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3rd International Conference on Sustainable civil engineering and Architecture, ICSCEA 2023

作者： Le, Tu Dang Minh Van Do, Vuong Nguyen Applied Computational Civil and Structural Engineering Research Group Faculty of Civil Engineering Ton Duc Thang University Ho Chi Minh City700000 Viet Nam

ISBN: (纸本)9789819974337

This study presents a Moving Kriging (MK) meshfree method and a simple Kirchhoff theory to analyze the natural frequency and thermal buckling deformations of advanced material plates. Compared to the Reissner-Mindlin plate theory, four degrees of freedom per node regarding to the displacement field are available by subtracting one variable reduce the computational cost. From the enhanced Kirchhoff theory and the given MK meshfree method, the locking phenomenon is negligible when the plate thickness becomes too thin. The gradient deflections imposed as essential boundary conditions are proposed and taken into account by Meshfree method to derive the governing equations. The simulations of thermal buckling and free vibration conducted are compared with reported literature to evaluate the accuracy and effectiveness of the current MK meshfree method. Consequently, a good agreement is observed and the numerical results evidenced that the competence of MK interpolation embedding into the meshfree method can accurately estimate the numerical computation. Moreover, illustrations by the obtained nonlinear solutions showed that the modified meshfree method is as the powerful tool to properly predict the results thats approximate practical engineering problems. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Kriging

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Toward Construction Payment Automation by Integrating BIM and Blockchain Technology

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Transportation research Procedia 2025年 85卷 143-149页

作者： Hai Chien Pham Si Van-Tien Tran Lan Bao Applied Computational Civil and Structural Engineering Research Group Faculty of Civil Engineering Ton Duc Thang University Ho Chi Minh City Vietnam School of Architecture and Building Science Chung-Ang University Seoul 06975 Republic of Korea

The construction industry encounters persistent obstacles, such as payment delays, disputes, and transparency, which hinder project efficacy and stakeholder confidence. To resolve these issues, this study proposes a transparent and automated construction payment approach by integrating BIM with its precise project data and blockchain, decentralized ledger, and smart contract capabilities. The new approach illustrates how BIM can facilitate precise progress monitoring and milestone verification while blockchain ensures secure, real-time payments upon milestone completion. The findings indicate that this integration encourages transparent payment processes, drastically reduces disputes, and enhances stakeholder trust, thereby reshaping the financial landscape of the construction industry and improving project outcomes. The research also discusses technical, security, and regulatory considerations, providing an all-encompassing view of the practicability and benefits of this innovative approach. The research contributions prove that incorporating BIM and blockchain can revolutionize construction payments by rendering them more efficient, transparent, and adaptable to the industry’s changing requirements.

关键词： BIM Blockchain construction payments contract management smart contract

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A deep neural network based surrogate model for damage identification in full-scale structures with incomplete noisy measurements

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Frontiers of structural and civil engineering 2024年第3期18卷 393-410页

作者： Tram BUI-NGOC Duy-Khuong LY Tam T TRUONG Chanachai THONGCHOM T.NGUYEN-THOI Laboratory for Computational Mechanics Institute for Computational Science and Artificial IntelligenceVan Lang UniversityHo Chi Minh City 70000Vietnam Faculty of Mechanical-Electrical and Computer Engineering School of TechnologyVan Lang UniversityHo Chi Minh City 70000Vietnam Faculty of Civil Engineering School of TechnologyVan Lang UniversityHo Chi Minh City 70000Vietnam Department of Computer Science Aarhus UniversityAarhus 8000Denmark Thammasat University research unit in structural and foundation engineering Department of Civil EngineeringThammasat UniversityPathumthani 12120Thailand Laboratory for Applied and Industrial Mathematics Institute for Computational Science and Artificial IntelligenceVan Lang UniversityHo Chi Minh City 70000Vietnam Thammasat School of Engineering Thammasat UniversityPathumthani 12120Thailand

The paper introduces a novel approach for detecting structural damage in full-scale structures using surrogate models generated from incomplete modal data and deep neural networks(DNNs).A significant challenge in this field is the limited availability of measurement data for full-scale structures,which is addressed in this paper by generating data sets using a reduced finite element(FE)model constructed by SAP2000 software and the MATLAB programming *** surrogate models are trained using response data obtained from the monitored structure through a limited number of measurement *** proposed approach involves training a single surrogate model that can quickly predict the location and severity of damage for all potential *** achieve the most generalized surrogate model,the study explores different types of layers and hyperparameters of the training algorithm and employs state-of-the-art techniques to avoid overfitting and to accelerate the training *** approach’s effectiveness,efficiency,and applicability are demonstrated by two numerical *** study also verifies the robustness of the proposed approach on data sets with sparse and noisy measured ***,the proposed approach is a promising alternative to traditional approaches that rely on FE model updating and optimization algorithms,which can be computationally *** approach also shows potential for broader applications in structural damage detection.

关键词： vibration-based damage detection deep neural network full-scale structures finite element model updating noisy incomplete modal data

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Wind speed prediction and insight for generalized predictive modeling framework: a comparative study for different artificial intelligence models

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Neural Computing and Applications 2024年第23期36卷 14119-14150页

作者： Bhagat, Suraj Kumar Tiyasha, Tiyasha Shather, A.H. Jamei, Mehdi Kumar, Adarsh Al-Khafaji, Zainab Goliatt, Leonardo Shafik, Shafik S. Alawi, Omer A. Yaseen, Zaher Mundher Faculty of Civil Engineering Ton Duc Thang University Ho Chi Minh City Viet Nam Department of Computer Engineering Technology Al Kitab University Altun Kopru Kirkuk00964 Iraq Faculty of Civil Engineering and Architecture Shahid Chamran University of Ahvaz Ahvaz Iran Canadian Centre for Climate Change and Adaptation University of Prince Edward Island St PetersPE Canada Building and Construction Techniques Engineering Department College of Engineering and Engineering Techniques Al-Mustaqbal University Hillah Babylon51001 Iraq Department of Computational and Applied Mechanics Federal University of Juiz de Fora Juiz de Fora Brazil Experimental Nuclear Radiation Research Group Scientific Research Center Al-Ayen University Thi-Qar64001 Iraq Johor Bahru Skudai81310 Malaysia Civil and Environmental Engineering Department King Fahd University of Petroleum and Minerals Dhahran31261 Saudi Arabia Department of Civil Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Dehradun India Dept of Environmental Science Gitam School of Science GITAM University Visakhapatnam India

Wind speed (WS) has played a vital role in local urban and sub-urban weather, agriculture, and ecosystem. Several meteorological parameters are influencing WS such as relative humidity (at 2 m, %), surface pressure (kPa), maximum temperature (at 2 m, °C), minimum temperature (at 2 m, °C), average temperature (at 2 m, °C), and all sky insolation incident on a horizontal surface (kW-h/m2/day). The current research was conducted to predict WS at different locations at Vietnam using the feasibility of computer aid models (i.e., multivariate adaptive regression splines (MARS), extreme gradient boosting (XGBoost) and random forest generator (Ranger)). Pearson correlation (PC) was investigated to select the high significant predictors to predict the WS at 10 m high. All inputs (maximum number, 6) are chosen by the PC approach for PhuongNinh, DaNang, and HaNoi;and for minimum number of inputs i.e four, are selected for PhuongHung, CanTho, and SaPa city;that exhibit the relationship with WS, citywise. The sequence selection of input parameters differed in each station as per the PC analysis. Based on the statistical evaluation and graphical presentation, MARS model attained the best prediction results, followed by XGBoost and Ranger. MARS predictive model remains at the top performance among others based on 95% confidence interval. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Forecasting

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Analysis of Twitter Data Using Evolutionary Clustering during the COVID-19 Pandemic

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Computers, Materials & Continua 2020年第10期65卷 193-203页

作者： Ibrahim Arpaci Shadi Alshehabi Mostafa Al-Emran Mahmoud Khasawneh Ibrahim Mahariq Thabet Abdeljawad Aboul Ella Hassanien Department of Computer Education and Instructional Technology Tokat Gaziosmanpasa UniversityTokatTurkey Department of Computer Engineering University of Turkish Aeronautical AssociationAnkaraTurkey Applied Computational Civil and Structural Engineering Research Group Faculty of Civil EngineeringTon Duc Thang UniversityHo Chi MinhVietnam College of Engineering and Technology American University of the Middle EastKuwaitKuwait Department of Mathematics and General Sciences Prince Sultan UniversityRiyadh66833Saudi Arabia Department of Medical Research China Medical UniversityTaichung40402Taiwan Department of Computer Science and Information Engineering Asia UniversityTaichungTaiwan Faculty of Computers and AI Cairo UniversityGizaEgypt Scientific Research Group in Egypt CairoEgypt

People started posting textual tweets on Twitter as soon as the novel coronavirus(COVID-19)*** these tweets can assist institutions in better decision-making and prioritizing their ***,this study aimed to analyze 43 million tweets collected between March 22 and March 30,2020 and describe the trend of public attention given to the topics related to the COVID-19 epidemic using evolutionary clustering *** results indicated that unigram terms were trended more frequently than bigram and trigram terms.A large number of tweets about the COVID-19 were disseminated and received widespread public attention during the *** high-frequency words such as“death”,“test”,“spread”,and“lockdown”suggest that people fear of being infected,and those who got infection are afraid of *** results also showed that people agreed to stay at home due to the fear of the spread,and they were calling for social distancing since they become aware of the *** can be suggested that social media posts may affect human psychology and *** results may help governments and health organizations to better understand the psychology of the public,and thereby,better communicate with them to prevent and manage the panic.

关键词： Twitter social media evolutionary clustering COVID-19 coronavirus

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Correction: An enhanced flux continuity three-dimensional finite element method for heterogeneous and anisotropic diffusion problems on general meshes

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Journal of engineering Mathematics 2024年第1期146卷 1-1页

作者： Hai, Ong Thanh Nguyen, Thi Hoai Thuong Le, Anh Ha Van Do, Vuong Nguyen Department of Analysis Faculty of Mathematics & Computer Science University of Science Ho Chi Minh Vietnam Vietnam National University Ho Chi Minh Vietnam Applied Computational Civil and Structural Engineering Research Group Faculty of Civil Engineering Ton Duc Thang University Ho Chi Minh Vietnam

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A tri-phasic continuum model for the numerical analysis of biological tissue proliferation using the Theory of Porous Media. Application to cardiac remodelling in rheumatic heart disease 12

A tri-phasic continuum model for the numerical analysis of b...

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12th South African Conference on computational and applied Mechanics, SACAM 2020

作者： Mosam, Adam Skatulla, Sebastian Ntusi, Ntobeko Computational Continuum Mechanics Group Department of Civil Engineering University of Cape Town South Africa Centre for Research in Computational and Applied Mechanics University of Cape Town South Africa Division of Cardiology Department of Medicine University of Cape Town South Africa

ISBN: (纸本)9781713840770

This research is part of an on-going project aimed at describing the mechanotransduction of rheumatic heart disease (RHD), in order to study long-term effects of new therapeutic concepts to treat inflammatory heart diseases and ultimately, estimate their effectiveness to prevent heart failure. RHD is a condition which is mostly common amongst low-income countries and accounts for approximately 250 000 deaths per annum. The Theory of Porous Media (TPM) can represent the proliferative growth and remodelling processes related to RHD within a thermodynamically consistent framework and is additionally advantageous with application to biological tissue due to the ability to couple multiple constituents. The research presented will extend an existing biphasic TPM model for the solid cardiac tissue (solid phase) saturated in a blood and interstitial fluid (liquid phase) [1], to a triphasic model with the inclusion of a third nutrient phase towards growth. This inclusion is motivated by the reason to constrain the volume of the liquid phase within the system in response to the description of growth, which is modelled through a mass exchange between the solid phase and liquid phase within the biphasic model. Although the nutrient phase acts as a source for growth, the proposed mass supply function used to correlate the deposition of sarcomeres in relation to growth is predominantly mechanically driven and bears no connection to any biochemical constituent, which therefore renders the nutrient phase as a physiologically arbitrary quantity. However, the provision of the nutrient phase is a platform for the inclusion of known constituents which actively contribute towards growth, which may be explored in future research. The triphasic model is applied to a full cardiac cycle of a left ventricle model, extracted from cardiovascular magnetic resonance (CMR) scans of patients diagnosed with RHD. © The Authors, published by EDP Sciences. This is an open access article distributed un

关键词： Tissue

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An innovative study of e-payment systems adoption in higher education: Theoretical constructs and empirical analysis

International Journal of Interactive Mobile Technologies

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International Journal of Interactive Mobile Technologies 2019年第6期13卷 68-83页

作者： Salloum, Said A. Al-Emran, Mostafa Khalaf, Rifat Habes, Mohammed Shaalan, Khaled University of Fujairah Al Fujairah United Arab Emirates Applied Computational Civil and Structural Engineering Research Group Faculty of Civil Engineering Ton Duc Thang University Ho Chi Minh City Viet Nam Faculty of Engineering and IT The British University in Dubai Dubai United Arab Emirates

Examining the adoption of e-payment systems is not a new research topic. Nevertheless, studying the factors affecting the adoption of epayment systems in higher educational institutions is a new research trend. Thus, this study is considered one of the few that attempts to investigate the factors affecting the e-payment systems adoption in six different universities in the United Arab of Emirates (UAE). A total number of 289 students took part in the study. This study proposed a new research model in which the students' intention to use the e-payment systems are affected by five different factors including perceived benefit, performance expectancy, perceived risk, perceived security/ privacy, and trust. The partial least squares-structural equation modeling (PLS-SEM) approach was used to validate the research model. The empirical results suggested that perceived benefit and performance expectancy have a significant positive relationship with the students' intention to use e-payment systems, whereas perceived security/privacy and perceived risk exhibited a significant negative relationship. However, the results triggered out that trust has an insignificant relationship with the students' intention to use e-payment systems. The results acquired from this research provide a fresh and an up-to-date information on the e-payment systems adoption in the higher educational institutions. © 2019, International Association of Online engineering.

关键词： Students

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Investigating partnering performance in the vietnamese construction industry

Investigating partnering performance in the vietnamese const...

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International Conference on Sustainable civil engineering and Architecture, ICSCEA 2019

作者： Vo, Khoa Dang Do, Sy Tien Nguyen, Thu Anh Dang, Chau Ngoc Tran, Thanh Huy Le-Hoai, Long Ho Chi Minh City Viet Nam Applied Computational Civil and Structural Engineering Research Group Faculty of Civil Engineering Ton Duc Thang University Ho Chi Minh City Viet Nam Uscons Construction Investment Corporation Ho Chi Minh City Viet Nam Ho Chi Minh City University of Technology Ho Chi Minh City Viet Nam

ISBN: (纸本)9789811551437

Partnering has been recommended as an innovative arrangement to avoid adversarial relations and orient participants towards a win-win attitude in construction projects. Although it has been widely applied in many countries’ construction activities in recent decades, the concept is relatively new to practitioners in the Vietnamese construction industry. The main aim of this paper is to develop a model that practitioners can easily employ to evaluate the level of their partnership success through the contribution of success factors (SFs). A questionnaire survey was conducted to provide a data set of 79 responses for the analysis. Factor analysis has presented eight underlying dimensions of SFs in Vietnam;namely dedication, readiness, coordination, teamwork, sufficiency, leading, balance, and clarity;which were used as potential independent variables for the model. The model, developed using logistic regression technique, is of relevance to practitioners in developing, adjusting and improving their strategies to improve partnering performance. © Springer Nature Singapore Pte Ltd 2020.

关键词： Factor analysis

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Mobile Payment Adoption: A Systematic Review of the UTAUT Model

Mobile Payment Adoption: A Systematic Review of the UTAUT Mo...

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2019 International Conference on Fourth Industrial Revolution, ICFIR 2019

作者： Al-Saedi, Karrar Al-Emran, Mostafa Abusham, Eimad El-Rahman, Sahar A. Faculty of Computing and Information Technology Sohar University Sohar Oman Applied Computational Civil and Structural Engineering Research Group Faculty of Civil Engineering Ton Duc Thang University Ho Chi Minh City Viet Nam Princess Nourah Bint Abdulrahman University Saudi Arabia Faculty of Engineering at Shoubra Benha University Egypt

ISBN: (纸本)9781728114781

Recently, Mobile payment (M-payment) is fast becoming an essential research field in the information technology domain. Although numerous sectors have adopted the M-payment in different contexts, the factors that affect its adoption is still not apparent. Different information systems (IS) theories/models were developed in order to study the adoption of a specific new technology. One of the most commonly used and validated models in empirical studies is the Unified Theory of Acceptance and Use of Technology (UTAUT) model. Based on the literature, research neglects to review the M-payment adoption studies. The main objective of this study is to systematically review the M-payment adoption studies that involve the UTAUT as the theoretical model. In that, a total of 25 research articles were synthesized and analyzed. The major findings include that 48% of the analyzed studies were conducted in the industrial sectors. Additionally, 80% of the analyzed studies were mainly relied on questionnaire surveys for data collection. Besides, our results revealed that perceived risk and perceived trust are regarded as the most frequent factors that were used to extend the UTAUT to study the M-payment adoption. These findings provide a comprehensive reference for researchers who intend to conduct further research in M-payment. © 2019 IEEE.

关键词： Surveys

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