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Electronic and Electrical engineering and Intelligent System (ICE3IS), International Conference on

作者： Yudhi Ardiyanto Kusworo Adi Kurnianingsih Karisma Trinanda Putra Pradityo Utomo Doctoral Program of Information System School of Postgraduate Studies Universitas Diponegoro Semarang Indonesia Department of Electrical Engineering Faculty of Engineering Universitas Muhammadiyah Yogyakarta Yogyakarta Indonesia Department of Physics Faculty of Science and Mathematics Universitas Diponegoro Semarang Indonesia Department of Electrical Engineering Faculty of Engineering Politeknik Negeri Semarang Semarang Indonesia Department of Informatics Management Faculty of Engineering Universitas Merdeka Madiun Madiun Indonesia

ISBN: (纸本)9781665465427

The decline in physical, cognitive, and sensory functions for most elderly people leads to the development of several health issues such as memory loss, a tendency to fall, dizziness, and reduced ability to care for oneself independently. These can be mitigated using devices designed to monitor vital signs and human activity such as a smart band. However, the application of a smart band is characterized by a disadvantage which involves storing user data in the vendor's cloud and only one device can access the client applications. Therefore, nurses, doctors, and family members cannot simultaneously analyze data and receive alerts when abnormal conditions occur in elderly patients. This study aims to develop a system capable of monitoring the health conditions of multiple elderly individuals and sending alerts during abnormal conditions based on the heart rate value read by the smart band sensor. The process involved installing a database on the Raspberry Pi to store data while a monitoring system was built on the Node-RED platform to display elderly health data and made it accessible locally. The detection of an abnormal heart rate condition in the elderly patient leads the system to send notifications via telegram to multiple receivers registered in the system using their telegram identity.

关键词： Heart rate Electrical engineering Cloud computing Databases Medical services Receivers Older adults

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Digital Technology in Health Education Trend Mapping through Bibliometrics Analysis

Digital Technology in Health Education Trend Mapping through...

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International Conference on informatics, Multimedia, Cyber and Information System (ICIMCIS)

作者： Fairuz Iqbal Maulana Dian Lestari Vandha Pradwiyasma Widartha Nirwana Haidar Wahyu Dirgantara Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Faculty of Medicine Airlangga University Surabaya Indonesia Information System of Industrial Engineering Faculty Telkom University Bandung Indonesia Informatics Engineering Study Program University of Madura Pamekasan Indonesia Department of Electrical Engineering University of Merdeka Malang Malang Indonesia

ISBN: (纸本)9781665473286

This study examines the mapping of research data on digital technology in the field of health education using bibliometric analysis method. Data was collected by identifying keywords in the Scopus database and sorting them out to sort the studies from the last 10 years (2012–2021). Through this step, a total of 1482 documents were obtained (articles, journals, proceedings, books, and others). The data is then processed using the VOSViewer instrument to obtain a visualization of the mapping analysis. This study also analyzes the network types of authors and co-authors through the VOSViewer instrument. The result of this study indicates that the most document types published within ten years are Articles (66.5%), Review (22.9 % ), Conference Paper (4.2 % ), and others. The most studied subjects are Medicine (55.7%), Nursing (9.0%), Health Professions (8.2%), Social Sciences (7.8%), engineering (3.9%), Computer Science (2.6 % ), Environmental Science (2.6 % ), Biochemistry-Genetics and Molecular Biology (2.2%), Psychology (1.6%), and Dentistry (1.3%). This study offers a written communication process and the nature and direction of developing descriptive means of counting and analyzing the various phases of communication as well as recognizing the authorship and direction of its symptoms in documents on the subject of digital technology in the health sector.

关键词： Training Pediatrics Instruments Education Bibliometrics Transportation Psychology

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E-tourism application development to support integrated and disaster-safe tourism villages in Kerambitan District, Tabanan

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AIP Conference Proceedings 2024年第1期2961卷

作者： I. GD Yudha Partama I. Dewa Gede Agung Pandawana Dewa Gede Agung Gana Kumara Regional Planning and Environmental Management Study Program Universitas Mahasaraswati Denpasar Denpasar Indonesia Informatics Engineering Study Program Fcaulty of Engineering Universitas Mahasaraswati Denpasar Denpasar Indonesia English Language Education Study Program Faculty of Teacher Training and Education Universitas Mahasaraswati Denpasar Denpasar Indonesia

Kerambitan District is one of the pioneers of tourism that has contributed to raising the name of Bali in the international community. However, so far the planning and implementation of tourism activities have not accommodated the integrated tourism aspects and disaster-safe tourism services. In fact, most tourist destinations in Kerambitan are dominated by natural tourism with hilly contours, which are included in areas prone to extreme weather disasters and areas prone to flooding and landslides during high-intensity rainfall. This study aims to build an early warning system based on digital application, to help create a disaster-safe tourist village. The Waterfall Method is used in development process. This application is Android-based, and integrating the Google Firebase Cloud Messaging feature for sending messages and notifications to various Android devices. The results of this study are an SIGADis E-tourism application, which in addition to display and promote tourist location information in Kerambitan, also has safe and disaster-responsive features including the early warning system feature through messages and notifications, information list of disasters that have occurred, disaster’s distribution map and the weather information each tourist location that combined with Balinese lunar calendar (Sasih). Based on the application testing results using BlackBox Testing and Beta Testing methods, the application has been running according to the desired function, able to provide information about tourism village in Kerambitam, also provide disaster messages and notifications to various android devices, and able to display disaster distribution maps and suggestions related to the disasters when bad weather or events occur.

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Airplane type identification based on mask RCNN;An approach to reduce airport traffic congestion

arXiv

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arXiv 2021年

作者： Al-Shaibani, Waleed Tawfik Abdullah Helvaci, Mustafa Shayea, Ibraheem Azizan, Azızul Department of Electrical and Electronics Engineering Istanbul Technical University Istanbul Turkey Institute of Informatics Satellite Communication and Remote Sensing Program Istanbul Technical University Istanbul Turkey Department of Telecommunication and electronics Engineering Istanbul Technical University Istanbul Turkey Advanced Informatics Department Razak Faculty of Technology and Informatics Universiti Teknologi Malaysia Kuala Lumpur Malaysia

One of the most difficult jobs in remote sensing is dealing with traffic bottlenecks at airports. This fact has been confirmed by several studies attempting to resolve this issue. Among a wide range of approaches employed, the most successful methods have been based on airplane object recognition using satellite images as datasets for deep learning models. Airplane object identification is not a viable method for resolving traffic congestion. There are several types of airplanes at the airport, each with its own set of requirements and specifications. Utilising satellite pictures will require the use of complex equipment, which is a financial burden. In this work, a universal, low-cost and efficient solution for airport traffic congestion is proposed. Drone-captured aerial pictures are used to train and assess a Mask Region Convolution Neural Network model. This model can detect the presence of any aircraft in a photograph and pinpoint its location. It also includes mask estimations to properly identify each detected airplane type based on the estimated surface area and cabin length, which are crucial variables in distinguishing planes. The study is conducted using Microsoft's Common Object in Context (COCO) metrics, average accuracies and a confusion matrix, all of which demonstrate the approach's potential in providing valuable aid for dealing with traffic congestion at airports. Copyright © 2021, The Authors. All rights reserved.

关键词： Aircraft

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Drone Application Model for Image Acquisition of Plantation Areas and Oil Palm Trees Counting 7

Drone Application Model for Image Acquisition of Plantation ...

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7th International Conference on Information Management and Technology, ICIMTech 2022

作者： Sastrohartono, Hermantoro Suryotomo, Andiko Putro Saifullah, Shoffan Suparyanto, Teddy Perbangsa, Anzaludin Samsinga Pardamean, Bens Instiper Yogyakarta Faculty of Agricultural Technology Department of Agricultural Engineering Yogyakarta55281 Indonesia Universitas Pembangunan Nasional Veteran Yogyakarta Department of Informatics Yogyakarta55283 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia BINUS Graduate Program - Master of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (数字)9781665450904

ISBN: (纸本)9781665450904

The area of oil palm plantations in Indonesia increased by 7% from 14 million ha in 2017 to 15 million ha in 2021. The vast land requires the support of effective and efficient management techniques to maintain sustainable productivity. The high-performance computing technologies, Internet of Things (IoT), Big Data, Artificial Intelligence, spatial modeling, and drones are the answers to these needs. This study aims to design an application that can obtain plantation image data and analyze the calculation of the number of oil palm trees. The image of oil palm plantations is obtained from processing photo data from drones through a mosaic and composite process. This study also employed Scrum and UML as a system model development method. The image of the oil palm plantation area is used to build a tree counting model using the Viola-Jones algorithm. The oil palm tree count information generated by this system can then be used by management for fertilizing, harvesting, and monitoring the condition of oil palm trees. © 2022 IEEE.

关键词： Drones

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Role of simulation models in understanding the generation of behavior in C. elegans

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Current Opinion in Systems Biology 2019年 13卷 93-101页

作者： Izquierdo, Eduardo J. Cognitive Science Program School of Informatics Computing and Engineering Indiana University United States

There has been a proliferation of studies using simulation models to achieve a system-level understanding of behavior in Caenorhabditis elegans. Here I discuss the different aims of these modeling approaches and review examples of each in the context of locomotion and spatial navigation in the worm. I argue that as the focus shifts from understanding sensorimotor transformations to understanding neuromechanical instantiations for how behaviors are generated, simulation models will become a more integral part of the experiment–theory cycle. I discuss the insights that simulation modeling provides that complement information obtained from experimental discovery methods. © 2018 Elsevier Ltd

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Anterior Cruciate Ligament Classification in Knee MRI using Automated Pseudo-Masking

Anterior Cruciate Ligament Classification in Knee MRI using ...

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Medical Imaging 2023: Computer-Aided Diagnosis

作者： Dadsetan, Saba Albers, Marcio Weinstock, Allison Musahl, Volker Kitamura, Gene Arefan, Dooman Wu, Shandong Intelligent Systems Program School of Computing and Information University of Pittsburgh PittsburghPA15213 United States Department of Radiology School of Medicine University of Pittsburgh PittsburghPA15213 United States Department of Biomedical Informatics School of Medicine University of Pittsburgh PittsburghPA15213 United States Department of Bioengineering School of Engineering University of Pittsburgh PittsburghPA15213 United States Department of Orthopedic Surgery School of Medicine University of Pittsburgh PittsburghPA15213 United States Department of Radiology Loma Linda University Medical Center Loma LindaCA92354 United States

ISBN: (纸本)9781510660359

Anterior cruciate ligament (ACL) is one of the most common injuries associated with sports. Knee osseous morphology can play a role in increased knee instability. Our hypothesis is that the morphological features of the knee, as seen in knee osseous morphology, can contribute to increased knee instability and, thus, increase the likelihood of ACL tear. To test this relationship, it is necessary to segment the femur and tibia bones and extract relevant imaging features. However, manual annotation of 3D medical images, such as on magnetic resonance imaging (MRI) scans, can be a time-consuming and challenging task. In this work, we propose an automated pipeline for creating pseudo-masks of the femur and tibia bones in knee MRI. Our approach involves unsupervised segmentation and deep learning models to classify ACL integrity (intact or torn). Our results demonstrate a high agreement between the automated pseudo-masks and a radiologist's manual segmentation, which also leads to comparable AUC values for the ACL integrity classification. © 2023 SPIE.

关键词： Magnetic resonance imaging

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Empowering Biomedical Discovery with AI Agents

arXiv

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arXiv 2024年

作者： Gao, Shanghua Fang, Ada Huang, Yepeng Giunchiglia, Valentina Noori, Ayush Schwarz, Jonathan Richard Ektefaie, Yasha Kondic, Jovana Zitnik, Marinka Department of Biomedical Informatics Harvard Medical School BostonMA United States Department of Chemistry and Chemical Biology Harvard University CambridgeMA United States Program in Biological and Biomedical Sciences Harvard Medical School BostonMA United States Department of Brain Sciences Imperial College London London United Kingdom Harvard College CambridgeMA United States Program in Biomedical Informatics Harvard Medical School BostonMA United States Department of Electrical Engineering and Computer Science MIT CambridgeMA United States Kempner Institute for the Study of Natural and Artificial Intelligence Harvard University MA United States Broad Institute of MIT and Harvard CambridgeMA United States Harvard Data Science Initiative CambridgeMA United States

We envision "AI scientists" as systems capable of skeptical learning and reasoning that empower biomedical research through collaborative agents that integrate AI models and biomedical tools with experimental platforms. Rather than taking humans out of the discovery process, biomedical AI agents combine human creativity and expertise with AI’s ability to analyze large datasets, navigate hypothesis spaces, and execute repetitive tasks. AI agents are poised to be proficient in various tasks, planning discovery workflows and performing self-assessment to identify and mitigate gaps in their knowledge. These agents use large language models and generative models to feature structured memory for continual learning and use machine learning tools to incorporate scientific knowledge, biological principles, and theories. AI agents can impact areas ranging from virtual cell simulation, programmable control of phenotypes, and the design of cellular circuits to developing new therapies. © 2024, CC BY.

关键词： Adversarial machine learning

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Dynamic programming Algorithm using Furniture Industry 0/1 Knapsack Problem 5

Dynamic Programming Algorithm using Furniture Industry 0/1 K...

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5th International Conference on Cybernetics and Intelligent Systems, ICORIS 2023

作者： Anditta, Mietha Amartya, Natashya Warnars, Laurens Spits Warnars, Harco Leslie Hendric Spits Ramadhan, Arief Siswanto, Teddy Mantoro, Teddy Noordin, Nurulhuda Bina Nusantara University School of Computer Science Computer Science Departement Jakarta11530 Indonesia Bina Nusantara University School of Information Systems Information Systems Departement Jakarta11530 Indonesia Bina Nusantara University Binus Graduate Program - Computer Science Computer Science Departement Jakarta11530 Indonesia Telkom University Pjj Informatika Bandung40257 Indonesia Trisakti University Information Systems Department Jakarta11440 Indonesia Sampoerna University Faculty of Engineering and Technology Jakarta12760 Indonesia Universiti Teknologi Mara School of Computing Sciences College of Computing Informatics and Mathematics Selangor Malaysia

ISBN: (纸本)9798350369489

Dynamic programming is a fundamental algorithm that can be found in our daily lives easily. One of the dynamic programming algorithm implementations consists of solving the 0/1 knapsack problem. A 0/1 knapsack problem can be seen from industrial production cost. It is prevalent that a production cost has to be as efficient as possible, but the expectation is to get the proceeds of the products higher. Thus, the dynamic programming algorithm can be implemented to solve the diverse knapsack problem, one of which is the 0/1 knapsack problem, which would be the main focus of this paper. The implementation was implemented using C language. This paper was created as an early implementation algorithm using a Dynamic program algorithm applied to an Automatic Identification System (AIS) dataset. © 2023 IEEE.

关键词： Dynamic programming

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The Application of Conjugate Gradient Method to Motion Control of Robotic Manipulators

The Application of Conjugate Gradient Method to Motion Contr...

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Innovative Manufacturing, Mechatronics and Materials Forum, iM3F 2021

作者： Sulaiman, Ibrahim M. Malik, Maulana Giyarti, Wed Mamat, Mustafa Ibrahim, Mohd Asrul Hery Ahmad, Muhammad Zaini School of Quantitative Sciences Universiti Utara Malaysia Kedah Sintok06010 Malaysia Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Terengganu Kuala Terennganu21300 Malaysia Department of Mathematics Universitas Indonesia Depok Indonesia Mathematics Education Study Program Universitas Islam Negeri Sunan Kalijaga Depok Indonesia Faculty of Entrepreneurship and Business Universiti Malaysia Kelantan Kota Bhar Malaysia Institute of Engineering Mathematics Universiti Malaysia Perlis Kangar Malaysia

ISBN: (纸本)9789811920943

Many industrial and engineering problems are transformed into optimization problems and solved using various numerical based methods. One of the frequently used method is the Steepest descent algorithm which converge to the solution in only one iteration, given the current point and provided the quadratic function is positive definite. However, this method is not suitable for large scale functions because of lack of gradient information and high computational cost. This study aims to suggest a new conjugate gradient algorithm for motion control of robotic manipulators and unconstrained optimization models. The convergence result of the new algorithm would be discussed under some suitable conditions. Computational simulations are carried out on the discrete-time kinematics equation of a two-joint planar robot manipulator to illustrates the efficiency of the algorithm. The algorithm was further extended to unconstrained optimization problems in addition to motion control of robotic manipulators. Preliminary results prove that the new algorithm is efficient compared to the existing CG algorithm. The comparisons are made using the set of 50 standard benchmark functions including number of iterations and CPU time. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Flexible manipulators

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