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Correction: Advancements in additive manufacturing for video laryngoscopes: a comprehensive scoping and technological review

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Systematic reviews 2024年第1期13卷 31页

作者： Ana Cristina Beitia Kraemer Moraes Chiara das Dores do Nascimento Everton Granemann Souza Mauricio Beitia Kraemer Mauricio Moraes Neftali Lenin Villarreal Carreno Evandro Piva Rafael Guerra Lund Pelotas Dental School Graduate Program in Dentistry Federal University of Pelotas Pelotas RS 96010‑560 Brazil. Master's Degree in Electronic and Computer Engineering Center for Social and Technological Sciences Catholic University of Pelotas Pelotas RS 96015‑560 Brazil. Faculty of Medicine São Francisco University Bragança Paulista SP 12916‑900 Brazil. Faculty of Medicine Federal University of Pelotas Pelotas RS 96010‑560 Brazil. Graduate Program in Materials Science and Engineering Technological Development Center Federal University of Pelotas Pelotas RS 96010‑610 Brazil. Pelotas Dental School Graduate Program in Dentistry Federal University of Pelotas Pelotas RS 96010‑560 Brazil. rafael.lund@***. Graduate Program in Materials Science and Engineering Technological Development Center Federal University of Pelotas Pelotas RS 96010‑610 Brazil. rafael.lund@***.

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An adaptive e-leaming model based on myers-briggs type indicator(MBTI) 3

An adaptive e-leaming model based on myers-briggs type indic...

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3rd International Conference on Informatics and Computing, ICIC 2018

作者： Yel, Mesra Betty Sfenrianto, Sfenrianto Meistiawan, Elisa Tri Faculty of Computer Science STI and KOM CKI Jakarta Indonesia Information Systems Management Department BINUS Graduate Program Master of Information System Management Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781538669204

Adaptive e-learning system is widely used to customize the content of teaching materials to student learning styles. This study aims to propose an adaptive e-learning model that is able to determine the MBTI learning styles of students. It can be used by the system as to provide learning materials or e-learning activities in each phase of learning. In this study, adaptive e-learning model there are learning sessions namely: Introduction, Content, Assignment, and Exercise. Each learning session is based on MBTI learning style. © 2018 IEEE.

关键词： Learning systems

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Industrial revolution 4.0 on big data adoption factors on social media users and popularity brands

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Journal of Physics: Conference Series 2021年第1期1839卷

作者： W Sardjono G Rama Putra E Selviyanti A Cholidin G Salim Information Systems Management Department BINUS Graduate Program – Master of Information Systems Management Bina Nusantara University Jakarta Indonesia 11480 Computer Science Study Program Faculty of Mathematics & Natural Sciences Pakuan University Bogor Indonesia Health Department Politeknik Negeri Jember Jember Jawa Timur Indonesia 68124 Law Studi program Faculty of Law University of Muhammadiyah Jakarta Indonesia Post Graduate Program Faculty of Economic Science University of Trisakti Jakarta Indonesia

The purpose of writing this paper is to look at how factors of big data adoption affect the users of social media and brand popularity. The method used in the writing of this paper is by using path analysis and also by doing literature study to find reference material. The results of the analysis indicate that there is influence of big data adoption factors that affect the popularity of the brand. With this research, we get big data model that influence the brand popularity.

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Specify of Estimation Using C4.5 Algorithm of Software Project Estimation at the Point of Sales Application with Cocomo II 4

Specify of Estimation Using C4.5 Algorithm of Software Proje...

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4th International Conference on science and Technology, ICST 2018

作者： Novel, Kadinar Sfenrianto, Sfenrianto Gata, Windu Nainggolan, Kaman Wahyudi, Mochamad Jakarta Indonesia Information Systems Management Department BINUS Graduate Program Master of Information Systems Management Bina Nusantara University Jakarta11480 Indonesia Master of Computer Science Postgraduate Programs STMIK Nusa Mandiri Jakarta Indonesia

ISBN: (纸本)9781538658130

In software development, it is required an appropriate estimate. One of the most commonly used software project estimation models is Constructive Cost Model(COCOMO II). The model is often used to obtain accurate results in estimating important factors such as cost and human resources. However, to obtain the more accurate estimation results, this study proposes a C4.5 algorithm based on COCOMO II estimation results. In this study, software project estimates are used in the Point of Sales (POS) applications. Based on these data with COCOMO II method, it is estimated that the schedule, staff, and cost are also specifying estimation from the result of COCOMO II using a C4.5 algorithm. The accuracy of the estimation results is around 90% with Algorithm C4.5. The value can be used as a reference for the development of the next POS software project. © 2018 IEEE.

关键词： Decision trees

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Numerical analysis of general-vibration-based method for structural health monitoring

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AIP Conference Proceedings 2020年第1期2227卷

作者： Fergyanto E. Gunawan Benfano Soewito Nico Surantha Tuga Mauritsius Nobumasa Sekishita 1Industrial Engineering Department BINUS Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia 11480 2Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 3Information Systems Management Department BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta Indonesia 11480 4Department of Mechanical Engineering Toyohashi University of Technology Toyohashi Aichi 441-8580 Japan

For damage detection, this research article discusses an easy-to-compute damage index derived from the governing dynamic of the structure that has potential practical application in Structural Health Monitoring (SHM). The research uses simplified structural models to explore the sensitivity of the index to damages, to compare the index performance with a traditional but popular damage detection method, and to understand the local/global predictive capability of the index. The research uses two simple models, namely, single- and two-degree-of-freedom systems. The results suggest that the damage index is local, that can only monitor damages occurring near the points of measurements, but it is sensitive to damages, unlike the natural frequency, which is global but less sensitive.

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Crowdsourcing annotation system of object counting dataset for deep learning algorithm 2

Crowdsourcing annotation system of object counting dataset f...

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2nd International Conference on Eco Engineering Development 2018, ICEED 2018

作者： Cenggoro, Tjeng Wawan Tanzil, Fidelson Aslamiah, Ayu Hidayah Karuppiah, Ettikan Kandasamy Pardamean, Bens Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia NVIDIA Corporation Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia

Deep Learning is currently the state-of-the-art technique for various computer Vision tasks, including object counting. Despite of its high performance, Deep Learning requires a gigantic amount of training data to show its best result. Getting this massive data in reasonable time requires a proper strategy such as crowdsourcing. However, in case of object counting, we found no crowdsourcing system able to effectively collect necessary data. To tackle this problem, we develop a crowdsourcing system to annotate image for object counting dataset. This system is also equipped with validation system to ensure the quality of collected dataset. © 2018 Institute of Physics Publishing. All rights reserved.

关键词： Crowdsourcing

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Transfer Learning from Chest X-Ray Pre-trained Convolutional Neural Network for Learning Mammogram Data 3

Transfer Learning from Chest X-Ray Pre-trained Convolutional...

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3rd International Conference on computer science and Computational Intelligence, ICCSCI 2018

作者： Pardamean, Bens Cenggoro, Tjeng Wawan Rahutomo, Reza Budiarto, Arif Karuppiah, Ettikan Kandasamy Computer Science Department BINUS Graduate Program Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia NVIDIA Corporation United States

Breast cancer is one of the deadliest cancer for female nowadays. Despite of the rapid advancement in medical image analysis with the rise of deep learning, development of breast cancer detection system is limited due to relatively small size of the publicly available mammogram dataset. In this paper, we discover an effective configuration for transfer learning from Chest X-Ray pre-trained Convolutional Neural Network to overcome the small-size mammogram dataset problem. We found that the best configuration achieve 90.38% validation accuracy for modified. © 2018 The Authors. Published by Elsevier Ltd.

关键词： Deep learning

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The accuracy of the F statistic for structural health monitoring

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AIP Conference Proceedings 2020年第1期2227卷

作者： Fergyanto E. Gunawan Benfano Soewito Nico Surantha Tuga Mauritsius Nobumasa Sekishita 1Industrial Engineering Department BINUS Graduate Program – Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia 11480 2Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 3Information Systems Management Department BINUS Graduate Program – Master of Information Systems Management Bina Nusantara University Jakarta Indonesia 11480 4Department of Mechanical Engineering Toyohashi University of Technology Toyohashi Aichi 441-8580 Japan

Understanding the reliability of engineering methods is crucial for its adoption and deployment. This research focuses on the reliability of the Power Spectral Density (PSD) method via the use of the F statistic for damage detection. To the author best knowledge, the method is rather classic but its realibility has not been discussed in the context of a large data size. Priory, the research anticipates that the accuracy is a function of the damage level. In this study, we evaluate 3500 cases with five levels of structural integrity, namely, healthy condition and damaged conditions with 1%, 5%, 10%, and 20% damage levels. The dataset is established via a numerical analysis of a seven degree-of-freedom system loaded with a concentrated dynamic force with random magnitude. A spring on the system is reduced in its stiffness to simulate damages. Our significant findings are the following: it is challenging for the PSD-based method to differentiate the healthy condition from the damaged conditions when the damage level is small. However, the reliability is high at 95% probability when the structural integrity has dropped by five percent.

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A Geoelectric Approach for Karst Groundwater Analysis

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IOP Conference Series: Earth and Environmental science 2022年第1期998卷

作者： Amallia Ferhat Taufik Seizarsyah Mohammad Prasanto Bimantio Nanda Satya Nugraha Dian Pratama Putra Teddy Suparyanto Alam Ahmad Hidayat Bens Pardamean Agribusiness Department Institute of Agricultural STIPER Yogyakarta 55282 Indonesia Geophysical Engineering Department Universitas Pembangunan Nasional 'Veteran' Yogyakarta Indonesia Agricultural Crop Technology Department Institute of Agricultural STIPER Yogyakarta 55282 Indonesia Forestry Department Institute of Agricultural STIPER Yogyakarta 55282 Indonesia Agricultural Engineering Department Institute of Agricultural STIPER Yogyakarta 55282 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Artesian well is one of the major efforts to obtain water source for fulfilling water demands in Eroniti Conservation park, Ponjong, Yogyakarta by drilling deep into several soil layers. Vertical Electrical Sounding (VES) method is the most common approach to determine the existence of groundwater. The method probes layers of rock below the ground surface based on their electrical properties, since the electrical resistivity of each layer is theoretically different. This study aims to utilize the VES approach for investigating the properties of the rock layers in the area to explore groundwater sources. We install six different VES points in the observation area using Schlumberger electrode configuration. The methodology of the work consists of three steps: the planning of the placement of the sounding points, the measurement step performed by a unit of IRIS SYSCAL Resistivity meter, and the data analysis and interpretation. Employing the resistivity analysis, we conclude that the observed region consists of Mediterranean soil as a result of weathering of limestone as well as lithology of the limestone. Furthermore, there are two types of aquifer found in the area: a perched aquifer found 27 meters below the ground surface of VES point 1 and a confined aquifer 166 meters below the ground surface of VES point 2 and 6.

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Biclustering Method to Capture the Spatial Pattern and to Identify the Causes of Social Vulnerability in Indonesia: A New Recommendation for Disaster Mitigation Policy

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Procedia computer science 2019年 157卷 31-37页

作者： Puspita Anggraini Kaban Robert Kurniawan Rezzy Eko Caraka Bens Pardamean Budi Yuniarto Sukim Computational Statistics Department Polytechnic of Statistics - STIS Jakarta 13330 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Indonesia College of Informatics Chaoyang University of Technology Taichung City 41349 Taiwan (R.O.C.) Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Geographically, Indonesia is a meeting point of three continental plates. Scilicet, the Eurasian Plate, the Indo-Australian Plate, and the Pacific Plate. Therefore, Indonesia is part of the infamous volcanic zone called the ”Ring of Fire” and one of the areas prone to natural disasters such as volcanic eruptions, earthquakes, tsunamis, floods, and landslides. This study aims to capture the spatial pattern and identify the causes of social vulnerability in the districts/cities in Indonesia using the biclustering method. The data is extracted from the Indonesian National Socio-Economic Survey (SUSENAS) by BPS-Statistics in 2014. The biclustering result indicates that each district/city has its own social vulnerability characteristics and shows that the vulnerable aspects of each district/city are different. The adjacent observations tend to have social vulenrability characteristics. The results of this study can be used as a reference for national disaster mitigation policy in Indonesia.

关键词： biclustering disaster mitigation social vulnerability SoVI spatial pattern

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