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Morphological Change in the Northern Red River Delta,Vietnam

Journal of Ocean University of China 2018年第6期17卷 1272-1280页

作者： BUI Vuong Van FAN Daidu nguyen dac ve TRAN Dinh Lan TRAN Duc Thanh HOANG Van Long nguyen Thi Hong Hanh Institute of Marine Environment and Resources Vietnam Academy of Science and TechnologyHaiphong 18000Vietnam State Key Laboratory of Marine Geology Tongji UniversityShanghai 200092China Hanoi University of Mining and Geology Hanoi 10000Vietnam Graduate University of Science and Technology Vietnam Academy of Science and TechnologyHanoi 10000Vietnam

Coastal erosion has become a worldwide concern, typically in the densely populated Asian mega-river deltas. Severe coastal erosion in the southern Red River Delta(RRD) has been intensively studied. Coastal morphological change in the northern RRD was examined in detail through DEM(Digital Elevation Model) analysis based on time series of bathymetrical maps(1965–2004) and Landsat images(1975–2015) in this study. The results show that the northern RRD is featured by rapid coastal accretion in the past few decades, although suspended sediment flux has dropped by roughly 60% after the completeness of Hoa Binh Dam(HBD) in 1988 and relative sea level rose at 1.9 mm yr^(-1). However, accretion at the outer part of subtidal shoals and platforms was observed to slow down quickly or even turned into erosion in the last two decades. The resuspended sediments from the erosion zone can be transported landward to replenish the inner coastal zone, keeping the latter accretion in the near future to compensate for the sediment discharge decrease from the river. However, this lag effect should be terminated soon if other adverse effects go worse, e.g., damming rivers, sea-level rising, strengthening storms, land reclamation and other poor-designed coastal engineering. Coastal planners and managers should pay full attention to these changes.

关键词： Morphological change DEM coastal erosion coastal engineering coastal management tide-dominated Red River Delta

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Fabrication and Characterization of Multi-layer Heat Mirror with Photocatalytic Properties

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Chinese Physics Letters 2009年第11期26卷 152-155页

作者： Tran Le Tuan Tran Huu Chi nguyen dac Ngoc Son Luu Minh Nam Hoang Dinh Quan nguyen Department of Applied Physics College of Natural Science National University of He Chi Mirth City 227 Nguyen Van Cu District 5 Ward 4 He Chi Minh City Vietnam Department of Chemical Engineering College of Technology National University of He Chi Minh City 168 Ly Thuong Kiet District 10 Ho chi Minh City Vietnam

A novel TiO2（5）/TiO2（buffer）/Ti（4）/Ag（3）/Ti（2）/TiO2（1） multi-layer film coating with corning glass is designed and fabricated by a dc magnetron sputtering method as a renovation of the well-known TiO2/Ti/Ag/Ti/TiO2 system in order to obtain a heat mirror system with photocatalytic properties due to sufficient thickness of the Ti02 layer. The outer TiO2 layer is fabricated in two steps, possibly claimed as two layers TiO2（5） and TiO2（buuer）, among which TiO2（buffer） the 70-nm-thick layer deposited in poor oxygen effectively minimizes the oxidation toward its neighbor Ti（4） layer. The optimal total thickness of the TiO2（5） and TiO（buffer） di-layer is found to be 300nm to yield a highly photo-catalytic property of the film without affecting the optical properties considerably. This multi-layer film can transmit light of above 75-85% in the visible spectrum （380 ≤ λ≤ 760 nm） and reflect radiation of above 90% in the infrared spectrum （ λ≥760 nm）. Such multi-layer coatings are strongly recommended not only as promising transparent heat mirrors but also as photo-catalytic films for architectural window coatings.

关键词： Condensed matter: electrical magnetic and optical Surfaces interfaces and thin films Chemical physics and physical chemistry

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Detecting Lumbar Implant and Diagnosing Scoliosis from Vietnamese X-Ray Imaging Using the Pre-Trained API Models and Transfer Learning

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Computers, Materials & Continua 2021年第1期66卷 17-33页

作者： Chung Le Van Vikram Puri nguyen Thanh Thao dac-Nhuong Le Duy Tan University Da Nang550000Vietnam Department of Radiology Hue University of Medicine and PharmacyHue UniversityHue530000Vietnam Institute of Research and Development Duy Tan UniversityDanang550000Vietnam Faculty of Information Technology Duy Tan UniversityDanang550000Vietnam

With the rapid growth of the autonomous system,deep learning has become integral parts to enumerate applications especially in the case of healthcare *** body vertebrae are the longest and complex parts of the human *** are numerous kinds of conditions such as scoliosis,vertebra degeneration,and vertebrate disc spacing that are related to the human body vertebrae or spine or *** detection of these problems is very important otherwise patients will suffer from a disease for a *** this proposed system,we developed an autonomous system that detects lumbar implants and diagnoses scoliosis from the modified Vietnamese x-ray *** applied two different approaches including pre-trained APIs and transfer learning with their pre-trained models due to the unavailability of sufficient x-ray medical *** results show that transfer learning is suitable for the modified Vietnamese x-ray imaging data as compared to the pre-trained API ***,we also explored and analyzed four transfer learning models and two pre-trained API models with our datasets in terms of accuracy,sensitivity,and specificity.

关键词： Lumbar implant diagnosing scoliosis X-Ray imaging transfer

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Optimizing Bidders Selection of Multi-Round Procurement Problem in Software Project Management Using Parallel Max-Min Ant System Algorithm

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Computers, Materials & Continua 2021年第1期66卷 993-1010页

作者： dac-Nhuong Le Gia Nhu nguyen arish Garg Quyet-Thang Huynh Trinh Ngoc Bao nguyen Ngoc Tuan Institute of Research and Development Duy Tan UniversityDa Nang550000Vietnam Faculty of Information Technology Duy Tan UniversityDa Nang550000Vietnam Faculty of Information Technology Haiphong UniversityHaiphong180000Vietnam Graduate School Duy Tan UniversityDa Nang550000Vietnam School of Mathematics Thapar Institute of Engineering and TechnologyPatiala147004India Hanoi University of Science and Technology Hanoi100000Vietnam Hanoi University Hanoi100000Vietnam Department of ICT Ministry of Education and TrainingHanoi100000Vietnam

This paper presents a Game-theoretic optimization via Parallel Min-Max Ant System(PMMAS)algorithm is used in practice to determine the Nash equilibrium value to resolve the confusion in choosing appropriate bidders of multi-round procurement problem in software project *** this end,we introduce an approach that proposes:(i)A Game-theoretic model of multiround procurement problem(ii)A Nash equilibrium strategy corresponds to multi-round strategy bid(iii)An application of PSO for the determination of global Nash *** balance point in Nash Equilibrium can help to maintain a sustainable structure not only in terms of project management but also in terms of future *** an alternative of procuring entities subjectively,a methodology to support decision making has been studied using Nash equilibrium to create a balance point on benefit in procurement where buyers and suppliers need multiple rounds of *** goal focus on the balance point in Nash Equilibrium to optimizing bidder selection in multi-round procurement which is the most beneficial for both investors and selected *** PMMAS algorithm is implemented based on MPI(message passing interface)to find the approximate optimal solution for the question of how to choose bidders and ensure a path for a win-win relationship of all participants in the procurement *** also evaluate the speedup ratio and parallel efficiency between our algorithm and other proposed *** the experiment results,the high feasibility and effectiveness of the PMMAS algorithm are verified.

关键词： Parallel min-max ant system multi-objective multi-round procurement software project management project conflicts Nash equilibrium game theory MPI

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A Method of Integrating Length Constraints into Encoder-Decoder Transformer for Abstractive Text Summarization

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Intelligent Automation & Soft Computing 2023年第10期38卷 1-18页

作者： Ngoc-Khuong nguyen dac-Nhuong Le Viet-Ha nguyen Anh-Cuong Le Faculty of Information Technology Haiphong UniversityHaiphong180000Vietnam Faculty of Information Technology VNU University of Engineering and TechnologyHanoi10000Vietnam Natural Language Processing and Knowledge Discovery Laboratory Faculty of Information TechnologyTon Duc Thang UniversityHo Chi Minh CityVietnam

Text summarization aims to generate a concise version of the original *** longer the summary text is,themore detailed it will be fromthe original text,and this depends on the intended ***,the problem of generating summary texts with desired lengths is a vital task to put the research into *** solve this problem,in this paper,we propose a new method to integrate the desired length of the summarized text into the encoder-decoder model for the abstractive text summarization *** length parameter is integrated into the encoding phase at each self-attention step and the decoding process by preserving the remaining length for calculating headattention in the generation process and using it as length embeddings added to theword *** conducted experiments for the proposed model on the two data sets,Cable News Network(CNN)Daily and NEWSROOM,with different desired output *** obtained results show the proposed model’s effectiveness compared with related studies.

关键词： Length controllable abstractive text summarization length embedding

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A new species of the genus Leptolalax (Anura： Megophryidae) from southern Vietnam

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Zoological Research 2018年第3期39卷 185-201页

作者： Tang Van Duong Dang Trong Do Chung dac Ngo Truong Quang nguyen Nikolay A. Poyarkov Vietnam National Museum of Nature Vietnam Academy of Science and Technology Hanoi Vietnam Department of vertebrate Zoology Biological FacultyLomonosov Moscow State University Moscow 119234 Russia Faculty of Natural Sciences Phu Yen University Tuy Hoa Phu Yen Vietnam College of Education Hue University Hue Vietnam Institute of Ecology and Biological Resources Vietnam Academy of Science and Technology Hanoi Vietnam Graduate University of Science and Technology Vietnam Academy of Science and Technology Cau Giay Hanoi Vietnam Joint Russian- Vietnamese Tropical Research and Technological Center Nghia Do Cau Giay Hanoi Vietnam

We describe a new species of megophryid frog from Phu Yen Province in southern Vietnam. Leptolalax macrops sp. nov. is distinguished from its congeners by a combination of the following morphological attributes：（1） body size medium （SVL 28.0-29.3 mm in three adult males, 30.3 mm in single adult female）; （2） supra-axillary glands present, creamy white; ventrolateral glands indistinct; （3） tympanum externally distinct; （4） dorsal skin roughly granular with larger tubercles, dermal ridges on dorsum absent; （5） rudimentary webbing present between fingers I-II and I1-111; rudimentary webbing between all toes; fingers and toes without dermal fringes; （6） in life ventral surface greyish-violet with white speckling; （7） supratympanic fold distinct, dark brown in life; （8） iris bicolored, typically golden in upper half, fading to golden green in lower half; （9） tibia short （TbL/SVL 0.44-0.45 in males）; and （10） eyes large and protuberant （ED/SVL 0.15-0.16 in males） From all congeners for which comparable sequences are available, the new species differs markedly in the 16S rRNA mitochondrial gene sequence （P-distance〉5.7%）. The new species is currently known only from montane evergreen tropical forests of Song Hinh District, Phu Yen Province, and M＇Drak District of Dak Lak Province at elevations of 470-630 m a.s.l.. We suggest the new species should be considered as Data Deficient following the IUCN＇s Red List categories. We also report a previously unknownLeptolalax mtDNA lineage from an evergreen tropica forest in the Hoa Thinh District of Phu Yen Province which may also represent an undescribed species.

关键词： Leptolalax macrops sp. nov. Phu YenProvince Dak Lak Province Southern coastal regionof Vietnam

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Deep Learning Based Optimal Multimodal Fusion Framework for Intrusion Detection Systems for Healthcare Data

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Computers, Materials & Continua 2021年第3期66卷 2555-2571页

作者： Phong Thanh nguyen Vy Dang Bich Huynh Khoa Dang Vo Phuong Thanh Phan Mohamed Elhoseny dac-Nhuong Le Department of Project Management Ho Chi Minh City Open UniversityHo Chi Minh City700000Vietnam Department of Learning Material Ho Chi Minh City Open UniversityHo Chi Minh City700000Vietnam Faculty of Computers and Information Mansoura UniversityDakahlia Governorate35516Egypt Institute of Research and Development Duy Tan UniversityDanang550000Vietnam Faculty of Information Technology Duy Tan UniversityDanang550000Vietnam

Data fusion is a multidisciplinary research area that involves different *** is used to attain minimum detection error probability and maximum reliability with the help of data retrieved from multiple healthcare *** generation of huge quantity of data from medical devices resulted in the formation of big data during which data fusion techniques become *** medical data is a crucial issue of exponentially-pacing computing world and can be achieved by Intrusion Detection Systems(IDS).In this regard,since singularmodality is not adequate to attain high detection rate,there is a need exists to merge diverse techniques using decision-based multimodal fusion *** this view,this research article presents a new multimodal fusion-based IDS to secure the healthcare data using *** proposed model involves decision-based fusion model which has different processes such as initialization,pre-processing,Feature Selection(FS)and multimodal classification for effective detection of *** FS process,a chaotic Butterfly Optimization(BO)algorithmcalled CBOA is *** the classic BO algorithm offers effective exploration,it fails in achieving faster *** order to overcome this,i.e.,to improve the convergence rate,this research work modifies the required parameters of BO algorithm using chaos ***,to detect intrusions,multimodal classifier is applied by incorporating three Deep Learning(DL)-based classification ***,the concepts like Hadoop MapReduce and Spark were also utilized in this study to achieve faster computation of big data in parallel computation *** validate the outcome of the presented model,a series of experimentations was performed using the benchmark NSLKDDCup99 Dataset *** proposed model demonstrated its effective results on the applied dataset by offering the maximum accuracy of 99.21%,precision of 98.93%and detection rate of 99.59%.The results assured the betterm

关键词： Big data data fusion deep learning intrusion detection bio-inspired algorithm spark

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Dynamic Data Optimization in IoT-Assisted Sensor Networks on Cloud Platform

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Computers, Materials & Continua 2022年第7期72卷 1357-1372页

作者： nguyen A.Tuan D.Akila Souvik Pal Bikramjit Sarkar Thien Khai Tran G.Mothilal Nehru dac-Nhuong Le Faculty of Information Technology Ho Chi Minh City University of Foreign Languages-Information TechnologyHo Chi Minh City70000Vietnam Department of Information Technology Vels Institute of ScienceTechnology&Advanced StudiesChennai600117India Department of Computer Science and Engineering Sister Nivedita UniversityKolkata700156India Department of Computer Science and Engineering JIS College of EngineeringNadia741235India Institute of Research and Development Duy Tan UniversityDanang550000Vietnam School of Computer Science Duy Tan UniversityDanang550000Vietnam

This article presents a new scheme for dynamic data optimization in IoT(Internet of Things)-assisted sensor *** various components of IoT assisted cloud platform are *** addition,a new architecture for IoT assisted sensor networks is ***,a model for data optimization in IoT assisted sensor networks is proposed.A novel Membership inducing Dynamic Data Optimization Membership inducing Dynamic Data Optimization(MIDDO)algorithm for IoT assisted sensor network is proposed in this *** proposed algorithm considers every node data and utilized membership function for the optimized data *** proposed framework is compared with two stage optimization,dynamic stochastic optimization and sparsity inducing optimization and evaluated in terms of reliability ratio,coverage ratio and sensing *** optimization was performed based on the availability of cloud resource,sensor energy,data flow volume and the centroid of each *** was inferred that the proposed MIDDO algorithm achieves an average performance ratio of 76.55%,reliability ratio of 94.74%,coverage ratio of 85.75%and sensing error of 0.154.

关键词： Data optimization IoT sensor network reliability membership sensor energy

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A New Genetic Algorithm Applied to Multi-Objectives Optimal of Upgrading Infrastructure in NGWN

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Communications and Network 2013年第3期5卷 223-231页

作者： dac-Nhuong Le Nhu Gia nguyen dac Binh Ha Vinh Trong Le Duytan University Danang Vietnam Faculty of Information Technology Haiphong University Haiphong Vietnam

A problem of upgrading to the Next Generation Wireless Network (NGWN) is backward compatibility with pre-existing networks, the cost and operational benefit of gradually enhancing networks, by replacing, upgrading and installing new wireless network infrastructure elements that can accommodate both voice and data demand. In this paper, we propose a new genetic algorithm has double population to solve Multi-Objectives Optimal of Upgrading Infrastructure (MOOUI) problem in NGWN. We modeling network topology for MOOUI problem has two levels in which mobile users are sources and both base stations and base station controllers are concentrators. Our objective function is the sources to concentrators connectivity cost as well as the cost of the installation, connection, replacement, and capacity upgrade of infrastructure equipment. We generate two populations satisfy constraints and combine them to build solutions and evaluate the performance of my algorithm with data randomly generated. Numerical results show that our algorithm is a promising approach to solve this problem.

关键词： Multi-Objectives Optimal Next Generation Wireless Network Network Design Capacity Planning Genetic Algorithm Two-populations

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Effective Electrical Submersible Pump Management Using Machine Learning

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Open Journal of Civil Engineering 2021年第1期11卷 70-80页

作者： Son Tung Pham Phi Son Vo dac Nhat nguyen Faculty of Geology & Petroleum Engineering Hochiminh City University of Technology-Vietnam National University Hochiminh Vietnam

Artificial lift plays an important role in petroleum industry to sustain production flowrate and to extend the lifespan of oil wells. One of the most popular artificial lift methods is Electric Submersible Pumps (ESP) because it can produce high flowrate even for wells with great depth. Although ESPs are designed to work under extreme conditions such as corrosion, high temperatures and high pressure, their lifespan is much shorter than expected. ESP failures lead to production loss and increase the cost of replacement, because the cost of intervention work for ESP is much higher than for other artificial lift methods, especially for offshore wells. Therefore, the prediction of ESP failures is highly valuable in oil production and contributes a lot to the design, construction and operation of oil wells. The contribution of this study is to use 3 machine learning algorithms, which are Decision Tree, Random Forest and Gradient Boosting Machine, to build predictive models for ESP lifespan while using both dynamic and static ESP parameters. The results of these models were compared to find out the most suitable model for the prediction of ESP life cycle. In addition, this study also evaluated the influence factor of various operating paramverdana;">ver

关键词： Machine Learning Electrical Submersible Pump Decision Tree Random For-est Gradient Boosting Machine

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