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Search Results: 1 - 10 of 872 matches for " Khanh Dinh "
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Plasmon modes of double-layer graphene at finite temperature
Dinh Van Tuan,Nguyen Quoc Khanh
Physics , 2011,
Abstract: We calculate the dynamical dielectric function of doped double-layer graphene (DLG), made of two parallel graphene monolayers with carrier densities n 1, n2, respectively, and an interlayer separation of d at finite temperature. The results are used to find the dispersion of plasmon modes and loss functions of DLG for several interlayer separations and layer densities. We show that in the case of n 2=0, the temperature plasmon modes are dramatically different from the zero temperature ones.
Acculturative and Psychosocial Predictors of Academic-Related Outcomes among Cambodian American High School Students
Khanh Dinh,Traci L. Weinstein,Su Yeong Kim
Journal of Southeast Asian American Education and Advancement , 2008,
Abstract: This study examined the acculturative and psychosocial predictors of academic-related outcomes among Cambodian American high school students from an urban school district in the State of Massachusetts. Student participants (N = 163) completed an anonymous survey that assessed demographic characteristics, acculturative experiences, intergenerational conflict, depression, and academic-related outcomes. The main results indicated that acculturative and psychosocial variables were significant predictors of academic-related outcomes. Specifically, Cambodian and Anglo/White cultural orientations and depression played significant roles across the four dimensions of academic-related outcomes, including grade point average, educational aspirations, beliefs in the utility of education, and psychological sense of school membership. This study provides important implications for school-based and family-based prevention and intervention programs in addressing the acculturative and academic challenges faced by Cambodian American students.
Comparisons of VAR Model and Models Created by Genetic Programming in Consumer Price Index Prediction in Vietnam  [PDF]
Pham Van Khanh
Open Journal of Statistics (OJS) , 2012, DOI: 10.4236/ojs.2012.23029
Abstract: In this paper, we present an application of Genetic Programming (GP) to Vietnamese CPI in?ation one-step prediction problem. This is a new approach in building a good forecasting model, and then applying inflation forecasts in Vietnam in current stage. The study introduces the within-sample and the out-of-samples one-step-ahead forecast errors which have positive correlation and approximate to a linear function with positive slope in prediction models by GP. We also build Vector Autoregression (VAR) model to forecast CPI in quaterly data and compare with the models created by GP. The experimental results show that the Genetic Programming can produce the prediction models having better accuracy than Vector Autoregression models. We have no relavant variables (m2, ex) of monthly data in the VAR model, so no prediction results exist to compare with models created by GP and we just forecast CPI basing on models of GP with previous data of CPI.
Optimal Stopping Time for Holding an Asset  [PDF]
Pham Van Khanh
American Journal of Operations Research (AJOR) , 2012, DOI: 10.4236/ajor.2012.24062
Abstract: In this paper, we consider the problem to determine the optimal time to sell an asset that its price conforms to the Black-Schole model but its drift is a discrete random variable taking one of two given values and this probability distribution behavior changes chronologically. The result of finding the optimal strategy to sell the asset is the first time asset price falling into deterministic time-dependent boundary. Moreover, the boundary is represented by an increasing and continuous monotone function satisfying a nonlinear integral equation. We also conduct to find the empirical optimization boundary and simulate the asset price process.
The First Order Autoregressive Model with Coefficient Contains Non-Negative Random Elements: Simulation and Esimation  [PDF]
Pham Van Khanh
Open Journal of Statistics (OJS) , 2012, DOI: 10.4236/ojs.2012.25064
Abstract: This paper considered an autoregressive time series where the slope contains random components with non-negative values. The authors determine the stationary condition of the series to estimate its parameters by the quasi-maximum likelihood method. The authors also simulates and estimates the coefficients of the simulation chain. In this paper, we consider modeling and forecasting gold chain on the free market in Hanoi, Vietnam.
Optimal Stopping Time to Buy an Asset When Growth Rate Is a Two-State Markov Chain  [PDF]
Pham Van Khanh
American Journal of Operations Research (AJOR) , 2014, DOI: 10.4236/ajor.2014.43013
Abstract:

In this paper we consider the problem of determining the optimal time to buy an asset in a position of an uptrend or downtrend in the financial market and currency market as well as other markets. Asset price is modeled as a geometric Brownian motion with drift being a two-state Markov chain. Based on observations of asset prices, investors want to detect the change points of price trends as accurately as possible, so that they can make the decision to buy. Using filtering techniques and stochastic analysis, we will develop the optimal boundary at which investors implement their decisions when the posterior probability process reaches a certain threshold.


When to Sell an Asset Where Its Drift Drops from a High Value to a Smaller One  [PDF]
Pham Van Khanh
American Journal of Operations Research (AJOR) , 2015, DOI: 10.4236/ajor.2015.56040
Abstract:

To solve the selling problem which is resembled to the buying problem in [1], in this paper we solve the problem of determining the optimal time to sell a property in a location the drift of the asset drops from a high value to a smaller one at some random change-point. This change-point is not directly observable for the investor, but it is partially observable in the sense that it coincides with one of the jump times of some exogenous Poisson process representing external shocks, and these jump times are assumed to be observable. The asset price is modeled as a geometric Brownian motion with a drift that initially exceeds the discount rate, but with the opposite relation after an unobservable and exponentially distributed time and thus, we model the drift as a two-state Markov chain. Using filtering and martingale techniques, stochastic analysis transform measurement, we reduce the problem to a one-dimensional optimal stopping problem. We also establish the optimal boundary at which the investor should liquidate the asset when the price process hit the boundary at first time.

Proposal of Cooperative Communication to Enhance Accuracy of Wireless Control Systems  [PDF]
Nguyen Cong Dinh
Communications and Network (CN) , 2019, DOI: 10.4236/cn.2019.112005
Abstract: Control systems are being changed from wired to wireless communications because of flexibility, mobility and extensibility of wireless communication systems; however the reliability of wireless communications is suspected. In this paper, we propose cooperative communication scheme for wireless control systems which consist of a controller and multiple machines; these machines cooperatively work in a group and for the same duty. In the proposed method, the controller can communicate with machines directly or via other machines, whereas in the conventional method, the controller only communicates with machines directly. The simple 2-link arm plant is used to evaluate our proposed system, and the simulation results indicate that the proposed method is more accurate, and more stable than the conventional method.
A Chance–Constrained Data Envelopment Analysis Approach to Problem Provincial Productivity Growth in Vietnamese Agriculture from 1995 to 2007  [PDF]
Nguyen Khac Minh, Pham Van Khanh
Open Journal of Statistics (OJS) , 2011, DOI: 10.4236/ojs.2011.13026
Abstract: This study employs a chance-constrained data envelopment analysis (CDEA) approach with two models (model A and model B) to decompose provincial productivity growth in Vietnamese agriculture from 1995 to 2007 into technological progress and efficiency change. The differences between the chance - constrained programming model A and model B are assumptions imposed on the covariance matrix. The decomposition allows us to identify the contributions of technical change and the improvement in technical efficiency to productivity growth in Vietnamese production. Sixty-one provinces in Vietnam are classified into Mekong - technology and other -technology categories. We conduct a Mann-Whitney test to verify whether the two samples, the Mekong technology province sample and the other technology sample, are drawn from the same productivity change populations. The result of the Mann-Whitney test indicates that the differences between the Mekong technology category and the other technology category from two models are more significant. Two important questions are whether some provinces in the samples could maintain their relative efficiency rank positions in comparison with the others over the study period and how to further examine the agreements between the two models. The Kruskal - Wallis test statistic shows that technical efficiency from both models for some provinces are higher than those of them in the study period. The Malmquist results show that production frontier has contracted by around 1.3 percent and 0.31 percent from chance-constrained model A and model B, respectively, a year on average over the sample period. To examine the agreements or disagreements in the total factor productivity indexes we compute the correlation between Malmquist indexes, which is positive and not very high. Thus there is a little discrepancy between the two Malmquist indexes, estimated from the chance - constrained models A and B.
Forecasting the Convergence State of per Capital Income in Vietnam  [PDF]
Nguyen Khac Minh, Pham Van Khanh
American Journal of Operations Research (AJOR) , 2013, DOI: 10.4236/ajor.2013.36047
Abstract: Convergence problem of an economic variable represents an underlying forecast of neoclassical economic growth model. This paper aims to analyze the convergence of provincial per capita GDP stability in Vietnam over the period of 1991-2007. This can be done by two approaches including bias data-based regression method for testing convergence and Markov chain model for describing features of long-term tendency of per capita income in Vietnam growth in provinces. The regression method results in the signs of convergence. To apply Markov process, we divide total pattern into 5 per capita income classes. Result estimated from the Markov chain model shows the poor convergence.
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