Displaying publications 21 - 40 of 735 in total

Abstract:
Sort:
  1. Abeysinghe T
    J Appl Stat, 1991;18(2):275-86.
    PMID: 12343764
    Matched MeSH terms: Models, Theoretical*
  2. Abidin, N. Z., Adam, M. B., Midi, H.
    MyJurnal
    Extreme Value Theory (EVT) is a statistical field whose main focus is to investigate extreme phenomena. In EVT, Fréchet distribution is one of the extreme value distributions and it is used to model extreme events. The degree of fit between the model and the observed values was measured by Goodness-of-fit (GOF) test. Several types of GOF tests were also compared. The tests involved were Anderson-Darling (AD), Cramer-von Mises (CVM), Zhang Anderson Darling (ZAD), Zhang Cramer von-Mises (ZCVM) and Ln. The values of parameters μ, σ and ξ were estimated by Maximum Likelihood. The critical values were developed by Monte-Carlo simulation. In power study, the reliability of critical values was determined. Besides, it is of interest to identify which GOF test is superior to the other tests for Fréchet distribution. Thus, the comparisons of rejection rates were observed at different significance levels, as well as different sample sizes, based on several alternative distributions. Overall, given by Maximum Likelihood Estimation of Fréchet distribution, the ZAD and ZCVM tests are the most powerful tests for smaller sample size (ZAD for significance levels 0.05 and 0.1, ZCVM for significance level 0.01) as compared to AD, which is more powerful for larger sample size.
    Matched MeSH terms: Models, Theoretical
  3. Abram NK, Xofis P, Tzanopoulos J, MacMillan DC, Ancrenaz M, Chung R, et al.
    PLoS One, 2014;9(6):e95388.
    PMID: 24887555 DOI: 10.1371/journal.pone.0095388
    Lowland tropical forests are increasingly threatened with conversion to oil palm as global demand and high profit drives crop expansion throughout the world's tropical regions. Yet, landscapes are not homogeneous and regional constraints dictate land suitability for this crop. We conducted a regional study to investigate spatial and economic components of forest conversion to oil palm within a tropical floodplain in the Lower Kinabatangan, Sabah, Malaysian Borneo. The Kinabatangan ecosystem harbours significant biodiversity with globally threatened species but has suffered forest loss and fragmentation. We mapped the oil palm and forested landscapes (using object-based-image analysis, classification and regression tree analysis and on-screen digitising of high-resolution imagery) and undertook economic modelling. Within the study region (520,269 ha), 250,617 ha is cultivated with oil palm with 77% having high Net-Present-Value (NPV) estimates ($413/ha-yr-$637/ha-yr); but 20.5% is under-producing. In fact 6.3% (15,810 ha) of oil palm is commercially redundant (with negative NPV of $-299/ha-yr-$-65/ha-yr) due to palm mortality from flood inundation. These areas would have been important riparian or flooded forest types. Moreover, 30,173 ha of unprotected forest remain and despite its value for connectivity and biodiversity 64% is allocated for future oil palm. However, we estimate that at minimum 54% of these forests are unsuitable for this crop due to inundation events. If conversion to oil palm occurs, we predict a further 16,207 ha will become commercially redundant. This means that over 32,000 ha of forest within the floodplain would have been converted for little or no financial gain yet with significant cost to the ecosystem. Our findings have globally relevant implications for similar floodplain landscapes undergoing forest transformation to agriculture such as oil palm. Understanding landscape level constraints to this crop, and transferring these into policy and practice, may provide conservation and economic opportunities within these seemingly high opportunity cost landscapes.
    Matched MeSH terms: Models, Theoretical
  4. Abrami M, Golob S, Pontelli F, Chiarappa G, Grassi G, Perissutti B, et al.
    Int J Pharm, 2019 Mar 25;559:373-381.
    PMID: 30716402 DOI: 10.1016/j.ijpharm.2019.01.055
    Bacterial infections represent an important drawback in the orthopaedic field, as they can develop either immediately after surgery procedures or after some years. Specifically, in case of implants, they are alleged to be troublesome as their elimination often compels a surgical removal of the infected implant. A possible solution strategy could involve a local coating of the implant by an antibacterial system, which requires to be easily applicable, biocompatible and able to provide the desired release kinetics for the selected antibacterial drug. Thus, this work focusses on a biphasic system made up by a thermo-reversible gel matrix (Poloxamer 407/water system) hosting a dispersed phase (PLGA micro-particles), containing a model antibacterial drug (vancomycin hydrochloride). In order to understand the key parameters ruling the performance of this delivery system, we developed a mathematical model able to discriminate the drug diffusion inside micro-particles and within the gel phase, eventually providing to predict the drug release kinetics. The model reliability was confirmed by fitting to experimental data, proposing as a powerful theoretical approach to design and optimize such in situ delivery systems.
    Matched MeSH terms: Models, Theoretical
  5. Abu Amr SS, Aziz HA, Adlan MN
    Waste Manag, 2013 Jun;33(6):1434-41.
    PMID: 23498721 DOI: 10.1016/j.wasman.2013.01.039
    The objective of this study was to investigate the performance of employing persulfate reagent in the advanced oxidation of ozone to treat stabilized landfill leachate in an ozone reactor. A central composite design (CCD) with response surface methodology (RSM) was applied to evaluate the relationships between operating variables, such as ozone and persulfate dosages, pH, and reaction time, to identify the optimum operating conditions. Quadratic models for the following four responses proved to be significant with very low probabilities (<0.0001): COD, color, NH3-N, and ozone consumption (OC). The obtained optimum conditions included a reaction time of 210 min, 30 g/m(3) ozone, 1g/1g COD0/S2O8(2-) ratio, and pH 10. The experimental results were corresponded well with predicted models (COD, color, and NH3-N removal rates of 72%, 96%, and 76%, respectively, and 0.60 (kg O3/kg COD OC). The results obtained in the stabilized leachate treatment were compared with those from other treatment processes, such as ozone only and persulfate S2O8(2-) only, to evaluate its effectiveness. The combined method (i.e., O3/S2O8(2-)) achieved higher removal efficiencies for COD, color, and NH3-N compared with other studied applications. Furthermore, the new method is more efficient than ozone/Fenton in advanced oxidation process in the treatment of the same studied leachate.
    Matched MeSH terms: Models, Theoretical
  6. Abu Bakar SA, Nadarajah S, Absl Kamarul Adzhar ZA, Mohamed I
    PLoS One, 2016;11(6):e0156537.
    PMID: 27272043 DOI: 10.1371/journal.pone.0156537
    In this paper, we introduce the R package gendist that computes the probability density function, the cumulative distribution function, the quantile function and generates random values for several generated probability distribution models including the mixture model, the composite model, the folded model, the skewed symmetric model and the arc tan model. These models are extensively used in the literature and the R functions provided here are flexible enough to accommodate various univariate distributions found in other R packages. We also show its applications in graphing, estimation, simulation and risk measurements.
    Matched MeSH terms: Models, Theoretical*
  7. Abualqumboz MS, Malakahmad A, Mohammed NI
    J Air Waste Manag Assoc, 2016 06;66(6):597-608.
    PMID: 27249105 DOI: 10.1080/10962247.2016.1154115
    Landfills throughout the world are contributing to the global warming problem. This is due to the existence of the most important greenhouse gases (GHG) in landfill gas (LFG); namely, methane (CH4) and carbon dioxide (CO2). The aim of this paper is quantifying the total potential emissions, as well as the variation in production with time of CH4 from a proposed landfill (El Fukhary landfill) in the Gaza Strip, Palestine. Two different methods were adopted in order to quantify the total potential CH4 emissions; the Default methodology based on the intergovernmental panel on climate change (IPCC) 1996 revised guidelines and the Landfill Gas Emissions model (LandGEM V3.02) provided by the United States Environmental Protection Agency (EPA). The second objective of the study has been accomplished using the Triangle gas production model. The results obtained from both Default and LandGEM methods were found to be nearly the same. For 25 years of disposing MSW, El Fukhary landfill expected to have potential CH4 emissions of 1.9542 ± 0.0037 ×109 m3. Triangle model showed that the peak production in term of CH4 would occur in 2043; 28 years beyond the open year. Moreover, the model shows that 50 % of the gas will be produced approximately at the middle of the total duration of gas production. Proper control of Methane emissions from El Fukhary landfill is highly suggested in order to reduce the harmful effects on the environment.

    IMPLICATIONS: Although, GHG emissions are extensively discussed in the developed countries throughout the world, it has gained little concern in the developing countries because they are forced most of the time to put environmental concerns at the end of their priority list. The paper shows that developing countries have to start recognizing their fault and change their way of dealing with environmental issues especially GHG emissions (mainly Methane and carbon dioxide). The authors estimated the potential methane emissions from a proposed central landfill that has been approved to be built in Palestine, a country that is classified as a developing country.

    Matched MeSH terms: Models, Theoretical
  8. Abunama T, Othman F, Younes MK
    Environ Monit Assess, 2018 Sep 20;190(10):597.
    PMID: 30238169 DOI: 10.1007/s10661-018-6966-y
    Landfill leachate is one of the sources of surface water pollution in Selangor State (SS), Malaysia. Leachate volume prediction is essential for sustainable waste management and leachate treatment processes. The accurate estimation of leachate generation rates is often considered a challenge, especially in developing countries, due to the lack of reliable data and high measurement costs. Leachate generation is related to several variable factors, including meteorological data, waste generation rates, and landfill design conditions. Large variations in these factors lead to complicated leachate modeling processes. The aims of this study are to determine the key elements contributing to leachate production and then develop an adaptive neural fuzzy inference system (ANFIS) model to predict leachate generation rates. Accuracy of the final model performance was tested and evaluated using the root mean square error (RMSE), the mean absolute error (MAE), and the correlation coefficient (R). The study results defined dumped waste quantity, rainfall level, and emanated gases as the most significant contributing factors in leachate generation. The best model structure consisted of two triangular fuzzy membership functions and a hybrid training algorithm with eight fuzzy rules. The proposed ANFIS model showed a good performance with an overall correlation coefficient of 0.952.
    Matched MeSH terms: Models, Theoretical*
  9. Abunama T, Othman F, Ansari M, El-Shafie A
    Environ Sci Pollut Res Int, 2019 Feb;26(4):3368-3381.
    PMID: 30511225 DOI: 10.1007/s11356-018-3749-5
    Leachate is one of the main surface water pollution sources in Selangor State (SS), Malaysia. The prediction of leachate amounts is elementary in sustainable waste management and leachate treatment processes, before discharging to surrounding environment. In developing countries, the accurate evaluation of leachate generation rates has often considered a challenge due to the lack of reliable data and high measurement costs. Leachate generation is related to several factors, including meteorological data, waste generation rates, and landfill design conditions. The high variations in these factors lead to complicating leachate modeling processes. This study aims at identifying the key elements contributing to leachate production and developing various AI-based models to predict leachate generation rates. These models included Artificial Neural Network (ANN)-Multi-linear perceptron (MLP) with single and double hidden layers, and support vector machine (SVM) regression time series algorithms. Various performance measures were applied to evaluate the developed model's accuracy. In this study, input optimization process showed that three inputs were acceptable for modeling the leachate generation rates, namely dumped waste quantity, rainfall level, and emanated gases. The initial performance analysis showed that ANN-MLP2 model-which applies two hidden layers-achieved the best performance, then followed by ANN-MLP1 model-which applies one hidden layer and three inputs-while SVM model gave the lowest performance. Ranges and frequency of relative error (RE%) also demonstrate that ANN-MLP models outperformed SVM models. Furthermore, low and peak flow criterion (LFC and PFC) assessment of leachate inflow values in ANN-MLP model with two hidden layers made more accurate values than other models. Since minimizing data collection and processing efforts as well as minimizing modeling complexity are critical in the hydrological modeling process, the applied input optimization process and the developed models in this study were able to provide a good performance in the modeling of leachate generation efficiently.
    Matched MeSH terms: Models, Theoretical*
  10. Abushammala MF, Noor Ezlin Ahmad Basri, Basri H, Ahmed Hussein El-Shafie, Kadhum AA
    Waste Manag Res, 2011 Aug;29(8):863-73.
    PMID: 20858637 DOI: 10.1177/0734242X10382064
    The decomposition of municipal solid waste (MSW) in landfills under anaerobic conditions produces landfill gas (LFG) containing approximately 50-60% methane (CH(4)) and 30-40% carbon dioxide (CO(2)) by volume. CH(4) has a global warming potential 21 times greater than CO(2); thus, it poses a serious environmental problem. As landfills are the main method for waste disposal in Malaysia, the major aim of this study was to estimate the total CH(4) emissions from landfills in all Malaysian regions and states for the year 2009 using the IPCC, 1996 first-order decay (FOD) model focusing on clean development mechanism (CDM) project applications to initiate emission reductions. Furthermore, the authors attempted to assess, in quantitative terms, the amount of CH(4) that would be emitted from landfills in the period from 1981-2024 using the IPCC 2006 FOD model. The total CH(4) emission using the IPCC 1996 model was estimated to be 318.8 Gg in 2009. The Northern region had the highest CH(4) emission inventory, with 128.8 Gg, whereas the Borneo region had the lowest, with 24.2 Gg. It was estimated that Pulau Penang state produced the highest CH(4) emission, 77.6 Gg, followed by the remaining states with emission values ranging from 38.5 to 1.5 Gg. Based on the IPCC 1996 FOD model, the total Malaysian CH( 4) emission was forecast to be 397.7 Gg by 2020. The IPCC 2006 FOD model estimated a 201 Gg CH(4) emission in 2009, and estimates ranged from 98 Gg in 1981 to 263 Gg in 2024.
    Matched MeSH terms: Models, Theoretical
  11. Adamu A, Abdul Wahab R, Aliyu F, Abdul Razak FI, Mienda BS, Shamsir MS, et al.
    J Mol Graph Model, 2019 11;92:131-139.
    PMID: 31352207 DOI: 10.1016/j.jmgm.2019.07.012
    Dehalogenases continue to garner interest of the scientific community due to their potential applications in bioremediation of halogen-contaminated environment and in synthesis of various industrially relevant products. Example of such enzymes is DehL, an L-2-haloacid dehalogenase (EC 3.8.1.2) from Rhizobium sp. RC1 that catalyses the specific cleavage of halide ion from L-2-halocarboxylic acids to produce the corresponding D-2-hydroxycarboxylic acids. Recently, the catalytic residues of DehL have been identified and its catalytic mechanism has been fully elucidated. However, the enantiospecificity determinants of the enzyme remain unclear. This information alongside a well-defined catalytic mechanism are required for rational engineering of DehL for substrate enantiospecificity. Therefore, using quantum mechanics/molecular mechanics and molecular mechanics Poisson-Boltzmann surface area calculations, the current study theoretically investigated the molecular basis of DehL enantiospecificity. The study found that R51L mutation cancelled out the dehalogenation activity of DehL towards it natural substrate, L-2-chloropropionate. The M48R mutation, however introduced a new activity towards D-2-chloropropionate, conveying the possibility of inverting the enantiospecificity of DehL from L-to d-enantiomer with a minimum of two simultaneous mutations. The findings presented here will play important role in the rational design of DehL dehalogenase for improving substrate utility.
    Matched MeSH terms: Models, Theoretical*
  12. Ademola James, Rohani JM, Olusegun AG, Rani MR
    Work, 2014;47(2):173-81.
    PMID: 23324693 DOI: 10.3233/WOR-121530
    OBJECTIVE: The unavailability of anthropometric data especially in developing countries has remained a limiting factor towards the design of learning facilities with sufficient ergonomic consideration. Attempts to use anthropometric data from developed countries have led to provision of school facilities unfit for the users. The purpose of this paper is to use factor analysis to investigate the suitability of the collected anthropometric data as a database for school design in Nigerian tertiary institutions.
    PARTICIPANTS: Anthropometric data were collected from 288 male students in a Federal Polytechnic in North-West of Nigeria. Their age is between 18-25 years.
    METHODS: Nine vertical anthropometric dimensions related to heights were collected using the conventional traditional equipment. Exploratory factor analysis was used to categorize the variables into a model consisting of two factors. Thereafter, confirmatory factor analysis was used to investigate the fit of the data to the proposed model.
    RESULTS: A just identified model, made of two factors, each with three variables was developed. The variables within the model accounted for 81% of the total variation of the entire data. The model was found to demonstrate adequate validity and reliability. Various measuring indices were used to verify that the model fits the data properly. The final model reveals that stature height and eye height sitting were the most stable variables for designs that have to do with standing and sitting construct.
    CONCLUSION: The study has shown the application of factor analysis in anthropometric data analysis. The study highlighted the relevance of these statistical tools to investigate variability among anthropometric data involving diverse population, which has not been widely used for analyzing previous anthropometric data. The collected data is therefore suitable for use while designing for Nigerian students.
    KEYWORDS: Exploratory factor analysis; measurement model; school ergonomics
    Matched MeSH terms: Models, Theoretical
  13. Adenuga KI, Iahad NA, Miskon S
    Int J Med Inform, 2017 08;104:84-96.
    PMID: 28599820 DOI: 10.1016/j.ijmedinf.2017.05.008
    Telemedicine systems have been considered as a necessary measure to alleviate the shortfall in skilled medical specialists in developing countries. However, the obvious challenge is whether clinicians are willing to use this technological innovation, which has aided medical practice globally. One factor which has received little academic attention is the provision of suitable encouragement for clinicians to adopt telemedicine, in the form of rewards, motivation or incentives. A further consideration for telemedicine usage in developing countries, especially sub-Saharan Africa and Nigeria in particular, are to the severe shortage of available practising clinicians. The researchers therefore explore the need to positively reinforce the adoption of telemedicine amongst clinicians in Nigeria, and also offer a rationale for this using the UTAUT model. Data were collected using a structured paper-based questionnaire, with 252 physicians and nurses from six government hospitals in Ondo state, Nigeria. The study applied SmartPLS 2.0 for analysis to determine the relationship between six variables. Demographic moderating variables, age, gender and profession, were included. The results indicate that performance expectancy (p<0.05), effort expectancy (p<0.05), facilitating condition (p<0.01) and reinforcement factor (p<0.001) have significant effects on clinicians' behavioural intention to use telemedicine systems, as predicted using the extended UTAUT model. Our results showed that the use of telemedicine by clinicians in the Nigerian context is perceived as a dual responsibility which requires suitable reinforcement. In addition, performance expectancy, effort expectancy, facilitating condition and reinforcement determinants are influential factors in the use of telemedicine services for remote-patient clinical diagnosis and management by the Nigerian clinicians.
    Matched MeSH terms: Models, Theoretical*
  14. Adeyemi AJ, Rohani JM, Abdul Rani MR
    Appl Ergon, 2017 Jan;58:573-582.
    PMID: 27132042 DOI: 10.1016/j.apergo.2016.04.009
    The study analysed backpack-related back pain in school children by investigating the possibility of multiple interactions among causative factors, which may be responsible for the non-conclusive findings on the issue. Using data from 444 prepubescent schoolchildren, a mixed method design combining survey, observation and direct measurement strategies was implemented. Using a multivariate structural equation modelling approach, the study investigated interactions among anthropometry, posture, backpack volume, rating and back pain constructs, with each construct made of 2-4 indicators. Additionally, regression analysis was used to determine the feasibility of considering the two additional factors of age and body mass index along with the globally accepted recommendation of a load of 10-15% of body weight. Our model demonstrated an acceptable model fit and revealed direct and indirect effects of the factors. Obese children were recommended to carry a one-third lighter load than other children. The application of systematic/multiple strategies provided an explanation for some of the issues associated with school children's backpack-related back pain.
    Matched MeSH terms: Models, Theoretical*
  15. Adham MI, Shirazi SM, Othman F, Rahman S, Yusop Z, Ismail Z
    ScientificWorldJournal, 2014;2014:379763.
    PMID: 25152911 DOI: 10.1155/2014/379763
    Runoff potentiality of a watershed was assessed based on identifying curve number (CN), soil conservation service (SCS), and functional data analysis (FDA) techniques. Daily discrete rainfall data were collected from weather stations in the study area and analyzed through lowess method for smoothing curve. As runoff data represents a periodic pattern in each watershed, Fourier series was introduced to fit the smooth curve of eight watersheds. Seven terms of Fourier series were introduced for the watersheds 5 and 8, while 8 terms of Fourier series were used for the rest of the watersheds for the best fit of data. Bootstrapping smooth curve analysis reveals that watersheds 1, 2, 3, 6, 7, and 8 are with monthly mean runoffs of 29, 24, 22, 23, 26, and 27 mm, respectively, and these watersheds would likely contribute to surface runoff in the study area. The purpose of this study was to transform runoff data into a smooth curve for representing the surface runoff pattern and mean runoff of each watershed through statistical method. This study provides information of runoff potentiality of each watershed and also provides input data for hydrological modeling.
    Matched MeSH terms: Models, Theoretical*
  16. 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
  17. Aftab SM, Mohd Rafie AS, Razak NA, Ahmad KA
    PLoS One, 2016;11(4):e0153755.
    PMID: 27104354 DOI: 10.1371/journal.pone.0153755
    One of the major flow phenomena associated with low Reynolds number flow is the formation of separation bubbles on an airfoil's surface. NACA4415 airfoil is commonly used in wind turbines and UAV applications. The stall characteristics are gradual compared to thin airfoils. The primary criterion set for this work is the capture of laminar separation bubble. Flow is simulated for a Reynolds number of 120,000. The numerical analysis carried out shows the advantages and disadvantages of a few turbulence models. The turbulence models tested were: one equation Spallart Allmars (S-A), two equation SST K-ω, three equation Intermittency (γ) SST, k-kl-ω and finally, the four equation transition γ-Reθ SST. However, the variation in flow physics differs between these turbulence models. Procedure to establish the accuracy of the simulation, in accord with previous experimental results, has been discussed in detail.
    Matched MeSH terms: Models, Theoretical*
  18. Agi A, Junin R, Arsad A, Abbas A, Gbadamosi A, Azli NB, et al.
    PLoS One, 2019;14(9):e0220778.
    PMID: 31560699 DOI: 10.1371/journal.pone.0220778
    Ascorbic acid was used for the first time to synthesize cellulose nanoparticles (CNP) extracted from okra mucilage. The physical properties of the CNP including their size distribution, and crystalline structures were investigated. The rheological properties of the cellulose nanofluid (CNF) were compared with the bulk okra mucilage and commercial polymer xanthan. The interfacial properties of the CNF at the interface of oil-water (O/W) system were investigated at different concentrations and temperatures. The effects of the interaction between the electrolyte and ultrasonic were determined. Core flooding experiment was conducted at reservoir condition to justify the effect of the flow behaviour and disperse phase behaviour of CNF on additional oil recovery. The performance of the CNF was compared to conventional EOR chemical. The combined method of ultrasonic, weak-acid hydrolysis and nanoprecipitation were effective in producing spherical and polygonal nanoparticles with a mean diameter of 100 nm, increased yield of 51% and preserved crystallinity respectively. The zeta potential result shows that the CNF was stable, and the surface charge signifies long term stability of the fluid when injected into oil field reservoirs. The CNF, okra and xanthan exhibited shear-thinning and pseudoplastic behaviour. The IFT decreased with increase in concentration of CNF, electrolyte and temperature. The pressure drop data confirmed the stability of CNF at 120°C and the formation of oil bank was enough to increase the oil recovery by 20%. CNF was found to be very effective in mobilizing residual oil at high-temperature high-pressure (HTHP) reservoir condition. The energy and cost estimations have shown that investing in ultrasonic-assisted weak-acid hydrolysis is easier, cost-effective, and can reduce energy consumption making the method economically advantageous compared to conventional methods.
    Matched MeSH terms: Models, Theoretical
  19. Ahamad, I.S., Choong, T.S.Y., Yunus, R., Chuah, T.G., Vassiliadis, V.S.
    MyJurnal
    Controller tuning is needed to select the optimum response for the controlled process. This work presents a new tuning procedure of PID controllers with safety and response quality measures on a non-linear process model by optimization procedure, with a demonstration of two tanks in series. The model was developed to include safety constraints in the form of path constraints. The model was then solved with a new optimization solver, NLPOPT1, which uses a primal-dual interior point method with a novel non-monotone line search procedure with discretized penalty parameters. This procedure generated a grid of optimal PID tuning parameters for various switching of steadystates to be used as apredictor of PID tunings for arbitrary transitions. The interpolation of tuning parameters between the available parameters was found to be capable to produce state profiles with no violation on the safety measures, while maintaining the quality of the solution with the final set points targeted achievable.
    Matched MeSH terms: Models, Theoretical
  20. Ahmad AL, Chong MF, Bhatia S
    J Hazard Mater, 2009 Nov 15;171(1-3):166-74.
    PMID: 19573986 DOI: 10.1016/j.jhazmat.2009.05.114
    The discharge of palm oil mill effluent (POME) causes serious pollution problems and the membrane based POME treatment is suggested as a solution. Three different designs, namely Design A, B and C distinguished by their different types and orientations of membrane system are proposed. The results at optimum condition proved that the quality of the recovered water for all the designs met the effluent discharge standards imposed by the Department of Environment (DOE). The economic analysis at the optimum condition shows that the total treatment cost for Design A was the highest (RM 115.11/m(3)), followed by Design B (RM 23.64/m(3)) and Design C (RM 7.03/m(3)). In this study, the membrane system operated at high operating pressure with low membrane unit cost is preferable. Design C is chosen as the optimal design for the membrane based POME treatment system based on the lowest total treatment cost.
    Matched MeSH terms: Models, Theoretical
Filters
Contact Us

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links