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Classification of apples based on color feature extraction and Euclidean distance search

AIP Conference Proceedings 2024年第1期3048卷

作者： Dian Nursantika Erna Piantari Information System Study Program Department of Engineering Universitas Terbuka Tangerang Indonesia Department of Computer Science Universitas Pendidikan Indonesia Bandung Indonesia

Apple is a popular fruit in the world, until it became an icon by one of the leading software and hardware developers. The colors of apples that are often found in Indonesia are red and green, humans are recognize the color of the apple through sight, based on previous knowledge and experience. How about the computer, is the computer able to recognize the color of the apple? Through this research, it is expected to solve these challenges, so the research results can be applied in various devices, for example for grade classification of apples, identification of types of apples, and educational games. The research consists of two parts, namely training and testing. Training is conducted to train images by means of preprocessing, feature extraction, and feature collection. Testing is carried out to determine the ability of computers to recognize apples with the stages of preprocessing, feature extraction, and feature matching using the Euclidean distance algorithm. The images used in this study were 40 training images and 65 testing images. The results of testing on the training image have an accuracy rate of 100%, while the accuracy level of the new image is 84% recognized as true and 16% recognized as false.

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Development and Validation of Customer Intention Factors for Live-Stream Shopping

Development and Validation of Customer Intention Factors for...

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Conference on New Media Studies (CoNMedia)

作者： Erick Fernando Desman Hidayat Christian Haposan Pengaribuan Yulius Denny Prabowo Department of Information System Faculty of Engineering and Informatics Universitas Multimedia Nusantara Tangerang Indonesia Management Department BINUS Entrepreneurship Center Bina Nusantara University Jakarta Indonesia Management Study Program Faculty of Business Sampoerna University Jakarta Indonesia Computer Science Department Binus Online Learning Bina Nusantara University Jakarta Indonesia

Along with technological improvements, online shopping is currently developing quickly. Online shops started by selling electronics, clothing, food, and home appliances and continue to evolve, selling various things. Currently, digital marketing has a novel technique, namely live shopping, where sellers can present, promote and offer their products directly through live streaming on social media and e-commerce platforms. This research will focus on gaining insight into the factors influencing customers to watch and purchase through live streaming. This research is an early-stage study of exploring and searching for research models. The study used a literature review approach by reviewing similar previous research articles. Several variable components were used in this study. The findings of the factors include visibility capacity, meta-vocation capacity, purchase orientation capacity, social presence, price, perceived product quality, perceived enjoyment, purchase orientation, perceived usefulness, and intention to buy. These factors were tested and proved to be valid with Cronbach's Alpha value being more than 0.5 and reliable with the value of the loading factor a greater than 0.6. Criteria The factors of the findings for further analysis of the relationship between factors and other variables.

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The Design of VBee Diary Writing Application

The Design of VBee Diary Writing Application

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International Conference on Education and Technology (ICET)

作者： Christiana Sidupa Hermawan Nugroho Yella Dezas Perdani Interior Design Department Digital Language Learning Center Faculty of Humanities Bina Nusantara University Jakarta Indonesia Informatics Engineering Study Program Faculty of Information Technology Satya Wacana Christian University Salatiga Indonesia Interior Design Department Digital Language Learning Center Faculty of Humanities Bina Nusantara University Bandung Indonesia

The development of critical thinking, creativity, and communication abilities is facilitated by the acquisition of writing skills, which are significant for students. Nevertheless, a considerable number of students presently encounter difficulties in locating the impetus and enthusiasm required for engagement in writing endeavors. The focus of the present paper is application design. The VBee application is a web-based application that facilitates the expression of user creativity and fosters a deeper appreciation for the art of writing. The application boasts a highly intuitive interface that effortlessly enables users to document their thoughts and experiences. It offers a plethora of features that not only facilitate writing but also foster self-expression, including customizable emoticons and the option to provide feedback. By designing the application, it could help support vocational school students in improving the quality of skill-focused education, particularly their English creative writing skill in enjoyment. Besides, the teachers are assisted to guide their students with technologically advanced and entertaining learning tools.

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Deep Learning in Smart Healthcare: A GAN-based Approach for Imbalanced Alzheimer's Disease Classification

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Procedia Computer Science 2024年 241卷 146-153页

作者： Hina Tufail Abdul Ahad Ira Puspitasari Ibraheem Shayea Paulo Jorge Coelho Ivan Miguel Pires Department of Computer Science University of Management and Technology Sialkot Pakistan Information System Study Program Faculty of Science and Technology Universitas Airlangga School of Software Northwestern Polytechnical University Xian Shaanxi P.R. China Department of Electronics and Communication Engineering Istanbul Technical University(ITU) Turkey Polytechnic University of Leiria Leiria Portugal Institute for Systems Engineering and Computers at Coimbra (INESC Coimbra) Coimbra Portugal Instituto de Telecomunicações Escola Superior de Tecnologia e Gestão de Águeda Universidade de Aveiro Águeda Portugal

Alzheimer's disease (AD) is a type of dementia that leads to memory loss and impairment, which afects patients’ lives badly. It is not curable yet, but its progression can be slowed down if detected at earlier stages. In this research study, we propose a transfer learning-based convolutional neural network (CNN) model to classify magnetic resonance imaging (MRI) into one of four stages of Alzheimer's disease. One of the major limitations of the deep learning-based classification model is the non-availability of healthcare datasets related to AD. The widely used Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset has a major class imbalance issue. We propose a generative adversarial network (GAN) based data augmentation technique to overcome the data imbalance. This promotes the investigation of applying GANs to generate synthetic samples for minority classes in Alzheimer's disease datasets to enhance classification performance. The results show the progression in the overall classification process of AD.

关键词： Alzheimer disease (AD) Deep learning Convolutional Neural Network (CNN) Computer-aided diagnosis (CAD)

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Data analysis guidelines for single‑cell RNA‑seq in biomedical studies and clinical applications

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Military Medical Research 2023年第4期10卷 529-553页

作者： Min Su Tao Pan Qiu‑Zhen Chen Wei‑Wei Zhou Yi Gong Gang Xu Huan‑Yu Yan Si Li Qiao‑Zhen Shi Ya Zhang Xiao He Chun‑Jie Jiang Shi‑Cai Fan Xia Li Murray J.Cairns Xi Wang Yong‑Sheng Li State Key Laboratory of Reproductive Medicine Nanjing Medical UniversityNanjing 211166China College of Biomedical Information and Engineering the First Affiliated Hospital of Hainan Medical UniversityHainan Medical UniversityHaikou 571199HainanChina College of Bioinformatics Science and Technology Harbin Medical UniversityHarbin 150081HeilongjiangChina Department of Immunology Nanjing Medical UniversityNanjing 211166China Department of Laboratory Medicine Women and Children’s Hospital of Chongqing Medical UniversityChongqing 401174China Baylor College of Medicine HoustonTX 77030USA Shenzhen Institute for Advanced Study University of Electronic Science and Technology of ChinaShenzhen 518110GuangdongChina School of Biomedical Sciences and Pharmacy Faculty of Health and Medicinethe University of NewcastleUniversity DriveCallaghanNSW 2308Australia Precision Medicine Research Program Hunter Medical Research InstituteNew Lambton HeightsNSW 2305Australia

The application of single-cell RNA sequencing(scRNA-seq)in biomedical research has advanced our understanding of the pathogenesis of disease and provided valuable insights into new diagnostic and therapeutic *** the expansion of capacity for high-throughput scRNA-seq,including clinical samples,the analysis of these huge volumes of data has become a daunting prospect for researchers entering this ***,we review the workflow for typical scRNA-seq data analysis,covering raw data processing and quality control,basic data analysis applicable for almost all scRNA-seq data sets,and advanced data analysis that should be tailored to specific scientific *** summarizing the current methods for each analysis step,we also provide an online repository of software and wrapped-up scripts to support the *** and caveats are pointed out for some specific analysis tasks and *** hope this resource will be helpful to researchers engaging with scRNA-seq,in particular for emerging clinical applications.

关键词： Single-cell RNA-sequencing(scRNA-seq) Data analysis Biomedical research Clinical applications

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Development of location suitability prediction for health facilities using random forest machine learning in 2030 integrating remote sensing and GIS in West Java, Indonesia

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Environmental Advances 2025年 19卷

作者： Virtriana, Riantini Ihsan, Kalingga Titon Nur Anggraini, Tania Septi Deliar, Albertus Harto, Agung Budi Riqqi, Akhmad Sakti, Anjar Dimara Remote Sensing and GIS Research Group Faculty of Earth Science and Technology Bandung Institute of Technology Bandung 40132 Indonesia Center for Remote Sensing Bandung Institute of Technology Bandung 40132 Indonesia Doctor Program in Program Study of Geodesy and Geomatic Engineering Faculty of Earth Sciences and Technology Bandung 40132 Indonesia Geographic Information Science Universitas Pendidikan Indonesia Bandung 40111 Indonesia Center for Spatial Data Infrastructure Bandung Institute of Technology Bandung 40132 Indonesia

Access to healthcare facilities is crucial in the present day. Healthcare facilities must be proportional to the population in a given area. Therefore, it is important to increase the number of healthcare facilities in regions where there is an imbalance. Proper planning and a sustainability review are necessary when determining locations for healthcare facilities. Environmental changes can affect the suitability of a location in the future. Thus, planning that can predict future suitability conditions is required to ensure that the built locations have high sustainability. This study predicts the suitability of healthcare facility locations in 2030 in West Java using remote sensing and Geographic information System (GIS). Both static and dynamic data processed at 30×30 meter intervals across West Java will be used. Geospatial and remote sensing data are utilized in the study. Dynamic parameter extrapolation uses data from 2000 to 2018. The random forest machine learning method is employed to obtain the suitability values for healthcare facility locations using existing health facility training data in West Java. The results show changes in the suitability classes of healthcare facilities in each region from 2018 to 2030, with some areas experiencing an increase or decrease in class. This research highlights consistently suitable locations, ensuring their sustainability as healthcare facility sites. © 2024

关键词： GIS Health Facility Machine Learning Remote Sensing

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Distributed Observer Approach for Scalable Formation Control of Multi-Agent Network

Distributed Observer Approach for Scalable Formation Control...

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International Seminar on Intelligent Technology and Its Applications (ISITIA)

作者： Djati Wibowo Djamari Muhamad Rausyan Fikri Mechanical Engineering Study Program Sampoerna University Jakarta Indonesia Information System Study Program Sampoerna University Jakarta Indonesia

ISBN: (数字)9781728174136

ISBN: (纸本)9781728174143

This work studies formation control of Multi-Agent Systems (MASs) where its formation size is scalable via a scaling factor (scalable formation). Previous works on scalable formation are limited to either fixed undirected graph or fixed directed graph with p-rooted graph condition. This work proposes a novel distributed algorithm for scalable formation based on a distributed observer to estimate agents' positions. The novel algorithm results in a new matrix, a Laplacian matrix with additional diagonal terms, where the desired formation pattern is embedded in this diagonal terms. With the proposed algorithm, only spanning tree condition is needed as the necessary and sufficient condition to achieve the scalable formation. Numerical examples are shown to illustrate the proposed method.

关键词： Eigenvalues and eigenfunctions Observers Distributed algorithms Laplace equations Standards Topology Nickel

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Energy Preservation in MANET Using Self-Adaptive CH Selection with Advanced Genetic Algorithm

Energy Preservation in MANET Using Self-Adaptive CH Selectio...

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Advanced engineering and Technologies (ICONNIC), International Conference on

作者： Bonifacius Vicky Indriyono Natalinda Pamungkas Fatima Hashim Abbas Ery Mintorini Mohammed Almohamadi Sarmad Nozad Mahmood Sameer Alani Ahmed H. Alkhayyat Eko Hari Rachmawanto Information System University of Dian Nuswantoro Kediri Indonesia Medical Laboratories Techniques Department Al-Mustaqbal University College Hillah Babil Iraq Visual Communication Design University of Dian Nuswantoro Kediri Indonesia College of Information Technology Imam Ja'afar Al-Sadiq University Al-Muthanna Iraq Computer Technology Engineering College of Engineering Technology Al-Kitab University Iraq Medical Laboratories Techniques University of Mashreq Research center Baghdad Iraq College of technical engineering University of Mashreq The Islamic University Najaf Iraq Study Program in Informatics Engineering University of Dian Nuswantoro Semarang Indonesia

Mobile Adhoc Networks (MANETs) is an emerging technology in both the industrial and academic research. The major drawback in MANETs is improving the battery capacity. MANETs are dynamic in nature therefore during communication it consumes more energy that reduces the overall energy efficiency of the network. Many past and present researches are concern about this problem. In this paper, Energy Preservation in MANETs using Self-Adaptive Cluster Head Selection with Advanced Genetic Algorithm (EPMSA-CHAG) approach is proposed where the CH selection is performed using two segments; they are initial parameter based on CH selection and Advanced Genetic Algorithm (AGA) based CH selection. At the initial stage the parameters which are considered for the CH selection are node degree, node stability, distance, residual energy, and speed and delivery rate. Using these parameters are the best fit for CH selection is chosen then in order to find the optimal best fit from the best fit calculation, Advanced Genetic Algorithm (AGA). The proposed EPMSA-CHAG approach is simulated using NS2 and the parameters which are considered for the performance analysis are packet delivery rate, energy efficiency, end to end delay, routing overhead and throughput. The methods that are taken for the comparative analysis are HLSPM-CHSR and HAMBO-CHLD. From the results calculated it is proven that the proposed EPMSA-CHAG approach achieved high packet delivery rate, energy efficiency and throughput as well as lower end to end delay and routing overhead when compared with the earlier methods HLSPM-CHSR and HAMBO-CHLD.

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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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Conformance Checking to Evaluate Business Process Models using Modified Time-based Heuristics Miner Algorithm

Conformance Checking to Evaluate Business Process Models usi...

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2019 IEEE Conference on Sustainable Utilization and Development in engineering and Technologies, CSUDET 2019

作者： Effendi, Yutika Amelia Retrialisca, Fitri Nuzulita, Nania Universitas Airlangga Information System Study Program Department of Engineering Surabaya Indonesia

ISBN: (纸本)9781728132761

Business processes are the collections of activities which produce some specific service for organizations. A lot of services are produced in the organization, making them difficult to document. information systems were built to perform the business processes and produce event logs as the documented business processes. The event log will be analyzed using process discovery technique to mine the process model by implementing some well-known algorithms such as Alpha Miner in deterministic algorithms and Heuristics Miner in heuristic algorithms. All of the algorithms have their own excellence and limitations in analyzing and discovering the event log into process models. Modified Time-based Heuristics Miner is the latest improvement of Heuristics Miner algorithm which can be mined the process model and define sequential and parallel (AND, OR, and XOR) relation. Comparing to the original, Heuristics Miner algorithm, is only able to discover sequential and parallel (AND and XOR) relation. To know the differences between original Heuristics Miner and Modified Time-based Heuristics Miner including the process model and its relations, the evaluation using conformance checking consist of fitness, precision, simplicity, and generalization was done in this research. This paper will be focused on the results of evaluation in conformance checking from both of the algorithms. The results presented that the conformance checking of Modified Time-based Heuristics Miner was higher than that of the original Heuristics Miner algorithm in those four criteria. © 2019 IEEE.

关键词： Miners

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