Displaying publications 41 - 60 of 189 in total

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  1. Suwanda Idris
    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].
    Matched MeSH terms: Biometry
  2. Adzhar Rambli, Safwati Ibrahim, Mohd Ikhwan Abdullah, Abdul Ghapor Hussin, Ibrahim Mohamed
    Sains Malaysiana, 2012;41:769-778.
    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.
    Matched MeSH terms: Biometry
  3. Khade S, Gite S, Thepade SD, Pradhan B, Alamri A
    Sensors (Basel), 2021 Nov 08;21(21).
    PMID: 34770715 DOI: 10.3390/s21217408
    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.
    Matched MeSH terms: Biometry
  4. Chan KW, Tan GH, Wong RC
    Sci Justice, 2012 Sep;52(3):136-41.
    PMID: 22841136 DOI: 10.1016/j.scijus.2012.04.006
    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.
    Matched MeSH terms: Biometry
  5. Allawi MF, Aidan IA, El-Shafie A
    Environ Sci Pollut Res Int, 2021 Feb;28(7):8281-8295.
    PMID: 33052565 DOI: 10.1007/s11356-020-11062-x
    The accuracy level for reservoir evaporation prediction is an important issue for decision making in the water resources field. The traditional methods for evaporation prediction could encounter numerous obstacles owing to the effect of several parameters on the shape of the evaporation pattern. The current research presented modern model called the Coactive Neuro-Fuzzy Inference System (CANFIS). Modification for such model has been achieved for enhancing the evaporation prediction accuracy. Genetic algorithm was utilized to select the effective input combination. The efficiency of the proposed model has been compared with popular artificial intelligence models according to several statistical indicators. Two different case studies Aswan High Dam (AHD) and Timah Tasoh Dam (TTD) have been considered to explore the performance of the proposed models. It is concluded that the modified GA-CANFIS model is better than GA-ANFIS, GA-SVR, and GA-RBFNN for evaporation prediction for both case studies. GA-CANFIS attained minimum RMSE (15.22 mm month-1 for AHD, 8.78 mm month-1 for TTD), minimum MAE (12.48 mm month-1 for AHD, 5.11 mm month-1 for TTD), and maximum determination coefficient (0.98 for AHD, 0.95 for TTD).
    Matched MeSH terms: Biometry
  6. Banadkooki FB, Ehteram M, Ahmed AN, Teo FY, Ebrahimi M, Fai CM, et al.
    Environ Sci Pollut Res Int, 2020 Oct;27(30):38094-38116.
    PMID: 32621196 DOI: 10.1007/s11356-020-09876-w
    Suspended sediment load (SSL) estimation is a required exercise in water resource management. This article proposes the use of hybrid artificial neural network (ANN) models, for the prediction of SSL, based on previous SSL values. Different input scenarios of daily SSL were used to evaluate the capacity of the ANN-ant lion optimization (ALO), ANN-bat algorithm (BA) and ANN-particle swarm optimization (PSO). The Goorganrood basin in Iran was selected for this study. First, the lagged SSL data were used as the inputs to the models. Next, the rainfall and temperature data were used. Optimization algorithms were used to fine-tune the parameters of the ANN model. Three statistical indexes were used to evaluate the accuracy of the models: the root-mean-square error (RMSE), mean absolute error (MAE) and Nash-Sutcliffe efficiency (NSE). An uncertainty analysis of the predicting models was performed to evaluate the capability of the hybrid ANN models. A comparison of models indicated that the ANN-ALO improved the RMSE accuracy of the ANN-BA and ANN-PSO models by 18% and 26%, respectively. Based on the uncertainty analysis, it can be surmised that the ANN-ALO has an acceptable degree of uncertainty in predicting daily SSL. Generally, the results indicate that the ANN-ALO is applicable for a variety of water resource management operations.
    Matched MeSH terms: Biometry
  7. Abdul Latiff D, Irfan M, Jafri Malin A
    Malays J Med Sci, 2012 Apr;19(2):1-4.
    PMID: 22973132
    As a small-although growing-journal based in Malaysia, the Malaysian Journal of Medical Sciences (MJMS) has faced several challenges in the past, such as promoting our journal as well as making sure our article bank does not go empty. However, we strive to improve ourselves by taking all means necessary to increase the quantity and, most importantly, quality of our publications, as well as to increase our journal's visibility and citability. This editorial will focus on MJMS statistics throughout 2011-where MJMS turned 18-as well as future plans for our journal.
    Matched MeSH terms: Biometry
  8. Bujang MA
    Malays J Med Sci, 2021 Apr;28(2):15-27.
    PMID: 33958957 DOI: 10.21315/mjms2021.28.2.2
    Determination of a minimum sample size required for a study is a major consideration which all researchers are confronted with at the early stage of developing a research protocol. This is because the researcher will need to have a sound prerequisite knowledge of inferential statistics in order to enable him/her to acquire a thorough understanding of the overall concept of a minimum sample size requirement and its estimation. Besides type I error and power of the study, some estimates for effect sizes will also need to be determined in the process to calculate or estimate the sample size. The appropriateness in calculating or estimating the sample size will enable the researchers to better plan their study especially pertaining to recruitment of subjects. To facilitate a researcher in estimating the appropriate sample size for their study, this article provides some recommendations for researchers on how to determine the appropriate sample size for their studies. In addition, several issues related to sample size determination were also discussed.
    Matched MeSH terms: Biometry
  9. Naik VR, Jaafar H, Seng CE
    Indian J Pathol Microbiol, 2010 Jan-Mar;53(1):12-4.
    PMID: 20090214 DOI: 10.4103/0377-4929.59175
    The purpose of this study was to count the number of lymphatic channels present in colorectal adenocarcinoma and correlate it with site, size, and stage of tumor, lymph node metastasis.
    Matched MeSH terms: Biometry/methods
  10. Simoneau G, Levis B, Cuijpers P, Ioannidis JPA, Patten SB, Shrier I, et al.
    Biom J, 2017 Nov;59(6):1317-1338.
    PMID: 28692782 DOI: 10.1002/bimj.201600184
    Individual patient data (IPD) meta-analyses are increasingly common in the literature. In the context of estimating the diagnostic accuracy of ordinal or semi-continuous scale tests, sensitivity and specificity are often reported for a given threshold or a small set of thresholds, and a meta-analysis is conducted via a bivariate approach to account for their correlation. When IPD are available, sensitivity and specificity can be pooled for every possible threshold. Our objective was to compare the bivariate approach, which can be applied separately at every threshold, to two multivariate methods: the ordinal multivariate random-effects model and the Poisson correlated gamma-frailty model. Our comparison was empirical, using IPD from 13 studies that evaluated the diagnostic accuracy of the 9-item Patient Health Questionnaire depression screening tool, and included simulations. The empirical comparison showed that the implementation of the two multivariate methods is more laborious in terms of computational time and sensitivity to user-supplied values compared to the bivariate approach. Simulations showed that ignoring the within-study correlation of sensitivity and specificity across thresholds did not worsen inferences with the bivariate approach compared to the Poisson model. The ordinal approach was not suitable for simulations because the model was highly sensitive to user-supplied starting values. We tentatively recommend the bivariate approach rather than more complex multivariate methods for IPD diagnostic accuracy meta-analyses of ordinal scale tests, although the limited type of diagnostic data considered in the simulation study restricts the generalization of our findings.
    Matched MeSH terms: Biometry/methods*
  11. Mohsin AH, Zaidan AA, Zaidan BB, Ariffin SAB, Albahri OS, Albahri AS, et al.
    J Med Syst, 2018 Oct 29;42(12):245.
    PMID: 30374820 DOI: 10.1007/s10916-018-1103-6
    In real-time medical systems, the role of biometric technology is significant in authentication systems because it is used in verifying the identity of people through their biometric features. The biometric technology provides crucial properties for biometric features that can support the process of personal identification. The storage of biometric template within a central database makes it vulnerable to attack which can also occur during data transmission. Therefore, an alternative mechanism of protection becomes important to develop. On this basis, this study focuses on providing a detailed analysis of the extant literature (2013-2018) to identify the taxonomy and research distribution. Furthermore, this study also seeks to ascertain the challenges and motivations associated with biometric steganography in real-time medical systems to provide recommendations that can enhance the efficient use of real-time medical systems in biometric steganography and its applications. A review of articles on human biometric steganography in real-time medical systems obtained from three main databases (IEEE Xplore, ScienceDirect and Web of Science) is conducted according to an appropriate review protocol. Then, 41 related articles are selected by using exclusion and inclusion criteria. Majority of the studies reviewed had been conducted in the field of data-hiding (particularly steganography) technologies. In this review, various steganographic methods that have been applied in different human biometrics are investigated. Thereafter, these methods are categorised according to taxonomy, and the results are presented on the basis of human steganography biometric real-time medical systems, testing and evaluation methods, significance of use and applications and techniques. Finally, recommendations on how the challenges associated with data hiding can be addressed are provided to enhance the efficiency of using biometric information processed in any authentication real-time medical system. These recommendations are expected to be immensely helpful to developers, company users and researchers.
    Matched MeSH terms: Biometry/methods*
  12. Rosdi BA, Shing CW, Suandi SA
    Sensors (Basel), 2011;11(12):11357-71.
    PMID: 22247670 DOI: 10.3390/s111211357
    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).
    Matched MeSH terms: Biometry
  13. Ibrahim Awad Mohammed, Abdallah Reghioua, Emad Yousif, Ali H. Jawad, Nurul Najwa Abd Malek
    Science Letters, 2020;14(1):96-108.
    MyJurnal
    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.
    Matched MeSH terms: Biometry
  14. NURUL HIDAYAH ZULKIPLI, SURIA BABA
    MyJurnal
    The problem in analysing qualitative study is regularly highlighted when it comes to data analysis process. Unlike quantitative data that deals with numerical and statistical issues, analysing qualitative data requires the researcher to deal with understanding human experiences and interpreting the data. Therefore, validity and reliability of the analysis are often questioned and becomes a challenge in analysing data from qualitative research. The objective of this writing is to highlight some of the challenges and strengths in the qualitative research process. Validity, reliability, and credibility are among the challenges in analysing qualitative study. Rigor in conducting data collection helps in overcoming the problem in validity, reliability and credibility. In addition, in-depth understanding and triangulation techniques such as interview, document analysis and observation used in qualitative researches are among the strengths for qualitative study.
    Matched MeSH terms: Biometry
  15. Nur Idalisa, Mohd. Rivaie, Nurul Hafawati Fadhilah, Nur Atikah, Anis Shahida, Nur Hidayah Mohd. Noh
    MATEMATIKA, 2019;35(2):229-235.
    MyJurnal
    Regression is one of the basic relationship models in statistics. This paper focuses on the formation of regression models for the rice production in Malaysia by analysing the effects of paddy population, planted area, human population and domestic consumption. In this study, the data were collected from the year 1980 until 2014 from the website of the Department of Statistics Malaysia and Index Mundi. It is well known that the regression model can be solved using the least square method. Since least square problem is an unconstrained optimisation, the Conjugate Gradient (CG) was chosen to generate a solution for regression model and hence to obtain the coefficient value of independent variables. Results show that the CG methods could produce a good regression equation with acceptable Root Mean-Square Error (RMSE) value.
    Matched MeSH terms: Biometry
  16. M. Kaviza
    MyJurnal
    This study aims at investigating the effect of using historical text document resources on the historical substantive concepts understanding among Form Four students. A learning activities module was developed based on using historical text document resources as reference for intervention in this study. Pre-Experimental Design: One Group PreTest-PostTest was used in this study. The impact of using historical teks document resources on the historical substantive concepts understanding were measured in the pre-test, post-test and delayed post-test. A sample of respondents comprising 55 students from existing classes was recruited in this study using cluster sampling techniques. The historical substantive concept understanding test was used in this study. Data were analyzed by descriptive and inference statistics using Repeated-Measures One Way ANOVA test. The findings showed that the use of historical text document resources has an impact on the historical substantive concepts understandingand retaintion. The implication of this study is to provide the content and methods for implementation of history learning by using a set of collections of historical text document resources which relevant to a historical topic.
    Matched MeSH terms: Biometry
  17. Hassim NA, Hambali K, Idris NSU, Amir A, Ismail A, Zulkifli SZ, et al.
    Trop Life Sci Res, 2018 Jul;29(2):175-186.
    PMID: 30112148 MyJurnal DOI: 10.21315/tlsr2018.29.2.12
    Long-tailed macaque (Macaca fascicularis) has the potential to be a good biological indicator for toxic exposure because they have an almost similar physiology and behaviour to humans. The objective of this study is to determine the concentration of lead (Pb) in hair samples of long-tailed macaques which were found in and out of the Kuala Selangor Nature Park (KSNP) area. The hypothesis is long-tailed macaques that live in the anthropogenic area (outside KSNP) may be exposed to high levels of lead compared to long-tailed macaques living in the forest area (inside KSNP). Analysis of hair samples were carried out using Inductively Coupled Plasma-Mass Spectrometry (ICP-MS). The study found that the average mean of lead concentration in the anthropogenic area is 6.31 μg/g while for the forest area it is 3.16 μg/g. Lead concentration in the two areas are statistically insignificant. Nevertheless, lead concentration in the anthropogenic area recorded a slightly higher mean concentration than in the forest area. Even so, results of this study indicate that long-tailed macaques in Kuala Selangor are not exposed to high levels of lead. This study is the first in Malaysia to utilise long-tailed macaques as a biological indicator for testing the concentration of toxic substances in the environment. This study is still in its early stages; thus, future research requires improvements.
    Matched MeSH terms: Biometry
  18. Jafarizadeh Malmiri, H., Osman, A., Tan, C.P., Abdul Rahman, R.
    MyJurnal
    Response surface methodology (RSM) was used to optimize the concentrations of chitosan and glycerol for coating Berangan banana (Musa sapientum cv. Berangan). The effects of main edible coating components, chitosan (0.5-2.5%, w/w) and glycerol (0-2%, w/w) on weight loss, firmness, total colour difference, total soluble solids content (TSS) and titratable acidity (TA) of coated banana were studied during 10 days of storage at 26±2°C and 40-50% relative humidity. Results showed that the experimental data could be adequately fitted into a second-order polynomial model with coefficient of determination (R 2 ) ranging from 0.745 to 0.930 for all the variables studied. In general, the chitosan concentration appeared to be the most significant (P< 0.1) factor influencing all variables except for TSS. The optimum concentration of chitosan and glycerol were predicted to be 2.02% and 0.18%, respectively. Statistical assessment showed insignificant difference between experimental and predicted values.
    Matched MeSH terms: Biometry
  19. Abidin, N. Z., Adam, M. B., Midi, H.
    MyJurnal
    Extreme Value Theory (EVT) is a statistical field whose main focus is to investigate extreme phenomena. In EVT, Fréchet distribution is one of the extreme value distributions and it is used to model extreme events. The degree of fit between the model and the observed values was measured by Goodness-of-fit (GOF) test. Several types of GOF tests were also compared. The tests involved were Anderson-Darling (AD), Cramer-von Mises (CVM), Zhang Anderson Darling (ZAD), Zhang Cramer von-Mises (ZCVM) and Ln. The values of parameters μ, σ and ξ were estimated by Maximum Likelihood. The critical values were developed by Monte-Carlo simulation. In power study, the reliability of critical values was determined. Besides, it is of interest to identify which GOF test is superior to the other tests for Fréchet distribution. Thus, the comparisons of rejection rates were observed at different significance levels, as well as different sample sizes, based on several alternative distributions. Overall, given by Maximum Likelihood Estimation of Fréchet distribution, the ZAD and ZCVM tests are the most powerful tests for smaller sample size (ZAD for significance levels 0.05 and 0.1, ZCVM for significance level 0.01) as compared to AD, which is more powerful for larger sample size.
    Matched MeSH terms: Biometry
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