Background: Safety and health audit study is a part of occupational safety and health risk assesment. Thus, student’s residential audit is important in order tu ensure the safety rules which implemented by the management is appropriate and follow the standard set forth. Furthermore, it also important to determine places, area or situation that might lead to hazard risk so that prevention step could be plan and implement.
Objective: This study was to determine the safety level of students residential in physical aspects.
Methods: Safety inspection or audit conducted is in accordance with criteria and indicators listed in the checklists that have been formed based on the audit forms from the Department of Safety and Health (DOSH), National Institute of Safety and health (NIOSH) and the Occupational Safety and Health Committee of UKMs (JKKP). Several indicators are also included in the audit form as to ensure it covers all the technical aspect and suited with the college conditions. The safety level for each of the blocks in KDO is categorized using points and percentage score obtained.
Results: Based on the overall score, the average safety score in percentage for areas in KDO are preceded by general office with score 85.5% followed by residential blocks with 71.5%, facilities with score 71.2% and administration block with 70.9%. The results of the study show that most of the areas are at least in a safe level.
Conclusion: Roles of employer and college administration, significant OSH programme and safety audit are important factors as to ensure the safety of student's residential college.
How people perceive risk influences their behaviour towards these risks. We do not know how workers perceive risk of dying from activities or technology. This study was conducted among 198 workers of a security company in Malaysia. The workers were asked to score on a Likert scale of 1 to 5 the perceived risk of death of Malaysians from activities and technology. The highest perceived risks of death were, in order of ranking, motorcycles, motor vehicles, handguns, alcoholic beverages and smoking. The difference in perception and reality is discussed.
During the early postwar years up to 1957, the three main races in Malaya - Malays, Chinese, and Indians - experienced some differences in their levels of fertility. The lowest fertility was recorded among the Malays, with Chinese and Indian fertility about 5 percent and 10 percent higher, respectively. The comparatively low fertility of the Malays was owing to the exceptionally high rate of divorce, which meant unstable marriages and shorter periods of exposure to the risk of childbearing.A fairly well-defined pattern of state differences in fertility levels is found to exist in Malaya. Briefly, fertility was on the high side in the northern states of Johore, Malacca, and Negri Sembilan, and on the low side in the northern states of Penanq, Kelantan, Perlis, Kedah, and Trengganu, with the central states of Perak, Selangor, and Pahang in the intermediate position.The usual rural-urban fertility differentials are seen to prevail in Malaya as a whole and in the smaller units at state levels. Finally, the three main races registered higher fertility in rural areas, and the greatest gap between rural and urban rates prevailed among the Chinese.
Individuals with Diabetes Mellitus (DM) are at increased risk for developing
diabetic ocular complications. This study was carried out to determine factors
influencing eye screening among Diabetes Mellitus patients. The descriptive findings of
participants’ sociodemographic data will be discussed. (Copied from article).
Rapid advances in technology make it necessary to prepare our society in every aspect. Some of the most significant technological developments of the last decade are the UAVs (Unnamed Aerial Vehicles) or drones. UAVs provide a wide range of new possibilities and have become a tool that we now use on a daily basis. However, if their use is not controlled, it could entail several risks, which make it necessary to legislate and monitor UAV flights to ensure, inter alia, the security and privacy of all citizens. As a result of this problem, several laws have been passed which seek to regulate their use; however, no proposals have been made with regards to the control of airspace from a technological point of view. This is exactly what we propose in this article: a platform with different modes designed to control UAVs and monitor their status. The features of the proposed platform provide multiple advantages that make the use of UAVs more secure, such as prohibiting UAVs’ access to restricted areas or avoiding collisions between vehicles. The platform has been successfully tested in Salamanca, Spain.
This study develops a Road Safety Index (RSI) for commercial bus with the aim of determining whether the
proposed index can be beneficial to the stakeholders for the purpose of mitigating road accident and promoting road
safety. Five risk factors which include drivers, Vehicle, Task, Hazard/Risk and Road, where three critical factors out of
these factors, were identified as high contributing factors (Drivers, Vehicle and Road) were selected for the construction
of RSI. Drivers risk perceptions data were collected using survey instrument with sample size (n= 465) to test the
model and the data fits the model perfectly. The main benefits of this approach and the subsequent development of
RSI are: (1) Enable organisations to justify the investment on road safety by providing a measurement and evaluation
mechanism. (2) The index provides a balanced view of the impact of the three critical (DVR) risk factors that the
management can improve upon.
This study is carried out to establish the prevalence of Work-related Musculoskeletal Disorders (MSD) among
the Malaysian workforce population in order to propose some measures to benefit the people at large. Secondary data
from three studies among drivers, clerical workers using visual display terminals (VDT) and fabrication workers were
used to report the prevalence of MSDs and the associated risk factors. The study identified high prevalence of MSDs in
multiple body regions. The MSD occurrence was also significantly associated with psychosocial factors. There is need
for organisations to consider such factors in work design, which will reduce the high prevalence and high financial
implications associated with MSDs among workers.
Eddy current testing (ECT) is an accurate, widely used and well-understood inspection technique, particularly in the aircraft and nuclear industries. The coating thickness or lift-off will influence the measurement of defect depth on pipes or plates. It will be an uncertain decision condition whether the defects on a workpiece are cracks or scratches. This problem can lead to the occurrence of pipe leakages, besides causing the degradation of a company’s productivity and most importantly risking the safety of workers. In this paper, a novel eddy current testing error compensation technique based on Mamdani-type fuzzy coupled differential and absolute probes was proposed. The general descriptions of the proposed ECT technique include details of the system design, intelligent fuzzy logic design and Simulink block development design. The detailed description of the proposed probe selection, design and instrumentation of the error compensation of eddy current testing (ECECT) along with the absolute probe and differential probe relevant to the present research work are presented. The ECECT simulation and hardware design are proposed, using the fuzzy logic technique for the development of the new methodology. The depths of the defect coefficients of the probe’s lift-off caused by the coating thickness were measured by using a designed setup. In this result, the ECECT gives an optimum correction for the lift-off, in which the reduction of error is only within 0.1% of its all-out value. Finally, the ECECT is used to measure lift-off in a range of approximately 1 mm to 5 mm, and the performance of the proposed method in non-linear cracks is assessed.
The attention on genetically modified (GM) food industry is increasing due to the flourishing
of biotechnology. However, there are some debates on the associated benefits and risks of
employing modification technology in food industry. This study strives to examine the causes
that determine consumers’ benefit and risk perceptions on GM foods. Besides, the influence of
perceived benefit and risk of GM food on consumers’ attitude is investigated. The empirical
results of this study showed that GM food knowledge, and GM food characteristics have been
acting as important predictors of both benefits and risks perceptions. Further, it is also found
that perceived benefits showed significant positive influence on attitude, and attitude affects
purchase intention towards GM food. Research implications to policy makers, scientists, and
market practitioners are covered, in which suggestions and recommendations are provided
to these parties. Lastly, research implications and recommendations to future research are
discussed.
Information on situation of air pollution is critically needed as input in four disciplines of research including risk management, risk evaluation, environmental epidemiology, as well as for status and trend analysis. Two normal practices were identified to evaluate daily air pollution situation; first, pollution magnitude has been treated as the common indicator, and second, the analysis was often conducted based on hourly average data. However, the information on the magnitude level alone to represent the pollution condition based on a rigid point data such as the average was seen as insufficient. Thus, to fill the gap, this study was conducted based on continuously measured data in the form of curves, which is also known as functional data, whereby pollution duration is emphasised. A statistical method based on curve ranking was used in the investigation. The application of the method at Klang, Petaling Jaya and Shah Alam air quality monitoring stations located in the Klang Valley, Malaysia, has shown that pollution duration decreases as the magnitude increases. Shah Alam has the longest pollution duration at low and medium magnitude levels. Meanwhile, all the three stations experienced quite a similar length of average pollution duration for the high magnitude level, that is, about 2.5 days. It was also shown that the occurrence of PM10 pollution at the area is significantly not random.
The selection criteria play an important role in the portfolio optimization
using any ratio model. In this paper, the authors have considered the mean return as
profit and variance of return as risk on the asset return as selection criteria, as the first
stage to optimize the selected portfolio. Furthermore, the sharp ratio (SR) has been
considered to be the optimization ratio model. In this regard, the historical data taken
from Shanghai Stock Exchange (SSE) has been considered. A metaheuristic technique
has been developed, with financial tool box available in MATLAB and the particle swarm
optimization (PSO) algorithm. Hence, called as the hybrid particle swarm optimization
(HPSO) or can also be called as financial tool box particle swarm optimization (FTBPSO).
In this model, the budgets as constraint, where as two different models i.e. with
and without short sale, have been considered. The obtained results have been compared
with the existing literature and the proposed technique is found to be optimum and better
in terms of profit.
Management is consistently facing fast-flowing and lots of changes in business, including in the inventory management. Especially for fast-moving inventories, the correct stocking, controlling, checking and safety stock calculation is highly needed to have an exquisite inventory management and to reduce the possibility of running out of inventory which leads to unavailability to meet the demand. One of the ways to overcome this is by doing an excellent and appropriate forecasting. Therefore, the objective of this concept paper is to analyse and recommend tools to improve inventory management using the appropriate time-series forecasting method. The firm studied in this study is serving its employees as customers that demand the routine items including stationeries and other routine products to support their job as auditors and consultants for its client. However, there are occasions when there is out-of-stock situation for fast-moving items, especially in the peak season period. Furthermore, the firm is only applying replenishment based on the used inventories from the previous month. Therefore, this study suggests to eliminate out-of-stock items situation by applying precaution initiatives such as time-series forecasting. This study is planned to employ 10 time-series forecasting methods such as moving average, exponential smoothing, regression analysis, Holt-Winters analysis, Seasonal analysis and Autoregressive Integrated Moving Average (ARIMA) using Risk Simulator Software. By simulating those methods, the most appropriate method is selected based on the forecasting accuracy measurement.
The innovations and developments in microbiology, biomedical sciences, and biotechnology come along with the challenges of biological risk (biorisk). Biorisk is defined as the "combination of the probability of occurrence of harm and the severity of that harm where the source of harm is a biological agent or toxin." Biorisk is a borderless challenge to the global community. Hence, all universities, colleges, centers of bio-excellence, and institutions of higher learning can and should do their bit to educate technical members, academicians, students and stakeholders (LASS) for the efficient and comprehensive biorisk management (BRM) for our and future generations safety and sustainability.
Statistical distributions of annual extreme (AE) and partial duration (PD) for rainfall events are analysed using a database of 50 rain-gauge stations in Peninsular Malaysia, involving records of time series data which extend from 1975 to 2004. The generalised extreme value (GEV) and generalised Pareto (GP) distributions are considered to model the series of annual extreme and partial duration. In both cases, the three parameter models such as GEV and GP distributions are fitted by means of L-moments method, which is one of the commonly used methods for robust estimation. The goodness-of-fit of the theoretical distribution to the data is then evaluated by means of L-moment ratio diagram and several goodness-of-fit (GOF) tests for each of the 50 stations. It is found that for the majority of stations, the AE and PD series are well fitted by the GEV and GP models, respectively. Based on the models that have been identified, we can reasonably predict the risks associated with extreme rainfall for various return periods.
The accuracy of financial time series forecasts often rely on the model precision and the availability of actual observations for forecast evaluations. This study aimed to tackle these issues in order to obtain a suitable asymmetric time-varying volatility model that outperformed in the forecast evaluations based on interday and intraday data. The model precision was examined based on the most appropriate time-varying volatility representation under the autoregressive conditional heteroscedascity framework. For forecast precision, the evaluations were conducted under three loss functions using the volatility proxies and realized volatility. The empirical studies were implemented on two major financial markets and the estimated results are applied in quantifying their market risks. Empirical results indicated that Zakoian model provided the best in-sample forecasts whereas DGE on the other hand indicated better out-of-sample forecasts. For the type of volatility proxy selection, the implementation of intraday data in the latent volatility indicated significant improvement in all the time horizon forecasts.
The aim of this paper was to identify the determinants that influence vehicle theft by applying a negative binomial regression model. The identification of these determinants is very important to policy-makers, car-makers and car owners, as they can be used to establish practical steps for preventing or at least limiting vehicle thefts. In addition, this paper also proposed a crime mapping application that allows us to identify the most risky areas for vehicle theft. The results from this study can be utilized by local authorities as well as management of internal resource planning of insurance companies in planning effective strategies to reduce vehicle theft. Indirectly, this paper has built ingenuity by combining information obtained from the database of Jabatan Perangkaan Malaysia and insurance companies to pioneer the development of location map of vehicle theft in Malaysia.
This paper focuses on measuring risk due to extreme events going beyond the multivariate normal distribution of joint returns. The concept of tail dependence has been found useful as a tool to describe dependence between extreme data in finance. Specifically, we adopted a multivariate Copula-EGARCH approach in order to investigate the presence of conditional dependence between international financial markets. In addition, we proposed a mixed Clayton-Gumbel copula with estimators for measuring both, the upper and lower tail dependence. The results showed significant dependence for Singapore and Malaysia as well as for Singapore and US, while the dependence for Malaysia and US was relatively weak
The conventional use of aminoglycoside antibiotics has several disadvantages including the need for regular pre- and post-dose assaying and the risks of toxicity. Achieving a therapeutic and non-toxic serum concentration may be difficult in many patients especially those with severe sepsis. Correct timing of doses and assays is essential, but this is often difficult to achieve. Many of these difficulties may be remedied by the use of once daily dosing. This dosing schedule appears to be equally effective as the conventional method and i s also less toxic. There are many other advantages including the need for less assays and venepuncture resulting in reduced costs. KEYWORDS: Aminoglycosides, antibiotic therapy, toxicity, therapeutic monitoring
The increasing involvement of women in the paid-labor market has led to multifactorial exposure towards the development of noncommunicable diseases (NCDs). This review aims to identify the prevalence of NCDs and the associated risk factors among working women. A systematic review was performed using PubMed and Scopus databases. Twelve articles published between 2015 and 2019 satisfied the inclusion and exclusion criteria and were selected for qualitative synthesis. Among working women, the prevalence of NCDs was as follows: coronary heart disease, 0.3%-5.9%; metabolic syndrome, 52.0%; diabetes mellitus, 8.9%-16.0%; hypertension, 16.6%-66.4%; non-skin cancer, 3.7%. The prevalence of NCD risk factors was as follows: overweight/obesity, 33.8%-77.0%; low physical activity, 51.0%; unhealthy diet, 44.9%-69.9%; dyslipidemia, 27.8%-44.0%. The factors associated with NCDs were long working hours, double work burden, and stress. NCD is an important burden of working women that will lead to reduced work quality and affect family well-being. Disease prevention approaches, such as the intervention of common workplace risk factors and specific work schedule design, are among the strategies for improving the situation.