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Machine-learning-based sampling inspection under OQC capacity for real-time quality monitoring in the TFT-LCd industry

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International Journal of Production Research 2025年第6期63卷 2090-2113页

作者： Shih, Ming-Sung Chen, James C. Chen, Tzu-Li Chiang, Chih-Hsiung Hsu, Ching-Lan International Intercollegiate Ph.D. Program National Tsing Hua University Hsinchu Taiwan Department of Industrial Engineering and Engineering Management National Tsing Hua University Hsinchu Taiwan Graduate Institute of Intelligent Manufacturing Technology National Taiwan University of Science and Technology Taipei Taiwan Division of Quality Control AUO Corporation Taichung Taiwan

In the thin film transistor-liquid crystal display (TFT-LCd) industry, the competition is fierce, and the external failure cost is high. To improve the quality of released products, sampling inspection under outgoing quality control (OQC) is conducted before products are released. Owing to the variety and complexity of inspection items, the task must be carried out manually while realising automation is difficult. Traditional random sampling inspection is limited by sampling quantity, manpower, and material resources. To effectively improve acceptable quality levels, this paper proposes a quality predictive monitoring framework tailored to the production and inspection characteristics of the TFT-LCd industry. This framework includes real-time automatic quality monitoring based on an optimal machine learning prediction model with two-phase feature creation, and it also addresses OQC inspection capacity constraints. Experimental results show the prediction performance based on proposed model is better than the traditional random sampling process. In practice, superior average outgoing quality improves by more than 70% at the same sampling level. In addition, the features of the process can be further controlled and managed based on the prediction model to monitor the key parameters in real time and respond to abnormalities quickly, thereby further improving the quality of released products. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Liquid crystal displays

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deep-Learning Approach for An Analysis of Real-estate Prices and Transactions

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IEEE Access 2025年 13卷 89248-89265页

作者： Yang, Cheng-Hong Lee, Borcy Lin, Yu-da Tainan University of Technology Department of Information Management Tainan Taiwan National Kaohsiung University of Science and Technology Department of Electronic Engineering Kaohsiung Taiwan Kaohsiung Medical University Ph.D. Program in Biomedical Engineering Kaohsiung Taiwan Kaohsiung Medical University School of Dentistry Kaohsiung Taiwan Kaohsiung Medical University Drug Development and Value Creation Research Center Kaohsiung Taiwan National Penghu University of Science and Technology Department of Computer Science and Information Engineering Penghu Taiwan

Research on the study of houses, condominiums and buildings in Taiwan’s metropolitan areas continues to be an important area of research. In real estate forecasting and analysis, methods such as statistical analysis and questionnaire data collection are widely used. However, when multidimensional data is considered, these methods are time-consuming and inadequate. This study aimed to build a real estate forecasting model that can adapt to a changing environment. data were collected from public government databases, the collected data were standardized for accurate clustering, an appropriate data clustering algorithm was applied to the standardized data, and cross-statistical analysis was performed to verify the adopted algorithm. We used a deep learning based on autoencoder algorithm to increase the accuracy of the clustering analysis. A double-bottom map particle swarm optimization (dBM-PSO) clustering algorithm was then used to determine the optimal clustering solution. Cluster analysis and deep learning were conducted on data collected from public websites to understand the factors that led to the sustained increase in housing prices in Taiwan over the past decade. The results of this study indicate that three key factors—the number of real estate transactions, the average unit price of real estate transactions, and the building material and construction index—significantly affected real estate prices in Taiwan. Our results could help researchers and governments to focus on specific aspects of real estate development without being influenced by other related factors. In addition, the relationships between real estate trends and the aforementioned three key factors were determined to obtain valuable information that can enable the Taiwanese government to regulate the property market and prevent excessive growth. The framework proposed in this paper allows researchers and governments to focus on specific aspects of real estate development without being influenced b

关键词： Houses

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Recommendation of Resource Allocation decision Based on Bipartite Graph Network Structure

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IEIE Transactions on Smart Processing and Computing 2025年第1期14卷 128-139页

作者： Pei, Wen Pan, Wen-An Huang, Jui-Chan College of Management Chung Hua University Hsinchu30012 Taiwan Ph.D Program of Management Chung Hua University Hsinchu30012 Taiwan Department of Industrial Engineering and Management National Kaohsiung University of Science and Technology Kaohsiung807618 Taiwan

In resource allocation decisions in business, fully understanding customers’ needs and preferences helps to maximise benefits. As a result, in the modern business environment, the design of customized recommendation systems has gained a lot of attention. To this end, the study designs a recommendation algorithm for resource allocation decision based on improved two-part graph network structure. In this algorithm, an improved K-means clustering algorithm is introduced to deeply mine potential information. The calculation of similarity between users is also optimised to assist the target user to find the real neighbouring users. The findings demonstrate that, in comparison to the other algorithms, the resource allocation recommendation algorithm based on improved bipartite graph suggested in the study has a greater hit rate. The hit rate of the suggested algorithm can reach 32.5% when the recommendation list length is 10, which is a 21.5% improvement over the collaborative filtering algorithm. The suggested algorithm’s popularity is only 39.1, which is 69.3 less than the collaborative filtering algorithm when the suggestion list length is 10. Furthermore, the suggested algorithm for resource allocation decision-making created by the research has a greater recommendation accuracy, more personalization, and diversity, as seen by the proposed algorithm’s mean Hamming distance of 0.976. Through an improved bipartite graph network, the algorithm can fully analyze the historical preference information of users, effectively capture the complex relationship between users and products, generate personalized recommendation lists, and improve user satisfaction and purchase conversion rates. It provides an effective recommendation role for resource allocation decisions in modern business and helps to create greater economic benefits. © 2025 Institute of Electronics Engineers of Korea. All rights reserved.

关键词： Collaborative filtering

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Eff-SAM: SAM-based Efficient Method for Brain Tumor Segmentation in Multimodal 3d MRI Scans

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IEEE Access 2025年 13卷 90063-90087页

作者： Ahmad, Nisar Chen, Yao-Tien Ming Chi University of Technology International Ph.D. Program in Innovative Technology of Biomedical Engineering Medical Devices New Taipei City243303 Taiwan

Accurate brain tumor segmentation in MRI scans is crucial for effective diagnosis and treatment planning, as even minor segmentation errors can lead to significant clinical concerns. However, this task is challenged by the complex anatomy of the brain, variable tumor shapes, and low contrast between tumor sub-regions. Moreover, existing methods often lack generalizability across diverse segmentation tasks and imaging modalities. Large Vision Model (LVM) like the Segment Anything Model (SAM) represents a foundational advancement in tumor segmentation. While SAM has shown impressive performance on natural images, its effectiveness in medical imaging, especially brain tumor segmentation, is limited due to domain differences and indistinct boundaries in MRI scans. To address these challenges, we propose Eff-SAM, a 3d brain tumor segmentation framework that adapts SAM for medical applications through Parameter-Efficient Fine-Tuning (PEFT) technique. The framework incorporates PEFT with adapters into SAM’s encoder to fine-tune the model effectively and optimize its performance for medical imaging while maintaining computational efficiency. Additionally, a Cross-Sliced Attention (CSA) mechanism captures semantic relationships, improves tumor localization, and is introduced into the encoder. Robust data preprocessing further enhances the model’s generalization across datasets. Eff-SAM demonstrates state-of-the-art performance and outperforms benchmark methods on the BraTS 2020 and BraTS 2021 datasets. It achieves dice scores of 0.884 for Whole Tumor (WT), 0.853 for Tumor Core (TC), and 0.818 for Enhancing Tumor (ET) on the BraTS 2020 dataset, and 0.880 (WT), 0.861 (TC), and 0.821 (ET) on the BraTS 2021 dataset. This work highlights the potential of integrating vision models like SAM with lightweight, domain-specific modules to deliver accurate and efficient brain tumor segmentation offering a clinically valuable tool, especially in scenarios with limited data and complex tu

关键词： Semantic Segmentation

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Nanoplasmonic Biosensors: A Comprehensive Overview and Future Prospects

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International Journal of Nanomedicine 2025年 20卷 5817-5836页

作者： Mutalik, Chinmaya Sharma, Shashwat Yougbaré, Sibidou Chen, Chih-Yu Kuo, Tsung-Rong Graduate Institute of Nanomedicine and Medical Engineering College of Biomedical Engineering Taipei Medical University Taipei 11031 Taiwan Center for Airborne Infection & Transmission Science Tulane University School of Medicine New Orleans 70112 LA United States International Ph.D. Program in Medicine College of Medicine Taipei Medical University Taipei 11031 Taiwan Institut de Recherche en Sciences de La Santé/Direction Régionale du Centre Ouest (IRSS/DRCO) BP 21811 Nanoro Burkina Faso Department of Orthopedics Shuang Ho Hospital Taipei Medical University New Taipei City 23561 Taiwan International Ph.D. Program in Biomedical Engineering College of Biomedical Engineering Taipei Medical University Taipei 11031 Taiwan School of Biomedical Engineering Taipei Medical University Taipei 11031 Taiwan

Recent nanotechnological advancements have resulted in a paradigm shift in biosensing applications through the advent of nanoplasmonic biosensors. These devices integrate nanomaterials with phenomena like surface plasmon resonance (SPR) and localized SPR (LSPR) to address the critical diagnostic and analytical needs across medicine, food safety, and drug discovery. Leveraging metals like gold and silver, these sensors exhibit enhanced optical and electronic properties, enabling the detection of biomolecules at ultralow concentrations. However, despite their transformative potential, challenges concerning stability, reproducibility, cost-efficiency, and scalability impede widespread implementation. This review offers a rigorous analysis of nanoplasmonic biosensors, emphasizing their underlying operational mechanisms and diverse applications. It also delves into design paradigms, fabrication protocols, and optimization strategies while concurrently examining prevailing challenges and prospective advancements. Furthermore, it highlights emerging trends, such as hybrid plasmonic nanostructures, conferring advantages in miniaturization, automation, and high-throughput analysis, thereby establishing a robust foundation for future innovation in the field. © 2025 Mutalik et al.

关键词： device nanomaterial nanoplasmonic optical biosensor SPR

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Impact of Compact City on Carbon Emission Reduction Based on Urban Size: A Spatial Analysis Using Satellite Imagery

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Sustainable Cities and Society 2025年 126卷

作者： Mun, Hansol Jung, Juchul Correspondence: Ph.D. Korea Institute of Ocean Science & Technology Busan Korea Republic of Department of Urban Planning & Engineering Pusan National University Busan Korea Republic of

Cities contribute significantly to global carbon emissions, making sustainable development through efficient spatial planning essential for achieving carbon neutrality. Compact cities are crucial for urban planning because of concerns regarding the impact of dispersed development on society and the environment. However, researchers hold differing opinions, and debates continue. As cities expand, they develop different influences, underscoring the need to consider regional characteristics rather than rely on a single assessment framework. Understanding the interaction between urban size and spatial structure is vital because the relationship between compact city elements and carbon emissions is complex. This study aimed to clarify the carbon emission reduction effects of compact cities by considering their urban size and analyzing cities in the United States and South Korea. For example, although the compactness in larger cities may reduce emissions, the opposite effect may occur in smaller cities. Using satellite imagery, this study not only measured carbon emissions and three compact city characteristics but also conducted a panel threshold regression analysis to assess how these elements influenced emissions across various urban sizes. The results indicated that the impact of compact city characteristics on emissions varied with urban size, highlighting the significant interaction between urban size and spatial structure. For example, the analysis confirmed that reducing per capita VKT is essential despite environmental regulations and technological advancements. In small cities, greater compactness tends to increase carbon emissions, but beyond a certain size it contributes to their reduction. Likewise, while polycentricity increase emissions in smaller cities, it helps lower them as the city grows. This underscores the importance of understanding emission trends in relation to urban size and structure, while advocating for tailored spatial planning and strategic

关键词： Low emission

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Innovation in Geriatric Care: An AI Assistant with LLM Integration Based on Health Guidelines

Innovation in Geriatric Care: An AI Assistant with LLM Integ...

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18th International Joint Conference on Biomedical engineering Systems and Technologies, BIOSTEC 2025

作者： Basulo-Ribeiro, Juliana Matos, Nádia C. G. Araujo, Sabrina Magalhães Capela, Nuno Bischoff, Francisco Teixeira, Leonor Cruz-Correia, Ricardo University of Aveiro Aveiro Portugal Faculty of Medicine University of Porto Porto Portugal Faculty of Medicine of the University of Porto Health Data Science Ph.D. Program Porto Portugal CINTESIS - Center for Health Technology and Services Research Faculty of Medicine University of Porto Porto Portugal VirtualCare Portugal

With the advance of artificial intelligence and natural language processing technology, a new tool is standing out in the field of understanding and generating natural language in a sophisticated way: the Large Language Model (LLM). According to several authors, LLMs can be used for various types of medical cases, providing access to different sources of information, and have opened up countless opportunities in the healthcare sector. This work aims to share the lessons learned during the process of developing an LLM-based assistant aimed at specific pathologies that are more prevalent in the elderly in order to support caregivers, whether they are private individuals, home care organizations, nursing homes or others. This study has a significant potential impact on the community by providing access to detailed information on developing an LLM-based assistant. © 2025 by SCITEPRESS – science and technology Publications, Lda.

关键词： Electronic health record

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Bioactive compounds from tropical fruit by-products: Extraction, characterization and therapeutic potential

Journal of Agriculture and Food Research

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Journal of Agriculture and Food Research 2025年 21卷

作者： Otero-Guzman, Niza Andrade-Pizarro, Ricardo Ph.D. Program in Food Science and Technology Universidad de Córdoba Cra. 6 #77-305 Córdoba Montería Colombia

The processing of tropical fruits generates large amounts of residues, such as peels or seeds, with great nutraceutical potential due to their high content of bioactive compounds: polyphenols, carotenoids, anthocyanins, flavonoids, tannins, and phenolic acids with antioxidant, anti-inflammatory, antimicrobial, anticancer and anti-obesity properties. However, there are several challenges associted with the efficient extraction and accurate characterization of these compounds, including the complexity of plant matrices, variability in compound polarity, and the need for scalable, eco-friendly methods that preserve their bioactivity. This review highlights the bioactive composition, the most important and studied therapeutic properties of the by-products of different tropical fruits such as mango, pineapple, and avocado, and the main extraction, identification, and characterization techniques of these compounds. A scientific surveillance analysis of studies published on the last 5 years revealed a 67.6 % increase in research activity, with a growing emphasis on green extraction technologies—such as ultrasound-assisted, microwave-assisted, and supercritical fluid extraction— and the use of emerging solvents like natural deep eutectic solvents. Moreover, there is increasing interest in optimizing extraction conditions and in validating the functional potential of bioactive compounds through in vitro digestion and bioavailability assays. These trends underscore the strategic relevance of tropical fruit by-products as a sustainable source of functional compounds. The integration of clean technologies, optimization and scale-up strategies, and advanced analytical methods supports their valorization and promotes the development of high value-added nutraceuticals aligned with circular economy principles and public health objectives. © 2025 The Authors

关键词： Antioxidants Bioaccessibility Green technologies Health benefits phytochemicals

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Cytocompatible and antibacterial Fe-, Cu- and Zn-substituted calcium hydroxyapatite materials for skin applications

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Ceramics International 2025年第9期51卷 11286-11296页

作者： Lukaviciute, L. Lukowiak, A. Stankeviciute, Z. Junka, A. Mortimer, M. Zarkov, A. Yang, J.-C. Ganceviciene, R. Kareiva, A. Faculty of Chemistry and Geosciences Vilnius University Naugarduko st. 24 Vilnius03225 Lithuania Institute of Low Temperature and Structure Research Polish Academy of Sciences Okolna 2 Wroclaw50422 Poland Department of Pharmaceutical Microbiology and Parasitology Wroclaw Medical University Borowska 211A Wroclaw50556 Poland Laboratory of Environmental Toxicology National Institute of Chemical Physics and Biophysics Akadeemia tee 23 Tallinn12618 Estonia Graduate Institute of Nanomedicine and Medical Engineering International Ph.D. Program in Biomedical Engineering College of Biomedical Engineering Research Center of Biomedical Device Research Center of Digital Oral Science and Technology Taipei Medical University Taiwan Faculty of Medicine Vilnius University M.K. Ciurlionio st. 21 Vilnius03101 Lithuania

Calcium hydroxyapatite (C10(PO4)6(OH)2;CHAp) and metal-substituted samples (Fe:CHAp, Cu:CHAp, and Zn:CHAp) were synthesized using a recently developed method. This method involved the wet precipitation of amorphous calcium phosphate (ACP), followed by solid-state reaction synthesis of α-tricalcium phosphate (α-TCP), and finally hydrothermal synthesis of CHAp. The effect of Fe3+, Cu2+, and Zn2+ substitution on the phase purity and antimicrobial properties of CHAp are summarized in this study. Notably, it highlights the phase purity of CHAp and Zn:CHAp (in the presence of Fe3+ and Cu2+ ions, the α- and β-TCP phases have formed) as well as the antimicrobial activity of Zn:CHAp and Cu:CHAp against Staphylococcus aureus and Candida albicans. The synthesized nanosized CHAp, Fe:CHAp, Cu:CHAp, and Zn:CHAp samples were used as additives in the preparation of skin creams. In vitro biological studies of the resulting skin creams demonstrated their antimicrobial activity against Pseudomonas aeruginosa, and showed a reduction in osteoblasts cells viability of in the range of 20–40 %. The addition of zinc enhances antimicrobial efficacy but reduces biocompatibility, while copper maintains both high antimicrobial activity and biocompatibility, making it more suitable for the development of medical or cosmetic materials. dermal creams containing CHAp with copper and iron ions also show significant antimicrobial activity while preserving good cell viability. These results highlight the importance of optimizing the balance between antimicrobial effectiveness and biocompatibility in these materials. © 2024

关键词： Biocompatibility

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Impact of transient liquid phase bonding on CuFeNiMnTi high entropy alloy: A microstructural and mechanical perspective

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physica B: Condensed Matter 2025年 712卷

作者： Hosseini, S.H. Adabavazeh, Z. Karimzadeh, F. Abbasi, M.H. Department of Materials Engineering Isfahan University of Technology Isfahan*** Iran Ph.D. Program Graduate Institute of Precision Manufacturing National Chin-Yi University of Technology Taichung411030 Taiwan

High-entropy alloys exhibit unique properties but face challenges in permanent joining, particularly in maintaining mechanical integrity. Transient liquid phase bonding offers an efficient solution using a controlled solidifying interlayer. This study investigates the effect of bonding temperature on the microstructure and mechanical properties of CuFeNiMnTi HEA joints using AWS BNi-2 and pure copper interlayers. Bonding was conducted at 980 °C, 1030 °C, and 1080 °C for 30 min. The HEA was cast using vacuum induction melting and heat-treated at 940 °C for 5 h. Samples underwent polishing, cleaning, and bonding in a furnace. Mechanical performance was assessed through microhardness and shear strength tests, while SEM and XRd characterized the diffusion-affected and isothermally solidified zones. AWS BNi-2 improved microstructural uniformity and increased joint strength from 200 MPa to over 350 MPa, achieving 91 % of the base metal's shear strength. These results confirm its effectiveness in optimizing HEA bonding for high-strength applications. © 2025

关键词： Microhardness

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