Malaysia will be an ageing population by 2030 as the number of those aged 60 years and above has increased drastically from 6.2 percent in 2000 and is expected to reach 13.6 percent by 2030. There are many challenges that will be faced due to the ageing population, one of which is the increasing cost of pensions in the future. In view of that, it is necessary to investigate the effect of actuarial assumptions on pension liabilities under the perspective of ageing. To estimate the pension liabilities, the Projected Unit Credit method is used in the study and commutation functions are employed in the process. Demographic risk and salary risk have been identified as major risks in analyzing pension liabilities in this study. The sensitivity analyses will be conducted in the study to investigate how the pension liabilities will be affected when these major risks changes. This study analyzes nine scenarios under assumptions in the actuarial model, namely age of retirement, rate of mortality and rate of salary growth. The result of this study indicates that the implied mortality experience and salary growth rate assumptions have a significant impact on pension liabilities.
Calcium carbonate is predominantly present in aqueous systems, which is
commonly used in industrial processes. It has inverse solubility characteristics
resulting in the deposition of scale on heat transfer surface. This paper focuses on
developing methods for inhibition of calcium carbonate scale formation in cooling
tower and air cooler system where scaling can cause serious problems, ZnCl 2 and ZnI
2 has been investigated as scale inhibitor on AISI 316 and 304. ZnCl 2 were more
effective than ZnI 2 in both systems, and AISI 316 show more receptivity to the
chlorides salt compared to AISI 304. The inhibitors were more effective in cooling
tower than air cooler system. AISI 316 show more constant inhibition effic
This research deals with a shrinking method concernes with the principal components similar to that one which used in the multiple regression “Least Absolute Shrinkage and Selection: LASS”. The goal here is to make an uncorrelated linear combinations from only a subset of explanatory variables that may have a multicollinearity problem instead taking the whole number say, (K) of them. This shrinkage will force some coefficients to equal zero, after making some restriction on them by some "tuning parameter" say, (t) which balances the bias and variance amount from side, and doesn't exceed the acceptable percent explained variance of these components. This had been shown by MSE criterion in the regression case and the percent explained v
... Show MoreThe river water salinity is a major concern in many countries, and salinity can be expressed as total dissolved solids. So, the water salinity impact of the river is one of the major factors effects of water quality. Tigris river water salinity increase with streamline and time due to the decrease in the river flow and dam construction from neighboring countries. The major objective of this research to developed salinity model to study the change of salinity and its impact on the Al-Karkh, Sharq Dijla, Al-Karama, Al-Wathba, Al-Dora, and Al-Wihda water treatment plant along Tigris River in Baghdad city using artificial neural network model (ANN). The parameter used in a model built is (Turbidity, Ec, T.s, S.s, and TDS in)
... Show MoreOptical Mark Recognition (OMR) is the technology of electronically extracting intended data from marked fields, such as squareand bubbles fields, on printed forms. OMR technology is particularly useful for applications in which large numbers of hand-filled forms need to be processed quickly and with a great degree of accuracy. The technique is particularly popular with schools and universities for the reading in of multiple choice exam papers. This paper proposed OMRbased on Modify Multi-Connect Architecture (MMCA) associative memory, its work in two phases: training phase and recognition phase. The proposed method was also able to detect more than one or no selected choice. Among 800 test samples with 8 types of grid answer sheets and tota
... Show MoreThis paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength. This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.
Moreover, the proposed controller i
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