Sylhet, Bangladesh

Leading University

www.lus.ac.bd
Sylhet, Bangladesh

Leading University or LU is a private university of Bangladesh. It was established in 2001 by the Private University Act 1992. The outreach campus of LU is located in Surma & Rangmahal Tower, Sylhet. Sylhet. Wikipedia.

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Dankevych E.,National Economics University | Dankevych V.,University of Management and Economics | Chaikin O.,Leading University
Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis | Year: 2017

The theoretical land relations reforming principles were reviewed. Land relations in agriculture transformation process was studied. The land use features were detected and agricultural land use efficiency analysis was conducted. Ukraine land market formation research problems results have been shown. It was established that private land ownership institution ambiguous attitude, rent relations deformation, lack of the property rights ensure mechanism inhibit the land market development. Sociological research of Ukrainian Polesie region to determine the prerequisites for agricultural land marketformation preconditions has been conducted. 787 respondents from Zhytomyr, Rivne and Volyn regions were interviewed. Land shares owners age structure, their distribution by education level, their employment, land shares owners and agricultural enterprises executives to the agricultural land sale moratorium cancellation attitudes, land purchase financial resources, directions of Ukrainian Polissya region land shares use, shares owners land issues level of awareness have been determined during the research. Was substantiated that agricultural land market turnover includes not only land sale moratorium cancellation but also the adoption of the legislative framework and the appropriate infrastructure development, one of the key elements of which is land relations regulation specialized state agency - State Land Bank.


Mahmud I.,Shahjalal University of Science and Technology | Bari S.H.,Leading University | Ur Rahman M.T.,Bangladesh Institute of Technology
Environmental Engineering Research | Year: 2017

Rainfall is one of the most important phenomena of the natural system. In Bangladesh, agriculture largely depends on the intensity and variability of rainfall. Therefore, an early indication of possible rainfall can help to solve several problems related to agriculture, climate change and natural hazards like flood and drought. Rainfall forecasting could play a significant role in the planning and management of water resource systems also. In this study, univariate Seasonal Autoregressive Integrated Moving Average (SARIMA) model was used to forecast monthly rainfall for twelve months lead-time for thirty rainfall stations of Bangladesh. The best SARIMA model was chosen based on the RMSE and normalized BIC criteria. A validation check for each station was performed on residual series. Residuals were found white noise at almost all stations. Besides, lack of fit test and normalized BIC confirms all the models were fitted satisfactorily. The predicted results from the selected models were compared with the observed data to determine prediction precision. We found that selected models predicted monthly rainfall with a reasonable accuracy. Therefore, year-long rainfall can be forecasted using these models. © 2017 Korean Society of Environmental Engineers.


Ahmed A.A.M.,Leading University
Journal of King Saud University - Engineering Sciences | Year: 2017

The objective of this study is to develop a feed forward neural network (FFNN) model and a radial basis function neural network (RBFNN) model to predict the dissolved oxygen from biochemical oxygen demand (BOD) and chemical oxygen demand (COD) in the Surma River, Bangladesh. The neural network model was developed using experimental data which were collected during a three year long study. The input combinations were prepared based on the correlation coefficient with dissolved oxygen. Performance of the ANN models was evaluated using correlation coefficient (R), mean squared error (MSE) and coefficient of efficiency (E). It was found that the ANN model could be employed successfully in estimating the dissolved oxygen of the Surma River. Comparative indices of the optimized RBFNN with input values of biochemical oxygen demand (BOD) and chemical oxygen demand (COD) for prediction of DO for testing array were MSE = 0.465, E = 0.905 and R = 0.904 and for validation array were MSE = 1.009, E = 0.966 and R = 0.963. Comparing the modeled values by RBFNN and FFNN with the experimental data indicates that neural network model provides reasonable results. © 2014


Ahmed A.A.M.,Leading University | Shah S.M.A.,Leading University
Journal of King Saud University - Engineering Sciences | Year: 2017

This paper describes the application of adaptive neuro-fuzzy inference system (ANFIS) to estimate the biochemical oxygen demand (BOD) of Surma River of Bangladesh. The data sets consist of 10 water quality parameters which include pH, alkalinity (mg/L as CaCO3), hardness, total solids (TS), total dissolved solids (TDS), potassium (K+), PO4 −3 (mg/l), NO3 − (mg/l), BOD (mg/l) and DO (mg/l). The performance of the ANFIS models was assessed through the correlation coefficient (R), mean squared error (MSE), mean absolute error (MAE) and Nash model efficiency (E). Study results show that the adaptive neuro-fuzzy inference system is able to predict the biochemical oxygen demand with reasonable accuracy, suggesting that the ANFIS model is a valuable tool for river water quality estimation. The result shows that, ANFIS-I has a high prediction capacity of BOD compared with ANFIS-II. The results also suggest that ANFIS method can be successfully applied to establish river water quality prediction model. © 2015


Gilbert K.A.,Leading University
Journal of Information Technology Education: Innovations in Practice | Year: 2017

Aim/Purpose Improving public schools is a focus of federal legislation in the United States with much of the burden placed on principals. However, preparing principals for this task has proven elusive despite many changes in programming by insti-tutions of higher learning. Emerging technologies that rely on augmented and virtual realities are posited to be powerful pedagogical tools for closing this gap. Background This study investigated the effects of immersive simulation technologies on principals' self-efficacy after treatment and the perceived significance of the design of the immersive simulation experience as an effective tool for adult learners. Methodology The investigator employed a multiple-methods study that relied on a purposive sample of graduate students enrolled in educational leadership programs at two small universities in the southeastern United States. Participants completed a two-hour module of immersive simulation designed to facilitate transfer of knowledge to skills thereby increasing their self-efficacy. Contribution This paper contributes to a small body of literature that examines the use of immersive simulation to prepare aspiring principals. Findings The findings indicate moderate effect sizes in changes in self-efficacy, positive attitudes toward immersive simulation as a pedagogical tool, and significance in the design of immersive simulation modules. This suggests that immersive sim-ulation, when properly designed, aids principals in taking action to improve schools. Recommendations for Practitioners Educational leadership programs might consider the use of immersive simula-tions to enhance principals' ability to meet the complex demands of leading in the 21st century. Impact on Society Principals may be more adept at improving schools if preparation programs provided consistent opportunities to engage in immersive simulations.Future Research Future research should be conducted with larger sample sizes and longitudinally to determine the effectiveness of this treatment.


Chakrabarty S.,University of Southern Queensland | Chakrabarty S.,Shahjalal University of Science and Technology | Boksh F.I.M.M.,Center for Policy Dialogue | Chakraborty A.,Leading University | Chakraborty A.,University of Southern Queensland
Renewable and Sustainable Energy Reviews | Year: 2013

To analyze economic viability of the biogas plants in Bangladesh six case studies are carried out in some selected upazilas of greater Sylhet district in Bangladesh where NGOs like Grameen Shakti (GS) and Rural Services Foundation (RSF) are delivering and servicing biogas plants. Economic viability of the biogas plants are measured by comparing prior expenditure (before implementing biogas plant) for firewood, kerosene, and other conventional sources. Economic viability refers to an estimator that not only seeks to maximize the effectiveness of financial viability but also considers environmental externalities. Economic viability for six different cases of biogas plants provides information about relative performance of the product in six different situations. A sensitivity analysis is performed using artificial neural network (ANN) model. Although economic viability of biogas is sensitive to kerosene price, firewood availability, this study reveals that biogas is economically more attractive when women could render their saved cooking time for other income generating green jobs. Biogas plant results a number of income generating new green employments for the rural community in Bangladesh. © 2013 Elsevier Ltd.


Rabbi M.F.,Leading University
2013 International Conference on Electrical Information and Communication Technology, EICT 2013 | Year: 2013

MIMO-OFDMA has become an efficient method characterizing diversity to multi-user transmission over doubly selective fading channels with high spectral efficiency. In this paper we develop a Basis Expansion Model (BEM) based MIMO-OFDMA system and we analyze the channel capacity for the system. It is shown that, by using BEM based channel approximation for MIMO-OFDMA system we can achieve diversity without any space-time coding. Specifically, BEM based system inherently exploits the receive diversity and maximizes channel capacity similar to existing diversity technique like Maximal Ratio Combining (MRC). © 2014 IEEE.


Haque M.A.,Leading University
Chemical Product and Process Modeling | Year: 2016

In this research, landfill solid waste was solidified as cement-waste matrix to protect the environment from excessive intrusive contaminants like Fe, Cu and Ni and minimize the waste load. Within this context, ingredients of cement-waste mortar were characterized to determine their physical properties. Long-term feasibility study was conducted to examine the metal contents stabilization by employing the standard mass transfer-leaching test. The cumulative leaching concentration of Fe, Cu and Ni were found to be 1.29 mg/l, 0.18 mg/l and 0.63 mg/l respectively up to 180 days static leaching test period that satisfied the surface water quality standard. Mechanical strength test was also conducted to characterize the solidification technique. Five well-established non-linear mathematical Models were conducted to evaluate the mechanisms of Fe, Cu and Ni migration. Goodness of fit statistical parameter analysis and visual examination indicated that polynomial equation Model is better for explaining the experimentally generated data. Moreover, parameter of polynomial equation was extended from five to nine for examining the best calibration profile to the observations. In context of slope-intercept and visual observation analysis resulted that polynomial equation based Model bearing five parameters with 0.5 power interval of each parameter describes the leaching phenomena quite similar with the experimental observations whereas goodness of fit parameters and information criterion shows reverse. It was found that the studied immobilized landfill waste mortar have acceptable mechanical performance that confirms to be used as construction material. © 2016 by De Gruyter.


Bari S.H.,Leading University | Hussain M.M.,Bangladesh University of Engineering and Technology | Husna N.-E.-A.,Bangladesh University of Engineering and Technology
Theoretical and Applied Climatology | Year: 2016

This paper aimed at the analysis of rainfall seasonality and variability for the northern part of South-Asian country, Bangladesh. The coefficient of variability was used to determine the variability of rainfall. While rainfall seasonality index (SI ) and mean individual seasonality index ((Formula presented.)) were used to identify seasonal contrast. We also applied Mann-Kendall trend test and sequential Mann-Kendall test to determine the trend in seasonality. The lowest variability was found for monsoon among the four seasons whereas winter has the highest variability. Observed variability has a decreasing tendency from the northwest region towards the northeast region. The mean individual seasonality index (0.815378 to 0.977228) indicates that rainfall in Bangladesh is “markedly seasonal with a long dry season.” It was found that the length of the dry period is lower at the northeastern part of northern Bangladesh. Trend analysis results show no significant change in the seasonality of rainfall in this region. Regression analysis of (Formula presented.) and SI, and longitude and mean individual seasonality index show a significant linear correlation for this area. © 2016 Springer-Verlag Wien


Rabbi M.F.,Leading University
Proceeding of the 15th International Conference on Computer and Information Technology, ICCIT 2012 | Year: 2012

In this paper, we investigate the Channel Impulse Response (CIR) estimation in an Orthogonal Frequency Division Multiple Access (OFDMA) uplink using a tracking based Basis Expansion Modeling (BEM) algorithm. By introducing a new tracking term in the BEM coefficients that gives the rate of change of the coefficients, the algorithm is particularly suitable for high mobility application. Specifically, the algorithm estimates the BEM coefficients for each OFDMA block in an iterative manner based on using a new objective function that takes into consideration first order variations in the coefficients of the current and adjacent blocks. © 2012 IEEE.

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