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  1. Haslina Hassan, Rosnah Sutan, Nursazila Asikin Mohd Azmi, Shuhaila Ahmad, Rohana Jaafar
    Int J Public Health Res, 2013;3(1):241-248.
    MyJurnal
    The aim of the Fourth Millennium Developmental Goal is to reduce mortality among children less than 5 years by two thirds between 1990 and 2015. Efforts are more focus on improving children's health. The aim of this study was to describe the trend of stillbirth and neonatal deaths in University Kebangsaan Malaysia Medical Centre from 2004 to 2010. A retrospective cross-sectional study was conducted using hospital data on perinatal mortality and monthly census delivery statistics. There were 45,277 deliveries with 526 stillbirths and neonatal deaths. More than half of the stillborn cases were classified as normally formed macerated stillbirth and prematurity was common in neonatal deaths. The trend of SB and NND was found fluctuating in this study. However, by using proportionate test comparing rate, there was a transient significant decline of stillbirth but not neonatal deaths rates between 2004 and 2006. On the other hand, the neonatal deaths rate showed significant increment from 2006 to 2008. When both mortality rates were compared using proportionate test, from the start of the study, year 2004 with end of the study, year 2010, there was no significant decline noted. Trends of stillbirth and neonatal death rates in University Kebangsaan Malaysia Medical Centre within 7 years study period did not show the expected outcome as in Millennium Developmental Goal of two thirds reduction.
  2. Goudarzi S, Haslina Hassan W, Abdalla Hashim AH, Soleymani SA, Anisi MH, Zakaria OM
    PLoS One, 2016;11(7):e0151355.
    PMID: 27438600 DOI: 10.1371/journal.pone.0151355
    This study aims to design a vertical handover prediction method to minimize unnecessary handovers for a mobile node (MN) during the vertical handover process. This relies on a novel method for the prediction of a received signal strength indicator (RSSI) referred to as IRBF-FFA, which is designed by utilizing the imperialist competition algorithm (ICA) to train the radial basis function (RBF), and by hybridizing with the firefly algorithm (FFA) to predict the optimal solution. The prediction accuracy of the proposed IRBF-FFA model was validated by comparing it to support vector machines (SVMs) and multilayer perceptron (MLP) models. In order to assess the model's performance, we measured the coefficient of determination (R2), correlation coefficient (r), root mean square error (RMSE) and mean absolute percentage error (MAPE). The achieved results indicate that the IRBF-FFA model provides more precise predictions compared to different ANNs, namely, support vector machines (SVMs) and multilayer perceptron (MLP). The performance of the proposed model is analyzed through simulated and real-time RSSI measurements. The results also suggest that the IRBF-FFA model can be applied as an efficient technique for the accurate prediction of vertical handover.
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