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1st Virtual Conference on engineering, Science and Technology, ViCEST 2020

作者： Cynthia, Eka Pandu Rahadjeng, Indra Riyana Karyadiputra, Erfan Rahman, Fauzi Yusa Windarto, Agus Perdana Limbong, Martalina Hermanto, Teguh Iman Rusiadi, E. Yarmani, Y. Informatics Engineering Study Program Faculty of Science and Technology UIN Sultan Syarif Kasim Riau Indonesia Universitas Bina Sarana Informatika Jakarta Indonesia Universitas Islam Kalimantan Muhammad Arsyad Al Banjari Banjarmasin Indonesia STIKOM Tunas Bangsa Pematangsiantar Indonesia Akademi Keperawatan Surya Nusantara Pematangsiantar Indonesia Informatics Engineering Study Program Sekolah Tinggi Teknologi Wastukancana Indonesia Universitas Pembangunan Panca Budi Medan Indonesia Universitas Bengkulu Bengkulu Indonesia

The objective of the research was to analyze the clustering method by optimizing Particle Swarm Optimization (PSO) in the case of measles immunization for children under the age of 5. The research data source used is the North Sumatra Province Central Bureau of Statistics (https://***/). The data used in 2019 included 33 records with variables BCG, DPT-HB3/DPT-HB/Hib3, CAMPAK (MEASLES + RUBELLA), POLIO 4 and HEPATITIS B. The methods used were k-medoids and PSOs. This method is used to determine the value of the Davies Bouldin Index (DBI) before the cluster value is determined (k). The resulting k values were compared to k-medoids without PSO. The best results of k-medoid and PSO will be tested by classification to see the accuracy value of the cluster formed. The results showed that the optimization of k-medoids and PSO was better with the number of clusters (k = 5) than 0.078. (DBI). The results also show that the accuracy of the cluster formed is 95% with a correlation of 0.98. © Published under licence by IOP Publishing Ltd.

关键词： Immunization

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The Study of Coastline Changing and Total Suspended Solid Distribution Based on the Remote Sensing Data in Teluk Lamong Multipurpose Port Terminal 8

The Study of Coastline Changing and Total Suspended Solid Di...

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8th International Seminar on Ocean and Coastal engineering, Environmental and Natural Disaster Management, ISOCEEN 2020

作者： Pratikto, Widi Agoes Fitriadhy, Ahmad Maulana, Muhammad Ilham Huda, Abiyani Choirul Putri, Destyariani Liana Simatupang, Liany Ayu Wahyudi, Nazariano Rahman Laksono, Rendatiyarso Dewi, Anggie Vibriyanti Rossari Ocean Engineering Departement Faculty of Marine Technology Institut Teknologi Sepuluh Nopember Surabaya60111 Indonesia Department of Maritime Technology Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Malaysia Ocean Engineering Study Program Institut Teknologi Kalimantan Kalimantan Timur76127 Indonesia

Looking forward to the abovementioned conditions, this research is needed to elaborate on the effects of the reclamation to the marine resources in Teluk Lamong Multipurpose Port Terminal as the reclaimed product. In order to describe the impact of the port development, this study will analyze the shoreline changing, the current pattern modeling, as well as the Total Suspended Solid (TSS) modeling using the remote sensing data. The several numbers of expected objectives through this study are to get the set of scientific information on the shoreline changing in Teluk Lamong Multipurpose Port Terminal in the year of 2012 and 2020, to get the figure of current pattern in Teluk Lamong Multipurpose Port Terminal in the year of 2012 and 2020, and to elaborate TSS concentration through the modeling approach in Teluk Lamong Multipurpose Port Terminal in the year of 2012 and 2020. Hence, there is a set of methodologies and tools to cooperate with the information before and after the reclamation. The use of the Digital Shoreline Analysis System (DSAS) software to analyze coastline conditions. The using of Mike 21 to analyze the current pattern and TSS concentrations. In addition to the TSS analysis, it will also need a set of remote sensing data from the Google Earth Engine (GEE). The modeling and calculation give information about the End Point Rate (EPR) values and TSS values. The EPR values are 107.5 m/year, 59,625 m/year and 10,375 m / year. The TSS values are 0-20 mg/L, 20.1-40 mg/L, 40.1-80 mg/L, 80.1-120 mg/L and >120.1 mg/L. Moreover, the result shows the different values among the length of coastline, the current pattern, and TTS in the years 2012 and 2020. The difference in the coastline reaches 950 m at this latest 8 years. While it also brings the changing to the current pattern and sediment transport which show through its current velocity and sediment content per liter of seawater during high and low tide accordingly. © Published under licence by IOP Publishing

关键词： Sediment transport

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Advanced Data Instrumentation for Stunting Analysis in Physical-Cyber Architecture

Advanced Data Instrumentation for Stunting Analysis in Physi...

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International Conference on Telecommunication Systems, Services, and Applications (TSSA)

作者： Daniel Nugraha M. Riza Nurtam Hartuti Mistialustina Didin Saepudin Welly Surjono Ary Setijadi Prihatmanto Doctoral Program of School of Electrical Engineering and Infomatics Institut Teknologi Bandung Bandung Indonesia Universitas Widya Dharma Pontianak Kalimantan Barat Indonesia Electrical Engineering Department Faculty of Engineering Universitas Sangga Buana Bandung Indonesia Universitas Sangga Buana Bandung Indonesia School of Electical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia

In Indonesia, stunting is a serious problem that has drawn a lot of attention from the government. This study offers a novel strategy for preventing stunting by combining the 5-Desk Model used in integrated health posts (Posyandu) with the Cyber-Physical System (CPS) architecture. Chronic malnutrition and childhood diseases can cause stunting, which can result in long-term health issues and cognitive deficits. Despite advancements, it still poses a serious threat to almost every Indonesian province. For the purpose of gathering data in Posyandu, such as registration, growth measurement, recording, counseling, and health services, the 5-Desk Model provides an organized framework. This promotes the well being of the community and gives healthcare professionals the ability to thoroughly monitor important health indicators. This strategy is improved with CPS integration, which results in a four-layered, comprehensive system that includes gamification, business intelligence, information systems, and instrumentation. To maximize efforts to avoid stunting, this architecture facilitates accurate monitoring, real-time data collecting, data analysis, and stakeholder communication. This study imagines a data-driven future for Indonesian stunting prevention, where cooperation, technology, and data are combined to address this pressing problem and safeguard the future prospects and wellbeing of Indonesia’s youth. Implementing this goal and expanding stunting prevention initiatives will be the main goals of future research.

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A Multi-phase Deep Learning Approach for Predicting HCC Response to TACE using Complete Computed Tomography

A Multi-phase Deep Learning Approach for Predicting HCC Resp...

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Data Science and engineering in Healthcare, Medicine and Biology, IEEE EMBS Special Topic Conference on

作者： Shun Cheng Chang Chien Fu Liu Marta Misztal Yi Hsien Hsieh Che Lin Graduate Institute of Communication Engineering National Taiwan University (NTU) Taiwan School of Electronic Engineering and Computer Science Queen Mary University of London UK Department of Electrical Engineering NTU Taiwan Center for Computational and Systems Biology and Center for Biotechnology NTU Taiwan Smart Medicine and Health Informatics Program NTU Taiwan

In this research study, we compare the predictive performance of two advanced deep learning-based models in order to provide a solution to TACE (Transarterial Chemoembolization) response prediction in HCC (Hepatocellular Carcinoma) patients. Using entire abdominal CT scans enabled a broader perspective available for the model, eliminating the need for segmentation during the preprocessing. Making use of both single-phase and multi-phase CT imaging, we have used DenseNet121 and have obtained an accuracy of 80% for the multi-phase *** Relevance: The ability to predict the effectiveness of TACE treatment prior to its administration makes it possible to provide a better decision-making aid for physicians and patients.

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Partial entropy decomposition reveals higher-order structures in human brain activity

arXiv

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arXiv 2023年

作者： Varley, Thomas F. Pope, Maria Puxeddu, Maria Grazia Faskowitz, Joshua Sporns, Olaf Department of Psychological and Brain Sciences Indiana University BloomingtonIN47405 United States School of Informatics Computing & Engineering Indiana University BloomingtonIN47405 United States Program in Neuroscience Indiana University BloomingtonIN47405 United States

The standard approach to modeling the human brain as a complex system is with a network, where the basic unit of interaction is a pairwise link between two brain regions. While powerful, this approach is limited by the inability to assess higher-order interactions involving three or more elements directly. In this work, we present a method for capturing higher-order dependencies in discrete data based on partial entropy decomposition (PED). Our approach decomposes the joint entropy of the whole system into a set of strictly non-negative partial entropy atoms that describe the redundant, unique, and synergistic interactions that compose the system's structure. We begin by showing how the PED can provide insights into the mathematical structure of both the FC network itself, as well as established measures of higher-order dependency such as the O-information. When applied to resting state fMRI data, we find robust evidence of higher-order synergies that are largely invisible to standard functional connectivity analyses. This synergistic structure is symmetrical across hemispheres, largely conserved across individual subjects, and is distinct from structural features based on redundancy that have previously dominated FC analyses. Our approach can also be localized in time, allowing a frame-by-frame analysis of how the distributions of redundancies and synergies change over the course of a recording. We find that different ensembles of regions can transiently change from being redundancy-dominated to synergy-dominated, and that the temporal pattern is structured in time. These results provide strong evidence that there exists a large space of unexplored structures in human brain data that have been largely missed by a focus on bivariate network connectivity models. This synergistic "shadow structures" is dynamic in time and, likely will illuminate new and interesting links between brain and behavior. Beyond brain-specific application, the PED provides a very general app

关键词： Entropy

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Application of factor analysis method to support the users acceptance model of ERP systems implementation 4

Application of factor analysis method to support the users a...

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4th International Conference on Combinatorics, Graph Theory, and Network Topology, ICCGANT 2020

作者： Sardjono, W. Sudirwan, J. Priatna, W. Putra, G.R. Information Systems Management Department BINUS Graduate Program Master of Information Systems Management Bina Nusantara University Jakarta11480 Indonesia School of Information Systems Department BINUS Undergraduate Program Bina Nusantara University Jakarta11480 Indonesia Informatics Engineering Engineering Bhayangkara University Jakarta Raya Indonesia Computer Science Study Program Faculty of Mathematics and Natural Sciences Pakuan University Bogor Indonesia

An e-Commerce company has been using an Enterprise Resource Planning (ERP) system for several years, but is still constrained in its implementation, this is reflected in the number of issue/change request tickets submitted by users who have not been able to reach ideal conditions. To overcome this problem, we need an appropriate reference model, the ERP system user acceptance model in companies. The study conducted factors that influence the level of acceptance of SAP ERP users in the XYZ group to then determine a model that is able to explain practically the level of ERP system user acceptance, which in turn can produce concrete proposals to increase ERP system user acceptance. Research is quantitative descriptive using factor analysis and regression analysis methods. The research method uses a questionnaire with a total of 107 valid respondents coming from 8 company names under the XYZ group in 6 Southeast Asian countries. The conclusion of the study is that there are 24 indicators and 4 factors that influence user acceptance of the SAP ERP system. These four factors are the low contribution of the ERP system, the quality of ERP systems and data, the development of ERP systems, and also the low quality of ERP system supporters. It is hoped that by optimizing the value of the 4 factors, the XYZ group can increase user acceptance of the SAP ERP system so that the system can provide benefits expected by the company to be competitive advantage. © 2021 Published under licence by IOP Publishing Ltd.

关键词： Factor analysis

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On the Evaluation of Access-point Handovers for UAVs in Long-distance Missions

On the Evaluation of Access-point Handovers for UAVs in Long...

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2021 International Conference on Unmanned Aircraft Systems, ICUAS 2021

作者： Fagundes, Leonardo A. Souza, Vitor Barbosa Brandao, Alexandre S. Núcleo de Especialização em Robótica Federal University of Viçosa Department of Electrical Engineering and Graduate Program on Computer Science Viçosa Brazil Federal University of Viçosa Graduate Program on Computer Science Department of Informatics Viçosa Brazil

ISBN: (纸本)9780738131153

Unmanned Aerial Vehicle (UAV) systems are being increasingly used in a broad range of applications requiring extensive communications either to interconnect the UAVs with each other or to connect them with Ground Control Stations (GCS). Due to the complexity and difficulty of performing long distance experiments with these robots, simulation becomes a viable and necessary alternative. However, focusing either on the modeling of UAV operations or communication dynamics, available simulation tools are not able to capture the complex interdependencies between these two aspects, especially in applications where extensive communications are required. The main contribution of this work is the modeling and implementation of strategies for enhancing connectivity of a UAV performing long-distance navigation tasks, taking into account applications' requirements. The proposed strategies aim at assessing the impact of frequent handovers between wireless access points in terms of packet loss and available bandwidth. The first strategy prioritizes maintaining a connection until the signal-to-noise ratio (SNR) observed by the robot reaches a predefined threshold. For this, it is assumed that the data to be transmitted is small enough so that the robot may change its modulation to obtain smaller bandwidths while improving connection time. The second one prioritizes bandwidth availability, thus, it always searches for a network that is able to offer data rates higher than a minimum threshold. A hybrid model is validated by considering the characteristics of each individual strategy. The capabilities of the simulation tool designed for this work are illustrated through some case-study scenarios. © 2021 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Benchmarking A New Dataset for Coffee Bean Defects Classification Based on SNI 01-2907-2008

Benchmarking A New Dataset for Coffee Bean Defects Classific...

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Information Technology Research and Innovation (ICITRI), International Conference on

作者： Made Windu Antara Kesiman Ismail Sulaiman I Made Dendi Maysanjaya Kadek Teguh Dermawan Dept. of Informatics Engineering Virtual Vision Image and Pattern Research Group Universitas Pendidikan Ganesha Bali Indonesia Program Study Teknologi Hasil Pertanian Faculty of Agriculture Universitas Syiah Kuala Banda Aceh Indonesia

To develop a device which can determine automatically the quality of coffee beans, the module to identify and classify coffee bean defects based on digital images processing is needed. For this reason, a new dataset of coffee bean defect images is built in this research. 3 classes were defined and obtained from the image sample of coffee beans, namely good coffee beans, defective coffee beans, and non-valid coffee beans. Moreover, specifically for the class of defective coffee beans, the new dataset also provides ground truth image samples for 17 classes of coffee bean with defects which was defined by SNI 01-2907-2008. Two Convolutional Neural Network (CNN) architecture models, InceptionResnetV2 and MobileNet, were tested to do an initial benchmarking process to classify coffee beans and their types of defects. Both architectures show very promising results to classify coffee bean images in 3-classes. With 92.52% of accuracy, MobileNet outperforms slightly InceptionResnetV2. Both architectures are fairly easy to classify the 3-classes of coffee bean images. But the experimental results indicate that the task of classifying more specifically the 17 classes of different types of defects in coffee beans is still quite difficult. Although the accuracy of InceptionResnetV2 of 53.35% seems much higher than the accuracy of MobileNet, the two architectures still seem to be struggling to identify each type of coffee bean defect. This benchmarking results will serve as the initial basis that helps to analyze the level of complexity of problems in the coffee bean new dataset, as well as the basis for further investigations and research processes to improve the performance of the future coffee bean classifier machine.

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Optimizing CLABSI Prediction: Data and Process Modeling Approach for Enhanced Model Performance

Optimizing CLABSI Prediction: Data and Process Modeling Appr...

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2024 Global Digital Health Knowledge Exchange and Empowerment Conference, gDigiHealth.KEE 2024

作者： Daboor, Mohammad Kharbat, Faten Azzuni, Fathi Mueen Sultan, Iyad Odeh, Mohammad King Hussein Cancer center Nursing Department Amman Jordan College of Engineering Al Ain University Abu Dhabi United Arab Emirates Kanad Hospital AlAin Pediatric Department Abu Dhabi United Arab Emirates King Hussein Cancer Center Department of Pediatrics Amman Jordan Cancer Care Informatics Program Amman Jordan Jordan College of Art Technology and Environment University of the West of England Bristol United Kingdom Global Academy for Digital Health Bristol United Kingdom

ISBN: (纸本)9798331531331

Central Line-Associated Bloodstream Infections (CLABSIs) are important Healthcare-Associated Infections (HAI) resulting in increased morbidity, mortality, and medical care costs. Data relevance, quality, and appropriateness are crucial characteristics for any effective and successful predictive model including CLABSI prediction. This study tackles the problem of finding out which among many possible features might be most representative or relevant to predict CLABSls by proposing a new objective method of selecting features;we integrate text mining techniques with process modeling thus making it possible for us to know objectively which amongst them are significant ones that should always reflect in any dataset used for CLABSI prediction. What our approach does is to enhance the strength and accuracy of predictive models by providing verified sets of features as shown by results achieved herein. Also, this research brings into focus such points like having validated data as well process models which may play a role in determining the readiness levels of CLABSI dataset at hospital settings. © 2024 IEEE.

关键词： Prediction models

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Need Analysis of Interactive Multimedia Development for Virtual Learning in Pandemic 4

Need Analysis of Interactive Multimedia Development for Virt...

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4th International Conference on Electrical, Electronics, informatics, and Vocational Education, ICE-ELINVO 2021

作者： Lempas, J.F. Soenarto, S. Barahama, A.D. Instructional Technology Post-Graduate Program Universitas Negeri Yogyakarta Jalan Colombo 01 Daerah Istimewa Yogyakarta 55281 Indonesia Department of Electronics and Informatics Engineering Education Post-Graduate Program Universitas Negeri Yogyakarta Jalan Colombo 01 Daerah Istimewa Yogyakarta 55281 Indonesia

The pandemic that has not ended has an impact on changing the educational paradigm. Existing conditions demand to continue to use virtual learning. During the epidemic, this study will examine students' demand for interactive multimedia in virtual learning. The interviews reveal that the media that teachers provide in virtual learning during this pandemic has limits. Data was gathered through interviews and questionnaires given to teachers and students. The student requirements questionnaire reveals that interactive multimedia is the most effective instructional medium for pupils. This study is part of a larger investigation of the evolution of multimedia learning during a pandemic. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Students

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