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A novel semantic segmentation approach based on U-Net,WU-Net,and U-Net++deep learning for predicting areas sensitive to pluvial flood at tropical area

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International Journal of Digital Earth 2023年第1期16卷 3661-3679页

作者： Laura Melgar-García Francisco Martínez-álvarez Dieu Tien bui Alicia Troncoso Data Science&Big Data Lab Pablo de Olavide UniversitySevilleSpain GIS Group Department of Business and ITUniversity of South-Eastern NorwayGullbringvegen 36B?i Telemark3800Norway

Floods remain one of the most devastating weather-induced disastersworldwide, resulting in numerous fatalities each year and severelyimpacting socio-economic development and the ***, the ability to predict flood-prone areas in advance is crucialfor effective risk management. The objective of this research is to assessand compare three convolutional neural networks, U-Net, WU-Net, andU-Net++, for spatial prediction of pluvial flood with a case study at atropical area in the north of Vietnam. They are relative new convolutionalgorithms developed based on U-shaped architectures. For this task, ageospatial database with 796 historical flood locations and 12 floodindicators was prepared. For training the models, the binary crossentropywas employed as the loss function, while the Adaptive momentestimation (ADAM) algorithm was used for the optimization of themodel parameters, whereas, F1-score and classification accuracy (Acc)were used to assess the performance of the models. The results unequivocally highlight the high performance of the three models,achieving an impressive accuracy rate of 96.01%. The flood susceptibility maps derived from this research possess considerable utility for local authorities, providing valuable insights and informationto enhance decision-making processes and facilitate the implementation of effective risk management strategies.

关键词： Flash-flood assessment convolutional networks climate change GIS

Mechanism of Japanese encephalitis virus genotypes replacement based on human,porcine and mosquito-originated cell lines model

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Asian Pacific Journal of Tropical Medicine 2016年第4期9卷 325-328页

作者： Loan Phuong Do Trang Minh bui Nga Thi Phan National Institute of Hygiene and Epidemiology

Objective:To examine the multiplication efficiency Japanese encephalitis virus(JEV)genotype Ⅰ(G Ⅰ) and genotype Ⅲ(GⅢ) of different cell lines which originated from human,porcine,mosquitoes in order to prove mechanism of JEV G Ⅰ replacement JEV GⅢ since it emerging in nature recent ***:The mixture of Gi and GⅢ JEV isolates was inoculated on human rhabdomyosarcoma(RD).pig kidney epithelial(PS) and Aedes albopictus C6/36 clone(C6/36) which originated from human,porcine and mosquitoes,*** assays were performed to calculate virus titer and real-time RT-PCR with GⅠand GⅢspecific primer sets to quantify the number of GⅠ and GUI RNA ***:The highest virus titer reached at the 3rd day of post infection when G Ⅰand GⅢ mixture was inoculated on RD and PS and that of C636 was at the 4^(th)*** were amplified and maintained by C6/36 cells after 10 passages whereas that by RD and PS only limited within 8 and 6 passages,respectively.GⅠ strain amplified and maintained more efficiently on C6/36 and PS but not *** GⅢ strain amplified and maintained more efficiently on ***:There is a correlation between the multiplication efficiency of GⅠ and GⅢ JEV strains when these two genotype strains co-infected on different cell lines with the predominance of GⅠstrains in C6/36 and PS and the limited detection of G 1 strains in RD cells proving a possible mechanism of shift JEV genotypes in nature recent decades since GⅠ emerging.

关键词： Japanese encephalitis virus Genotype I Genotype Ⅲ Multiplication Shift genotype

＂RADIOTRANSCRIPTOMICS＂： A synergy of imaging and transcriptomics in clinical assess- ment

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Frontiers of Electrical and Electronic Engineering in China 2016年第1期4卷 1-12页

作者： Amal Katrib William Hsu Alex bui Yi Xing Department of Microbiology Immunology and Molecular Genetics University of California Los Angeles Los Angeles CA_ 90095 USA Department of Radiological Sciences University of California Los Angeles Los Angeles CA 90095 USA

Recent advances in quantitative imaging and ＂omics＂ technology have generated a wealth of mineable biological ＂big data＂. With the push towards a P4 ＂predictive, preventive, personalized, and participatory＂ approach to medicine, researchers began integrating complementary tools to further tune existing diagnostic and therapeutic models. The field of radiogenomics has long pioneered such multidisciplinary investigations in neuroscience and oncology, correlating genotypic and phenotypic signatures to study structural and functional changes in relation to altered molecular behavior. Given the innate dynamic nature of complex disorders and the role of environmental and epigenetic factors in pathogenesis, the transcriptome can further elucidate serial modifications undetected at the genome level. We therefore propose ＂radiotranscriptomics＂ as a new member of the P4 medicine initiative, combining transcriptome information, including gene expression and isoform variation, and quantitative image annotations.

关键词： quantitative imaging transcriptomics RNA-seq genomics image genomics radiogenomics systems biology precision medicine

Spatial prediction of rainfall-induced shallow landslides using hybrid integration approach of Least-Squares Support Vector Machines and differential evolution optimization:a case study in Central Vietnam

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International Journal of Digital Earth 2016年第11期9卷 1077-1097页

作者： Dieu Tien bui Binh Thai Pham Quoc Phi Nguyen Nhat-Duc Hoang Geographic Information System Group Department of Business Administration and Computer ScienceUniversity College of Southeast NorwayBøi TelemarkNorway Faculty of Geomatics and Land Administration Hanoi University of Mining and GeologyHanoiVietnam Department of Civil Engineering Gujarat Technological UniversityAhmedabadGujaratIndia Department of Geotechnical Engineering University of Transport TechnologyHa NoiVietNam Department of Environmental Sciences Hanoi University of Mining and GeologyHanoiVietnam Faculty of Civil Engineering Institute of Research and DevelopmentDuy Tan UniversityDanangVietnam

This study represents a hybrid intelligence approach based on the differential evolution optimization and Least-Squares Support Vector Machines for shallow landslide prediction,named as *** LSSVM is used to establish a landslide prediction model whereas the DE is adopted to search the optimal tuning parameters of the LSSVM *** this research,a GIS database with 129 historical landslide records in the Quy Hop area(Central Vietnam)has been collected to establish the hybrid *** receiver operating characteristic(ROC)curve and area under the curve(AUC)were used to assess the performance of the newly constructed *** results show that the proposed model has high performances with approximately 82%of AUCs on both training and validating *** model’s results were compared with those obtained from other methods,Support Vector Machines,Multilayer Perceptron Neural Networks,and J48 Decision *** result comparison demonstrates that the DE-LSSVMSLP deems best suited for the dataset at hand;therefore,the proposed model can be a promising tool for spatial prediction of rainfall-induced shallow landslides for the study area.

关键词： Shallow landslide Least-Squares Support Vector Machines differential evolution GIS Vietnam

Coverage Optimization of LTE Networks Based on Antenna Tilt Adjusting Considering Network Load

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China Communications 2017年第5期14卷 48-58页

作者： NhuQuan Phan ThiOanh bui Huilin Jiang Pei Li Zhiwen Pan Nan Liu National Mobile Communications Research Laboratory Southeast UniversityNanjing 210096JiangsuChina Faculty of Mechatronics-Electronics Lac Hong UniversityBien Hoa City 810000Viet Nam Institute of electrical engineering Nanjing Xiaozhuang UniversityNanjing 211171China

In this paper,we investigate the coverage optimization for LTE networks considering the network load. The network coverage is defined as the number of served users of evolved Node B(eNB)which is determined by e NBs' antenna tilt angles(ATA). The coverage is optimized by optimizing the number of served users based on the Modified Particle Swarm Optimization(MPSO)algorithm. Simulation results show that both the number of served users by each e NB and the system throughput are significantly increased. As well,the average load and the bandwidth efficiency of the network are improved.

关键词： LTE networks antenna tilt angle coverage optimization and modified particle swarm optimization

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

Households’ Willingness-to-Pay to Reduce the Use of Plastic Bags: Case Study in Viet Nam

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Journal of Environmental Protection 2022年第3期13卷 289-298页

作者： Nguyen Van Song Nguyen Minh hieu Vu Ngoc Huyen Nguyen Dang Que Nguyen Van Huong bui Thi Minh Nguyet Viet Nam National University of Agriculture (VNUA) Ha Noi Viet Nam National Academy of Public Administration (NAPA) Ha Noi Viet Nam Hung Yen University of Technology and Education (UTEHY) Hung Yen Viet Nam Vietnam National University of Forestry Xuan Mai Ha Noi Vietnam

This study used the Binary Logistic regression model to estimate the willingness to pay (WTP) to reduce the use of plastic bags in the daily life of people in the Linh Nam ward. This study notes that households with higher incomes and higher levels of education tend to be more willing to pay. In addition, those who do not have access to information about the harmful effects of plastic bags and receive a higher proposed price often refuse to pay.

关键词： Binary Logistic Regression Willingness to Pay Plastic Bags

Climate change and groundwater resources in Mekong Delta, Vietnam

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Journal of Groundwater Science and Engineering 2017年第1期5卷 76-90页

作者： Duong D bui Nghia C Nguyen Nuong T bui Anh T T Le Dao T Le National Center for Water Resources Planning and Investigation MONRE Vietnam Tokyo Metropolitan University Japan Center for Environmental Fluid Dynamics Hanoi University of Science Vietnam

Groundwater resources have considerable influences on the human population and socioeconomic development of Vietnam and the Mekong River Delta(MRD). This paper presents an overview of the relationship between climate change and groundwater in the MRD, including the challenges, strategies and technical measures. Our results showed that groundwater levels are related to other climate and hydrological variables(i.e., rainfall, river levels, etc.); therefore, the impacts of climate change on the groundwater resources of the Mekong delta are significant, especially on groundwater recharge. Based on the results of this study, it is recommended that groundwater development in the future should focus on reducing groundwater harvesting, enhancing groundwater quantity by establishing artificial works and exploiting surface water. This study suggests that the Artificial Neural Network(ANN) model is an effective tool for forecasting groundwater levels in periods of 1 month and 3 months for aquifers in the natural and tidal regime areas of the delta.

关键词： Groundwater management Climate change ANN model Mekong River Delta

Advances in scalable gas-phase manufacturing and processing of nanostructured solids： A review

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Particuology 2017年第1期15卷 15-39页

作者： Samir Salameh Jesus Gomez-Hernandez Aristeidis Goulas Hao Van bui J. Ruud van Ommen Delft University ofTechnology Julianalaan 136 2628 BL Delft The Netherlands Carlos III University of Madrid Avda. de la Universidad 30 28911 Leganes Madrid Spain Delft IMP B.V. Mekelweg 2 2628 CD Delft The Netherlands

Although the gas-phase production of nanostructured solids has already been carried out in industry for decades, only in recentyears has research interest in this topic begun to increase. Nevertheless, despite the remarkable scientific progress made recently, many long-established processes are still used in industry. Scientific advancements can potentially lead to the improvement of existing industrial processes, but also to the development of completely new routes. This paper aims to review state-of-the-art synthesis and processing technologies, as well as the recent developments in academic research. Flame reactors that produce inorganic nanoparticles on industrial- and lab-scales are described, alongside a detailed overview of the different systems used for the production of carbon nanotubes and graphene. We discuss the problems of agglomeration and mixing of nanoparticles, which are strongly related to synthesis and processing. Finally, we focus on two promising processing techniques, namely nanoparticle fluidization and atomic layer deposition.

关键词： Nanoparticle synthesis Gas-phase process Nanoparticle fluidization Atomic layer deposition Agglomeration