69 research outputs found

    Monthly and Diurnal Variability of Rain Rate and Rain Attenuation during the Monsoon Period in Malaysia

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    Rain is the major source of attenuation for microwave propagation above 10 GHz. In tropical and equatorial regions where the rain intensity is higher, designing a terrestrial and earth-to-satellite microwave links is very critical and challenging at these frequencies. This paper presents the preliminary results of rain effects in a 23 GHz terrestrial point-to-point communication link 1.3km long. The experimental test bed had been set up at Skudai, Johor Bahru, Malaysia. In this area, a monsoon equatorial climate prevails and the rainfall rate can reach values well above 100mm/h with significant monthly and diurnal variability. Hence, it is necessary to implement a mitigation technique for maintaining an adequate radio link performance for the action of very heavy rain. Since we now know that the ULPC (Up Link Power Control) cannot guarantee the desired performance, a solution based on frequency band diversity is proposed in this paper. Here, a secondary radio link operating in a frequency not affected by rain (C band for instance) is placed parallel with the main link. Under no rain or light rain conditions, the secondary link carries without priority radio signals. When there is an outage of the main link due to rain, the secondary link assumes the priority traffic. The outcome of the research shows a solution for higher operating frequencies during rainy events

    Zero Truncated Bivariate Poisson Model: Marginal-Conditional Modeling Approach with an Application to Traffic Accident Data

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    Abstract A new covariate dependent zero-truncated bivariate Poisson model is proposed in this paper employing generalized linear model. A marginal-conditional approach is used to show the bivariate model. The proposed model with estimation procedure and tests for goodness-of-fit and under (or over) dispersion are shown and applied to road safety data. Two correlated outcome variables considered in this study are number of cars involved in an accident and number of casualties for given number of cars

    EXPERIMENTAL ANALYSIS ON THE PHOTOVOLTAICTHERMAL SOLAR COLLECTOR WITH COMPOUND PARABOLIC CONCENTRATOR USING PHASE CHANGE MATERIAL-TOWARDS SOLAR ENERGY UTILIZATION

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    In this study, the performance of a photovoltaic-thermal solar collector with compound parabolic collector for clear day in winter and summer season was investigated. Phase change material storage unit, compound parabolic collector unit, photovoltaic thermal unit were integrated into one piece to reduce the area to get higher performance and better concentration ratio. The performance of water flow rate, heat removal factor, amount of energy storage of the collector in winter season and comparison of temperature variation, total generated energy, performance factor in summer season by varying different parameters were evaluated. Water flow rate increases up to 0.004 kg/s corresponding to the thermal efficiency of around 42%. Heat removal factor for thermal collector was in the range of 0.94-0.96, which indicates better energy gain of the system and effective outlet water temperature was found 55 0C in winter season. The total generated thermal energy 1500W and maximum performance factor of a collector was 0.0135 kW-1m2 in summer season. Finally total efficiency of a collector varies from 58% -68% in summer season

    Rice grain cadmium concentrations in the global supply-chain

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    One of cadmium’s major exposure routes to humans is through rice consumption. The concentrations of cadmium in the global polished (white), market rice supply-chain were assessed in 2270 samples, purchased from retailers across 32 countries, encompassing 6 continents. It was found on a global basis that East Africa had the lowest cadmium with a median for both Malawi and Tanzania at 4.9 ÎŒg/kg, an order of magnitude lower than the highest country, China with a median at 69.3 ÎŒg/kg. The Americas were typically low in cadmium, but the Indian sub-continent was universally elevated. In particular certain regions of Bangladesh had high cadmium, that when combined with the high daily consumption rate of rice of that country, leads to high cadmium exposures. Concentrations of cadmium were compared to the European Standard for polished rice of 200 ÎŒg/kg and 5% of the global supply-chain exceeded this threshold. For the stricter standard of 40 ÎŒg/kg for processed infant foods, for which rice can comprise up to 100% by composition (such as rice porridges, puffed rice cereal and cakes), 25% of rice would not be suitable for making pure rice baby foods. Given that rice is also elevated in inorganic arsenic, the only region of the world where both inorganic arsenic and cadmium were low in grain was East Africa

    Transformation of Biomass into Commodity Chemicals Using Enzymes or Cells

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    A generalized right truncated bivariate Poisson regression model with applications to health data.

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    A generalized right truncated bivariate Poisson regression model is proposed in this paper. Estimation and tests for goodness of fit and over or under dispersion are illustrated for both untruncated and right truncated bivariate Poisson regression models using marginal-conditional approach. Estimation and test procedures are illustrated for bivariate Poisson regression models with applications to Health and Retirement Study data on number of health conditions and the number of health care services utilized. The proposed test statistics are easy to compute and it is evident from the results that the models fit the data very well. A comparison between the right truncated and untruncated bivariate Poisson regression models using the test for nonnested models clearly shows that the truncated model performs significantly better than the untruncated model

    Analysis of repeated measures data

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    This book presents a broad range of statistical techniques to address emerging needs in the field of repeated measures. It also provides a comprehensive overview of extensions of generalized linear models for the bivariate exponential family of distributions, which represent a new development in analysing repeated measures data. The demand for statistical models for correlated outcomes has grown rapidly recently, mainly due to presence of two types of underlying associations: associations between outcomes, and associations between explanatory variables and outcomes. The book systematically addresses key problems arising in the modelling of repeated measures data, bearing in mind those factors that play a major role in estimating the underlying relationships between covariates and outcome variables for correlated outcome data. In addition, it presents new approaches to addressing current challenges in the field of repeated measures and models based on conditional and joint probabilities. Markov models of first and higher orders are used for conditional models in addition to conditional probabilities as a function of covariates. Similarly, joint models are developed using both marginal-conditional probabilities as well as joint probabilities as a function of covariates. In addition to generalized linear models for bivariate outcomes, it highlights extended semi-parametric models for continuous failure time data and their applications in order to include models for a broader range of outcome variables that researchers encounter in various fields. The book further discusses the problem of analysing repeated measures data for failure time in the competing risk framework, which is now taking on an increasingly important role in the field of survival analysis, reliability and actuarial science. Details on how to perform the analyses are included in each chapter and supplemented with newly developed R packages and functions along with SAS codes and macro/IML. It is a valuable resource for researchers, graduate students and other users of statistical techniques for analysing repeated measures data

    Parameter estimates for the truncated bivariate poisson models using the data on number of conditions and utilization of healthcare services (HRS, 2010).

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    <p>Parameter estimates for the truncated bivariate poisson models using the data on number of conditions and utilization of healthcare services (HRS, 2010).</p

    A Markov Model for Analyzing Polytomous Outcome Data

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    This paper highlights the estimation and test procedures for multi-state Markov models with covariate dependences in higher orders. Logistic link functions are used to analyze the transition probabilities of three or more states of a Markov model emerging from a longitudinal study. For illustration purpose the models are used for analysis of panel data on Health and Retirement Study conducted in USA during 1992-2002. The applications use self reported data on perceived emotional health at each round of the nationwide survey conducted among the elderly people. Useful and detailed results on the change in the perceived emotional health status among the elderly people are obtained
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