Displaying publications 1 - 20 of 310 in total

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  1. Abdul-Rahman H, Berawi MA
    Qual Assur, 2001;9(1):5-30.
    PMID: 12465710
    Knowledge Management (KM) addresses the critical issues of organizational adoption, survival and competence in the face of an increasingly changing environment. KM embodies organizational processes that seek a synergistic combination of the data and information processing capabilities of information and communication technologies (ICT), and the creative and innovative capacity of human beings to improve ICT In that role, knowledge management will improve quality management and avoid or minimize losses and weakness that usually come from poor performance as well as increase the competitive level of the company and its ability to survive in the global marketplace. To achieve quality, all parties including the clients, company consultants, contractors, entrepreneurs, suppliers, and the governing bodies (i.e., all involved stake-holders) need to collaborate and commit to achieving quality. The design based organizations in major business and construction companies have to be quality driven to support healthy growth in today's competitive market. In the march towards vision 2020 and globalization (i.e., the one world community) of many companies, their design based organizations need to have superior quality management and knowledge management to anticipate changes. The implementation of a quality system such as the ISO 9000 Standards, Total Quality Management, or Quality Function Deployment (QFD) focuses the company's resources towards achieving faster and better results in the global market with less cost. To anticipate the needs of the marketplace and clients as the world and technology change, a new system, which we call Power Quality System (PQS), has been designed. PQS is a combination of information and communication technologies (ICT) and the creative and innovative capacity of human beings to meet the challenges of the new world business and to develop high quality products.
    Publication year= 2001 Jan-2002 Mar
    Matched MeSH terms: Models, Statistical
  2. Endarti D, Riewpaiboon A, Thavorncharoensap M, Praditsitthikorn N, Hutubessy R, Kristina SA
    Value Health Reg Issues, 2018 May;15:50-55.
    PMID: 29474178 DOI: 10.1016/j.vhri.2017.07.008
    OBJECTIVES: To gain insight into the most suitable foreign value set among Malaysian, Singaporean, Thai, and UK value sets for calculating the EuroQol five-dimensional questionnaire index score (utility) among patients with cervical cancer in Indonesia.

    METHODS: Data from 87 patients with cervical cancer recruited from a referral hospital in Yogyakarta province, Indonesia, from an earlier study of health-related quality of life were used in this study. The differences among the utility scores derived from the four value sets were determined using the Friedman test. Performance of the psychometric properties of the four value sets versus visual analogue scale (VAS) was assessed. Intraclass correlation coefficients and Bland-Altman plots were used to test the agreement among the utility scores. Spearman ρ correlation coefficients were used to assess convergent validity between utility scores and patients' sociodemographic and clinical characteristics. With respect to known-group validity, the Kruskal-Wallis test was used to examine the differences in utility according to the stages of cancer.

    RESULTS: There was significant difference among utility scores derived from the four value sets, among which the Malaysian value set yielded higher utility than the other three value sets. Utility obtained from the Malaysian value set had more agreements with VAS than the other value sets versus VAS (intraclass correlation coefficients and Bland-Altman plot tests results). As for the validity, the four value sets showed equivalent psychometric properties as those that resulted from convergent and known-group validity tests.

    CONCLUSIONS: In the absence of an Indonesian value set, the Malaysian value set was more preferable to be used compared with the other value sets. Further studies on the development of an Indonesian value set need to be conducted.

    Matched MeSH terms: Models, Statistical
  3. Kamarudin ND, Ooi CY, Kawanabe T, Odaguchi H, Kobayashi F
    J Healthc Eng, 2017;2017:7460168.
    PMID: 29065640 DOI: 10.1155/2017/7460168
    In tongue diagnosis, colour information of tongue body has kept valuable information regarding the state of disease and its correlation with the internal organs. Qualitatively, practitioners may have difficulty in their judgement due to the instable lighting condition and naked eye's ability to capture the exact colour distribution on the tongue especially the tongue with multicolour substance. To overcome this ambiguity, this paper presents a two-stage tongue's multicolour classification based on a support vector machine (SVM) whose support vectors are reduced by our proposed k-means clustering identifiers and red colour range for precise tongue colour diagnosis. In the first stage, k-means clustering is used to cluster a tongue image into four clusters of image background (black), deep red region, red/light red region, and transitional region. In the second-stage classification, red/light red tongue images are further classified into red tongue or light red tongue based on the red colour range derived in our work. Overall, true rate classification accuracy of the proposed two-stage classification to diagnose red, light red, and deep red tongue colours is 94%. The number of support vectors in SVM is improved by 41.2%, and the execution time for one image is recorded as 48 seconds.
    Matched MeSH terms: Models, Statistical
  4. Jilnai MT, Wen WP, Cheong LY, ur Rehman MZ
    Sensors (Basel), 2016;16(1).
    PMID: 26805828 DOI: 10.3390/s16010052
    The assessment of moisture loss from meat during the aging period is a critical issue for the meat industry. In this article, a non-invasive microwave ring-resonator sensor is presented to evaluate the moisture content, or more precisely water holding capacity (WHC) of broiler meat over a four-week period. The developed sensor has shown significant changes in its resonance frequency and return loss due to reduction in WHC in the studied duration. The obtained results are also confirmed by physical measurements. Further, these results are evaluated using the Fricke model, which provides a good fit for electric circuit components in biological tissue. Significant changes were observed in membrane integrity, where the corresponding capacitance decreases 30% in the early aging (0D-7D) period. Similarly, the losses associated with intracellular and extracellular fluids exhibit changed up to 42% and 53%, respectively. Ultimately, empirical polynomial models are developed to predict the electrical component values for a better understanding of aging effects. The measured and calculated values are found to be in good agreement.
    Matched MeSH terms: Models, Statistical
  5. Jairoun AA, Al-Hemyari SS, Shahwan M, El-Dahiyat F, Jairoun M, Al-Tamimi SK, et al.
    Risk Manag Healthc Policy, 2021;14:967-977.
    PMID: 33727873 DOI: 10.2147/RMHP.S283068
    Background: The flux of pharmaceutical data can have a negative impact on the complexity of a pharmacist's decision-making process, which will demand an extensive evaluation from healthcare providers trying to choose the most suitable therapeutic plans for their patients.

    Objective: The current study aimed to assess the beliefs and implementations of community pharmacists in the UAE regarding evidence-based practice (EBP) and to explore the significant factors governing their EBP.

    Setting: Community pharmacies in Dubai and the Northern Emirates, UAE.

    Methods: A descriptive cross-sectional study was conducted over six months between December 2017 and June 2018. Community pharmacists who had three months' professional experience or more and were registered with one of three regulatory bodies (Ministry of Health, Health Authority Abu Dhabi, or Dubai Health Authority) were interviewed by three trained final-year pharmacy students. Face-to-face interviews were then carried out and a structured questionnaire was used.

    Metrics: The average beliefs score was 36% (95% CI: [34%, 39%]) compared to an implementation score of 35% (95% CI: [33%, 37%]).

    Results: A total of 505 subjects participated in the study and completed the entire questionnaire. On average, participants scored higher in beliefs score than implementation score. The results of the statistical modelling showed that younger, female, higher-position pharmacists with more experience and with low percentages of full-time working, and graduates from international/regional universities were more likely to believe in and implement the concept of EBP.

    Conclusion: A gap was identified between the beliefs and implementation of EBP. Developing educational EBP courses in undergraduate pharmacy curricula is of high importance, not only to increase knowledge levels but also to encourage commitment in those pharmacists to strive for professionalism and to support the provided patient care with evidence.

    Matched MeSH terms: Models, Statistical
  6. Yazdani S, Yusof R, Karimian A, Riazi AH, Bennamoun M
    Comput Math Methods Med, 2015;2015:829893.
    PMID: 26089978 DOI: 10.1155/2015/829893
    Brain MRI segmentation is an important issue for discovering the brain structure and diagnosis of subtle anatomical changes in different brain diseases. However, due to several artifacts brain tissue segmentation remains a challenging task. The aim of this paper is to improve the automatic segmentation of brain into gray matter, white matter, and cerebrospinal fluid in magnetic resonance images (MRI). We proposed an automatic hybrid image segmentation method that integrates the modified statistical expectation-maximization (EM) method and the spatial information combined with support vector machine (SVM). The combined method has more accurate results than what can be achieved with its individual techniques that is demonstrated through experiments on both real data and simulated images. Experiments are carried out on both synthetic and real MRI. The results of proposed technique are evaluated against manual segmentation results and other methods based on real T1-weighted scans from Internet Brain Segmentation Repository (IBSR) and simulated images from BrainWeb. The Kappa index is calculated to assess the performance of the proposed framework relative to the ground truth and expert segmentations. The results demonstrate that the proposed combined method has satisfactory results on both simulated MRI and real brain datasets.
    Matched MeSH terms: Models, Statistical
  7. Wang M, Han L, Liu S, Zhao X, Yang J, Loh SK, et al.
    Biotechnol J, 2015 Sep;10(9):1424-33.
    PMID: 26121186 DOI: 10.1002/biot.201400723
    Renewable energy from lignocellulosic biomass has been deemed an alternative to depleting fossil fuels. In order to improve this technology, we aim to develop robust mathematical models for the enzymatic lignocellulose degradation process. By analyzing 96 groups of previously published and newly obtained lignocellulose saccharification results and fitting them to Weibull distribution, we discovered Weibull statistics can accurately predict lignocellulose saccharification data, regardless of the type of substrates, enzymes and saccharification conditions. A mathematical model for enzymatic lignocellulose degradation was subsequently constructed based on Weibull statistics. Further analysis of the mathematical structure of the model and experimental saccharification data showed the significance of the two parameters in this model. In particular, the λ value, defined the characteristic time, represents the overall performance of the saccharification system. This suggestion was further supported by statistical analysis of experimental saccharification data and analysis of the glucose production levels when λ and n values change. In conclusion, the constructed Weibull statistics-based model can accurately predict lignocellulose hydrolysis behavior and we can use the λ parameter to assess the overall performance of enzymatic lignocellulose degradation. Advantages and potential applications of the model and the λ value in saccharification performance assessment were discussed.
    Matched MeSH terms: Models, Statistical*
  8. Pek CK, Jamal O
    J Environ Manage, 2011 Nov;92(11):2993-3001.
    PMID: 21820795 DOI: 10.1016/j.jenvman.2011.07.013
    In Malaysia, most municipal wastes currently are disposed into poorly managed 'controlled tipping' systems with little or no pollution protection measures. This study was undertaken to assist the relevant governmental bodies and service providers to identify an improved waste disposal management strategy. The study applied the choice experiment technique to estimate the nonmarket values for a number of waste disposal technologies. Implicit prices for environmental attributes such as psychological fear, land use, air pollution, and river water quality were estimated. Compensating surplus estimates incorporating distance from the residences of the respondents to the proposed disposal facility were calculated for a number of generic and technology-specific choice sets. The resulting estimates were higher for technology-specific options, and the distance factor was a significant determinant in setting an equitable solid waste management fee.
    Matched MeSH terms: Models, Statistical*
  9. Hosseinpour M, Pour MH, Prasetijo J, Yahaya AS, Ghadiri SM
    Traffic Inj Prev, 2013;14(6):630-8.
    PMID: 23859313 DOI: 10.1080/15389588.2012.736649
    The objective of this study was to examine the effects of various roadway characteristics on the incidence of pedestrian-vehicle crashes by developing a set of crash prediction models on 543 km of Malaysia federal roads over a 4-year time span between 2007 and 2010.
    Matched MeSH terms: Models, Statistical*
  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: Models, Statistical*
  11. Abdul Ghapor Hussin, Norli Anida Abdullah, Ibrahim Mohamed
    This paper gives a comprehensive discussion on complex regression model by extending the idea of regression model to circular variables. Various aspect have been considered such as the biasness of parameters, error assumptions and model checking. The advantage of this approach is that it allows the use of usual technique available in ordinary linear regression for the regression of circular variables. The quality of the estimates and the feasibility of the approach were illustrated via simulation. The model was then applied to the wave direction data.
    Matched MeSH terms: Models, Statistical
  12. Khalid R, Nawawi MK, Kawsar LA, Ghani NA, Kamil AA, Mustafa A
    PLoS One, 2013;8(4):e58402.
    PMID: 23560037 DOI: 10.1371/journal.pone.0058402
    M/G/C/C state dependent queuing networks consider service rates as a function of the number of residing entities (e.g., pedestrians, vehicles, and products). However, modeling such dynamic rates is not supported in modern Discrete Simulation System (DES) software. We designed an approach to cater this limitation and used it to construct the M/G/C/C state-dependent queuing model in Arena software. Using the model, we have evaluated and analyzed the impacts of various arrival rates to the throughput, the blocking probability, the expected service time and the expected number of entities in a complex network topology. Results indicated that there is a range of arrival rates for each network where the simulation results fluctuate drastically across replications and this causes the simulation results and analytical results exhibit discrepancies. Detail results that show how tally the simulation results and the analytical results in both abstract and graphical forms and some scientific justifications for these have been documented and discussed.
    Matched MeSH terms: Models, Statistical*
  13. Cheah YN, Chong YH, Neoh SL
    Stud Health Technol Inform, 2006;124:575-80.
    PMID: 17108579
    The mobilisation of cohesive and effective groups of healthcare human resource is important in ensuring the success of healthcare organisations. However, forming the right team or coalition in healthcare organisations is not always straightforward due to various human factors. Traditional coalition formation approaches have been perceived as 'materialistic' or focusing too much on competency or pay-off. Therefore, to put prominence on the human aspects of working together, we present a cohesiveness-focused healthcare coalition formation methodology and framework that explores the possibilities of social networks, i.e. the relationship between various healthcare human resources, and adaptive resonance theory.
    Matched MeSH terms: Models, Statistical
  14. Zare H, Tavana M, Mardani A, Masoudian S, Kamali Saraji M
    Health Care Manag Sci, 2019 Sep;22(3):475-488.
    PMID: 30225622 DOI: 10.1007/s10729-018-9456-4
    Performance measurement plays an important role in the successful design and reform of regional healthcare management systems. In this study, we propose a hybrid data envelopment analysis (DEA) and game theory model for measuring the performance and productivity in the healthcare centers. The input and output variables associated with the efficiency of the healthcare centers are identified by reviewing the relevant literature, and then used in conjunction with the internal organizational data. The selected indicators and collected data are then weighted and prioritized with the help of experts in the field. A case study is presented to demonstrate the applicability and efficacy of the proposed model. The results reveal useful information and insights on the efficiency levels of the regional healthcare centers in the case study.
    Matched MeSH terms: Models, Statistical*
  15. Tavana M, Khosrojerdi G, Mina H, Rahman A
    Eval Program Plann, 2019 12;77:101703.
    PMID: 31442587 DOI: 10.1016/j.evalprogplan.2019.101703
    The primary goal in project portfolio management is to select and manage the optimal set of projects that contribute the maximum in business value. However, selecting Information Technology (IT) projects is a difficult task due to the complexities and uncertainties inherent in the strategic-operational nature of the process, and the existence of both quantitative and qualitative criteria. We propose a two-stage process to select an optimal project portfolio with the aim of maximizing project benefits and minimizing project risks. We construct a two-stage hybrid mathematical programming model by integrating Fuzzy Analytic Hierarchy Process (FAHP) with Fuzzy Inference System (FIS). This hybrid framework provides the ability to consider both the quantitative and qualitative criteria while considering budget constraints and project risks. We also present a real-world case study in the cybersecurity industry to exhibit the applicability and demonstrate the efficacy of our proposed method.
    Matched MeSH terms: Models, Statistical*
  16. Smith JD
    J Math Biol, 2004 Jan;48(1):105-18.
    PMID: 14685774
    A canonical/lognormal model for human demography is established, specifying the net maternity function and the age distribution for mothers of new-borns using a single macroscopic parameter vector of dimension five. The age distribution of mothers is canonical, while the net maternity function normalizes to a lognormal density. Comparison of an actual population with the model serves to identify anomalies in the population which may be indicative of phase transitions or influences from levels outside the demographic. Tracking the time development of the parameter vector may be used to predict the future state of a population, or to interpolate for data missing from the record. In accordance with classical theoretical considerations of Backman, Prigogine, et al., it emerges that the logarithm of a mother's age is the most fundamental time variable for demographic purposes.
    Matched MeSH terms: Models, Statistical*
  17. Mohamad MS, Omatu S, Deris S, Yoshioka M
    IEEE Trans Inf Technol Biomed, 2011 Nov;15(6):813-22.
    PMID: 21914573 DOI: 10.1109/TITB.2011.2167756
    Gene expression data are expected to be of significant help in the development of efficient cancer diagnoses and classification platforms. In order to select a small subset of informative genes from the data for cancer classification, recently, many researchers are analyzing gene expression data using various computational intelligence methods. However, due to the small number of samples compared to the huge number of genes (high dimension), irrelevant genes, and noisy genes, many of the computational methods face difficulties to select the small subset. Thus, we propose an improved (modified) binary particle swarm optimization to select the small subset of informative genes that is relevant for the cancer classification. In this proposed method, we introduce particles' speed for giving the rate at which a particle changes its position, and we propose a rule for updating particle's positions. By performing experiments on ten different gene expression datasets, we have found that the performance of the proposed method is superior to other previous related works, including the conventional version of binary particle swarm optimization (BPSO) in terms of classification accuracy and the number of selected genes. The proposed method also produces lower running times compared to BPSO.
    Matched MeSH terms: Models, Statistical*
  18. Ibrahim RW, Hasan AM, Jalab HA
    Comput Methods Programs Biomed, 2018 Sep;163:21-28.
    PMID: 30119853 DOI: 10.1016/j.cmpb.2018.05.031
    BACKGROUND AND OBJECTIVES: The MRI brain tumors segmentation is challenging due to variations in terms of size, shape, location and features' intensity of the tumor. Active contour has been applied in MRI scan image segmentation due to its ability to produce regions with boundaries. The main difficulty that encounters the active contour segmentation is the boundary tracking which is controlled by minimization of energy function for segmentation. Hence, this study proposes a novel fractional Wright function (FWF) as a minimization of energy technique to improve the performance of active contour without edge method.

    METHOD: In this study, we implement FWF as an energy minimization function to replace the standard gradient-descent method as minimization function in Chan-Vese segmentation technique. The proposed FWF is used to find the boundaries of an object by controlling the inside and outside values of the contour. In this study, the objective evaluation is used to distinguish the differences between the processed segmented images and ground truth using a set of statistical parameters; true positive, true negative, false positive, and false negative.

    RESULTS: The FWF as a minimization of energy was successfully implemented on BRATS 2013 image dataset. The achieved overall average sensitivity score of the brain tumors segmentation was 94.8 ± 4.7%.

    CONCLUSIONS: The results demonstrate that the proposed FWF method minimized the energy function more than the gradient-decent method that was used in the original three-dimensional active contour without edge (3DACWE) method.

    Matched MeSH terms: Models, Statistical
  19. Du L, Pang Y
    Sci Rep, 2021 06 24;11(1):13275.
    PMID: 34168200 DOI: 10.1038/s41598-021-92484-6
    Influenza is an infectious disease that leads to an estimated 5 million cases of severe illness and 650,000 respiratory deaths worldwide each year. The early detection and prediction of influenza outbreaks are crucial for efficient resource planning to save patient's lives and healthcare costs. We propose a new data-driven methodology for influenza outbreak detection and prediction at very local levels. A doctor's diagnostic dataset of influenza-like illness from more than 3000 clinics in Malaysia is used in this study because these diagnostic data are reliable and can be captured promptly. A new region index (RI) of the influenza outbreak is proposed based on the diagnostic dataset. By analysing the anomalies in the weekly RI value, potential outbreaks are identified using statistical methods. An ensemble learning method is developed to predict potential influenza outbreaks. Cross-validation is conducted to optimize the hyperparameters of the ensemble model. A testing data set is used to provide an unbiased evaluation of the model. The proposed methodology is shown to be sensitive and accurate at influenza outbreak prediction, with average of 75% recall, 74% precision, and 83% accuracy scores across five regions in Malaysia. The results are also validated by Google Flu Trends data, news reports, and surveillance data released by World Health Organization.
    Matched MeSH terms: Models, Statistical
  20. Noman AE, Al-Barha NS, Sharaf AM, Al-Maqtari QA, Mohedein A, Mohammed HHH, et al.
    Sci Rep, 2020 08 11;10(1):13527.
    PMID: 32782276 DOI: 10.1038/s41598-020-70404-4
    A novel bacterial strain of acetic acid bacteria capable of producing riboflavin was isolated from the soil sample collected in Wuhan, China. The isolated strain was identified as Gluconobacter oxydans FBFS97 based on several phenotype characteristics, biochemicals tests, and 16S rRNA gene sequence conducted. Furthermore, the complete genome sequencing of the isolated strain has showed that it contains a complete operon for the biosynthesis of riboflavin. In order to obtain the maximum concentration of riboflavin production, Gluconobacter oxydans FBFS97 was optimized in shake flask cultures through response surface methodology employing Plackett-Burman design (PBD), and Central composite design (CCD). The results of the pre-experiments displayed that fructose and tryptone were found to be the most suitable sources of carbon and nitrogen for riboflavin production. Then, PBD was conducted for initial screening of eleven minerals (FeSO4, FeCl3, KH2PO4, K2HPO4, MgSO4, ZnSO4, NaCl, CaCl2, KCl, ZnCl2, and AlCl3.6H2O) for their significances on riboflavin production by Gluconobacter oxydans strain FBFS97. The most significant variables affecting on riboflavin production are K2HPO4 and CaCl2, the interaction affects and levels of these variables were optimized by CCD. After optimization of the medium compositions for riboflavin production were determined as follows: fructose 25 g/L, tryptone 12.5 g/L, K2HPO4 9 g/L, and CaCl2 0.06 g/L with maximum riboflavin production 23.24 mg/L.
    Matched MeSH terms: Models, Statistical*
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