Mersing is one of the places that have the potential for wind power development in Malaysia. Researchers often suggest it as an ideal place for generating electricity from wind power. However, before a location is chosen, several factors need to be considered. By analyzing the location ahead of time, resource waste can be avoided and maximum profitability to various parties can be realized. For this study, the focus is to identify the distribution of the wind speed of Mersing and to determine the optimal average of wind speed. This study is critical because the wind speed data for any region has its distribution. It changes daily and by season. Moreover, no determination has been made regarding selecting the average wind speed used for wind studies. The wind speed data is averaged to 1, 10, 30, and 60 minutes and used to find the optimal wind speed average. This study used Kolmogorov-Smirnov and Chi-Square as the goodness of fit. The finding shows that the wind speed distribution in Mersing varies according to the time average used and the best fit distribution is Gen. Gamma. In contrast, the optimal average wind speed is 10 minutes due to the highest similarity results with 1-minute data. These affect the reliability of the finding, accuracy of the estimation and decisions made. Therefore, the implementation of this study is significant so that the wind distribution in a particular area is more accurate.
Computations of the relative permeability curves were made through their representation by two functions for wetting and nonwetting phases. Each function contains one parameter that controls the shape of the relative permeability curves. The values of these parameters are chosen to minimize an objective function, that is represented as a weighted sum of the squared differences between experimentally measured data and the corresponding data calculated by a mathematical model simulating the experiment. These data comprise the pressure drop across core samples and the recovery response of the displacing phase. Two mathematical models are constructed in this study to simulate incompressible, one-dimensional, two-phase flow. The first model d
... Show MoreThe main goal of this work is to put a simple model of the spectral energy distribution of binary stars called WW Cha. This model is built up on the extracted data from various telescopes and archives for the target WW Cha stars and then analyzing them using a python environment. The result of the fitting proposes that there are two protoplanetary disks around the WW Cha star, with different physical properties for each disk, such as the size of the inner disk being 10 AU, while the size of the outer disk being 300 AU. The shape of the outer disk is a flaring disk not a flat disk according to the value of the power law for the surface density (1.5). The emission in the disk is caused by small amorphous olivine grains rangin
... Show MoreThyroid hormones, triiodothyronine (T3) and thyroxin (T4) play an important role in growth, development, and physiology of the kidney. The kidney has a central role in metabolism and clearance of these hormones as well as thyroid – stimulating hormone (TSH). Chronic renal failure (CRF) is a state of irreversible deceleration in renal function results in alterations in internal milieu, which affects the synthesis and secretory rate of hormones. To evaluate the thyroid hormone levels in non-dialyzed patients with chronic renal failure (CRF); 24 patients with CRF aged 30-70 years, mean±S.d. (48.458 ± 13.569) and 48 healthy volunteers who served as controls aged 30-70 years (43.104 ± 12.387) were studied for their thyroid function status u
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The great scientific progress has led to widespread Information as information accumulates in large databases is important in trying to revise and compile this vast amount of data and, where its purpose to extract hidden information or classified data under their relations with each other in order to take advantage of them for technical purposes.
And work with data mining (DM) is appropriate in this area because of the importance of research in the (K-Means) algorithm for clustering data in fact applied with effect can be observed in variables by changing the sample size (n) and the number of clusters (K)
... Show MoreThe Back-Propagation (BP) is the best known and widely used learning algorithm in training multiple neural network. A vast variety of improvements to BP algorithm have been proposed since ninety’s. in this paper, the effects of changing the number of hidden neurons and activation equation are investigated. According to the simulation results, the convergence speed have been improved and become much faster by the previous two modifications on the BP algorithm.
Diverting river flow during construction of a main dam involves the construction of cofferdams, and tunnels, channels or other temporary passages. Diversion channels are commonly used in wide valleys where the high flow makes tunnels or culverts uneconomic. The diversion works must form part of the overall project design since it will have a major impact on its cost, as well as on the design, construction program and overall cost of the permanent works. Construction costs contain of excavation, lining of the channel, and construction of upstream and downstream cofferdams. The optimization model was applied to obtain optimalchannel cross section, height of upstream cofferdam, and height of downstream cofferdamwith minimum construction cost
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