Displaying publications 1 - 20 of 734 in total

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  1. Al-Mekhlafi ZG, Hanapi ZM, Othman M, Zukarnain ZA
    PLoS One, 2017;12(1):e0167423.
    PMID: 28056020 DOI: 10.1371/journal.pone.0167423
    Recently, Pulse Coupled Oscillator (PCO)-based travelling waves have attracted substantial attention by researchers in wireless sensor network (WSN) synchronization. Because WSNs are generally artificial occurrences that mimic natural phenomena, the PCO utilizes firefly synchronization of attracting mating partners for modelling the WSN. However, given that sensor nodes are unable to receive messages while transmitting data packets (due to deafness), the PCO model may not be efficient for sensor network modelling. To overcome this limitation, this paper proposed a new scheme called the Travelling Wave Pulse Coupled Oscillator (TWPCO). For this, the study used a self-organizing scheme for energy-efficient WSNs that adopted travelling wave biologically inspired network systems based on phase locking of the PCO model to counteract deafness. From the simulation, it was found that the proposed TWPCO scheme attained a steady state after a number of cycles. It also showed superior performance compared to other mechanisms, with a reduction in the total energy consumption of 25%. The results showed that the performance improved by 13% in terms of data gathering. Based on the results, the proposed scheme avoids the deafness that occurs in the transmit state in WSNs and increases the data collection throughout the transmission states in WSNs.
    Matched MeSH terms: Models, Theoretical
  2. Ahmad AL, Wong SS, Teng TT, Zuhairi A
    J Hazard Mater, 2007 Jun 25;145(1-2):162-8.
    PMID: 17161910
    Coagulation-flocculation is a proven technique for the treatment of high suspended solids wastewater. In this study, the central composite face-centered design (CCFD) and response surface methodology (RSM) have been applied to optimize two most important operating variables: coagulant dosage and pH, in the coagulation-flocculation process of pulp and paper mill wastewater treatment. The treated wastewater with high total suspended solids (TSS) removal, low SVI (sludge volume index) and high water recovery are the main objectives to be achieved through the coagulation-flocculation process. The effect of interactions between coagulant dosage and pH on the TSS removal and SVI are significant, whereas there is no interaction between coagulant dosage and water recovery. Quadratic models have been developed for the response variables, i.e. TSS removal, SVI and water recovery based on the high coefficient of determination (R(2)) value of >0.99 obtained from the analysis of variances (ANOVA). The optimum conditions for coagulant dosage and pH are 1045mgL(-1) and 6.75, respectively, where 99% of TSS removal, SVI of 37mLg(-1) and 82% of water recovery can be obtained.
    Matched MeSH terms: Models, Theoretical*
  3. Hossain ME, Jassim WA, Zilany MS
    PLoS One, 2016;11(3):e0150415.
    PMID: 26967160 DOI: 10.1371/journal.pone.0150415
    Sensorineural hearing loss occurs due to damage to the inner and outer hair cells of the peripheral auditory system. Hearing loss can cause decreases in audibility, dynamic range, frequency and temporal resolution of the auditory system, and all of these effects are known to affect speech intelligibility. In this study, a new reference-free speech intelligibility metric is proposed using 2-D neurograms constructed from the output of a computational model of the auditory periphery. The responses of the auditory-nerve fibers with a wide range of characteristic frequencies were simulated to construct neurograms. The features of the neurograms were extracted using third-order statistics referred to as bispectrum. The phase coupling of neurogram bispectrum provides a unique insight for the presence (or deficit) of supra-threshold nonlinearities beyond audibility for listeners with normal hearing (or hearing loss). The speech intelligibility scores predicted by the proposed method were compared to the behavioral scores for listeners with normal hearing and hearing loss both in quiet and under noisy background conditions. The results were also compared to the performance of some existing methods. The predicted results showed a good fit with a small error suggesting that the subjective scores can be estimated reliably using the proposed neural-response-based metric. The proposed metric also had a wide dynamic range, and the predicted scores were well-separated as a function of hearing loss. The proposed metric successfully captures the effects of hearing loss and supra-threshold nonlinearities on speech intelligibility. This metric could be applied to evaluate the performance of various speech-processing algorithms designed for hearing aids and cochlear implants.
    Matched MeSH terms: Models, Theoretical
  4. Islam MA, Jassim WA, Cheok NS, Zilany MS
    PLoS One, 2016;11(7):e0158520.
    PMID: 27392046 DOI: 10.1371/journal.pone.0158520
    Speaker identification under noisy conditions is one of the challenging topics in the field of speech processing applications. Motivated by the fact that the neural responses are robust against noise, this paper proposes a new speaker identification system using 2-D neurograms constructed from the responses of a physiologically-based computational model of the auditory periphery. The responses of auditory-nerve fibers for a wide range of characteristic frequency were simulated to speech signals to construct neurograms. The neurogram coefficients were trained using the well-known Gaussian mixture model-universal background model classification technique to generate an identity model for each speaker. In this study, three text-independent and one text-dependent speaker databases were employed to test the identification performance of the proposed method. Also, the robustness of the proposed method was investigated using speech signals distorted by three types of noise such as the white Gaussian, pink, and street noises with different signal-to-noise ratios. The identification results of the proposed neural-response-based method were compared to the performances of the traditional speaker identification methods using features such as the Mel-frequency cepstral coefficients, Gamma-tone frequency cepstral coefficients and frequency domain linear prediction. Although the classification accuracy achieved by the proposed method was comparable to the performance of those traditional techniques in quiet, the new feature was found to provide lower error rates of classification under noisy environments.
    Matched MeSH terms: Models, Theoretical*
  5. Wang X, Sun B, Liu B, Fu Y, Zheng P
    PLoS One, 2017;12(11):e0186853.
    PMID: 29095845 DOI: 10.1371/journal.pone.0186853
    Experimental design focuses on describing or explaining the multifactorial interactions that are hypothesized to reflect the variation. The design introduces conditions that may directly affect the variation, where particular conditions are purposely selected for observation. Combinatorial design theory deals with the existence, construction and properties of systems of finite sets whose arrangements satisfy generalized concepts of balance and/or symmetry. In this work, borrowing the concept of "balance" in combinatorial design theory, a novel method for multifactorial bio-chemical experiments design is proposed, where balanced templates in combinational design are used to select the conditions for observation. Balanced experimental data that covers all the influencing factors of experiments can be obtianed for further processing, such as training set for machine learning models. Finally, a software based on the proposed method is developed for designing experiments with covering influencing factors a certain number of times.
    Matched MeSH terms: Models, Theoretical*
  6. Zhou J, Wu C, Yeh PJ, Ju J, Zhong L, Wang S, et al.
    Sci Total Environ, 2023 Sep 01;889:164274.
    PMID: 37209749 DOI: 10.1016/j.scitotenv.2023.164274
    The successive flood-heat extreme (SFHE) event, which threatens the securities of human health, economy, and building environment, has attracted extensive research attention recently. However, the potential changes in SFHE characteristics and the global population exposure to SFHE under anthropogenic warming remain unclear. Here, we present a global-scale evaluation of the projected changes and uncertainties in SFHE characteristics (frequency, intensity, duration, land exposure) and population exposure under the Representative Concentration Pathway (RCP) 2.6 and 6.0 scenarios, based on the multi-model ensembles (five global water models forced by four global climate models) within the Inter-Sectoral Impact Model Intercomparison Project 2b framework. The results reveal that, relative to the 1970-1999 baseline period, the SFHE frequency is projected to increase nearly globally by the end of this century, especially in the Qinghai-Tibet Plateau (>20 events/30-year) and the tropical regions (e.g., northern South America, central Africa, and southeastern Asia, >15 events/30-year). The projected higher SFHE frequency is generally accompanied by a larger model uncertainty. By the end of this century, the SFHE land exposure is expected to increase by 12 % (20 %) under RCP2.6 (RCP6.0), and the intervals between flood and heatwave in SFHE tend to decrease by up to 3 days under both RCPs, implying the more intermittent SFHE occurrence under future warming. The SFHE events will lead to the higher population exposure in the Indian Peninsula and central Africa (<10 million person-days) and eastern Asia (<5 million person-days) due to the higher population density and the longer SFHE duration. Partial correlation analysis indicates that the contribution of flood to the SFHE frequency is greater than that of heatwave for most global regions, but the SFHE frequency is dominated by the heatwave in northern North America and northern Asia.
    Matched MeSH terms: Models, Theoretical
  7. Elhag AA, Mohamad R, Aziz MW, Zeshan F
    PLoS One, 2015;10(4):e0123086.
    PMID: 25928358 DOI: 10.1371/journal.pone.0123086
    The composite service design modeling is an essential process of the service-oriented software development life cycle, where the candidate services, composite services, operations and their dependencies are required to be identified and specified before their design. However, a systematic service-oriented design modeling method for composite services is still in its infancy as most of the existing approaches provide the modeling of atomic services only. For these reasons, a new method (ComSDM) is proposed in this work for modeling the concept of service-oriented design to increase the reusability and decrease the complexity of system while keeping the service composition considerations in mind. Furthermore, the ComSDM method provides the mathematical representation of the components of service-oriented design using the graph-based theoryto facilitate the design quality measurement. To demonstrate that the ComSDM method is also suitable for composite service design modeling of distributed embedded real-time systems along with enterprise software development, it is implemented in the case study of a smart home. The results of the case study not only check the applicability of ComSDM, but can also be used to validate the complexity and reusability of ComSDM. This also guides the future research towards the design quality measurement such as using the ComSDM method to measure the quality of composite service design in service-oriented software system.
    Matched MeSH terms: Models, Theoretical
  8. Tan J, Altice FL, Madden LM, Zelenev A
    Lancet HIV, 2020 02;7(2):e121-e128.
    PMID: 31879250 DOI: 10.1016/S2352-3018(19)30373-X
    BACKGROUND: As HIV incidence and mortality continue to increase in eastern Europe and central Asia, particularly among people who inject drugs (PWID), it is crucial to effectively scale-up opioid agonist therapy (OAT), such as methadone or buprenorphine maintenance therapy, to optimise HIV outcomes. With low OAT coverage among PWID, we did an optimisation assessment using current OAT procurement and allocation, then modelled the effect of increased OAT scale-up on HIV incidence and mortality for 23 administrative regions of Ukraine.

    METHODS: We developed a linear optimisation model to estimate efficiency gains that could be achieved based on current procurement of OAT. We also developed a dynamic, compartmental population model of HIV transmission that included both injection and sexual risk to estimate the effect of OAT scale-up on HIV infections and mortality over a 10-year horizon. The compartmental population model was calibrated to HIV prevalence and incidence among PWID for 23 administrative regions of Ukraine. Sources for regional data included the SyrEx database, the Integrated Biological and Behavioral Survey, the Ukrainian Center for Socially Dangerous Disease Control of the Ministry of Health of Ukraine, the Public Health Center of the Ministry of Health of Ukraine, and the Ukrainian Census.

    FINDINGS: Under a status-quo scenario (OAT coverage of 2·7% among PWID), the number of new HIV infections among PWID in Ukraine over the next 10 years was projected to increase to 58 820 (95% CI 47 968-65 535), with striking regional differences. With optimum allocation of OAT without additional increases in procurement, OAT coverage could increase from 2·7% to 3·3% by increasing OAT doses to ensure higher retention levels. OAT scale-up to 10% and 20% over 10 years would, respectively, prevent 4368 (95% CI 3134-5243) and 10 864 (7787-13 038) new HIV infections and reduce deaths by 7096 (95% CI 5078-9160) and 17 863 (12 828-23 062), relative to the status quo. OAT expansion to 20% in five regions of Ukraine with the highest HIV burden would account for 56% of new HIV infections and 49% of deaths prevented over 10 years.

    INTERPRETATION: To optimise HIV prevention and treatment goals in Ukraine, OAT must be substantially scaled up in all regions. Increased medication procurement is needed, combined with optimisation of OAT dosing. Restricting OAT scale-up to some regions of Ukraine could benefit many PWID, but the regions most affected are not necessarily those with the highest HIV burden.

    FUNDING: National Institute on Drug Abuse.

    Matched MeSH terms: Models, Theoretical
  9. Kura NU, Ramli MF, Ibrahim S, Sulaiman WN, Aris AZ, Tanko AI, et al.
    Environ Sci Pollut Res Int, 2015 Jan;22(2):1512-33.
    PMID: 25163562 DOI: 10.1007/s11356-014-3444-0
    In this work, the DRASTIC and GALDIT models were employed to determine the groundwater vulnerability to contamination from anthropogenic activities and seawater intrusion in Kapas Island. In addition, the work also utilized sensitivity analysis to evaluate the influence of each individual parameter used in developing the final models. Based on these effects and variation indices of the said parameters, new effective weights were determined and were used to create modified DRASTIC and GALDIT models. The final DRASTIC model classified the island into five vulnerability classes: no risk (110-140), low (140-160), moderate (160-180), high (180-200), and very high (>200), covering 4, 26, 59, 4, and 7 % of the island, respectively. Likewise, for seawater intrusion, the modified GALDIT model delineates the island into four vulnerability classes: very low (<90), low (90-110), moderate (110-130), and high (>130) covering 39, 33, 18, and 9 % of the island, respectively. Both models show that the areas that are likely to be affected by anthropogenic pollution and seawater intrusion are within the alluvial deposit at the western part of the island. Pearson correlation was used to verify the reliability of the two models in predicting their respective contaminants. The correlation matrix showed a good relationship between DRASTIC model and nitrate (r = 0.58). In a similar development, the correlation also reveals a very strong negative relationship between GALDIT model and seawater contaminant indicator (resistivity Ωm) values (r = -0.86) suggesting that the model predicts more than 86 % of seawater intrusion. In order to facilitate management strategy, suitable areas for artificial recharge were identified through modeling. The result suggested some areas within the alluvial deposit at the western part of the island as suitable for artificial recharge. This work can serve as a guide for a full vulnerability assessment to anthropogenic pollution and seawater intrusion in small islands and will help policy maker and manager with understanding needed to ensure sustainability of the island's aquifer.
    Matched MeSH terms: Models, Theoretical*
  10. Che Nor Zarida Che Seman, Zamzuri Zakaria
    MyJurnal
    Critical size defects (CSD) in the long bones of New Zealand White rabbits (Oryctolagus cuniculus) have been used for years as an experimental model for investigation of the effectiveness of a new bone substitute material. There are varieties of protocols available in the literature. This technical note attempts to present an alternative surgical technique of a CSD in the New Zealand white rabbit tibia. Methods: Thirty-nine New Zealand White rabbits were used in this study. A CSD of approximately 4.5 mm (width) X 9.0 mm (length) was surgically drilled at the proximal tibial metaphysis, approximately 1 cm from the knee joint. The surrounding of soft tissue was repositioned and sutured layer by layer with bioabsorbable surgical suture. Two x-rays of anteroposterior and lateral were taken before assessed under computed tomography scan at 6, 12 and 24 weeks. Results: This alternative method created CSD with less bleeding from the muscle observed. No mortality or other surgical complications observed within 6 weeks, 12 weeks and 24 weeks following surgery. Conclusion: A simple and safe method for performing CSD was demonstrated and recommended as an alternative approach for surgery on New Zealand White rabbits.
    Matched MeSH terms: Models, Theoretical
  11. Gul S, Zou X, Hassan CH, Azam M, Zaman K
    Environ Sci Pollut Res Int, 2015 Dec;22(24):19773-85.
    PMID: 26282441 DOI: 10.1007/s11356-015-5185-0
    This study investigates the relationship between energy consumption and carbon dioxide emission in the causal framework, as the direction of causality remains has a significant policy implication for developed and developing countries. The study employed maximum entropy bootstrap (Meboot) approach to examine the causal nexus between energy consumption and carbon dioxide emission using bivariate as well as multivariate framework for Malaysia, over a period of 1975-2013. This is a unified approach without requiring the use of conventional techniques based on asymptotical theory such as testing for possible unit root and cointegration. In addition, it can be applied in the presence of non-stationary of any type including structural breaks without any type of data transformation to achieve stationary. Thus, it provides more reliable and robust inferences which are insensitive to time span as well as lag length used. The empirical results show that there is a unidirectional causality running from energy consumption to carbon emission both in the bivariate model and multivariate framework, while controlling for broad money supply and population density. The results indicate that Malaysia is an energy-dependent country and hence energy is stimulus to carbon emissions.
    Matched MeSH terms: Models, Theoretical*
  12. 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
  13. Yasin SM, Taib KM, Zaki RA
    Asian Pac J Cancer Prev, 2011;12(6):1439-43.
    PMID: 22126478
    The transtheoretical model (TTM) has been used as one of the major constructs in developing effective cognitive behavioural interventions for smoking cessation and relapse prevention, in Western societies. This study aimed to examine the reliability and construct validity of the translated Bahasa Malaysia version of TTM questionnaire among adult smokers in Klang Valley, Malaysia. The sample consisted of 40 smokers from four different worksites in Klang Valley. A 26-item TTM questionnaire was administered, and a similar set one week later. The questionnaire consisted of three measures; decisional balance, temptations and impact of smoking. Construct validity was measured by factor analysis and the reliability by Cronbach' s alpha (internal consistency) and test-retest correlation. Results revealed that Cronbach' s alpha coefficients for the items were: decisional balance (0.84; 0.74) and temptations (0.89; 0.54; 0.85). The values for test retest correlation were all above 0.4. In addition, factor analysis suggested two meaningful common factors for decisional balance and three for temptations. This is consistent with the original construct of the TTM questionnaire. Overall results demonstrated that construct validity and reliability were acceptable for all items. In conclusion, the Bahasa Malaysia version of TTM questionnaire is a reliable and valid tool in ass.
    Matched MeSH terms: Models, Theoretical
  14. Kalsum HU, Shah ZA, Othman RM, Hassan R, Rahim SM, Asmuni H, et al.
    Comput Biol Med, 2009 Nov;39(11):1013-9.
    PMID: 19720371 DOI: 10.1016/j.compbiomed.2009.08.002
    Protein domains contain information about the prediction of protein structure, function, evolution and design since the protein sequence may contain several domains with different or the same copies of the protein domain. In this study, we proposed an algorithm named SplitSSI-SVM that works with the following steps. First, the training and testing datasets are generated to test the SplitSSI-SVM. Second, the protein sequence is split into subsequence based on order and disorder regions. The protein sequence that is more than 600 residues is split into subsequences to investigate the effectiveness of the protein domain prediction based on subsequence. Third, multiple sequence alignment is performed to predict the secondary structure using bidirectional recurrent neural networks (BRNN) where BRNN considers the interaction between amino acids. The information of about protein secondary structure is used to increase the protein domain boundaries signal. Lastly, support vector machines (SVM) are used to classify the protein domain into single-domain, two-domain and multiple-domain. The SplitSSI-SVM is developed to reduce misleading signal, lower protein domain signal caused by primary structure of protein sequence and to provide accurate classification of the protein domain. The performance of SplitSSI-SVM is evaluated using sensitivity and specificity on single-domain, two-domain and multiple-domain. The evaluation shows that the SplitSSI-SVM achieved better results compared with other protein domain predictors such as DOMpro, GlobPlot, Dompred-DPS, Mateo, Biozon, Armadillo, KemaDom, SBASE, HMMPfam and HMMSMART especially in two-domain and multiple-domain.
    Matched MeSH terms: Models, Theoretical
  15. Goudarzi S, Haslina Hassan W, Abdalla Hashim AH, Soleymani SA, Anisi MH, Zakaria OM
    PLoS One, 2016;11(7):e0151355.
    PMID: 27438600 DOI: 10.1371/journal.pone.0151355
    This study aims to design a vertical handover prediction method to minimize unnecessary handovers for a mobile node (MN) during the vertical handover process. This relies on a novel method for the prediction of a received signal strength indicator (RSSI) referred to as IRBF-FFA, which is designed by utilizing the imperialist competition algorithm (ICA) to train the radial basis function (RBF), and by hybridizing with the firefly algorithm (FFA) to predict the optimal solution. The prediction accuracy of the proposed IRBF-FFA model was validated by comparing it to support vector machines (SVMs) and multilayer perceptron (MLP) models. In order to assess the model's performance, we measured the coefficient of determination (R2), correlation coefficient (r), root mean square error (RMSE) and mean absolute percentage error (MAPE). The achieved results indicate that the IRBF-FFA model provides more precise predictions compared to different ANNs, namely, support vector machines (SVMs) and multilayer perceptron (MLP). The performance of the proposed model is analyzed through simulated and real-time RSSI measurements. The results also suggest that the IRBF-FFA model can be applied as an efficient technique for the accurate prediction of vertical handover.
    Matched MeSH terms: Models, Theoretical
  16. Lee HW, Ramayah T, Zakaria N
    J Med Syst, 2012 Aug;36(4):2129-40.
    PMID: 21384267 DOI: 10.1007/s10916-011-9675-4
    Studies related to healthcare ICT integration in Malaysia are relatively little, thus this paper provide a literature review of the integration of information and communication technologies (ICT) in the healthcare sector in Malaysia through the hospital information system (HIS). Our study emphasized on secondary data to investigate the factors related to ICT integration in healthcare through HIS. Therefore this paper aimed to gather an in depth understanding of issues related to HIS adoption, and contributing in fostering HIS adoption in Malaysia and other countries. This paper provides a direction for future research to study the correlation of factors affecting HIS adoption. Finally a research model is proposed using current adoption theories and external factors from human, technology, and organization perspectives.
    Matched MeSH terms: Models, Theoretical*
  17. Md Yusof AH, Abd Gani SS, Zaidan UH, Halmi MIE, Zainudin BH
    Molecules, 2019 Feb 16;24(4).
    PMID: 30781448 DOI: 10.3390/molecules24040711
    This study investigates the ultrasound-assisted extraction of flavonoids from Malaysian cocoa shell extracts, and optimization using response surface methodology. There are three variables involved in this study, namely: ethanol concentration (70⁻90 v/v %), temperature (45⁻65 °C), and ultrasound irradiation time (30⁻60 min). All of the data were collected and analyzed for variance (ANOVA). The coefficient of determination (R²) and the model was significant in interaction between all variables (98% and p < 0.0001, respectively). In addition, the lack of fit test for the model was not of significance, with p > 0.0684. The ethanol concentration, temperature, and ultrasound irradiation time that yielded the maximum value of the total flavonoid content (TFC; 7.47 mg RE/g dried weight (DW)) was 80%, 55 °C, and 45 min, respectively. The optimum value from the validation of the experimental TFC was 7.23 ± 0.15 mg of rutin, equivalent per gram of extract with ethanol concentration, temperature, and ultrasound irradiation time values of 74.20%, 49.99 °C, and 42.82 min, respectively. While the modelled equation fits the data, the T-test is not significant, suggesting that the experimental values agree with those predicted by the response surface methodology models.
    Matched MeSH terms: Models, Theoretical
  18. Ahmad Fuad AF, Said MH, Samo K, Rahman MAA, Mohd MH, Zainol I
    ScientificWorldJournal, 2020;2020:6957171.
    PMID: 33414690 DOI: 10.1155/2020/6957171
    Introduction. Trawling is a method of catching fish in a large volume where fish nets are pulled through water using one or two boats. Bottom trawling is where the nets are pulled over on the seabed. The gear of the bottom trawling would impact the exposed subsea pipeline, on the seabed. Subsea pipelines transport crude oil and gas from the offshore platform to shore facility. This study assesses the risk of fish trawling activities to the subsea pipelines at Sabah and Labuan offshore. The specification of trawl equipment used by local trawlers in Sabah was determined by the on-site survey. The frequency of a fish trawler crossing over the pipelines was calculated based interview on operation and site survey. The calculation of the pull-over load of the otter board was calculated using the DNVGL algorithm. The severity and frequency index of the risk matrix was developed based on literature review. Results showed that the pull-over load of the otter board would not damage the pipelines. The risk posed by the fish trawler activity to the pipelines is low and moderate.
    Matched MeSH terms: Models, Theoretical
  19. 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*
  20. Chang SW, Kareem SA, Kallarakkal TG, Merican AF, Abraham MT, Zain RB
    Asian Pac J Cancer Prev, 2011;12(10):2659-64.
    PMID: 22320970
    The incidence of oral cancer is high for those of Indian ethnic origin in Malaysia. Various clinical and pathological data are usually used in oral cancer prognosis. However, due to time, cost and tissue limitations, the number of prognosis variables need to be reduced. In this research, we demonstrated the use of feature selection methods to select a subset of variables that is highly predictive of oral cancer prognosis. The objective is to reduce the number of input variables, thus to identify the key clinicopathologic (input) variables of oral cancer prognosis based on the data collected in the Malaysian scenario. Two feature selection methods, genetic algorithm (wrapper approach) and Pearson's correlation coefficient (filter approach) were implemented and compared with single-input models and a full-input model. The results showed that the reduced models with feature selection method are able to produce more accurate prognosis results than the full-input model and single-input model, with the Pearson's correlation coefficient achieving the most promising results.
    Matched MeSH terms: Models, Theoretical
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