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International Conference on Information and communication Technology Convergence (ICTC)

作者： Maria Mahardini Sakanti Viacheslav Siniaev Aurelia Amaris Win-Jet Luo Suhartono C. Bambang dwi Kuncoro Graduate Institute of Precision Manufacturing National Chin-Yi University of Technology Taichung Taichung Taiwan Institute of Applied Computer Science ITMO University St. Petersburg Russian Federation Department of Informatics Engineering Faculty of Computer Science Universitas Brawijaya Malang Indonesia Ph.D. Program Prospective Technology of Electrical Engineering and Computer Science National Chin-Yi University of Technology Taichung Taichung Taiwan Department of Refrigeration Air Conditioning and Energy Engineering National Chin-Yi University of Technology Taichung Taiwan

ISBN: (数字)9798350364637

ISBN: (纸本)9798350364644

Stress, as a reaction to threatening situations, can raise heart rate and result in serious conditions that might cause significant damage or even be life-threatening. Traditional methods for evaluating stress, which rely on subjective self-reporting and clinical assessments, often suffer from biases and inconsistencies. Artificial intelligence models have been explored to predict stress levels more accurately. This paper investigates the application of Extreme Gradient Boosting in classifying psychological stress using the WESAd dataset, which includes parameters such as acceleration, electrocardiogram, electromyography, electrodermal activity, temperature, and respiration. The dataset was balanced and sampled to create a manageable subset for experimental. Extreme Gradient Boosting was chosen for its efficiency and scalability in handling complex datasets. The model was trained and validated, achieving a 95% accuracy in predicting stress levels. This study highlights the potential of integrating Extreme Gradient Boosting models into wearable devices for real-time stress monitoring. Future work involves optimizing the model to utilize fewer sensors without decreasing accuracy, ensuring it can be integrated into portable/wearable systems using tiny microcontrollers.

关键词： Accuracy Microcontrollers Psychology Human factors Predictive models Boosting Prediction algorithms Real-time systems Sensors Wearable devices

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Color Refractive Error Exam for Speech disorder

Color Refractive Error Exam for Speech Disorder

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IEEE International Symposium on Intelligent Signal Processing and communication Systems (ISPACS)

作者： Feng-Ming Yeh Liang-Ying Huang Chun-Yu Chiang Rong-Seng Chang Chuen-Lin Tien Ya-Hui Hsieh der-Chin Chen Department of Optometry Yuanpei University of Medical Technology Hsinchu Taiwan Department of Optics and Photonics National Central University Taoyuan Taiwan Ph.D. Program of Electrical and Communications Engineering Feng Chia University Taichung Taiwan Department of Electrical Engineering Feng Chia University Taichung Taiwan Department of Healthcare Information and Management Ming Chuan University Taoyuan Taiwan

In this study, a micro-led display, an eye chart player software, and image capture and processing module were used to construct a color refractive error exam for subject with speech disorder. This method can be used to test subjects with refractive errors, eye's color vision and other pathological problems. The micro-led display uses an eye chart player program to display the capital letters E and the other fonts, and the gaps of the E letters can be tumbled in any direction. When subjects with speech disorder were examined for vision, the E chart was displayed sequentially from big letters to small letters, and the image capture and processing module was synchronized with the eye chart player program. The subjects only need to point out the direction of the gap with gestures, and the image capture and processing module can simultaneously capture the gestures of the subjects to judge visual test status. In this study, twenty subjects were tested and all obtained the correct VA value and wore excellent eye glasses. The characteristic of this innovative method is that the subjects with a speech disorder can use simple hand gestures to complete the visual exam through the image capture and processing module during the inspection.

关键词： Visualization Pathology Image color analysis Glass Image capture Signal processing Inspection

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Automated Eight-Arm Maze Trajectory Tracking System for Feature Extraction of TBI Animals

Automated Eight-Arm Maze Trajectory Tracking System for Feat...

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ACIS International Conference on Software engineering, Artificial Intelligence, Networking, and Parallel/distributed Computing (SNPd)

作者： Shu-Cing Wu Chi-Yuan Lin Liang-Jyun Hong Chi-Chun Chen Ph.D. Program Prospective Technology of Electrical Engineering and Computer Science National Chin-Yi University of Technology Taichung Taiwan National Chin-Yi University of Technology Taichung Taiwan

ISBN: (纸本)9781665447324

Traumatic Brain Injury (TBI) is most commonly accident injury in modern society. The deterioration of cognition and memory is a common phenomenon caused by TBI. Most of the basic experiments used rats for pathological research. Moreover, an eight-arm maze was often used to test the spatial learning behavior of brain diseases, such as Alzheimer’s disease and TBI. However, most of maze experimental data were collected in manual records. This process would take a lot of manpower and time. Therefore, the research built an automatic tracking trajectory system of the eight-arm maze to collect experiment data. Furthermore, the path trajectory of the rat can be recorded in time. Finally, these path trajectory data were used to analysis behavior feature of TBI animals. The results showed that TBI rats have a 40%~80% chance of having a trajectory to the right.

关键词： Pathology Trajectory tracking Manuals Rats Feature extraction Cognition Trajectory

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The effect of Zentangle on cognitive focus, emotional well-being, and stress levels: A neural perspective

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Brain and Behavior 2024年第8期14卷 e3628页

作者： Usman, Muhammad Jung, Tzzy-Ping Hsin, ding-Yun Lin, Chun-Ling International Ph.D. Program in Innovative Technology of Biomedical Engineering and Medical Devices Ming Chi University of Technology New Taipei City Taiwan Institute for Neural Computation and Institute of Engineering in Medicine University of California San Diego San Diego CA United States Taipei Municipal Yangming High School Taipei City Taiwan Department of Electrical Engineering Ming Chi University of Technology New Taipei City Taiwan Department of Electronic Engineering National Taipei University of Technology Taipei Taiwan

Purpose: This study aimed to assess how a Zentangle intervention influences cognitive focus, emotional well-being, stress levels, and neural activity patterns across brain regions and frequency bands. Method: A cohort of 30 healthy adults, all without prior Zentangle experience, participated in this study. Electroencephalography (EEG) was used to measure their brain activity, and self-reported data were collected through questionnaires to assess subjects’ concentration levels, emotional calm, and stress and anxiety. Findings: Participants reported enhanced cognitive focus and emotional well-being, evidenced by increased self-reported concentration and emotional calmness, and reduced stress and anxiety levels during the intervention. EEG analyses revealed notable changes in neural activity patterns, including decreased delta power and increased theta, alpha, beta, and gamma bands. Functional connectivity analysis also highlighted alterations in the brain's functional connectivity, suggesting potential effects on neural communication and information processing. Conclusion: This study provides compelling evidence of Zentangle's impact on EEG data, aligning it with equanimity and tranquility consistent with previous mindfulness research. These findings underscore Zentangle as an effective mindfulness practice, potentially enhancing cognitive focus and emotional well-being, and emerging as a valuable intervention for improving mental health and overall well-being. © 2024 The Author(s). Brain and Behavior published by Wiley Periodicals LLC.

关键词： art therapy electroencephalography mediation mindfulness well-being Zentangle

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Intrinsic synaptic plasticity of ferroelectric field effect transistors for online learning

arXiv

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arXiv 2021年

作者： Saha, Arnob Nafiul Islam, A.N.M. Zhao, Zijian deng, Shan Ni, Kai Sengupta, Abhronil School of Electrical Engineering & Computer Science Pennsylvania State University University ParkPA16802 United States Microsystems Engineering Ph.D. program Rochester Institute of Technology RochesterNY14623 United States

Nanoelectronic devices emulating neuro-synaptic functionalities through their intrinsic physics at low operating energies is imperative toward the realization of brain-like neuromorphic computers. In this work, we leverage the non-linear voltage dependent partial polarization switching of a ferroelectric field effect transistor to mimic plasticity characteristics of biological synapses. We provide experimental measurements of the synaptic characteristics for a 28nm high-k metal gate technology based device and develop an experimentally calibrated device model for large-scale system performance prediction. decoupled read-write paths, ultra-low programming energies and the possibility of arranging such devices in a cross-point architecture demonstrate the synaptic efficacy of the device. Our hardware-algorithm co-design analysis reveals that the intrinsic plasticity of the ferroelectric devices has potential to enable unsupervised local learning in edge devices with limited training data. Copyright © 2021, The Authors. All rights reserved.

关键词： E-learning

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Evaluating the Robustness of Complementary Channel Ferroelectric FETs Against Total Ionizing dose Towards Radiation-Tolerant Embedded Nonvolatile Memory

TechRxiv

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TechRxiv 2023年

作者： Jiang, Zhouhang Guo, Zixiang Luo, Xuyi Sayed, Munazza Faris, Zubair Mulaosmanovic, Halid duenkel, Stefan Soss, Steven Beyer, Sven Gong, Xiao Kurinec, Santosh Narayanan, Vijaykrishnan Amrouch, Hussam Zhang, Enxia Fleetwood, daniel M. Schrimpf, Ronald d. Ni, Kai The Microsystems Engineering Ph.D. Program The Mechanical Engineering Rochester Institute of Technology RochesterNY14623 United States The Department of Electrical and Computer Engineering Vanderbilt University NashvilleTN37235 United States University of Stuttgart Stuttgart70174 Germany Germany The Munich Institute of Robotics and Machine Intelligence Arcisstrasse 21 Munich80333 Germany The GlobalFoundries Fab1 LLC Dresden Germany The Department of Electrical Computer Engineering National University of Singapore 119077 Singapore The Department of Computer Science and Engineering Penn State University University ParkPA16802 United States The Department of Electrical and Microelectric Engineering Rochester Institute of Technology RochesterNY14623 United States

In this work, a thorough assessment of the robustness of complementary channel HfO2 ferroelectric FET (FeFET) against total ionizing dose (TId) radiation is conducted, with the goal of determining its suitability for use as high-performance and energy-efficient embedded nonvolatile memory (eNVM) for space applications. We demonstrate that: i) ferroelectric HfO2 thin film is robust against X-ray and proton irradiation;ii) FeFET exhibits a polarization state dependent radiation sensitivity where the high-VTH (HVT) state sees noticeable negative VTH shift and low-VTH (LVT) is immune to irradiation, irrespective of the channel type;iii) the state dependence is ascribed to the depolarization field in the HVT, which points toward the channel and facilitates the transport and trapping of radiation-generated holes close to the channel. In the future, radiation hardening techniques need to be considered. © 2023, CC BY.

关键词： Radiation effects

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Unveiling Multivariate EEG Features: A Novel Approach to Enhancing AdHd diagnosis Through Visual and Auditory Attention Tests

Unveiling Multivariate EEG Features: A Novel Approach to Enh...

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International Conference on Fuzzy Theory and it's Applications (iFUZZY)

作者： Zuo-Cian Fan Ro-Wei Lin Ching-Shu Tsai Wen-Jiun Chou Chia-Jung Li Zih-Jun Huang Bin-Yu Shih Liang-Jen Wang Li-Wei Ko Department of Biological Science & Technology Center for Intelligent Drug Systems and Smart Bio-Devices (IDS2B) College of Biological Science and Technology National Yang Ming Chiao Tung University Hsinchu Taiwan International Ph.D. Program in Interdisciplinary Neuroscience National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Child and Adolescent Psychiatry Kaohsiung Chang Gung Memorial Hospit Department of Electronics and Electrical Engineering Institute of Electrical and Control Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan

We sought to revolutionize the classification of Attention-deficit/Hyperactivity disorder (AdHd) by pioneering an innovative approach that seamlessly integrated auditory and visual tests with electroencephalogram (EEG) coherence analysis, forming the foundation for our Support Vector Machine (SVM) models. Our primary objective was to achieve precise differentiation between individuals with AdHd and those without, aiming to reshape the landscape of AdHd diagnosis and early intervention. We constructed an SVM model based on CATA coherence, incorporating a carefully selected set of 180 features, and another grounded in CPT coherence with 70 features. Astonishingly, our exploration uncovered that a model incorporating CATA's coherence and Power Spectral density (PSd) as features achieved an astounding accuracy rate of 97.7%, using only half the number of features. This revelation hints at untapped potential for multivariate advancements in the realm of AdHd classification. The landscape of AdHd diagnosis and intervention is perpetually evolving, most notably with the FdA's approval of game therapy for AdHd. Leveraging the transformative power of our findings, we envision the development of user-friendly game therapies for in-home use, empowering both clinicians and parents alike. This marks a paradigm shift in the realm of AdHd intervention, offering objective, data-driven tools for the early management of AdHd. Gamified therapy not only enhances accessibility but also fosters engagement and compliance, all of which are pivotal in the long-term care of individuals with AdHd. In summary, our study represents a significant advancement in our comprehension and classification of AdHd. By fusing auditory and visual tests with EEG coherence analysis, fortified by state-of-the-art machine learning techniques, we have achieved an unprecedented level of accuracy in identifying individuals with AdHd. Our findings, aligned with the FdA-approved game therapy, offer a glimpse into a

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deep Unsupervised Learning for Biomedical Image Translation from Harmonic Generation Microscopy Image to H&E-stained Image

Deep Unsupervised Learning for Biomedical Image Translation ...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Wei-Ju Chen En-Yu Liao Tsung-Ming Tai Yi-Hua Liao Chi-Kuang Sun Cheng-Kuang Lee Simon See Hung-Wen Chen International Intercollegiate Ph.D. Program National Tsing Hua University Hsinchu Taiwan Department of Electrical Engineering and Graduate Institute of Photonics and Optoelectronics National Taiwan University Taipei Taiwan NVIDIA AI Technology Center NVIDIA Taipei Taiwan Department of Dermatology National Taiwan University Hospital and College of Medicine National Taiwan University Taipei Taiwan Institute of Photonics Technologies National Tsing Hua University Hsinchu Taiwan

This work proposes an unsupervised deep learning-based image translation from Harmonic generation microscopy (HGM) to widely used H&E-stained images. The proposed methodology is promising and hopefully will facili... 详细信息

ISBN: (纸本)9781957171258

关键词： Harmonic generation Image analysis Image stacking Second harmonic generation Third harmonic generation Three dimensional imaging

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photodamage Reduction on Harmonic Generation Microscopy at Low-Level Optical Power based on deep Learning

Photodamage Reduction on Harmonic Generation Microscopy at L...

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Laser Science, LS 2021 - Part of Frontiers in Optics, FiO 2021

作者： Shen, Yi-Jiun Liao, En-Yu Tai, Tsung-Ming Liao, Yi-Hua Sun, Chi-Kuang Lee, Cheng-Kuang See, Simon Chen, Hung-Wen International Intercollegiate Ph.D. Program National Tsing Hua University Hsinchu Taiwan Department of Electrical Engineering Graduate Institute of Photonics and Optoelectronics National Taiwan University Taipei Taiwan NVIDIA AI Technology Center NVIDIA Department of Dermatology National Taiwan University Hospital College of Medicine National Taiwan University Taipei Taiwan Institute of Photonics Technologies National Tsing Hua University Hsinchu Taiwan Hsinchu Taiwan

We demonstrated a power enhancement method in harmonic generation microscopy based on deep learning to reduce the optical input power and consequently reduce the risk of photodamage. © Optica Publishing Group 202... 详细信息

ISBN: (纸本)9781557528209

关键词： deep learning

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Implementation of Tire Status Estimation Using Hall Sensor and G-Sensor

Implementation of Tire Status Estimation Using Hall Sensor a...

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ACIS International Conference on Software engineering, Artificial Intelligence, Networking, and Parallel/distributed Computing (SNPd)

作者： Wei-Hsuan Chang Rong-Terng Juang Min-Hsiang Huang Min-Feng Sung Ph.D Program of Electrical and Communication Engineering Feng-Chia University Taichung Taiwan Feng-Chia University Taichung Taiwan Automotive Research and Testing Center Changhua Taiwan Kenda Tire Taiwan Changhua Taiwan

ISBN: (纸本)9781665447324

Vehicles are one kind of human’s transport tools that can carry us to anywhere. Safety is an important issue for vehicle applications. Tire is an important element of the vehicle, because the vehicle only has four points connect on the road through tires. Many accidents are caused the tire problems. There are more and more researches in intelligent tire base on safety issues. Tire pressure monitor system (TPMS) can be called an application of intelligent tires that are currently a very popular tire monitoring device, it provides pressure and temperature information for drivers. The information can let drivers understand their tire’s status through simple information. Not only pressure and temperature can affect safety, but also tire’s use mileage. The tire wear has some relation to safety. The mileage has been defined by tire spec. The different tires have different specs and the tire wear status cannot be defined clearly. The wear status is hard to get that is because the vehicle condition, use scenario and situation are complicated. drivers can’t understand how many miles did the tire use and what status the tire. This paper proposed a method to estimate and monitor tire mileage and wear base on simple sensors. G-sensor and hall sensors are common sensors in applications. The method will use these simple sensors to implement the method. drivers can accord information to evaluate the tire status and decide the timing to replace the tire. It can help drivers to increase safety during the drive and provide a solution to support intelligent tire function.

关键词： Temperature sensors Temperature measurement Tire pressure Tires Safety Timing Intelligent sensors

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