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8th International Conference on Medical and Health informatics, ICMHI 2024

作者： Yi, Chia-Pin Ting, Hsien-Wei Yang, Tzu-Fang Chien, Ting-Ying Department of Computer Science and Engineering Yuan Ze University Taoyuan City Taiwan Department of Neurosurgery Taipei Hospital Ministry of Health and Welfare New Taipei City242 Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan City Taiwan TaiwanInnovation Center for Big Data and Digital Convergence Yuan Ze University Taoyuan City Taiwan

ISBN: (纸本)9798400716874

Alzheimer’s disease (AD) often presents only mild symptoms in its early stages, and as there is no direct diagnostic method currently available, many patients are diagnosed only after the condition has worsened. Considering that magnetic resonance imaging (MRI) can provide key information in the diagnosis of AD, but the condition may go undiagnosed under manual interpretation due to the subtleness of symptoms and the reliance on radiologists to interpret MRI images, this study aimed to develop an automated method for interpreting brain MR images, hoping to screen for potential AD patients. By combining image processing, the U-Net model, YOLOv8 model, various CNN model architectures, and ensemble data statistics, our method was able to identify features related to AD and predict whether a patient has the disease. Our method can process a complete set of MR images and automatically extract important slices for prediction, making it practical for medical applications. Furthermore, we tested the accuracy and reliability of the method with additional datasets. © 2024 Copyright ACM.

关键词： Magnetic resonance imaging

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Security Authentication on the Edge: A Step Further to Defense in Depth for Internet of Battle Things

Security Authentication on the Edge: A Step Further to Defen...

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International Conference on Software Defined Systems (SDS)

作者： Márcio Antônio Lawisch Julio César S. dos Anjos Edison Pignaton de Freitas Institute of Informatics Federal University of Rio Grande do Sul (UFRGS) RS Brazil Federal University of Ceara Campus Itapaje and Graduate Program in Teleinformatics Engineering - PPGETI CE Brazil

ISBN: (数字)9798331518325

ISBN: (纸本)9798331518332

Currently, the demand for the security of network assets in companies grows dramatically because of several factors, including the growth of the attack surface combined with the variety of connection standards and correlated to the emerging Internet of Things (IoT) related devices and services. This reality is also evident regarding nodes connected to military networks, especially Tactical Edge (TE) devices. Due to the wide variety of equipment connected to the networks (from small sensors to powerful radars) and their possible limitations in resources and transmission means, mainly caused by the terrain and operational conditions, these networks called the Internet of Battle Things (IoBT), also face important security challenges. In this context full of many intentional and unintentional security challenges, this work proposes using blockchain technology as a network access security solution within an in-depth defense concept at three levels: hardware, network, and application. Tests for attacks against the network layer resulted in high resistance rates without consuming significant resources.

关键词： Resistance Scalability Authentication Radar equipment Software Blockchains Sensors Security Internet of Things Standards

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Between you and me: A systematic analysis of mutual social interaction in perceptual crossing agents

Between you and me: A systematic analysis of mutual social i...

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Conference on Artificial Life, ALIFE 2023

作者： Severino, Gabriel J. Merritt, Haily Izquierdo, Eduardo J. Cognitive Science Program Indiana University Bloomington United States Program in Neuroscience Indiana University Bloomington United States Luddy School of Informatics Computing and Engineering Indiana University Bloomington United States

The perceptual crossing task has been used to understand social interaction for over a decade. To what extent is the inter action between evolved perceptual crossers truly mutual? To address this question, we undertake a three-pronged examination of the mutuality of simulated social interaction. First, we construct a decoy object that moves at a set amplitude and frequency. This decoy object serves as a benchmark to systematically assess whether the agents can be deceived by non-social oscillatory movement-essentially, whether they mistake the simple, mechanical movement of the decoy for the behavior of another agent. Second, we use agents’ performance with the decoy and agents’ performance with each other to identify convincingly social agents for further analysis. This approach helped us identify that many agents, previously thought to be robust, did not meet our criteria for mutual interaction. However, it also importantly led to the identification of three agents that demonstrate the strongest potential for genuine mutual interaction. Finally, we delve into a detailed investigation of these three agents, focusing on their behavioral patterns and the dynamic strategies they employ. © 2023, Massachusetts Institute of Technology. All rights reserved.

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Predicting Types of Urinary Crystals and Diameter Using Image Processing Techniques and Deep Learning Models 24

Predicting Types of Urinary Crystals and Diameter Using Imag...

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8th International Conference on Medical and Health informatics, ICMHI 2024

作者： Huang, Yu-Ju Tseng, Yi-Shiou Chen, Tzu-Jung Chien, Ting-Ying Department of Computer Science and Engineering Yuan Ze University Taoyuan City Taiwan Department of Surgery Far Eastern Memorial Hospital Graduate Institute of Medicine Yuan Ze University Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan City Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University Taoyuan City Taiwan

ISBN: (纸本)9798400716874

Kidney stones are primarily crystals formed from ion oversaturation in urine. Currently, the diagnosis of kidney stones involves experienced professionals manually interpreting images of urinary crystals under a microscope. In recent years, with the rapid development of artificial intelligence (AI), many researchers have proposed various methods to assist in diagnosis, hoping to improve medical quality. This study explored the application of AI in the medical field, aiming to automate the interpretation of urinary crystal images, such as red blood corpuscles (RBCs), calcium oxalate monohydrate (COM), calcium oxalate dihydrate octahedron (COD-OCT), calcium oxalate dihydrate dodecahedron (COD-DOD), debris, and others, and to use image processing techniques to classify urinary crystal types. This research is expected to assist medical personnel in quickly determining the categories of urinary crystals. Ultimately, our model achieved an F1-score of 0.93, indicating that this architecture has significant potential. © 2024 Copyright ACM.

关键词： Deep learning

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The Scientific Progress and Prospects of Artificial Intelligence for Cancer Detection: A Bibliometric Analysis 24

The Scientific Progress and Prospects of Artificial Intellig...

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24th International Seminar on Intelligent Technology and Its Applications, ISITIA 2023

作者： Maulana, Fairuz Iqbal Adi, Puput Dani Prasetyo Lestari, Dian Ariyanto, Sandy Vikki Purnomo, Agung Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia National Research and Innovation Agency Telecommunication Research Center Jakarta11480 Indonesia Universitas Airlangga Faculty of Medicine Surabaya60132 Indonesia University of Madura Informatics Engineering Study Program Pamekasan Indonesia Bina Nusantara University BINUS Business School Undergraduate Program Entrepreneurship Department Jakarta11480 Indonesia

ISBN: (纸本)9798350313956

Using the Scopus database, this study aims to investigate the use of artificial intelligence for cancer detection in the last ten years from 2013 to 2022. The researchers used bibliometric analysis combined with VosViewer and Rstudio software quantification method for literature analysis. The results of the flushed articles show data such as publication year, journal, country, keywords, and authors, to the highest number of citations. Common keywords used by researchers are artificial intelligence, medical, and human. Researchers limited the findings through keywords such as in the last ten years, documents are journals, and English only so that 1868 articles were obtained. The results found that Harvard Medical School affiliation had the highest number of articles, with 101 articles, by subject area, Medicine had a proportion of 41.9% (n=1320). This bibliometric study will be useful for other researchers to examine the development of research on Artificial Intelligence for Cancer Detection in the last ten years. © 2023 IEEE.

关键词： Diseases

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Hand-Woven Fabric Motif Recognition Methods: A Systematic Literature Review 3

Hand-Woven Fabric Motif Recognition Methods: A Systematic Li...

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3rd International Conference on informatics, Multimedia, Cyber, and Information System, ICIMCIS 2021

作者： Noprisson, Handrie Ermatita, Ermatita Abdiansah, Abdiansah Ayumi, Vina Purba, Mariana Utami, Marissa Universitas Sriwijaya Doctoral Program in Engineering Palembang Indonesia Universitas Sriwijaya Faculty of Computer Science Palembang Indonesia Program of Informatics Management Politeknik Anika Palembang Indonesia Muhammadiyah University of Bengkulu Faculty of Engineering Bengkulu Indonesia

ISBN: (纸本)9781665427333

Knowledge of hand-woven motif recognition is only owned by the older generation, which has not been passed down to the younger generation. Moreover, computer technology can be used to support the recognition of traditional woven fabric motifs. The aim of this research is to conduct a literature review on hand-woven fabric motif recognition, with an emphasis on performance accuracy, techniques, and datasets utilized. This research included three distinct stages of systematic literature review (SLR): planning, execution, and reporting of findings. We found several datasets between 924,845 data and the number of classes between 3-25 class. Based on research result, we obtained several methods for hand-woven fabric motif recognition focused on performance examination. We recommended image pre-processing method, including Adaptive Filtering Denoising, Adaptive Wiener Filtering, Histogram Equalization, Gradient Pyramid (GP) Decomposition. Moreover, we suggested five feature extraction methods, including Radon Transform, Wavelet Transform, Locally Rotation Invariance Measure (LBP-ROR), Transform Invariant Low-Rank Textures (TILT) and Histogram of Oriented Gradients (HOG). For learning method, we recommend Fuzzy C-Mean (FCM), Convolutional neural network (CNN), Deep Neural Network (DNN), MobileNets, Inception-v3 and ResNet-50. © 2021 IEEE.

关键词： Weaving

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Sentiment Analysis using Recurrent Neural Network 1

Sentiment Analysis using Recurrent Neural Network

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1st Bukittinggi International Conference on Education, BICED 2019

作者： Kurniasari, Lilis Setyanto, Arif Program of Informatics Engineering Universitas AMIKOM Yogyakarta Indonesia

This study aims to measure the accuracy of the sentiment analysis classification model using deep learning and neural networks. This study used the algorithm Recurrent Neural Network (RNN) and Word2vec. No previous research has used this model to analyze sentiments written using Indonesian language so that the level of accuracy is unknown. The research began by making a classification model of sentiment analysis. Then, the model was tested through experiments. In this study, They used two classifications (positive and negative). Experiments are carried out using training data sets and the test used data sets sourced from Traveloka theybsite. The result shows that the model presents outstanding results and reaches about 91.9%. © Published under licence by IOP Publishing Ltd.

关键词： Sentiment analysis

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Minimizing the Number of Stunting Prevalence Using the Euclid Algorithm Clustering Approach 7

Minimizing the Number of Stunting Prevalence Using the Eucli...

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7th IEEE International Conference of Computer Science and Information Technology, ICOSNIKOM 2023

作者： Zarlis, Muhammad Oktavia, Tanty Buaton, Relita Ernawan, Ferda Andrian, Kevin Bina Nusantara University Information System Management Department BINUS Graduate Program - Master of Information System Management Jakarta11480 Indonesia STMIK Kaputama Informatics Engineering Binjai20714 Indonesia Universiti Malaysia Pahang Al-Sultan Abdullah Faculty of Computing Pekan26600 Malaysia BINUS Graduate Program-Master of Information Systems Management Bina Nusantara University Department of Information Systems Management Jakarta Indonesia

ISBN: (纸本)9798350360752

Superior and quality human resources are based on healthy human resources with indicators of adequate nutritional intake according to age development. However, the world still faces the problem of hunger and malnutrition today. According to a UNICEF report, the number of people suffering from malnutrition in the world will reach 767.9 million people in 2021. The World Health Organization (WHO) said that malnutrition is a dangerous threat to the health of the world's population. Stunting also has an impact in Indonesia, the prevalence of toddlers experiencing stunting in Indonesia is 24.4% in 2021. The solution created is to classify and cluster the prevalence of stunting to produce a pattern that can be used as best practice to be transmitted to other affected areas. The algorithm used is Euclid. The Euclid algorithm can cluster stunting prevalence data into 4 clusters with the very little category at 79%, the little category at 67%, the many categories at 51%, and the very much category at 21%. The results of the classification and clustering of the best stunting prevalence in cluster one with a very small number, can be used as a source of accurate and updated information that can be used by the government in its efforts to optimize stunting handling in each district/city based on artificial intelligence which can provide handling and optimization patterns. stunting in every district/city. © 2023 IEEE.

关键词： Classification (of information)

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The association between urinary tract infections and diet: a literature review

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Discover Medicine 2025年第1期2卷 1-17页

作者： Çelik, Haluk Kozan, Esra Caf, Balım Bengisu Çebi, Gizem Koç, Murat Vivosens Inc. San Francisco USA Program of Stem Cell and Tissue Engineering Institute of Graduate Education Istinye University Istanbul Türkiye Department of Health Informatics University of Health Science Hamidiye Institute of Health Sciences Istanbul Türkiye

Urinary tract infections (UTIs) are a significant global health concern, affecting millions worldwide, with particular prevalence among specific vulnerable populations. Women of sexually active age, post-menopausal women, pregnant women, individuals with diabetes, catheterized patients, childs and older indivisuals face heightened risk due to various physiological, hormonal, and anatomical factors. While anatomical abnormalities and behavioral factors contribute to UTI susceptibility, the growing challenge of antibiotic resistance has necessitated exploration of alternative treatment approaches. Non-antibiotic interventions, including probiotics, cranberry products, and natural remedies, are gaining attention for their potential role in UTI prevention and management. Recent studies suggest the efficacy of probiotics and plant extracts in promoting urinary tract health and preventing bacterial colonization. Additionally, research highlights the importance of dietary factors, such as vitamin D and probiotic intake, in reducing UTI susceptibility. This review examines the emerging shift toward non-drug strategies, offering a more comprehensive approach to UTI management while addressing the pressing concern of antibiotic resistance.

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Analysis of the Effect of Capacitors on the Voltage Generated by a 3-Phase Induction Generator

Analysis of the Effect of Capacitors on the Voltage Generate...

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2022 International Conference on Electrical engineering and informatics, ICELTICs 2022

作者： Syukri, Mahdi Syuhada, Ahmad Tarmizi Suriadi Ramadhani, Satika Marwan Affan, Muzailin Yanis, Muhammad Universitas Syiah Kuala Doctoral Program School of Engineering Post Graduate Program Banda Aceh23111 Indonesia Universitas Syiah Kuala Dept. of Mechanical and Industrial Engineering Banda Aceh Indonesia Universitas Syiah Kuala Dept. of Electrical and Computer Engineering Banda Aceh Indonesia Universitas Syiah Kuala Dept. of Geophisic Engineering Banda Aceh Indonesia Universitas Syiah Kuala Dept. of Informatics Fmipa Banda Aceh Indonesia

ISBN: (数字)9781665487665

ISBN: (纸本)9781665487665

Induction motors can be operated as induction generators when additional capacitors are added to the stator terminals. Capacitors connected to induction generators can generate voltage and can provide reactive power. The advantage of induction generators can be used in small-scale plants such as micro-hydro power plants. However, the weakness of induction generators are weak voltage regulation and dependence on capacitors to generate voltage. This study conducted a test to see how the effect of capacitor capacity on the voltage generated by a induction generator when serving multiple incandescent lamp loads. The capacitor used is connected with a wye connection because the Wye connection can generate a higher voltage than the Delta connection circuit. This research has been successfully carried out with variations in capacitor values, namely 45 F, 60 F, and 75 F and variations in lamp load values, namely 5W, 15W, 25W, 40W and 60W. Based on the results of the study, the induction generators uses a 45 F capacitor with a load of 5 W, the terminal voltage for line to line is 374 V. However, when using a 75 F capacitor with a 60W load, the terminal voltage for line to line is 239 V. The terminals voltage of the induction generators can also be kept at a constant 380 V by providing varying capacitor values even though it serves varying loads. © 2022 IEEE.

关键词： Asynchronous generators

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