Stations In Malaysia Research Articles

Interpolation Using Cubic Bѐzier Triangular Patches

Spatial interpolation is a method that can be used to estimate the unknown value (or parameter) at certain time or location. Besides of that, shape preserving interpolation especially positivity preserving interpolation play an important role for data visualization where the resulting interpolating surface must be positive everywhere. In this study, we use a triangulation based method consists of positivity preserving cubic Bezier triangular patches to estimate the unknown value of rainfall amount at spatial localization. This scheme is useful for spatial data interpolation compared to the mesh free methods which are required the optimization technique in order to ensure the positivity of basis functions.The data is triangulated by using Delaunay’s triangulation algorithm and from there the triangular surfaces are constructed piecewisely comprising three local schemes that are blended together via convex combination to form a scattered interpolating surface. Sufficient conditions on Bezier ordinates are derived in order to preserve the positivity of the surface. Validation of the propose schemes are conducted by using well-known test function used in previous researches. Then, the best the scheme is selected to visualize a rainfall data distribution based on secondary data collected at various meteorology stations in Malaysia obtain from Malaysian Meteorology Department. Finally, we estimate the unknown rainfall amount at certain locations that lies inside the convex hull formed by all given stations. The finding shows that positivity preserving cubic triangular patches is able to preserve the positivity of rainfall distribution surface and has a significant application in estimating the rainfall amount at unallocated meteorology stations in Malaysia.

Integrated approach for the determination of an accurate wind-speed distribution model

The distribution model of wind-speed data is critical for the assessment of wind-energy potential because it reduces uncertainties in the estimation of wind power output. Thus, an accurate distribution model for describing wind-speed data should be determined before a detailed analysis of energy potential is conducted. In this study, information from several goodness-of-fit criteria, e.g., the R2 coefficient, Kolmogorov–Smirnov statistic, Akaike’s information criterion, and deviation in skewness/kurtosis were integrated for the conclusive selection of the best-fit distribution model of wind-speed data. The proposed approach integrates standardized scores and subjects each criterion to multiplicative aggregation. The approach was applied in a case study to fit eight statistical distributions to hourly wind-speed data collected at two stations in Malaysia. The results showed that the proposed approach provides a good basis for the selection of the optimal wind-speed distribution model. Furthermore, graphical representations agreed with the analytical results.

Solving shift scheduling problem with days-off preference for power station workers using binary integer goal programming model

Shift scheduling problem (SSP) is a complex NP-hard integer programming problem, especially when many shifts and large number of workers of various ranks and multi-skills are involved. Shift scheduling also needs to comply with certain labour regulations and organisation’s rules and policies. Various models for SSP have been developed and solved. However, studies on SSP for workers of power stations or utility providers are still lacking. This paper presents the study on shift scheduling of workers at the largest power station in Malaysia. The objectives of this study are to identify main criteria and conditions of SSP at the power station, to formulate a Binary Integer Goal Programming (BGP) model for SSP that optimises workers’ day-off preference and to determine the optimal schedule for workers based on the model. The scheduling focuses on three processes which are demand modelling, shift scheduling and day-off scheduling. The study involves scheduling 43 workers in a selected department of the power station for 28 days where workers work in three shifts (morning, evening and night shifts) and have standby and rest days. The SSP-BGP model considers workers’ day-off preference as its main feature and introduces objective function that maximises the overachievement and minimises under-achievement of the day-off preference. It addresses conflicting multi-objectives in determining the optimal schedule using the goal programming approach. The model also put forward new hard and soft constraints, which reflect the nature of shifts’ requirements for these workers when determining the optimal schedule. The required data have been obtained from the power station and validation and verification of the model has been acquired with the cooperation from its personnel. The SSP-BGP model was solved using MATLAB in reasonable time. It significantly reduces the time to obtain a monthly schedule as compared to current manually done scheduling. Based on the 28-day schedule obtained, the day-off preference’s satisfaction of workers has increased by 37.21% that is from 43.02% based on the existing prepared schedule to 80.23% according to the schedule produced based on the SSP-BGP model. The model has shown good performance by not only generating optimal schedule based on the required number and composition of workers for shifts but also providing positive impacts on workers through day-off preferences’ satisfaction and the possibility of working with different groups.

Performance of pilot scale anaerobic biofilm digester (ABD) for the treatment of leachate from a municipal waste transfer station

The anaerobic treatment of leachate from a municipal waste transfer station in Malaysia was tested using a pilot scale anaerobic biofilm digester system that was operated under HRT sequence of 30-day, 25-day, 20-day and 10-day for 163 days under mesophilic conditions. Despite the leachate’s complex characteristics, the system showed great performance given its maximum COD, BOD5 and total phosphorus removal efficiencies of 98 ± 1%, 99 ± 1% and 92 ± 9% respectively. The system was stable throughout its operation and showed optimal average values for the monitored parameters such as pH (7.53 ± 0.14), total VFA (79 ± 66 mg HOAc/L), alkalinity (10,919 ± 1556 mg CaCO3/L) and a non-toxic value for accumulated ammonia (960 ± 106 mg NH3-N/L). Measurement of the average daily biogas production yielded a value of 25 ± 1 m3/day throughout the system’s operation with a composition of 57 ± 12% methane and 26 ± 6% carbon dioxide.

Primary Study of Tracking Photovoltaic System for Mobile Station in Malaysia

<span>This paper describes the performance of tracking photovoltaic (PV) system for mobile station. The system consists of tracking PV array, the battery bank, the maximum power point tracking (MPPT) controller and the DC/AC inverter). This system is the first full solar power station, which acts as pilot project by Celcom Sdn. Bhd. Success of this system shows potential of electrify rural remote area. The design is hoped to be a pioneer and acts as well-known system in order to ensure renewable energy is the future supply of electricity in far located urban area. This paper showes the record of the battery state-of-charge (SOC) as a function of time for rainy and sunny days.</span>

ANALYSIS OF RAINFALL INDICES AT JPS AMPANG STATION

Understanding characteristics of rainfall of a region could provide vital information for management of water resources. This study aims to explore the spatial pattern and trends of the daily rainfall data based on seasonal rainfall indices. Rainfall indices are adopted to explain main characteristics of rainfall such as the total amount of rainfall, frequency of wet days, rainfall intensity, extreme frequency, and extreme intensity. In particular, these five rainfall indices are used to capture the changes in a variety of aspects of rainfall distribution at a rainfall station, namely JPS Ampang station in Malaysia. The correlation between total amount of rainfall (TAR), frequency of wet days of at least 1 mm of rain (FREQ), mean rainfall amount on wet days or rainfall intensity (RI), frequency of wet days exceeding the 95th percentile (XFREQ) and rainfall intensity exceeding the 95th percentile (XI) indices is estimated. Results show that there is a strong positive correlation between TAR and extreme indices (XFREQ and XI). There is also high positive correlation between TAR and RI. However, a moderate positive correlation is shown between TAR and FREQ as well as between extreme indices (XFREQ and XI) and FREQ.This indicates that higher XFREQ, XI and RI will result in higher value of TAR at JPS Ampang station. Annual rainfall indices show that higher indices including extremes (XFREQ and XRI) are more prominent during La Nina while lower indices are more prominent during El Nino. Keywords: Rainfall intensity; Weibull distribution; hourly rainfall; rainfall indices

Discovering meaningful patterns for tropical climate change in Malaysia

This paper investigated patterns of climate change in Malaysia and proposed a fuzzy based symbolic data representation known as a shapelet patterns algorithm (SPA). The Shapelet Pattern visualise climate change patterns in the form of coloured shapes to indicate annual changes in temperature patterns. The experiment used climate change data collected from four stations in Malaysia, Petaling-jaya, Subang, KLIA-Sepang and University Malaya, to produce three types of results. The results revealed various climate change patterns that can be used by climate change experts to further analyse the effects of climate change and for better decision making.

Solar radiation forecast using hybrid SARIMA and ANN model

Solar Energy have an enormous potential for generating renewable electricity. In the tropics solar energy are abundance all year long but suffer from uncertainty caused by rain and clouds. Accurate prediction of solar radiation can increase the affectivity and productivity of solar energy sources. Monthly average of solar radiation data are obtained from stations in Malaysia. The data are modeled using the Seasonal Autoregressive Integrated Moving Average (SARIMA) model, artificial neural network (ANN) model and Hybrid ANN and SARIMA model. The SARIMA model is a reliable tool in forecasting seasonal data, on the other hand the ANN model have been proven to be a good model in forecasting non-linear data. By combining both model a more accurate model can be obtained. Finally the forecasting performance each model is compared by using mean absolute error (MAE), the mean absolute percentage error (MAPE) and root mean square error (RMSE). The result shows that the hybrid model is better in forecasting solar radiation data.

Regression and multivariate models for predicting particulate matter concentration level.

The devastating health effects of particulate matter (PM10) exposure by susceptible populace has made it necessary to evaluate PM10 pollution. Meteorological parameters and seasonal variation increases PM10 concentration levels, especially in areas that have multiple anthropogenic activities. Hence, stepwise regression (SR), multiple linear regression (MLR) and principal component regression (PCR) analyses were used to analyse daily average PM10 concentration levels. The analyses were carried out using daily average PM10 concentration, temperature, humidity, wind speed and wind direction data from 2006 to 2010. The data was from an industrial air quality monitoring station in Malaysia. The SR analysis established that meteorological parameters had less influence on PM10 concentration levels having coefficient of determination (R 2) result from 23 to 29% based on seasoned and unseasoned analysis. While, the result of the prediction analysis showed that PCR models had a better R 2 result than MLR methods. The results for the analyses based on both seasoned and unseasoned data established that MLR models had R 2 result from 0.50 to 0.60. While, PCR models had R 2 result from 0.66 to 0.89. In addition, the validation analysis using 2016 data also recognised that the PCR model outperformed the MLR model, with the PCR model for the seasoned analysis having the best result. These analyses will aid in achieving sustainable air quality management strategies.

Derivation of GPS TEC and receiver bias for Langkawi station in Malaysia

This paper presents the polynomial-type TEC model to derive total electron content (TEC) and receiver bias for Langkawi (LGKW) station in Malaysia at geographic latitude of 6.32° and longitude of 99.85°. The model uses a polynomial function of coordinates of the ionospheric piercing point to describe the TEC distribution in space. In the model, six polynomial coefficients and a receiver bias are unknown which can be solved by the least squares method. A reasonable agreement is achieved for the derivation of TEC and receiver bias for IENG station in Italy, as compared with that derived by the IGS analysis center, CODE. We process one year of LGKW data in 2010 and show the monthly receiver bias and the seasonal TEC variation. The monthly receiver bias varies between −48 and −24 TECu (1016 electrons/m2), with the mean value at −37 TECu. Large variations happen in the monthly receiver biases due to the low data coverage of high satellite elevation angle (60° < α ≤ 90°). Post-processing TEC approach is implemented which can resolve the wavy pattern of the monthly TEC baseline resulted from the large variation of the receiver bias. The seasonal TEC variation at LGKW exhibits a semi-annual variation, where the peak occurs during equinoctial months, and the trough during summer and winter months.

Characteristics of precipitation extremes in Malaysia associated with El Niño and La Niña events

ABSTRACTThis study investigates the El Niño‐Southern Oscillation (ENSO)‐related seasonal variations in precipitation extremes based on the observed daily precipitation dataset of 23 meteorological stations in Malaysia, spanning a period of 46 years from 1966 to 2011. The extreme indices were a subset of the Expert Team for Climate Change Detection and Indices (ETCCDI) that covers the duration, frequency and intensity aspects of precipitation extremes. Seasonal composites of ‘El Niño minus neutral’ and ‘La Niña minus neutral’ years of these indices were computed based on El Niño and La Niña occurrences during the period. The results showed that the ENSO‐related variations in precipitation extremes were generally coherent with the variations in total precipitation. Generally, dry (wet) precipitation extremes tended to enhance during El Niño (La Niña); however, this was dependent on season and location. The El Niño and La Niña influences on precipitation extremes were not entirely linear. While the impacts of El Niño and La Niña were generally opposite for most locations and seasons, there were cases where both exerted in‐phase influences. The impacts were also dependent on the intensity of the event itself. While the El Niño impacts were generally coherent across different intensities, La Niña can have entirely different impacts among different categories. During December–January–February (DJF), strong (moderate) La Niña caused a significant decrease (increase) in wet precipitation extremes over the Peninsular Malaysia. This was related to the broadening (narrowing and westward displacement) of the anomalous cyclonic circulation over the western north Pacific during strong (moderate) La Niña. Hence, the likelihood for widespread flooding over the east coast of the Peninsular Malaysia during DJF increases during moderate but not during strong La Niña events.

Existing Noise Level at Railway Stations in Malaysia

Railway transportation known as one of the most environmental friendly transportation mode. However, the significance problems of railway transportation are noise pollution and negatively impact the wellbeing of the whole community. Unfortunately, there has been lack of public awareness about the noise level produce by the railway transportation in Malaysia. This study investigates the noise level produced by railway transportation in Malaysia specifically by Keretapi Tanah Melayu Berhad (KTMB). Methods of collecting existing noise level at railway stations in Malaysia are briefly discussed in this study. The finding indicates that the noise level produced by the railway transportation in Malaysia which is by KTMB is considered as dangerous to human being and also exceed the noise limit that has been assigned by Department of Environment Ministry of Natural Resources and Environment of Malaysia. A better noise barrier and improved material should be developed to mitigate the existing noise level produced by railway transportations in Malaysia.

Earth-Space Rain Attenuation Prediction: Its Impact at Ku, Ka and V-band Over Some Equatorial Stations

Attenuation due to rain predictive models have been used to calculate the impact of rainfall on satellite communication for six stations in Malaysia. The impact of rainfall is very important for designing a modern satellite system for heavy rainfall climatic regions like Malaysia, with large annual rainfall accumulation exceeding 3000 mm and rainfall rate exceeding 150 mm/h at Ku (12/14 GHz), Ka (20/30 GHz) and V (40/50 GHz) bands. The present result shows that the avalibility of link for 99.99% at the three bands for uplink and downlink to Malaysian Communication Satellite (MEASAT-3a) is not practicable. The results suggest link availability of 99.9% for Ku-uplink and Ka downlink, while 99% for Ka uplink and 99% for V band uplink and downlink due to high annual rainfall rates for most of the stations. The overall result shows that the impact of heavy rainfall on satellite communication will be more severe in the Eastern part than the Western of Malaysia.

Understanding perception of fire risk from petrol station's workers

This research is about the perception of fire risk and its function of petrol station. Fewer researched in understanding perception of risk in petrol fuel station among its workers. Any prolong of the issues might cause catastrophic in case of leakage, pollution and fire to gas explosion engulf with it. Therefore, a need of qualitative research to carry out to justify the perception of risk not just to the workers but also to give a general information of risk precautions to the people living vicinity of the petrol fuel station. However, Petrol Fuel Station (PFS) category as a hazardous workplace. All flammable substances such as petrol, diesel and CNG are stored either underground or above ground. It is a place where various mode of transportation fuelling and refuelling at every hours. Due to the existing of the flammable substance at PFS pose a potential hazard to the staff, public, property and environment. A simple mismanagement could cause catastrotophic. The issue of risk in petrol station always regards as important since the workplace has been category as non major hazard installation. Nevertheless, the consequences of disaster are very huge. Therefore, it is very crucial to investigate in conducting and questioning of the perception of risk towards petrol fuel station. The qualitative approach will consists of reviewing design drawings (documents), semi structure interview, observation at the premise and analysis to determine and acknowledge the perception of risk among the workers. The research results shows that there is indeed a needs to understand the perception of risk characteristic in order to improve a good practice of especially petrol fuel station in Malaysia. The findings are very precious in better understanding of risk, mitigation plan and formulate a new proposal to the government especially the authority regards to petrol fuel station. The further research should also focus on the risk emulate with the petrol station in future.

Development of new attenuation equation for subduction mechanisms in Malaysia water

The attenuation equation for far field earthquake is important because the earthquake occurring in neighboring countries can be felt in Malaysia. In this study, a new attenuation was generated using the regression method. It was developed to calculate the peak ground acceleration (PGA) onsite (offshore platform). The database consisting of more than 150 PGAs from 9 events of earthquakes recorded by the Seismology Station in Malaysia was used to develop the relationship. In addition, attenuation relationships for subduction mechanisms from previous researchers are then compared with the newly generated ones in this research. The new attenuation equation was also validated and used to calculate the acceleration for far field earthquake in a case study of offshore platform at a Terengganu seaside. The result of PGA from the new generated attenuation relationship was in a good match with previous attenuation equations.

The Position of Da’wah Messages and Ethics in Malaysian and Indonesian Television Programs

Rapid changes in the whole aspects of our lives as a result of the global development need to be addressed by spreading da’wah messages through television channels. To be an effective da’wah media, television should have a strong editorial policy. The policy forwarded could prove the dynamic representation of the country. This study aims to explore the editorial policy of TV Malaysia and Indonesia in presenting da’wah programs, and secondly, to understand the position of ethics in the da’wah messages broadcast on Malaysian and Indonesian TVs. By using qualitative methods, the data have been derived from direct observations and interviews with three television stations in Malaysia (two government-owned and one private-owned TVs) and TVRI and RCTI in Indonesia. Data are also enriched by relevant information from watching Malaysian and Indonesian TV channels. The results showed similarities and differences between the TV editorial policies of the two countries. Respondent from both countries showed that they tried to attract viewers through providing various kinds of religious broadcasts and carefully considered what they should show on prime time. The different thing is the determination of the da’i and program duration. On Malaysian television, determination of the religious speakers is very strict, whereas in Indonesia determination television speakers tend to be rather easy. In terms of duration, the whole da’wah broadcasts per day on Malaysian television are longer and are more frequent than that on the Indonesian’s. In Malaysia, the programs are decided to be on schedule for prime time while in Indonesia the da’wah programs are mostly not in the prime time.

Application of Step Wise Regression Analysis in Predicting Future Particulate Matter Concentration Episode

Particulate matter is an air pollutant that has resulted in tremendous health effects to the exposed populace. Air quality forecasting is an established process where air pollutants particularly, particulate matter (PM10) concentration is predicted in advance, so that adequate measures are implemented to reduce the health effect of PM10 to the barest level. The present study used daily average PM10 concentration and meteorological parameters (temperature, humidity, wind speed and wind direction) for 5 years (2006–2010) from three industrial air quality monitoring stations in Malaysia (Balok Baru, Tasek and Paka). Time series plot was used to assess PM10 pollution trend in the industrial areas. Additionally, step wise regression (SWR) analysis was used to predict next day PM10 concentrations for the three industrial areas. The SWR method was compared with a persistence model to assess its predictive capabilities. The results for the trend analysis showed that, Balok Baru (BB) had higher PM10 concentration levels, having high values in 2006, 2007 and 2009. These values were higher than the Malaysian Ambient Air Quality Guideline (MAAQG) of 150 μg/m3. Subsequently, the other two industrial areas Tasek (TK) and Paka (PK) had no record of violating the MAAQG. The results for the SWR analysis had significant R 2 values of 0.64, 0.66 and 0.60, respectively. The model performance results for variance inflation factor (VIF) were less than 5 and Durbin-Watson test (DW) had value of 2 for each of the study areas, which were significant. The comparative analysis between SWR and persistence model showed that the SWR had better capabilities, having lower errors for the BB, TK and PK areas. Using root mean square error (RMSE), the results showed error differences of 7, 12 and 16 %, and higher predictability using index of agreement (IA), having a difference of 17, 19 and 16 % for BB, TK, and PK areas, respectively. The results showed that SWR can be used in predicting PM10 next day average concentration, while the extreme event detection results showed that 100 μg/m3 were better detected than the 150 μg/m3 bench marked levels.

Provisions of Disabled Facilities at The Malaysian Public Transport Stations

Public transport stations need to provide access and facilities for people with disabilities (PWD) in fulfilling the requirements of the Malaysian Standard Code of Practice on Access of Disabled Persons (MS). However, most public transport stations in Malaysia are reported as still lacking in terms of providing good designs and facilities for the PWDs. This inaccessible environment affects the PWDs to negatively participate in the social and economic mainstream. The research aims at identifying the compliance of disabled facilities provided at the electronic train service (ETS) railway station in Perak. Two research objectives were established (1) to identify the range of disabled facilities provided at the ETS railway station in Perak and (2) to determine the compliance of the disabled facilities as outlined in the MS. Eight ETS railway stations in Perak were chosen for the case study. Purely qualitative methods were adopted. An observation checklist was developed by conducting document analysis on three main documents. The findings suggest that there are 14 disabled facilities to be provided at the ETS railway stations. Majority of these facilities are available and comply with the MS. Conversely, some improvement can be made to further promote sustainability atmosphere of the ETS railway stations.

Assessment of Wind Energy Potential in Three Different Locations of Malaysia

In this study, wind energy potential in three different stations in Malaysia in period of 5 years is analyzed. Base on Weibull distribution parameters, the mean wind speed, wind power density and wind energy density is estimated for each defined location. Although there are many works about wind potential in Malaysia, however a few of them have been provided a comprehensive study about wind power in different places in Malaysia. According to the findings, the annual mean wind speeds indicates that the highest wind speed variation is about 2 m/s and is belonged to the Subang station and the highest wind speed is 3.5 m/s in in Kudat. It is also found that the maximum wind power densities among these three sites are 22 W/m2, 24 W/m2 and 22 W/m2 in Kudat station in January, February and September respectively. The results of the study show that as the second parameter for Weibull model, the highest wind energy density has been 190 kWh/m2 per year in Kudat and the lowest one has been about 60 kWh/m2 in Kuching.

Attenuation Function Relationship for Far Field Earthquake Considered by Strike Slip Mechanism

An attenuation relationship for far field earthquakes considered by strike slip has been developed. The attenuation relationship function was develop using regression analysis. The database consisting of more than 130 peak ground accelerations from seven earthquake sources recorded by Seismology Station in Malaysia have been used to develop the relationship. This study aims to investigate the new relationship attenuation to gain exact peak ground acceleration at the location on site. Based on this study, the location is a structure located at Terengganu seaside.