Displaying publications 81 - 100 of 735 in total

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  1. Magableh A, Shukur Z, Ali NM
    ScientificWorldJournal, 2014;2014:327808.
    PMID: 25136656 DOI: 10.1155/2014/327808
    Unified Modeling Language is the most popular and widely used Object-Oriented modelling language in the IT industry. This study focuses on investigating the ability to expand UML to some extent to model crosscutting concerns (Aspects) to support AspectJ. Through a comprehensive literature review, we identify and extensively examine all the available Aspect-Oriented UML modelling approaches and find that the existing Aspect-Oriented Design Modelling approaches using UML cannot be considered to provide a framework for a comprehensive Aspectual UML modelling approach and also that there is a lack of adequate Aspect-Oriented tool support. This study also proposes a set of Aspectual UML semantic rules and attempts to generate AspectJ pseudocode from UML diagrams. The proposed Aspectual UML modelling approach is formally evaluated using a focus group to test six hypotheses regarding performance; a "good design" criteria-based evaluation to assess the quality of the design; and an AspectJ-based evaluation as a reference measurement-based evaluation. The results of the focus group evaluation confirm all the hypotheses put forward regarding the proposed approach. The proposed approach provides a comprehensive set of Aspectual UML structural and behavioral diagrams, which are designed and implemented based on a comprehensive and detailed set of AspectJ programming constructs.
    Matched MeSH terms: Models, Theoretical
  2. Ong HC, Alih E
    PLoS One, 2015;10(4):e0125835.
    PMID: 25923739 DOI: 10.1371/journal.pone.0125835
    The tendency for experimental and industrial variables to include a certain proportion of outliers has become a rule rather than an exception. These clusters of outliers, if left undetected, have the capability to distort the mean and the covariance matrix of the Hotelling's T2 multivariate control charts constructed to monitor individual quality characteristics. The effect of this distortion is that the control chart constructed from it becomes unreliable as it exhibits masking and swamping, a phenomenon in which an out-of-control process is erroneously declared as an in-control process or an in-control process is erroneously declared as out-of-control process. To handle these problems, this article proposes a control chart that is based on cluster-regression adjustment for retrospective monitoring of individual quality characteristics in a multivariate setting. The performance of the proposed method is investigated through Monte Carlo simulation experiments and historical datasets. Results obtained indicate that the proposed method is an improvement over the state-of-art methods in terms of outlier detection as well as keeping masking and swamping rate under control.
    Matched MeSH terms: Models, Theoretical*
  3. Rahman HS, Tan BL, Othman HH, Chartrand MS, Pathak Y, Mohan S, et al.
    Biomed Res Int, 2020;2020:8857428.
    PMID: 33381591 DOI: 10.1155/2020/8857428
    Angiogenesis is a crucial area in scientific research because it involves many important physiological and pathological processes. Indeed, angiogenesis is critical for normal physiological processes, including wound healing and embryonic development, as well as being a component of many disorders, such as rheumatoid arthritis, obesity, and diabetic retinopathies. Investigations of angiogenic mechanisms require assays that can activate the critical steps of angiogenesis as well as provide a tool for assessing the efficacy of therapeutic agents. Thus, angiogenesis assays are key tools for studying the mechanisms of angiogenesis and identifying the potential therapeutic strategies to modulate neovascularization. However, the regulation of angiogenesis is highly complex and not fully understood. Difficulties in assessing the regulators of angiogenic response have necessitated the development of an alternative approach. In this paper, we review the standard models for the study of tumor angiogenesis on the macroscopic scale that include in vitro, in vivo, and computational models. We also highlight the differences in several modeling approaches and describe key advances in understanding the computational models that contributed to the knowledge base of the field.
    Matched MeSH terms: Models, Theoretical
  4. Atee HA, Ahmad R, Noor NM, Rahma AM, Aljeroudi Y
    PLoS One, 2017;12(2):e0170329.
    PMID: 28196080 DOI: 10.1371/journal.pone.0170329
    In image steganography, determining the optimum location for embedding the secret message precisely with minimum distortion of the host medium remains a challenging issue. Yet, an effective approach for the selection of the best embedding location with least deformation is far from being achieved. To attain this goal, we propose a novel approach for image steganography with high-performance, where extreme learning machine (ELM) algorithm is modified to create a supervised mathematical model. This ELM is first trained on a part of an image or any host medium before being tested in the regression mode. This allowed us to choose the optimal location for embedding the message with best values of the predicted evaluation metrics. Contrast, homogeneity, and other texture features are used for training on a new metric. Furthermore, the developed ELM is exploited for counter over-fitting while training. The performance of the proposed steganography approach is evaluated by computing the correlation, structural similarity (SSIM) index, fusion matrices, and mean square error (MSE). The modified ELM is found to outperform the existing approaches in terms of imperceptibility. Excellent features of the experimental results demonstrate that the proposed steganographic approach is greatly proficient for preserving the visual information of an image. An improvement in the imperceptibility as much as 28% is achieved compared to the existing state of the art methods.
    Matched MeSH terms: Models, Theoretical*
  5. Zelenev A, Long E, Bazazi AR, Kamarulzaman A, Altice FL
    Int J Drug Policy, 2016 11;37:98-106.
    PMID: 27639995 DOI: 10.1016/j.drugpo.2016.08.008
    BACKGROUND: HIV is primarily concentrated among people who inject drugs (PWID) in Malaysia, where currently HIV prevention and treatment coverage is inadequate. To improve the targeting of interventions, we examined HIV clustering and the role that social networks and geographical distance play in influencing HIV transmission among PWID.

    METHODS: Data were derived from a respondent-driven survey sample (RDS) collected during 2010 of 460 PWID in greater Kuala Lumpur. Analysis focused on socio-demographic, clinical, behavioural, and network information. Spatial probit models were developed based on a distinction between the influence of peers (individuals nominated through a recruitment network) and neighbours (residing a close distance to the individual). The models were expanded to account for the potential influence of the network formation.

    RESULTS: Recruitment patterns of HIV-infected PWID clustered both spatially and across the recruitment networks. In addition, HIV-infected PWID were more likely to have peers and neighbours who inject with clean needles were HIV-infected and lived nearby (<5km), more likely to have been previously incarcerated, less likely to use clean needles (26.8% vs 53.0% of the reported injections, p<0.01), and have fewer recent injection partners (2.4 vs 5.4, p<0.01). The association between the HIV status of peers and neighbours remained significantly correlated even after controlling for unobserved variation related to network formation and sero-sorting.

    CONCLUSION: The relationship between HIV status across networks and space in Kuala Lumpur underscores the importance of these factors for surveillance and prevention strategies, and this needs to be more closely integrated. RDS can be applied to identify injection network structures, and this provides an important mechanism for improving public health surveillance, accessing high-risk populations, and implementing risk-reduction interventions to slow HIV transmission.

    Matched MeSH terms: Models, Theoretical
  6. Morozova O, Crawford FW, Cohen T, Paltiel AD, Altice FL
    Addiction, 2020 Mar;115(3):437-450.
    PMID: 31478285 DOI: 10.1111/add.14797
    BACKGROUND AND AIMS: Although opioid agonist treatment (OAT) for opioid use disorder (OUD) is cost-effective in settings where the HIV epidemic is concentrated among people who inject drugs, OAT coverage in Ukraine remains far below internationally recommended targets. Scale-up is limited by both OAT availability and demand. This study aimed to evaluate the cost-effectiveness of a range of plausible OAT scale-up strategies in Ukraine incorporating the potential impact of treatment spillover and the real-world demand for addiction treatment.

    DESIGN, SETTING AND PARTICIPANTS: Ten-year horizon (2016-25) modeling study of opioid addiction epidemic and treatment that accommodated potential peer effects in opioid use initiation and supply-induced treatment demand in three Ukrainian cities: Kyiv, Mykolaiv and Lviv, comprising a simulated population of people at risk of and with OUD.

    MEASUREMENTS: Incremental cost per quality-adjusted life-year gained in the simulated population.

    FINDINGS: An estimated 12.2-, 2.4- and 13.4-fold OAT capacity increase over 2016 baseline capacity in Kyiv, Mykolaiv and Lviv, respectively, would be cost-effective at a willingness-to-pay of one per-capita gross domestic product (GDP) per quality-adjusted life-year gained. This result is robust to parametric and structural uncertainty. Even under the most ambitious capacity increase, OAT coverage (i.e. the proportion of people with OUD receiving OAT) over a 10-year modeling horizon would be 20, 11 and 17% in Kyiv, Mykolaiv and Lviv, respectively, owing to limited demand.

    CONCLUSIONS: It is estimated that a substantial increase in opioid agonist treatment (OAT) capacity in three Ukrainian cities would be cost-effective for a wide range of willingness-to-pay thresholds. Even a very ambitious capacity increase, however, is unlikely to reach internationally recommended coverage levels. Further increases in coverage may be limited by demand and would require addressing existing structural barriers to OAT access.

    Matched MeSH terms: Models, Theoretical
  7. Shuib, A., Alwadood, Z.
    MyJurnal
    This paper presents a mathematical approach to solve railway rescheduling problems. The approach assumes that the trains are able to resume their journey after a given time frame of disruption whereby The train that experiences disruption and trains affected by the incident are rescheduled. The approach employed mathematical model to prioritise certain types of train according the railway operator’s requirement. A pre-emptive goal programming model was adapted to find an optimal solution that satisfies the operational constraints and the company’s stated goals. Initially, the model minimises the total service delay of all trains while adhering to the minimum headway requirement and track capacity. Subsequently, it maximises the train service reliability by only considering the trains with delay time window of five minutes or less. The model uses MATLAB R2014a software which automatically generates the optimal solution of the problem based on the input matrix of constraints. An experiment with three incident scenarios on a double-track railway of local network was conducted to evaluate the performance of the proposed model. The new provisional timetable was produced in short computing time and the model was able to prioritise desired train schedule.
    Matched MeSH terms: Models, Theoretical
  8. Shafie AA, Yeo HY, Coudeville L, Steinberg L, Gill BS, Jahis R, et al.
    Pharmacoeconomics, 2017 May;35(5):575-589.
    PMID: 28205150 DOI: 10.1007/s40273-017-0487-3
    BACKGROUND: Dengue disease poses a great economic burden in Malaysia.

    METHODS: This study evaluated the cost effectiveness and impact of dengue vaccination in Malaysia from both provider and societal perspectives using a dynamic transmission mathematical model. The model incorporated sensitivity analyses, Malaysia-specific data, evidence from recent phase III studies and pooled efficacy and long-term safety data to refine the estimates from previous published studies. Unit costs were valued in $US, year 2013 values.

    RESULTS: Six vaccination programmes employing a three-dose schedule were identified as the most likely programmes to be implemented. In all programmes, vaccination produced positive benefits expressed as reductions in dengue cases, dengue-related deaths, life-years lost, disability-adjusted life-years and dengue treatment costs. Instead of incremental cost-effectiveness ratios (ICERs), we evaluated the cost effectiveness of the programmes by calculating the threshold prices for a highly cost-effective strategy [ICER <1 × gross domestic product (GDP) per capita] and a cost-effective strategy (ICER between 1 and 3 × GDP per capita). We found that vaccination may be cost effective up to a price of $US32.39 for programme 6 (highly cost effective up to $US14.15) and up to a price of $US100.59 for programme 1 (highly cost effective up to $US47.96) from the provider perspective. The cost-effectiveness analysis is sensitive to under-reporting, vaccine protection duration and model time horizon.

    CONCLUSION: Routine vaccination for a population aged 13 years with a catch-up cohort aged 14-30 years in targeted hotspot areas appears to be the best-value strategy among those investigated. Dengue vaccination is a potentially good investment if the purchaser can negotiate a price at or below the cost-effective threshold price.

    Matched MeSH terms: Models, Theoretical*
  9. Adnan N, Nordin SM, Rahman I, Amini MH
    Environ Sci Pollut Res Int, 2017 Aug;24(22):17955-17975.
    PMID: 28612311 DOI: 10.1007/s11356-017-9153-8
    With the rising concern about climate change, there has been an increased public awareness that has resulted in new government policies to support scientific research for mitigating these problems. Malaysia is among the major energy-intense countries and is under an excessive burden to advance its energy efficiency and to also work towards the reduction of its carbon emission. Plug-in hybrid electric vehicles (PHEVs) have the potential to lessen the carbon emission and gasoline consumption in order to alleviate environmental problems. Most of the energy problems linked to the increasing transportation pollution are now being reduced with the solution of the adoption of PHEVs. PHEVs are seen as a solution to cut carbon emission, which prevents environmental damages. Furthermore, PHEVs' driving range and performance can be comparable to the other hybrid vehicles as well as the conventional IC engines that have gasoline and diesel tanks. Thus, many efforts are being initiated to promote the use of PHEVs as an innovative and affordable transportation system. In order to achieve making the consumers aware of the adoption of PHEVs, we used a model which is based on the extended theory of planned behavior (TPB). This review is based on the factors affecting the adoption of PHEVs among Malaysian consumers. The model takes into account the ten key features that influence the adoption of PHEVs, such as environmental concern, personal norm, attitude, vehicle ownership costs, driving range, charging time, intention, subjective norm, perceived behavioral control, and personal norm. All these constructs are drivers towards the adoption of PHEVs. These factors affect the relationship between the adoption of PHEVs and how consumers intend to protect the environment. This review is based on improving how the "attitude-action" gap is understood as it is an important element for further studies on PHEVs. The aim of the research is to come up with a framework that examines how to modify the consumer's environmental concerns in acquiring PHEVs. This will pave the way for more academic research and future works that can emphasize how to obtain empirical results. The authors' recommendation is that, before a consumer's behavior is assessed and considered, an observation of the current technology is needed with methods and knowledge of the existing technology adoption aspect.
    Matched MeSH terms: Models, Theoretical
  10. Ehbrecht M, Seidel D, Annighöfer P, Kreft H, Köhler M, Zemp DC, et al.
    Nat Commun, 2021 01 22;12(1):519.
    PMID: 33483481 DOI: 10.1038/s41467-020-20767-z
    The complexity of forest structures plays a crucial role in regulating forest ecosystem functions and strongly influences biodiversity. Yet, knowledge of the global patterns and determinants of forest structural complexity remains scarce. Using a stand structural complexity index based on terrestrial laser scanning, we quantify the structural complexity of boreal, temperate, subtropical and tropical primary forests. We find that the global variation of forest structural complexity is largely explained by annual precipitation and precipitation seasonality (R² = 0.89). Using the structural complexity of primary forests as benchmark, we model the potential structural complexity across biomes and present a global map of the potential structural complexity of the earth´s forest ecoregions. Our analyses reveal distinct latitudinal patterns of forest structure and show that hotspots of high structural complexity coincide with hotspots of plant diversity. Considering the mechanistic underpinnings of forest structural complexity, our results suggest spatially contrasting changes of forest structure with climate change within and across biomes.
    Matched MeSH terms: Models, Theoretical
  11. Chong NS, Smith SR, Werkman M, Anderson RM
    PLoS Negl Trop Dis, 2021 08;15(8):e0009625.
    PMID: 34339450 DOI: 10.1371/journal.pntd.0009625
    The World Health Organization has recommended the application of mass drug administration (MDA) in treating high prevalence neglected tropical diseases such as soil-transmitted helminths (STHs), schistosomiasis, lymphatic filariasis, onchocerciasis and trachoma. MDA-which is safe, effective and inexpensive-has been widely applied to eliminate or interrupt the transmission of STHs in particular and has been offered to people in endemic regions without requiring individual diagnosis. We propose two mathematical models to investigate the impact of MDA on the mean number of worms in both treated and untreated human subpopulations. By varying the efficay of drugs, initial conditions of the models, coverage and frequency of MDA (both annual and biannual), we examine the dynamic behaviour of both models and the possibility of interruption of transmission. Both models predict that the interruption of transmission is possible if the drug efficacy is sufficiently high, but STH infection remains endemic if the drug efficacy is sufficiently low. In between these two critical values, the two models produce different predictions. By applying an additional round of biannual and annual MDA, we find that interruption of transmission is likely to happen in both cases with lower drug efficacy. In order to interrupt the transmission of STH or eliminate the infection efficiently and effectively, it is crucial to identify the appropriate efficacy of drug, coverage, frequency, timing and number of rounds of MDA.
    Matched MeSH terms: Models, Theoretical
  12. Nor Azizah Yacob, Anuar Ishak
    Sains Malaysiana, 2014;43:491-496.
    The steady, two-dimensional laminar flow of a power-law fluid over a permeable shrinking sheet of constant surface temperature is investigated. The governing partial differential equations were transformed into a system of nonlinear ordinary differential equations using a similarity transformation, before being solved numerically by the Runge-Kutta- Fehlberg method with shooting technique. The results are presented graphically and the effects of the power-law index n, suction parameter fw and Prandtl number Pr were discussed. It was found that stronger suction is necessary for the solution to exist for a pseudoplastic fluid (n<1) compared to a dilatant fluid (n>1).
    Matched MeSH terms: Models, Theoretical
  13. Sookhak M, Akhunzada A, Gani A, Khurram Khan M, Anuar NB
    ScientificWorldJournal, 2014;2014:269357.
    PMID: 25121114 DOI: 10.1155/2014/269357
    Cloud computing is a significant shift of computational paradigm where computing as a utility and storing data remotely have a great potential. Enterprise and businesses are now more interested in outsourcing their data to the cloud to lessen the burden of local data storage and maintenance. However, the outsourced data and the computation outcomes are not continuously trustworthy due to the lack of control and physical possession of the data owners. To better streamline this issue, researchers have now focused on designing remote data auditing (RDA) techniques. The majority of these techniques, however, are only applicable for static archive data and are not subject to audit the dynamically updated outsourced data. We propose an effectual RDA technique based on algebraic signature properties for cloud storage system and also present a new data structure capable of efficiently supporting dynamic data operations like append, insert, modify, and delete. Moreover, this data structure empowers our method to be applicable for large-scale data with minimum computation cost. The comparative analysis with the state-of-the-art RDA schemes shows that the proposed scheme is secure and highly efficient in terms of the computation and communication overhead on the auditor and server.
    Matched MeSH terms: Models, Theoretical*
  14. Appleyard RT
    Asian Pac Migr J, 1992;1(1):1-18.
    PMID: 12317235
    "Wide income differentials, the threat of increased illegal immigration from developing countries, and sub-replacement fertility in the developed countries are some reasons for the recent reassessment of the relationship between migration and development.... The model presented in this article proposes different roles for permanent immigrants, contract workers, professional transients, illegal migrants and others according to the stages of modernization of the sending and receiving countries. The model was found consistent with the experiences of Mauritius, Seychelles, Singapore and, to a lesser extent, Malaysia."
    Matched MeSH terms: Models, Theoretical*
  15. Islam MS, Hannan MA, Basri H, Hussain A, Arebey M
    Waste Manag, 2014 Feb;34(2):281-90.
    PMID: 24238802 DOI: 10.1016/j.wasman.2013.10.030
    The increasing requirement for Solid Waste Management (SWM) has become a significant challenge for municipal authorities. A number of integrated systems and methods have introduced to overcome this challenge. Many researchers have aimed to develop an ideal SWM system, including approaches involving software-based routing, Geographic Information Systems (GIS), Radio-frequency Identification (RFID), or sensor intelligent bins. Image processing solutions for the Solid Waste (SW) collection have also been developed; however, during capturing the bin image, it is challenging to position the camera for getting a bin area centralized image. As yet, there is no ideal system which can correctly estimate the amount of SW. This paper briefly discusses an efficient image processing solution to overcome these problems. Dynamic Time Warping (DTW) was used for detecting and cropping the bin area and Gabor wavelet (GW) was introduced for feature extraction of the waste bin image. Image features were used to train the classifier. A Multi-Layer Perceptron (MLP) classifier was used to classify the waste bin level and estimate the amount of waste inside the bin. The area under the Receiver Operating Characteristic (ROC) curves was used to statistically evaluate classifier performance. The results of this developed system are comparable to previous image processing based system. The system demonstration using DTW with GW for feature extraction and an MLP classifier led to promising results with respect to the accuracy of waste level estimation (98.50%). The application can be used to optimize the routing of waste collection based on the estimated bin level.
    Matched MeSH terms: Models, Theoretical*
  16. Abdul-Kadir, M.A., Ariffin, J.
    ASM Science Journal, 2012;6(2):128-137.
    MyJurnal
    This paper reviews the advances made on studies related to bank erosion. Bank erosion has been an area of interest by researchers in geological, geotechnical, hydraulic, hydrology and river engineering disciplines. With anticipated global challenges from climate change impacts, bank erosion studies could support challenges faced in ensuring sustainable environmental management. The evolution in the theoretical and laboratory findings have led to the advances in bank erosion and contributed to new knowledge in the said field. This review summarises the findings of previous investigators including measurements approach and prediction of rates of bank erosion through the use of physical models and numerical approach.
    Matched MeSH terms: Models, Theoretical
  17. Gazzaz NM, Yusoff MK, Ramli MF, Juahir H, Aris AZ
    Water Environ Res, 2015 Feb;87(2):99-112.
    PMID: 25790513
    This paper describes the design of an artificial neural network (ANN) model to predict the water quality index (WQI) using land use areas as predictors. Ten-year records of land use statistics and water quality data for Kinta River (Malaysia) were employed in the modeling process. The most accurate WQI predictions were obtained with the network architecture 7-23-1; the back propagation training algorithm; and a learning rate of 0.02. The WQI forecasts of this model had significant (p < 0.01), positive, very high correlation (ρs = 0.882) with the measured WQI values. Sensitivity analysis revealed that the relative importance of the land use classes to WQI predictions followed the order: mining > rubber > forest > logging > urban areas > agriculture > oil palm. These findings show that the ANNs are highly reliable means of relating water quality to land use, thus integrating land use development with river water quality management.
    Matched MeSH terms: Models, Theoretical*
  18. Laurance WF, Clements GR, Sloan S, O'Connell CS, Mueller ND, Goosem M, et al.
    Nature, 2014 Sep 11;513(7517):229-32.
    PMID: 25162528 DOI: 10.1038/nature13717
    The number and extent of roads will expand dramatically this century. Globally, at least 25 million kilometres of new roads are anticipated by 2050; a 60% increase in the total length of roads over that in 2010. Nine-tenths of all road construction is expected to occur in developing nations, including many regions that sustain exceptional biodiversity and vital ecosystem services. Roads penetrating into wilderness or frontier areas are a major proximate driver of habitat loss and fragmentation, wildfires, overhunting and other environmental degradation, often with irreversible impacts on ecosystems. Unfortunately, much road proliferation is chaotic or poorly planned, and the rate of expansion is so great that it often overwhelms the capacity of environmental planners and managers. Here we present a global scheme for prioritizing road building. This large-scale zoning plan seeks to limit the environmental costs of road expansion while maximizing its benefits for human development, by helping to increase agricultural production, which is an urgent priority given that global food demand could double by mid-century. Our analysis identifies areas with high environmental values where future road building should be avoided if possible, areas where strategic road improvements could promote agricultural development with relatively modest environmental costs, and 'conflict areas' where road building could have sizeable benefits for agriculture but with serious environmental damage. Our plan provides a template for proactively zoning and prioritizing roads during the most explosive era of road expansion in human history.
    Matched MeSH terms: Models, Theoretical
  19. Aamir K., Khan H., Arya A.
    MyJurnal
    Introduction: Polymetabolic syndrome is a malady encompassing centralized accumulation of lipids and subsequent resistance to insulin leading towards diabesity. Currently, this condition is perilous threat to public health and also, creating perplexity for medical scientists. There is an intensive need for the development of obese rodent model having close resemblance with human metabolic syndrome (MetS); so that intricate molecular and/or therapeutic
    targets can be elucidated. The resultant simulations will be beneficial to explicate not only pathogenesis but also secret conversation of signaling pathways in inducing MetS related complications in other organs. Methods: Currently, there are different methods for the development of rodent models of MetS, for instance, utilizing high lipogenic diet, genetic alterations, induction by chemicals or by combination of high fat diet and few others. In general, combination of cafeteria or western diet and low dose of streptozotocin (STZ) is a fine example of diet induced experimental model. In this model animals are allowed free access to highly palatable, energy dense, unhealthy human food for 12-18 weeks which promotes voluntary hyperphagia resulting in weight gain, increased fat mass and insulin resistance. At the end of feeding period 30mg/kg STZ is given intraperitoneally to mimic human type 2 diabetic condition.
    Conclusion: Consumption of cafeteria diet with low dose STZ is considered to be the robust model of diabesity offering an exceptional stage to investigate the genomic, molecular, biochemical and cellular mechanisms of obesity and type 2 diabetes.
    Matched MeSH terms: Models, Theoretical
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