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International Conference on information Management and technology (ICIMTech)

作者： Diana Wijayanti Satriawansyah Urbaya Taufiq Sitompul Verry Adrian Department of Information Systems BINUS Graduate Program Bina Nusantara University Jakarta Indonesia Country Health Information Systems and Data Use (CHISU) Program USAID Indonesia Jakarta Indonesia Department of Informatics University of Oslo Oslo Norway Computer Science Department Binus Graduate Program – Doctor Computer Science Bina Nusantara University Jakarta Indonesia Center of Data and Information Technology Jakarta Provincial Health Office Jakarta Indonesia

ISBN: (数字)9798350390025

ISBN: (纸本)9798350390032

The process of using ICT to provide services to the public is known as the Indonesian e-Government system, or Sistem Pemerintahan Berbasis Elektronik (SPBE). The e-Government initiative in Jakarta Provincial Health Office involves enhancing collaboration among public health entities for efficient data exchange and streamlined processes, especially between the Provincial and District Health Offices, public hospitals, government clinics, and primary health care centers (Puskesmas). Achieving interoperability requires standardized protocols and a well-defined architectural model to integrate data seamlessly. This study presents a provincial-level architectural model focused on improving electronic health records interoperability, aiming to promote the adoption of the national Fast Healthcare Interoperability Resources (FHIR) health information exchange platform and enhance the integrity of health data in Jakarta. The study methodology involves conducting literature reviews, observations, and discussions with representatives from healthcare facilities to develop the e-Government architecture model and prototype of the infrastructure layer aiming to facilitate the interoperability of Electronic Health Records (EHRs) across 93 healthcare facilities, all of which are part of the SPBE users.

关键词： Prototypes Medical services Data models Security Public healthcare Electronic medical records Interoperability information exchange Standards Electronic government

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The reliability of deep learning models in assessing the shoulder arthroscopic field's visual clarity in relation to bleeding

JSES International

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JSES International 2025年第3期9卷 864-870页

作者： Tran, Son Quang Bui, Minh Cong Nguyen, Dat Tien Itthipanichpong, Thun Limskul, Danaithep Thamrongskulsiri, Napatpong Tanpowpong, Thanathep Clinical Sciences Program Faculty of Medicine Chulalongkorn University Bangkok Thailand Faculty of Medicine Department of Orthopaedics Cantho University of Medicine and Pharmacy Can Tho Viet Nam Faculty of Computer Science University of Information Technology Ho Chi Minh City National University Ho Chi Minh City Viet Nam Sports Medicine Research Group Faculty of Medicine Chulalongkorn University Bangkok Thailand

Background: The clarity of visualization in shoulder arthroscopy is significantly influenced by intraoperative bleeding. This study aims to develop deep learning models to classify the visual clarity of arthroscopic shoulder images and evaluate their reliability compared to rater assessment. Methods: We retrospectively reviewed videos from 113 shoulder arthroscopies, using 63 patients’ videos to create a 3750-image training dataset and 50 patients’ videos to evaluate the reliability and agreement of the trained models. Images extracted from the videos were assessed for visual clarity with a 3-grade scale. Subsequently, we implemented transfer learning techniques for the pretrained deep learning models involving DensetNet169, DenseNet201, Xception, InceptionResNetV2, VGG16, and ViT. The reliability and agreement of the trained predictive models compared with raters in classifying the visual clarity of shoulder arthroscopic images were reported with percent agreement and weighted kappa coefficients. Similarly, for quantifying the visual clarity of surgical videos, the reliability and agreement were evaluated through intraclass coefficients, bias, and limits of agreement. Results: Most models achieved over 90% accuracy in validation step, with InceptionResNetV2, DenseNet169, and ViT exhibiting good percent agreements of 82.3%, 79.2%, and 77.8%, respectively, and their weighted kappa coefficients above 0.8. DenseNet169 model had the highest reliability for evaluating the visual clarity of surgical videos with an intraclass correlation coefficient of 0.9, a bias of 0.027, and the narrowest limits of agreement. Conclusion: The trained DenseNet169 predictive model was reliable enough to be utilized as an objective measure of the visual clarity of the shoulder arthroscopic field for further research. © 2025 The Authors

关键词： Basic Science Study Bleeding Convolutional neural network Deep learning model Grading scale Shoulder arthroscopy Validation of Artificial Intelligence Software Visual clarity Visualization

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Optimation Cavacity Vehicle Routing Problem with K-Nearest Neighbor in Classification of Goods Ditribution Route

Optimation Cavacity Vehicle Routing Problem with K-Nearest N...

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International Conference of computer Science and information technology

作者： Muhammad Syahputra Novelan Syahril Efendi Poltak Sihombing Herman Mawengkang Doctoral Program of Computer Science Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Department of Computer Science Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Department of Mathematics Faculty of Mathematics and Natural Sciences Universitas Sumatera Utara Medan Indonesia

Industrial and distribution service problems that belong to combinatorial optimization include vehicle routing with Vehicle Routing Problem. This research builds a framework and implements it in a multi-class optimization model to reduce overfitting and misclassification results caused by unbalanced multiclassification in the influence of the number of ‘nodes’ on vehicle routes with machine learning. The problem of imbalance in vehicle route classification has been a challenge in the classification process and attracted the attention of a number of researchers. The purpose of the model in general is to gain an understanding of the mechanism in the problem so as to classify the imbalanced vehicle route data based on JNE delivery routes. The solution method that will be used by applying k-nearest neighbor to determine the amount of carrying capacity of the goods will then determine the delivery location point with the vehicle routing problem. So that this model can be a model in determining vehicle routes based on the capacity limit of the number of shipments of goods.

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Preliminary Evaluation of Kyokko for Inter-FPGA Communication Framework CIRCUS

Preliminary Evaluation of Kyokko for Inter-FPGA Communicatio...

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IEEE International Conference on Cluster Computing Workshops and Posters (CLUSTER WORKSHOPS)

作者： Kaito Kitazume Norihisa Fujita Ryohei Kobayashi Taisuke Boku Master's Program in Computer Science Degree Programs in Systems and Information Engineering Graduate School of Science and Technology University of Tsukuba Center for Computational Sciences University of Tsukuba

In recent years, Field-programmable Gate Arrays (FPGAs) are gaining attention as computational acceleration devices in the field of high-performance computing. By implementing specialized circuits that can be customiz... 详细信息

ISBN: (数字)9798350383454

ISBN: (纸本)9798350383461

关键词： Conferences High performance computing Circuits Cluster computing Low latency communication Field programmable gate arrays

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Robust Object Detection Model for UAV Application

Robust Object Detection Model for UAV Application

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International Automatic Control Conference

作者： Chun Ku Xiu-Zhi Chen Yen-Lin Chen Master Program in Artificial Intelligence Technology National Taipei University of Technology Taipei Taiwan Department of Computer Science and Information Engineering National Taipei University of Technology Taipei Taiwan

Not only common issues on object detection task need to be deal with, for Unmanned Aerial Vehicle (UAV) applications, small object is one of the critical problems that needs to be solved. YOLOv7 is a powerful network architecture that provides high efficiency and accuracy object detection results. This paper adopts YOLOv7 as an object detection model for two different kinds of targets, one is vehicle, and the other is ocean flotsam. By training the model with open datasets and fine-tuning the model with self-collected datasets, we prove through sequences collected from real-world scenarios that YOLOv7 is able to provide robust and accurate object detection results, including vehicles and ocean flotsam, with real-time efficiency. Based on such experimental result, we confirmed that YOLOv7 can be the baseline for object detection model development.

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Camera-Only Perception System for Traffic Jam Assistance

Camera-Only Perception System for Traffic Jam Assistance

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International Automatic Control Conference

作者： Xiao-Wei Huang Xiu-Zhi Chen Yen-Lin Chen Master Program in Artificial Intelligence Technology National Taipei University of Technology Taipei Taiwan Department of Computer Science and Information Engineering National Taipei University of Technology Taipei Taiwan

Traditional perception systems for TJA (Traffic Jam Assistance) are mostly implemented by fusing images with radar or lidar. As computer vision techniques become more powerful, cameras can almost replace the need for radar and lidar in perception tasks, which reduces the hardware cost of the system. In this research, we propose a camera-only perception system for TJA, which is able to provide the information of the vehicles ahead and the drivable area. The proposed system has been evaluated through real-world scenario sequences, and proved that it achieves high robustness, which is highly possible to be adopted for TJA development.

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Efficient Automatic External Defibrillator Using the Slope of Hilbert Transformed ECG Signals 11

Efficient Automatic External Defibrillator Using the Slope o...

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11th International Japan-Africa Conference on Electronics, Communications, and Computations, JAC-ECC 2023

作者： Elsagheer, Samir A. Sayed, Mohammed S. Hassan, Mohsen A. Egypt-Japan University of Science and Technology Computer Science and Information Technology Alexandria21934 Egypt Aswan Universty Facurlty of Engineering Aswan Egypt Egypt-Japan University of Science and Technology Department of Electronics and Communications Engineering Alexandria21934 Egypt Zagazig University Department of Electronics and Communications Engineering Zagazig Egypt Egypt-Japan University of Science and Technology Materials science and engineering program IDE Alexandria21934 Egypt

ISBN: (纸本)9798350369328

Sudden cardiac arrest (SCA) is a life-threatening condition that demands immediate intervention. The key to survival often lies in the timely and precise analysis of electrocardiogram (ECG) signals to determine the necessity of a shock from an Automatic External Defibrillator (AED). In this paper, we address the critical need for improved accuracy in AED decision-making by presenting a novel approach that leverages the Hilbert Transform to calculate the slope of ECG signals by harnessing the analytical power of Hilbert Transformed ECG signals. By scrutinizing the heart's electrical activity through this method, we aim to enhance the AED's ability to differentiate between cases of ventricular fibrillation and other non-shockable rhythms, ultimately leading to more efficient and effective treatment. Our research explores two distinct approaches for signal analysis and correlates their findings to achieve higher precision in defibrillation decisions. To validate the effectiveness of our approach, we employ a diverse and publicly available dataset containing various heart conditions, allowing us to demonstrate the robustness of our method across a wide spectrum of cases. This study represents a significant advancement in the field of automatic external defibrillation, with the potential to save countless lives through more accurate and timely interventions. © 2023 IEEE.

关键词： Defibrillators

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Mapping the Scientific Landscape of Integrated Scheduling Towards Industry 5.0 with A Bibliometric Analysis

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Procedia computer Science 2025年 253卷 84-93页

作者： Anak Agung Ayu Putri Ardyanti Zhiqiang Xie Andrea Stevens Karnyoto Bens Pardamean Ni Made Estiyanti School of Computer Science and Technology Harbin University of Science and Technology Harbin 150000 China Faculty of Information Technology and Design Primakara University Bali 80226 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Doctoral School of Management and Business University of Debrecen Debrecen Hungary

The industry is rapidly transitioning from the 4.0 era to the 5.0 era, prompting renewed interest among scholars in scheduling problems. They allow operations to process and assemble various components simultaneously. This bibliometric analysis provides a comprehensive understanding of the diverse research perspectives on the potential challenges of integrated scheduling within the framework. We identified 357 Scopus articles and analysed co-occurrence keyword (CNK) by VOSViewer tools and Global Citation Score (GCS) by Scopus tools. The research data obtained from 1993 to 2023 mainly in the subject areas of Engineering, computer Science, Maths, and others. CNK identified six cluster keywords, and nine most cited articles based on normalised GCS. These results contribute to our understanding of the development of scheduling algorithms, shifting from an emphasis on manufacturing transfers to contemporary demand-centric research directions. Furthermore, this research provides a valuable perspective for policymakers, plant personnel, and manufacturing managers to make informed decisions.

关键词： integrated scheduling assembly job shop scheduling heuristic algorithm genetic algorithm bibliometric analysis

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Automatic Identification and Reconstruction 3D Image of the Rhinosinusitis Mucus

Automatic Identification and Reconstruction 3D Image of the ...

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International Conference of information and Communication technology (ICoICT)

作者： Ondra Eka Putra Sumijan Muhammad Tajuddin Department of Informatics Technology Faculty of Computer Science Universitas Putra Indonesia YPTK Padang Padang Indonesia Doctoral Program in Information Technology Universitas Putra Indonesia YPTK Padang Padang Indonesia Department of Computer Science Bumigora University Mataram Indonesia

ISBN: (数字)9798350363432

ISBN: (纸本)9798350363449

Rhinosinusitis Mucus is mucus produced by mucus glands found in the nose in the paranasal sinus area which indicates inflammation. Segmentation of rhinosinusitis mucus is very difficult to do because of the many characteristics of different objects in the image of the paranasal Sinus CT-Scan in separating the mucus object with its background before the extraction process. The purpose of this study was to accurately identify and measure the mucus area of rhinosinusitis from CT-scan images of rhinosinusitis patients. The test data used in this study is secondary data from CT-Scan of paranasal sinus sagittal view in radiology RSUP M. Djamil Padang, Padang City, West Sumatra, Indonesia, using the Philips Ingenuity CT CT-Scan model type MRC880 numbered Tube series 163889. The segmentation process is carried out to obtain the optimal multi threshold value from each slice of the test image using the Improved Adaptive Multi Threshold (IAMT) segmentation method which produces a binary image to separate the mucus object with its background before the extraction process. Furthermore, the results of IAMT are applied to the identification and extraction model automatically to obtain the area of the rhinosinusitis mucus object. The extraction results were used for 2D to 3D image reconstruction in calculating the volume of rhinosinusitis mucus objects. The test results showed that the smallest area of rhinosinusitis mucus was 0.516 cm 2 and the largest was 1.807 cm 2 , and the average volume was 0.95 cm 3 with Accuracy is 96,5%. The identified areas and volumes indicate inflammation in the area of the paranasal sinuses and require treatment. Thus, this study can help doctors in making the right decision to take further medical action.

关键词： Image segmentation Visualization Adaptation models Three-dimensional displays Computed tomography Urban areas Nose Radiology Object recognition Image reconstruction

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A Study of Enhancing Computational Thinking Skills through STEAM Robotics Activities 2

A Study of Enhancing Computational Thinking Skills through S...

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2nd International Annual Meeting on STEM Education, IAMSTEM 2019

作者： Phadung, Muneeroh Yokkhun, Atcharaporn Persoh, Sulaiman Computer Education Program Faculty of Science Technology and Agriculture Yala Rajabhat University Yala95000 Thailand Information Technology Program Faculty of Science Technology and Agriculture Yala Rajabhat University Yala95000 Thailand Computer Science Program Faculty of Science Technology and Agriculture Yala Rajabhat University Yala95000 Thailand

STEAM robotics activities are designed to be an enhancement on students' computational thinking skills, which are claimed to be essential for the 21st century. The aims of this study were to examine the learning outcomes of secondary students' computational thinking skills through the use of STEAM robotics activities, and to investigate the students' satisfaction after the implementation of STEAM robotics activities. A quasi-experimental research design was deployed in this study. The research participants were 37 eleventh-grade students of Private Islamic Schools in Yala province, Thailand. A quiz with pre- and post-test and satisfaction questionnaires were employed as data. Descriptive statistics - including mean, standard deviation and a pair sample t-test - was used to analyse the collected data. The findings were that students' learning outcomes indicated a significant improvement in their computational skills after the use of STEAM robotics activities as compared with before, with the statistical level of significance of 0.05. In response to the second research question, the overall satisfaction of the students after the use of such STEAM robotics activities was high (mean=4.01;SD=0.54). © Published under licence by IOP Publishing Ltd.

关键词： Robotics

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