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International Conference on ICT For Smart Society (ICISS)

作者： Muhammad Reza Azhar Priyadi Suharjito Computer Science Department BINUS Online Learning Bina Nusantara University Jakarta Indonesia Industrial Engineering Department BINUS Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia

Despite Indonesia's leading position in palm oil processing, the inaccurate assessment of oil palm fruit maturity poses challenges in determining the optimal harvest timing and maintaining product quality. With advancements in information technology, including image processing and object detection techniques like YOLO and EfficientDet, there is potential for automated and precise identification of palm fruit maturity. To explore this, the authors conducted research to identify the most suitable algorithm for detecting the ripeness of palm oil fruit. The study utilized a dataset consisting of 8299 images with six maturity levels, employing augmentation techniques to increase image variability. Results show that YOLO V8s outperformed EfficientDet Lite 4 in terms of object detection precision, achieving higher mean average precision (mAP) scores. YOLO V8s showed a 4% improvement in mAP@50 and a 16% improvement in mAP@50-95 compared to EfficientDet Lite 4. YOLO V8s achieved a mAP of 0.978 for mAP@50 and 0.765 for mAP@50-95, surpassing EfficientDet Lite 4. However, EfficientDet Lite 4 had an advantage in terms of class accuracy and bounding box placement, as indicated by smaller box loss and cIs_ loss values. YOLO V8s also demonstrated better frames per second (FPS) performance, ranging from 10 to 15 FPS, compared to EfficientDet Lite 4.

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Understanding ADC variation by fat content effect using a dual-function MRI phantom

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European Radiology Experimental 2024年第1期8卷 19页

作者： Liu, Yi-Jui Tsai, Tung-Sheng Li, Ya-Hui Peng, Jo-Hua Chang, Hing-Chiu Peng, Hsu-Hsia Lee, Ying-Chieh Lee, Tung-Yang Liou, Chang-Hsien Lin, Tz-Feng Chew, Fatt-Yang Chou, Ruey-Hwang Juan, Chun-Jung Department of Automatic Control Engineering Feng Chia University Taichung Taiwan Ph.D. Program in Electrical and Communication Engineering Feng Chia University Taichung Taiwan Department of Medical Imaging China Medical University Hsinchu Hospital 199 Sec. 1 Xinglong Rd. Hsinchu County Zhubei City 302 Taiwan Department of Biomedical Engineering and Environmental Sciences National Tsing Hua University Hsinchu Taiwan Department of Biomedical Engineering Chinese University of Hong Kong Hong Kong Master’s Program of Biomedical Informatics and Biomedical Engineering Feng Chia University Taichung Taiwan Cheng Ching Hospital Taichung Taiwan Institute of Nuclear Engineering and Science National Tsing Hua University Hsinchu Taiwan Department of Fiber and Composite Materials Feng Chia University Taichung Taiwan Department of Medical Imaging China Medical University Hospital Taichung Taiwan Department of Radiology School of Medicine China Medical University Taichung Taiwan Graduate Institute of Biomedical Sciences China Medical University Taichung 406 Taiwan Center for Molecular Medicine China Medical University Hospital Taichung Taiwan Department of Medical Laboratory and Biotechnology Asia University Taichung Taiwan

Background: A dual-function phantom designed to quantify the apparent diffusion coefficient (ADC) in different fat contents (FCs) and glass bead densities (GBDs) to simulate the human tissues has not been documented yet. We propose a dual-function phantom to quantify the FC and to measure the ADC at different FCs and different GBDs. Methods: A fat-containing diffusion phantom comprised by 30 glass-bead-containing fat-water emulsions consisting of six different FCs (0, 10, 20, 30, 40, and 50%) multiplied by five different GBDs (0, 0.1, 0.25, 0.5, and 1.0 g/50 mL). The FC and ADC were measured by the “iterative decomposition of water and fat with echo asymmetry and least squares estimation-IQ,” IDEAL-IQ, and single-shot echo-planar diffusion-weighted imaging, SS-EP-DWI, sequences, respectively. Linear regression analysis was used to evaluate the relationship among the fat fraction (FF) measured by IDEAL-IQ, GBD, and ADC. Results: The ADC was significantly, negatively, and linearly associated with the FF (the linear slope ranged from -0.005 to -0.017, R² = 0.925 to 0.986, all p < 0.001). The slope of the linear relationship between the ADC and the FF, however, varied among different GBDs (the higher the GBD, the lower the slope). ADCs among emulsions across different GBDs and FFs were overlapped. Emulsions with low GBDs plus high FFs shared a same lower ADC range with those with median or high GBDs plus median or lower FFs. Conclusions: A novel dual-function phantom simulating the human tissues allowed to quantify the influence of FC and GBD on ADC. Relevance statement: The study developed an innovative dual-function MRI phantom to explore the impact of FC on ADC variation that can affect clinical results. The results revealed the superimposed effect on FF and GBD density on ADC measurements. Key points: • A dual-function phantom made of glass bead density (GBD) and fat fraction (FF) emulsion has been developed. • Apparent diffusion coefficient (ADC) values

关键词： Adipose tissue Diffusion magnetic resonance imaging Phantoms (imaging) Quality assurance (healthcare) Quality control

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Upgrading the Quality of Solid Fuel Made from Nyamplung (Calophyllum inophyllum) Wastes Using Hydrothermal Carbonization Treatment

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Energy engineering 2021年第1期118卷 189-197页

作者： Riina Syivarulli Nugroho Agung Pambudi Mochamad Syamsiro Lip Huat Saw Graduate Program of Vocational Teacher Education Sebelas Maret UniversitySurakarta57126Indonesia Department of Mechanical Engineering Education Sebelas Maret UniversitySurakarta57126Indonesia Department of Mechanical Engineering Janabadra UniversityYogyakarta55231Indonesia Lee Kong Chian Faculty of Engineering and Science UTARKajang43000Malaysia

One of the major problems faced in managing biomass waste to higher quality products is choosing the right *** are used as an alternative fuel,with increase in the calorific *** carbonization(HTC)is a biomass conversion technology,used to obtain solid *** study aims to utilize of Calophyllum inophyllum as an alternative solid fuel through *** calorific value and proximate of the hydrochar will be determined and analyzed to find out its *** experiments were carried out at temperature variations of 160℃,190℃,and 220℃ and holding times of 30 and 60 *** results show that an increase in temperature and holding time causes a decline in the moisture content 1.87%,volatile matter 54.03%,and ash content 12.35%,respectively,leading to elevations in the fixed carbon at 31.75%.In addition,the highest calorific value of 4149 Kcal/Kg was produced at a temperature of 220℃,within a holding time of 60 *** results showed a significant increase in the quality of solid fuels between 3500–4611 Kcal/Kg in accordance with the American Standard Testing and Materials(ASTM).Therefore,this research leads to an important finding that Calophyllum inophyllum waste through the HTC process can be used as an alternative fuel to substitute lignite coal,which is environmentally friendly.

关键词： Hydrothermal carbonization solid fuel Calophyllum inophyllum Nyamplung

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Genomic analysis of the SARS-CoV-2 variants circulated in the Philippines, 2020–2024

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Dialogues in Health 2024年 5卷 100193-100193页

作者： Dimaano, Arnie Carreon, Kiana Dominique Camaya, Giselle Sophia Rondolo, Irvin Tolentino, Jarel Elgin Department of Biological Sciences College of Science The University of Santo Tomas Philippines Department of Biology School of Science and Engineering Ateneo de Manila University Philippines Department of Computational Biology and Medical Sciences Graduate School of Frontier Sciences The University of Tokyo Kashiwa Japan

Purpose: Genomic sequencing has been an invaluable tool to determine the evolution of SARS-CoV-2. In the present study, we provided a comprehensive description of the SARS-CoV-2 variants circulated in the Philippines. Methods: The dataset from the human COVID-19 infections was acquired by downloading the sequences and their associated metadata spanning from March 2020 to April 2024. Then, we executed several filtering criteria to acquire the final dataset for the Philippine samples and performed spatial distribution analysis and phylogenetic tree construction of the reported SARS-CoV-2 sequences. Results: A total of 16,679,203 SARS-CoV sequences were obtained, of which 17,393 (0.10 %) were sampled in the Philippines. Western Visayas reported the highest SARS-CoV-2 sequences (21.33 %), while the Bangsamoro Autonomous Region in Muslim Mindanao reported the least (0.48 %). The phylogenetic tree revealed the evolution of the detected SARS-CoV-2 variants circulating in the Philippines with 19 A as the first reported case (based on the GISAID submission), and 24 A (JN.1) as the currently circulating variant. Omicron variants have dominated the Philippines with 21 L (Omicron, BA.2) having 5102 cases (29.33 %), followed by 22B (BA.5) having 2184 cases (12.57 %). Using Pearson's Chi-square test of independence, we showed that there is a significant association between the age-groups and gender with the detection years. Conclusion: Altogether, this analysis showed the updated epidemiological trends of the reported SARS-CoV-2 variants in the Philippines. This increases the importance of conducting surveillance on viral infectious diseases such as COVID-19 to provide the scope and trajectory of viral spread in a country. © 2024

关键词： COVID-19 Epidemiology Philippines SARS-CoV-2 variants

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Data Logging and Non-invasive IoMT Approach for Rats Monitoring in Laboratory Experiments 37th

Data Logging and Non-invasive IoMT Approach for Rats Monit...

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37th International Conference on Advanced Information Networking and Applications, AINA 2023

作者： Barbosa, Bryan C. M. Garan, Steven A. Quintela, Barbara Melo Dantas, Mario R. Universidade Federal de Juiz de Fora Juiz de Fora Brazil Center for Research and Education in Aging University of California Berkeley and Lawrence Berkeley National Laboratory BerkeleyCA United States Computational Physiology and High Performance Computing Laboratory and Computer Science Department at Universidade Federal de Juiz de Fora Juiz de Fora Brazil Computer Science Graduate Program at Universidade Federal de Juiz de Fora Juiz de Fora Brazil

ISBN: (纸本)9783031290558

It is being observed that the use of Internet of Medical Things (IoMT) in health sciences research grows as the technology and miniaturization of devices occur. Those devices often times suffer from several issues such as: being invasive, lacking the ability to collect many signals concurrently and communication. The present work proposes an approach to the use of an ultra-small IoMT device to fulfill the functions of a bio-signals data collector, a mathematical models processor, a data transmitter-receptor through the network, and a mechanical actuators controller. Our test environment was conceived to be used in animal models. This is an ongoing project from which partial results indicate that, when functioning, the device will use real-time data for monitoring bio-signals and helping with decision-making as it interacts with the organism. The data collection is going to be made through low-cost non-invasive sensors. Therefore, it can favor installation, maintenance, access, and promote a better quality of life for the user. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Decision making

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Layer-by-Layer Assembly of Chitosan and Quince Seed Gum Polyelectrolytes as a Ph-Responsive, On-Off Switchable Multilayer Film for Controlled Release of Ibuprofen

SSRN

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SSRN 2024年

作者： Kaviani, Alireza Pircheraghi, Gholamreza Bagheri, Reza Azizi Saadatlou, Ghazaleh Demirel, A. Levent Department of Materials Science and Engineering Sharif University of Technology P.O. Box: 11365‐9466 Tehran Iran Materials Science & Engineering Graduate Program Koç University Sarıyer Istanbul34450 Turkey Chemistry Department Koç University Sarıyer Istanbul34450 Turkey

Polysaccharide-based multilayer films have shown substantial potential for drug delivery application. Herein, polyelectrolyte multilayers using Chitosan (CS) and Quince seed gum (QSG) are constructed and the effects of assembly pH, salt concentration, and post-assembly pH are systematically investigated. It was evident that both mass per unit area (10000 ng/cm2) and the wet thickness (107.8 nm) after the deposition of 5 bilayers were accurately estimated by viscoelastic model due to the highly swollen state of films. Atomic Force Microscopy (AFM) could feasibly demonstrate the development of globular structures during the layer-by-layer assembly. Ellipsometry analysis showed that the variation assembly pH resulted in conformational changes from extended to coiled. Consequently, different optical thicknesses as well as transitions from exponential to linear growth were observed. Moreover, extrinsic charge compensation was responsible for coiling or extensive counterion screening of polyelectrolyte chains depending on the NaCl concentration. CS/QSG films displayed pH-stimulus on–off switching behavior in pH 2 and 7.4 for 3 cycles. The constructed film could absorb 1200 ng/cm2 within 60 min at pH 7.4. The in vitro release kinetic from IBF-loaded samples showed pH dependency. The CS/QSG multilayer film can be considered as a smart and tunable pH stimuli system for drug loading/release applications. © 2024, The Authors. All rights reserved.

关键词： Chitosan

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3D Geometric Shape Assembly via Efficient Point Cloud Matching

arXiv

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arXiv 2024年

作者： Lee, Nahyuk Min, Juhong Lee, Junha Kim, Seungwook Lee, Kanghee Park, Jaesik Cho, Minsu Department of Computer Science and Engineering POSTECH Pohang Korea Republic of Graduate School of Artificial Intelligence POSTECH Pohang Korea Republic of Department of Computer Science and Engineering Seoul National University Seoul Korea Republic of Interdisciplinary Program in Artificial Intelligence Seoul National University Seoul Korea Republic of

Learning to assemble geometric shapes into a larger target structure is a pivotal task in various practical applications. In this work, we tackle this problem by establishing local correspondences between point clouds of part shapes in both coarse- and fine-levels. To this end, we introduce Proxy Match Transform (PMT), an approximate high-order feature transform layer that enables reliable matching between mating surfaces of parts while incurring low costs in memory and computation. Building upon PMT, we introduce a new framework, dubbed Proxy Match TransformeR (PMTR), for the geometric assembly task. We evaluate the proposed PMTR on the large-scale 3D geometric shape assembly benchmark dataset of Breaking Bad and demonstrate its superior performance and efficiency compared to state-of-the-art methods. Project page: https://***/pmtr. Copyright © 2024, The Authors. All rights reserved.

关键词： Large datasets

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A Cascade Deep Neural Network Approach for Oil Spills Classification and Detection

A Cascade Deep Neural Network Approach for Oil Spills Classi...

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International Conference on Electric Power and Energy Conversion Systems (EPECS)

作者： Mohammad Rashwan Mohammed Alhadi Mohammad A. Jaradat Mohammad I. Daoud Mechatronics Graduate Program American University of Sharjah Sharjah United Arab Emirates Mechanical Engineering Department American University of Sharjah Sharjah United Arab Emirates Computer Science and Engineering Department American University of Sharjah Sharjah United Arab Emirates

ISBN: (数字)9798331516963

ISBN: (纸本)9798331516970

Oil spills represent a growing environmental challenge that poses a significant threat to living organisms. Moreover, the treatment of oil spills, especially in severe cases, has serious economic repercussions and requires substantial labor and time. Therefore, the effective detection of oil spills has become an important research problem. Traditional methods for detecting oil spills, such as manual patrolling and dynamic sensors, are often limited in accuracy and coverage. As a result, the automation of oil spills detection has emerged as a critical global imperative in scientific research. The aim of this paper is to employ deep learning technology to achieve effective detection of oil spills based on aerial images. Our approach is composed of two phases. In the first phase, a Deep Convolutional Neural Network (DCNN), namely ResNet50, is trained on a large dataset containing images showing oil spills at a seaport. The trained DCNN is used to classify the input image as "Oil Spill" or "No Oil Spill". In the second phase, the images classified as "Oil Spill" are analyzed using a deep learning detection model, namely You-Only-Look-Once (YOLOv4), to localize the oil spills. The results indicate the capability of the proposed method to achieve effective oil spill detection. In particular, the classification accuracy obtained by the ResNet50 model is equal to 98%. Moreover, the YOLOv4 model was able to obtain effective localization of the oil spills with mean-average precision of 62%.

关键词： Deep learning Accuracy Oils Manuals Seaports Organisms Sensors Power systems Convolutional neural networks Residual neural networks

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Pelvic bone region segmentation (PBRS) from X-ray image using convolutional neural network (CNN)

Pelvic bone region segmentation (PBRS) from X-ray image usin...

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International Conference on Computer and Information Technology (ICCIT)

作者： Syed Alif Ul Alam Saadia Binte Alam Sourav Saha Mahmudul Haque Rashedur Rahman Syoji Kobashi Department of Computer Science and Engineering Independent University Bangladesh Dhaka Bangladesh Center for Computational & Data Sciences Independent University Bangladesh Dhaka Bangladesh Graduate School of Engineering University of Hyogo Shosha Himeji Hyogo Japan

Pelvic and hip fractures offer considerable public health risks with high morbidity and mortality rates. Because of the complicated bone structure of the pelvic bone region, detecting fractures is difficult. Though X-ray imaging is routinely utilised for detecting fractures, manual fracture diagnosis is prone to inaccuracies. This paper proposes the use of deep learning algorithms for automated segmentation of the pelvic bone region in X-ray images. In our work, we have investigated U-Net based pelvic area segmentation models with various convolutional neural network (CNN) backbones. The DenseNet121-based U-Net design emerged as the most optimal model, establishing a compromise between performance and computational efficiency. Although it had a modest loss in IoU and F1 scores when compared to InceptionNetV3, it had a remarkable 59.44% reduction in the number of parameters.

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Sweet–Bitter Taste Interactions in Binary Mixtures of Sweeteners: Relationship of Taste Receptor Activities with Sensory Perception

SSRN

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SSRN 2024年

作者： Choi, Yoonha Wong, RunRou Cha, Yeon Kyung Park, Tai Hyun Kim, Yuri Chung, Seo-Jin Department of Nutritional Science and Food Management Ewha Womans University Seoul03760 Korea Republic of Interdisciplinary Program in Bioengineering Seoul National University Seoul08826 Korea Republic of Graduate Program in System Health Science and Engineering Ewha Womans University Seoul03760 Korea Republic of

Combining several low-calorie sweeteners in a food is a common strategy for reducing caloric sweeteners. The effects of binary sweetener mixtures on sweetness enhancement and sweet–bitter taste receptor interactions, specifically sensory perception and receptor activity, were investigated. Acesulfame K or saccharin was mixed with allulose, aspartame, erythritol, fructose, glucose, or sucrose to match a target sucrose sweetness. The effects of the mixtures on sweet and bitter taste receptors (expressed in HEK-293 cells) and sensory taste intensities were evaluated. Sweetness was enhanced in limited cases at the taste receptor level. Several monosaccharides reduced the bitter taste receptor activity triggered by acesulfame K or saccharin. The sweetness of acesulfame K and saccharin combined with any of the six sweeteners was perceptually enhanced, correlating with a reduction in their inherent bitterness. This finding suggested that sweetness perception likely increased because of the ability of monosaccharides to diminish bitter receptor activation by high-potency sweeteners. © 2024, The Authors. All rights reserved.

关键词： Binary mixtures

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