Displaying publications 61 - 80 of 183 in total

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  1. 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
  2. Mohd. Yunus Shukor
    MyJurnal
    The growth of microorganism on substrates, whether toxic or not usually exhibits sigmoidal
    pattern. This sigmoidal growth pattern can be modelled using primary models such as Logistic,
    modified Gompertz, Richards, Schnute, Baranyi-Roberts, Von Bertalanffy, Buchanan threephase
    and Huang. Previously, the modified Gompertz model was chosen to model the growth of
    Burkholderia sp. strain Neni-11 on acrylamide, which shows a sigmoidal curve. The modified
    Gompertz model relies on the ordinary least squares method, which in turn relies heavily on
    several important assumptions, which include that the data does not show autocorrelation. In this
    work we perform statistical diagnosis test to test for the presence of autocorrelation using the
    Durbin-Watson test and found that the model was adequate and robust as no autocorrelation of
    the data was found.
    Matched MeSH terms: Biometry
  3. Mohmmed AO, Nasif MS, Al-Kayiem HH
    Data Brief, 2018 Feb;16:527-530.
    PMID: 29270452 DOI: 10.1016/j.dib.2017.11.026
    The data presented in this article were the basis for the study reported in the research articles entitled "Statistical assessment of experimental observation on the slug body length and slug translational velocity in a horizontal pipe" (Al-Kayiem et al., 2017) [1] which presents an experimental investigation of the slug velocity and slug body length for air-water tow phase flow in horizontal pipe. Here, in this article, the experimental set-up and the major instruments used for obtaining the computed data were explained in details. This data will be presented in the form of tables and videos.
    Matched MeSH terms: Biometry
  4. Naicker P, Sundralingam S, Peyman M, Juana A, Mohamad NF, Win MM, et al.
    Int Ophthalmol, 2015 Aug;35(4):459-66.
    PMID: 25024102 DOI: 10.1007/s10792-014-9970-4
    To determine the accuracy of intraocular lens (IOL) calculations in eyes undergoing phacoemulsification cataract surgery with IOL implantation using immersion A-scan ultrasound (US) and Lenstar LS 900(®) biometry. In this prospective study, 200 eyes of 200 patients were randomized to undergo either Lenstar LS 900(®) or immersion A-scan US biometry to determine the IOL dioptric power prior to phacoemulsification cataract surgery. Post-operative refractive outcomes of these two groups of patients were compared. The result showed no significant difference between the target spherical equivalent (SE) and the post-operative SE value by the Lenstar LS 900(®) (p value = 0.632) or immersion A-scan US biometry (p value = 0.438) devices. The magnitude of difference between the two biometric devices were not significantly different (p value = 0.868). There was no significant difference in the predicted post-operative refractive outcome between immersion A-scan US biometry and Lenstar LS 900(®). Based on the results, the immersion A-scan US technique is as accurate as Lenstar LS 900(®) in the hands of an experienced operator.
    Matched MeSH terms: Biometry/instrumentation; Biometry/methods*
  5. Harighi MF, Wahid H, Thomson PC, Rafii MY, Jesse FFA
    Anim. Reprod. Sci., 2019 Sep;208:106113.
    PMID: 31405472 DOI: 10.1016/j.anireprosci.2019.106113
    Testicular volume (TV) is one of the most important traits used in evaluation of the reproductive capacity of male animals. The levelled-container used in the present study was found to be reliable instrument to measure TV, based on a water displacement method. Sperm-associated antigen 11 (SPAG11) is an important gene that affects male reproductive performance. An objective of the present study, therefore, was to determine if single nucleotide polymorphisms (SNPs) in a fragment of the SPAG11 gene could be used to determine associations with values of testicular biometric variables in Boer goats. Primers were designed to amplify the full length of the first two exons of SPAG11. The targeted fragment was generated using a molecular cloning technique. As the result, four SNPs, [g.1256A > G(ss19199134542), g.1270C > T(ss19199134541), g.1325A > G(ss19199134540) and g.1327 G > A (ss19199134543)], were detected using a single-base extension (SBE) method. Two of these SNPs were synonymous (ss19199134540 and ss19199134542). The other two SNPs were nonsynonymous, thus, there were changes in amino acid in the resulting protein: threonine to isoleucine (for ss19199134541) and arginine to glutamine (for ss19199134543). The SNP ss19199134543 was the only locus detected that was associated with TV (P = 0.002). None of the testes dimensions nor TW were associated with detected SPAG11 gene SNPs. Most likely, the ss19199134543 locus affects tissue structures adjacent to the testes, causing the change in TV. In conclusion, among the studied testicular biometric variables, TV had the greatest potential for preselecting of bucks with desirable semen quality. The use of the levelled-container as a TV measurement approach was an accurate and reliable method.
    Matched MeSH terms: Biometry/instrumentation; Biometry/methods*
  6. Al-Dubai S, Ganasegeran K, Barua A, Rizal A, Rampal K
    Ann Med Health Sci Res, 2014 Jul;4(Suppl 2):S104-7.
    PMID: 25184074 DOI: 10.4103/2141-9248.138023
    BACKGROUND: The 10-item version of Perceived Stress Scale (PSS-10) is a widely used tool to measure stress. The Malay version of the PSS-10 has been validated among Malaysian Medical Students. However, studies have not been conducted to assess its validity in occupational settings.
    AIM: The aim of this study is to assess the psychometric properties of the Malay version of the PSS-10 in two occupational setting in Malaysia.
    SUBJECTS AND METHODS: This study was conducted among 191 medical residents and 513 railway workers. An exploratory factor analysis was performed using the principal component method with varimax rotation. Correlation analyses, Kaiser-Meyer-Olkin, Bartlett's test of Sphericity and Cronbach's alpha were obtained. Statistical analysis was carried out using statistical package for the social sciences version 16 (SPSS, Chicago, IL, USA) software.
    RESULTS: Analysis yielded two factor structure of the Malay version of PSS-10 in both occupational groups. The two factors accounted for 59.2% and 64.8% of the variance in the medical residents and the railway workers respectively. Factor loadings were greater than 0.59 in both occupational groups. Cronbach's alpha co-efficient was 0.70 for medical residents and 0.71 for railway workers.
    CONCLUSION: The Malay version of PSS-10 had adequate psychometric properties and can be used to measure stress among occupational settings in Malaysia.
    KEYWORDS: Factor structure; Malaysia; Occupational; Perceived stress scale; Psychometric properties; Validity
    Matched MeSH terms: Biometry
  7. Huda AS, Taib S, Ghazali KH, Jadin MS
    ISA Trans, 2014 May;53(3):717-24.
    PMID: 24593986 DOI: 10.1016/j.isatra.2014.02.003
    Infrared thermography technology is one of the most effective non-destructive testing techniques for predictive faults diagnosis of electrical components. Faults in electrical system show overheating of components which is a common indicator of poor connection, overloading, load imbalance or any defect. Thermographic inspection is employed for finding such heat related problems before eventual failure of the system. However, an automatic diagnostic system based on artificial neural network reduces operating time, human efforts and also increases the reliability of system. In the present study, statistical features and artificial neural network (ANN) with confidence level analysis are utilized for inspection of electrical components and their thermal conditions are classified into two classes namely normal and overheated. All the features extracted from images do not produce good performance. Features having low performance reduce the diagnostic performance. The study reveals the performance of each feature individually for selecting the suitable feature set. In order to find the individual feature performance, each feature of thermal image was used as input for neural network and the classification of condition types were used as output target. The multilayered perceptron network using Levenberg-Marquardt training algorithm was used as classifier. The performances were determined in terms of percentage of accuracy, specificity, sensitivity, false positive and false negative. After selecting the suitable features, the study introduces the intelligent diagnosis system using suitable features as inputs of neural network. Finally, confidence percentage and confidence level were used to find out the strength of the network outputs for condition monitoring. The experimental result shows that multilayered perceptron network produced 79.4% of testing accuracy with 43.60%, 12.60%, 21.40, 9.20% and 13.40% highest, high, moderate, low and lowest confidence level respectively.
    Matched MeSH terms: Biometry
  8. Goh PP, Azura R
    Med J Malaysia, 2012 Oct;67(5):497-502.
    PMID: 23770867 MyJurnal
    This is the first population based study on ocular biometric measurements (OBMs) conducted in Malaysia. Its objective is to measure and compare among children of different ethnicity who have myopia and emmetropia. Subsets of children aged between 7 and 8 years old who participated in a larger population based refractive error study had their axial length, anterior chamber depth, lens thickness and vitreous depth measured using A scan and vertical and horizontal corneal curvature measured using an autokeratorefractometer. Eighty eight of the 870 children (10.1%) examined had myopia. Boys, Chinese and children with myopia had significantly longer axial length and vitreous depth compared to girls, Malay and Indian and children who were emmetropic respectively. Girls and children with myopia had steeper corneal curvature. The baseline OBMs in Malaysian children of different ethnicity are valuable for studies in myopia progression. Like other studies, children with myopia have longer axial length (P <0.001). and vitreous depth (P <0.001) compared to children who are emmetropia (without myopia).
    Matched MeSH terms: Biometry
  9. Chan KW, Tan GH, Wong RC
    J Forensic Sci, 2013 Jan;58 Suppl 1:S199-207.
    PMID: 23013257 DOI: 10.1111/j.1556-4029.2012.02285.x
    Statistical validation is crucial for the clustering of unknown samples. This study aims to demonstrate how statistical techniques can be optimized using simulated heroin samples containing a range of analyte concentrations that are similar to those of the case samples. Eight simulated heroin distribution links consisting of 64 postcut samples were prepared by mixing one of two mixtures of paracetamol-caffeine-dextromethorphan at different proportions with eight precut samples. Analyte contents and compositional variation of the prepared samples were investigated. A number of data pretreatments were evaluated by associating the postcut samples with the corresponding precut samples using principal component analysis and discriminant analysis. Subsequently, combinations of seven linkage methods and five distance measures were explored using hierarchical cluster analysis. In this study, Ward-Manhattan showed better distinctions between unrelated links and was able to cluster all related samples in very close distance under the known links on a dendogram. A similar discriminative outcome was also achieved by 90 unknown case samples when clustered via Ward-Manhattan.
    Matched MeSH terms: Biometry
  10. Gunny AA, Arbain D, Jamal P, Gumba RE
    Saudi J Biol Sci, 2015 Jul;22(4):476-83.
    PMID: 26150755 DOI: 10.1016/j.sjbs.2014.11.021
    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.
    Matched MeSH terms: Biometry
  11. Nur Zania Azurin Abdullah Sani, Ahmad Shazeer Mohamed Thaheer, Zahariah Mohd Zain
    MyJurnal
    Internationalization procedure of small to medium-sized enterprises (SMEs) is part of the increasing economy. The study aims to identify relationships between the factors influencing the SMEs to internationalize and identifying the most impactful factor that affects the internationalization of SMEs. The factors affecting internationalization of SMEs identified were external, internal, networking as well as barriers and challenges. The study focusses on SMEs in the service sector in Klang Valley, Malaysia. The methods used to conduct the survey is by distributing the questionnaire through email. There are 100 selected SMEs in the service sector which are listed in SME Corp Malaysia website and MATRADE website. Regardless of whether the SME’s are practising international business or not, they will still be one of the potential respondents. The data were examined and obtained using the statistical software SPSS. The analysis used is reliability analysis, correlation analysis and regression analysis to meet the research objectives. The expected outcome from this research is to analyze the factors that will impact the internationalization of SMEs. The results of the analysis show that all the variables have a low positive correlation. The most influential factors that effects SMEs decision to go international are barriers and challenges.
    Matched MeSH terms: Biometry
  12. Othman WMN, Ithnin M, Wan Abdul Aziz WNA, Wan Ali WNS, Ramli H
    J Int Soc Prev Community Dent, 2021 01 30;11(1):33-40.
    PMID: 33688471 DOI: 10.4103/jispcd.JISPCD_336_20
    Aims: This study aimed at exploring the self-perception of Orang Asli (OA) from the Temuan tribe in Jelebu by using the Global Self-rated Oral Health (GSROH) and General Oral Health Assessment Index (GOHAI).

    Materials and Methods: It was a cross-sectional study involving a two-stage sampling to select the district and villages. A total of 325 participants were selected based on convenience sampling.

    Results: Almost half of the participants rated their oral health as poor or average. The mean GOHAI score was 52.96 (±7.749), ranging from 29 to 60. The GOHAI score was statistically significantly lower for female gender (P = 0.025), lower education level (P = 0.001), and elderly (P = 0.001). The GSROH score was also statistically significant with GOHAI score (P = 0.001).

    Conclusions: A limited number of studies were conducted in this area, particularly in the vulnerable population of OA. Our study found that half of the OA living in the fringe had a poor GOHAI score. It is, therefore, suggested that potential study and intervention programs concentrate on the low GOHAI score group; the male, lower educational context, and the elderly.

    Matched MeSH terms: Biometry
  13. Sing, Lui Lo, Chen, Cheng Ann, Tzuen, Kiat Yap, Teruaki Yoshida
    MyJurnal
    A comparison of zooplankton abundance and community in the seagrass and non-seagrass areas of Limau-limauan and Bak- Bak waters within the newly established Tun Mustapha Marine Park was made during 15-17 May 2017. Samples were collected via horizontal tow of a 140 μm plankton net. Environmental variables (temperature, salinity, DO, pH, turbidity) showed no significant differences among the study sites. However, zooplankton showed increasing abundance from non-seagrass, seagrass edge, to seagrass areas at Limau-limauan, while abundance values were comparable among the stations at Bak-bak. Overall zooplankton abundance was significantly higher at the seagrass areas relative to the non-seagrass station at Limau-limauan (p < 0.005), while no statistical difference was found at Bak-Bak (p < 0.21). Mean canopy height was 3-fold higher (p < 0.001) at Limau-limauan than Bak-Bak, suggesting the importance of seagrass bed structural complexity in habitat preference for zooplankton. Cluster analysis revealed the zooplankton community from the seagrass area at Limau-limauan was different from that at seagrass edge and non-seagrass areas, which may be attributed to the influence of seagrass meadows in forming characteristic zooplankton compositions. Marked differences in zooplankton composition and abundance even in close vicinity of sites suggest the importance of local small-scale variations in seagrass habitats in shaping the zooplankton community.
    Matched MeSH terms: Biometry
  14. Ahmad Zamri Khairani, Nor Shafrin Ahmad, Aziah Ismail, Rahimi Che Aman
    MyJurnal
    Introduction: This study examines the psychometric characteristics of a translated version of the Beck Depression Inventory II (BDI – II) among Malaysian school students. Methods: The sample consisted of 257 boys and 302 girls. This study employed WINSTEPS 3.74 to provide statistics and other information from Rasch Model analysis, namely, the fit statistics, dimensionality analysis, rating scale analysis, reliability and separation indices, differential item func- tioning analysis, and distribution of items difficulty and students’ ability. Results: Rating scale analysis showed that category 2 and category 3 of the ratings were not different. Meanwhile, Item 19 did not fit the model’s expectations; and thus, it was omitted from further analyses. The scale demonstrated a high person reliability and a high person separation index. There were no items demonstrating gender DIF. The school students endorsed feeling guilty as the least severe symptom of depression, while committing suicide as the most serious symptom. Conclusion: In general, the BDI-II demonstrated acceptable properties in measuring depression symptoms among school students.
    Matched MeSH terms: Biometry
  15. Hassan H, Jin B, Dai S
    Environ Technol, 2021 Apr 01.
    PMID: 33749543 DOI: 10.1080/09593330.2021.1907451
    The interactions within microbial, chemical and electronic elements in microbial fuel cell (MFC) system can be crucial for its bio-electrochemical activities and overall performance. Therefore, this study explored polynomial models by response surface methodology (RSM) to better understand interactions among anode pH, cathode pH and inoculum size for optimising MFC system for generation of electricity and degradation of 2,4-dichlorophenol. A statistical central composite design by RSM was used to develop the quadratic model designs. The optimised parameters were determined and evaluated by statistical results and the best MFC systematic outcomes in terms of current generation and chlorophenol degradation. Statistical results revealed that the optimum current density of 106 mA/m2 could be achieved at anode pH 7.5, cathode pH 6.3-6.6 and 21-28% for inoculum size. Anode-cathode pHs interaction was found to positively influence the current generation through extracellular electron transfer mechanism. The phenolic degradation was found to have lower response using these three parameter interactions. Only inoculum size-cathode pH interaction appeared to be significant where the optimum predicted phenolic degradation could be attained at pH 7.6 for cathode pH and 29.6% for inoculum size.
    Matched MeSH terms: Biometry
  16. 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
  17. Ahmad, Mani Malam, Abd. Aziz Mohd Azoddein, Jami, Mohammed Saed
    MyJurnal
    : Studies on bacterial growth pattern from the conventional approach are defective due
    to their failure to explain the interactions or simply the complementary effects of the factors
    influencing the bacterial growth. In this study, the individual and collaborative effects of
    Pseudomonas putida growth variables were evaluated using a 2-level fractional factorial design of
    experiment (FFDOE). The growth of the organism was found to respond remarkably to different
    concentrations of nutrient media (carbon source) and the other independent variables. Factorial
    models were developed from the experimental design to study the individual and interactive effects
    of the studied parameters on the response. The studied parameters and their levels were as follows:
    nutrient concentration (4-16 g/L), acclimatization time (24-72 hrs), agitation (140-200 rpm), and
    temperature (30-40oC). These parameters were statistically validated using analysis of variance
    (ANOVA) and the results revealed that the model terms were statistically significant with an Fvalue of 415.17 at P temperature > nutrient concentration versus temperature >
    agitation > nutrient concentration versus agitation. Based on the R
    2
    and the adjusted R
    2
    values of
    >95%, the estimated variables showed a high degree of relationship between the observed and the
    predicted values; thus, the predictive ability of the models was suggested. It could, therefore, be
    concluded that nutrient concentration, temperature, and agitation can greatly influence the growth
    of P. putida within a specific range.
    Matched MeSH terms: Biometry
  18. Nataraj SK, Paulraj MP, Yaacob SB, Adom AHB
    J Med Signals Sens, 2020 11 11;10(4):228-238.
    PMID: 33575195 DOI: 10.4103/jmss.JMSS_52_19
    Background: A simple data collection approach based on electroencephalogram (EEG) measurements has been proposed in this study to implement a brain-computer interface, i.e., thought-controlled wheelchair navigation system with communication assistance.

    Method: The EEG signals are recorded for seven simple tasks using the designed data acquisition procedure. These seven tasks are conceivably used to control wheelchair movement and interact with others using any odd-ball paradigm. The proposed system records EEG signals from 10 individuals at eight-channel locations, during which the individual executes seven different mental tasks. The acquired brainwave patterns have been processed to eliminate noise, including artifacts and powerline noise, and are then partitioned into six different frequency bands. The proposed cross-correlation procedure then employs the segmented frequency bands from each channel to extract features. The cross-correlation procedure was used to obtain the coefficients in the frequency domain from consecutive frame samples. Then, the statistical measures ("minimum," "mean," "maximum," and "standard deviation") were derived from the cross-correlated signals. Finally, the extracted feature sets were validated through online sequential-extreme learning machine algorithm.

    Results and Conclusion: The results of the classification networks were compared with each set of features, and the results indicated that μ (r) feature set based on cross-correlation signals had the best performance with a recognition rate of 91.93%.

    Matched MeSH terms: Biometry
  19. Othman, E. A., Mohamad, M., Abdul Manan, H., Yusoff, A. N.
    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
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