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International Conference on Computer and Automation engineering, ICCAE

作者： Mao-Jen Ko Yu-Chen Lin Chih-Hung Cheng Thanh-Tan Nguyen Department of Automatic Control Engineering Feng Chia University Taichung Taiwan Ph.D. Program of Electrical and Communications Engineering Feng Chia University Taichung Taiwan

ISBN: (数字)9798350370058

ISBN: (纸本)9798350370164

In recent years, the rapid development of autonomous system technology has increasingly positioned it as a crucial player in modern transportation. Appropriate speed planning emerges as one of the key elements for achieving safe and efficient autonomous system operations. Speed planning not only requires adherence to road speed limits and ensuring safe distances to avoid collisions but also necessitates consideration for ensuring passenger comfort. This paper proposes a method that restricts acceleration and jerk to achieve smooth speed control, enabling autonomous system to emulate the driving style of human drivers. Utilizing visual SLAM for feature extraction and matching on images, a sparse point cloud three-dimensional map of the environment is constructed. The recorded path is tracked using the Pure Pursuit algorithm. Finally, this paper will validate the proposed approach through an embedded system deployed in a real vehicle. The integration of visual SLAM and smooth speed control technology realizes a real-time and smooth autonomous system, providing a safer autonomous system experience.

关键词： Point cloud compression Visualization Simultaneous localization and mapping Autonomous systems Velocity control Feature extraction Real-time systems

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Experimental Study on Aerodynamic Effects of different Blade Types with PIV-Method for Coaxial Counter-Rotating Rotors 7

Experimental Study on Aerodynamic Effects of Different Blade...

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7th International Conference on Mechanical Manufacturing and Industrial engineering, MMIE 2024

作者： Sung, Chen-Yu Shieh, Tzong-Hann Ma, Yen-Huai Soong, Chyi-Yeou Yeh, Chun-Liang Yang, Fuh-Sen Ph.D. Program of Mechanical and Aeronautical Engineering Feng Chia University No.100 Wenhwa Rd. Seatwen Taichung40724 Taiwan Department of Aerospace and Systems Engineering Feng Chia University No.100 Wenhwa Rd. Seatwen Taichung40724 Taiwan Master's Program of Space Systems Engineering Feng Chia University No.100 Wenhwa Rd. Seatwen Taichung40724 Taiwan

ISBN: (数字)9781510683297

ISBN: (纸本)9781510683280

This paper is about the PIV experimental study on aerodynamics of a coaxial counter-rotating rotors aircraft. The main purpose is to observe and record the flow field distribution of the coaxial counter-rotating rotors when hovering, and to determine the rotor blade profile design for stable flight. The experimental method is to observe the flow field coupling effect of coaxial counter-rotating rotors with flow field visualization technology. This study uses the blade S-0 improved by the symmetrical airfoil NACA0012 and the blade AS-0 improved by the asymmetrical airfoil Viper-X to conduct flow field observation experiments. In order to survey the aerodynamic characteristics of blade configurations in the flow field under different flight conditions. This study also conducted experiments on conditions such as low and medium rotational speed at high angles of attack, medium and high angles of attack at high rotational speed. The experimental results show that the flow field of the blade S-0 has a relatively stable flow field characteristics at low rotational speed. But when the rotational speed increases and the angle of attack becomes higher, the flow field stability of the blade AS-0 is better. Finally, the flow field of blade AS-0 is more stable than the flow field of blade S-0 under most flight conditions. Therefore, blade AS-0 is more suitable for assembly on coaxial counter-rotating rotors. © 2024 SPIE.

关键词： Angle of attack

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Cuisine Image Recognition and Recommender System using Convolutional Neural Network 5

Cuisine Image Recognition and Recommender System using Convo...

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5th IEEE Eurasia Conference on IOT, Communication and engineering, ECICE 2023

作者： Chang, Chin-Chih Wei, Chi-Hung Wu, Kuan-Yun Kao, Hao-Xiang Hsiao, Sean Chung Hua University Department of Computer Science and Information Engineering Hsinchu Taiwan Chung Hua University Ph.D. Program in Engineering Science Hsinchu Taiwan National Kaohsiung University of Science and Technology Department of Computer Science and Information Engineering Kaohsiung Taiwan Chung Hua University Program of Applied Foreign Language and Smart Commerce Hsinchu Taiwan

ISBN: (纸本)9798350314694

The fusion of technology and culinary exploration has allowed for the emergence of advanced online customer service systems. We developed a novel approach to enhance the dining experience. We used a Cuisine Image Recognition and Recommender System (CIRRS) powered by Convolutional Neural Network (CNN) to identify and suggest diverse cuisines based on visual inputs. CIRRS swiftly identified diverse cuisines from user-captured images, offering information on origin, ingredients, and variations by crawling websites. The system enhanced dining experiences by suggesting personalized menus based on individual preferences and past selections. Extensively tested across various culinary genres, CIRRS consistently demonstrated accuracy and adaptability. User feedback validated its potential to simplify dining choices and elevate satisfaction. This innovative system enriched dining experiences as a valuable tool for culinary enthusiasts, chefs, and restaurateurs, bridging the gap between technology and gastronomy, It also offers a unique way to explore Taiwanese cuisines. © 2023 IEEE.

关键词： convolutional neural network (CNN) deep learning image recognition recommender system web crawler

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A Probabilistic Formulation of LidAR Mapping with Neural Radiance Fields

arXiv

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arXiv 2024年

作者： Mcdermott, Matthew Rife, Jason The Mechanical Engineering Ph.D. program Tufts University MedfordMA United States The Department of Mechanical Engineering Tufts University in Medford MA United States

In this paper we reexamine the process through which a Neural Radiance Field (NeRF) can be trained to produce novel LidAR views of a scene. Unlike image applications where camera pixels integrate light over time, LidAR pulses arrive at specific times. As such, multiple LidAR returns are possible for any given detector and the classification of these returns is inherently probabilistic. Applying a traditional NeRF training routine can result in the network learning "phantom surfaces" in free space between conflicting range measurements, similar to how "floater" aberrations may be produced by an image model. We show that by formulating loss as an integral of probability (rather than as an integral of optical density) the network can learn multiple peaks for a given ray, allowing the sampling of first, nth, or strongest returns from a single output channel. Copyright © 2024, The Authors. All rights reserved.

关键词： Aberrations

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Enhanced deep Learning Model Performance in 3d Multimodal Brain Tumor Segmentation with Gabor Filter

Enhanced Deep Learning Model Performance in 3D Multimodal Br...

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International Conference on Applied System Innovation (ICASI)

作者： Nisar Ahmad Yao-Tien Chen International Ph.D. Program in Innovative Technology of Biomedical Engineering and Medical Devices Ming Chi University of Technology New Taipei City Taiwan

ISBN: (数字)9798350394924

ISBN: (纸本)9798350394931

Medical image segmentation plays a crucial role in identifying and analyzing anatomical structures in medical images. This requires an accurate medical segmentation tool to delineate and quantitatively analyze the target regions, diagnose any abnormality, and assist in treatment planning. deep learning approaches have emerged as a promising solution for automating medical segmentation. However, challenges arise when dealing with the complex shapes and spatial variations of some target regions, especially in 3d MRI scans. To deal with such transformations, specific techniques are required to properly analyze and preprocess the dataset and perform image filtering to provide better features for improved prediction performance of deep learning architectures. This study focuses on improving brain tumor segmentation in multimodal 3d MRI images. We observed significant improvements in multimodal brain tumor segmentation results (accuracy, IoU, and mIoU) using an optimized 3d Gabor filter, which helps extract meaningful features. Multichannel input images were preprocessed to remove noise and select an appropriate resolution to reduce computational complexity. An improvement in mean Intersection over Union (mIoU) from 0.714 to 0.804 and accuracy from 0.982 to 0.991 were achieved, which shows a major improvement. This work contributes to the field of medical image segmentation by offering an improved and efficient approach for brain tumor analysis in 3d MRI scans, potentially aiding in diagnosis and treatment planning.

关键词： deep learning Image segmentation Solid modeling Three-dimensional displays Magnetic resonance imaging Feature extraction Planning

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3d Brain Tumor Segmentation in Multimodal MRI Images

3D Brain Tumor Segmentation in Multimodal MRI Images

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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Nisar Ahmad Yao-Tien Chen International Ph.D. Program in Innovative Technology of Biomedical Engineering and Medical Devices Ming Chi University of Technology New Taipei City Taiwan

ISBN: (数字)9798350386844

ISBN: (纸本)9798350386851

In brain tumor research, the use of machine learning based methods using MRI data to locate brain tumors accurately has significantly increased and new techniques are proposed to facilitate the medical experts. There is still room for improvement as tumors have complex anatomy which requires efforts to explore further and propose new deep learning based solutions. In this research, we propose 3d UNet based multimodal brain tumor segmentation for Non Enhancing Tumor (NET), Peritumoral Edema (PE), and Enhancing Tumor (ET). data preprocessing and augmentation techniques are employed to optimise the model's performance. The dataset used in this study to train, validate, and test the model performance is the BraTS 2020 dataset. The model achieved improved accuracy and IoU after implementing the mentioned techniques. Results before and after data augmentation demonstrate a significant enhancement in model performance. The model achieved an improved mIoU of 0.77 and accuracies of 98.21% and 99.36% for actual data and augmented data for three brain tumor classes, i.e., NET, PE, and ET. Our model performed multiclass brain tumor segmentation with high accuracies, and we aim to enhance this study to propose a valuable medical assistance model.

关键词： Solid modeling Image segmentation Three-dimensional displays Accuracy Magnetic resonance imaging Brain modeling data augmentation

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Effects of an automated programming assessment system on the learning performances of experienced and novice learners

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Interactive Learning Environments 2023年第8期31卷 5347-5363页

作者： Cheng, Li-Chen Li, Wei Tseng, Judy C. R. Department of Information and Finance Management National Taipei University of Technology Taipei Taiwan STEM Education Research Center Wenzhou University Zhejiang Province Wenzhou China Ph.D. Program in Engineering Science Chung Hua University Hsinchu Taiwan Department of Computer Science and Information Engineering Chung Hua University Hsinchu Taiwan

programming ability is the core ability of this era and can be obtained and improved through practice. In this paper, an Automated programming Assessment system based on Mastery learning and Peer competition (APAMP) was proposed and developed. APAMP allows students to practice repeatedly by providing immediate feedback after their programs are submitted. It also presents an analytical dashboard as a competition mechanism for students to visualize their learning performance and compare their performance with peers. By incorporating APAMP into programming courses, students can master programming skills through repeated practice, and their enthusiasm for learning programming can also be encouraged by peer competition. To evaluate the effects of APAMP on the learning performance of students with programming language learning and novice students, a quasi-experiment was conducted in a high school. The experimental results showed that the learning achievement of the two groups of students improved significantly. Moreover, the learning attitude of students in the experienced group improved significantly, with the experienced students benefiting more from the system than the novice students. In fact, the novice students showed a significant decline in learning attitude and learning motivation, which was contrary to our intuition. © 2021 Informa UK Limited, trading as Taylor & Francis Group.

关键词： automated programming assessment systems learning performance mastery learning peer competition programming instruction

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Atrophy of the cholinergic regions advances from early to late mild cognitive impairment

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Neuroradiology 2024年第4期66卷 543-556页

作者： Lai, Ying-Liang Larry Hsu, Fei-Ting Yeh, Shu-Yi Kuo, Yu-Tzu Lin, Hui-Hsien Lin, Yi-Chun Kuo, Li-Wei Chen, Cheng-Yu Liu, Hua-Shan Ph.D. Program in Medical Neuroscience College of Medical Science and Technology Taipei Medical University and National Health Research Institutes Taipei Taiwan Department of Biological Science and Technology China Medical University Taichung Taiwan School of Biomedical Engineering College of Biomedical Engineering Taipei Medical University Taipei Taiwan CT/MR Division Rotary Trading CO. LTD Taipei Taiwan Institute of Biomedical Engineering and Nanomedicine National Health Research Institutes Miaoli Taiwan Institute of Medical Device and Imaging National Taiwan University College of Medicine Taipei Taiwan Department of Radiology School of Medicine College of Medicine Taipei Medical University Taipei Taiwan Department of Medical Imaging Taipei Medical University Hospital Medical University Taipei Taiwan International Ph.D. Program in Biomedical Engineering College of Biomedical Engineering Taipei Medical University Taipei Taiwan

Purpose: We investigated the volumetric changes in the components of the cholinergic pathway for patients with early mild cognitive impairment (EMCI) and those with late mild cognitive impairment (LMCI). The effect of patients’ apolipoprotein 4 (APOE-ε4) allele status on the structural changes were analyzed. Methods: Structural magnetic resonance imaging data were collected. Patients’ demographic information, plasma data, and validated global cognitive composite scores were included. Relevant features were extracted for constructing machine learning models to differentiate between EMCI (n = 312) and LMCI (n = 541) and predict patients’ neurocognitive function. The data were analyzed primarily through one-way analysis of variance and two-way analysis of covariance. Results: Considerable differences were observed in cholinergic structural changes between patients with EMCI and LMCI. Cholinergic atrophy was more prominent in the LMCI cohort than in the EMCI cohort (P < 0.05 family-wise error corrected). APOE-ε4 differentially affected cholinergic atrophy in the LMCI and EMCI cohorts. For LMCI cohort, APOE-ε4 carriers exhibited increased brain atrophy (left amygdala: P = 0.001;right amygdala: P = 0.006, and right Ch123, P = 0.032). EMCI and LCMI patients showed distinctive associations of gray matter volumes in cholinergic regions with executive (R² = 0.063 and 0.030 for EMCI and LMCI, respectively) and language (R² = 0.095 and 0.042 for EMCI and LMCI, respectively) function. Conclusions: Our data confirmed significant cholinergic atrophy differences between early and late stages of mild cognitive impairment. The impact of the APOE-ε4 allele on cholinergic atrophy varied between the LMCI and EMCI groups. © 2024, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： APOE-ε4 allele cholinergic pathway Early mild cognitive impairment (EMCI) mild cognitive impairment (MCI) nucleus basalis of Meynert

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Cytometry in the Short-Wave Infrared

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ACS Nano 2024年第28期18卷 18534-18547页

作者： Liu, Te-I Wang, Jhih-Shan Nguyen, Ai-phuong Raabe, Marco Quiroz Reyes, Carlos Jose Lin, Chih-Hsin Lin, Ching-Wei Institute of Atomic and Molecular Sciences Academia Sinica Taipei City106319 Taiwan Department of Materials Science and Engineering National Taiwan University Taipei City106319 Taiwan Department of Physics University of Stuttgart Stuttgart70174 Germany Department of Chemistry National Tsing Hua University Hsinchu300044 Taiwan International Ph.D. Program in Biomedical Engineering Taipei Medical University New Taipei City235603 Taiwan Graduate Institute of Nanomedicine and Medical Engineering Taipei Medical University New Taipei City235603 Taiwan

Cytometry plays a crucial role in characterizing cell properties, but its restricted optical window (400-850 nm) limits the number of stained fluorophores that can be detected simultaneously and hampers the study and utilization of short-wave infrared (SWIR;900-1700 nm) fluorophores in cells. Here we introduce two SWIR-based methods to address these limitations: SWIR flow cytometry and SWIR image cytometry. We develop a quantification protocol for deducing cellular fluorophore mass. Both systems achieve a limit of detection of ∼0.1 fg cell-1 within a 30 min experimental time frame, using individualized, high-purity (6,5) single-wall carbon nanotubes as a model fluorophore and macrophage-like RAW264.7 as a model cell line. This high-sensitivity feature reveals that low-dose (6,5) serves as an antioxidant, and cell morphology and oxidative stress dose-dependently correlate with (6,5) uptake. Our SWIR cytometry holds immediate applicability for existing SWIR fluorophores and offers a solution to the issue of spectral overlapping in conventional cytometry. © 2024 The Authors. Published by American Chemical Society.

关键词： Oxygen

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Reusable Hydrogen Storage Tank with Flange design 10

Reusable Hydrogen Storage Tank with Flange Design

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10th International Conference on Applied System Innovation, ICASI 2024

作者： Li, Yun-Qi Chen, Hsuan-Jung Yang, Hsi-Wen Chen, Chih-Yuan Chang, Shao-Fu Chen, Ssu-Ying Chen, Chien-Chon College of Engineering and Science Ph.D. Program in Materials and Chemical Engineering National United University Miaoli Taiwan Michigan State University Department of Chemistry MI48824 United States National United University Department of Materials Engineering Miaoli Taiwan Graduate Institute of Intellectual Property National Taipei University of Technology Taiwan National United University Department of Energy Engineering Miaoli Taiwan

ISBN: (纸本)9798350394924

For how to store and transport hydrogen, the first thought is to store hydrogen directly in the cylinder. However, this method is not desirable, because generally at least 700 atm high pressure, the hydrogen contained in the cylinder to be useful. Therefore it is very unsafe at such high pressures. In This paper, we design and production of a new generation of solid-state hydrogen storage and discharge container. The goal of 'development of solid-state hydrogen storage technology' is to break through the bottlenecks of hydrogen storage technology safety, hydrogen storage density, high-efficiency hydrogen absorption and release, transportation safety, and engineering practice. © 2024 IEEE.

关键词： Aluminum

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