Displaying publications 101 - 120 of 735 in total

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  1. Alslaibi TM, Abustan I, Mogheir YK, Afifi S
    Waste Manag Res, 2013 Jan;31(1):50-9.
    PMID: 23148014 DOI: 10.1177/0734242X12465462
    Landfills are a source of groundwater pollution in Gaza Strip. This study focused on Deir Al Balah landfill, which is a unique sanitary landfill site in Gaza Strip (i.e., it has a lining system and a leachate recirculation system). The objective of this article is to assess the generated leachate quantity and percolation to the groundwater aquifer at a specific site, using the approaches of (i) the hydrologic evaluation of landfill performance model (HELP) and (ii) the water balance method (WBM). The results show that when using the HELP model, the average volume of leachate discharged from Deir Al Balah landfill during the period 1997 to 2007 was around, 6800 m3/year. Meanwhile, the average volume of leachate percolated through the clay layer was 550 m3/year, which represents around 8% of the generated leachate. Meanwhile, the WBM indicated that the average volume of leachate discharged from Deir Al Balah landfill during the same period was around 7660 m3/year--about half of which comes from the moisture content of the waste, while the remainder comes from the infiltration of precipitation and re-circulated leachate. Therefore, the estimated quantity of leachate to groundwater by these two methods was very close. However, compared with the measured leachate quantity, these results were overestimated and indicated a dangerous threat to the groundwater aquifer, as there was no separation between municipal, hazardous and industrial wastes, in the area.
    Matched MeSH terms: Models, Theoretical
  2. Altalmas T, Aula A, Ahmad S, Tokhi MO, Akmeliawati R
    Assist Technol, 2016;28(3):159-74.
    PMID: 27187763 DOI: 10.1080/10400435.2016.1140688
    Two-wheeled wheelchairs are considered highly nonlinear and complex systems. The systems mimic a double-inverted pendulum scenario and will provide better maneuverability in confined spaces and also to reach higher level of height for pick and place tasks. The challenge resides in modeling and control of the two-wheeled wheelchair to perform comparably to a normal four-wheeled wheelchair. Most common modeling techniques have been accomplished by researchers utilizing the basic Newton's Laws of motion and some have used 3D tools to model the system where the models are much more theoretical and quite far from the practical implementation. This article is aimed at closing the gap between the conventional mathematical modeling approaches where the integrated 3D modeling approach with validation on the actual hardware implementation was conducted. To achieve this, both nonlinear and a linearized model in terms of state space model were obtained from the mathematical model of the system for analysis and, thereafter, a 3D virtual prototype of the wheelchair was developed, simulated, and analyzed. This has increased the confidence level for the proposed platform and facilitated the actual hardware implementation of the two-wheeled wheelchair. Results show that the prototype developed and tested has successfully worked within the specific requirements established.
    Matched MeSH terms: Models, Theoretical*
  3. Alwan FM, Baharum A, Hassan GS
    PLoS One, 2013;8(8):e69716.
    PMID: 23936346 DOI: 10.1371/journal.pone.0069716
    The reliability of the electrical distribution system is a contemporary research field due to diverse applications of electricity in everyday life and diverse industries. However a few research papers exist in literature. This paper proposes a methodology for assessing the reliability of 33/11 Kilovolt high-power stations based on average time between failures. The objective of this paper is to find the optimal fit for the failure data via time between failures. We determine the parameter estimation for all components of the station. We also estimate the reliability value of each component and the reliability value of the system as a whole. The best fitting distribution for the time between failures is a three parameter Dagum distribution with a scale parameter [Formula: see text] and shape parameters [Formula: see text] and [Formula: see text]. Our analysis reveals that the reliability value decreased by 38.2% in each 30 days. We believe that the current paper is the first to address this issue and its analysis. Thus, the results obtained in this research reflect its originality. We also suggest the practicality of using these results for power systems for both the maintenance of power systems models and preventive maintenance models.
    Matched MeSH terms: Models, Theoretical*
  4. Amin MS, Reaz MB, Nasir SS, Bhuiyan MA, Ali MA
    ScientificWorldJournal, 2014;2014:597180.
    PMID: 25276855 DOI: 10.1155/2014/597180
    Precise navigation is a vital need for many modern vehicular applications. The global positioning system (GPS) cannot provide continuous navigation information in urban areas. The widely used inertial navigation system (INS) can provide full vehicle state at high rates. However, the accuracy diverges quickly in low cost microelectromechanical systems (MEMS) based INS due to bias, drift, noise, and other errors. These errors can be corrected in a stationary state. But detecting stationary state is a challenging task. A novel stationary state detection technique from the variation of acceleration, heading, and pitch and roll of an attitude heading reference system (AHRS) built from the inertial measurement unit (IMU) sensors is proposed. Besides, the map matching (MM) algorithm detects the intersections where the vehicle is likely to stop. Combining these two results, the stationary state is detected with a smaller timing window of 3 s. A longer timing window of 5 s is used when the stationary state is detected only from the AHRS. The experimental results show that the stationary state is correctly identified and the position error is reduced to 90% and outperforms previously reported work. The proposed algorithm would help to reduce INS errors and enhance the performance of the navigation system.
    Matched MeSH terms: Models, Theoretical
  5. Amin MZM, Shaaban AJ, Ercan A, Ishida K, Kavvas ML, Chen ZQ, et al.
    Sci Total Environ, 2017 Jan 01;575:12-22.
    PMID: 27723460 DOI: 10.1016/j.scitotenv.2016.10.009
    Impacts of climate change on the hydrologic processes under future climate change conditions were assessed over Muda and Dungun watersheds of Peninsular Malaysia by means of a coupled regional climate and physically-based hydrology model utilizing an ensemble of future climate change projections. An ensemble of 15 different future climate realizations from coarse resolution global climate models' (GCMs) projections for the 21st century was dynamically downscaled to 6km resolution over Peninsular Malaysia by a regional climate model, which was then coupled with the watershed hydrology model WEHY through the atmospheric boundary layer over Muda and Dungun watersheds. Hydrologic simulations were carried out at hourly increments and at hillslope-scale in order to assess the impacts of climate change on the water balances and flooding conditions in the 21st century. The coupled regional climate and hydrology model was simulated for a duration of 90years for each of the 15 realizations. It is demonstrated that the increase in mean monthly flows due to the impact of expected climate change during 2040-2100 is statistically significant from April to May and from July to October at Muda watershed. Also, the increase in mean monthly flows is shown to be significant in November during 2030-2070 and from November to December during 2070-2100 at Dungun watershed. In other words, the impact of the expected climate change will be significant during the northeast and southwest monsoon seasons at Muda watershed and during the northeast monsoon season at Dungun watershed. Furthermore, the flood frequency analyses for both watersheds indicated an overall increasing trend in the second half of the 21st century.
    Matched MeSH terms: Models, Theoretical
  6. Amini A, Saboohi H, Wah TY, Herawan T
    ScientificWorldJournal, 2014;2014:926020.
    PMID: 25110753 DOI: 10.1155/2014/926020
    Data streams are continuously generated over time from Internet of Things (IoT) devices. The faster all of this data is analyzed, its hidden trends and patterns discovered, and new strategies created, the faster action can be taken, creating greater value for organizations. Density-based method is a prominent class in clustering data streams. It has the ability to detect arbitrary shape clusters, to handle outlier, and it does not need the number of clusters in advance. Therefore, density-based clustering algorithm is a proper choice for clustering IoT streams. Recently, several density-based algorithms have been proposed for clustering data streams. However, density-based clustering in limited time is still a challenging issue. In this paper, we propose a density-based clustering algorithm for IoT streams. The method has fast processing time to be applicable in real-time application of IoT devices. Experimental results show that the proposed approach obtains high quality results with low computation time on real and synthetic datasets.
    Matched MeSH terms: Models, Theoretical*
  7. Amir S. A. Hamzah, Ali H. M. Murid
    MATEMATIKA, 2018;34(2):293-311.
    MyJurnal
    This study presents a mathematical model examining wastewater pollutant removal through
    an oxidation pond treatment system. This model was developed to describe the reaction
    between microbe-based product mPHO (comprising Phototrophic bacteria (PSB)), dissolved
    oxygen (DO) and pollutant namely chemical oxygen demand (COD). It consists
    of coupled advection-diffusion-reaction equations for the microorganism (PSB), DO and
    pollutant (COD) concentrations, respectively. The coupling of these equations occurred
    due to the reactions between PSB, DO and COD to produce harmless compounds. Since
    the model is nonlinear partial differential equations (PDEs), coupled, and dynamic, computational
    algorithm with a specific numerical method, which is implicit Crank-Nicolson
    method, was employed to simulate the dynamical behaviour of the system. Furthermore,
    numerical results revealed that the proposed model demonstrated high accuracy when
    compared to the experimental data.
    Matched MeSH terms: Models, Theoretical
  8. Anderson KH, Hill MA, Butler JS
    J Dev Econ, 1987 Aug;26(2):223-34.
    PMID: 12280709
    "This paper estimates a proportional hazards model for the timing of age at marriage of women in Malaysia. We hypothesize that age at marriage responds significantly to differences in male and female occupations, race, and age. We find considerable empirical support for the relevance of economic variables in determining age at marriage as well as evidence of strong differences in marriage patterns across races."
    Matched MeSH terms: Models, Theoretical*
  9. Andiappan V, Benjamin MFD, Tan RR, Ng DKS
    Heliyon, 2019 Oct;5(10):e02594.
    PMID: 31720447 DOI: 10.1016/j.heliyon.2019.e02594
    Designers of energy systems often face challenges in balancing the trade-off between cost and reliability. In literature, several papers have presented mathematical models for optimizing the reliability and cost of energy systems. However, the previous models only addressed reliability implicitly, i.e., based on availability and maintenance planning. Others focused on allocation of reliability based on individual equipment requirements via non-linear models that require high computational effort. This work proposes a novel mixed-integer linear programming (MILP) model that combines the use of both input-output (I-O) modelling and linearized parallel system reliability expressions. The proposed MILP model can optimize the design and reliability of energy systems based on equipment function and operating capacity. The model allocates equipment with sufficient reliability to meet system functional requirements and determines the required capacity. A simple pedagogical example is presented in this work to illustrate the features of proposed MILP model. The MILP model is then applied to a polygeneration case study consisting of two scenarios. In the first scenario, the polygeneration system was optimized based on specified reliability requirements. The technologies chosen for Scenario 1 were the CHP module, reverse osmosis unit and vapour compression chiller. The total annualized cost (TAC) for Scenario 1 was 53.3 US$ million/year. In the second scenario, the minimum reliability level for heat production was increased. The corresponding results indicated that an additional auxiliary boiler must be operated to meet the new requirements. The resulting TAC for the Scenario 2 was 5.3% higher than in the first scenario.
    Matched MeSH terms: Models, Theoretical
  10. Ang TN, Young BR, Taylor M, Burrell R, Aroua MK, Chen WH, et al.
    Chemosphere, 2020 Dec;260:127496.
    PMID: 32659541 DOI: 10.1016/j.chemosphere.2020.127496
    Activated carbons have been reported to be useful for adsorptive removal of the volatile anaesthetic sevoflurane from a vapour stream. The surface functionalities on activated carbons could be modified through aqueous oxidation using oxidising solutions to enhance the sevoflurane adsorption. In this study, an attempt to oxidise the surface of a commercial activated carbon to improve its adsorption capacity for sevoflurane was conducted using 6 mol/L nitric acid, 2 mol/L ammonium persulfate, and 30 wt per cent (wt%) of hydrogen peroxide (H2O2). The adsorption tests at fixed conditions (bed depth: 10 cm, inlet concentration: 528 mg/L, and flow rate: 3 L/min) revealed that H2O2 oxidation gave desirable sevoflurane adsorption (0.510 ± 0.005 mg/m2). A parametric study was conducted with H2O2 to investigate the effect of oxidation conditions to the changes in surface oxygen functionalities by varying the concentration, oxidation duration, and temperature, and the Conductor-like Screening Model for Real Solvents (COSMO-RS) was applied to predict the interactions between oxygen functionalities and sevoflurane. The H2O2 oxidation incorporated varying degrees of both surface oxygen functionalities with hydrogen bond (HB) acceptor and HB donor characters under the studied conditions. Oxidised samples with enriched oxygen functionalities with HB acceptor character and fewer HB donor character exhibited better adsorption capacity for sevoflurane. The presence of a high amount of oxygen functional groups with HB donor character adversely affected the sevoflurane adsorption despite the enrichment of oxygen functional groups with HB acceptor character that have a higher tendency to adsorb sevoflurane.
    Matched MeSH terms: Models, Theoretical
  11. Anis S, Zainal ZA
    Bioresour Technol, 2014 Jan;151:183-90.
    PMID: 24231266 DOI: 10.1016/j.biortech.2013.10.065
    Kinetic model parameters for toluene conversion under microwave thermocatalytic treatment were evaluated. The kinetic rate constants were determined using integral method based on experimental data and coupled with Arrhenius equation for obtaining the activation energies and pre-exponential factors. The model provides a good agreement with the experimental data. The kinetic model was also validated with standard error of 3% on average. The extrapolation of the model showed a reasonable trend to predict toluene conversion and product yield both in thermal and catalytic treatments. Under microwave irradiation, activation energy of toluene conversion was lower in the range of 3-27 kJ mol(-1) compared to those of conventional heating reported in the literatures. The overall reaction rate was six times higher compared to conventional heating. As a whole, the kinetic model works better for tar model removal in the absence of gas reforming within a level of reliability demonstrated in this study.
    Matched MeSH terms: Models, Theoretical*
  12. Ansari M, Othman F, El-Shafie A
    Sci Total Environ, 2020 Jun 20;722:137878.
    PMID: 32199382 DOI: 10.1016/j.scitotenv.2020.137878
    Sewage treatment plants (STPs) keep sewage contamination within safe levels and minimize the risk of environmental disasters. To achieve optimum operation of an STP, it is necessary for influent parameters to be measured or estimated precisely. In this research, six well-known influent chemical and biological characteristics, i.e., biochemical oxygen demand (BOD), chemical oxygen demand (COD), Ammoniacal Nitrogen (NH3-N), pH, oil and grease (OG) and suspended solids (SS), were modeled and predicted using the Sugeno fuzzy logic model. The membership function range of the fuzzy model was optimized by ANFIS, the integrated Genetic algorithms (GA), and the integrated particle swarm optimization (PSO) algorithms. The results were evaluated by different indices to find the accuracy of each algorithm. To ensure prediction accuracy, outliers in the predicted data were found and replaced with reasonable values. The results showed that both integrated GA-FIS and PSO-FIS algorithms performed at almost the same level and both had fewer errors than ANFIS. As the GA-FIS algorithm predicts BOD with fewer errors than PSO-FIS and the aim of this study is to provide an accurate prediction of missing data, GA-FIS was only used to predict the BOD parameter; the other parameters were predicted by PSO-FIS algorithm. As a result, the model successfully could provide outstanding performance for predicting the BOD, COD, NH3-N, OG, pH and SS with MAE equal to 3.79, 5.14, 0.4, 0.27, 0.02, and 3.16, respectively.
    Matched MeSH terms: Models, Theoretical
  13. Ansari M, Othman F, Abunama T, El-Shafie A
    Environ Sci Pollut Res Int, 2018 Apr;25(12):12139-12149.
    PMID: 29455350 DOI: 10.1007/s11356-018-1438-z
    The function of a sewage treatment plant is to treat the sewage to acceptable standards before being discharged into the receiving waters. To design and operate such plants, it is necessary to measure and predict the influent flow rate. In this research, the influent flow rate of a sewage treatment plant (STP) was modelled and predicted by autoregressive integrated moving average (ARIMA), nonlinear autoregressive network (NAR) and support vector machine (SVM) regression time series algorithms. To evaluate the models' accuracy, the root mean square error (RMSE) and coefficient of determination (R2) were calculated as initial assessment measures, while relative error (RE), peak flow criterion (PFC) and low flow criterion (LFC) were calculated as final evaluation measures to demonstrate the detailed accuracy of the selected models. An integrated model was developed based on the individual models' prediction ability for low, average and peak flow. An initial assessment of the results showed that the ARIMA model was the least accurate and the NAR model was the most accurate. The RE results also prove that the SVM model's frequency of errors above 10% or below - 10% was greater than the NAR model's. The influent was also forecasted up to 44 weeks ahead by both models. The graphical results indicate that the NAR model made better predictions than the SVM model. The final evaluation of NAR and SVM demonstrated that SVM made better predictions at peak flow and NAR fit well for low and average inflow ranges. The integrated model developed includes the NAR model for low and average influent and the SVM model for peak inflow.
    Matched MeSH terms: Models, Theoretical*
  14. Apenteng OO, Ismail NA
    PLoS One, 2014;9(6):e98288.
    PMID: 24911023 DOI: 10.1371/journal.pone.0098288
    Previous models of disease spread involving delay have used basic SIR (susceptible--infectious--recovery) formulae and approaches. This paper demonstrates how time-varying SEIRS (S--exposed--I - R - S) models can be extended with delay to produce wave propagations that simulate periodic wave fronts of disease spread in the context of population movements. The model also takes into account the natural mortality associated with the disease spread. Understanding the delay of an infectious disease is critical when attempting to predict where and how fast the disease will propagate. We use cellular automata to model the delay and its effect on the spread of infectious diseases where population movement occurs. We illustrate an approach using wavelet transform analysis to understand the impact of the delay on the spread of infectious diseases. The results indicate that including delay provides novel ways to understand the effects of migration and population movement on disease spread.
    Matched MeSH terms: Models, Theoretical*
  15. 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*
  16. Arif M, Darus M, Raza M, Khan Q
    ScientificWorldJournal, 2014;2014:989640.
    PMID: 25506621 DOI: 10.1155/2014/989640
    The aim of the present paper is to investigate coefficient estimates, Fekete-Szegő inequality, and upper bound of third Hankel determinant for some families of starlike and convex functions of reciprocal order.
    Matched MeSH terms: Models, Theoretical*
  17. Ariffin MRK, Gopal K, Krishnarajah I, Che Ilias IS, Adam MB, Arasan J, et al.
    Sci Rep, 2021 Oct 20;11(1):20739.
    PMID: 34671103 DOI: 10.1038/s41598-021-99541-0
    Since the first coronavirus disease 2019 (COVID-19) outbreak appeared in Wuhan, mainland China on December 31, 2019, the geographical spread of the epidemic was swift. Malaysia is one of the countries that were hit substantially by the outbreak, particularly in the second wave. This study aims to simulate the infectious trend and trajectory of COVID-19 to understand the severity of the disease and determine the approximate number of days required for the trend to decline. The number of confirmed positive infectious cases [as reported by Ministry of Health, Malaysia (MOH)] were used from January 25, 2020 to March 31, 2020. This study simulated the infectious count for the same duration to assess the predictive capability of the Susceptible-Infectious-Recovered (SIR) model. The same model was used to project the simulation trajectory of confirmed positive infectious cases for 80 days from the beginning of the outbreak and extended the trajectory for another 30 days to obtain an overall picture of the severity of the disease in Malaysia. The transmission rate, β also been utilized to predict the cumulative number of infectious individuals. Using the SIR model, the simulated infectious cases count obtained was not far from the actual count. The simulated trend was able to mimic the actual count and capture the actual spikes approximately. The infectious trajectory simulation for 80 days and the extended trajectory for 110 days depicts that the inclining trend has peaked and ended and will decline towards late April 2020. Furthermore, the predicted cumulative number of infectious individuals tallies with the preparations undertaken by the MOH. The simulation indicates the severity of COVID-19 disease in Malaysia, suggesting a peak of infectiousness in mid-March 2020 and a probable decline in late April 2020. Overall, the study findings indicate that outbreak control measures such as the Movement Control Order (MCO), social distancing and increased hygienic awareness is needed to control the transmission of the outbreak in Malaysia.
    Matched MeSH terms: Models, Theoretical
  18. Arrivé E, Ayaya S, Davies MA, Chimbetete C, Edmonds A, Lelo P, et al.
    J Int AIDS Soc, 2018 Jul;21(7):e25157.
    PMID: 29972632 DOI: 10.1002/jia2.25157
    INTRODUCTION: Disclosure of HIV status to HIV-infected children and adolescents is a major care challenge. We describe current site characteristics related to disclosure of HIV status in resource-limited paediatric HIV care settings within the International Epidemiology Databases to Evaluate AIDS (IeDEA) consortium.

    METHODS: An online site assessment survey was conducted across the paediatric HIV care sites within six global regions of IeDEA. A standardized questionnaire was administered to the sites through the REDCap platform.

    RESULTS: From June 2014 to March 2015, all 180 sites of the IeDEA consortium in 31 countries completed the online survey: 57% were urban, 43% were health centres and 86% were integrated clinics (serving both adults and children). Almost all the sites (98%) reported offering disclosure counselling services. Disclosure counselling was most often provided by counsellors (87% of sites), but also by nurses (77%), physicians (74%), social workers (68%), or other clinicians (65%). It was offered to both caregivers and children in 92% of 177 sites with disclosure counselling. Disclosure resources and procedures varied across geographical regions. Most sites in each region reported performing staff members' training on disclosure (72% to 96% of sites per region), routinely collecting HIV disclosure status (50% to 91%) and involving caregivers in the disclosure process (71% to 100%). A disclosure protocol was available in 14% to 71% of sites. Among the 143 sites (79%) routinely collecting disclosure status process, the main collection method was by asking the caregiver or child (85%) about the child's knowledge of his/her HIV status. Frequency of disclosure status assessment was every three months in 63% of the sites, and 71% stored disclosure status data electronically.

    CONCLUSION: The majority of the sites reported offering disclosure counselling services, but educational and social support resources and capacities for data collection varied across regions. Paediatric HIV care sites worldwide still need specific staff members' training on disclosure, development and implementation of guidelines for HIV disclosure, and standardized data collection on this key issue to ensure the long-term health and wellbeing of HIV-infected youth.

    Matched MeSH terms: Models, Theoretical
  19. Asadi-Shekari Z, Moeinaddini M, Zaly Shah M
    Traffic Inj Prev, 2015;16:283-8.
    PMID: 24983474 DOI: 10.1080/15389588.2014.936010
    The objectives of this research are to conceptualize the Bicycle Safety Index (BSI) that considers all parts of the street and to propose a universal guideline with microscale details.
    Matched MeSH terms: Models, Theoretical
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