Abstract: This study investigated climatic factors associated
with influenza cases in Southern Thailand. The main aim for use
regression analysis to investigate possible causual relationship of
climatic factors and variability between the border of the Andaman
Sea and the Gulf of Thailand. Southern Thailand had the highest
Influenza incidences among four regions (i.e. north, northeast, central
and southern Thailand). In this study, there were 14 climatic factors:
mean relative humidity, maximum relative humidity, minimum
relative humidity, rainfall, rainy days, daily maximum rainfall,
pressure, maximum wind speed, mean wind speed, sunshine duration,
mean temperature, maximum temperature, minimum temperature,
and temperature difference (i.e. maximum – minimum temperature).
Multiple stepwise regression technique was used to fit the statistical
model. The results indicated that the mean wind speed and the
minimum relative humidity were positively associated with the
number of influenza cases on the Andaman Sea side. The maximum
wind speed was positively associated with the number of influenza
cases on the Gulf of Thailand side.
Abstract: Predicting short term wind speed is essential in order
to prevent systems in-action from the effects of strong winds. It also
helps in using wind energy as an alternative source of energy, mainly
for Electrical power generation. Wind speed prediction has
applications in Military and civilian fields for air traffic control,
rocket launch, ship navigation etc. The wind speed in near future
depends on the values of other meteorological variables, such as
atmospheric pressure, moisture content, humidity, rainfall etc. The
values of these parameters are obtained from a nearest weather
station and are used to train various forms of neural networks. The
trained model of neural networks is validated using a similar set of
data. The model is then used to predict the wind speed, using the
same meteorological information. This paper reports an Artificial
Neural Network model for short term wind speed prediction, which
uses back propagation algorithm.
Abstract: The wind resource in the Italian site of Lendinara
(RO) is analyzed through a systematic anemometric campaign
performed on the top of the bell tower, at an altitude of over 100 m
above the ground. Both the average wind speed and the Weibull
distribution are computed. The resulting average wind velocity is in
accordance with the numerical predictions of the Italian Wind Atlas,
confirming the accuracy of the extrapolation of wind data adopted for
the evaluation of wind potential at higher altitudes with respect to the
commonly placed measurement stations.
Abstract: Contour filter strips planted with perennial vegetation
can be used to improve surface and ground water quality by reducing
pollutant, such as NO3-N, and sediment outflow from cropland to a
river or lake. Meanwhile, the filter strips of perennial grass with biofuel
potentials also have economic benefits of producing ethanol. In
this study, The Soil and Water Assessment Tool (SWAT) model was
applied to the Walnut Creek Watershed to examine the effectiveness
of contour strips in reducing NO3-N outflows from crop fields to the
river or lake. Required input data include watershed topography,
slope, soil type, land-use, management practices in the watershed and
climate parameters (precipitation, maximum/minimum air
temperature, solar radiation, wind speed and relative humidity).
Numerical experiments were conducted to identify potential
subbasins in the watershed that have high water quality impact, and
to examine the effects of strip size and location on NO3-N reduction
in the subbasins under various meteorological conditions (dry,
average and wet). Variable sizes of contour strips (10%, 20%, 30%
and 50%, respectively, of a subbasin area) planted with perennial
switchgrass were selected for simulating the effects of strip size and
location on stream water quality. Simulation results showed that a
filter strip having 10%-50% of the subbasin area could lead to 55%-
90% NO3-N reduction in the subbasin during an average rainfall
year. Strips occupying 10-20% of the subbasin area were found to be
more efficient in reducing NO3-N when placed along the contour
than that when placed along the river. The results of this study can
assist in cost-benefit analysis and decision-making in best water
resources management practices for environmental protection.