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An efficient method for online identification of steady state for multivariate systems 13

ASME 2018 13th International Manufacturing Science and engineering Conference, MSEC 2018

作者： Xu, Honglun Wu, Jianguo Tseng, Tzu-Liang Bill Computational Science Program University of Texas El PasoTX79968 United States Department of Industrial Engineering and Management Peking University Beijing100871 China Industrial Manufacturing and Systems Engineering University of Texas El PasoTX79968 United States

ISBN: (纸本)9780791851388

Most of the existing steady state detection approaches are designed for univariate signals. For multivariate signals, the univariate approach is often applied to each process variable and the system is claimed to be steady once all signals are steady, which is computationally inefficient and also not accurate. The article proposes an efficient online method for multivariate steady state detection. It estimates the covariance matrices using two different approaches, namely, the mean-squared-deviation and mean-squared-successive-difference. To avoid the usage of a moving window, the process means and the two covariance matrices are calculated recursively through exponentially weighted moving average. A likelihood ratio test is developed to compare the difference of the two covariance matrices and to detect the steady state. The intensive numerical studies and real case study show that the proposed method can accurately detect the steady state of a multivariate system. © Copyright 2018 ASME.

关键词： Covariance matrix

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Bitcoin’s future carbon footprint

arXiv

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arXiv 2020年

作者： Qin, Shize Klaaßen, Lena Gallersdörfer, Ulrich Stoll, Christian Zhang, Da Institute of Energy Environment and Economy Tsinghua University Beijing100084 China TUM School of Management Technical University of Munich Munich Germany TUM Software Engineering for Business Information Systems Department of Informatics Technical University of Munich Munich Germany MIT Center for Energy and Environmental Policy Research Massachusetts Institute of Technology CambridgeMA United States TUM Center for Energy Markets TUM School of Management Technical University of Munich Munich Germany MIT Joint Program on the Science and Policy of Global Change CambridgeMA02139 United States

The carbon footprint of Bitcoin has drawn wide attention, but Bitcoin’s long-term impact on the climate remains uncertain. Here we present a framework to overcome uncertainties in previous estimates and project Bitcoin’s electricity consumption and carbon footprint in the long term. If we assume Bitcoin’s market capitalization grows in line with the one of gold, we find that the annual electricity consumption of Bitcoin may increase from 50 to 400 TWh between 2020 and 2100. The future carbon footprint of Bitcoin strongly depends on the decarbonization pathway of the electricity sector. If the electricity sector achieves carbon neutrality by 2050, Bitcoin’s carbon footprint has peaked already. However, in the business-as-usual scenario, emissions sum up to 2 gigatons until 2100, an amount comparable to 6% of global emissions in 2018. Therefore, we also discuss policy instruments to reduce Bitcoin’s future carbon footprint. Copyright © 2020, The Authors. All rights reserved.

关键词： Carbon footprint

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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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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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Integrating Tuberculosis data in State of São Paulo over Semantic Web: a proof of concept

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Procedia Computer Science 2019年 164卷 686-691页

作者： Felipe Carvalho Pellison Vinícius Costa Lima Rui Pedro Chartes Lopes Rijo Domingos Alves Bioengineering Postgraduate Program University of São Paulo São Carlos Brazil School of Technology and Management Polytechnic Institute of Leiria Leiria Portugal Center 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 São Paulo Ribeirão Preto Brazil

Although tuberculosis is a curable disease and, in most cases, with low cost drugs, its mortality still is a global concern. This facts turns our attention to management issues and the difficulties related to retrieving data of interest that are powdered on many applications. This work presents a semantic web approach to achieve functional and semantic interoperability between two applications in State of São Paulo that contain tuberculosis data. By combining a theoretical-practical development, the geolocalization tool created is a proof of concept that could help managers to take strategic decisions and develop better health policies by showing the distribution of tuberculosis cases across the state. This work stands out the importance of working in solutions that could improve the quality of data in health field and daily activities of health professionals.

关键词： Tuberculosis Semantic Web Health Information System Interoperability Data Integration

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The Affecting Factors of Blockchain Technology Adoption of Payments systems in Indonesia Banking Industry 3

The Affecting Factors of Blockchain Technology Adoption of P...

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

作者： Taufiq, Rohmat Meyliana Hidayanto, Achmad Nizar Prabowo, Harjanto Computer Science Department BINUS Graduate Program-Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Informatic Engineering Engineering Faculty University Muhammadiyah of Tangerang Tangerang15117 Indonesia Information Systems Department Bina Nusantara University School of Information Systems Jakarta11480 Indonesia Faculty of Computer Science University of Indonesia Depok16424 Indonesia Management Department Bina Nusantara University BINUS Business School Undergraduate Program Jakarta11480 Indonesia

ISBN: (纸本)9781538658215

The purpose of this study is to find the influence factors of blockchain technology adoption of payments system in Indonesia banking industry. Moreover, the researchers proposed new model of payment system by using blockchain technology in Indonesia banking industry. All this time, the researchers of blockchain in payment systems were done in major countries such as UK, USA, Australia, Scotland, Germany, Japan, France, Italy, and China. Systematic Literature Review (SLR) used as a method in this study and there were five databases that taken as references, such as IEEE, Science direct, AIS electronic, ACM and Google Scholar. The researchers were found 26 references Studies Included in Quantitative Synthesis and 9 variables (Easy to use, Usefulness, Transaction fees, Risk perception, Behaviour intention of use, Attitude toward, Cognitive style, Subjective Norm, Effectiveness). Based on the result of data analysis and discussion, there were two conclusions in this study, the first, the researchers found nine factors that expected tobe used as a reference if Indonesia banking industry wants to adopt blockchain technology for payment system;and second, the researchers had to propose payment system model by using blockchain technology in Indonesia banking industry. © 2018 IEEE.

关键词： Blockchain

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Willingness to pay for flood insurance: a case study in Phang Khon, Sakon Nakhon Province, Thailand

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IOP Conference Series: Earth and Environmental Science 2020年第1期612卷

作者： S Paopid J Tang N Leelawat Risk and Disaster Management Program Graduate School Chulalongkorn University Phayathai Road Pathumwan Bangkok 10330 Thailand International School of Engineering Faculty of Engineering Chulalongkorn University Phayathai Road Pathumwan Bangkok 10330 Thailand Disaster and Risk Management Information Systems Research Group Chulalongkorn University Phayathai Road Pathumwan Bangkok 10330 Thailand Department of Industrial Engineering Faculty of Engineering Chulalongkorn University Phayathai Road Pathumwan Bangkok 10330 Thailand

Long droughts and floods can reduce agricultural productivity and negatively impact upon businesses in the agriculture and food industries. The prevention and response to floods require both public and private efforts (e.g., 'Pay for Flood' insurance) for utmost effectiveness. The purpose of this study was to determine the potential factors that influence the people of Phang Khon District, near the Nam Un Dam, in paying flood insurance. The regression results showed that the height and duration of flooding, house price, and flood damage, were all key factors that triggered the willingness to pay flood insurance. In contrast, having a house with stairs decreased the likelihood of paying insurance. Our research suggested that 12.69 -19.04 USD/month is a commonly accepted flood insurance premium in Thailand. These findings can guide governments and insurance providers and companies towards improving their flood insurance practices.

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Left ventricular hypertrophy detection using electrocardiographic signal

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Scientific reports 2023年第1期13卷 2556页

作者： Cheng-Wei Liu Fu-Hsing Wu Yu-Lun Hu Ren-Hao Pan Chuen-Horng Lin Yung-Fu Chen Guo-Shiang Tseng Yung-Kuan Chan Ching-Lin Wang Division of Cardiology Department of Internal Medicine Tri-Service General Hospital Songshan Branch National Defense Medical Center Taipei Taiwan. Bachelor Degree Program of Artificial Intelligence National Taichung University of Science and Technology Taichung Taiwan. Department of Management Information Systems National Chung-Hsing University Taichung Taiwan. La Vida Tec. Co. Ltd. Taichung Taiwan. Preventive Medicine Center National Yang Ming Chiao Tung University Taipei Taiwan. Department of Information Management Tunghai University Taichung Taiwan. Department of Computer Science and Information Engineering National Taichung University of Science and Technology Taichung Taiwan. Department of Dental Technology and Materials Science Central Taiwan University of Science and Technology Taichung Taiwan. Division of Cardiology Department of Internal Medicine Taoyuan Armed Force General Hospital Hsinchu Branch Hsinchu Taiwan. Department of Management Information Systems National Chung-Hsing University Taichung Taiwan. ykchan@nchu.edu.tw. Department of Information Management National Chin-Yi University of Technology Taichung Taiwan. clwang@ncut.edu.tw.

Left ventricular hypertrophy (LVH) indicates subclinical organ damage, associating with the incidence of cardiovascular diseases. From the medical perspective, electrocardiogram (ECG) is a low-cost, non-invasive, and easily reproducible tool that is often used as a preliminary diagnosis for the detection of heart disease. Nowadays, there are many criteria for assessing LVH by ECG. These criteria usually include that voltage combination of RS peaks in multi-lead ECG must be greater than one or more thresholds for diagnosis. We developed a system for detecting LVH using ECG signals by two steps: firstly, the R-peak and S-valley amplitudes of the 12-lead ECG were extracted to automatically obtain a total of 24 features and ECG beats of each case (LVH or non-LVH) were segmented; secondly, a back propagation neural network (BPN) was trained using a dataset with these features. Echocardiography (ECHO) was used as the gold standard for diagnosing LVH. The number of LVH cases (of a Taiwanese population) identified was 173. As each ECG sequence generally included 8 to 13 cycles (heartbeats) due to differences in heart rate, etc., we identified 1466 ECG cycles of LVH patients after beat segmentation. Results showed that our BPN model for detecting LVH reached the testing accuracy, precision, sensitivity, and specificity of 0.961, 0.958, 0.966 and 0.956, respectively. Detection performances of our BPN model, on the whole, outperform 7 methods using ECG criteria and many ECG-based artificial intelligence (AI) models reported previously for detecting LVH.

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Risk based framework for assessing resilience in a complex multi-actor supply chain domain

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Supply Chain Forum 2018年第4期19卷 266-281页

作者： Ravulakollu, Anil Kumar Urciuoli, Luca Rukanova, Boriana Tan, Yao-Hua Hakvoort, Rudi A. Faulty of Technology Policy and Management Delft University of Technology Delft Netherlands Department of Industrial Economics and Management KTH Royal Institute of Technology Stockholm Sweden MIT International Logistics Program Zaragoza Logistics Center Zaragoza Spain Section Information and Communication Technology Faulty of Technology Policy and Management Technical University Delft Delft Netherlands Section Engineering Systems and Services Faulty of Technology Policy and Management Technical University Delft Delft Netherlands

Risk management frameworks offer excellent tools to identify and manage risks in supply chains. Existing tools can be used to evaluate impacts of countermeasures, however, analysts struggle with modelling how disruptions escalate in complex supply chain systems within a certain amount of time and across several stakeholders. On the contrary, the resilience discipline offers the possibility to understand how a supply chain reacts to disruptions as a function of time. Hence, this paper integrates the concepts of resilience with risk management techniques and develops a risk based resilience assessment framework in a multi-actor context. Further, the framework is operationalized by developing a computer based tool that is tested in case of fruit import in Netherlands. © 2018, © 2018 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

关键词： cost impact analysis multi-actor analysis resilience triangle Risk analysis risk matrix supply chain resilience

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Blockchain ased Network for Tuberculosis: Data Sharing Initiative in Brazil

Blockchain ased Network for Tuberculosis: Data Sharing Initi...

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作者： Bernardi, Filipe Lima, Vinicius Pellison, Felipe De Azevedo Marques, Paulo Mazzoncini Rijo, Rui Galliez, Rafael Mello Kritski, Afrânio Alves, Domingos Bioengineering Postgraduate Program University of São Paulo Health Intelligence Laboratory Ribeirão Preto Medical School Ribeirão Preto Brazil School of Technology and Management Polytechnic Institute of Leiria Portugal Center of Scientific and Technological Information Oswaldo Cruz Foundation Brazil Ribeirão Preto Medical School University of São Paulo Brazil CINTESIS Center for Health Technology and Services Research Portugal INESCC Institute for Systems and Computers Engineering at Coimbra Portugal Faculty of Medicine Federal University of Rio de Janeiro Brazil

ISBN: (纸本)9781614999867

Data sharing, information exchange, knowledge acquisition and health intelligence are the basis of an efficient and effective evidence-based decision-making tool. A decentralized blockchain architecture is a flexible solution that can be adapted to institutional and managerial culture of organizations and services. Blockchain can play a fundamental role in enabling data sharing within a network and, to achieve that, this work defines the high-level resources necessary to apply this technology to Tuberculosis related issues. Thus, relying in open-source tools and in a collaborative development approach, we present a proposal of a blockchain based network, the TB Network, to underpin an initiative of sharing of Tuberculosis scientific, operational and epidemiologic data between several stakeholders across Brazilian cities. © 2019 The authors and IOS Press. All rights reserved.

关键词： Blockchain

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