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

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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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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Stakeholder Act as an IT and General Compliance Auditor

Stakeholder Act as an IT and General Compliance Auditor

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International Conference on Sustainable information Engineering and Technology (SIET)

作者： Surjandy Erick Fernando Meyliana Raymond Kosala Suhono Harso Supangkat Diani Dwiningrum Merry Marshela Angelica Renita Amalia Information Systems Audit Program Information Systems Department Bina Nusantara University Jakarta Indonesia Information Systems Departement Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia

ISBN: (纸本)9781538674086;9781538674079

Recently, the Indonesian government requires auditors, the need for auditors around 40,000 auditors in 2016, currently has only about 10,800 auditors, however, the lack of the auditors impacting the risk of financial loss for the state. Referring to the problem, this experimental research was conducted. The experiment of the research was conducted two times and the audit topic is a compliance audit in the year 2017 and year 2018. The goal of this research is to know, can the stakeholder act as an IT and general compliance auditor? The experiment was conducted by 8 university students in 2017 and 19 university students in 2018, and the supporting tools of audit activities the university student use the smartphone to capture the object as evidence. The experiment results with descriptive method show university students can act as an auditor and found several pieces of evidence that might cause future impact to the institution.

关键词： Regulation Stakeholders Companies Libraries Finance

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Author Correction: The high-dimensional space of human diseases built from diagnosis records and mapped to genetic loci

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Nature computational science 2023年第7期3卷 658页

作者： Gengjie Jia Yu Li Xue Zhong Kanix Wang Milton Pividori Rabab Alomairy Aniello Esposito Hatem Ltaief Chikashi Terao Masato Akiyama Koichi Matsuda David E Keyes Hae Kyung Im Takashi Gojobori Yoichiro Kamatani Michiaki Kubo Nancy J Cox James Evans Xin Gao Andrey Rzhetsky Shenzhen Branch Guangdong Laboratory of Lingnan Modern Agriculture Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs Agricultural Genomics Institute at Shenzhen Chinese Academy of Agricultural Sciences Shenzhen China. jiagengjie@***. Computational Bioscience Research Center King Abdullah University of Science and Technology Thuwal Saudi Arabia. Computer Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia. Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong People's Republic of China. Department of Medicine and Vanderbilt Genetics Institute Vanderbilt University Medical Center Nashville TN US. Department of Medicine Institute of Genomics and Systems Biology Committee on Genomics Genetics and Systems Biology University of Chicago Chicago IL US. Department of Operations Business Analytics and Information Systems University of Cincinnati Cincinnati OH US. Department of Systems Pharmacology and Translational Therapeutics Perelman School of Medicine University of Pennsylvania Philadelphia PA US. Extreme Computing Research Center Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia. College of Computer Science and Engineering University of Jeddah Jeddah Saudi Arabia. HPE HPC/AI EMEA Research Laboratory Bristol UK. RIKEN Center for Integrative Medical Sciences Yokohama Japan. Clinical Research Center Shizuoka General Hospital Shizuoka Japan. Department of Applied Genetics The School of Pharmaceutical Sciences University of Shizuoka Shizuoka Japan. Department of Ophthalmology Graduate School of Medical Sciences Kyushu University Fukuoka Japan. Department of Computational Biology and Medical Sciences Graduate School of Frontier Sciences The University of Tokyo Tokyo Japan. Biological and Environmenta

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Classification of Land Cover from Sentinel-2 Imagery Using Supervised Classification Technique (Preliminary Study)

Classification of Land Cover from Sentinel-2 Imagery Using S...

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International Conference on information Management and Technology (ICIMTech)

作者： Eka Miranda Achmad Benny Mutiara Ernastuti Wahvu Catur Wibowo Information Systems Department Doctoral Program in Information Technology Gunadarma University Jakarta Indonesia Faculty of Computer Science and Information Technology Gunadarma University Jakarta Indonesia Computer Science Faculty Universitas Jakarta Indonesia

This paper intended to classify land cover of high-resolution satellite image using supervised classification method. The object of this research was the land cover image of the central java area in Indonesia which chosen as an area observed with the cloud cover consideration. The Satellite image was obtained from Sentinel-2 through https://***. Supervised Classification and ArcMap 10.5 was used to classified image object. This research classified the land cover into four classifications class namely Water, Forest, Urban and Bare Land due to show the main classes in the Land Cover Classification of RSNI-l National Standardization Body of Indonesia, RSNI-l was used as reference for classification process. The confusion matrix used to calculate classification accuracy value. Subsequently, confusion matrix results compared to the truth information. The truth information was derived from the actual value of RASTERVALUE obtained from Google Earth. This research shown supervised classification maximum-likelihood classification has been classified land cover into four class (forest, water body, urban and bare land) with overall accuracy = 1 and kappa value = 0.4896. This result showed this research got moderate kappa accuracy value but high overall accuracy value. High accuracy value reached due to fully supervised experiment during classification process.

关键词： Satellites Forestry Training Java Probability Standardization Vegetation mapping

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Development Conceptual Model and Validation Instrument for E-Learning Succes Model at Universities in Indonesia: Perspectives influence of Instructor's Activities and Motivation

Development Conceptual Model and Validation Instrument for E...

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International Congress on Applied information Technology

作者： Titan Erick Fernando Dina Fitria Murad Harco Leslie Hendric Spits Warnars Kristianus Oktriono BINUS Online Learning Bina Nusantara University Jakarta Indonesia School of Information Systems Bina Nusantara University Jakarta Indonesia BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Language Center Faculty of Humanities Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781728158624

ISBN: (纸本)9781728158631

The purpose of this study is to develop conceptual models and validation instruments for the success of e-learning systems in Indonesian universities from factors that influence instructor activity and user motivation. Model development is based on the IS success model of DeLone and Mclean by adding instructor activity and motivational variables based on related literature studies. Evaluation is done by testing the reliability and validity of the instrument. Data collection by distributing instruments online with the snowball method, respondents obtained were 234 used as data analysis with SmartPLS 2.0 software. The results of this study produced a conceptual model consisting of 9 variables and 83 instruments which were validated according to the provisions. From these results, it can be implemented in future research by increasing larger respondents to get results that represent the success of e-learning systems at universities in Indonesia.

关键词： Electronic learning information systems Instruments Reliability Learning systems Organizations Computational modeling

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Proposal of an integrated decision support system for Tuberculosis based on Semantic Web

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Procedia computer Science 2019年 164卷 552-558页

作者： Vinícius Lima Felipe Pellison Filipe Bernardi Isabelle Carvalho Rui Rijo Domingos Alves Bioengineering Postgraduate Program University of Sao Paulo Sao Carlos Brazil Institute of Mathematical and Computer Sciences University of Sao Paulo Sao Carlos Brazil School of Technology and Management Polytechnic Institute of Leiria Leiria Portugal Centre for Research in Health Technologies and Information Systems (CINTESIS) University of Porto Porto Portugal Institute for Systems and Computers Engineering at Coimbra (INESCC) Coimbra Portugal Ribeirão Preto Medical School University of Sao Paulo Ribeirao Preto Brazil

Epidemiological surveillance of Tuberculosis (TB) requires a strong integration of different health services, programs and levels of care. The deepening and broadening of data management techniques must be constantly carried out to increase the integrality of healthcare. Otherwise, knowledge extraction and clinical and administrative decision-making processes are significantly hampered, directly affecting the management and quality of health services. Thus, this work aims to establish a computerized decision support system capable of collecting, integrating and sharing TB health data in Brazilian Unified Public Health System. Also, it will allow the monitoring of infected patients and the visualization of consolidated information of regular TB and its resistant variants for health professionals and managers. The data will be made available from heterogeneous, disconnected and unstructured sources by combining traditional web services, Semantic Web resources and security algorithms. A solid knowledge base applied to epidemiological surveillance, health information governance and clinical support will be enabled to integrate the multiple areas of TB patients care, as well as to support the creation of more accurate operational and diagnostics models.

关键词： Tuberculosis Decision Support System Health information System Health information Management Semantic Web

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Data-Driven Two-Stage Framework for Identification and Characterization of Different Antibiotic-Resistant Escherichia coli Isolates Based on Mass Spectrometry Data

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Microbiology spectrum 2023年第3期11卷 e0347922页

作者： Chia-Ru Chung Hsin-Yao Wang Chun-Han Yao Li-Ching Wu Jang-Jih Lu Jorng-Tzong Horng Tzong-Yi Lee Department of Computer Science and Information Engineering National Central University Taoyuan Taiwan. Department of Laboratory Medicine Chang Gung Memorial Hospital at Linkou Taoyuan Taiwan. Ph.D. Program in Biomedical Engineering Chang Gung University Taoyuan Taiwan. Department of Biomedical Sciences and Engineering National Central University Taoyuan Taiwan. College of Medicine Chang Gung University Taoyuan Taiwan. Department of Medical Biotechnology and Laboratory Science Chang Gung University Taoyuan Taiwan. Department of Bioinformatics and Medical Engineering Asia University Taichung Taiwan. Institute of Bioinformatics and Systems Biology National Yang Ming Chiao Tung University Hsinchu Taiwan.

In clinical microbiology, matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) is frequently employed for rapid microbial identification. However, rapid identification of antimicrobial resistance (AMR) in Escherichia coli based on a large amount of MALDI-TOF MS data has not yet been reported. This may be because building a prediction model to cover all E. coli isolates would be challenging given the high diversity of the E. coli population. This study aimed to develop a MALDI-TOF MS-based, data-driven, two-stage framework for characterizing different AMRs in E. coli. Specifically, amoxicillin (AMC), ceftazidime (CAZ), ciprofloxacin (CIP), ceftriaxone (CRO), and cefuroxime (CXM) were used. In the first stage, we split the data into two groups based on informative peaks according to the importance of the random forest. In the second stage, prediction models were constructed using four different machine learning algorithms-logistic regression, support vector machine, random forest, and extreme gradient boosting (XGBoost). The findings demonstrate that XGBoost outperformed the other four machine learning models. The values of the area under the receiver operating characteristic curve were 0.62, 0.72, 0.87, 0.72, and 0.72 for AMC, CAZ, CIP, CRO, and CXM, respectively. This implies that a data-driven, two-stage framework could improve accuracy by approximately 2.8%. As a result, we developed AMR prediction models for E. coli using a data-driven two-stage framework, which is promising for assisting physicians in making decisions. Further, the analysis of informative peaks in future studies could potentially reveal new insights. Based on a large amount of matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) clinical data, comprising 37,918 Escherichia coli isolates, a data-driven two-stage framework was established to evaluate the antimicrobial resistance of E. coli. Five antibiotics, including a

关键词： MALDI-TOF MS antimicrobial resistance cephalosporin cephalosporins fluoroquinolones machine learning matrix-assisted laser desorption ionization–time of flight mass spectrometry penicillin penicillins

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Performance comparison of CATA's information retrieval system application vs WTS

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Journal of Physics: Conference Series 2019年第1期1367卷

作者： Jajang Jaya Purnama Sri Rahayu Sfenrianto Fitra Septia Nugraha Ridan Nurfalah Hendri Mahmud Nawawi Muhammad Ja'far Shidiq Nurul Ichsan Haerul Fatah Master of Computer Science-Postgraduate Program STMIK Nusa Mandiri Jakarta Indonesia Information Systems Management Department BINUS Graduate Program – Master of Information Systems Management Bina Nusantara University Indonesia Information Systems Bina Sarana Informatika University Indonesia

Searching for data or documents that are always a necessity in the world of education, work, research an others requires convenience so that time efficiency occurs. This is supported by the emergence of various information Retrieval system applications, one of which is cata, which is built on the Java programming language and applies the Generalized Vector Space Model method which can search based on similar keywords. Other facilities need to be developed, one of which is by applying the stemmer porter algorithm applied to the WTS (Web Tokenization Stemming) web which is built with the laravel framework that can search data or documents simply by typing the basic words so that searches are easier and faster.

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Development of a Web Based Corruption Case Mapping Using Machine Learning with Artificial Neural Network 3

Development of a Web Based Corruption Case Mapping Using Mac...

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

作者： Noerlina Dewanti, Retno Mursitama, Tirta Nugraha Fairianti, Sheila Putri Kristin, Desi Maya Sasmoko Muqsith, Andi Muhammad Krishti, Nathasya Shesilia Makalew, Brillv Andro Information Systems Department Bina Nusantara University School of Information Systems Jakarta11480 Indonesia Management Department Bina Nusantara University BINUS Business School Undergraduate Program Jakarta11480 Indonesia International Relations Department Faculty of Humanities Bina Nusantara University Jakarta11480 Indonesia Psychology Department Faculty of Humanities Bina Nusantara University Jakarta11480 Indonesia Primary Teacher Education Department Faculty of Humanities Bina Nusantara University Jakarta11480 Indonesia Computer Science Department Bina Nusantara University School of Computer Science Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Mobile Application Technology Program Jakarta11480 Indonesia

ISBN: (纸本)9781538658215

Cumulative state loss over the years caused by corruption in Indonesia has reached a fantastic number of 15 Billion usn up until 2016 [1]. To imagine the severances of it, 10.000 KM of highway can be built with that much amount of fund. Several responses has been done by Indonesian government to fight corruption from both prevention and persecution. This work focuses on the development of a web application aimed to provide insight to corruption case per province in Indonesia. The web application was developed using Machine Learning, specifically Backpropagation Artificial Neural Network (ANN). Web crawling and web scraping techniques are used to gather news content from 7 major news portal in Indonesia. Accuracy is measured by comparing correct prediction by ANN to its true value. Upon finding corruption news, data is saved and further analysis is done to establish the number of corruption news per region. Finally, the output is visualized using Google Map API. The purpose of this work is to provide regional depiction of corruption case to give further insight to be used by decision makers. Upon using this web application, objectivity of program development is expected to increase. The final output of the web application is a map of corruption case in Indonesia per region. The accuracy of ANN used in this work to classify corruption and non-corruption news is 96.91 % using Sigmoid Activation Function. © 2018 IEEE.

关键词： Neural networks

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