In this paper, a personal verification method using finger vein is presented. Finger vein can be considered more secured compared to other hands based biometric traits such as fingerprint and palm print because the features are inside the human body. In the proposed method, a new texture descriptor called local line binary pattern (LLBP) is utilized as feature extraction technique. The neighbourhood shape in LLBP is a straight line, unlike in local binary pattern (LBP) which is a square shape. Experimental results show that the proposed method using LLBP has better performance than the previous methods using LBP and local derivative pattern (LDP).
Biometric verification methods have gained significant popularity in recent times, which has brought about their extensive usage. In light of theoretical evidence surrounding the development of biometric verification, we proposed an experimental multi-biometric system for laboratory testing. First, the proposed system was designed such that it was able to identify and verify a user through the hand contour, and blood flow (blood stream) at the upper part of the hand. Next, we detailed the hard and software solutions for the system. A total of 40 subjects agreed to be a part of data generation team, which produced 280 hand images. The core of this paper lies in evaluating individual metrics, which are functions of frequency comparison of the double type faults with the EER (Equal Error Rate) values. The lowest value was measured for the case of the modified Hausdorff distance metric - Maximally Helicity Violating (MHV). Furthermore, for the verified biometric characteristics (Hamming distance and MHV), appropriate and suitable metrics have been proposed and experimented to optimize system precision. Thus, the EER value for the designed multi-biometric system in the context of this work was found to be 5%, which proves that metrics consolidation increases the precision of the multi-biometric system. Algorithms used for the proposed multi-biometric device shows that the individual metrics exhibit significant accuracy but perform better on consolidation, with a few shortcomings.
Unmanned Aerial Vehicle (UAV) is one of the latest technologies for high spatial resolution 3D modeling of the Earth. The objectives of this study are to assess low-cost UAV data using image radiometric transformation techniques and investigate its effects on global and local accuracy of the Digital Surface Model (DSM). This research uses UAV Light Detection and Ranging (LIDAR) data from 80 meters and UAV Drone data from 300 and 500 meters flying height. RAW UAV images acquired from 500 meters flying height are radiometrically transformed in Matrix Laboratory (MATLAB). UAV images from 300 meters flying height are processed for the generation of 3D point cloud and DSM in Pix4D Mapper. UAV LIDAR data are used for the acquisition of Ground Control Points (GCP) and accuracy assessment of UAV Image data products. Accuracy of enhanced DSM with DSM generated from 300 meters flight height were analyzed for point cloud number, density and distribution. Root Mean Square Error (RMSE) value of Z is enhanced from ±2.15 meters to 0.11 meters. For local accuracy assessment of DSM, four different types of land covers are statistically compared with UAV LIDAR resulting in compatibility of enhancement technique with UAV LIDAR accuracy.
Iris biometric detection provides contactless authentication, preventing the spread of COVID-19-like contagious diseases. However, these systems are prone to spoofing attacks attempted with the help of contact lenses, replayed video, and print attacks, making them vulnerable and unsafe. This paper proposes the iris liveness detection (ILD) method to mitigate spoofing attacks, taking global-level features of Thepade's sorted block truncation coding (TSBTC) and local-level features of the gray-level co-occurrence matrix (GLCM) of the iris image. Thepade's SBTC extracts global color texture content as features, and GLCM extracts local fine-texture details. The fusion of global and local content presentation may help distinguish between live and non-live iris samples. The fusion of Thepade's SBTC with GLCM features is considered in experimental validations of the proposed method. The features are used to train nine assorted machine learning classifiers, including naïve Bayes (NB), decision tree (J48), support vector machine (SVM), random forest (RF), multilayer perceptron (MLP), and ensembles (SVM + RF + NB, SVM + RF + RT, RF + SVM + MLP, J48 + RF + MLP) for ILD. Accuracy, precision, recall, and F-measure are used to evaluate the performance of the projected ILD variants. The experimentation was carried out on four standard benchmark datasets, and our proposed model showed improved results with the feature fusion approach. The proposed fusion approach gave 99.68% accuracy using the RF + J48 + MLP ensemble of classifiers, immediately followed by the RF algorithm, which gave 95.57%. The better capability of iris liveness detection will improve human-computer interaction and security in the cyber-physical space by improving person validation.
Most of existing image encryption schemes are proposed in the spatial domain which easily destroys the correlation between pixels. This paper proposes an image encryption scheme by employing discrete cosine transform (DCT), quantum logistic map and substitution-permutation network (SPN). The DCT is used to transform the images in the frequency domain. Meanwhile, the SPN is used to provide the security properties of confusion and diffusion. The SPN provides fast encryption as compared to the asymmetric based image encryption since operations with low computational complexity are used (e.g., exclusive-or and permutation). Different statistical experiments and security analysis are performed against six grayscale and color images to justify the effectiveness and security of the proposed image encryption scheme.
Chitosan-epichlorohydrin/TiO2 composite was synthesized to be employed as an adsorbent for the
removal of reactive red 4 (RR4) dye from aqueous solution. Response surface methodology (RSM) with 3-level Box-Behnken design (BBD) was utilized for the optimization of the removal of RR4. The process key variables which include adsorbent dose (A: 0.5 – 1.5 g), pH (B: 4 – 10) and time (30 – 80 min) were selected for the optimization process. The experimental data for RR4 removal were statistically analysed using analysis of variance (ANOVA). The significant interaction between key parameters on RR4 removal efficiency was observed by interaction between AB and AC. The highest RR4 removal (95.08%) was obtained under the following conditions; adsorbent dose (1.0 g), pH 4 and time of 80 min.
Statistical classification remains the most useful statistical tool for forensic chemists to assess the relationships between samples. Many clustering techniques such as principal component analysis and hierarchical cluster analysis have been employed to analyze chemical data for pattern recognition. Due to the feeble foundation of this statistics knowledge among novice drug chemists, a tetrahedron method was designed to simulate how advanced chemometrics operates. In this paper, the development of the graphical tetrahedron and computational matrices derived from the possible tetrahedrons are discussed. The tetrahedron method was applied to four selected parameters obtained from nine illicit heroin samples. Pattern analysis and mathematical computation of the differences in areas for assessing the dissimilarity between the nine tetrahedrons were found to be user-convenient and straightforward for novice cluster analysts.
Halophilic cellulases from the newly isolated fungus, Aspergillus terreus UniMAP AA-6 were found to be useful for in situ saccharification of ionic liquids treated lignocelluloses. Efforts have been taken to improve the enzyme production through statistical optimization approach namely Plackett-Burman design and the Face Centered Central Composite Design (FCCCD). Plackett-Burman experimental design was used to screen the medium components and process conditions. It was found that carboxymethylcellulose (CMC), FeSO4·7H2O, NaCl, MgSO4·7H2O, peptone, agitation speed and inoculum size significantly influence the production of halophilic cellulase. On the other hand, KH2PO4, KOH, yeast extract and temperature had a negative effect on enzyme production. Further optimization through FCCCD revealed that the optimization approach improved halophilic cellulase production from 0.029 U/ml to 0.0625 U/ml, which was approximately 2.2-times greater than before optimization.
Rainfalls data have been broadly used in researches including in hydrological and meteorological areas. Two common ways in extracting observations from hourly rainfalls data are the window-based analysis (WBA) and storm-event analysis (SEA) approach. However, the differences in the qualitative and quantitative properties of both methods are still vaguely discussed. The aim of studying these dissimilarities is to understand the effects of each approach in modelling and analysis. The qualitative difference is due to the way the two analyses define the accumulated rainfalls for observations which are referred to as rainfall and storm depths, respectively. The repetitiveness of rainfall depths provide nested structure while the storm depths are considered independent. The quantitative comparisons include their statistical and scaling properties that are linked by the self-similarity concept from simple scaling characteristics. If self-similarity concept
holds, then the rainfall or storm depths follow simple scaling and the analysis would be simplified. The rainfall depths showed clearer simple scaling characteristics compared to the storm depths. Though the storm depths do not yield self-similarity for a large range of storm duration but the characteristics of simple scaling can be observed for a reduced range of the considered duration. In general, the context of the research and the region of the time interval and duration will be an important aspects to consider in choosing which method is best to use for analyzing the data.
Over the years, maximum likelihood estimation and Bayesian method became popular statistical tools in which applied to fit finite mixture model. These trends begin with the advent of computer technology during the last decades. Moreover, the asymptotic properties for both statistical methods also act as one of the main reasons that boost the popularity of the methods. The difference between these two approaches is that the parameters for maximum likelihood estimation are fixed, but unknown meanwhile the parameters for Bayesian method act as random variables with known prior distributions. In the present paper, both the maximum likelihood estimation and Bayesian method are applied to investigate the relationship between exchange rate and the rubber price for Malaysia, Thailand, Philippines and Indonesia. In order to identify the most plausible method between Bayesian method and maximum likelihood estimation of time series data, Akaike Information Criterion and Bayesian Information Criterion are adopted in this paper. The result depicts that the Bayesian method performs better than maximum likelihood estimation on financial data.
In this research we introduce an analyzing procedure using the Kullback-Leibler information criteria (KLIC) as a statistical tool to evaluate and compare the predictive abilities of possibly misspecified density forecast models. The main advantage of this statistical tool is that we use the censored likelihood functions to compute the tail minimum of the KLIC, to compare the performance of a density forecast models in the tails. Use of KLIC is practically attractive as well as convenient, given its equivalent of the widely used LR test. We include an illustrative simulation to compare a set of distributions, including symmetric and asymmetric distribution, and a family of GARCH volatility models. Our results on simulated data show that the choice of the conditional distribution appears to be a more dominant factor in determining the adequacy and accuracy (quality) of density forecasts than the choice of volatility model.
A cross-sectional study was undertaken to determine the refractive and biometric status of premature children without Retinopathy of Prematurity (ROP) and full term children. Fifty eight children between the ages of 3 and 7 years (32 children born premature without ROP and another 26 children born full term and normal) were examined. Refractive error, corneal curvature, axial length, anterior chamber depth and crystalline lens thickness were determined. The results revealed that children between the age of 3 and 7 years were emmetropic, irrespective of whether they were born premature without ROP or full term. However, children born premature without ROP had significantly steeper corneas (t = 3.14, p = 0.0349), shorter axial lengths (t = 3.18, p = 0.0313) and thicker crystalline lens (t = 3.31, p = 0.0256) compared to children born full term within the same age group. This study suggests that compensation in ocular parameters can occur to maintain emmetropia, mainly by adjustment of axial length and corneal curvature.
This study investigated the spatial pattern and trends of the daily rainfall data in Peninsular Malaysia based on seasonal rainfall indices. Five rainfall indices which describe the main characteristics of rainfall, the total amount of rainfall, frequency of wet days, rainfall intensity, extreme frequency, and extreme intensity, were employed in this study. The statistics of rainfall indices were calculated in terms of their means for four regions in Peninsular Malaysia for the period 1975 to 2004. The findings indicate that the southwest monsoon had the greatest impact on the western part of the Peninsula, particularly in characterizing the rainfall pattern of the northwest region. During this season, the northwest region could be considered as the wettest region since all rainfall indices tested are higher than in other regions of the Peninsula. Otherwise, the northwest region is denoted as the driest part of the Peninsula during the northeast monsoon period. The northwest region is less influenced by the northeast monsoon because of the existence of the Titiwangsa Range, which blocks the region from receiving heavy rainfall. On the other hand, it is found that the lowlands areas such as the eastern part of the Peninsula are strongly characterized by the northeast monsoonal flow. Based on the results of the Mann-Kendall test, as the trend of the total amount of rainfall and the frequency of wet days during the southwest monsoon decrease at most of the stations, the rainfall intensity increases. In contrast, increasing trends in both the total amount of rainfall and the frequency of wet days were observed at several stations during the northeast monsoon, which give rise to the increasing trend of rainfall intensity. The results for both seasons indicate that there are significantly decreasing trends in the frequency of wet days during the extreme events for most of the stations on the peninsula. However, a smaller number of significant trends was found for extreme intensity.
A Poisson model typically is assumed for count data, but when there are so many zeroes in the response variable, because of overdispersion, a negative binomial regression is suggested as a count regression instead of Poisson regression. In this paper, a zero-inflated negative binomial regression model with right truncation count data was developed. In this model, we considered a response variable and one or more than one explanatory variables. The estimation of regression
parameters using the maximum likelihood method was discussed and the goodness-of-fit for the regression model was examined. We studied the effects of truncation in terms of parameters estimation, their standard errors and the goodnessof-fit statistics via real data. The results showed a better fit by using a truncated zero-inflated negative binomial regression model when the response variable has many zeros and it was right truncated.
Hidden truncation (HT) and additive component (AC) are two well known paradigms of generating skewed distributions from known symmetric distribution. In case of normal distribution it has been known that both the above paradigms lead to Azzalini's (1985) skew normal distribution. While the HT directly gives the Azzalini's ( 1985) skew normal distribution, the one generated by AC also leads to the same distribution under a re parameterization proposed by Arnold and Gomez (2009). But no such re parameterization which leads to exactly the same distribution by these two paradigms has so far been suggested for the skewed distributions generated from symmetric logistic and Laplace distributions. In this article, an attempt has been made to investigate numerically as well as statistically the closeness of skew distributions generated by HT and AC methods under the same re parameterization of Arnold and Gomez (2009) in the case of logistic and Laplace distributions.
The statistical characteristics of wind direction that was recorded at maximum wind speed in Peninsular Malaysia for two monsoons from 1999 to 2008 for seven stations were analyzed in this study. Modeled by von Mises distribution, the change in parameters values namely mean direction and concentration parameter was measured. Statistical summary, graphical representations, Watson-William Test and linear-circular correlation are used in the analysis. It is found that there is a significant change in the mean direction of wind over the period of ten years for most stations in Peninsular Malaysia. However, there is a weak relationship between wind direction and wind speed. This study suggested the presence of prominent direction of wind that blows in Peninsular Malaysia by monsoon. This finding may provide useful information on giving a better understanding of the behavior of the wind in Peninsular Malaysia and the potential use of wind as an alternative source of energy.
This paper presents the accuracy of age statistics in the 1991 census. The quality of age statistics were evaluated using Myers index and United Nations index. The indices obtained were compared to the indices of 1970 and 1980. This study found that age statistics for 1991 census are better than the previous censuses and in general the statistics are having high quality.
Dalam kertas ini dibentangkan ketepatan statistik umur pada banci 1991. Kualiti statistik umur dinilai dengan menggunakan indeks Myers dan United Nations. Indeks yang diperoleh dibandingkan dengan indeks pada banci 1970 dan 1980. Kajian ini mendapati statistik umur banci 1991 lebih baik daripada hasil banci sebelumnya dan pada keseluruhannya ia mempunyai kualiti yang baik.
Total Variance (TV) and Generalized Variance (GV) are commonly used as a measure multivariate dispersion. However, these two statistics has some drawbacks. This paper proposes a new measure of multivariate dispersion, named Vectorial Variance (VV) an inner product for set of operators defined on a Hilbert-Smith space. Since, the exact sampling distribution of VV is difficult to find, therefore the asymptotic sampling distribution is obtained.
[Jumlah Varians dan Varians Teritlak kebiasaannya digunakan sebagai ukuran dispersi multivariate. Namun begitu, kedua-dua statistik ini mempunyai beberapa kelemahan. Dalam tulisan ini akan dicadankgan satu ukuran dispersi multivariate yang baru, dikenali sebagai varians bervektor (VV) yang merupakan suatu hasil darab terkedalam bagi set pengoperasi yang tertakrif ke atas suatu ruang Hilbert-Smith. Oleh kerana taburan pensampilan tepat dari statistik vv tersebut sangat sukar untuk ditentukan, maka taburan pensampilan asimtot telah diperolehi].
This paper focuses on detecting outliers in the circular data which follow the wrapped normal distribution. We considered four discordance tests based on M, C, D and A statistics. The cut-off points of the four tests were obtained and the performance of the detection procedures was studied via simulations. In general, we showed that the discordance test based on the A statistic outperforms the other tests in all cases. For illustration, the city of Kuantan wind direction data set was considered.
Otoliths, which can be used for the evaluation of relationships between the environment and organisms, are structures
consisting of calcium carbonate. The aim of this study was to realize the shape analysis. In addition, it is to detect the
characteristics of otolith biometrics in order to determine the relationship between the fish size of Engraulis encrasicolus
L. from the Black and Marmara Seas. The samples were obtained from the Black and Marmara Seas between December
2013 and February 2014. The relationships between the TL (Total length) and OL (Otolith length), TL and OB (Otolith
breadth), and TL and OW (Otolith weight) were determined using the linear regression equation. Form factor, roundness,
circularity and rectangularity were used for shape analyses. According to the data, there was no difference between
localities (p>0.05). Moreover, there was no difference between the left and right otoliths of the individuals sampled from
the same locality (p>0.05). According to the regression coefficient for relationships of TL-OL, TL-OB and TL-OW, otolith
length was identified as the best index for estimating fish length (r
2
>0.70). It showed that index values were statistically
different between two populations (p<0.001).