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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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High-Energy Lithium-Ion Capacitors Using the NiS2@MXene Electrode: Evidence of Dual Faradaic Reactions Driven by the Choice of Electrolytes

ACS Applied Engineering Materials

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ACS Applied engineering Materials 2025年第5期3卷 1277-1291页

作者： Keerthana Dileep Pamangadan C. Sharafudeen Mani Govindasamy Pin-Yi Chen Perumal Elumalai Electrochemical Energy Storage Lab Department of Green Energy Technology Madanjeet School of Green Energy Technologies Pondicherry University Puducherry 605014 India International Ph.D. Program in Innovative Technology of Biomedical Engineering and Medical Devices Ming Chi University of Technology New Taipei City 24301 Taiwan；Research Centre for Intelligence Medical Devices Ming Chi University of Technology New Taipei City 243303 Taiwan International Ph.D. Program in Innovative Technology of Biomedical Engineering and Medical Devices Ming Chi University of Technology New Taipei City 24301 Taiwan；Department of Mechanical Engineering Ming Chi University of Technology New Taipei City 24301 Taiwan；Department of Mechanical Engineering Chang Gung University Taoyuan City 33302 Taiwan

Transition metal sulfides (TMSs) are emerging as promising supercapacitor electrodes due to their excellent pseudocapacitive properties and substantial theoretical charge density. The combination of TMS and layered MXene synergistically enhances the energy and power, making them ideal for advanced energy storage applications. Here, NiS2@MXene composites were successfully synthesized via a simple probe sonication, and their formation, morphology, and composition were scrutinized using materials characterization techniques. Electrochemical analyses of the NiS2@MXene electrode in the KOH electrolyte revealed the occurrence of a Faradaic reaction involving (Ni3+/Ni2+) redox. Consequently, lithium-ion capacitors (LICs) using the NiS2@MXene and reduced graphene oxide (rGO) as respective positive and negative electrodes in aqueous and different nonaqueous electrolytes were fabricated, and their performances were analyzed in the form of coin cells. It turned out that the aqueous LIC (NiS2@MXene|1 M LiClO4(aq.)|rGO) delivered a specific energy of 48.4 W h kg–1at a specific power of 800 W kg–1. Notably, the nonaqueous LIC (NiS2@MXene|1 M LiClO4(EC/DMC)|rGO) achieved an increased specific energy of 64 W h kg–1at a specific power of 1500 W kg–1and exhibited excellent capacity retention of 80% over 20,000 long cycles. Excitingly, the nonaqueous LIC (NiS2@MXene|1 M LiPF6(EC/DEC)|rGO) delivered a remarkable specific energy of 117.3 W h kg–1at a specific power of 2100 W kg–1and successfully powered a commercial LED bulb and a stopwatch, showcasing the practicality of the electrode. The electrochemical measurements and the ex situ X-ray diffraction analyses confirmed the simultaneous occurrence of the conversion/reconversion and the intercalation/deintercalation reactions, facilitated on the electrode that led to such a high Li+charge storage performance. The conductive MXene matrix contributed to enhancing the charge transport by reducing the diffusion path and led to more active s

关键词： lithium-ion capacitor transition-metalsulfide NiS2 MXene nonaqueouselectrolyte conversion/intercalation reactions

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UNet-based Automatic Multicalss Brain Tissue Segmentation

UNet-based Automatic Multicalss Brain Tissue Segmentation

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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

In brain research, brain tissue segmentation techniques have offered vast aid and possibilities for quantitative analysis of the brain to detect brain tumor and other brain issues. In this paper, UNet-based multiclass brain tissue segmentation is presented. To achieve the best performance of the model, data augmentation techniques are applied. The training, validation and testing of the model is performed on the BrainWeb dataset. The model has achieved improved accuracy and IoU after data augmentation. Both pre and post data augmentation results are presented which show clear improvement in model performance after data augmentation. The achieved IoU for white matter, gray matter and cerebrospinal fluid are 0.84, 0.95 and 0.92, respectively. Our model accurately performed the multiclass brain tissue segmentation and this study proposes a valuable medical aid model.

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Colorectal Polyp Detection and Classification using Deep Learning Techniques

Colorectal Polyp Detection and Classification using Deep Lea...

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

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

ISBN: (数字)9798350386844

ISBN: (纸本)9798350386851

According to recent studies, colorectal cancer is one of the leading causes of death these days. Colorectal polyps are irregular formation of tissues that lead to colorectal cancer. Conventional methods are not sufficient to properly detect colorectal cancer in the early stages. Therefore, an efficient method is inevitable to detect and classify colorectal polyps in the early stage. In recent years, deep learning-based methods have been proposed, but there is still a need for improvement to make these methods more efficient. In this study, we have made a detailed comparison of the latest methods based on their computations and performance to propose an efficient model for real-time polyp detection. The comparison is made between deep learning based on three computation strategies: Edge Computing, General Purpose, and High Computing, using a custom colorectal dataset from a hospital. Similarly, data augmentation is also applied to analyse the performance of the mentioned techniques. We expect this study to provide insight into selecting an efficient method that would play a significant role in real-time polyp detection and classification to ensure invaluable medical aid.

关键词： Deep learning Training Learning systems Hospitals Computational modeling Colorectal cancer Data augmentation

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Developing a Respiratory Pressure Simulation Platform for a Portable Negative Pressure Filtering Chest Drainage System

Developing a Respiratory Pressure Simulation Platform for a ...

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IEEE international Conference on Nano/Molecular Medicine and engineering (NANOMED)

作者： Hao-Yen Liao Cheng-Shane Chu Yang-Shun Wu Sheng-Chieh Lin Chia-Tsai Lin Kuo-Yung Hung Department of International Ph.D Program in Innovative Technology of Biomedical Engineering and Medical Devices Ming Chi University of Technology TAIWAN Department of Mechanical Engineering Ming Chi University of Technology TAIWAN Research Center for Intelligent Medical Devices Ming Chi University of Technology TAIWAN

This study aims to reduce the risk of aerosol infection in patients and healthcare workers by establishing a portable negative pressure filtering chest drainage system (PNPFCDS) that filters aerosols and microparticles. By controlling the negative pressure precisely, the system can prevent aerosol transmission under different air leaks. By using a respiratory pressure simulation platform (RPSP), it has been demonstrated that the negative pressure filtering chest drainage system can achieve a minimum measured pressure error of 1.6% without simulated intrapleural pressure changes when the air leak flow rises to 800 ml/min. When the target pressure is −1.5 kPa under simulated intrapleural pressure changes with air leak of 500 ml/min, the measured pressure change rate ranges from −16.7 % to +22.7%. When the target pressure is −9 kPa, the measured pressure change rates ranges from −2% to +6.7%. According to ISO 10079-1, this study provides a model of a negative pressure filtering chest drainage system that is effective and safe.

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Using electroencephalography signals to explore the influence of Zentangle on meditation and mindfulness

Using electroencephalography signals to explore the influenc...

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international Conference on Applied System Innovation (ICASI)

作者： Muhammad Usman Chun-Ling Lin International Ph.D Program in Innovative Technology of Biomedical Engineering and Medical Devices Ming Chi University of Technology New Taipei City Taiwan Department of Electrical Engineering Ming Chi University of Technology New Taipei City Taiwan

Fifteen novices completed a Zentangle task while their brain activity was measured with electroencephalography (EEG) and their concentration emotional state, stress, and anxiety levels were evaluated with questionnaires. The study found increased activity in theta, alpha, beta, and gamma ranges associated with relaxation, focus, and mental activity. Participants reported improved concentration, emotional state, and reduced stress and anxiety levels after completing the task, suggesting the potential of Zentangle to enhance cognitive and emotional well-being.

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Microwave dielectric and structural characteristics in Li2O-B2O3-SiO2 glass ceramics

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Ceramics international 2025年

作者： Qiu, Jun-Yan Tu, Chi-Shun Huang, Szu-Ting Li, Yongxiang Chen, Pin-Yi Chen, Cheng-Sao Montecillo, Rhys Feng, Kuei-Chih International Ph.D. Program in Innovative Technology of Biomedical Engineering and Medical Devices Ming Chi University of Technology New Taipei City Taiwan Department of Physics Fu Jen Catholic University New Taipei City Taiwan Department of Mechanical Engineering Ming Chi University of Technology New Taipei City Taiwan School of Engineering RMIT University MelbourneVIC3000 Australia Research Center for Intelligent Medical Devices Ming Chi University of Technology New Taipei City Taiwan Department of Mechanical Engineering Hwa Hsia University of Technology New Taipei City Taiwan

Advancements in high-frequency communication devices have emphasized miniaturization and low energy consumption. This work focuses on developing microwave dielectric materials characterized by an ultra-low dielectric constant and low dielectric loss coefficient. In this study, B2O3 and Li2O were added into the SiO2 matrix to form the LBS glass-ceramics. The B2O3-added SiO2 shows a formation of α-cristobalite phase, and the Li2O additive in the B2O3-SiO2 glass-ceramics sintered at 900 °C reveal a primary quartz phase with a secondary phase Li2Si2O5, that partially transformed into Li2SiO3 in the specimen sintered at 950 °C. The LBS12 (x = 12 wt%) show stronger Raman peaks of Li2Si2O5 and Li2SiO3, indicating increase of highly-crystallized Si-O network. As the quartz phase diminishes, Li2Si2O5 and Li2SiO3 begin to develop in the glass-ceramic matrix. Dense microstructures and well-formed crystalline grains were observed in the LBS glass-ceramics. The quality factors were primarily affected by grain size and density. The Li2Si2O5 additive in the LBS glass-ceramics can reduce dielectric permittivity (Εr) and increase Q × f, particularly at higher frequencies. A low Εr of 4.7–5, a high Q × f of 2600 GHz, and a hardness of 249 MHV were achieved in the LBS12 sintered at 900 °C. These LBS glass-ceramics exhibit potential for use in low-temperature co-fired ceramic (LTCC) applications in high-frequency communication devices. © 2025

关键词： Sintering

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Optical Sensor for Dissolved Ammonia by Embedding Eosin Y in Cellulose Acetate and Silicone Rubber Via the Phase Inversion Method

SSRN

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SSRN 2024年

作者： Putro, Dimas Trio Sari, Desy Purnama Chu, Cheng-Shane International Ph.D. Program in Innovative Technology of Biomedical Engineering and Medical Devices Ming Chi University of Technology Taishan Dist. New Taipei City24301 Taiwan Department of Mechanical Engineering Ming Chi University of Technology Taishan Dist. New Taipei City24301 Taiwan Research Center for Intelligent Medical Devices Ming Chi University of Technology Taishan Dist. New Taipei City24301 Taiwan

The potential applications of optical sensors in biological systems, environmental monitoring, and renewable energy remain critically important. This study presents the phase inversion method for fabricating a new optical sensing membrane designed for dissolved ammonia detection. Eosin Y was embedded into composite materials of cellulose acetate (CA) and silicone rubber to enhance optical performance and modify the membrane’s structure. Luminescence quenching was used to evaluate sensing performance by measuring changes in intensity and wavelength. Eosin Y exhibited a sensitivity factor of approximately 19.15 within a detection range extending up to 480 millimolar dissolved ammonia. The results also demonstrated excellent selectivity when tested against nine different interferences, including methanol, acetic acid, and acetone. The membrane operated effectively within pH range of 3-9 and a temperature range of 20-50oC, with an average response time (t90) of approximately 20 seconds, though sensitivity decrease slightly at higher temperatures and extreme pH values. Furthermore, reduced photoexcitation of the indicator, resulting in a bathochromic shift of eosin Y by approximately 16.56 nm towards longer wavelengths. These findings highlight the potential of optical sensors for rapid and highly selective monitoring of changes in dissolved ammonia concentrations. © 2024, The Authors. All rights reserved.

关键词： Silicones

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Optical sensor for dissolved ammonia by embedding eosin Y in cellulose acetate and silicone rubber via the phase inversion method

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Microchemical Journal 2025年 213卷

作者： Putro, Dimas Trio Sari, Desy Purnama Chu, Cheng-Shane International Ph.D. Program in Innovative Technology of Biomedical Engineering and Medical Devices Ming Chi University of Technology Taishan Dist. New Taipei City 24301 Taiwan Department of Mechanical Engineering Ming Chi University of Technology Taishan Dist. New Taipei City 24301 Taiwan Research Center for Intelligent Medical Devices Ming Chi University of Technology Taishan Dist. New Taipei City 24301 Taiwan

This study presents the phase inversion method for fabricating a new optical sensing membrane designed for dissolved ammonia detection. Eosin Y was embedded into composite materials of cellulose acetate (CA) and silicone rubber to enhance optical performance and modify the membrane structure. Sensing performance was evaluated using luminescence quenching, which involved measuring changes in both intensity and wavelength. The fabricated membrane exhibited a microporous structure with pore diameters ranging from 1 to 10 µm, a quenching response (I₀/I₄₀₀) of 15.15, a response time (↓t₉₀) of 53 s, and effective detection at a concentration of 400 mM, a room temperature (20–25 °C), and pH 6.02, with sensing response slightly decreasing at elevated temperatures (up to 50 °C) and at pH 3.17 and 9.29. The nonlinear quenching response plot was converted into a linear form using the decibel (dB) formula, significantly improving linearity (R² = 0.9862). The membrane also exhibited excellent selectivity and the ability to detect in both gas and dissolved phases. Additionally, the sensing mechanism was investigated, revealing a combination of static and dynamic quenching, which led to an intensity decrease and a bathochromic shift of 16.56 nm. These findings highlight the potential of the developed optical sensor for rapid and highly selective ammonia monitoring in various environments. © 2025 Elsevier B.V.

关键词： Bathochromic shift Dissolved ammonia detection Eosin Y Optical sensing membrane Phase inversion method

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Development of ternary hybrid composites of transition metal and noble metal-based heterostructures: Ultrasensitive simultaneous electrochemical detection of bisphenol A and bisphenol S in food samples

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Food Chemistry 2024年 459卷 140451页

作者： Nandhini, Chinnathambi Huang, Chi-Hsien Mani, Govindasamy Arul, Ponnusamy Huang, Sheng-Tung Department of Materials Engineering Ming Chi University of Technology New Taipei City24303 Taiwan Center for Plasma and Thin Film Technologies Biochemical Technology R&D Center Ming Chi University of Technology New Taipei City243303 Taiwan College of Engineering Chang Gung University Taoyuan City33302 Taiwan International Ph.D. Program in Innovative Technology of Biomedical Engineering and Medical Devices Ming Chi University of Technology New Taipei City243301 Taiwan Institute of Biochemical and Biomedical Engineering Department of Chemical Engineering and Biotechnology National Taipei University of Technology Taipei10608 Taiwan

Bisphenols threaten human health and sensitive detection is crucial. The present study aims to develop ternary composites of copper metal-organic framework (Cu-MOF) with Au[sbnd]Ag microstructures. The composite structure was formed by a galvanic displacement reaction and confirmed using SEM. A binder-free catalyst was used to study the electrochemical redox reaction of bisphenol A (BPA) and bisphenol S (BPS);an irreversible cyclic voltammetric signal at +0.70 V and + 0.91 V (vs. Ag/AgCl), in the dynamic range of 20 nM to 2.0 mM, and 10 nM to 1.0 mM, with limits of detection of 2.9 nM, and 3.2 nM (S/N = 3) was obtained. Practical analysis was applied to frozen tomatoes, tuna fish, milk powder, PET bottles, raw milk, and urine samples with a recovery rate of 94.00–100.80% (n = 3). Voltammetric results were validated using HPLC detection with high precision. The sensor is a promising alternative platform for measuring BPA in food samples. © 2024

关键词： Phenols

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