Displaying publications 41 - 60 of 183 in total

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  1. On the estimation of three parameters lognormal distribution based on fuzzy life time data
    Shafiq M, Alamgir, Atif M
    Sains Malaysiana, 2016;45:1773-1777.
    Countless statistical tools are available to extract information from data. Life time modeling is considered as one of
    the most prominent fields of statistics, which is evident from the developments made in this field in the last few decades.
    Almost every statistic for life time analysis is based on precise life time observations, however, life time is not a precise
    measurement but more or less fuzzy. Therefore, in addition to classical statistical tools, fuzzy number approaches to
    describe life time data are more suitable. In order to incorporate fuzziness of the observations, fuzzy estimators for the
    three parameter lognormal distribution were suggested. The proposed estimators cover stochastic variation as well as
    fuzziness of the observations.
    Matched MeSH terms: Biometry
  2. Prevalence of Workplace Bullying and Its Associated Factors among Workers in a Malaysian Public University Hospital: A Cross-Sectional Study
    Awai NS, Ganasegeran K, Abdul Manaf MR
    Risk Manag Healthc Policy, 2021;14:75-85.
    PMID: 33447111 DOI: 10.2147/RMHP.S280954
    Background and Purpose: Workplace bullying has been regarded as a serious phenomenon, particularly in health-care settings, due to its tendency to predispose health workers to serious psychological repercussions, job dissatisfaction, and turnover. Such consequences are costly to health systems and disruptive to the continuity of patient care. While global bullying literature in health settings grows, evidence on the magnitude of the problem from a Malaysian perspective is scarce. This study aimed to determine the prevalence of workplace bullying and its associated factors among health workers in a Malaysian public university hospital.

    Methods: This cross-sectional study was conducted from October to December 2019 among 178 hospital workers at the Hospital Canselor Tuanku Muhriz in Kuala Lumpur, Malaysia. The study utilized a self-administered questionnaire that consisted of items on sociodemographics, work characteristics, sources of bullying, and the validated Malay version of the 23-item Negative Acts Questionnaire - revised to determine the prevalence of bullying. Descriptive and inferential statistics were analyzed using SPSS 22.0. Statistical significance was set at P<0.05.

    Results: The prevalence of workplace bullying in this sample was 11.2%. Superiors or supervisors from other departments and colleagues were the main perpetrators. In the multivariate model, working for 10 years or less (aOR 4, 95% CI 1.3-12.3; P=0.014) and not being involved in patient care (aOR 5, 95% CI 2.5-10; P<0.001) were statistically significant attributes associated with workplace bullying.

    Conclusion: Workplace bullying in the current study was strongly associated with occupational characteristics, particularly length of service and service orientation of the workers. Hospital directors and managers could undertake preventive measures to identify groups vulnerable to bullying and subsequently craft appropriate coping strategies and mentoring programs to curb bullying.

    Matched MeSH terms: Biometry
  3. Machine learning improves early prediction of small-for-gestational-age births and reveals nuchal fold thickness as unexpected predictor
    Saw SN, Biswas A, Mattar CNZ, Lee HK, Yap CH
    Prenat Diagn, 2021 Mar;41(4):505-516.
    PMID: 33462877 DOI: 10.1002/pd.5903
    OBJECTIVE: To investigate the performance of the machine learning (ML) model in predicting small-for-gestational-age (SGA) at birth, using second-trimester data.

    METHODS: Retrospective data of 347 patients, consisting of maternal demographics and ultrasound parameters collected between the 20th and 25th gestational weeks, were studied. ML models were applied to different combinations of the parameters to predict SGA and severe SGA at birth (defined as 10th and third centile birth weight).

    RESULTS: Using second-trimester measurements, ML models achieved an accuracy of 70% and 73% in predicting SGA and severe SGA whereas clinical guidelines had accuracies of 64% and 48%. Uterine PI (Ut PI) was found to be an important predictor, corroborating with existing literature, but surprisingly, so was nuchal fold thickness (NF). Logistic regression showed that Ut PI and NF were significant predictors and statistical comparisons showed that these parameters were significantly different in disease. Further, including NF was found to improve ML model performance, and vice versa.

    CONCLUSION: ML could potentially improve the prediction of SGA at birth from second-trimester measurements, and demonstrated reduced NF to be an important predictor. Early prediction of SGA allows closer clinical monitoring, which provides an opportunity to discover any underlying diseases associated with SGA.

    Matched MeSH terms: Biometry
  4. Fulltext Determinants of posterior corneal biometric measurements in a multi-ethnic Asian population
    Ang M, Chong W, Huang H, Wong TY, He MG, Aung T, et al.
    PLoS One, 2014;9(7):e101483.
    PMID: 25006679 DOI: 10.1371/journal.pone.0101483
    To describe the corneal and anterior segment determinants of posterior corneal arc length (PCAL) and posterior corneal curvature (PCC).
    Matched MeSH terms: Biometry
  5. Fulltext Vicarious traumatization in healthcare providers in response to COVID-19 pandemic in Kelantan, Malaysia
    Norhayati MN, Che Yusof R, Azman MY
    PLoS One, 2021;16(6):e0252603.
    PMID: 34086747 DOI: 10.1371/journal.pone.0252603
    BACKGROUND: In the fight against the COVID-19 pandemic, frontline healthcare providers who are engaged in the direct diagnosis, treatment, and care of patients face a high risk of infection yet receive inadequate protection from contamination and minimal support to cope with overwork, frustration, and exhaustion. These problems have created significant psychological and mental health concerns for frontline healthcare providers. This study aimed to compare the levels of vicarious traumatization between frontline and non-frontline healthcare providers in response to the COVID-19 pandemic.

    METHODOLOGY: All the subjects who met the inclusion criteria were recruited for this comparative cross-sectional study, which was conducted from May to July 2020 in two hospitals in Kelantan, Malaysia. A self-administered questionnaire, namely, the Malay-version Vicarious Traumatization Questionnaire and the Medical Outcome Study Social Support Survey were utilized. A descriptive analysis, independent t-test, and analysis of covariance were performed using SPSS Statistics version 26.

    RESULTS: A total of 160 frontline and 146 non-frontline healthcare providers were recruited. Vicarious traumatization was significantly higher among the non-frontline healthcare providers (estimated marginal mean [95% CI]: 79.7 [75.12, 84.30]) compared to the frontline healthcare providers (estimated marginal mean [95% CI]: 74.3 [68.26, 80.37]) after adjusting for sex, duration of employment, and social support.

    CONCLUSION: The level of vicarious traumatization was higher among non-frontline compared to frontline healthcare providers. However, the level of severity may differ from person to person, depending on how they handle their physical, psychological, and mental health. Hence, support from various resources, such as colleagues, family, the general public, and the government, may play an essential role in the mental health of healthcare providers.

    Matched MeSH terms: Biometry
  6. Fulltext Classification of Partial Discharge Measured under Different Levels of Noise Contamination
    Jee Keen Raymond W, Illias HA, Abu Bakar AH
    PLoS One, 2017;12(1):e0170111.
    PMID: 28085953 DOI: 10.1371/journal.pone.0170111
    Cable joint insulation breakdown may cause a huge loss to power companies. Therefore, it is vital to diagnose the insulation quality to detect early signs of insulation failure. It is well known that there is a correlation between Partial discharge (PD) and the insulation quality. Although many works have been done on PD pattern recognition, it is usually performed in a noise free environment. Also, works on PD pattern recognition in actual cable joint are less likely to be found in literature. Therefore, in this work, classifications of actual cable joint defect types from partial discharge data contaminated by noise were performed. Five cross-linked polyethylene (XLPE) cable joints with artificially created defects were prepared based on the defects commonly encountered on site. Three different types of input feature were extracted from the PD pattern under artificially created noisy environment. These include statistical features, fractal features and principal component analysis (PCA) features. These input features were used to train the classifiers to classify each PD defect types. Classifications were performed using three different artificial intelligence classifiers, which include Artificial Neural Networks (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS) and Support Vector Machine (SVM). It was found that the classification accuracy decreases with higher noise level but PCA features used in SVM and ANN showed the strongest tolerance against noise contamination.
    Matched MeSH terms: Biometry
  7. Fulltext How many roads must a Malaysian walk down? Mapping the accessibility of radiotherapy facilities in Malaysia
    Yahya N, Sukiman NK, Suhaimi NA, Azmi NA, Manan HA
    PLoS One, 2019;14(3):e0213583.
    PMID: 30897166 DOI: 10.1371/journal.pone.0213583
    BACKGROUND: The accessibility to radiotherapy facilities may affect the willingness to undergo treatment. We sought to quantify the distance and travel time of Malaysian population to the closest radiotherapy centre and to estimate the megavoltage unit (MV)/million population based on the regions.

    MATERIALS & METHODS: Data for subdistricts in Malaysia and radiotherapy services were extracted from Department of Statistics Malaysia and Directory of Radiotherapy Centres (DIRAC). Data from DIRAC were validated by direct communication with centres. Locations of radiotherapy centres, distance and travel time to the nearest radiotherapy were estimated using web mapping service, Google Map.

    RESULTS: The average distance and travel time from Malaysian population to the closest radiotherapy centre were 82.5km and 83.4mins, respectively. The average distance and travel were not homogenous; East Malaysia (228.1km, 236.1mins), Central (14.4km, 20.1mins), East Coast (124.2km, 108.8mins), Northern (42.9km, 42.8mins) and Southern (36.0km, 39.8mins). The MV/million population for the country is 2.47, East Malaysia (1.76), Central (4.19), East Coast (0.54), Northern (2.40), Southern (2.36). About 25% of the population needs to travel >100 km to get to the closest radiotherapy facility.

    CONCLUSION: On average, Malaysians need to travel far and long to reach radiotherapy facilities. The accessibility to radiotherapy facilities is not equitable. The disparity may be reduced by adding centres in East Malaysia and the East Coast.

    Matched MeSH terms: Biometry
  8. Fulltext Correlation of the anterior ocular segment biometry with HbA1c level in type 2 diabetes mellitus patients
    Suraida AR, Ibrahim M, Zunaina E
    PLoS One, 2018;13(1):e0191134.
    PMID: 29324896 DOI: 10.1371/journal.pone.0191134
    OBJECTIVES: To compare the anterior ocular segment biometry among Type 2 diabetes mellitus (DM) with no diabetic retinopathy (DR) and non-proliferative diabetic retinopathy (NPDR), and to evaluate the correlation of anterior ocular segment biometry with HbA1c level.

    METHODS: A cross-sectional study was conducted in Hospital Universiti Sains Malaysia, Kelantan from November 2013 till May 2016 among Type 2 DM patients (DM with no DR and DM with NPDR). The patients were evaluated for anterior ocular segment biometry [central corneal thickness (CCT), anterior chamber width (ACW), angle opening distance (AOD) and anterior chamber angle (ACA)] by using Anterior Segment Optical Coherence Tomography (AS-OCT). Three ml venous blood was taken for the measurement of HbA1c.

    RESULTS: A total of 150 patients were included in this study (DM with no DR: 50 patients, DM with NPDR: 50 patients, non DM: 50 patients as a control group). The mean CCT and ACW showed significant difference among the three groups (p < 0.001 and p = 0.015 respectively). Based on post hoc result, there were significant mean difference of CCT between non DM and DM with NPDR (mean difference 36.14 μm, p < 0.001) and also between non DM and DM with no DR (mean difference 31.48 μm, p = 0.003). The ACW was significantly narrower in DM with NPDR (11.39 mm SD 0.62) compared to DM with no DR (11.76 mm SD 0.53) (p = 0.012). There were no significant correlation between HbA1c and all the anterior ocular segment biometry.

    CONCLUSION: Diabetic patients have significantly thicker CCT regardless of retinopathy status whereas ACW was significantly narrower in DM with NPDR group compared to DM with no DR. There was no significant correlations between HbA1c and all anterior ocular segment biometry in diabetic patients regardless of DR status.

    Matched MeSH terms: Biometry/methods*
  9. Fulltext A new Multi Sine-Cosine algorithm for unconstrained optimization problems
    Rehman MZ, Khan A, Ghazali R, Aamir M, Nawi NM
    PLoS One, 2021;16(8):e0255269.
    PMID: 34358237 DOI: 10.1371/journal.pone.0255269
    The Sine-Cosine algorithm (SCA) is a population-based metaheuristic algorithm utilizing sine and cosine functions to perform search. To enable the search process, SCA incorporates several search parameters. But sometimes, these parameters make the search in SCA vulnerable to local minima/maxima. To overcome this problem, a new Multi Sine-Cosine algorithm (MSCA) is proposed in this paper. MSCA utilizes multiple swarm clusters to diversify & intensify the search in-order to avoid the local minima/maxima problem. Secondly, during update MSCA also checks for better search clusters that offer convergence to global minima effectively. To assess its performance, we tested the MSCA on unimodal, multimodal and composite benchmark functions taken from the literature. Experimental results reveal that the MSCA is statistically superior with regards to convergence as compared to recent state-of-the-art metaheuristic algorithms, including the original SCA.
    Matched MeSH terms: Biometry*
  10. Fulltext Low complexity smart grid security protocol based on elliptic curve cryptography, biometrics and hamming distance
    Mutlaq KA, Nyangaresi VO, Omar MA, Abduljabbar ZA, Abduljaleel IQ, Ma J, et al.
    PLoS One, 2024;19(1):e0296781.
    PMID: 38261555 DOI: 10.1371/journal.pone.0296781
    The incorporation of information and communication technologies in the power grids has greatly enhanced efficiency in the management of demand-responses. In addition, smart grids have seen considerable minimization in energy consumption and enhancement in power supply quality. However, the transmission of control and consumption information over open public communication channels renders the transmitted messages vulnerable to numerous security and privacy violations. Although many authentication and key agreement protocols have been developed to counter these issues, the achievement of ideal security and privacy levels at optimal performance still remains an uphill task. In this paper, we leverage on Hamming distance, elliptic curve cryptography, smart cards and biometrics to develop an authentication protocol. It is formally analyzed using the Burrows-Abadi-Needham (BAN) logic, which shows strong mutual authentication and session key negotiation. Its semantic security analysis demonstrates its robustness under all the assumptions of the Dolev-Yao (DY) and Canetti- Krawczyk (CK) threat models. From the performance perspective, it is shown to incur communication, storage and computation complexities compared with other related state of the art protocols.
    Matched MeSH terms: Biometry
  11. Fulltext Effects of Stochastic Facilitation in Healthy Subjects with Different Auditory Working Memory Capacity
    Othman, E. A., Mohamad, M., Abdul Manan, H., Yusoff, A. N.
    Physics and Technology in Medicine, 2020;1(2):27-31.
    MyJurnal
    This study investigated the effects of stochastic facilitation in healthy subjects with normal and low auditory working memory capacity (AWMC). Forty healthy volunteers were recruited in this study. They performed a backward recall task (BRT) in quiet and under four white noise intensity levels: 45, 50, 55, and 60 dB. Brain activations during the task were measured using functional magnetic resonance imaging (fMRI). The behavioral performance in both groups increased significantly in 50 and 55 dB white noise. The normal AWMC group (mean score = 48.70) demonstrated higher activation in the superior temporal gyrus and prefrontal cortex than the low AWMC group (mean score = 30.85). However, comparisons in the brain activation between groups for all noise levels were not statistically different. The results support previous findings that stochastic facilitation enhances cognitive performance in healthy individuals. The results also proposed that brain activity among healthy subjects is more or less similar, at least in the context of auditory working memory. These findings indicated that there were no differential effects of stochastic facilitation in healthy subjects with different AWMC.
    Matched MeSH terms: Biometry
  12. Observation of ϒ(2S)→γη_{b}(1S) Decay
    Fulsom BG, Pedlar TK, Adachi I, Aihara H, Al Said S, Asner DM, et al.
    Phys Rev Lett, 2018 Dec 07;121(23):232001.
    PMID: 30576207 DOI: 10.1103/PhysRevLett.121.232001
    We report the observation of ϒ(2S)→γη_{b}(1S) decay based on an analysis of the inclusive photon spectrum of 24.7  fb^{-1} of e^{+}e^{-} collisions at the ϒ(2S) center-of-mass energy collected with the Belle detector at the KEKB asymmetric-energy e^{+}e^{-} collider. We measure a branching fraction of B[ϒ(2S)→γη_{b}(1S)]=(6.1_{-0.7-0.6}^{+0.6+0.9})×10^{-4} and derive an η_{b}(1S) mass of 9394.8_{-3.1-2.7}^{+2.7+4.5}  MeV/c^{2}, where the uncertainties are statistical and systematic, respectively. The significance of our measurement is greater than 7 standard deviations, constituting the first observation of this decay mode.
    Matched MeSH terms: Biometry
  13. First Measurements of Absolute Branching Fractions of the Ξ_{c}^{0} Baryon at Belle
    Li YB, Shen CP, Yuan CZ, Adachi I, Aihara H, Al Said S, et al.
    Phys Rev Lett, 2019 Mar 01;122(8):082001.
    PMID: 30932568 DOI: 10.1103/PhysRevLett.122.082001
    We present the first measurements of absolute branching fractions of Ξ_{c}^{0} decays into Ξ^{-}π^{+}, ΛK^{-}π^{+}, and pK^{-}K^{-}π^{+} final states. The measurements are made using a dataset comprising (772±11)×10^{6} BB[over ¯] pairs collected at the ϒ(4S) resonance with the Belle detector at the KEKB e^{+}e^{-} collider. We first measure the absolute branching fraction for B^{-}→Λ[over ¯]_{c}^{-}Ξ_{c}^{0} using a missing-mass technique; the result is B(B^{-}→Λ[over ¯]_{c}^{-}Ξ_{c}^{0})=(9.51±2.10±0.88)×10^{-4}. We subsequently measure the product branching fractions B(B^{-}→Λ[over ¯]_{c}^{-}Ξ_{c}^{0})B(Ξ_{c}^{0}→Ξ^{-}π^{+}), B(B^{-}→Λ[over ¯]_{c}^{-}Ξ_{c}^{0})B(Ξ_{c}^{0}→ΛK^{-}π^{+}), and B(B^{-}→Λ[over ¯]_{c}^{-}Ξ_{c}^{0})B(Ξ_{c}^{0}→pK^{-}K^{-}π^{+}) with improved precision. Dividing these product branching fractions by the result for B^{-}→Λ[over ¯]_{c}^{-}Ξ_{c}^{0} yields the following branching fractions: B(Ξ_{c}^{0}→Ξ^{-}π^{+})=(1.80±0.50±0.14)%, B(Ξ_{c}^{0}→ΛK^{-}π^{+})=(1.17±0.37±0.09)%, and B(Ξ_{c}^{0}→pK^{-}K^{-}π^{+})=(0.58±0.23±0.05)%. For the above branching fractions, the first uncertainties are statistical and the second are systematic. Our result for B(Ξ_{c}^{0}→Ξ^{-}π^{+}) can be combined with Ξ_{c}^{0} branching fractions measured relative to Ξ_{c}^{0}→Ξ^{-}π^{+} to yield other absolute Ξ_{c}^{0} branching fractions.
    Matched MeSH terms: Biometry
  14. Observation of tt[over ¯]H Production
    Sirunyan AM, Tumasyan A, Adam W, Ambrogi F, Asilar E, Bergauer T, et al.
    Phys Rev Lett, 2018 Jun 08;120(23):231801.
    PMID: 29932697 DOI: 10.1103/PhysRevLett.120.231801
    The observation of Higgs boson production in association with a top quark-antiquark pair is reported, based on a combined analysis of proton-proton collision data at center-of-mass energies of sqrt[s]=7, 8, and 13 TeV, corresponding to integrated luminosities of up to 5.1, 19.7, and 35.9  fb^{-1}, respectively. The data were collected with the CMS detector at the CERN LHC. The results of statistically independent searches for Higgs bosons produced in conjunction with a top quark-antiquark pair and decaying to pairs of W bosons, Z bosons, photons, τ leptons, or bottom quark jets are combined to maximize sensitivity. An excess of events is observed, with a significance of 5.2 standard deviations, over the expectation from the background-only hypothesis. The corresponding expected significance from the standard model for a Higgs boson mass of 125.09 GeV is 4.2 standard deviations. The combined best fit signal strength normalized to the standard model prediction is 1.26_{-0.26}^{+0.31}.
    Matched MeSH terms: Biometry
  15. Fulltext Stochastic electromagnetic field propagation- measurement and modelling
    Gradoni G, Russer J, Baharuddin MH, Haider M, Russer P, Smartt C, et al.
    Philos Trans A Math Phys Eng Sci, 2018 Oct 29;376(2134).
    PMID: 30373944 DOI: 10.1098/rsta.2017.0455
    This paper reviews recent progress in the measurement and modelling of stochastic electromagnetic fields, focusing on propagation approaches based on Wigner functions and the method of moments technique. The respective propagation methods are exemplified by application to measurements of electromagnetic emissions from a stirred, cavity-backed aperture. We discuss early elements of statistical electromagnetics in Heaviside's papers, driven mainly by an analogy of electromagnetic wave propagation with heat transfer. These ideas include concepts of momentum and directionality in the realm of propagation through confined media with irregular boundaries. We then review and extend concepts using Wigner functions to propagate the statistical properties of electromagnetic fields. We discuss in particular how to include polarization in this formalism leading to a Wigner tensor formulation and a relation to an averaged Poynting vector.This article is part of the theme issue 'Celebrating 125 years of Oliver Heaviside's 'Electromagnetic Theory''.
    Matched MeSH terms: Biometry
  16. Fulltext Prevalence of Drug-Related Problems and Complementary and Alternative Medicine Use in Malaysia: A Systematic Review and Meta-Analysis of 37,249 Older Adults
    Chang CT, Ang JY, Islam MA, Chan HK, Cheah WK, Gan SH
    Pharmaceuticals (Basel), 2021 Feb 25;14(3).
    PMID: 33669084 DOI: 10.3390/ph14030187
    Drug-related problems (DRPs) in the elderly include polypharmacy, potentially inappropriate medications, nonadherence, and drug-related falls. In this systematic review and meta-analysis, the prevalence of DRPs and complementary and alternative medicine (CAM) use among the Malaysian elderly was estimated. PubMed, Scopus, Web of Science, and Google Scholar databases were searched to identify studies published since their inception up to 24 August 2020. A random-effects model was used to generate the pooled prevalence of DRPs along with its corresponding 95% confidence interval (CI). The heterogeneity of the results was estimated using the I2 statistics, and Cochran's Q test and sensitivity analyses were performed to confirm the robustness of the results. We identified 526 studies, 23 of which were included in the meta-analysis. (n = 29,342). The pooled prevalence of DRPs among Malaysian elderly was as follows: (1) polypharmacy: 49.5% [95% CI: 20.5-78.6], (2) potentially inappropriate medications: 28.9% [95% CI: 25.4-32.3], (3) nonadherence to medications: 60.6% [95% CI: 50.2-70.9], and (4) medication-related falls 39.3% [95% CI: 0.0-80.8]. Approximately one in two Malaysian elderly used CAM. The prevalence of polypharmacy and potentially inappropriate medications among the Malaysian elderly population was high, calling for measures and evidence-based guidelines to ensure the safe medication use.
    Matched MeSH terms: Biometry
  17. Fulltext Interval estimation for parameters of a bivariate time varying covariate model
    Arasan, Jayanthi
    Pertanika Journal of Science & Technology, 2009;17(2):-.
    MyJurnal
    This paper investigates several asymptotic confidence interval estimates, based on the Wald, likelihood ratio and the score statistics for the parameters of a parallel two-component system model, with dependent failure and a time varying covariate, when data is censored. This model is an extension of the bivariate exponential model. The procedures are investigated via a coverage probability study using the simulated data. The results clearly indicate that the interval estimates, based on the likelihood ratio method, work better than any of the other two methods when dealing with the censored data.
    Matched MeSH terms: Biometry
  18. Fulltext Hypothesis tests of Goodness-of-Fit for Fréchet distribution
    Abidin, N. Z., Adam, M. B., Midi, H.
    Pertanika Journal of Science & Technology, 2014;22(2):419-432.
    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
  19. Fulltext GPU implementation of Sub-Iris technique in Iris recognition system
    Shahrizan Jamaludin, Nasharuddin Zainal, W. Mimi Diyana W. Zaki
    Pertanika Journal of Science & Technology, 2017;25(103):263-274.
    MyJurnal
    Iris recognition has become a widely popular biometric system. The stable textures and features of the human iris have made such biometric systems efficient and accurate for purposes of verification and identification. The term non-ideal iris refers to a situation in which the iris is occluded by noise, including reflections, eyelashes, eyelids and so on. Most current iris recognition algorithms assume that the iris is not occluded, which is less accurate. A method using only some parts of the iris may be suitable to deal with a non-ideal iris. The current application of iris recognition systems are plagued by weaknesses such as slow processing times, especially when dealing with many irises. In this study, a sub-iris recognition technique is proposed to deal with the non-ideal iris, while reducing execution time via an embedded system using a graphical processing unit (GPU). The experiment revealed that the proposed method was accurate and fast.
    Matched MeSH terms: Biometry
  20. Fulltext FNG-IE: an improved graph-based method for keyword extraction from scholarly big-data
    Tahir N, Asif M, Ahmad S, Malik MSA, Aljuaid H, Butt MA, et al.
    PeerJ Comput Sci, 2021;7:e389.
    PMID: 33817035 DOI: 10.7717/peerj-cs.389
    Keyword extraction is essential in determining influenced keywords from huge documents as the research repositories are becoming massive in volume day by day. The research community is drowning in data and starving for information. The keywords are the words that describe the theme of the whole document in a precise way by consisting of just a few words. Furthermore, many state-of-the-art approaches are available for keyword extraction from a huge collection of documents and are classified into three types, the statistical approaches, machine learning, and graph-based methods. The machine learning approaches require a large training dataset that needs to be developed manually by domain experts, which sometimes is difficult to produce while determining influenced keywords. However, this research focused on enhancing state-of-the-art graph-based methods to extract keywords when the training dataset is unavailable. This research first converted the handcrafted dataset, collected from impact factor journals into n-grams combinations, ranging from unigram to pentagram and also enhanced traditional graph-based approaches. The experiment was conducted on a handcrafted dataset, and all methods were applied on it. Domain experts performed the user study to evaluate the results. The results were observed from every method and were evaluated with the user study using precision, recall and f-measure as evaluation matrices. The results showed that the proposed method (FNG-IE) performed well and scored near the machine learning approaches score.
    Matched MeSH terms: Biometry
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