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Articles by K. Ibrahim
Total Records ( 2 ) for K. Ibrahim
  N.Z. M. Saat , A.A. Jemain and K. Ibrahim
  There was limited information on the analysis of sleep disorder especially apnea. Therefore, study on sleep apnea is essential to understand the sleep behavior during the occurrence of apnea. Markov chain analysis particularly suitable to analyze discrete data that involves time. Data on apnea is discrete as it was measured by recording if the apnea events happens during each epoch of sleep. In this study, the Markov chain model is fitted to the apnea and no apnea data to determine the optimum order of the occurrence of apnea using the Akaike’s Information Criterion (AIC) and Bayesian Information Criteria (BIC) for each subjects of 14 subjects that has apnea problem. The results indicated that the optimum order varies according to sleep stages and period of sleep. Generally, the higher order of Markov chain models is suggested during light and deep sleep stages. However, it is found that regardless of sleep stages the optimum order of Markov chain model is varies during the first, second, third and fourth quarter period of sleep. The analysis for describing the most appropriate order showed that the third order model is suitable for most subjects. In conclusion, the analysis indicates that the third order of the Markov chain model is the most appropriate order regardless of sleep stages and sleep period.
  K. Ibrahim , M.N. Shamsudin , R. Yacob and A. Radam
  In recent years, climate change has become a more serious issue than any other environmental problem. One of the main concerns is the risk it poses to food production in developing countries, due to heavy reliance on agriculture. This study examined the influence of climate change on net revenue from maize production in northern Nigeria and the role of socioeconomic factors on farm adaptation. The results are intended to inform farmers, researchers and policy makers, on the impact of climate change on net revenue from maize production in the study area. A farm survey of the respondents found that, there was a significant correlation between climate change (temperature and rainfall) and net revenue from maize production. Results of the study revealed that precipitation plays a more important role as a determinant of farm net revenue, as against temperature, particularly during the rainy season. Furthermore, socioeconomic factors were found to have a mix effect on net revenue. In conclusion the study found that climate change affects net revenue from maize production in the area and there is the need to focus attention on the greatest environmental threat of our time, an issue that previous studies have not addressed comprehensively. The policy implications of the results, if carefully evaluated are expected to serve as a framework for developing climate change adaptation and mitigation options in the study area.
 
 
 
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