Nur Amalina Mat Jan

An ambulance is a vehicle used to transport sick or injured people, and the patient will be sent to a hospital for further treatment. This study aims to predict hourly use of ambulances in two selected government hospital, namely the Hospital Sultanah Nur Zahirah (HSNZ), located in Terengganu, a state in the East Peninsular Malaysia, and Hospital Tapah, located in Perak state, in the West Peninsular Malaysia. Data on hourly ambulance usage were obtained from the hospital’s emergency department for 2010. Two distinct statistical models, namely the Seasonal Autoregressive Integrated Moving Average (SARIMA) and Seasonal Decomposition model, were used to model the dataset. The study found that both hospitals have different best forecasting models: HSNZ uses the Seasonal Decomposition Model, whereas the SARIMA model was found to forecast better at Hospital Tapah. For example, in the HSNZ study, the study determined the best SARIMA model from a few candidate models, namely. This model showed good performance on the training dataset and performed best on the test dataset. However, when further compared with the seasonal decomposition model, the study found the latter model to perform better. When visually investigated as well, the model’s forecasted values were close to the actual values, or at least relatively acceptable. So far, this study concludes that the developed model is highly localized and specific to the given dataset.

The accessibility of campus buildings and infrastructure in the context of wheelchair users remains an ongoing challenge. This reality prompted an examination of selected facilities through quantitative measurements as well as qualitative data gathered via simulation experiments and surveys involving volunteer participants. Sixteen volunteers took on the role of wheelchair users to directly experience navigation-related difficulties. The findings highlighted several areas where accessibility can be improved to integrate with the Malaysian Standards to gain a better accessibility standard. For instance, some of the ramps were found to be too steep, certain disabled toilet layouts consist of limited manoeuvring space, and the elevator’s design has minor challenges for users. These insights provide the suggestions required to implement a seamless and inclusive experience for all students. This research pinpoints priority areas for improvement to infrastructure with recommendations aimed at strengthening accessibility in support of the Perak Private University campus’s efforts to cultivate an inclusive learning environment welcoming of all students.

This study aimed to determine whether the service performance (SERVPERF) model, with five dimensions (tangibility, reliability, responsiveness, assurance, and e This study aimed to determine whether the service performance (SERVPERF) model, with five dimensions (tangibility, reliability, responsiveness, assurance, and e

Accurate prediction of rainfall is crucial for anticipating and preparing for potential disasters such as floods or droughts in specific areas. This study intro Accurate prediction of rainfall is crucial for anticipating and preparing for potential disasters such as floods or droughts in specific areas. This study intro

The occurrence of floods has the potential to escalate the transmission of infectious diseases. To enhance our comprehension of the health impacts of flooding and facilitate effective planning for mitigation strategies, it is necessary to explore the flood risk management. The variability present in hydrological records is an important and neglecting non-stationary patterns in flood data can lead to significant biases in estimating flood quantiles. Consequently, adopting a non-stationary flood frequency analysis appears to be a suitable approach to challenge the assumption of independent and identically distributed observations in the sample. This research employed the generalized extreme value (GEV) distribution to examine annual maximum flood series. To estimate non-stationary models in the flood data, several statistical tests, including the TL-moment method was utilized on the data from ten stream-flow stations in Johor, Malaysia, which revealed that two stations, namely Kahang and Lenggor, exhibited non-stationary behaviour in their annual maximum streamflow. Two non-stationary models efficiently described the data series from these two specific stations, the control of which could reduce outbreak of infectious diseases when used for controlling the development measures of the hydraulic structures. Thus, the application of these models may help prevent biased prediction of flood occurrences leading to lower number of cases infected by disease.

The non-stationarity in hydrological records is a significant concerning area of interest within the field of flood risk management. Ignoring the non-stationary behaviour in flood series will result in a substantial bias in floods quantile. Hence, the non-stationary flood frequency analysis appeared to be an appropriate option to maintain the independent and identically distributed (IID) assumptions in sample observation. This paper utilized the Generalized Extreme Value (GEV) distribution to analyze extreme flood series. The time-varying moment technique, namely the L-moment and TL-moment methods are employed to estimate the non-stationary model (GEV 1, GEV 2, and GEV 3) in the flood series. The ADF test, Mann-Kendall trend test, and Spearman’s Rho test showed that two out of ten streamflow stations in Johor, Malaysia demonstrated a non-stationary behaviour in the annual maximum streamflow. Results from the simulation study demonstrate a consistent performance on the non-stationary model. Furthermore, the TL-moments method could efficiently predict the flood event estimated at quantiles of the higher return periods.

Extreme flood event are among environmental events with the most disastrous consequences for human society. This paper deals with the identification of homogeneous regions through important steps in the regional frequency analysis. Streamflow totals measured at 70 stations over 1960-2009. The cluster analysis uses kriging technique and shows three regions of streamflow in Peninsular Malaysia. The homogeneity test of L-moments shows that some of these regions are homogeneous. Using the goodness-of-fit test, Z-Dist, the regional frequency distribution functions for each group are then selected. In this study, five three parameter distributions generalized logistic (GLO), generalized extreme-value (GEV), generalized pareto distributions (GPA), Pearson Type III (P3), and three parameter Lognormal (LN3) were fitted to the three homogeneous regions.