Fitting Wind Speed to a 3-Parameter Distribution Using Maximum Likelihood Technique
Okumu Otieno Kevin,
Troon John Benedict,
Samuel Muthiga Ngaga
Issue:
Volume 7, Issue 1, March 2021
Pages:
1-6
Received:
13 December 2020
Accepted:
30 December 2020
Published:
4 March 2021
Abstract: Kenya is one of the countries in the world with a good quantity of wind. This makes the country to work on technologies that can help in harnessing the wind with a vision of achieving a total capacity of 2GW of wind energy by 2030. The objective of this research is to find the best three-parameter wind speed distribution for examining wind speed using the maximum likelihood fitting technique. To achieve the objective, the study used hourly wind speed data collected for a period of three years (2016 – 2018) from five sites within Narok County. The study examines the best distributions that the data fits and then conducted a suitability test of the distributions using the Kolmogorov-Smirnov test. The distribution parameters were fitted using maximum likelihood technique and model comparison test conducted using Akaike’s Information Criterion (AIC) and the Bayesian Information Criterion (BIC) values with the decision rule that the best distribution relies on the distribution with the smaller AIC and BIC values. The research showed that the best distribution is the gamma distribution with the shape parameter of 2.071773, scale parameter of 1.120855, and threshold parameter of 0.1174. A conclusion that gamma distribution is the best three-parameter distribution for examining the Narok country wind speed data.
Abstract: Kenya is one of the countries in the world with a good quantity of wind. This makes the country to work on technologies that can help in harnessing the wind with a vision of achieving a total capacity of 2GW of wind energy by 2030. The objective of this research is to find the best three-parameter wind speed distribution for examining wind speed us...
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Physiological Analysis and Evaluation of Heavy Metal Contents in Leafy Vegetables and Fruits Collected from the Local Market of Prayagraj
Swati Singh Chandel,
Amar Singh Rana,
Muhammad Ibrahim
Issue:
Volume 7, Issue 1, March 2021
Pages:
7-12
Received:
28 December 2020
Accepted:
8 January 2021
Published:
10 March 2021
Abstract: The following research work has been undertaken to examine the presence of heavy metals i.e lead (Pb), Cadmium (Cd), Copper (Cu), Iron (Fe), Cobalt (Co) in some selected vegetables and fruits supplied in the local market. The process used to determine heavy metals is Atomic Absorption Spectrometer. Iron concentration in spinach, tomato, cauliflower and lady finger showed higher ranges which were exceeding the permissible limits. Cauliflower and spinach were within the limits specified. The pH value, ascorbic concentration and moisture content significantly decreased after oven drying of vegetables and fruits. However, the Total Soluble Solids (TSS) and ash content significantly increased after oven drying as compared with fresh vegetables and fruits. The present research data revealed that the fresh and oven dried vegetables such as Spinach, Cauliflower, Lady finger and Tomato contains 0.13-1.50%, 0.25-2.32%, 0.26-2.52% and 0.19-3.13% Titratable acidity respectively. Similarly, fresh and oven dried Guava Titratable acidity was highest 0.27 and 1.92 as compared with Water melon and Mango. The reduction in acidity may be due to catabolic activities in fruit cells and increased in pH. The pH value of vegetables and fruits dropped after oven drying. Similarly, ascorbic concentration and moisture content significantly decreased after oven drying as compared to fresh vegetables and fruits. However, the Total Soluble solids (TSS) and ash content significantly increased after oven drying as compared with fresh vegetables and fruits. Overall from the following study we can conclude that vegetables and fruits were found to be contaminated by heavy toxic metals. Regular monitoring is required because these toxic metals will damage human body as well disturb our food chain. The main objective to conduct this study is to monitor the heavy metal toxicity and provide some recommendation, which in future will assure food safety and human health.
Abstract: The following research work has been undertaken to examine the presence of heavy metals i.e lead (Pb), Cadmium (Cd), Copper (Cu), Iron (Fe), Cobalt (Co) in some selected vegetables and fruits supplied in the local market. The process used to determine heavy metals is Atomic Absorption Spectrometer. Iron concentration in spinach, tomato, cauliflower...
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Optimal Allocation in Small Area Mean Estimation Using Stratified Sampling in the Presence of Non-Response
Ongoma Jackson,
Alilah David Anekeya,
Okuto Erick
Issue:
Volume 7, Issue 1, March 2021
Pages:
13-24
Received:
3 November 2020
Accepted:
1 December 2020
Published:
12 March 2021
Abstract: Sample survey provides reliable current statistics for large areas or sub-population (domains) with large sample sizes. There is a growing demand for reliable small area statistics, however, the sample sizes are too small to provide direct (or area specific) estimators with acceptable and reliable accuracy. This study gives theoretical description of the estimation of small area mean by use of stratified sampling with a linear cost function in the presence of non-response. The estimation of small area mean is proposed using auxiliary information in which the study and auxiliary variable suffers from non-response during sampling. Optimal sample sizes have been obtained by minimizing the cost of survey for specific precision within a given cost using lagrangian function multiplier lambda and Partial Differential Equations (PDEs). Results demonstrate that as the values of the respondent sample increases sample units that supply information to study and auxiliary variable tends to small area population size, the non-response sample unit tends to sample units that supply the information as the sampling rate tends to one. From theoretic analysis it is practical that the Mean Square Error will decrease as the sub-sampling fraction and auxiliary characters increase. As the sub-sampling fraction increases and the value of beta increases then the value of large sample size is minimized with a reduction of Lagrangian multiplier value which minimizes the cost function.
Abstract: Sample survey provides reliable current statistics for large areas or sub-population (domains) with large sample sizes. There is a growing demand for reliable small area statistics, however, the sample sizes are too small to provide direct (or area specific) estimators with acceptable and reliable accuracy. This study gives theoretical description ...
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