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37th International Symposium on Automation and Robotics in Construction: From Demonstration to Practical Use - To New Stage of Construction Robot, ISARC 2020

作者： Hashiguchi, Nobuki Lim, Yeongjoo Sya, Cyo Kuroishi, Shinichi Miyazaki, Shigeo Kitahara, Shigeo Kobayashi, Taizo Tateyamad, Kazuyoshi Kodamaa, Kota Graduate School of Technology Management Ritsumeikan University Japan Faculty of Business Administration Ritsumeikan University Japan Kumagai Gumi Co. Ltd. Japan Department of Environmental Systems College of Science and Engineering Ritsumeikan University Japan Department of Civil Engineering College of Science and Engineering Ritsumeikan University Japan

ISBN: (纸本)9789529436347

Workers in a construction site may be exposed various hazards and risks and may work with excessive demands beyond their physical abilities. It is important for construction companies to sustain a workforce in the work environment that does not sacrifice worker safety and health and maintains the required productivity. The purpose of this study was to develop a method for real-time estimation of the workload risk of individual workers at a construction site. Based on previous studies, we developed a workload model that includes behavioral information and physical characteristics of workers in addition to heart rate reserve (%HRR). Recent wearable devices have sufficient performance for measuring biological and physical load data without interfering from their work. In this case study, heart rate and physical activity were measured using smart wear equipped with a biosensor, an acceleration sensor and IoT system developed in our research. Using a logistic regression analysis as the statistical methods and SPSS as the analysis tool, we analyzed the risk caused by the workload. As a result, it became clear that the physical activity and the heart rate will be the important parameters for estimating workload risk in construction works. However, worker age and body mass index (BMI) did not have a significant effect on estimating workload risk. In the construction site, types of works and skills of workers will change according to the progress of the project. In order to ensure a stable workforce and productivity, it is necessary for construction industry to manage workers' health and safety. In conclusion of this paper, we propose that the real-time monitoring of heart rate and physical activity during construction work can be used for human resource management (HRM). With the development of this study, it will be possible to determine how the workers' workload affects productivity. It is believed that this research will be useful as an element of the integrated manageme

关键词： Construction industry

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Categorizing learning analytics models according to their goals and identifying their relevant components: A review of the learning analytics literature from 2011 to 2019

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Computers and Education: Artificial Intelligence 2021年 2卷

作者： Quadir, Benazir Chang, Maiga Yang, Jie Chi Information Management Department School of Business. Shandong University of Technology China School of Computing and Information Systems Athabasca University Canada Graduate Institute of Network Learning Technology. &. Department of Computer Science and Information Engineering National Central University Taiwan

This study aimed to categorize learning analytics (LA) models and identify their relevant components by analyzing LA-related articles published between 2011 and 2019 in international journals. A total of 101 articles discussing various LA models were selected. These models were characterized according to their goals and components. A qualitative content analysis approach was used to develop a coding scheme for analyzing the aforementioned models. The results reveal that the studied LA models belong to five categories, namely performance, meta-cognitive, interactivity, communication, and data models. The majority of the selected LA-related articles were data models, followed by performance models. This review also identified 16 components that were commonly used in the studied models. The results indicate that analytics was the most common component in the studied models (used in 10 LA models). Furthermore, visualization was the most relevant component in the studied communication models. © 2021 The Authors

关键词： Learning systems

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Structural Investigation and Enriched Catalysis of Cu-complex Encapsulated Microporous Catalyst with Pragmatic Modelling for Prediction of Activity by Using Machine Learning

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Chemphyschem : a European journal of chemical physics and physical chemistry 2025年 e202400950页

作者： Rohit Prajapati Jetal Chaudhari Parikshit Paredi Nao Tsunoji Daksh Vyawhare Rayan Bandyopadhyay Krupa Shah Rajib Bandyopadhyay Mahuya Bandyopadhyay Pandit Deendayal Energy University Chemistry INDIA. Institute of Infrastructure Technology Research and Management Electrical and Computer Science Engineering INDIA. Institute of Infrastructure Technology Research and Management Basic Sciences INDIA. Hiroshima University Graduate School of Advanced Science and Engineering Applied Chemistry JAPAN. Campus Kleve: Hochschule Rhein-Waal Mechatronic Systems Engineering GERMANY. Institute of Infrastructure Technology Research and Management Chemistry Khokhara Circle Maninagar (East) 380008 Ahmedabad INDIA.

A facile and efficient post-synthetic method has been systematically employed to prepare a hybrid silicoaluminophosphate by immobilizing a mixed ligand copper (׀׀) complex comprising 2,9-dimethyl-1,10-phenanthroline and copper nitrate on base-functionalized material. The effective activity of this catalyst in ring opening reaction of epoxide was achieved when this complex was anchored on amine functionalized SAPO materials. Structure, phase integrity, thermal stability and the existence of functional groups are identified by using different analytical techniques like powder XRD, N2 adsorption-desorption, FT-IR, nuclear magnetic resolution, etc. 90% and 88% conversion were achieved using copper complex immobilized SAPO-34, and SAPO-5 materials, respectively which demonstrate the effectiveness of the materials for this reaction. Machine learnings are employed to predict product conversion and selectivity for scaling up the reaction for further industrial applications. Linear regression (LR), support vector machine (SVM), and k-nearest neighbors (kNN), have been utilized in this study, whereas SVM and kNN both exhibited good performance in predicting catalyst conversion and selectivity, by analysing mean squared error (MSE), mean absolute percentage error (MAPE), and R score. This study showcases the innovative synthesis and performance of the hybrid silicoaluminophosphate catalyst, illustrating the accurate predictive machine learning algorithms to find quality of catalyst for specific reactions.

关键词： data augmentation hybrid porous materials k-nearest neighbors linear regression ring-opening reactions of epoxide

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Adsorption of single and mixed haloacetonitriles on silica-based porous materials: Mechanisms and effects of porous structures

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Journal of Environmental Sciences 2019年第5期31卷 346-360页

作者： Panida Prarat Chawalit Ngamcharussrivichai Sutha Khaodhiar Patiparn Punyapalakul International Postgraduate Programs in Hazardous Substance and Environmental Management Graduate School Chulalongkorn University Center of Excellence on Hazardous Substance Management (HSM) Chulalongkorn University Department of Chemical Technology Faculty of Science Chulalongkorn University The Center of Excellence on Petrochemical and Materials Technology (PETROMAT) Chulalongkorn University Department of Environmental Engineering Faculty of Engineering Chulalongkorn University Research unit Control of Emerging Micropollutants in Environment Chulalongkorn University Research Network of NANOTEC - CU on Environment

Adsorption mechanisms and the role of different porous and crystalline structures on the removal of five haloacetonitriles(HANs) over hexagonal mesoporous silica(HMS), titanium substituted mesoporous silica(Ti-HMS), rod-shaped SBA-15 and microporous zeolite Na Y were investigated. In addition, the effect of p H on adsorption mechanism and selective adsorption of five HANs individually and in an equimolar mixed solution were *** results indicated that the intraparticle diffusion rate constants of the mesoporous adsorbents were higher than that of the microporous Na Y. In single solute, the order of adsorption preference(highest to lowest) was mono-HANs > di-HANs > tri-HAN. However,in mixed solute, the large molecular weight of the tri-HAN and di-HANs are more easily adsorbed than the smaller molecular weight mono-HANs. Except for SBA-15, the order of adsorption capacities in mixed HANs solute was not different compared to that observed for the single HAN solute, which might be caused by the higher accessibility to the active sites due to larger pore size. The ion-dipole electrostatic interaction was likely to be the main adsorption mechanism, and was favored at high p H values due to the high negative surface charge density of the adsorbent. The molecular structure of the HANs and hydrophilic/hydrophobic nature affected the adsorption capacities and their selective adsorption from mixed solutes.

关键词： Haloacetonitrile Adsorption mechanism Porous structure Ion-dipole electrostatic interaction Hydrophilicity

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The Evaluation of the Local Beer Industry during the COVID-19 Pandemic and Its Relationship with Open Innovation

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Journal of Open Innovation: Technology, Market, and Complexity 2022年第3期8卷

作者： Ong, Ardvin Kester S. Pequeña, Arianne R. Prasetyo, Yogi Tri Chuenyindee, Thanatorn Buaphiban, Thapanat Persada, Satria Fadil Nadlifatin, Reny School of Industrial Engineering and Engineering Management Mapua University 658 Muralla St. Intramuros Manila 1102 Philippines School of Graduate Studies Mapúa University 658 Muralla St. Intramuros Manila 1002 Philippines Department of Industrial Engineering and Management Yuan Ze University 135 Yuan-Tung Road Chung-Li 32003 Taiwan Department of Industrial Engineering and Aviation Management Navaminda Kasatriyadhiraj Royal Air Force Academy Bangkok 10220 Thailand BINUS Business School Undergraduate Program Entrepreneurship Department Bina Nusantara University Jakarta 11480 Indonesia Department of Information Systems Institut Teknologi Sepuluh Nopember Kampus ITS Sukolilo Surabaya 60111 Indonesia

The beer industry is one of the businesses affected during the COVID-19 pandemic. Despite the exponential growth of the beer industry throughout the years, this aspect of the beverage industry has gained limited attention and has been underexplored. This study aimed to provide a better and up-to-date understanding of Philippine-beer consumers to speed up its recovery. An online survey with 853 volunteer respondents was conducted to investigate Filipinos’ local beer consumption considering frequency, intake, expenses, and preference. A descriptive analysis of the consumers’ self-perceived evaluation of the changes in drinking showed a slight decrease in frequency, intake, and expenses and a minor change in preference. Somers’ d and the chi-squared test results indicated significant relationships between each demographic information (age, sex, and income) and frequency, intake, and expenses. In addition, a conjoint analysis with an orthogonal design indicated that price was the most important attribute (58.025%), followed by primary taste (12.452%), alcohol content (9.706%), mouthfeel (6.445%), aftertaste (6.355%), aroma (5.189%), and, lastly, color (1.827%). The findings of this study could be used as a baseline for improved product offerings, customized advertisements, and market segmentation. Moreover, the results of this study could be applied and extended by breweries to promote and create strategies. Lastly, this study could be extended and utilized by other beverage industries worldwide. © 2022 by the authors.

关键词： beer conjoint analysis consumer preference COVID-19 pandemic expenditure

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How different spatial resolutions of digital models affects the geospatial distribution evaluation of the Index of Connectivity

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Journal of South American Earth Sciences 2025年 163卷

作者： Eberval Marchioro Geraldo André Rosseto Barreto Ialy Gomes Ferreira Adelsom Soares Filho Diogo Costa Buarque Department of Geography (DGEO) Graduate Program in Geography (PPGG) Federal University of Espírito Santo/Brazil (UFES) Coordinator of the Laboratory for Monitoring and Modeling Environmental Systems (Lamosa) Brazil Graduate Program in Management and Regulation of Water Resources (ProfÁgua/UFES) Brazil Graduate Program in Geography at UFES Brazil Graduate Program in Civil Engineering at UFV Brazil Department of Geography Graduate Program in Geography Federal University of Grande Dourados (UFGD) Brazil Department of Environmental Engineering Graduate Program in Environmental Engineering (PPGEA) Professional Master's in Water Resources Management and Regulation (ProfÁgua/UFES) Federal University of Espírito Santo/Brazil (UFES) Brazil

Digital Terrain Models (DTM) and Digital Elevation Models (DEM) are important for obtaining the Index of Connectivity, as they provide valuable information to assess the possibility of sediments reaching the riverbed in watershed basins. This is crucial for proactive management, as it allows the adoption of preventive and mitigating measures. Therefore, this study aims to analyze the effect of the spatial resolution of DEMs with resolutions of 5 m and 2 m, and between the DTM and DEM at 2 m, in determining the Index of Connectivity (IC). Additionally, it was investigated whether it is possible to use only one spatial resolution of digital models to assess the geospatial distribution of IC for all hydrogeomorphological landscapes of the Duas Bocas River watershed, located in the Metropolitan Region of Greater Vitória, in the state of Espírito Santo, Southeast Brazil. For this study, the Borselli Index of Connectivity model (et al., 2008) was used, originally developed for rural areas of Italy and widely applied in different regions worldwide. The data used, including Digital Elevation and Terrain Models and land use and cover information, were obtained from the Integrated Geospatial Base System of the State of Espírito Santo (Brazil), which is publicly *** results indicate that a better geospatial representation of IC occurs when changing the spatial resolution of DEMs from a 5 m pixel to a 2 m pixel and when using the 2 m DTM instead of the 2 m DEM. When analyzing the relationship between IC and the hydrogeomorphological landscapes in the basin, it was observed that, in the absence of models with an even finer pixel resolution, the 2 m DTM is the most suitable option, as it presented IC values consistent within and between landscapes in the Escalated Terraces of Southern Espírito Santo, Coastal Hills and Massifs, and Coastal Plateaus sectors. The exception was the fluvio-lagoon plain, which requires an even finer pixel resolution, necessitating further st

关键词： DEM DTM Erosion Espatial resolution Sediment

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Cardiovascular Disease Prediction Using Machine Learning Algorithms

Cardiovascular Disease Prediction Using Machine Learning Alg...

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IEEE International Conference on engineering Technologies and Applied Sciences (ICETAS)

作者： Kalapraveen Bagadi Visalakshi Annepu Adnan Naji Jameel AL-Tamimi Naga Raju Challa H.S. S. Aljibori M. N. Mohammed Oday I. Abdullah Rabab Alayham Abbas Helmi M. Alfiras School of Electronics Enineering VIT-AP University Amaravati India School of Comp. Science & Eng. VIT-AP University Amaravati India College of Technical Engineering Al-Farahidi University Baghdad Iraq Dept. of Elec. and Comm. Eng. Bapatla Engineering College Baptla India College of Engineering University of Warith Al-Anbiyaa Karbala Iraq Mechanical Engineering Department College of Engineering Gulf University Sanad Bahrain Dept of Energy Engineering University of Baghdad Iraq Mechanical Engineering Dept College of Engineering Gulf University Sanad Bahrain Hamburg University of Technology Institute of Laser and Systems Technologies Hamburg Germany School of Graduate Studies Management and Science University Shah Alam Selangor Malaysia Electrical and Electronic Engineering Department College of Engineering Gulf University Sanad Kingdom of Bahrain

The fact that cardiovascular disease (CVD) is a major cause of death worldwide highlights the significance of accurate prediction for successful preventative and treatment measures. Machine learning algorithms, which use the analysis of vast patient data to reveal hidden patterns and risk variables, have recently come to light as potential techniques for CVD prediction. This study intends to analyse how machine learning (ML) techniques are used in CVD prediction and evaluate how well they perform in comparison to conventional approaches. The study makes use of a sizable patient cohort's medical history, demographic data, and clinical factors in a complete dataset. Predictive models are built using a variety of machine learning algorithms, including support vector machine (SVM), gradient boosting, K-nearest neighbours, naive Bayes classifier, and logistic regression. To find the most important factors influencing CVD risk, feature selection techniques are used. Metrics like accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve are used to assess how well the machine learning models work. The outcomes are contrasted with well-known risk prediction models and clinical guidelines in order to assess the added value of machine learning methods. This work intends to improve CVD prediction capabilities and offer useful insights for better risk assessment and management strategies by utilizing the power of machine learning.

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3D printing of soft-matter mono pump in infant ventricular assist device (VAD) for blood pumping

3D printing of soft-matter mono pump in infant ventricular a...

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Pacific Rim Meeting on Electrochemical and Solid State Science 2020, PRiME 200

作者： Yeh, Y.C. Yamada, N. Watanabe, Y. Shiblee, M.N.I. Ogawa, J. Khosla, A. Kawakami, M. Akamatsu, T. Furukawa, H. Department of Management of Technology Graduate School of Science and Engineering Yamagata University 4-3-16 Jonan Yonezawa Yamagata992-8510 Japan Department of Mechanical Systems Engineering Graduate School of Science and Engineering Yamagata University 4-3-16 Jonan Yonezawa Yamagata992-8510 Japan Muromachi-dori and Nakadachiuri dori 3-471 Kamigyō-ku Kyoto602-0915 Japan

ISBN: (纸本)9781607689089

We want to develop a soft-matter Mono pump for infant Ventricular Assist Device (VAD). In this research, we have developed the Mono pump, which is made of soft materials and hard materials to study the effect of applying the soft materials to the Mono pump. The stator of the 3D printed Mono pump was made with biocompatible soft materials called Inter Cross-linking Network (ICN) gels. We believe that ICN gels have not only specific toughness and low friction but also excellent biocompatibility that can prevent blood cell trauma and the transplant rejection. Moreover, the rotor is made of hard materials using commercial resin or filament based 3D printers, (Form 2 and Flashforge Creator). Finally, we will compare the practical and theoretical displacement from the flow rate measurement to implement the best performance of the Mono pump in practical use. © The Electrochemical Society.

关键词： Pumps

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An analytical investigation of body parts more susceptible to aging and composition changes using statistical hypothesis testing

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Healthcare Analytics 2024年 5卷 100284-100284页

作者： Mori, Masaya Flores, Roberto Gonzalez Kamimura, Hiroteru Yamaura, Kentaro Nonaka, Hirofumi Information and Management Systems Engineering Nagaoka University of Technology 1603-1 Kamitomioka Niigata Nagaoka-city 940-2188 Japan Division of Gastroenterology and Hepatology Graduate School of Medical and Dental Sciences Niigata University 757-1 Asahimachidori Chuo-ku Niigata NIigata-city 951-8510 Japan Department of Network Medicine for Digestive Diseases School of Medicine Niigata University 757-1 Asahimachidori Chuo-ku Niigata NIigata-city 951-8510 Japan

In recent years, age-related changes in body composition in the elderly are attracting attention. This is associated with a decline in physical functions and an increased risk of disease development. In general, age-related changes in body composition can be minimized with appropriate exercise. However, there are no studies that investigate body parts susceptibility to aging and changes in body composition of those parts. Therefore, devising exercise programs and advising daily life while taking these into account becomes difficult. This study aims to identify body parts that are more susceptible to aging and their body composition changes. The body composition was obtained with a Direct Segmental Multi-frequency Bioelectrical Impedance Analysis using InBody770 in 8 male elderly patients who had been shortly hospitalized. Statistical hypothesis testing was used to determine whether site-specific body composition changed significantly between hospital discharge and 1 year, 1 year and 2 years, and hospital discharge and 2 years. The results showed that Lean body mass, Total Body Water, Intracellular Water, Extracellular Water in the right arm;Lean body mass and Total Body Water in the left arm and trunk are more sensitive to aging. © 2023 The Author(s)

关键词： Age-related changes Body composition Bootstrap method Multi-frequency impedance analysis Nonparametric test Older adults

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Cognition and evaluation of the public regarding final cutting methods

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Nihon Ringakkai Shi/Journal of the Japanese Forestry Society 2020年第3期102卷 180-190页

作者： Takayama, Norimasa Sanai, Sato Yamaura, Yuichi Administration Bureau Forestry and Forest Products Research Institute Forest Research and Management Organization 1 Matsunosato Tsukuba Ibaraki305-8687 Japan Graduate School of Systems and Information Engineering University of Tsukuba 1-1-1 Tennodai Tsukuba Ibaraki305-8573 Japan Shikoku Research Center Forestry and Forest Products Research Institute Forest Research and Management Organization 2-915 Asakuranishi Kochi Kochi780-8077 Japan Fenner School of Environment and Society Australian National University CanberraACT2601 Australia

To promote domestic forestry smoothly in the future, understanding nonexperts' views on forestry and cutting methods is necessary. In the present study, we investigated an aesthetic (cognitive/evaluative) value of the nonexperts for the six types of cutting methods (clear-cutting, group cutting, old tree residual cutting, extensive residual cutting (100 pieces/ha), medium residual cutting (50 pieces/ha), small residual cutting (10 pieces/ha)) and before cutting. Then, we compared the aesthetic perspectives of the nonexperts regarding the methods and their application with those of the experts to evaluate their potential impacts on biodiversity conservation and rationality as forestry. According to the results, 1) nonexperts tended to rate clear-cutting and old tree residual cutting positively whereas group cutting with viewed with negative impacts. Besides, 2) because nonexperts are more likely to resist tree cutting, they should be furnished with information about the role of logging activities, and the need to take into account ecosystem functions and tree planting activities for final cutting. 3) There was a considerable gap between experts and nonexperts based on their perspectives on the roles of different final cutting methods, which implies that further efforts should be made to understand the perspectives of nonexperts to facilitate their education. © 2020 Nihon Ringakkai. All rights reserved.

关键词： Biodiversity

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