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6th International Conference on Biomedical and Health informatics, ICBHI 2024

作者： Hung, Wen-Kai Sun, Ming-Hsuan Lu, Chi-Jen Chen, Yu-Xian Lin, Yue-Der Master’s Program in the Department of Automatic Control Engineering Feng Chia University Taichung40724 Taiwan Master’s Program of Biomedical Informatics and Biomedical Engineering Feng Chia University Taichung40724 Taiwan

ISBN: (纸本)9783031863226

Cardiovascular diseases (CVD) are one of the major global health threats, causing millions of deaths each year. According to data from the World Health Organization, over 500 million people are affected by cardiovascular diseases, resulting in over 20 million deaths in 2021 alone, accounting for about one-third of the total global deaths. Invasive blood pressure measurement methods not only cause discomfort to patients but also pose a risk of infection. Meanwhile, cuffless cuff-based methods cannot provide continuous monitoring. Therefore, the purpose of this study is to develop a cuffless continuous blood pressure measurement system based on photoplethysmography (PPG). By using waveform measurement technology, we aim to provide a more comfortable and safer method for blood pressure monitoring, thereby enhancing the management of cardiovascular diseases. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Blood pressure

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Beyond the Scroll: Eye-Tracking Evaluations on the National Gallery of Indonesia’s Instagram 26th

Beyond the Scroll: Eye-Tracking Evaluations on the National ...

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26th International Conference on Asia-Pacific Digital Libraries, ICADL 2024

作者： Sari, Desy Novita Prameswari, Clarissa Rahmi Anshori, Isa Master’s Program in Library Science Universitas Indonesia Kota Depok Indonesia Department of Library and Information Sciences Universitas Indonesia Kota Depok Indonesia Biomedical Engineering Department School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia National Gallery of Indonesia Central Jakarta Indonesia

ISBN: (纸本)9789819608676

Eye-tracking studies focused on art galleries and museums within the realm of Instagram, especially in the Indonesian context, are notably scant. This investigation elucidates the user interaction and experience of the art gallery’s Instagram account, @galerinasional. Employing a quantitative approach, we implemented eye-tracking experiments using the well-known online eye-tracking software RealEye. The study participants were followers of the National Gallery of Indonesia’s (Galnas) Instagram profile, seven women and three men, in two age brackets: 18–24 years (n = 5) and 25–34 years (n = 5). The experimental protocol required participants to execute five tasks centered on locating exhibition details and artwork on the Galnas Instagram platform, with a duration of 100 s allocated to each task. The Participant Quality Grade (PQG), examination duration, optimal browser dimensionality, K-factor mean, gaze and fixation frequencies, and heat maps were determined for the participants. The key findings are as follows. (1) The participants’ PQG scores were predominantly between 4 and 6. (2) Investigative browsing typically exceeded the 100-s limit. (3) The consensus on the ideal browser dimensions hovered around 1,368.6 × 814.8 px. (4) The K-factor mean across participants tended toward K > 0. (5) The average gaze occurrence was 27 items per second for most participants. (6) A noticeable disparity in fixation counts was observed between the two age groups, with individuals aged 25–34 demonstrating prolonged engagement with Galnas’ content. (7) Heat maps accentuated a pronounced concentration on visual content, encompassing photographs, videos, and their associated captions. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Economic and social effects

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Evaluating the Impact of Data Cleaning for Improving Road Damage Detection Through Vision Transformer

Evaluating the Impact of Data Cleaning for Improving Road Da...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Andy Desman Kahlil Muchtar Maulisa Oktiana Maya Fitria Yuwaldi Away Fardian Fardian Hammam Riza Dept. of Electrical and Computer Engineering Universitas Syiah Kuala Banda Aceh Indonesia Dept. of Electrical and Computer Engineering Department of Informatics Universitas Syiah Kuala The Master Program in Artificial Intelligence Universitas Syiah Kuala (USK) Banda Aceh Indonesia Department of Informatics BRIN (National Research and Innovation Agency) Indonesia The Master Program in Artificial Intelligence Universitas Syiah Kuala Banda Aceh Indonesia

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

The WHO predicts that by 2030 road accidents will be the 5th leading cause of death. Globally, road accidents account for 1.25 million casualties each year, and road defects cause 34% of these casualties. The road survey process in many countries have several challenges, one of which is detection using cameras that do not have a recognition system. In this study, a model with YOLOS architecture based on Vision Transformer trained on the RDD2022 dataset successfully recognizes road damage well, as indicated by the number of objects detected, bounding box on accurate objects, and the ability to recognize objects with inconsistent shadow and light inference. This research uses assessment parameters such as Average Precision (AP) and Average Recall (AR) to determine the overall performance of the model. The model achieves the highest AP value at Intersection of Union (IoU) 0.5, 0.75, and 0.5-0.95, worth 62.1%, 37.1%, and 36.2% respectively, and the highest AR value in Large, Medium, and Small Areas, worth 42.1%, 60.3%, and 75.4% respectively. The supplementary material can be found through this link: https://***/watch?v=LzkI2e_IORE.

关键词： YOLO Surveys Computer vision Road accidents Roads Manuals Transformers Cameras Cleaning Tuning

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A Reconfigurable Compute-In-Memory Design with Adaptive Bit-Precision and Power Adjustment

A Reconfigurable Compute-In-Memory Design with Adaptive Bit-...

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Consumer Technology (ICCT-Pacific), International Conference on

作者： I-Chieh Hsu Chun-Fu Chen Dao-Long Huang Yun-Kai Yeh Wei-Chieh Lee Qi-Hua Lin Jinjia Zhou I-Chyn Wey Electrical Engineering Department College of Engineering Chang-Gung University Taiwan School of Electrical Engineering National Taiwan University of Science and Technology Taiwan Master Program in Nano-Electronic Engineering and Design Chang Gung University Taiwan Department of Applied Informatics Faculty of Science and Engineering Hosei University Japan

ISBN: (数字)9798331504120

ISBN: (纸本)9798331504137

With the successful development of artificial intelligence (AI), Convolutional Neural Networks (CNNs) occupy a large amount of computing time and power consumption in the entire AI computing process. However, in traditional von Neumann architectures, the separation of the computing element and memory leads to the memory-wall problem of memory data transmission bandwidth from memory to processing element when executing multiply-accumulate-based CNN operations. The data transmission time and power consumption all are much higher than the CNN computing part. Therefore, this paper proposes a memory-in-computation design that can flexibly adjust energy usage, achieve high energy efficiency, and support multiple operation frequencies. By controlling the switches of each memory row, unnecessary energy consumption is avoided, leading to a reduction in total power consumption by 15% to 60%. Additionally, by adjusting the pulse width, the charging power consumption of capacitors is reduced by 65% per charge cycle.

关键词： Energy consumption Power demand Capacitors Bandwidth In-memory computing Control systems Energy efficiency Convolutional neural networks Data communication Artificial intelligence

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Supply Chain Sustainability in Disruption: SC Intelligence, Customer Knowledge Transfer, and the Mediating Role of IS/IT

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IEEE engineering Management Review 2025年

作者： Ratna, Silvia Saide, Saide Rater, Salya Svyazhanovna, Baizakova Saule Herzavina, Herzavina Faculty of Information Technology Department of Informatics Engineering and Department of Information Systems Banjarmasin Indonesia State Islamic University of Sultan Syarif Kasim Riau Universitas Islam Negeri Sultan Syarif Kasim Riau-UIN SUSKA Riau Department of Information Systems Faculty of Science and Technology Indonesia PRO Knowledge Indonesia Pekanbaru Indonesia Universitas Pahlawan Tuanku Tambusai Indonesia Lembaga Enreach UIN Suska Riau Indonesia Politeknik Aceh Selatan Department of Informatics Engineering Aceh Indonesia Information Communication Technologies Robotics in Arkalyk Pedagogical Institute Master of Natural Sciences Educational Program for the Informatics Computer Science Kazakhstan Universitas Pahlawan Tuanku Tambusai Department of Informatics Engineering Indonesia National Taiwan University of Science and Technology Taiwan

Knowledge resource and information system/technology (IS/IT) capability have been considered to improve firm performance, however there is still a gap regarding the sustainability of supply chain to face and recover from disruption (e.g., COVID-19). Questionnaire-based surveys was adopted and received feedback from sixty (160) Indonesian companies or about 28.07% of response rate. © 1973-2011 IEEE.

关键词： customer knowledge transfer disruption information system/technology (IS/IT) responding knowledge management resource-based view (RBV) Supply chain (SC) sustainability supply chain knowledge transfer

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A computationally efficient algorithm for estimating respiratory rate from seismocardiogram

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Biomedical Signal Processing and Control 2025年 109卷

作者： Ku, Tienhsiung Lin, Yue-Der Department of Anesthesiology Changhua Christian Hospital Changhua50051 Taiwan Artificial Intelligence Development Center Changhua Christian Hospital Changhua50051 Taiwan Department of Automatic Control Engineering Feng Chia University Taichung40724 Taiwan Master's Program of Biomedical Informatics and Biomedical Engineering Feng Chia University Taichung40724 Taiwan

Respiratory rate (RR) monitoring is crucial in clinical and healthcare settings. With advancements in microelectromechanical system (MEMS) technology, monitoring respiration using seismocardiogram (SCG) has emerged as a promising approach. This study presents a computationally efficient algorithm for estimating RR from SCG signal. The proposed algorithm consists of two primary steps: first, applying Gaussian averaging filter for pre-processing, followed by computing the averaged spectrum from the scalogram based on complex Morlet wavelet within the specified frequency range. RR is then estimated from the dominant frequency that appears in the averaged spectrum. This study also establishes the analytical relationship between the parameters of Gaussian averaging filter and the sampling frequency of SCG signal, which serves as the design criterion for pre-processing filter. The proposed algorithm undergoes testing on two SCG datasets and demonstrates its feasibility for estimating RR from SCG signal. The algorithm is also tested on both finger and wrist PPG datasets for RR estimation. The test results present high agreement between the RR estimations from SCG (or PPG) signal and those from respiration signal. Furthermore, an experiment using the dataset collected with a magnetic field-based respiration sensor during pulmonary rehabilitation is conducted to validate the algorithm's robustness against motion artifacts. Based on the testing results, the proposed algorithm shows significant potential in clinical and healthcare applications. © 2025 Elsevier Ltd

关键词： Gaussian distribution

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Fish Freshness Identification Using Machine Learning: Performance Comparison of k-NN and Naïve Bayes Classifier

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Journal of Computing Science and engineering 2022年第3期16卷 153-164页

作者： Yudhana, Anton Umar, Rusydi Saputra, Sabarudin Department of Electrical Engineering Universitas Ahmad Dahlan Yogyakarta Indonesia Master Program of Informatics Universitas Ahmad Dahlan Yogyakarta Indonesia

Fish is one of the food sources that should be examined for freshness before being consumed. The consumption of rotten fish can cause various diseases. The rotten fish have changed color on the gills, skin, flesh, and eyes and have a pungent odour. Fish freshness can be assessed using a variety of conventional methods, but these methods have limitations, such as requiring relatively expensive equipment, trained personnel and being destructive. The machine learning method is used because it is non-destructive, reduces costs, and is easy to use. This study aims to identify the freshness of fish using k-nearest neighbor (k-NN) and Naïve Bayes (NB) classification methods based on the fish-eye image. The features used in the classification process are RGB and GLCM. The research stages consist of the fish collection process, image acquisition and class division, preprocessing and ROI detection, feature extraction and dataset split, and the classification process. Based on these results, it can be stated that the k-NN method has better performance than NB with average accuracy, precision, recall, specificity, and AUC of 0.97, 0.97, 0.97, 0.97, and 0.97. © 2022. The Korean Institute of Information Scientists and Engineers

关键词： Fish

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Detection of CT - Scan Lungs COVID-19 Image Using Convolutional Neural Network and CLAHE 3

Detection of CT - Scan Lungs COVID-19 Image Using Convolutio...

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3rd International Conference on Information and Communications Technology, ICOIACT 2020

作者： James, Ronaldus Morgan Sunyoto, Andi Universitas Amikom Yogyakarta Master Program of Informatics Engineering Yogyakarta Indonesia

ISBN: (纸本)9781728173566

Detecting COVID-19 is a significant task for medical professionals today because of its rapid spread. To overcome this problem, medical professionals have used various techniques and methods todetect to inhibit the proliferation of COVID-19. CT (Computed Tomography) Scan is currently the best method for detecting COVID-19. This diagnostic method is very accurate because it can see organs in three dimensions. However, this method requires a radiologist to detect the disease and requiresa long time, which means it will cut valuable time for medical practitioners if a patient is sick. Therefore it is necessary to implement a system to detect the coronavirus automatically as an alternative quickly. This study intends to help medical practitioners to detect computed tomography (CT)Scans of lungs infected with COVID-19. The methods to be used are Limited Adaptive histogram equalization (CLAHE) contrast to improve the quality of CT (Computed Tomography) Scan images of COVID-19 lungs and Convolutional Neural Network (CNN) for the image classification process. The dataset usedis 698 RGB images. This study uses three convolutional layers, 3 Max-Pooling layers, and two fully connected layers, resulting in 83.28% accuracy. © 2020 IEEE.

关键词： Coronavirus

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Building a Simple COVID-19 Knowledge Graph in Bahasa Indonesia: A Preliminary Study 3

Building a Simple COVID-19 Knowledge Graph in Bahasa Indones...

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3rd IEEE International Biomedical Instrumentation and Technology Conference, IBITeC 2023

作者： Muharram, Arief Purnama Taufikulhakim, Farhan Hilmi Purwarianti, Ayu Universitas Indonesia Faculty of Medicine Jakarta Indonesia Institut Teknologi Bandung School of Electrical Engineering and Informatics Master Program of Informatics Bandung Indonesia

ISBN: (纸本)9798350302424

COVID-19 is an acute respiratory disease that has become a pandemic worldwide. Many studies have been conducted to enhance our understanding of COVID-19. However, the abundance of information obtained from these studies has resulted in information overload. In this study, we purposed a simple COVID-19 Knowledge Graph in Bahasa Indonesia as a way to reconstruct knowledge to combat this information overload. We used Bahasa Indonesia in our study to explore its potential for constructing a Knowledge Graph (KG). The construction of our KG involved manual curation of medical literatures and annotation of entities and relationships by the domain experts. The KG was implemented using Neo4J version 5. We successfully demonstrated our COVID-19 KG, which consists of 240 nodes and 276 relationships with 15 and 14 node and relationship labels, respectively. Accessing the information within the KG is made effortless through the use of Cypher queries in Neo4J. Further research is still needed to develop the KG into a larger and better one. However, our COVID-19 KG can serve as a basis for further development. © 2023 IEEE.

关键词： COVID-19

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Digital Divide Measurement in Lembata Regency Using SIBIS 2

Digital Divide Measurement in Lembata Regency Using SIBIS

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2nd International Conference on Energy, Environmental and Information System, ICENIS 2017

作者： Gabriel, Cecilia Dai Payon Binti Setyohadi, Djoko Budiyanto Suyoto Informatics Engineering STIMIKOM Stella Maris Sumba Sumba Barat Daya NTT85274 Indonesia Master Program of Informatics Engineering Universitas Atma Jaya Yogyakarta Yogyakarta55281 Indonesia

Along with technological development in Indonesia, digital divide occurs in various regions, which were behind in terms of information on how to use, access and utilize ICT in collecting information from internet. One of the regions is Lembata Regency in East Nusa Tenggara, where digital divide among the people should be measured. The purpose of this study was to determine the level of digital divide among the people of Lembata Regency. To determine the level of digital divide, we used SIBIS GPS (General Population Survey) method, which consisted of several indicators or aspect, i.e. internet usage behavior, internet utilization, and e-government. We also performed two tests, i.e. validity test and reliability test to obtain value of index of digital divide measurement among the people of Lembata Regency. The results of validity test which is processed using SPSS program are categorized valid for each variable indicator and the reliability test results show reliable status. According to the test results on digital discrepancy in Lembata people, the internet usage attitude indicator is categorized low which is 63.1%, the internet usage function indicator is categorized low which is 64%, and the digital discrepancy of e-government indicator is categorized medium which is 40.4%. Therefore, the result of this study because consideration for the government of Lembata Regency in improving ICT services in e-government and in distributing ICT access and ability equally to the people. © 2018 The Authors, published by EDP Sciences.

关键词： Software testing

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