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Ethylene Glycol-Manipulated Syntheses of Calcium Carbonate Particles and dNA Capsules toward Efficient ATP-Responsive Cargo Release

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ACS Applied Bio materials 2023年第8期6卷 3351-3360页

作者： Lin, Yu-Hsuan Singuru, Murali Mohana Rao Marpaung, david Septian Sumanto Liao, Wei-Ching Chuang, Min-Chieh Department of Chemistry Tunghai University Taichung407224 Taiwan International Ph.D. Program in Biomedical and Materials Science Tunghai University Taichung407224 Taiwan Department of Biosystems Engineering Institut Teknologi Sumatera Lampung Selatan35365 Indonesia Institute of Biochemistry and Molecular Biology National Yang Ming Chiao Tung University Taipei112304 Taiwan

Cargo molecule-encapsulated dNA capsules synthesized with a solid sacrificial template have elicited significant interest in the last decade and have been used for active materials in applications ranging from biosensors to drug delivery. However, the correlation between template properties and the subsequent assembly and triggered release behavior of the resultant carriers remain uninvestigated. In this study, ethylene glycol (EG) was added during the CaCO3 precipitation synthesis to yield particles of various sizes and surface properties, and the adenosine triphosphate (ATP)-responsive release characteristics of the fabricated dNA capsules affected by these particle properties were investigated. The geometry, crystallization, and surface morphology of the CaCO3 particles co-precipitated at various EG concentrations were characterized. We discuss the integrity of cross-linking hybridization, fluorescent molecule internalization, degree of leakage, and release efficiency of the resulting dNA capsules and their relevance brought by particle properties. To achieve efficient encapsulation and cargo release, the surface roughness of the CaCO3 particles was explored and was deemed a key determinant of the compactness of the dNA shell after template removal. This effect was particularly strong in CaCO3 particles in connection with high EG concentrations. The dNA capsules fabricated using 83% EG exhibited low leakage, high loading, and moderate release efficiencies as well as a greater apparent association constant with ATP due to their small particle size and the high-integrity dNA shells. © 2023 American Chemical Society.

关键词： Ethylene glycol

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A Fitness Movement Evaluation System Using deep Learning 15

A Fitness Movement Evaluation System Using Deep Learning

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15th International Conference on Knowledge and Systems engineering, KSE 2023

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

ISBN: (纸本)9798350329742

This paper proposes a fitness movement evaluation system using deep learning. The system uses a deep convolutional neural network (CNN) to extract features from pictures of fitness movements. The features are then used to classify the movements into different categories. The system is evaluated on a dataset of pictures of fitness movements. The results show that the system can accurately classify the movements into different categories. The system is designed to provide feedback to users on their fitness movements. The proposed system is a valuable tool for fitness enthusiasts. The main contribution of this paper is to propose a way to give users a score for their fitness movement. It can help users improve their fitness and track their progress over time. The system is also a valuable tool for fitness professionals. It can help professionals develop new fitness programs and provide feedback to their clients. © 2023 IEEE.

关键词： Convolutional neural networks

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deep Learning-Based Positioning Error Fault diagnosis of Wire Bonding Equipment and an Empirical Study for IC Packaging

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IEEE Transactions on Semiconductor Manufacturing 2023年第4期36卷 619-628页

作者： Kao, Sheng-Xiang Chien, Chen-Fu International Intercollegiate Ph.D. Program National Tsing Hua University Hsinchu30013 Taiwan Intelligent Manufacturing and Circular Economy Research Center National Tsing Hua University Artificial Intelligence for Intelligent Manufacturing Systems Research Center National Science and Technology Council Department of Industrial Engineering and Engineering Management Hsinchu300044 Taiwan

Little research has been done for artificial intelligence applications of semiconductor backend. This study aims to develop a deep learning based fault diagnosis framework as prognostics and health management (phM) solutions with a comprehensive analytics process. A linear encoder sensor is employed to measure position, while data preparation is conducted to convert position information into a signal. Then, signal processing is used to extract the features, in which high pass filter is applied to normalize the signal and emphasize the features. High-dimensional features including time domain statistical features, time-frequency domain features obtained by continuous wavelet transform (CWT), and frequency domain features converted by fast Fourier transform (FFT) are extracted to prepare the dataset. An ensemble neural network model that integrates deep neural network (dNN) and convolutional neural network (CNN) is employed to recognize the pattern and diagnose the positioning errors. The accuracy and false alarm rate are considered to support maintenance decisions. An empirical study was conducted in a world leading IC assembly and testing company for validation. The results have shown that the proposed approach can effectively detect inappropriate installation of the bond head in wire bonding equipment for predictive maintenance and cost reduction. © 1988-2012 IEEE.

关键词： Failure analysis

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An Application-Aware Clustering Strategy in Vehicular Ad Hoc Network 6

An Application-Aware Clustering Strategy in Vehicular Ad Hoc...

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6th International Conference on Computing, Electronics and Communications engineering, iCCECE 2023

作者： Wei, Chi-Hung Chang, Chin-Chih Chu, Chien-Hao Hsiao, Sean Chung Hua University Ph.D. Program in Engineering Science Hsinchu City Taiwan Chung Hua University Department of Computer Science and Information Engineering Hsinchu City Taiwan Chung Hua University Bachelor Program in Applied Foreign Language and Smart Commerce Hsinchu City Taiwan

ISBN: (纸本)9798350340921

VANET (Vehicular Ad Hoc Network) was developed to address the unique challenges of communication in a mobile vehicular environment. This technology can enhance driving safety and traffic control. Moreover, similar principles can be applied to unmanned aerial vehicles and robotics. When transmitting data in moving vehicles, it is challenging as access points and base stations keep changing, requiring handovers between different access points and base stations. Clustering is a popular approach used to address this challenge. Common clustering strategies are based on the proximity, communication range, the density, the application requirements of the moving vehicles, or hybrid of them. In this paper, we propose a clustering strategy based on the application sublayer in the vehicle communication protocol. If two computing devices on the move run the same application, they can be grouped together. The contribution of this research is to develop a clustering mechanism based on the application with very low overhead. We also validate the proposed method through simulations. The simulation results indicate that the proposed method is feasible. © 2023 IEEE.

关键词： Vehicular ad hoc networks

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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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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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Robust Audio Watermarking Based on Empirical Mode decomposition and Group differential Relations

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AES: Journal of the Audio engineering Society 2023年第3期71卷 100-117页

作者： Lai, Wen-Hsing Chou, Tsung-Yuan Chou, Meng-Chen Schuller, Björn W. Department of Computer and Communication Engineering National Kaohsiung University of Science and Technology No. 1 University Rd. Yanchao Dist. Kaohsiung City82445 Taiwan ZD.B Chair of Embedded Intelligence for Health Care and Wellbeing University of Augsburg Germany Ph.D. Program in Engineering Science and Technology College of Engineering National Kaohsiung University of Science and Technology Taiwan GLAM – Group on Language Audio & Music Imperial College London United Kingdom

An audio watermarking technique using Complementary Ensemble Empirical Mode decomposition and group differential relations of average absolute amplitudes of the last Intrinsic Mode Function (IMF) is proposed. By using group differential relations, the relationship with neighboring samples in the last IMF is well preserved, and near-imperceptibility can be achieved. Placing a watermark on low-frequency components, the last IMF, which is perceptually significant, therefore makes the watermark difficult to be removed. The embedding watermark, which is a logo image in our experiment, is processed by Arnold transformation, secret key encryption, and Bose–Chaudhuri–Hocquenghem coding to enhance robustness and security. Experimental results of the signal-to-noise ratio fit the recommendations of imperceptibility of the International Federation of the phonographic Industry. The average Objective difference Grade (an objective measure that correlates very well with subjective assessment) and subjective quality assessment were performed to evaluate the imperceptibility. Furthermore, our method accomplishes robustness under 13 different categories of attacks, including noise corruption, amplitude scaling, echo addition, resampling, re-quantization, low-pass filtering, MPEG-1 Audio Layer III compression, digital-to-Analog/Analog-to-digital conversion, cropping, time shift, zero thresholding, jittering, and combined attacks. © 2023 Authors. All rights reserved.

关键词： Intrinsic mode functions

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Enhanced Thermoelectric Performance of Mg-Sn Thin Films: Role of Mg9Sn5 phase and One-dimensional Electronic Structure

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ACS Applied materials and Interfaces 2024年第3期16卷 3520-3531页

作者： Chen, Cheng-Lung Chen, Sheng-Chi Chou, Ching-Lin Wang, Te-Hsien Chuang, Min-Chen Tang, Bo-Chen Chen, Yang-Yuan Bachelor Program in Semiconductor Materials and Fabrication Ming Chi University of Technology New Taipei City243 Taiwan Department of Materials Engineering and Center for Plasma and Thin Film Technologies Ming Chi University of Technology New Taipei City243 Taiwan College of Engineering and Center for Green Technology Chang Gung University Taoyuan333 Taiwan Department of Physics National Chung Hsing University Taichung40227 Taiwan Institute of Physics Academia Sinica Taipei115 Taiwan International Ph.D. Program in Plasma and Thin Film Technology Department of Materials Engineering and Center for Plasma and Thin Film Technologies Ming Chi University of Technology New Taipei City243 Taiwan

Mg-Sn alloy thin films have garnered significant attention for their outstanding thermoelectric (TE) properties and cost-effective elemental composition, making them potential candidates for wearable energy harvesting devices. While previous studies have explored the properties of these thin films, limited research has been conducted to identify physical factors that can further enhance their performance. In this study, we present a novel approach utilizing a convenient electron beam coevaporation technique to fabricate Mg-Sn alloy thin films. Experimental results revealed that controlling the tin content in the Mg-Sn thin films at 38.9% led to the formation of a mixed-phase structure, comprising Mg2Sn and Mg9Sn5. This dual-phase structure exhibited a notable advantage in enhancing the TE performance. The presence of the Mg9Sn5 phase significantly increased the carrier concentration, while maintaining the original Seebeck coefficient and mobility, thereby improving the conductivity of Mg2Sn. Theoretical calculations indicated that the Mg9Sn5 phase displayed 1d-like characteristics, leading to a highly effective valley degeneracy and consequently a high power factor. Overall, this work introduces a promising approach to fabricate high-performance Mg-Sn alloy thin films through electron beam coevaporation, opening up possibilities for their application in wearable energy harvesting devices. © 2024 American Chemical Society.

关键词： Energy efficiency

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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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Students Learning Performance and Engagement in a Visual programming Environment

Students Learning Performance and Engagement in a Visual Pro...

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Proceedings of the 6th International Conference on Innovative Technologies and Learning, ICITL 2023

作者： Wen, Fu-Hsiang Wu, Tienhua Hsu, Wei-Chih Ph.D. Program in Engineering Science and Technology College of Engineering National Kaohsiung University of Science and Technology Kaohsiung Taiwan Department of Management Air Force Institute of Technology Kaohsiung Taiwan Department of Computer and Communication Engineering National Kaohsiung University of Science and Technology Kaohsiung Taiwan

ISBN: (纸本)9783031401121

This study employed a quasi-experimental method to explore differences in students’ learning performance and engagement between visual and textual language programming environments. Specifically, this study examined how strongly engagement dimensions affect participants’ learning achievement in a Scratch experimental setting. One hundred and thirty-two undergraduate students participated. The results revealed that participants with Scratch intervention outperformed those with text-based language instructions in terms of performance and behavioral, emotional, cognitive, and agentic engagement. The findings indicated that engagement significantly predicted student academic success in a visual learning environment. This study concluded that visual programming tools such as Scratch help novices engaged and effectively learn core aspects of programming concepts. Additionally, student engagement deepens an understanding of predictions of programmers’ behaviors and achievements and mechanisms behind the effectiveness of visualization intervention. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Students

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