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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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Implementation on Indonesian property real estate industry based on service oriented architecture

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IOP Conference Series: Materials Science and Engineering 2020年第1期725卷

作者： Ahmad Nurul Fajar Nunung Nurul Qomariyah Albert Baihaqi Siregar Information Systems Management Department BINUS Graduate Program-Master of Information Systems Management Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department Faculty of Computing and Media Bina Nusantara University Jakarta Indonesia 11480 Department of Information Technology Universitas Sumatera Utara Medan Indonesia

This study focuses on the implementation of business property in real estate market. This is due to inability of the current technology to support the property products. Some people feel uncomfortable to buy houses from the online market. Buyers need to be very careful to deal with the sellers as the houses price is considered quite expensive. On the other hand, improving real estate market is still a challenge. This business still needs a physical representation, although it can be sold from the online market. In this paper, we propose the Service Oriented Architecture (SOA) system of virtual reality and drone. We use drone to help scanning the property units and then make 3D models with visual mapping so it can be run in a virtual reality environment, video 360. In real estate, business process can be developed in various ways. Our proposed SOA in this study can be used to integrate all of them.

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Web Application Vulnerability Detection Using Taint Analysis and Black-box Testing

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IOP Conference Series: Materials Science and Engineering 2020年第1期879卷

作者： Heribertus Yulianton Agung Trisetyarso Wayan Suparta Bahtiar Saleh Abbas Chul Ho Kang Computer Science Department Binus Graduate Program | Doctor of Computer Science Bina Nusantara University West Jakarta Indonesia Faculty of Information Technology Universitas Stikubank Semarang Department of Informatics Universitas Pembangunan Jaya

Web applications continue to grow however web attacks are also increasing, this shows an increase in web application vulnerabilities. Several methods have been used to detect vulnerabilities in web applications such as black-box testing, dynamic analysis, and static analysis. In this article, we propose a framework for detecting web application vulnerabilities by combining all three methods. The strengths of one method are used to overcome the weaknesses of another method. This framework is believed to provide better results than if each method was used separately.

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The Accuracies of ANFIS and Genetic Algorithm with Tournament Selection on Classifying Hepatitis Data

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Journal of Physics: Conference Series 2020年第1期1566卷

作者： W FA Siahaan O S Sitompul Z Situmorang Graduate Program of Computer Science Universitas Sumatera Utara Medan Indonesia Department of Information Technology Universitas Sumatera Utara Medan Indonesia Department of Computer Science Universitas Katolik Santo Thomas Medan Indonesia

Classification is an important technique in data mining to create patterns and data modeling. Hepatitis is a disease that is dangerous to humans as this disease affects the human liver which is a vital organ. Early detection of hepatitis by diagnosing its occurrence on patients is needed to give them help, care, and treatment. Therefore, a classification technique is required to create patterns and models of data. To achieve accuracy in classifying hepatitis there would be requirements to separate relevant from irrelevant features. By only considering relevance features in classifying hepatitis, it is expected that the classification process will be faster, easier, and more accurate. In this research, the ANFIS algorithm and genetic algorithm are used in classifying the diagnosis of hepatitis based on a dataset from the UCI data mining repository. Results obtained showed that the genetic algorithm gave a slightly higher accuracy of 98.73% compared to 86.67% results obtained using ANFIS.

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Speech Enhancement Based on Bayesian Low-Rank and Sparse Decomposition of Multichannel Magnitude Spectrograms

Speech Enhancement Based on Bayesian Low-Rank and Sparse Dec...

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作者： Bando, Yoshiaki Itoyama, Katsutoshi Konyo, Masashi Tadokoro, Satoshi Nakadai, Kazuhiro Yoshii, Kazuyoshi Kawahara, Tatsuya Okuno, Hiroshi G. Graduate School of Informatics Kyoto University Kyoto606-8501 Japan Graduate School of Information Science Tohoku University Sendai980-8579 Japan Tokyo Institute of Technology Saitama351-0114 Japan Honda Research Institute Japan Co. Ltd Wako351-0188 Japan Graduate Program for Enbodiment Informatics Waseda University Tokyo169-0072 Japan

This paper presents a blind multichannel speech enhancement method that can deal with the time-varying layout of microphones and sound sources. Since nonnegative tensor factorization (NTF) separates a multichannelmagnitude (or power) spectrogram into source spectrograms without phase information, it is robust against the time-varying mixing system. This method, however, requires prior information such as the spectral bases (templates) of each source spectrogram in advance. To solve this problem, we develop a Bayesian model called robust NTF (Bayesian RNTF) that decomposes a multichannel magnitude spectrogram into target speech and noise spectrograms based on their sparseness and low rankness. Bayesian RNTF is applied to the challenging task of speech enhancement for a microphone array distributed on a hose-shaped rescue robot. When the robot searches for victims under collapsed buildings, the layout of themicrophones changes over time and some of them often fail to capture target speech. Our method robustly works under such situations, thanks to its characteristic of time-varying mixing system. Experiments using a 3-m hose-shaped rescue robot with eight microphones show that the proposed method outperforms conventional blind methods in enhancement performance by the signal-to-noise ratio of 1.03 dB. © 2017 IEEE.

关键词： Microphones

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Warding off the plagiarism with the applications (Case study at Bina Nusantara University student and faculty member) 1

Warding off the plagiarism with the applications (Case study...

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1st International Conference on information and Communications technology, ICOIACT 2018

作者： Surjandy Suparta, Wayan Trisetyarso, Agung Kang, Chul Ho Abbas, Bahtiar Saleh Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Information Systems Audit Program Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Civil Engineering Department University of Technology Yogyakarta Yogyakarta Indonesia Department of Electronics and Communication Engineering Kwangwoon University Korea Republic of Department of Industrial Engineering Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781538609545

Plagiarism in the education sector is as serious issues. In 2015 Indonesia ministry of research, technology and higher education stated to eradicate the plagiarism, and after 2 years the similar statement by Indonesia ministry of research, technology, and higher education. The plagiarism becomes the serious program by the ministry. The plagiarism in higher education happened, the faculty member or even a professor found did the plagiarism. Therefore, this paper research conducted using descriptive analysis methodology to elaborate on deep the correlation plagiarism variables. Hence, warding off the plagiarism might possible to perform using the applications. The aim of this research to find the correlation variables that might use to ward off the plagiarism in the future. The very interesting result from 15 questioners and the report shows there are several significant correlation variables of the plagiarism. © 2018 IEEE.

关键词： Intellectual property

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Bridge Sub Structure Defect Inspection Assistance by using Deep Learning

Bridge Sub Structure Defect Inspection Assistance by using D...

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IEEE International Conference on Awareness Science and technology

作者： Pravee Kruachottikul Kittikul Kovitanggoon Nagul Cooharojananone Donnaphat Trakulwaranont Gridsada Phanomchoeng Kanokwan Atchariyachanvanich Thira Chavarnakul Technopreneurship and Innovation Management Program Graduate School Chulalongkorn University Bangkok Thailand Department of Mathematics and Computer Science Chulalongkorn University Bangkok Thailand Department of Mechanical Engineering Chulalongkorn University Bangkok Thailand Department of Commerce Chulalongkorn University Bangkok Thailand Faculty of Information Technology King Mongkut’s Institute of Technology Ladkrabang Bangkok Thailand

Road transportation is the most popular transportation in Thailand, which the top two highest traffic are the region-to-region highways;and then inter-city highways. Therefore, the regular maintenance is required to maintain the good condition due to road safety. The most significant process of bridge inspection procedures is sub structure inspection, which requires visual inspection as an initial step. This process is used to quick determine the damage severity i.e. appearance and crack that may cause damage to the structure strength. The current process requires that the experienced maintenance engineer to be on the field in order to visual inspect and estimate whether the maintenance is required. Yet, due to the limitation of number of expert engineers to be on the field, the photo verification is introduced to assist them so that they are no need on every inspection site. However, using human to verify has no standard and uncontrollable. They need to have experience and good knowledge. As well as it is highly depended on individual decisionmaking skill. Thus, in this paper, the deep learning technique will be presented to assist the expert for quality inspection process of bridge sub structure images. That is using image enhancement and then image splitting and overlapping for image pre-processing. After that applying CNNs for object classification. As a result, the total accuracy is 89% based on 3926 dataset.

关键词： Bridges Inspection Machine learning Maintenance engineering Convolution Training Concrete

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Use of machine learning algorithms to determine the relationship between air pollution and cognitive impairment in Taiwan

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Ecotoxicology and environmental safety 2024年 284卷 116885页

作者： Cheng-Hong Yang Chih-Hsien Wu Kuei-Hau Luo Huang-Chih Chang Sz-Chiao Wu Hung-Yi Chuang Department of Information Management Tainan University of Technology Tainan 71002 Taiwan Department of Electronic Engineering National Kaohsiung University of Science and Technology Kaohsiung 80778 Taiwan Ph. D. Program in Biomedical Engineering Kaohsiung Medical University Kaohsiung 80708 Taiwan School of Dentistry Kaohsiung Medical University Kaohsiung 80708 Taiwan Drug Development and Value Creation Research Center Kaohsiung Medical University Kaohsiung 80708 Taiwan. Electronic address: chyang@nkust.edu.tw. Department of Electronic Engineering National Kaohsiung University of Science and Technology Kaohsiung 80778 Taiwan. Electronic address: F108152123@nkust.edu.tw. Graduate Institute of Medicine College of Medicine Kaohsiung Medicine University Kaohsiung 80708 Taiwan. Electronic address: u107800007@kmu.edu.tw. Divisions of Pulmonary & Critical Care Medicine Department of Internal Medicine Kaohsiung Chang Gung Memorial Hospital Chang Gung University College of Medicine Kaohsiung 83341 Taiwan Ph.D Program in Environmental and Occupational Medicine and Research Center for Environmental Medicine College of Medicine Kaohsiung Medical University Kaohsiung 80708 Taiwan. Electronic address: kuan2101@yahoo.com.tw. Epidemiology in the Public Health Program College of Health Oregon State University Oregon 97331 USA. Electronic address: wusz550@***. Graduate Institute of Medicine College of Medicine Kaohsiung Medicine University Kaohsiung 80708 Taiwan Ph.D Program in Environmental and Occupational Medicine and Research Center for Environmental Medicine College of Medicine Kaohsiung Medical University Kaohsiung 80708 Taiwan Department of Public Health and Environmental Medicine School of Medicine College of Medicine Kaohsiung Medical University Kaohsiung 80708 Taiwan Department of Occupational and Environmental Medicine Kaohsiung Medicine University Hospital Kaohsiung Medicine University Kaohsiung 80708 Taiwan. Electronic address: ericch@kmu.edu.tw.

Air pollution has become a major global threat to human health. Urbanization and industrialization over the past few decades have increased the air pollution. Plausible connections have been made between air pollutants and dementia. This study used machine learning algorithms (k-nearest neighbors, random forest, gradient-boosted decision trees, eXtreme gradient boosting, and CatBoost) to investigate the association between cognitive impairment and air pollution. Data from the Taiwan Biobank and 75 air-pollution-monitoring stations in Taiwan were analyzed to determine individual levels of exposure to air pollutants. The pollutants examined were particulate matter with a diameter of ≤ 2.5 μm (PM), nitrogen dioxide, nitric oxide, carbon monoxide, and ozone. The results revealed that the most strongly correlated with cognitive impairment were ozone, PM, and carbon monoxide levels with adjustment of educational level, age, and household income. The model based on these factors achieved accuracy as high as 0.97 for detecting cognitive impairment, indicating a positive association between air pollutions and cognitive impairment.

关键词： Air pollution Carbon monoxide Cognitive impairment Dementia Ozone PM(2.5)

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A fuzzy expert system-based adaptive learning approach to improving students’ learning performances by considering affective and cognitive factors

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Computers and Education: Artificial Intelligence 2020年 1卷

作者： Hwang, Gwo-Jen Sung, Han-Yu Chang, Shao-Chen Huang, Xing-Ci Graduate Institute of Digital Learning and Education National Taiwan University of Science and Technology 43 Sec.4 Keelung Rd. Taipei106 Taiwan Department of Allied Health Education and Digital Learning National Taipei University of Nursing and Health Sciences No.365 Ming-te Road Peitou District Taipei City Taiwan Department of International Bachelor Program in Informatics and the Department of Information Communication Yuan Ze University No. 135 Yuandong Rd. Zhongli Dist. Taoyuan City320 Taiwan

Scholars have indicated the importance of providing guidance and support for individual learners. In the past decades, most studies have developed adaptive learning systems to address this issue mainly based on students’ cognitive status, such as their learning achievements. However, several educators have pointed out the need to take learners’ affective status into account. Therefore, this study proposed an expert system approach by taking into account both the affective and cognitive status of individual learners. An adaptive learning system was implemented based on the proposed approach. In addition, an experiment was conducted in a fifth-grade Mathematics course to compare the learning performances and perceptions of the students who learned with the adaptive learning system with affective and cognitive status analysis, a cognitive-status-based adaptive learning system, and a conventional learning system. The ANCOVA results revealed that the adaptive learning model with the affective and cognitive performance analysis mechanism outperformed the other two approaches in terms of improving the students’ learning achievement (F = 3.12, p © 2020 The Author(s)

关键词： Expert systems

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