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Possible changes in rainfall extremes in Peninsular Malaysia were assessed in this study using an ensemble of four GCMs of CMIP5. The performance of four bias correction methods was compared, and the most suitable method was used for downscaling of GCM simulated daily rainfall to the spatial resolution (0.25°) of APHRODITE rainfall. The multi-model ensemble (MME) mean of the downscaled rainfall was developed using a random forest regression algorithm. The MME projected rainfall for four RCPs were compared with APHRODITE rainfall for the base year (1961–2005) to assess the annual and seasonal changes in eight extreme rainfall indices. The results showed power transformation as the most suitable bias correction method. The maximum changes in most of the annual and seasonal extreme rainfall indices were observed for RCP8.5 in the last part of this century. The maximum increase was observed for 1-day and 5 consecutive days' rainfall amount for RCP4.5. Spatial distribution of the changes revealed higher increase of the extremes in the northeast region where rainfall extremes are already very high. The increase in rainfall extremes would increase the possibility of frequent hydrological disasters in Peninsular Malaysia.

Reinforced concrete structures are subjected to frequent maintenance and repairs due to steel reinforcement corrosion. Fiber-reinforced polymer (FRP) laminates are widely used for retrofitting beams, columns, joints, and slabs. This study investigated the non-linear capability of artificial intelligence (AI)-based gene expression programming (GEP) modelling to develop a mathematical relationship for estimating the interfacial bond strength (IBS) of FRP laminates on a concrete prism with grooves. The model was based on five input parameters, namely axial stiffness (Eftf), width of FRP plate (bf), concrete compressive strength (fc′), width of groove (bg), and depth of the groove (hg), and IBS was considered the target variable. Ten trials were conducted based on varying genetic parameters, namely the number of chromosomes, head size, and number of genes. The performance of the models was evaluated using the correlation coefficient (R), mean absolute error (MAE), and root mean square error (RMSE). The genetic variation revealed that optimum performance was obtained for 30 chromosomes, 11 head sizes, and 4 genes. The values of R, MAE, and RMSE were observed as 0.967, 0.782 kN, and 1.049 kN for training and 0.961, 1.027 kN, and 1.354 kN. The developed model reflected close agreement between experimental and predicted results. This implies that the developed mathematical equation was reliable in estimating IBS based on the available properties of FRPs. The sensitivity and parametric analysis showed that the axial stiffness and width of FRP are the most influential parameters in contributing to IBS.

Concrete is an economical and efficient material for attenuating radiation. The potential of concrete in attenuating radiation is attributed to its density, which in turn depends on the mix design of concrete. This paper presents the findings of a study conducted to evaluate the radiation attenuation with varying water-cement ratio (w/c), thickness, density, and compressive strength of concrete. Three different types of concrete, i.e., normal concrete, barite, and magnetite containing concrete, were prepared to investigate this study. The radiation attenuation was calculated by studying the dose absorbed by the concrete and the linear attenuation coefficient. Additionally, artificial neural network (ANN) and gene expression programming (GEP) models were developed for predicting the radiation shielding capacity of concrete. A correlation coefficient (R), mean absolute error (MAE), and root mean square error (RMSE) were calculated as 0.999, 1.474 mGy, 2.154 mGy and 0.994, 5.07 mGy, 5.772 mGy for the training and validation sets of the ANN model, respectively. Similarly, for the GEP model, these values were recorded as 0.981, 13.17 mGy, and 20.20 mGy for the training set, whereas the validation data yielded R = 0.985, MAE = 12.2 mGy, and RMSE = 14.96 mGy. The statistical evaluation reflects that the developed models manifested close agreement between experimental and predicted results. In comparison, the ANN model surpassed the accuracy of the GEP models, yielding the highest R and the lowest MAE and RMSE. The parametric and sensitivity analysis revealed the thickness and density of concrete as the most influential parameters in contributing towards radiation shielding. The mathematical equation derived from the GEP models signifies its importance such that the equation can be easily used for future prediction of radiation shielding of high-density concrete.

In this study, a non-local MOS is proposed for the downscaling of daily rainfall of couple model intercomparison project phase 5 (CMIP5) GCMs for the projections of rainfall in Peninsular Malaysia for two representative concentration pathways (RCP) scenarios, RCP4.5 and RCP8.5. Projections of eight GCMs for both the mentioned RCPs were used for this purpose. The GCM simulations were downscaled at 19 observed stations distributed over Peninsular Malaysia. Random Forest (RF) was used for the development of non-local regression-based MOS models. The results revealed a high accuracy of the models in downscaling rainfall at all the observed stations. The mean absolute error (MAE) of the models were found in the range of 0.8–0.39; normalized root mean square error (NRMSE) between 7.4 and 41.7, Percent Bias (PBIAS) between –0.3 and 10.1, Nash–Sutcliffe coefficient (NSE) between 0.81 and 0.99 and R2 between 0.89 and 0.99. The increase in annual rainfall was in the range of 7.3–29.5%. The increase was higher for RCP8.5 compared to RCP4.5. The maximum increase was observed in the northern part of Peninsular Malaysia in the range of 20.7–29.5%, while the minimum in the south-west region was in the range of 7.6–15.2%.

10We present results from a vertical array of accelerometers that was recently installed in 11 Bishkek (Kyrgyzstan) with the long-term aim of recording strong motion data. Taking 12 advantage of recordings of a Mb 4.7 earthquake that occurred 40 km from the array site 13 during the installation phase, we provide results of some preliminary data analysis. First, 14 estimates of the S-wave velocity and Qs structure are deduced by the inversion of the 15 deconvolved wavefield between the sensors in the borehole. Furthermore, the application 16 of the nonstationary ray decomposition (Kinoshita, 2009) allowed at least 3 reflectors in the 17 shallow velocity structure below the array to be identified. The complex nature of the 18 wavefield (with upgoing, down-going waves, and converted phases) due to the coarse, 19 unconsolidated subsoil structure is highlighted by means of numerical simulations of ground 20 motion. 21 2

Microgrid deployments are expanding around the world as the most suitable solution to integrate distributed renewable energy sources to meet the increasing load demands and to power-up the remote areas. The installation of DC microgrid can improve system efficiency and reduces the cost of electrical infrastructure compared to the AC microgrid. However, the main challenge of implementing DC microgrid is the existing structure of the AC distribution system. In addition to the previous researches performed on DC microgrids, this paper proposes a framework to assess the technical and financial benefits of implementing the AC and DC microgrids. The power loss, voltage drop and system efficiency have been investigated for the AC and DC microgrids during the steady-state condition. Furthermore, the dynamic behaviors of AC and DC microgrids have been analyzed when each system subjected to disturbance such as short-circuit fault, aiming to evaluate the system response. In the next stage, techno-economic analysis has been carried out to determine the optimal size of solar PV system connected to each AC or DC microgrid with its energy storage, according to the meteorological and load profile data of the selected remote area in Sarawak (Malaysia). The study presented in this paper justifies that DC microgrid is potentially more beneficial than AC microgrid. However, the stability of the system during fault condition is the main problem in the DC microgrid. Therefore, it can be concluded that the protection and control of DC microgrids should be the key areas of future researches.