Displaying publications 81 - 100 of 389 in total

Abstract:
Sort:
  1. Wide range of body composition measures are associated with cognitive function in community-dwelling older adults
    Won H, Abdul Manaf Z, Mat Ludin AF, Shahar S
    Geriatr Gerontol Int, 2017 Apr;17(4):554-560.
    PMID: 27231255 DOI: 10.1111/ggi.12753
    AIM: Studies of the association between body composition, both body fat and body muscle, and cognitive function are rarely reported. The aim of the present study was to determine the association between a wide range of body composition measures with cognitive function in older adults.

    METHODS: A total of 2322 Malaysian older adults aged 60 years and older were recruited using multistage random sampling in a population-based cross-sectional study. Out of 2322 older adults recruited, 2309 (48% men) completed assessments on cognitive function and body composition. Cognitive functions were assessed using the Malay version of the Mini-Mental State Examination, the Bahasa Malaysia version of Montreal Cognitive Assessment, Digit Span Test, Digit Symbol Test and Rey Auditory Verbal Learning Test. Body composition included body mass index, mid-upper arm circumference, waist circumference, calf circumference, waist-to-hip ratio, percentage body fat and skeletal muscle mass.

    RESULTS: The association between body composition and cognitive functions was analyzed using multiple linear regression. After adjustment for age, education years, hypertension, hypercholesterolemia, diabetes mellitus, depression, smoking status and alcohol consumption, we found that calf circumference appeared as a significant predictor for all cognitive tests among both men and women (P 

    Matched MeSH terms: Linear Models
  2. Fulltext Development of HPLC Method for Quantification of Sinigrin from Raphanus sativus Roots and Evaluation of Its Anticancer Potential
    Nair AB, Gandhi D, Patel SS, Morsy MA, Gorain B, Attimarad M, et al.
    Molecules, 2020 Oct 26;25(21).
    PMID: 33114598 DOI: 10.3390/molecules25214947
    Sinigrin, a precursor of allyl isothiocyanate, present in the Raphanus sativus exhibits diverse biological activities, and has an immense role against cancer proliferation. Therefore, the objective of this study was to quantify the sinigrin in the R. sativus roots using developed and validated RP-HPLC method and further evaluated its' anticancer activity. To achieve the objective, the roots of R. sativus were lyophilized to obtain a stable powder, which were extracted and passed through an ion-exchange column to obtain sinigrin-rich fraction. The RP-HPLC method using C18 analytical column was used for chromatographic separation and quantification of sinigrin in the prepared fraction, which was attained using the mobile phase consisting of 20 mM tetrabutylammonium: acetonitrile (80:20%, v/v at pH 7.0) at a flow rate of 0.5 mL/min. The chromatographic peak for sinigrin was showed at 3.592 min for pure sinigrin, where a good linearity was achieved within the concentration range of 50 to 800 µg/mL (R2 > 0.99), with an excellent accuracy (-1.37% and -1.29%) and precision (1.43% and 0.94%), for intra and inter-day, respectively. Finally, the MTT assay was performed for the sinigrin-rich fraction using three different human cancer cell lines, viz. prostate cancer (DU-145), colon adenocarcinoma (HCT-15), and melanoma (A-375). The cell-based assays were extended to conduct apoptotic and caspase-3 activities, to determine the mechanism of action of sinigrin in the treatment of cancer. MTT assay showed IC50 values of 15.88, 21.42, and 24.58 µg/mL for DU-145, HCT-15, and A-375 cell lines, respectively. Increased cellular apoptosis and caspase-3 expression were observed with sinigrin-rich fraction, indicating significant increase in overexpression of caspase-3 in DU-145 cells. In conclusion, a simple, sensitive, fast, and accurate RP-HPLC method was developed for the estimation of sinigrin in the prepared fraction. The data observed here indicate that sinigrin can be beneficial in treating prostate cancer possibly by inducing apoptosis.
    Matched MeSH terms: Linear Models
  3. Estimating groundwater recharge using empirical method: a case study in the tropical zone
    Seyed Reza Saghravani, Ismail Yusoff, Sa’ari Mustapha, Seyed Fazlollah Saghravani
    Sains Malaysiana, 2013;42:553-560.
    Estimation and forecast of groundwater recharge and capacity of aquifer are essential issues in water resources investigation. In the current research, groundwater recharge, recharge coefficient and effective rainfall were determined through a case study using empirical methods applicable to the tropical zones. The related climatological data between January 2000 and December 2010 were collected in Selangor, Malaysia. The results showed that groundwater recharge was326.39 mm per year, effective precipitation was 1807.97 mm per year and recharge coefficient was 18% for the study area. In summary, the precipitation converted to recharge, surface runoff and evapotranspiration are 12, 32 and 56% of rainfall, respectively. Correlation between climatic parameters and groundwater recharge showed positive and negative relationships. The highest correlation was found between precipitation and recharge. Linear multiple regressions between
    recharge and measured climatologic data proved significant relationship between recharge and rainfall and wind speed. It was also proven that the proposed model provided an accurate estimation for similar projects.
    Matched MeSH terms: Linear Models
  4. Comparative study of artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS) and multiple linear regression (MLR) for modeling of Cu (II) adsorption from aqueous solution using biochar derived from rambutan (Nephelium lappaceum) peel
    Wong YJ, Arumugasamy SK, Chung CH, Selvarajoo A, Sethu V
    Environ Monit Assess, 2020 Jun 17;192(7):439.
    PMID: 32556670 DOI: 10.1007/s10661-020-08268-4
    Presence of copper within water bodies deteriorates human health and degrades natural environment. This heavy metal in water is treated using a promising biochar derived from rambutan (Nephelium lappaceum) peel through slow pyrolysis. This research compares the efficacies of artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), and multiple linear regression (MLR) models and evaluates their capability in estimating the adsorption efficiency of biochar for the removal of Cu (II) ions based on 480 experimental sets obtained in a laboratory batch study. The effects of operational parameters such as contact time, operating temperature, biochar dosage, and initial Cu (II) ion concentration on removing Cu (II) ions were investigated. Eleven different training algorithms in ANN and 8 different membership functions in ANFIS were compared statistically and evaluated in terms of estimation errors, which are root mean squared error (RMSE), mean absolute error (MAE), and accuracy. The effects of number of hidden neuron in ANN model and fuzzy set combination in ANFIS were studied. In this study, ANFIS model with Gaussian membership function and fuzzy set combination of [4 5 2 3] was found to be the best method, with accuracy of 90.24% and 87.06% for training and testing dataset, respectively. Contribution of this study is that ANN, ANFIS, and MLR modeling techniques were used for the first time to study the adsorption of Cu (II) ions from aqueous solutions using rambutan peel biochar.
    Matched MeSH terms: Linear Models
  5. VIS-NIR spectral signature and quantitative analysis of HeLa and DU145 cell line
    Ghani KA, Sudik S, Omar AF, Mail MH, Seeni A
    Spectrochim Acta A Mol Biomol Spectrosc, 2019 Nov 05;222:117241.
    PMID: 31216502 DOI: 10.1016/j.saa.2019.117241
    Cancer is increasing in incidence and the leading cause of death worldwide. Controlling and reducing cancer requires early detection and technique to accurately detect and quantify predictive biomarkers. Optical spectroscopy has shown promising non-destructive ability to display distinctive spectral characteristics between cancerous and normal tissues from different part of human organ. Nonetheless, not many information is available on spectroscopic properties of cancer cell lines. In this research, the visible-near infrared (VIS-NIR) absorbance spectroscopy measurement of cultured cervical cancer (HeLa) and prostate cancer cells (DU145) lines has been performed to develop spectral signature of cancer cells and to generate algorithm to quantify cancer cells. Spectroscopic measurement on mouse skin fibroblast (L929) was also taken for comparative purposes. In visible region, the raw cells' spectra do not produce any noticeable peak absorbance that provides information on color because the medium used for cells is colorless and transparent. NIR wavelength between 950 and 975 nm exhibit significant peak due to water absorbance by the medium. Development of spectral signature for the cells through the application of regression technique significantly enhances the diverse characteristics between L929, HeLa and DU145. The application of multiple linear regression allows high measurement accuracy of the cells with coefficient of determination above 0.94.
    Matched MeSH terms: Linear Models
  6. Rapid quantification of quinine by multi-stacking in a portable microchip electrophoresis system
    Tai CT, See HH
    Electrophoresis, 2019 02;40(3):455-461.
    PMID: 30450561 DOI: 10.1002/elps.201800398
    A new multi-stacking pre-concentration procedure based on field-enhanced sample injection (FESI), field-amplified sample stacking, and transient isotachophoresis was developed and implemented in a compact microchip electrophoresis (MCE) with a double T-junction glass chip, coupled with an on-chip capacitively coupled contactless conductivity detection (C4 D) system. A mixture of the cationic target analyte and the terminating electrolyte (TE) from the two sample reservoirs was injected under FESI conditions within the two sample-loading channels. At the double T-junction, the stacked analyte zones were further concentrated under field-amplified stacking conditions and then subsequently focused by transient-isotachophoresis and separated along the separation channels. The proposed multi-stacking strategy was verified under a Universal Serial Bus (USB) fluorescence microscope employing Rhodamine 6G as the model analyte. This developed approach was subsequently used to monitor the target quinine present in human plasma samples. The total analysis time for quinine was approximately 200 s with a sensitivity enhancement factor of approximately 61 when compared to the typical gated injection. The detection and quantification limits of the developed approach for quinine were 3.0 μg/mL and 10 μg/mL, respectively, with intraday and interday repeatability (%RSDs, n = 5) of 3.6 and 4.4%. Recoveries in spiked human plasma were 98.1-99.8%.
    Matched MeSH terms: Linear Models
  7. Factors Affecting Quality of Life in Adult Patients with Thalassaemia Major and Intermedia
    Gan GG, Hue YL, Sathar J
    Ann Acad Med Singap, 2016 Nov;45(11):520-523.
    PMID: 27922147
    Matched MeSH terms: Linear Models
  8. Fulltext Influence of refractive condition on retinal vasculature complexity in younger subjects
    Azemin MZ, Daud NM, Ab Hamid F, Zahari I, Sapuan AH
    ScientificWorldJournal, 2014;2014:783525.
    PMID: 25371914 DOI: 10.1155/2014/783525
    The aim of this study was to compare the retinal vasculature complexity between emmetropia, and myopia in younger subjects.
    Matched MeSH terms: Linear Models
  9. Fulltext Crude oil price forecasting based on hybridizing wavelet multiple linear regression model, particle swarm optimization techniques, and principal component analysis
    Shabri A, Samsudin R
    ScientificWorldJournal, 2014;2014:854520.
    PMID: 24895666 DOI: 10.1155/2014/854520
    Crude oil prices do play significant role in the global economy and are a key input into option pricing formulas, portfolio allocation, and risk measurement. In this paper, a hybrid model integrating wavelet and multiple linear regressions (MLR) is proposed for crude oil price forecasting. In this model, Mallat wavelet transform is first selected to decompose an original time series into several subseries with different scale. Then, the principal component analysis (PCA) is used in processing subseries data in MLR for crude oil price forecasting. The particle swarm optimization (PSO) is used to adopt the optimal parameters of the MLR model. To assess the effectiveness of this model, daily crude oil market, West Texas Intermediate (WTI), has been used as the case study. Time series prediction capability performance of the WMLR model is compared with the MLR, ARIMA, and GARCH models using various statistics measures. The experimental results show that the proposed model outperforms the individual models in forecasting of the crude oil prices series.
    Matched MeSH terms: Linear Models*
  10. Fulltext Quality of life among women with breast cancer from Universiti Kebangsaan Malaysia Medical Centre, Malaysia
    Redhwan, A.A., Md Idris, M.N., Zaleha, M.I., Robert, C., Fuad, I., Sami, R.A.
    Malaysian Journal of Community Health, 2008;14(2):46-55.
    MyJurnal
    Introduction : The purpose of this study was to determine the quality of life (QOL) of breast cancer survivors based on socio-demographic and clinical characteristics.
    Methods : A cross-sectional study was performed on 125 breast cancer survivors from the outpatient clinics. FACT-B (Functional Assessment of Cancer Therapy-Breast) questionnaire was used to assess survivors’ QOL.
    Results : Survivors with low body mass index (BMI) (underweight) were found to have the lowest overall QOL. Those who were overweight had a higher overall QOL, and those who were normal-weight had the highest QOL. Low educational level, being underweight and low monthly household income were significantly associated with lower overall QOL Tamoxifen use and employment status were significantly associated with QOL in some domains. Time since diagnosis to QOL interview was significantly associated with greater scores in emotional well-being (EWB). Multiple linear regression indicated that age, marital status, monthly household income, surgery and histological grade were indicative of the patients QOL.
    Conclusion : The four primary factors related to better QOL were high educational level, high income, normal body weight and greater duration from the time of diagnosis to the time of interview. Age, marital status, income, lumpectomy and histological grade were indicative of the patient QOL.
    Study site: Oncology and Surgical clinics; Pusat Perubatan Universiti Kebangsaan Malaysia (PPUKM), Kuala Lumpur, Malaysia
    Matched MeSH terms: Linear Models
  11. Behavioral responses to the influenza A(H1N1) outbreak in Malaysia
    Wong LP, Sam IC
    J Behav Med, 2011 Feb;34(1):23-31.
    PMID: 20680674 DOI: 10.1007/s10865-010-9283-7
    In the setting of the new A(H1N1) outbreak, the study was conducted to assess: (1) fear of the A(H1N1) pandemic; (2) risk avoidance behavior; (3) health-protective behavior; and (4) psychosocial impact in the ethnically diverse population of Malaysia. A cross-sectional, computer-assisted telephone interview was conducted between July 11 and September 12, 2009. A total of 1,050 respondents were interviewed. Fear about the pandemic was high, with 73.2% of respondents reporting themselves as Slightly fearful/Fearful. High risk avoidance and health protective behavior were reported, with 78.0 and 99.0% reporting at least one avoidance and protective behavior respectively. Knowledge was a significant predictor for practice of healthprotective behavior across the three ethnic groups. Level of fear was significantly correlated with number of protective and avoidance behaviors. The study highlights the need for provision of accurate information that increases risk avoidance and health protective behaviors, while at the same time decreases fear or panic in the general public.
    Matched MeSH terms: Linear Models
  12. Blood lead levels of a population group not occupationally exposed to lead in Singapore
    Neo KS, Goh KT, Sam CT
    Southeast Asian J. Trop. Med. Public Health, 2000 Jun;31(2):295-300.
    PMID: 11127329
    A survey was conducted between 1995 and 1997 to assess the impact of introduction of unleaded petrol and other public health measures on the blood lead level of the population. The geometric mean blood lead level of 269 government employees as determined by graphite furnace atomic absorption spectroscopy, was 66.0 microg/l, much lower than that recorded before introduction of lead-free petrol. Using multiple regression analysis, factors significantly associated with blood lead levels were: exposure to traffic, age (>50 years) and active smoking. Passive smoking, exposure to recent paint work, consumption of alcohol and traditional medicine were found not to be significantly associated with the blood lead level.
    Matched MeSH terms: Linear Models
  13. Clinical relevance of VKORC1 (G-1639A and C1173T) and CYP2C9*3 among patients on warfarin
    Teh LK, Langmia IM, Fazleen Haslinda MH, Ngow HA, Roziah MJ, Harun R, et al.
    J Clin Pharm Ther, 2012 Apr;37(2):232-6.
    PMID: 21507031 DOI: 10.1111/j.1365-2710.2011.01262.x
    Testing for cytochrome P450-2C9 (CYP2C9) and vitamin K epoxide reductase complex subunit 1 (VKORC1) variant alleles is recommended by the FDA for dosing of warfarin. However, dose prediction models derived from data obtained in one population may not be applicable to another. We therefore studied the impact of genetic polymorphisms of CYP2C9 and VKORC1 on warfarin dose requirement in Malaysia.
    Matched MeSH terms: Linear Models
  14. Determination of underivatized long chain fatty acids using RP-HPLC with capacitively coupled contactless conductivity detection
    Makahleh A, Saad B, Siang GH, Saleh MI, Osman H, Salleh B
    Talanta, 2010 Apr 15;81(1-2):20-4.
    PMID: 20188881 DOI: 10.1016/j.talanta.2009.11.030
    A reversed-phase high-performance liquid chromatographic method with capacitively coupled contactless conductivity detector (C(4)D) has been developed for the separation and the simultaneous determination of five underivatized long chain fatty acids (FAs), namely myristic, palmitic, stearic, oleic, and linoleic acids. An isocratic elution mode using methanol/1mM sodium acetate (78:22, v/v) as mobile phase with a flow rate of 0.6 mL min(-1) was used. The separation was effected by using a Hypersil ODS C(18) analytical column (250 mm x 4.6 mm x 5 microm) and was operated at 45 degrees C. Calibration curves of the five FAs were well correlated (r(2)>0.999) within the range of 5- 200 microg mL(-1) for stearic acid, and 2-200 microg mL(-1) for the other FAs. The proposed method was tested on four vegetable oils, i.e., pumpkin, soybean, rice bran and palm olein oils; good agreement was found with the standard gas chromatographic (GC) method. The proposed method offers distinct advantages over the official GC method, especially in terms of simplicity, faster separation times and sensitivity.
    Matched MeSH terms: Linear Models
  15. Fulltext Assessment of predictive models for chlorophyll-a concentration of a tropical lake
    Malek S, Syed Ahmad SM, Singh SK, Milow P, Salleh A
    BMC Bioinformatics, 2011;12 Suppl 13:S12.
    PMID: 22372859 DOI: 10.1186/1471-2105-12-S13-S12
    This study assesses four predictive ecological models; Fuzzy Logic (FL), Recurrent Artificial Neural Network (RANN), Hybrid Evolutionary Algorithm (HEA) and multiple linear regressions (MLR) to forecast chlorophyll- a concentration using limnological data from 2001 through 2004 of unstratified shallow, oligotrophic to mesotrophic tropical Putrajaya Lake (Malaysia). Performances of the models are assessed using Root Mean Square Error (RMSE), correlation coefficient (r), and Area under the Receiving Operating Characteristic (ROC) curve (AUC). Chlorophyll-a have been used to estimate algal biomass in aquatic ecosystem as it is common in most algae. Algal biomass indicates of the trophic status of a water body. Chlorophyll- a therefore, is an effective indicator for monitoring eutrophication which is a common problem of lakes and reservoirs all over the world. Assessments of these predictive models are necessary towards developing a reliable algorithm to estimate chlorophyll- a concentration for eutrophication management of tropical lakes.
    Matched MeSH terms: Linear Models*
  16. Fulltext Evaluation of extra virgin olive oil adulteration with edible oils using ATR-FTIR spectroscopy
    Nuraznee Mashodi, Nurul Yani Rahim, Norhayati Muhammad, Saliza Asman
    Malaysian Journal of Applied Sciences, 2020;5(1):35-44.
    MyJurnal
    Extra virgin olive oil (EVOO) is categorized as expensive oil due to high-quality nutritional value. Unfortunately, EVOO is easily adulterated with other low-quality edible oils. Therefore, this study was done to differentiate and analyze the adulteration of EVOO with other edible oils using Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) spectroscopy. The study was used several edible oils included canola oil, corn oil, sunflower oil, and soybean oil as an adulterant for EVOO. The adulterant EVOO samples were prepared by mixing with dissimilar concentrations of the solely edible oils (20 %, 40 %, 60 % and 80 % (v/v)). The main functional groups of EVOO and other edible oils are O-H, C-H, C=C and C=O groups were assigned around 3500 cm-1, 2925 cm-1, 3006 cm-1 and 1745 cm-1 wavenumbers, respectively. From the comparison of EVOO and other adulterant edibles oil spectra, it showed that the EVOO has the lowest absorbance intensity at around 3006 cm-1 represented double bond which is closely related to the composition of oil sample. The adulteration of EVOO was evaluated by analysing the changes in the absorbance based on the linear regression analysis graph of the bands at 3006 and 2925 cm-1 and the limit of detection (LOD) was measured. The graph of A3008/A2925 with good relative coefficients (R2) and lower LOD is more favourable than the linear regression graph of A3006 versus percentage of edible oils added in EVOO. This study showed that ATR-FTIR spectroscopy is a convenient tool for analysing the adulteration of EVOO.
    Matched MeSH terms: Linear Models
  17. Interaction modeling and classification scheme for augmenting the response accuracy of human-robot interaction systems
    Tao H, Rahman MA, Jing W, Li Y, Li J, Al-Saffar A, et al.
    Work, 2021;68(3):903-912.
    PMID: 33720867 DOI: 10.3233/WOR-203424
    BACKGROUND: Human-robot interaction (HRI) is becoming a current research field for providing granular real-time applications and services through physical observation. Robotic systems are designed to handle the roles of humans and assist them through intrinsic sensing and commutative interactions. These systems handle inputs from multiple sources, process them, and deliver reliable responses to the users without delay. Input analysis and processing is the prime concern for the robotic systems to understand and resolve the queries of the users.

    OBJECTIVES: In this manuscript, the Interaction Modeling and Classification Scheme (IMCS) is introduced to improve the accuracy of HRI. This scheme consists of two phases, namely error classification and input mapping. In the error classification process, the input is analyzed for its events and conditional discrepancies to assign appropriate responses in the input mapping phase. The joint process is aided by a linear learning model to analyze the different conditions in the event and input detection.

    RESULTS: The performance of the proposed scheme shows that it is capable of improving the interaction accuracy by reducing the ratio of errors and interaction response by leveraging the information extraction from the discrete and successive human inputs.

    CONCLUSION: The fetched data are analyzed by classifying the errors at the initial stage to achieve reliable responses.

    Matched MeSH terms: Linear Models
  18. Relationship between emotional intelligence and job satisfaction in newly qualified Malaysian dentists
    Pau A, Sabri BA
    Asia Pac J Public Health, 2015 Mar;27(2):NP1733-41.
    PMID: 22743863 DOI: 10.1177/1010539512449855
    Job satisfaction (JS) is considered to be a key factor in workforce retention. This article reports on the association between emotional intelligence (EI) and JS in newly qualified dentistsemployed in the Malaysian 3-year compulsory service. A postal questionnaire survey collected data on sociodemographic and occupational characteristics, EI, and JS. In a sample of 342 (58.9%) respondents, sociodemographic characteristics were not statistically significantly associated with both EI and JS total scores, whereas overseas graduates scored more highly on the EI scale compared with local graduates. Linear regression analysis indicated that EI was the only statistically significant predictor of JS. EI was statistically significantly associated with JS with patient relationships (r = 0.28; P = .001), peer support (r = 0.30; P = .001), professional development (r = 0.21; P = .001), quality of care (r = 0.57; P = .001), supporting staff (r = 0.24;P = .001), overall JS (r = 0.28; P = .001), and total JS score (r = 0.40; P = .001). However, EI was not statistically significantly associated with JS with income (r = 0.06; P = .302). These findings have implications for the development of interventions to enhance EI and JS in order to promote retention of dentists in the public sector.
    Matched MeSH terms: Linear Models
  19. Simultaneous determination of veterinary antibiotics and hormone in broiler manure, soil and manure compost by liquid chromatography-tandem mass spectrometry
    Ho YB, Zakaria MP, Latif PA, Saari N
    J Chromatogr A, 2012 Nov 2;1262:160-8.
    PMID: 23026257 DOI: 10.1016/j.chroma.2012.09.024
    A multi-residue analytical method was developed to quantify nine antibiotics and one hormone in soil, broiler manure and manure compost. The developed method was based on ultrasonic extraction with MeOH:ACN:EDTA:McIlvaine buffer, solid phase extraction (SPE) using HLB (3 cc/60 mg) cartridge, followed by instrumental analysis using liquid chromatography-tandem mass spectrometry (LC-MS/MS) with 25 min total run time. It was validated and tested on soil, broiler manure and manure compost samples and showed that the method is able to simultaneously detect and quantify the target analytes with good selectivity and sensitivity. The developed method was linear in a concentration range from its instrumental quantification limit (IQL) to 500 ng/mL, with correlation coefficients higher than 0.999. The overall method performance was good for the majority of the analytes, with recoveries range from 63% to 121% in all the sample matrices. The method quantification limit (MQL) for the 10 target analytes in the soil, broiler manure and manure compost samples were 2-10, 3-16 and 5-15 μg/kg dry weight (DW), respectively. The method has also included tilmicosin, an antibiotic known to be reported in the environment for the first time. The developed method was then applied on broiler manure samples and its relative manure amended agricultural soil samples to identify and quantify veterinary antibiotic and hormone residues in the environment. These analytes were detected in broiler manure and soil samples, with maximum concentrations reaching up to 78516.1 μg/kg DW (doxycycline) and 1331.4 μg/kg DW (flumequine), respectively. The results showed that the method can potentially be adopted for the analysis of veterinary antibiotic and hormone wastes in solid environmental matrices.
    Matched MeSH terms: Linear Models
  20. MIMO model of an interacting series process for Robust MPC via System Identification
    Wibowo TC, Saad N
    ISA Trans, 2010 Jul;49(3):335-47.
    PMID: 20304404 DOI: 10.1016/j.isatra.2010.02.005
    This paper discusses the empirical modeling using system identification technique with a focus on an interacting series process. The study is carried out experimentally using a gaseous pilot plant as the process, in which the dynamic of such a plant exhibits the typical dynamic of an interacting series process. Three practical approaches are investigated and their performances are evaluated. The models developed are also examined in real-time implementation of a linear model predictive control. The selected model is able to reproduce the main dynamic characteristics of the plant in open-loop and produces zero steady-state errors in closed-loop control system. Several issues concerning the identification process and the construction of a MIMO state space model for a series interacting process are deliberated.
    Matched MeSH terms: Linear Models
Related Terms
Filters
Contact Us

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

External Links