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5th International Conference on Combinatorics, Graph Theory, and Network Topology, ICCGANT 2021

作者： Umilasari, Reni Saifudin, Ilham Study Program of Informatics Engineering Universitas Muhammadiyah Jember Jl. Karimata 49 Jember68121 Indonesia

Bulog is a state-owned public company engaged in food logistics. There are about 18 Bulog warehouses in East Java Province with an uneven distribution. Because the scope of Bulog's business includes logistics or warehousing, surveys and pest eradication, provision of plastic bags, transportation business, food commodity trading and retail business, there must be good coordination between regional sub-divisions and warehouse complexes. In this study, the minimum regional sub-division recommendations in the East Java region were determined using the theory of connected domination number in graphs. The location of the warehouse complex is described as the vertex and adjacent warehouse complexes are connected by edges. In this research, we also determine the connected domination number of unicyclic graph and vertex amalgamation operations for several classes of graphs. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： Metals

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Multiplicative Seasonal ARIMA Modeling and Forecasting of COVID_19 Daily Deaths in Hungary 10

Multiplicative Seasonal ARIMA Modeling and Forecasting of CO...

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10th International Conference on Bioinformatics and Computational Biology, ICBCB 2022

作者： Chudo, Solomon Buke Program of Applied Information Technology and Its Theoretical Background Doctoral School of Informatics University of Debrecen Debrecen Hungary

ISBN: (纸本)9781665401081

The coronavirus disease (COVID-19) is a terrifying pandemic that is rapidly spreading over the world. Up to this point, Hungary has had a significant COVID-19 death rate. The main purpose of this article is to model and forecast basic seasonal time series for COVID-19 death rates. The COVID 19 data, which was collected between 2020-10-04 and 2021-05-12 by the Hungarian government and the World Health Organization (WHO), has been used. The data was analyzed and models were fitted using R software version 4.1.2. The statistical time series model is fitted with the Multiplicative Seasonal Autoregressive Integrated Moving Average (SARIMA) model. Forecasts are made using the fitted model. The data output is used to find seasonality, trend patterns, and unstable variance patterns in the time series plot. The trend is made stationary using the starting difference of the converted data approach, and the variance is made constant using the logarithmic transformation of the original data set. Based on the Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) plot data, the ARIMA (1, 1, 2) (1, 0, 1) (7) model is proposed. The standardized residuals, ACF of residuals, normal Q-Q plot, and p-value for Ljung-Box statistics of the fitted model were found to be within confidence limits and to have no distinct behavioral pattern. The ARIMA (1, 1, 2) (1, 0, 1) (7) model has the smallest estimated value, with a sigma square estimated value of 0.02764, log-likelihood = 80.41, and an Akaike Information Criterion (AIC) value of 148.82. As a consequence, the fitted model ARIMA (1,1,2) (1,0,1) (7) is identified as the best model for forecasting the COVID-19 daily death rate in the country. © 2022 IEEE.

关键词： COVID-19

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Advancing a telehealth and cancer control research agenda at the US National Cancer Institute

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Journal of the National Cancer Institute - Monographs 2024年第64期2024卷 51-54页

作者： Vanderpool, Robin C. Muro, Abigail Jensen, Roxanne E. National Cancer Institute Division of Cancer Control and Population Sciences Behavioral Research Program Health Communication and Informatics Research Branch Rockville MD United States National Cancer Institute Division of Cancer Control and Population Sciences Healthcare Delivery Research Program Outcomes Research Branch Rockville MD United States

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Sports Analytics: A Comparison of Machine Learning Perfomance for Profiling Badminton Athlete 1

Sports Analytics: A Comparison of Machine Learning Perfomanc...

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1st International Conference on Technology Innovation and Its Applications, ICTIIA 2022

作者： Sinadia, Herbie Ewaldo Murwantara, I Made Universitas Pelita Harapan Faculty Of Computer Science Graduate Program Informatics Dept. Tangerang Banten Indonesia

ISBN: (数字)9781665488266

ISBN: (纸本)9781665488266

Sports analytics have become an important part in the improvement of athlete performances in the last decade. Badminton is one such sport where sports analytics can prove beneficial for its athletes. By incorporating data analysis and machine learning techniques, we can learn more about an athlete's performance and profile them via their results in official badminton matches, and coaches as well as athletes may use the results to identify possible improvements for the athlete. This work presents a model to profile the performances of two Indonesian badminton athletes through machine learning using official score data of matches played from 2018 to 2021. We have built a model that performs athlete profiling through regression, classification, and clustering methods. Our result shows that Random Forest outperformed SVM method on regression and the two methods performed similarly on classification, while K-means and hierarchical clustering models displayed similar results in data clustering. © 2022 IEEE.

关键词： Sports

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Software Quality Practices in Growing Startups: A Qualitative Study 20

Software Quality Practices in Growing Startups: A Qualitativ...

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20th Brazilian Symposium on Software Quality, SBQS 2021

作者： Pizzini, Adriano Bortolo Vieira, Ricardo Deda Gomes, Rhodrigo Santos, Gleison Malucelli, Andreia Reinehr, Sheila Graduate Program in Informatics Pontifical Catholic University of Paraná Paran Curitiba Brazil Department of Applied Informatics Federal University of the State of Rio de Janeiro Rio de Janeiro Brazil

ISBN: (纸本)9781450395533

Startups arise in environments of extreme uncertainty, with few resources and the need to scale quickly. In the growth phase, they still need agility, but they tend to concern more with software quality and the development process by having more human and financial resources. Studying the factors that lead startups in the growth phase to seek quality in their processes can help new startups anticipate implementing quality practices. In this paper, we aim to identify how startups adopt quality practices in the growth phase. We carried out a multiple case study with four growth phase startups. We applied qualitative analysis techniques to summarize the findings. The studied startups adopt limited quality practices and are influenced by the development team's maturity level, organizational culture, and experience. Furthermore, they tend to be reactive towards quality, solving the problems when they impact their product, business, customer, or when technical debt can no longer be managed. The findings are relevant to support stabilizing and growing startups to define actions to improve the quality of their processes and products. Besides, they suggest that growth phase startups begin a process of change in the organizational culture concerning quality, adopting the behavior of mature companies as soon as they get more human and financial resources. © 2021 ACM.

关键词： Quality control

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Implementation of the Fuzzy Inference System Tsukamoto Method in the Decision Support System

Implementation of the Fuzzy Inference System Tsukamoto Metho...

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2022 International Symposium on Electronics and Smart Devices, ISESD 2022

作者： Alamsyah, Doni Purnama Ramdhani, Yudi Nurbeni, Resza Dendi Bina Nusantara University Binus Business School Undergraduate Program Entrepreneurship Department Jakarta Indonesia Universitas Adhirajasa Reswara Sanjaya Informatics Engineering Program Bandung Indonesia

ISBN: (数字)9798350396607

ISBN: (纸本)9798350396607

Education is one of the basic and initial formations for the growth and development of a child in the process of obtaining a better future. Once the importance of education, the state really supports every citizen in achieving a decent education. The assessment system in each school has a different system, but the assessment system refers to the national education regulations that have been set by the government. Grade promotion aims to measure the achievement of learning outcomes in accordance with the standard of graduate ability and measure the value of quality. An important decision-making, especially in the field of education, is the decision-making to increase grades in school for students. In making the decision to increase this class, it should refer to the results of the competence or academic ability of the student, not because of the intervention of several parties who do not have the capacity to determine whether or not a student is promoted. Therefore, it is necessary to make a decision support system that will assist in obtaining a decision on the feasibility of a grade increase in students using the Fuzzy Inference System of the Tsukamoto Method. The results of this study are a decision support system that can determine the decision to increase grades in students. © 2022 IEEE.

关键词： Decision support systems

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The Impact of Clinical Decision Support on Health Disparities and the Digital Divide

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Yearbook of Medical informatics 2023年第1期32卷 169-178页

作者： Douthit, Brian J. McCoy, Allison B. Nelson, Scott D. Post-Doctoral Research Fellow: United States Department of Veterans Affairs Vanderbilt University Nashville TN United States Assistant Professor: Department of Biomedical Informatics Vanderbilt University Nashville TN United States Vanderbilt University Medical Center Nashville TN United States Associate Professor: Department of Biomedical Informatics Vanderbilt University Nashville TN United States Program Director: MS in Applied Clinical Informatics Program (MS-ACI) Vanderbilt University Nashville TN United States Vanderbilt University Medical Center Nashville TN United States

OBJECTIVES: This literature review summarizes relevant studies from the last three years (2020-2022) related to clinical decision support (CDS) and CDS impact on health disparities and the digital divide. This survey identifies current trends and synthesizes evidence-based recommendations and considerations for future development and implementation of CDS tools. METHODS: We conducted a search in PubMed for literature published between 2020 and 2022. Our search strategy was constructed as a combination of the MEDLINE®/PubMed® Health Disparities and Minority Health Search Strategy and relevant CDS MeSH terms and phrases. We then extracted relevant data from the studies, including priority population when applicable, domain of influence on the disparity being addressed, and the type of CDS being used. We also made note of when a study discussed the digital divide in some capacity and organized the comments into general themes through group discussion. RESULTS: Our search yielded 520 studies, with 45 included at the conclusion of screening. The most frequent CDS type in this review was point-of-care alerts/reminders (33.3%). Health Care System was the most frequent domain of influence (71.1%), and Blacks/African Americans were the most frequently included priority population (42.2%). Throughout the literature, we found four general themes related to the technology divide: inaccessibility of technology, access to care, trust of technology, and technology *** survey revealed the diversity of CDS being used to address health disparities and several barriers which may make CDS less effective or potentially harmful to certain populations. Regular examinations of literature that feature CDS and address health disparities can help to reveal new strategies and patterns for improving healthcare. IMIA and Thieme. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying

关键词： cancer common data models Data sharing encryption federated learning

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Performance Evaluation of Oversampling Methods on Deep Learning-Based Skin Cancer Classification

Performance Evaluation of Oversampling Methods on Deep Learn...

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2023 International Seminar on Application for Technology of Information and Communication, iSemantic 2023

作者： Supriyanto, Catur Salam, Abu Zeniarja, Junta Wijaya, Adi Universitas Dian Nuswantoro Bachelor Program in Informatics Engineering Faculty of Computer Science Semarang Indonesia Universitas Indonesia Maju Department of Health Information Management Jakarta Indonesia

ISBN: (纸本)9798350339215

The field of dermatology faces considerable challenges when it comes to early detection of skin cancer. Our study focused on using different datasets, including original data, augmented data, and SMOTE oversampled data, to identify skin cancer. Our dataset consisted of images of skin lesions from the MNIST Skin Cancer dataset (HAM 10000), including samples of both cancerous and benign cases in the dataset. We employed data augmentation to expand the dataset's size and increase the diversity of skin lesion features. Furthermore, to tackle class imbalance in the dataset, we applied the SMOTE oversampling technique to generate synthetic samples for the under-represented group. With the original, augmented, and SMOTE oversampled datasets, we trained a Convolutional Neural Network (CNN) model. The performance of the model was evaluated using accuracy, recall, precision, and F1-score. The comparison between the results obtained from the original data, augmented data, and SMOTE oversampling data clearly revealed distinctions in performance. Our findings clearly demonstrate that employing data augmentation and SMOTE oversampling can significantly enhance the efficacy of skin cancer detection. © 2023 IEEE.

关键词： Neural network models

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Optimizing Indoor Vertical Farming with DDPG Reinforcement Learning: Enhancing Control of Nutrient Levels, Climate Conditions, and Plant Health 5

Optimizing Indoor Vertical Farming with DDPG Reinforcement L...

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5th IEEE International Conference on Technology, informatics, Management, Engineering and Environment, TIME-E 2024

作者： Albert Panggabean, Good Fried Romadhon, Rahmat Lubis, Ramot Joelianto, Endra Institut Teknologi Bandung Doctoral Program in Engineering Physics Bandung Indonesia Institut Teknologi Del Faculty of Informatics and Electrical Engineering Toba Indonesia Institut Teknologi Bandung Engineering Physics Study Program Bandung Indonesia Institut Teknologi Bandung Instrumentation Control and Automation Research Group Bandung Indonesia

ISBN: (纸本)9798350364743

In indoor vertical farming systems, managing dynamic and complex environments poses significant challenges. Traditional control strategies often fall short in adapting to rapid changes in critical parameters such as nutrient levels, climate conditions, and plant health indicators. To address these challenges, this paper presents a novel approach for optimizing indoor vertical farming using Deep Deterministic Policy Gradient (DDPG), a reinforcement learning algorithm well-suited for environments with continuous action spaces. Our study focused on the control and monitoring of key parameters, including nutrient levels (pH and EC), climate conditions (temperature, humidity, light, and CO2 levels), and plant health indicators (biomass accumulation and leaf size structure). By defining a comprehensive state and action space, we simulated an indoor farming environment and trained the DDPG model to maximize crop yield and health. © 2024 IEEE.

关键词： DDPG indoor vertical farming precision agriculture reinforcement learning smart farming

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Design Enterprise Architecture Using the TOGAFADM Framework to Support Academic Information Systems at Nusa Nipa University 1

Design Enterprise Architecture Using the TOGAFADM Framework ...

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1st IEEE International Conference on Smart Technology, ICE-SMARTec 2023

作者： Darkel, Yohanes Brekmans M. Emanuel, Andi W. R. Mudjihartono, Paulus Informatics Engineering Study Program Universitas Nusa Nipa Faculty of Engineering Indonesia Fakultas Teknologi Industri Universitas Atma Jaya Yogyakarta Departemen Informatika Yogyakarta Indonesia

ISBN: (纸本)9798350306156

Information technology support is desperately needed for higher education. Universities must use information technology to effectively and efficiently manage potential resources to compete with other institutions. Utilization of IT in Higher Education Governance, particularly the academic information system at Nusa Nipa University, lacks a structured architecture. The current IT infrastructure is insufficient to respond promptly and precisely to application and business change solutions. This study aims to simplify the process of developing information system architecture by developing an architectural model and an implementation roadmap. This study's design uses the TOGAF ADM model, The organization's initial condition analysis stage is the preliminary requirement management phase;architectural vision;and business architecture. The enterprise architecture design begins with the second stage's information system architecture and technology architecture phases. The subsequent phases of opportunities and solutions, migration planning, and change management, recommendations for implementing enterprise architecture are presented in the third section. The consequences of this study are IT outlines for each engineering stage given the TOGAF ADM structure for business processes in new understudy affirmations frameworks, scholastic cycles, graduated classes, and libraries to help data frameworks at Nusa Nipa College. This research can create a blueprint for IT development suggestions for expected business techniques at Nusa Nipa College. © 2023 IEEE.

关键词： Blueprints

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