Abdul Aziz Jemain

This paper introduces a recognition system for firearms identification based on cartridge case image. When a gun is fired, a unique characteristic on the cartridge and projectile of a bullet are produced. There are more than 30 marks left on the sur- face of a fired bullet which are invaluable towards identifying the firearm used. These characteristics are known as the mechanical fingerprint of firearm. Therefore, this re- search has extracted forty eight significantly different features of geometric moment from cartridge case images. Then correlation analysis was used to select the vital and relevant features for classification using discriminant analysis.

Firearms identification is a vital aim of firearm analysis. The firing pin impression image on a cartridge case from a fired bullet is one of the most significant clues in firearms identification. In this study, a set of data which focused on selected 6 features of firing pin impression images before an entirety of five different pistols of South African made; the Parabellum Vector SPI 9mm model, were used. The numerical features are geometric moments of whole image computed from a total of 747 cartridge case images. Under pattern recognition theory, the supervised features of firing pin impression images were then trained and validated using a two-layer backpropagation neural network (BPNN) design with computed hidden layers. A two-layer 6-7-5 connections BPNN of sigmoid/linear transfer functions with `trainlm' algorithm was found to yield the best classification result using cross-validation, where 96% of the images were correctly classified according to the pistols used. Moreover, the network was trained under very small mean-square error (MSE=0.01). This means that neural network method is capable to learn and validate well the numerical features of whole firing pin impression with high precision and fast classification results.

The task of identifying firearms from forensic ballistics specimens is exacting in crime investigation since the last two decades. Every firearm, regardless of its size, make and model, has its own unique ‘fingerprint’. These fingerprints transfer when a firearm is fired to the fired bullet and cartridge case. The components that are involved in producing these unique characteristics are the firing chamber, breech face, firing pin, ejector, extractor and the rifling of the barrel. These unique characteristics are the critical features in identifying firearms. It allows investigators to decide on which particular firearm that has fired the bullet. Traditionally the comparison of ballistic evidence has been a tedious and time-consuming process requiring highly skilled examiners. Therefore, the main objective of this study is the extraction and identification of suitable features from firing pin impression of cartridge case images for firearm recognition. Some previous studies have shown that firing pin impression of cartridge case is one of the most important characteristics used for identifying an individual firearm. In this study, data are gathered using 747 cartridge case images captured from five different pistols of type 9 mm Parabellum Vektor SP1, made in South Africa. All the images of the cartridge cases are then segmented into three regions, forming three different set of images, i.e. firing pin impression image, centre of firing pin impression image and ring of firing pin impression image. Then geometric moments up to the sixth order were generated from each part of the images to form a set of numerical features. These 48 features were found to be significantly different using the MANOVA test. This high dimension of features is then reduced into only 11 significant features using correlation analysis. Classification results using cross-validation under discriminant analysis show that 96.7% of the images were classified correctly. These results demonstrate the value of geometric moments technique for producing a set of numerical features, based on which the identification of firearms are made.

This study examines the relationship between quality management practices and the efficiency in cost management in Local Authorities. Eighty organizations participated in this study, whereby the data are gathered through self-administered structured questionnaire. Employing regression analysis, the results revealed that both employee focus and ICT have positive association with the efficiency in cost management while process management has the inverse relationship. Thus, in order to achieve a superior level of efficiency in cost management, Local Authorities need to address these three components.

The development of rainfall occurrence models is continuously being explored by a number of researchers in the field since the 20th century. In order to further enhance the development of rainfall occurrence modeling, this present study is aimed to propose a new probability model which is able to describe the daily series of rainfall occurrence, particularly on the duration of consecutive dry or wet days in Peninsular Malaysia. In selecting the most successful model to describe the distribution of the rainfall event, the model with the less ...

The aim of this study is to model rainfall amounts on a daily basis by fitting a smooth curve to the mean rainfall per rainy day. The rainfall amounts are described as gamma distributions with smoothing parameters. The smoothing technique used is the approach of the Fourier series. Six rain gauge stations with the daily rainfall series covering the same period (1975–2004) are examined. Different rainfall patterns are observed among the stations, particularly between the east and the west. The stations in the western area have a bimodal pattern of rainfall and are best described with two harmonics, while four harmonics are required for the stations in the eastern area which exhibit a unimodal pattern of rainfall. The resulting curves with fitted smoothing parameters provide a good summary of statistics and useful information for describing the rainfall patterns and climate of the studied stations. Copyright © 2009 Royal Meteorological Society

Normally, rainfall data is collected on a daily, monthly or annual basis in the form of discrete observations. The aim of this study is to convert these rainfall values into a smooth curve or function which could be used to represent the continuous rainfall process at each region via a technique known as functional data analysis. Since rainfall data shows a periodic pattern in each region, the Fourier basis is introduced to capture these variations. Eleven basis functions with five harmonics are used to describe the unimodal rainfall pattern for stations ...

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 ...

Double quartile ranked set sampling procedure (DQRSS) and its properties for estimating the population mean are introduced. The performance of DQRSS with respect to simple random sapling (SRS), ranked set sampling (RSS) and quartile ranked set samples (QRSS) for estimating the population mean, is considered. The DQRSS estimator is unbiased of the population mean for symmetric distributions about its mean.

The main objective of this study is to determine the best fitting distribution to describe the annual series of maximum daily rainfall from 1975 to 2004 for 50 rain gauge stations in Peninsular Malaysia based on L-moment and LQ-moment. Five three-parameter extreme-value distributions which are considered are generalized extreme value (GEV), generalized Pareto (GP), generalized logistic (GL), lognormal (LN3) and Pearson (P3) distributions. The estimation of parameters of these distributions is determined using the L-moment and LQ-moment. The adequacy of the distributions based on parameter estimates computed using the two methods are evaluated using goodness-of-fit tests. When the goodness-of-fit results for these distributions are compared, it is found that, on the average, the performance of L-moment is better than the performance of LQ-moment. Although the best fitting distribution may vary according to the method of estimation and stations considered, in most cases, data for the majority of the stations are found to follow the generalized logistic distribution.

The development of the rainfall occurrence model is greatly important not only for data-generation purposes, but also in providing informative resources for future advancements in water-related sectors, such as water resource management and the hydrological and agricultural sectors. Various kinds of probability models had been introduced to a sequence of dry (wet) days by previous researchers in the field. Based on the probability models developed previously, the present study is aimed to propose three types of mixture distributions, namely, the mixture of two log series distributions (LSD), the mixture of the log series Poisson distribution (MLPD), and the mixture of the log series and geometric distributions (MLGD), as the alternative probability models to describe the distribution of dry (wet) spells in daily rainfall events. In order to test the performance of the proposed new models with the other nine existing probability models, 54 data sets which had been published by several authors were reanalyzed in this study. Also, the new data sets of daily observations from the six selected rainfall stations in Peninsular Malaysia for the period 1975–2004 were used. In determining the best fitting distribution to describe the observed distribution of dry (wet) spells, a Chi-square goodness-of-fit test was considered. The results revealed that the new method proposed that MLGD and MLPD showed a better fit as more than half of the data sets successfully fitted the distribution of dry and wet spells. However, the existing models, such as the truncated negative binomial and the modified LSD, were also among the successful probability models to represent the sequence of dry (wet) days in daily rainfall occurrence.

The amount of daily rainfall for a solitary wet day (Class 0) is normally less than the rainfall for a wet day that is enclosed by wet days on either side (Class 2). The same characteristics hold true for the case of the first or last day of wet spells (Class 1) where the rainfall here is found to be smaller than the Class 2 rainfall. In many cases, there exist large differences between these rainfall classes. However, this is not the case for the Malaysian rainfall data. The daily rainfall data from 50 rain gauge stations which represent four regions in ...

The analysis of the daily rainfall occurrence behavior is becoming more important, particularly in water-related sectors. Many studies have identified a more comprehensive pattern of the daily rainfall behavior based on the Markov chain models. One of the aims in fitting the Markov chain models of various orders to the daily rainfall occurrence is to determine the optimum order. In this study, the optimum order of the Markov chain models for a 5-day sequence will be examined in each of the 18 rainfall stations in Peninsular Malaysia, which have been selected based on the availability of the data, using the Akaike’s (AIC) and Bayesian information criteria (BIC). The identification of the most appropriate order in describing the distribution of the wet (dry) spells for each of the rainfall stations is obtained using the Kolmogorov-Smirnov goodness-of-fit test. It is found that the optimum order varies according to the levels of threshold used (e.g., either 0.1 or 10.0 mm), the locations of the region and the types of monsoon seasons. At most stations, the Markov chain models of a higher order are found to be optimum for rainfall occurrence during the northeast monsoon season for both levels of threshold. However, it is generally found that regardless of the monsoon seasons, the first-order model is optimum for the northwestern and eastern regions of the peninsula when the level of thresholds of 10.0 mm is considered. The analysis indicates that the first order of the Markov chain model is found to be most appropriate for describing the distribution of wet spells, whereas the higher-order models are found to be adequate for the dry spells in most of the rainfall stations for both threshold levels and monsoon seasons.

This study aims to trace changes in the dry spells over Peninsular Malaysia based on the daily rainfall data from 36 selected rainfall stations which include four subregions, namely northwest, west, southwest, and east for the periods of 1975 to 2004. Six dry spell indices comprising of the main characteristics of dry spells, the persistency of dry events, and the frequency of the short and long duration of dry spells will be used to identify whether or not these indices have increased or decreased over Peninsular Malaysia during the monsoon seasons. The findings of this study indicate that the northwestern areas of the Peninsular could be considered as the driest area since almost all the indices of dry spells over these areas are higher than in the other regions during the northeast (NE) monsoon. Based on the individual and the field significant trends, the results of the Mann–Kendall test indicate that as the total number of dry days, the maximum duration, the mean, and the persistency of dry days are decreased, the trend of the frequency of long dry spells of at least 4 days is also found to decrease in almost all the stations over the Peninsula; however, an increasing trend is observed in the frequency of short spells in these stations during the NE monsoon season. On the other hand, during the southwest monsoon, a positive trend is observed in the characteristics of dry spells including the persistency of two dry days in many stations over the Peninsula. The frequency of longer dry periods exhibits a decreasing trend in most stations over the western areas during both monsoon seasons for the periods of 1975 to 2004.

Abstract The objective of this study is to develop improved LQ-moments that do not impose restrictions on the value of p and alpha such as the median, trimean or the Gastwirth but we explore an extended class of LQMOM with consideration combinations of p and alpha ...

Abstract: Disease mapping is a method used to display the geographical distribution of disease occurrence. Recently, this method has received much attention from many researchers including epidemiologists, biostatisticians and medical demographers. Some traditional methods of classification for detection of high or low risk area such as traditional percentiles method and significant method have been used in disease mapping for map construction.

Abstract Use of instruments or questionnaires in different cultural settings without proper validation can result in inaccurate results. Issues like reliability, validity, feasibility and acceptability should be considered in the use of an instrument. The study aims to determine the usefulness of the CIS-R Malay version in detecting common mental health problems specifically to establish the validity. The CIS-R instrument (PROQSY* format) was translated through the back translation process into Malay.

Abstract Prolonged dry condition has become a recurrent phenomenon in Peninsular Malaysia. The country's agricultural sector and water resources are under severe constraints from this condition. The dry conditions are examined using the Standard Precipitation Index based on the data of monthly rainfall for the period of 30 years from ten stations.

Abstract: This study examines the relationship between babies' mortality, prosperity and amenities. Our objective is to investigate some factors (Prosperity and Amenities), which are related to infant, neonatal and stillbirth mortality. The importance of our goal or our purpose is followed from what Weeks1'1 stated: There are few things in the world more frightening and awesome than the responsibility for a newborn child-fragile and completely dependent on others for survival.

Abstract The Extreme Ranked Set Sampling (ERSS), which was introduced by Samawi et al.(1996), is a modification of the Ranked Set Sampling (RSS) of McIntyre (1952). In this paper, we study the power of a set of modified Empirical Distribution Function (EDF) goodness of fit tests under both Simple Random Sampling (SRS) and ERSS. A simulation study is conducted to compare the power functions of these tests to SRS counterparts.

Abstract In classification ratemaking, the multiplicative and additive models derived by actuaries are based on two common methods; minimum bias and maximum likelihood. These models are already considered as established and standard, particularly in automobile and general liability insurance. This paper aims to identify the relationship between both methods by rewriting the equations of both minimum bias and maximum likelihood as a weighted equation.

ABSTRACT Apnea is one of the sleep disorder and many study relates apnea with gender, age and BMI of the patients. Few study indicates that apnea occurred in REM and NREM sleep stages. This study involves a sleep record from apnea patients in Hospital Sarawak, Malaysia. The objective of the study is to find the homogenous of REM sleep between patients using the Gini index. Furthermore the differences of mean functional of REM according to gender, age and bmi.

This paper presents several types of exponential distributions to describe rainfall distribution in Peninsular Malaysia over a multi-year period. The exponential, gamma, mixed exponential and mixed gamma distributions are compared to identify the optimal model for daily rainfall amount based on data recorded at rain gauges stations in Peninsular Malaysia. The models are evaluated based on the Akaike Information criterion (AIC).

Abstract—Information on the best probability models in representing the weekly distribution of dry and wet spells is increasingly important in various sectors including hydrological and water resource management. The application of the mixed probability models such as the mixture among the log series and geometric, Poisson as well as the truncated distributions is considered in fitting the observed data sets.

ABSTRACT The purpose of this study was to identify the rainfall distribution patterns in Peninsular Malaysia using Standard Precipitation Index at different time scales which are one month, six months and twelve months. Daily rainfall data for 75 rain-gauge stations covering four zones which are Northwest, West, Southwest and East for 33 years: 1975–2007 were considered. The results of the analysis showed that the dispersion value for occurrence of wet/dry condition increases with higher time scale.

ABSTRACT The objective of this study was to map the infant mortality cases over Peninsular Malaysia by district for the period of 1991 to 2000. Relative risks estimation based on empirical Bayes method was used in this study. Three methods of estimation were described which include moment method, maximum likelihood method and combination of moment and maximum likelihood method. The robustness of the parameters estimation was examined using Bootstrap method.

Abstract This paper presents a case study of the Malaysian technical education system. The Technical and Vocational Department (TVED) is designated to prepare skilled technical and intelligent workforce to Malaysia in order to meet the goals of Vision 2020. For that reason, a web-based management support system is proposed to TVED for its planning, management and decision-making activities. e-BME is a system for education monitoring and evaluation by means of establishing internal and external efficiency indicators.

Abstract Makalah ini membincangkan penggunaan momen ortogon Legendre (MOL) sebagai suatu fitur untuk pengelasan imej kedudukan penumpang yang tersegmen-sempurna. Keupayaan mengenal pasti kedudukan penumpang dalam kenderaan adalah penting misalnya sebagai input kepada suatu sistem kereta pintar yang dapat memberikan maklumat untuk pelepasan beg udara keselamatannya.

Abstract In actuarial hteramre, researchers suggested various statistical procedures to estimate the parameters in claim count or frequency model. In particular, the Poisson regression model, which is also known as the Generahzed Linear Model (GLM) with Poisson error structure, has been x~ adely used in the recent years.

Statistical analysis of extremes is conducted for predicting large return periods events. LQ-moments that are based on linear combinations are reviewed for characterizing the upper quantiles of distributions and larger events in data. The LQ-moments method is presented based on a new quick estimator using five points quantiles and the weighted kernel estimator to estimate the parameters of the generalized extreme value (GEV) distribution.

Abstract Semenjak beberapa tahun yang lepas, model regresi Poisson telah diguna secara meluas untuk pengkelasan risiko. Narnun, model regresi Poisson mengandaikan bahawa min dan varians pemboleh ubah bersandar adalah sama, sedangkan secara praktis, masalah lebih–serakan mungkin wujud di dalam data, yakni, situasi di mana varians adalah lebih besar daripada min.

Abstrak. Kadar fertiliti umur tertentu mempunyai bentuk lengkung yang tekal. Keistimewaan ini memungkinkan lengkung tersebut dipadankan dengan suatu fungsi matematik. Usaha menjejak fungsi matematik ini telah dilakukan oleh ramai ahli demografi dan data kelahiran di pelbagai negara telah digunakan untuk proses pemadanan. Kertas ini menyelidiki kesesuaian model-model matematik fertiliti umur tertentu yang pernah dicadangkan oleh ahli demografi dengan data kelahiran di Semenanjung Malaysia.

Abstract The method of LQ-moments (LQMOM) for estimating parameters and quantiles of the Generalized Logistic (GL) distribution are introduced. We explore and extend class of LQMOM with consideration combinations of p and α values in the range 0 and 0.5. The popular quantile estimator namely the weighted kernel quantile (WKQ) estimator is proposed to estimate the quantile function. A comparison of these methods is done by simulation.

Abstract Objective The health of an individual is influenced by many factors. These could include factors that are related to the economy and the environment, as well as social and biological factors. Many studies have been carried out to study the effect of these factors on health, in terms of the individual factors or combined factors. The main purpose of this study was to demonstrate the value of structural equation modeling for the construction of an index to describe the health status of an individual.

Abstract. The fertility pattern has been investigated in several studies but concisely focus more on discrete data. Thus, this study examines the functional form of fertility changes and identifies the characteristics curve patterns based on mothers' aged group. A set of age specific fertility rates from year 1968 to 2005 (38 years) is applied in this study.

This paper investigates the degree of emphasis given on each of nine criteria normally considered by working women in their everyday decision-makings. It attempts to quantify the degree of how one criterion is more important than the other. A method of deriving weight for each criterion that takes into consideration the raw weight and variation in the data is suggested.

Abstract Over the last decades, the development of the Klang Valley (Malaysia), as an urban commercial and industrial area, has elevated the risk of atmospheric pollutions. There are several significant sources of air pollutants which vary depending on the background of the location they originate from. The aim of this study is to determine the trend and status of air quality and their correlation with the meteorological factors at different air quality monitoring stations in the Klang Valley.

Abstract—In this paper, we have examined the applicability of single site disaggregation model (HYETOS) based on the Poisson cluster model to disaggregate daily rainfall to hourly data using proportional adjusting procedure. In this study, the modified Bartlett Lewis Model (MBL) is fitted to the hourly rainfall depth from 1970 to 2008 available at the rain gauge station in Petaling Jaya. In addition, the synthetic hourly rainfall is generated by inputting the estimated parameters found based on MBL into the Hyetos model.

ABSTRACT In this paper a comparative study is made for the efficiency of an empirical distribution function goodness of fit tests. The tests are used for the logistic distribution. A new method is introduced to improve the efficiency of these tests under ranked set sampling. Simulation is used to show that the tests are more efficient than their counterparts in simple random sampling. The percentage points are obtained under the null hypotheses.