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Human Anatomy Learning Systems Using Augmented Reality on Mobile Application

Procedia computer science 2018年 135卷 80-88页

作者： Michael H Kurniawan Suharjito Diana Gunawan Witjaksono Computer Science Department BINUS Graduate Program- Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Students generally experience difficulties in learning human body anatomy due to constraints to visualize the body anatomy from 2D into 3D image. This research aims to develop a human anatomy learning system using augmented reality technology. By using this system, it is expected that students can easily understand the anatomy of the human body using a 3D image visualization. The method used in this system is augmented reality marker on mobile computing platform. The marker is captured by taking a picture. Then, the captured image is divided into pieces and the pattern is matched with images stored in the database. In this research, we use Floating Euphoria Framework and combine it with the SQLite database. Augmented reality anatomy system of the human body has features that can interactively display the whole body or parts of the human organs. To evaluate the usefulness of the application, we tested the augmented reality anatomy system with high school students and medical students for learning the anatomy of the human body. The results show that the human anatomy learning system with interactive augmented reality visualization helps students learn human anatomy more easily.

关键词： Augmented Reality Human Anatomy Learning Android Application

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Waiting-Time Estimation in Bank Customer Queues using RPROP Neural Networks

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Procedia computer science 2018年 135卷 35-42页

作者： Rinda Parama Satya Hermanto Suharjito Diana Ariadi Nugroho Computer Science Department BINUS Graduate Program- Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480

In daily banking customer queues, unknown waiting-time could lower customer experience. Little’s Law formula in Queue Theory provides a generic formula for waiting-time, but it cannot be implemented directly to give finite wait-time estimation in real-life. This study aims to investigate predictive variables that explain waiting-time duration. This paper uses Fast Artificial Neural Network engine to implement Artificial Neural Networks method. To train Artificial Neural Networks, Resilient Propagation was used. Time-series approach and structural approach for input neuron was compared. Average duration from previous interval and number of server was proposed to increase structural variable like Queue Length and Head of Line Duration estimator variable. To determine the best configuration for number of neuron in input and hidden layer, experimental method was used. The results of this study show that structural approach provides better estimation than time-series approach. Furthermore, modified helper variable combination provides a more refined result.

关键词： waiting-time estimation neural networks time-series queue

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Measuring the quality of various version an object-oriented software utilizing CK metrics 1

Measuring the quality of various version an object-oriented ...

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1st International Conference on Information and Communications Technology, ICOIACT 2018

作者： Binanto, Iwan Warnars, Harco Leslie Hendric Spits Gaol, Ford Lumban Abdurachman, Edi Soewito, Benfano Informatics Department Faculty of Scence and Engineering Sanata Dharma University Yogyakarta55002 Indonesia Computer Science Department BINUS Graduate Program - Doctor Computer Science Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781538609545

There are many object-oriented software quality measurement techniques. One of them is CK metric. This paper utilizes CK metrics to measure qualities per version of an open source software namely Statcato. Measurements are done in each class, each version of the software. The measurement is used to analyze the quality of the software. This paper concludes that the quality of software has improved during its lifecycle, although its features increase. © 2018 IEEE.

关键词： Open source software

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Comparing CART and C5.0 algorithm performance of human development index 3

Comparing CART and C5.0 algorithm performance of human devel...

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3rd International Conference on Informatics and Computing, ICIC 2018

作者： Assiroj, Priati Warnars, Harco Leslie Hendric Spits Fauzi, Ahmad Dept. of Information System Faculty of Technology and Computer Science Buana Perjuangan University Karawang Indonesia Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Dept. of Computer Science Faculty of Technology and Computer Science Buana Perjuangan University Karawang Indonesia

ISBN: (纸本)9781538669204

Human Development Index (HDI) is a reference to how far the administration can develops their people. The development of a territory is related to a prosperity of the people. This research is focused on Human Development Index in West Java, a Province of Indonesia. Research identifies variables which are influence and very important to HDI and compares the model of CART and C5.0 algorithm based on HDI concept that has developed by United Nation (UN). Research uses 14 variables which are commonly used for measuring HDI and found that there are two variables that most influencing to HDI, MYS-index and EDU-Index. By knowing the MYS and EDU-Index research can predict and classify each territory to its HDI. Research could be conducted to predict HDI in the other territory. The results evaluated by measuring the accuracy and confusion matrix, 91.35 for CART algorithm and 90.80 for C5.0 algorithm. © 2018 IEEE.

关键词： Algorithm Classification Comparison EDU-Index Human Development Index (HDI) MYS-Index Territory

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A Model Configuration of Social Media Text Mining for Projecting the Online-Commerce Transaction (Case: Twitter Tweets Scraping)

A Model Configuration of Social Media Text Mining for Projec...

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International Conference on Cyber and IT Service Management (CITSM)

作者： Emil Robert Kaburuan Ang Swat Lin Lindawati Surjandy Siswantini Muhammad Ryanda Putra Ditdit Nugeraha Utama BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta Indonesia Faculty of Economics and Communication Bina Nusantara University Jakarta Indonesia School of Information Systems Bina Nusantara University Jakarta Indonesia UIN Syarif Hidayatullah Jakarta Indonesia BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

Text mining is a process to extract data based on text. The source of text mining should be coming from social media users' activities; e.g. posting, fans page, group, hashtag, tweet, etc. As raw data and information, the text mining sources are able to be gold information to be operated for academic analyzing purposes. This paper proposes the Python-based model to scrape text from Twitter user's tweets and then analyze them to see the commerce and tax-income potency in purposely Indonesia. The mathematical and statistical methods are technically operated. The constructed model finally exhibited. Also, the information on sale-behavior and tax-income forecasts are able to be portrayed.

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Mitigating errors in mobile-based dietary assessments: Effects of a data modification process on the validity of an image-assisted food and nutrition app

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Nutrition 2023年 116卷 112212-112212页

作者： Ho, Dang Khanh Ngan Chiu, Wan-Chun Kao, Jing-Wen Tseng, Hsiang-Tung Yao, Chih-Yuan Su, Hsiu-Yueh Wei, Pin-Hui Le, Nguyen Quoc Khanh Nguyen, Hung Trong Chang, Jung-Su School of Nutrition and Health Sciences College of Nutrition Taipei Medical University Taipei Taiwan Department of Nutrition Wan Fang Hospital Taipei Medical University Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Dietetics Taipei Medical University Hospital Taipei Taiwan Professional Master Program in Artificial Intelligence in Medicine College of Medicine Taipei Medical University Taipei Taiwan Research Center for Artificial Intelligence in Medicine Taipei Medical University Taipei Taiwan Translational Imaging Research Center Taipei Medical University Hospital Taipei Taiwan Department of Adult Nutrition Counselling National Institute of Nutrition Hanoi Viet Nam Department of Clinical Nutrition and Dietetics National Hospital of Endocrinology Hanoi Viet Nam Graduate Institute of Metabolism and Obesity Sciences College of Nutrition Taipei Medical University Taipei Taiwan Nutrition Research Center Taipei Medical University Hospital Taipei Taiwan Chinese Taipei Society for the Study of Obesity (CTSSO) Taipei Taiwan TMU Research Center for Digestive Medicine Taipei Medical University Taipei Taiwan

Objective: Mobile nutrition applications (apps) provide a simple way for individuals to record their diet, but the validity and inherent errors need to be carefully evaluated. The aim of this study was to assess the validity and clarify the sources of measurement errors of image-assisted mobile nutrition apps. Methods: This was a cross-sectional study with 98 students recruited from School of Nutrition and Health sciences, Taipei Medical University. A 3-d nutrient intake record by Formosa Food and Nutrient Recording App (FoodApp) was compared with a 24-h dietary recall (24-HDR). A two-stage data modification process, manual data cleaning, and reanalyzing of prepackaged foods were employed to address inherent errors. Nutrient intake levels obtained by the two methods were compared with the recommended daily intake (DRI), Taiwan. Paired t test, Spearman's correlation coefficients, and Bland–Altman plots were used to assess agreement between the FoodApp and 24-HDR. Results: Manual data cleaning identified 166 food coding errors (12%;stage 1), and 426 food codes with missing micronutrients (32%) were reanalyzed (stage 2). Positive linear trends were observed for total energy and micronutrient intake (all P_trend < 0.05) after the two stages of data modification, but not for dietary fat, carbohydrates, or vitamin D. There were no statistical differences in mean energy and macronutrient intake between the FoodApp and 24-HDR, and this agreement was confirmed by Bland–Altman plots. Spearman's correlation analyses showed strong to moderate correlations (r = 0.834 ∼ 0.386) between the two methods. Participants’ nutrient intake tended to be lower than the DRI, but no differences in proportions of adequacy/inadequacy for DRI values were observed between the two methods. Conclusions: Mitigating errors significantly improved the accuracy of the Formosa FoodApp, indicating its validity and reliability as a self-reporting mobile-based dietary assessment tool. Dietitians a

关键词： Food records Mobile application Mobile health Smartphone application

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Health Assistant Wearable-Based Data science System Model: A Pilot Study 3

Health Assistant Wearable-Based Data Science System Model: A...

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3rd International Conference on Information Management and Technology, ICIMTech 2018

作者： Budiarto, Arif Febriana, Trisna Suparyanto, Teddy Caraka, Rezzy Eko Pardamean, Bens Computer Science Department Bina Nusantara University School of Computer Science Jakarta11480 Indonesia Information Systems Department Bina Nusantara University School of Information Systems Jakarta11480 Indonesia Bina Nusantara University Bioinformatics and Data Science Research Center Indonesia Faculty of Science National University of Malaysia School of Mathematical Science Bangi43000 Malaysia Computer Science Department Bina Nusantara University BINUS Graduate Program-Master of Computer Science Jakarta11480 Indonesia

ISBN: (纸本)9781538658215

The rapid development of Information and Communication Technology (ICT) has an impact on the innovation of new technology that gives benefits for health. One of its latest development is wearable device technology. Nowadays, the growth of this technology market is very positive. But unfortunately the growth of this technology is not followed by the availability of supporting applications that provide maximum benefits for users by utilizing personal health and activity data. This paper is intended to provide a report of our initial research in developing a health assistant solution that utilizes wearable device generated data. The whole research process is executed using Design Thinking approach that put the users as the main consideration. This initial research is started by designing a field research that can potentially gathered users' data generated from wearable device. A series of statistical and machine learning techniques are presented to analyze time series data to create a model. Finally, to implement the model, a mobile application prototype is also proposed. The outcomes from this initial research will be used to develop a fully working solution. © 2018 IEEE.

关键词： Learning systems

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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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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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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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