Nodes can communicate directly or through intermediaries without the need for permanent infrastructure. In dynamic networks like MANETs, routing procedures enhance the overall appearance of the network by ensuring Quality of Service (QoS). A routing protocol may use a composite routing measure to determine the best path for transferring data. Optimal location-based routing for MANETs based on energy-awareness is presented in this paper. Optimal routes are selected using this fast algorithm. Particle swarm optimization (PSO) is used instead of location-aided routing to select the normal data transmission route. Last but not least, the network is tested by simulating its packet delivery ratio, its energy level, its delay, and its overhead.

关键词： Scalability Transportation Quality of service Routing Particle measurements Routing protocols Real-time systems Delays Security Particle swarm optimization

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Application of Pose Estimation on Webcam for Fall Risk Assessment

Application of Pose Estimation on Webcam for Fall Risk Asses...

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International ECTI Northern Section Conference on Electrical, Electronics, computer and Telecommunications Engineering (ECTI-NCON)

作者： Surapong Uttama Patsakorn Chumpoo Worasak Rueangsirarak Center of Excellence in Artificial Intelligence and Emerging Technologies School of Information Technology Mae Fah Luang University Chiang Rai Thailand Computer Science Program School of Information Technology Mae Fah Luang University Chiang Rai Thailand Computer and Communication Engineering for Capacity Building School of Information Technology Mae Fah Luang University Chiang Rai Thailand

Fall risk assessment is an effective and simple measure to evaluate the balance of people especially the elderly who are likely to have balance disorder. Lose of body balance increases a fall risk which could lead to severe damage to aging persons. In this paper, we propose to apply pose estimation technique based on PoseNet method to detect body joints from webcam's video for two types of fall risk assessment: Five Times Sit to Stand Test (FTSTS) and 30-Second Chair Stand Test (30CST). The experiments were performed with 17 volunteers concurrently with the measures of a healthcare expert. The results revealed that our proposed technique corresponds well with the measure of the expert evaluating by a Pearson correlation coefficient which equals to 0.903 and 0.980 for FTSTS and 30CST respectively.

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Explainable machine learning models for estimating daily dissolved oxygen concentration of the Tualatin River

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Engineering Applications of Computational Fluid Mechanics 2024年第1期18卷

作者： Li, Shuguang Qasem, Sultan Noman Band, Shahab S. Ameri, Rasoul Pai, Hao-Ting Mehdizadeh, Saeid School of Computer Science and Technology Shandong Technology and Business University Yantai China Computer Science Department College of Computer and Information Sciences Imam Mohammad Ibn Saud Islamic University (IMSIU) Riyadh Saudi Arabia Computer Science Department Faculty of Applied Science Taiz University Taiz Yemen Future Technology Research Center National Yunlin University of Science and Technology Douliu Taiwan Department of Information Management International Graduate School of Artificial Intelligence National Yunlin University of Science and Technology Douliu Taiwan Department of Information Management National Yunlin University of Science and Technology Douliu Taiwan Bachelor Program of Big Data Applications in Business National Pingtung University Pingtung Taiwan Water Engineering Department Urmia University Urmia Iran

Monitoring the quality of river water is of fundamental importance and needs to be taken into consideration when it comes to the research into the hydrological field. In this context, the concentration of the dissolved oxygen (DO) is one of the most significant indicators of the quality of river water. The current study aimed to estimate the minimum, maximum, and mean DO concentrations (DO min, DO max, DO mean) at a gauging station located on Tualatin River, United States. To that end, four machine learning models, such as support vector regression (SVR), multi-layer perceptron (MLP), random forest (RF), and gradient boosting (GB) were established. Root mean square error (RMSE), mean absolute error (MAE), coefficient of correlation (R), and Nash-Sutcliffe efficiency (NSE) metrics were employed to better assess the accuracies of these models. The modeling results demonstrated that the SVR and MLP surpassed the RF and GB models. Despite this, the SVR was concluded to be the best-performing method when used to estimate the DO min, DO max, and DO mean. The best error statistics in the testing phase were related to the SVR model with full (four) inputs to estimate DO mean concentration (RMSE = 0.663 mg/l, MAE = 0.508 mg/l, R = 0.945, NSE = 0.875). Finally, the explainability of the superior models (i.e. SVR models) was conducted using SHapley Additive exPlanations (SHAP) for the first time to estimate DO concentration. In fact, evaluating the explainability of machine learning models can provide useful information about the impact of each of the input estimators used in the procedure of models development. It was concluded that the specific conductance (SC) and followed by water temperature (WT) could provide the most contributions for estimating the DO min, DO max, and DO mean concentrations. © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

关键词： dissolved oxygen concentration estimation Explainable machine learning SHapley additive explanations

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Privacy Preserving Electronic Health Record with Consortium Blockchain

Privacy Preserving Electronic Health Record with Consortium ...

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International Conference on information technology, information Systems and Electrical Engineering (ICITISEE)

作者： Adri Gautama Adian Fatchur Rochim Luhur Bayuaji Doctoral Program of Information System School of Postgraduate Studies Diponegoro University Semarang Indonesia Department of Computer Engineering Diponegoro University Semarang Indonesia Computer Science Budi Luhur University Jakarta Indonesia

Every patient has health record, it was written as statement of patient's conditions, treatments, and medications, and nowadays it is become digitalized, it can be copied and shared easily, but the nature of EHR is private, not for public, private between patients and healthcare provider. Privacy preserving can be done by implementing Blockchain network for storing EHR, only authorized users or nodes can access and write data to the network. New block in blockchain created as per consensus among nodes, every node can join a blockchain network if it is public, to meet a consensus required resources intensive cryptographic challenge, in private blockchain, only selected can join and involved in the network or specific transaction. In healthcare, data privacy is the main concerned, need a secure, scalable, and efficient blockchain hence implementing consortium blockchain is perfect match for EHR where multiple healthcare provider can operate in a single platform to conduct transaction or sharing EHR among members. This study analyzes 15 articles derived from IEEE Explore, science Direct and Scopus by implementing screening with keyword Consortium Blockchain and EHR and proposing new blockchain model accommodating solution for challenges on access, storage, sharing, privacy, and performance.

关键词： Electrical engineering Data privacy Privacy Analytical models Monte Carlo methods Medical services Blockchains

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Poultry raising light control system for laying hens and broilers

Poultry raising light control system for laying hens and bro...

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Cybernetics and Innovations (ICCI), International Conference on

作者： Thidarat Pinthong Thittaporn Ganokratanaa Department. of Business Information Management Phetchaburi Rajabhat University Phetchaburi Thailand Applied Computer Science Program King Mongkut's University of Technology Thonburi Bangkok Thailand

Chicken is an economic animal. one kind At present, it has been raised as a business and has expanded extensively. This is because both domestic and foreign populations have a greater demand for products and processed products from laying hens. which the raising of laying hens must be more attention to the productivity and quality of eggs in order to meet the needs of consumers with high or low temperatures Too low has an effect on the physiological system of laying hens. Reduce egg production or may result in inefficient production. And with the aforementioned problems, technology has been used to help in notifying. Warn whether the temperature in the house is suitable to increase the production of high-quality eggs.

关键词： Productivity Time-frequency analysis Technological innovation Animals Sleep Sociology Morphology

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Home smart alarm system for the visually impaired

Home smart alarm system for the visually impaired

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Cybernetics and Innovations (ICCI), International Conference on

作者： Worawut Yimyam Thittaporn Ganokratanaa Department. of Business Information Management Phetchaburi Rajabhat University Phetchaburi Thailand Applied Computer Science Program King Mongkut's University of Technology Thonburi Bangkok Thailand

This research aims to study the working principles of IOT devices or Internet of Things in order to promote the use of information technology systems, both hardware and software, with visually impaired people. rehabilitation of persons with disabilities, enhancing the capacity or ability of persons with disabilities to improve their condition or or existing capabilities through the advancement of technology so that people with disabilities have the opportunity to work or live in society to the full potential of the researcher The concept of technology acceptance model (technology Acceptance Model or TAM) to help further develop This research shows the importance of information technology systems, both hardware and software, to visually impaired people, which is the basis for product development of healthcare service businesses in the future.

关键词： Technological innovation technology acceptance model Medical services Software Hardware Product development Internet of Things

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Long Short Term Memory (LSTM) Improvement Accuracy Using FastText and Glove for Language Translation Batak - Indonesian

Long Short Term Memory (LSTM) Improvement Accuracy Using Fas...

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technology Innovation and Its Applications (ICTIIA), International Conference on

作者： Atikah Rahayu Mandasari Erna Budhiarti Nababan Herman Mawengkang Master of Informatics Program Universitas Sumatera Utara Medan Indonesia Faculty Of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Faculty of Mathematics and Natural Sciences Universitas Sumatera Utara Medan Indonesia

ISBN: (数字)9798350351613

ISBN: (纸本)9798350351620

This research discusses the improvement of Long Short-Term Memory (LSTM) model accuracy in translating Batak to Indonesian by utilizing FastText and GloVe embeddings. Traditional LSTM models often struggle with the complexity and richness of underrepresented languages like Batak. By integrating FastText and GloVe, which provide word vectors with deeper semantic meanings, the translation quality can be significantly enhanced. Experimental results show that this approach offers a substantial performance improvement compared to conventional LSTM models, producing more accurate and contextual translations. These findings have the potential to be applied in broader multilingual translation systems and support the preservation and digital accessibility of minority languages.

关键词： Long short term memory Training Vectors Accuracy Machine translation Vocabulary Predictive models Numerical models Decoding Context modeling

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Inappropriate Benefits and Identification of ChatGPT Misuse in programming Tests: A Controlled Experiment

arXiv

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arXiv 2023年

作者： Toba, Hapnes Karnalim, Oscar Johan, Meliana Christianti Tada, Terutoshi Djajalaksana, Yenni Merlin Vivaldy, Tristan Master of Computer Science Study Program Faculty of Information Technology Maranatha Christian University Bandung Indonesia Bachelor of Informatics Study Program Faculty of Information Technology Maranatha Christian University Bandung Indonesia Media Culture Department Faculty of Information Sciences and Arts Toyo University Kawagoe Japan EC-Council TampaFL United States

While ChatGPT may help students to learn to program, it can be misused to do plagiarism, a breach of academic integrity. Students can ask ChatGPT to complete a programming task, generating a solution from other people’s work without proper acknowledgment of the source(s). To help address this new kind of plagiarism, we performed a controlled experiment measuring the inappropriate benefits of using ChatGPT in terms of completion time and programming performance. We also reported how to manually identify programs aided with ChatGPT (via student behavior while using ChatGPT) and student perspective of ChatGPT (via a survey). Seventeen students participated in the experiment. They were asked to complete two programming tests. They were divided into two groups per the test: one group should complete the test without help while the other group should complete it with ChatGPT. Our study shows that students with ChatGPT complete programming tests two times faster than those without ChatGPT, though their programming performance is comparable. The generated code is highly efficient and uses complex data structures like lists and dictionaries. Based on the survey results, ChatGPT is recommended to be used as an assistant to complete programming tasks and other general assignments. ChatGPT will be beneficial as a reference as other search engines do. Logical and critical thinking are needed to validate the result presented by ChatGPT. © 2023, CC BY.

关键词： Students

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Amniotic fluid segmentation based on pixel classification using local window information and distance angle pixel

Amniotic fluid segmentation based on pixel classification us...

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作者： Ayu, Putu Desiana Wulaning Hartati, Sri Musdholifah, Aina Nurdiati, Detty S. Doctoral Program Department of Computer Science and Electronics Faculty of Mathematics and Natural Science Universitas Gadjah Mada Yogyakarta Indonesia Department of Computer Science and Electronics Faculty of Mathematics and Natural Sciences Universitas Gadjah Mada Yogyakarta Indonesia Department of Obstetrics and Gynecology Faculty of Medicine Universitas Gadjah Mada Yogyakarta Indonesia Department of Information Technology Faculty Computer and Informatics Institut Teknologi dan Bisnis STIKOM Bali Denpasar Indonesia

The amniotic fluid surrounds and protects the fetus from colliding with one another during the uterus development process. It also protects the umbilical cord from the uterine wall pressure, helps fetus movement, and develops muscles and bones. Selection of the most profound areas of improper and withdrawal points are not straight caliper is very likely that affect the outcome screening. Furthermore, there are similarities in texture and gray level between objects, especially in the boundary area between amniotic fluid and other objects, such as the placenta and uterus, which causes the border area to be less clear. Therefore, this research proposes a novel pixel classification model to separate amniotic fluid from other objects with a limit on the specified window size to solve this issue. In contrast to the most existing semantic segmentation methods or pixel-wise classification, we use the sampling window technique to construct train sets of data to produce pixel-level information more specifically in certain areas. Furthermore, each window extracts pixel information on gray level features and local variance (GLLV), using a novel Distance Angle Pixel (DAP). To evaluate the proposed model performance, we perform an extensive comparison with state-of-art methods by testing it on amniotic fluid ultrasound images. The results showed that the proposed model with a 3 × 3 window and random forest classifier could achieve the best value using an average Dice similarity coefficient (DSC) of 0.876, Jaccard/IoU of 0.768, and Pixel accuracy of 85.7%. The proposed model has 0.324 DSC improved from U-Net, 0.046 from gray-level pixel classification, 0.092 from thresholding, 0,252 from active contour, and 0.19 from rectangle window sampling. © 2021

关键词： Pixels

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