Displaying publications 141 - 160 of 258 in total

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  1. Dynamic disequilibrium: demographic policies and trends in Asia
    Hull TH, Larson A
    Asia Pac Econ Lit, 1987 May;1(1):25-59.
    PMID: 12314890
    Matched MeSH terms: Forecasting*
  2. Ageing in Asia and the Pacific. A multidimensional cross-national study in four countries
    Andrews GR
    Compr Gerontol C, 1987 Dec;1:24-32.
    PMID: 3502916
    Although ageing is not yet a high priority issue for health planners, policy makers and clinicians in most developing countries, there will be a growing need in coming years to pay more attention to the important health issues associated with population ageing in the developing world. This paper reports some of the relevant findings of a cross-national study (sponsored by the World Health Organization) of the health and social aspects of ageing in four developing countries: Korea, the Philippines, Fiji and Malaysia. The key findings are compared and contrasted with those of a similar 11-country WHO study in Europe. In broad terms, the overall demographic, physical, mental health and social patterns and trends associated with ageing as demonstrated by age group and sex differences were consistent throughout the four countries studied. Comparisons with European findings in other similar studies underlined the fundamental universality of age-related changes in biophysical, behavioural and social characteristics. The importance of the family in developing countries was evident with about three-quarters of those aged 60 and over in the four countries living with children, often in extended family situations. Levels of adverse health-related behaviour and the prospect of changing patterns of morbidity with further increases in the total and proportional numbers of aged persons point to a need for emphasis on preventive health measures and programmes directed to the maintenance of the physical and mental health of the ageing population.
    Matched MeSH terms: Forecasting*
  3. Environmental engineering education for developing countries: framework for the future
    Ujang Z, Henze M, Curtis T, Schertenleib R, Beal LL
    Water Sci Technol, 2004;49(8):1-10.
    PMID: 15193088
    This paper presents the existing philosophy, approach, criteria and delivery of environmental engineering education (E3) for developing countries. In general, environmental engineering is being taught in almost all major universities in developing countries, mostly under civil engineering degree programmes. There is an urgent need to address specific inputs that are particularly important for developing countries with respect to the reality of urbanisation and industrialisation. The main component of E3 in the near future will remain on basic sanitation in most developing countries, with special emphasis on the consumer-demand approach. In order to substantially overcome environmental problems in developing countries, E3 should include integrated urban water management, sustainable sanitation, appropriate technology, cleaner production, wastewater minimisation and financial framework.
    Matched MeSH terms: Forecasting*
  4. Fulltext Prediction of dengue outbreak in Selangor Malaysia using machine learning techniques
    Salim NAM, Wah YB, Reeves C, Smith M, Yaacob WFW, Mudin RN, et al.
    Sci Rep, 2021 01 13;11(1):939.
    PMID: 33441678 DOI: 10.1038/s41598-020-79193-2
    Dengue fever is a mosquito-borne disease that affects nearly 3.9 billion people globally. Dengue remains endemic in Malaysia since its outbreak in the 1980's, with its highest concentration of cases in the state of Selangor. Predictors of dengue fever outbreaks could provide timely information for health officials to implement preventative actions. In this study, five districts in Selangor, Malaysia, that demonstrated the highest incidence of dengue fever from 2013 to 2017 were evaluated for the best machine learning model to predict Dengue outbreaks. Climate variables such as temperature, wind speed, humidity and rainfall were used in each model. Based on results, the SVM (linear kernel) exhibited the best prediction performance (Accuracy = 70%, Sensitivity = 14%, Specificity = 95%, Precision = 56%). However, the sensitivity for SVM (linear) for the testing sample increased up to 63.54% compared to 14.4% for imbalanced data (original data). The week-of-the-year was the most important predictor in the SVM model. This study exemplifies that machine learning has respectable potential for the prediction of dengue outbreaks. Future research should consider boosting, or using, nature inspired algorithms to develop a dengue prediction model.
    Matched MeSH terms: Forecasting/methods*
  5. Fulltext A malaria-control experiment in the interior of Borneo
    De Zulueta J, Lachance F
    Bull World Health Organ, 1956;15(3-5):673-93.
    PMID: 13404443
    A first experiment on malaria control in the interior of Borneo by spraying with residual insecticides is described. The work was carried out in the isolated, sparsely populated valleys of the Baram River and its tributary, the Tinjar, in northern Sarawak. The experimental area was divided into three parts: a DDT test area, where a 75% suspension of wettable powder was applied at the rate of 2 g of DDT per m(2) of surface; a BHC test area, where a 50% suspension of wettable powder was applied at the rate of 0.10 g of gamma isomer per m(2); and a check area.Entomological investigations made before the spraying operations were started showed that Anopheles leucosphyrus Dönitz, 1901 was the main malaria vector in both the test and the check areas. Out of a total of 7568 A. leucosphyrus dissected, 30 gland infections were detected-a sporozoite-rate of 0.40%. A. barbirostris was found to be a secondary vector throughout the experimental area.THE RESULTS OF INSECTICIDE SPRAYING WERE SATISFACTORY: in the DDT test area, the spleen-rate fell from 51.8% to 25.1%, and the parasite-rate from 35.6% to 1.6%, in 21 months, and a similar reduction in the rates was observed in the BHC test area. In the check area, the spleen- and parasite-rates rose during the period of observations. It is considered that if such a degree of control can be obtained in 21 months, complete eradication can be expected in the near future.Although BHC spraying proved effective, the fact that it has to be repeated every three months makes it impracticable in the interior of Sarawak, where communications are very poor and difficulties of transport very great. DDT spraying, which need only be done twice a year, is therefore to be preferred. The cost of the DDT operations-US$ 0.45 per person protected per year-is comparatively high, owing to the difficulty of communications and to the necessity for spraying not only the village "longhouses", but also the temporary shelters which the semi-nomadic people in the interior of Sarawak build each year in the rice-fields.
    Matched MeSH terms: Forecasting*
  6. A comparative study of clonal selection algorithm for effluent removal forecasting in septic sludge treatment plant
    Chun TS, Malek MA, Ismail AR
    Water Sci Technol, 2015;71(4):524-8.
    PMID: 25746643 DOI: 10.2166/wst.2014.451
    The development of effluent removal prediction is crucial in providing a planning tool necessary for the future development and the construction of a septic sludge treatment plant (SSTP), especially in the developing countries. In order to investigate the expected functionality of the required standard, the prediction of the effluent quality, namely biological oxygen demand, chemical oxygen demand and total suspended solid of an SSTP was modelled using an artificial intelligence approach. In this paper, we adopt the clonal selection algorithm (CSA) to set up a prediction model, with a well-established method - namely the least-square support vector machine (LS-SVM) as a baseline model. The test results of the case study showed that the prediction of the CSA-based SSTP model worked well and provided model performance as satisfactory as the LS-SVM model. The CSA approach shows that fewer control and training parameters are required for model simulation as compared with the LS-SVM approach. The ability of a CSA approach in resolving limited data samples, non-linear sample function and multidimensional pattern recognition makes it a powerful tool in modelling the prediction of effluent removals in an SSTP.
    Matched MeSH terms: Forecasting
  7. A time series based sequence prediction algorithm to detect activities of daily living in smart home
    Marufuzzaman M, Reaz MB, Ali MA, Rahman LF
    Methods Inf Med, 2015;54(3):262-70.
    PMID: 25604028 DOI: 10.3414/ME14-01-0061
    OBJECTIVES: The goal of smart homes is to create an intelligent environment adapting the inhabitants need and assisting the person who needs special care and safety in their daily life. This can be reached by collecting the ADL (activities of daily living) data and further analysis within existing computing elements. In this research, a very recent algorithm named sequence prediction via enhanced episode discovery (SPEED) is modified and in order to improve accuracy time component is included.

    METHODS: The modified SPEED or M-SPEED is a sequence prediction algorithm, which modified the previous SPEED algorithm by using time duration of appliance's ON-OFF states to decide the next state. M-SPEED discovered periodic episodes of inhabitant behavior, trained it with learned episodes, and made decisions based on the obtained knowledge.

    RESULTS: The results showed that M-SPEED achieves 96.8% prediction accuracy, which is better than other time prediction algorithms like PUBS, ALZ with temporal rules and the previous SPEED.

    CONCLUSIONS: Since human behavior shows natural temporal patterns, duration times can be used to predict future events more accurately. This inhabitant activity prediction system will certainly improve the smart homes by ensuring safety and better care for elderly and handicapped people.

    Matched MeSH terms: Forecasting
  8. Fulltext Partial discharge characteristics of polymer nanocomposite materials in electrical insulation: a review of sample preparation techniques, analysis methods, potential applications, and future trends
    Izzati WA, Arief YZ, Adzis Z, Shafanizam M
    ScientificWorldJournal, 2014;2014:735070.
    PMID: 24558326 DOI: 10.1155/2014/735070
    Polymer nanocomposites have recently been attracting attention among researchers in electrical insulating applications from energy storage to power delivery. However, partial discharge has always been a predecessor to major faults and problems in this field. In addition, there is a lot more to explore, as neither the partial discharge characteristic in nanocomposites nor their electrical properties are clearly understood. By adding a small amount of weight percentage (wt%) of nanofillers, the physical, mechanical, and electrical properties of polymers can be greatly enhanced. For instance, nanofillers in nanocomposites such as silica (SiO2), alumina (Al2O3) and titania (TiO2) play a big role in providing a good approach to increasing the dielectric breakdown strength and partial discharge resistance of nanocomposites. Such polymer nanocomposites will be reviewed thoroughly in this paper, with the different experimental and analytical techniques used in previous studies. This paper also provides an academic review about partial discharge in polymer nanocomposites used as electrical insulating material from previous research, covering aspects of preparation, characteristics of the nanocomposite based on experimental works, application in power systems, methods and techniques of experiment and analysis, and future trends.
    Matched MeSH terms: Forecasting
  9. Forecasting asthma-related hospital admissions in London using negative binomial models
    Soyiri IN, Reidpath DD, Sarran C
    Chron Respir Dis, 2013 May;10(2):85-94.
    PMID: 23620439 DOI: 10.1177/1479972313482847
    Health forecasting can improve health service provision and individual patient outcomes. Environmental factors are known to impact chronic respiratory conditions such as asthma, but little is known about the extent to which these factors can be used for forecasting. Using weather, air quality and hospital asthma admissions, in London (2005-2006), two related negative binomial models were developed and compared with a naive seasonal model. In the first approach, predictive forecasting models were fitted with 7-day averages of each potential predictor, and then a subsequent multivariable model is constructed. In the second strategy, an exhaustive search of the best fitting models between possible combinations of lags (0-14 days) of all the environmental effects on asthma admission was conducted. Three models were considered: a base model (seasonal effects), contrasted with a 7-day average model and a selected lags model (weather and air quality effects). Season is the best predictor of asthma admissions. The 7-day average and seasonal models were trivial to implement. The selected lags model was computationally intensive, but of no real value over much more easily implemented models. Seasonal factors can predict daily hospital asthma admissions in London, and there is a little evidence that additional weather and air quality information would add to forecast accuracy.
    Matched MeSH terms: Forecasting
  10. Regional landfills methane emission inventory in Malaysia
    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: Forecasting
  11. 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: Forecasting
  12. Transformation of nitrogen dioxide into ozone and prediction of ozone concentrations using multiple linear regression techniques
    Ghazali NA, Ramli NA, Yahaya AS, Yusof NF, Sansuddin N, Al Madhoun WA
    Environ Monit Assess, 2010 Jun;165(1-4):475-89.
    PMID: 19440846 DOI: 10.1007/s10661-009-0960-3
    Analysis and forecasting of air quality parameters are important topics of atmospheric and environmental research today due to the health impact caused by air pollution. This study examines transformation of nitrogen dioxide (NO(2)) into ozone (O(3)) at urban environment using time series plot. Data on the concentration of environmental pollutants and meteorological variables were employed to predict the concentration of O(3) in the atmosphere. Possibility of employing multiple linear regression models as a tool for prediction of O(3) concentration was tested. Results indicated that the presence of NO(2) and sunshine influence the concentration of O(3) in Malaysia. The influence of the previous hour ozone on the next hour concentrations was also demonstrated.
    Matched MeSH terms: Forecasting
  13. Comparison between field experiment and PERSIST model simulation: dissipation of fenvalerate in a Malaysian agricultural soil
    Ismail BS, Maznah Z
    Bull Environ Contam Toxicol, 2005 Jun;74(6):1143-50.
    PMID: 16158853
    Matched MeSH terms: Forecasting
  14. Solid waste forecasting using modified ANFIS modeling
    Younes MK, Nopiah ZM, Basri NE, Basri H, Abushammala MF, K N A M
    J Air Waste Manag Assoc, 2015 Oct;65(10):1229-38.
    PMID: 26223583 DOI: 10.1080/10962247.2015.1075919
    Solid waste prediction is crucial for sustainable solid waste management. Usually, accurate waste generation record is challenge in developing countries which complicates the modelling process. Solid waste generation is related to demographic, economic, and social factors. However, these factors are highly varied due to population and economy growths. The objective of this research is to determine the most influencing demographic and economic factors that affect solid waste generation using systematic approach, and then develop a model to forecast solid waste generation using a modified Adaptive Neural Inference System (MANFIS). The model evaluation was performed using Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and the coefficient of determination (R²). The results show that the best input variables are people age groups 0-14, 15-64, and people above 65 years, and the best model structure is 3 triangular fuzzy membership functions and 27 fuzzy rules. The model has been validated using testing data and the resulted training RMSE, MAE and R² were 0.2678, 0.045 and 0.99, respectively, while for testing phase RMSE =3.986, MAE = 0.673 and R² = 0.98.
    Matched MeSH terms: Forecasting
  15. Comparison of field measurements to predicted reaeration coefficients, k2, in the application of a water quality model, QUAL2E, to a tropical river
    Mohamed M, Stednick JD, Smith FM
    Water Sci Technol, 2002;46(9):47-54.
    PMID: 12448451
    Some of the many tools used for watershed management are mathematical and computer models for wasteload allocations. QUAL2E is one of the most popular water quality models used for such purposes. The question arises as to whether the model is applicable in a different climate such as that in the tropics. In this study, QUAL2E was used to model Sg. Selangor River in Malaysia using the predictive equations for reaeration coefficient (k2) within the model and the measured reaeration coefficients for the river. The study results indicated that use of the reaeration coefficient (k2) measured at Sg. Selangor River did give the lowest standard error (SE) for the simulation of water quality during the 7Q10 low-flow period which is considered as the worst scene scenario in water quality modeling. But during calibration and validation using actual low-flow discharge data, the measured reaeration coefficients did not give the lowest standard error (SE). In conclusion, the results indicated that QUAL2E is applicable in tropical rivers when used with the modeled river parameters (i.e. hydraulic parameters, meteorological conditions etc.). Measured reaeration coefficients produced good results and several predictive equations also produced comparatively good results.
    Matched MeSH terms: Forecasting
  16. Predicting arsenic solubility in contaminated soils using isotopic dilution techniques
    Tye AM, Young SD, Crout NM, Zhang H, Preston S, Bailey EH, et al.
    Environ Sci Technol, 2002 Mar 1;36(5):982-8.
    PMID: 11924544
    An isotopic dilution assay was developed to measure radiolabile As concentration in a diverse range of soils (pH 3.30-7.62; % C = 1.00-6.55). Soils amended with 50 mg of As kg(-1) (as Na2HAsO4 x 7H2O) were incubated for over 800 d in an aerated "microcosm" experiment. After 818 d, radiolabile As ranged from 27 to 57% of total applied As and showed a pH-dependent increase above pH 6. The radiolabile assay was also applied to three sets of soils historically contaminated with sewage sludge or mine-spoil. Results reflected the various geochemical forms in which the arsenic was present. On soils from a sewage disposal facility, radiolabile arsenate ranged from 3 to 60% of total As; mean lability was lower than in the equivalent pH range of the microcosm soils, suggesting occlusion of As into calcium phosphate compounds in the sludge-amended soils. In soils from mining areas in the U.K. and Malaysia, radiolabile As accounted for 0.44-19% of total As. The lowest levels of lability were associated with extremely large As concentrations, up to 17,000 mg kg(-1), from arsenopyrite. Soil pore water was extracted from the microcosm experiment and speciated using "GEOCHEM". The solid<==>solution equilibria of As in the microcosm soils was described by a simple model based on competition between HAsO4(2-) and HPO4(2-) for "labile" adsorption sites.
    Matched MeSH terms: Forecasting
  17. Dengue vector control: present status and future prospects
    Yap HH, Chong NL, Foo AE, Lee CY
    Gaoxiong Yi Xue Ke Xue Za Zhi, 1994 Dec;10 Suppl:S102-8.
    PMID: 7844836
    Dengue Fever (DF) and Dengue Haemorrhagic Fever (DHF) have been the most common urban diseases in Southeast Asia since the 1950s. More recently, the diseases have spread to Central and South America and are now considered as worldwide diseases. Both Aedes aegypti and Aedes albopictus are involved in the transmission of DF/DHF in Southeast Asian region. The paper discusses the present status and future prospects of Aedes control with reference to the Malaysian experience. Vector control approaches which include source reduction and environmental management, larviciding with the use of chemicals (synthetic insecticides and insect growth regulators and microbial insecticide), and adulticiding which include personal protection measures (household insecticide products and repellents) for long-term control and space spray (both thermal fogging and ultra low volume sprays) as short-term epidemic measures are discussed. The potential incorporation of IGRs and Bacillus thuringiensis-14 (Bti) as larvicides in addition to insecticides (temephos) is discussed. The advantages of using water-based spray over the oil-based (diesel) spray and the use of spray formulation which provide both larvicidal and adulticidal effects that would consequently have greater impact on the overall vector and disease control in DF/DHF are highlighted.
    Matched MeSH terms: Forecasting
  18. Present status of cancer treatment in several Asian countries
    Puribhat S
    Gan To Kagaku Ryoho, 1992 Jul;19(8 Suppl):1153-9.
    PMID: 1514828
    Most of Asian Countries are still developing. Hence there are constraints in cancer treatment. There are those countries with fully equipped and fully distributed like western world such as Japan, Korea and Singapore. Other with some comprehensive cancer centers but confine to only big cities with poor coverage of the population resulting in a lot of late cases of cancer patients seen. Such countries are Bangladesh, China, India, Indonesia, Malaysia, Sri-Lanka, Thailand and etc. Still a lot of countries have no facilities to cope with cancer patients such as Brunei, Kampuchea, Laos, Nepal, Vietnam and etc. International collaboration and supports are needed.
    Matched MeSH terms: Forecasting
  19. Prospects and programs for fertility reduction, 1990-2015
    Mauldin WP, Ross JA
    Stud Fam Plann, 1994 Mar-Apr;25(2):77-95.
    PMID: 8059448 DOI: 10.2307/2138086
    What is the likelihood that each of the 37 developing countries with populations of 15 million or more in 1990 will reach replacement fertility by the year 2015? These countries have a combined population of 3.9 billion, 91 percent of the population of all developing countries. For this article, a composite index was used as the basis for predicting future levels of total fertility. The index was constructed from socioeconomic variables (life expectancy at birth, infant mortality rates, percent adult literacy, ratio of children enrolled in primary or secondary school, percent of the labor force in nonagricultural occupations, gross national product per capita, and percent of the population living in urban areas), total fertility rates for the years 1985-90, total fertility rate decline from 1960-65 to 1985-90, family planning program effort scores in 1989, and the level of contraceptive prevalence in 1990. Eight countries are classified as certain to reach replacement fertility by 2015, and an additional thirteen probably will also. Five countries are classified as possibly reaching replacement fertility, and eleven as unlikely to do so.
    Matched MeSH terms: Forecasting
  20. Mortality in Asia
    WHO Chron, 1981;35(5):163-7.
    PMID: 7324457
    Matched MeSH terms: Forecasting
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