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1

Short Term Electricity Demand Forecasting of an Isolated Area using Two Different Approach

Islam A., Hasib S. R., Islam M. S.

Journal of Power Technologies

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2013

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Vol. 93, nr 4

185--193

EN

Electricity demand forecasting of an off-grid area, where no previous load data is available, is an important prerequisite for power system expansion planning. Bangladesh is a small as well as densely populated country in South Asia with a large portion of the population living under poverty line. About 48.5% of the total population has access in grid electricity. Uninterruptable power supply is one of the most important parameter for future development which ends up with a decision of obvious expansion of present grid coverage. This paper represents an analysis to forecast the electricity demand of an isolated island in Bangladesh where past history of electrical load demand is not available. The analysis is based on the identification of factors on which electrical load growth of an area depends. The forecasting has been done through inverse matrix calculation and linear regression analysis method. It has been found that the demand data, calculated from two different approaches, are close enough which spans the reliability of the proposed method. This method can be applicable for short term load forecasting of any isolated area throughout the world.

2

Uptake of phenol from aqueous solution by burned water hyacinth

Uddin M.T., Islam M.S., Islam M.A., Abedin M.Z.

Polish Journal of Chemical Technology

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2008

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Vol. 10, nr 2

43-49

EN

The potential of burned water hyacinth (BWH) for phenol adsorption from aqueous solution was studied. Batch kinetic and isotherm studies were carried out under varying experimental conditions of contact time, phenol concentration, adsorbent dosage and pH. The pH at the point of zero charge (pH(PZC)) of the adsorbent was determined by the titration method and the value of 8.8 š 0.2 was obtained. The FTIR of the adsorbent was carried out in order to find the potential adsorption sites for the interaction with phenol molecules. The Freundlich and Langmuir adsorption models were used for the mathematical description of adsorption equilibrium and it was found that the experimental data fitted very well to the Langmuir model. Maximum adsorption capacity of the adsorbent was found to be 30.49 mg/g. Batch adsorption models, based on the assumption of the pseudo-first-order and pseudo-second-order models, were applied to examine the kinetics of the adsorption. The results showed that kinetic data closely followed the pseudo-second-order model.

3

Detecting and matching interest points in relative scale

Islam M. S., Sluzek A., Zhu L.

Machine Graphics and Vision

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2005

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Vol. 14, No. 3

259-283

EN

The same object seen in two different images can be geometrically and photometrically transformed. In this paper, a method of interest point detection and matching is described for the same object in different images. One of the main considerations is the change in the object scale. In this method, a reference scale is assigned to a particular instance of the object, and the change of scale is represented by a relative scale. Then, Harris' relative scale method is used for interest point detection. This method is robust to linear geometric transformations. A heuristic method for threshold selection is also described for robustness to intensity changes in a cluttered environment with partial occlusions. The repeatability rate of interest points for this method is higher then that for the existing methods. For the matching process, a local invariant descriptor is computed in the relative scale for each of the detected interest points. A hashing technique is applied to find the matches efficiently. The matching method enables finding a good number of correct matches for different types of transformations in a cluttered environment and one with partial occlusions. The proposed single scale detection and matching method could be effectively used for many practical applications, where the relative scale of the object can be predicted in advance.