Vietnam National University, Hanoi

www.vnu.edu.vn
Hanoi, Vietnam

Vietnam National University, Hanoi is a university in Hanoi, the capital of Vietnam.The university has 10 colleges and faculties. This is one of two national universities and also one of the two largest universities in Vietnam, along with Vietnam National University, Ho Chi Minh City. Wikipedia.

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Do T.Q.,Vietnam National University, Hanoi
Physical Review D - Particles, Fields, Gravitation and Cosmology | Year: 2016

We study higher-dimensional scenarios of massive bigravity, which is a very interesting extension of nonlinear massive gravity since its reference metric is assumed to be fully dynamical. In particular, the Einstein field equations along with the following constraint equations for both physical and reference metrics of a five-dimensional massive bigravity will be addressed. Then, we study some well-known cosmological spacetimes such as the Friedmann-Lemaitre-Robertson-Walker, Bianchi type I, and Schwarzschild-Tangherlini metrics for the five-dimensional massive bigravity. As a result, we find that massive graviton terms will serve as effective cosmological constants in both physical and reference sectors if a special scenario, in which reference metrics are chosen to be proportional to physical ones, is considered for all mentioned metrics. Thanks to the constancy property of massive graviton terms, consistent cosmological solutions will be figured out accordingly. © 2016 American Physical Society.


Wong J.J.-M.,Vietnam National University, Hanoi
Critical Care Medicine | Year: 2017

OBJECTIVES:: The Pediatric Acute Lung Injury Consensus Conference developed a pediatric specific definition for acute respiratory distress syndrome (PARDS). In this definition, severity of lung disease is stratified into mild, moderate, and severe groups. We aim to describe the epidemiology of patients with PARDS across Asia and evaluate whether the Pediatric Acute Lung Injury Consensus Conference risk stratification accurately predicts outcome in PARDS. DESIGN:: A multicenter, retrospective, descriptive cohort study. SETTING:: Ten multidisciplinary PICUs in Asia. PATIENTS:: All mechanically ventilated children meeting the Pediatric Acute Lung Injury Consensus Conference criteria for PARDS between 2009 and 2015. INTERVENTIONS:: None. MEASUREMENTS AND MAIN RESULTS:: Data on epidemiology, ventilation, adjunct therapies, and clinical outcomes were collected. Patients were followed for 100 days post diagnosis of PARDS. A total of 373 patients were included. There were 89 (23.9%), 149 (39.9%), and 135 (36.2%) patients with mild, moderate, and severe PARDS, respectively. The most common risk factor for PARDS was pneumonia/lower respiratory tract infection (309 [82.8%]). Higher category of severity of PARDS was associated with lower ventilator-free days (22 [17–25], 16 [0–23], 6 [0–19]; p < 0.001 for mild, moderate, and severe, respectively) and PICU free days (19 [11–24], 15 [0–22], 5 [0–20]; p < 0.001 for mild, moderate, and severe, respectively). Overall PICU mortality for PARDS was 113 of 373 (30.3%), and 100-day mortality was 126 of 317 (39.7%). After adjusting for site, presence of comorbidities and severity of illness in the multivariate Cox proportional hazard regression model, patients with moderate (hazard ratio, 1.88 [95% CI, 1.03–3.45]; p = 0.039) and severe PARDS (hazard ratio, 3.18 [95% CI, 1.68, 6.02]; p < 0.001) had higher risk of mortality compared with those with mild PARDS. CONCLUSIONS:: Mortality from PARDS is high in Asia. The Pediatric Acute Lung Injury Consensus Conference definition of PARDS is a useful tool for risk stratification. Copyright © by 2017 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.


Van Hieu D.,Vietnam National University, Hanoi
Mathematical Methods in the Applied Sciences | Year: 2017

Based on the extended extragradient-like method and the linesearch technique, we propose three projection methods for finding a common solution of a finite family of equilibrium problems. The linesearch used in the proposed algorithms has allowed to reduce some conditions imposed on equilibrium bifunctions. The strongly convergent theorems are established without the Lipschitz-type condition of bifunctions. The paper also helps in the design and analysis of practical algorithms and gives us a generalization of some previously known problems. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.


Horby P.,Vietnam National University, Hanoi
American Journal of Epidemiology | Year: 2012

Prospective community-based studies have provided fundamental insights into the epidemiology of influenza in temperate regions, but few comparable studies have been undertaken in the tropics. The authors conducted prospective influenza surveillance and intermittent seroprevalence surveys in a household-based cohort in Vietnam between December 2007 and April 2010, resulting in 1,793 person-seasons of influenza surveillance. Age-and sex-standardized estimates of the risk of acquiring any influenza infection per season in persons 5 years of age or older were 21.1% (95% confidence interval: 17.4, 24.7) in season 1, 26.4% (95% confidence interval: 22.6, 30.2) in season 2, and 17.0% (95% confidence interval: 13.6, 20.4) in season 3. Some individuals experienced multiple episodes of infection with different influenza types/subtypes in the same season (n = 27) or reinfection with the same subtype in different seasons (n = 22). The highest risk of influenza infection was in persons 5-9 years old, in whom the risk of influenza infection per season was 41.8%. Although the highest infection risk was in school-aged children, there were important heterogeneities in the age of infection by subtype and season. These heterogeneities could influence the impact of school closure and childhood vaccination on influenza transmission in tropical areas, such as Vietnam. © The Author 2012. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.2012This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. © The Author 2012. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.


Duc N.D.,Vietnam National University, Hanoi
Composite Structures | Year: 2013

This paper presents an analytical investigation on the nonlinear dynamic response of eccentrically stiffened functionally graded double curved shallow shells resting on elastic foundations and being subjected to axial compressive load and transverse load. The formulations are based on the classical shell theory taking into account geometrical nonlinearity, initial geometrical imperfection and the Lekhnitsky smeared stiffeners technique with Pasternak type elastic foundation. The non-linear equations are solved by the Runge-Kutta and Bubnov-Galerkin methods. Obtained results show effects of material and geometrical properties, elastic foundation and imperfection on the dynamical response of reinforced FGM shallow shells. Some numerical results are given and compared with ones of other authors. © 2012 Elsevier Ltd.


Son L.H.,Vietnam National University, Hanoi
Applied Soft Computing Journal | Year: 2014

Geo-Demographic Analysis, which is one of the most interesting inter-disciplinary research topics between Geographic Information Systems and Data Mining, plays a very important role in policies decision, population migration and services distribution. Among some soft computing methods used for this problem, clustering is the most popular one because it has many advantages in comparison with the rests such as the fast processing time, the quality of results and the used memory space. Nonetheless, the state-of-the-art clustering algorithm namely FGWC has low clustering quality since it was constructed on the basis of traditional fuzzy sets. In this paper, we will present a novel interval type-2 fuzzy clustering algorithm deployed in an extension of the traditional fuzzy sets namely Interval Type-2 Fuzzy Sets to enhance the clustering quality of FGWC. Some additional techniques such as the interval context variable, Particle Swarm Optimization and the parallel computing are attached to speed up the algorithm. The experimental evaluation through various case studies shows that the proposed method obtains better clustering quality than some best-known ones. © 2014 Elsevier B.V.


Municipal Solid Waste (MSW) is an increasing concern at any municipality in the world, and is one of the primary factors that contribute greatly to the rising of climate change and global warming. MSW collection and disposal especially in the context of developing countries are indeed the urgent requirements for the sustainable development of environment and landscape, which rule over the quality-of-life and life expectancy of human being. In this paper, we concentrate on MSW collection at Danang city, which is one of four largest municipalities in Vietnam having high quantity of the average waste load per person and is bearing negative impacts of climate change such as severe weather conditions and natural disasters as a result. A novel vehicle routing model for the MSW collection problem at Danang city is presented. A novel hybrid method between Chaotic Particle Swarm Optimization and ArcGIS is proposed to generate optimal solutions from the vehicle routing model of Danang. Experimental results on the real dataset of Danang show that the proposed hybrid method obtains better total collected waste quantity than the relevant ones including the manual MSW collection procedure that is currently applied at this city. © 2014 Elsevier Ltd. All rights reserved.


Son L.H.,Vietnam National University, Hanoi
Expert Systems with Applications | Year: 2014

Recommender Systems (RS) have been being captured a great attraction of researchers by their applications in various interdisciplinary fields. Fuzzy Recommender Systems (FRS) is an extension of RS with the fuzzy similarity being calculated based on the users' demographic data instead of the hard user-based degree. Based upon the observations that the FRS researches did not offer a mathematical definition of FRS accompanied with its algebraic operations and properties, and the fuzzy similarity degree is not enough to express accurately the analogousness between users, in this paper we will present a systematic mathematical definition of FRS including theoretical analyses of algebraic operations and properties and propose a novel hybrid user-based fuzzy collaborative filtering method that integrates the fuzzy similarity degrees between users based on the demographic data with the hard user-based degrees calculated from the rating histories into the final similarity degrees in order to obtain high accuracy of prediction. Experimental results on some benchmark datasets show that the proposed method obtains better accuracy than other relevant methods. Lastly, an application for the football results prediction is given to illustrate the uses of the proposed method. © 2014 Elsevier Ltd. All rights reserved.


Grant
Agency: European Commission | Branch: FP7 | Program: ERC-AG | Phase: ERC-AG-PE10 | Award Amount: 1.62M | Year: 2014

More than 100 million people living on the floodplains of the Ganges-Brahmaputra-Meghna, Mekong and Red River, all draining the Himalayas, are consuming arsenic contaminated water. Providing safe drinking water for these people requires a quantitative understanding of the processes regulating the groundwater arsenic content and this knowledge is presently not available. In PREDIAS we propose a revolutionary new approach to study these arsenic contaminated aquifers where sediments and groundwaters are considered as one reacting unit that is changing over time. The key hypothesis is that it is the aquifer sediment burial age that is the overall controlling parameter for the arsenic content. This new approach is explored by studying the groundwater chemistry as a function of sediment burial age, which is equivalent to the geological evolution over time, in part of the Red River floodplain in Vietnam. The investigations comprise delineating the sedimentological development over the last 9000 yrs as well as reconstructing hydrogeological conditions over that period. Process studies will reveal the effect of burial age on the chemical properties of the sediments and the arsenic release mechanisms. They comprise the binding and release mechanisms of arsenic to the aquifer sediment, and the reactivity of sedimentary organic carbon and iron oxides which drive the redox reactions controlling the water chemistry and arsenic mobilization. Information on the sedimentological and hydrogeological development over time as well as a quantification of the geochemical processes will be incorporated in a 3-D reactive transport model which over the last 9000 years, in steps of about 1000 years, can predict the evolution of the arsenic content over space and time in the groundwater of the studied area. The model can be extended in a more conceptual form to larger parts of the Red River delta and Bangladesh using satellite imaging to reveal the geological development in those areas.


Son L.H.,Vietnam National University, Hanoi
Expert Systems with Applications | Year: 2015

Fuzzy clustering is considered as an important tool in pattern recognition and knowledge discovery from a database; thus has been being applied broadly to various practical problems. Recent advances in data organization and processing such as the cloud computing technology which are suitable for the management, privacy and storing big datasets have made a significant breakthrough to information sciences and to the enhancement of the efficiency of fuzzy clustering. Distributed fuzzy clustering is an efficient mining technique that adapts the traditional fuzzy clustering with a new storage behavior where parts of the dataset are stored in different sites instead of the centralized main site. Some distributed fuzzy clustering algorithms were presented including the most effective one - the CDFCM of Zhou et al. (2013). Based upon the observation that the communication cost and the quality of results in CDFCM could be ameliorated through the integration of a distributed picture fuzzy clustering with the facilitator model, in this paper we will present a novel distributed picture fuzzy clustering method on picture fuzzy sets so-called DPFCM. Experimental results on various datasets show that the clustering quality of DPFCM is better than those of CDFCM and relevant algorithms. © 2014 Elsevier B.V. All rights reserved.

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