Abstract: Cheating on standardized tests has been a major
concern as it potentially minimizes measurement precision. One
major way to reduce cheating by collusion is to administer multiple
forms of a test. Even with this approach, potential collusion is still
quite large. A Latin-square treatment structure for distributing
multiple forms is proposed to further reduce the colluding potential.
An index to measure the extent of colluding potential is also
proposed. Finally, with a simple algorithm, the various Latin-squares
were explored to find the best structure to keep the colluding
potential to a minimum.
Abstract: Water hyacinth has been used in aquatic systems for
wastewater purification in many years worldwide. The role of water
hyacinth (Eichhornia crassipes) species in polishing nitrate and
phosphorus concentration from municipal wastewater treatment plant
effluent by phytoremediation method was evaluated. The objective
of this project is to determine the removal efficiency of water
hyacinth in polishing nitrate and phosphorus, as well as chemical
oxygen demand (COD) and ammonia. Water hyacinth is considered
as the most efficient aquatic plant used in removing vast range of
pollutants such as organic matters, nutrients and heavy metals. Water
hyacinth, also referred as macrophytes, were cultivated in the
treatment house in a reactor tank of approximately 90(L) x 40(W) x
25(H) in dimension and built with three compartments. Three water
hyacinths were placed in each compartments and water sample in
each compartment were collected in every two days. The plant
observation was conducted by weight measurement, plant uptake and
new young shoot development. Water hyacinth effectively removed
approximately 49% of COD, 81% of ammonia, 67% of phosphorus
and 92% of nitrate. It also showed significant growth rate at starting
from day 6 with 0.33 shoot/day and they kept developing up to 0.38
shoot/day at the end of day 24. From the studies conducted, it was
proved that water hyacinth is capable of polishing the effluent of
municipal wastewater which contains undesirable amount of nitrate
and phosphorus concentration.
Abstract: In order to investigate a PROX microreactor
performance, two-dimensional modeling of the reacting flow
between two parallel plates is performed through a finite volume
method using an improved SIMPLE algorithm. A three-step surface
kinetics including hydrogen oxidation, carbon monoxide oxidation
and water-gas shift reaction is applied for a Pt-Fe/γ-Al2O3 catalyst
and operating temperatures of about 100ºC. Flow pattern, pressure
field, temperature distribution, and mole fractions of species are
found in the whole domain for all cases. Also, the required reactive
length for removing carbon monoxide from about 2% to less than 10
ppm is found. Furthermore, effects of hydraulic diameter, wall
temperature, and inlet mole fraction of air and water are investigated
by considering carbon monoxide selectivity and conversion. It is
found that air and water addition may improve the performance of
the microreactor in carbon monoxide removal in such operating
conditions; this is in agreement with the pervious published results.
Abstract: In this work, study the location of interface in a stirred vessel with Rushton impeller by computational fluid dynamic was presented. To modeling rotating the impeller, sliding mesh (SM) technique was used and standard k-ε model was selected for turbulence closure. Mean tangential, radial and axial velocities and also turbulent kinetic energy (k) and turbulent dissipation rate (ε) in various points of tank was investigated. Results show sensitivity of system to location of interface and radius of 7 to 10cm for interface in the vessel with existence characteristics cause to increase the accuracy of simulation.
Abstract: The purpose of this study was to explore the complex
flow structure a novel active-type micromixer that based on concept of
Wankle-type rotor. The characteristics of this micromixer are two
folds; a rapid mixing of reagents in a limited space due to the
generation of multiple vortices and a graduate increment in dynamic
pressure as the mixed reagents is delivered to the output ports.
Present micro-mixer is consisted of a rotor with shape of triangle
column, a blending chamber and several inlet and outlet ports. The
geometry of blending chamber is designed to make the rotor can be
freely internal rotated with a constant eccentricity ratio. When the
shape of the blending chamber and the rotor are fixed, the effects of
rotating speed of rotor and the relative locations of ports on the mixing
efficiency are numerical studied. The governing equations are
unsteady, two-dimensional incompressible Navier-Stokes equation
and the working fluid is the water. The species concentration equation
is also solved to reveal the mass transfer process of reagents in various
regions then to evaluate the mixing efficiency.
The dynamic mesh technique was implemented to model the
dynamic volume shrinkage and expansion of three individual
sub-regions of blending chamber when the rotor conducted a complete
rotating cycle. Six types of ports configuration on the mixing
efficiency are considered in a range of Reynolds number from 10 to
300. The rapid mixing process was accomplished with the multiple
vortex structures within a tiny space due to the equilibrium of shear
force, viscous force and inertial force. Results showed that the highest
mixing efficiency could be attained in the following conditions: two
inlet and two outlet ports configuration, that is an included angle of 60
degrees between two inlets and an included angle of 120 degrees
between inlet and outlet ports when Re=10.
Abstract: In this work study the location of interface in a stirred vessel with a Concave impeller by computational fluid dynamic was presented. To modeling rotating the impeller, sliding mesh (SM) technique was used and standard k-ε model was selected for turbulence closure. Mean tangential, radial and axial velocities and also turbulent kinetic energy (k) and turbulent dissipation rate (ε) in various points of tank was investigated. Results show sensitivity of system to location of interface and radius of 7 to 10cm for interface in the vessel with existence characteristics cause to increase the accuracy of simulation.
Abstract: Cameron Highlands is a mountainous area subjected
to torrential tropical showers. It extracts 5.8 million liters of water
per day for drinking supply from its rivers at several intake points.
The water quality of rivers in Cameron Highlands, however, has
deteriorated significantly due to land clearing for agriculture,
excessive usage of pesticides and fertilizers as well as construction
activities in rapidly developing urban areas. On the other hand, these
pollution sources known as non-point pollution sources are diverse
and hard to identify and therefore they are difficult to estimate.
Hence, Geographical Information Systems (GIS) was used to provide
an extensive approach to evaluate landuse and other mapping
characteristics to explain the spatial distribution of non-point sources
of contamination in Cameron Highlands. The method to assess
pollution sources has been developed by using Cameron Highlands
Master Plan (2006-2010) for integrating GIS, databases, as well as
pollution loads in the area of study. The results show highest annual
runoff is created by forest, 3.56 × 108 m3/yr followed by urban
development, 1.46 × 108 m3/yr. Furthermore, urban development
causes highest BOD load (1.31 × 106 kgBOD/yr) while agricultural
activities and forest contribute the highest annual loads for
phosphorus (6.91 × 104 kgP/yr) and nitrogen (2.50 × 105 kgN/yr),
respectively. Therefore, best management practices (BMPs) are
suggested to be applied to reduce pollution level in the area.
Abstract: The aim of this research is to use artificial neural networks computing technology for estimating the net heating value (NHV) of crude oil by its Properties. The approach is based on training the neural network simulator uses back-propagation as the learning algorithm for a predefined range of analytically generated well test response. The network with 8 neurons in one hidden layer was selected and prediction of this network has been good agreement with experimental data.
Abstract: Rice, which is the staple food in Sierra Leone, is
consumed on a daily basis. It is the most imperative food crop
extensively grown by farmers across all ecologies in the country.
Though much attention is now given to rice grain production through
the small holder commercialization programme (SHCP), however, no
attention has been given in investigating the limitations faced by rice
producers. This paper will contribute to attempts to overcome the
development challenges caused by food insecurity. The objective of
this paper is thus, to analysis the relationship between rice production
and the domestic retail price of rice. The study employed a log linear
model in which, the quantity of rice produced is the dependent
variable, quantity of rice imported, price of imported rice and price of
domestic rice as explanatory variables. Findings showed that, locally
produced rice is even more expensive than the imported rice per ton,
and almost all the inhabitants in the capital city which hosts about
65% of the entire population of the country favor imported rice, as it
is free from stones with other impurities. On the other hand, to
control price and simultaneously increase rice production, the
government should purchase the rice from the farmers and then sell to private retailers.
Abstract: In this study, active tendons with Proportional Integral
Derivation type controllers were applied to a SDOF and a MDOF
building model. Physical models of buildings were constituted with
virtual springs, dampers and rigid masses. After that, equations of
motion of all degrees of freedoms were obtained. Matlab Simulink
was utilized to obtain the block diagrams for these equations of
motion. Parameters for controller actions were found by using a trial
method. After earthquake acceleration data were applied to the
systems, building characteristics such as displacements, velocities,
accelerations and transfer functions were analyzed for all degrees of
freedoms. Comparisons on displacement vs. time, velocity vs. time,
acceleration vs. time and transfer function (Db) vs. frequency (Hz)
were made for uncontrolled and controlled buildings. The results
show that the method seems feasible.
Abstract: The use of artificial neural network (ANN) modeling
for prediction and forecasting variables in water resources
engineering are being increasing rapidly. Infrastructural applications
of ANN in terms of selection of inputs, architecture of networks,
training algorithms, and selection of training parameters in different
types of neural networks used in water resources engineering have
been reported. ANN modeling conducted for water resources
engineering variables (river sediment and discharge) published in
high impact journals since 2002 to 2011 have been examined and
presented in this review. ANN is a vigorous technique to develop
immense relationship between the input and output variables, and
able to extract complex behavior between the water resources
variables such as river sediment and discharge. It can produce robust
prediction results for many of the water resources engineering
problems by appropriate learning from a set of examples. It is
important to have a good understanding of the input and output
variables from a statistical analysis of the data before network
modeling, which can facilitate to design an efficient network. An
appropriate training based ANN model is able to adopt the physical
understanding between the variables and may generate more effective
results than conventional prediction techniques.
Abstract: Dengue is a mosquito-borne infection that has peaked to an alarming rate in recent decades. It can be found in tropical and sub-tropical climate. In Malaysia, dengue has been declared as one of the national health threat to the public. This study aimed to map the spatial distributions of dengue cases in the district of Hulu Langat, Selangor via a combination of Geographic Information System (GIS) and spatial statistic tools. Data related to dengue was gathered from the various government health agencies. The location of dengue cases was geocoded using a handheld GPS Juno SB Trimble. A total of 197 dengue cases occurring in 2003 were used in this study. Those data then was aggregated into sub-district level and then converted into GIS format. The study also used population or demographic data as well as the boundary of Hulu Langat. To assess the spatial distribution of dengue cases three spatial statistics method (Moran-s I, average nearest neighborhood (ANN) and kernel density estimation) were applied together with spatial analysis in the GIS environment. Those three indices were used to analyze the spatial distribution and average distance of dengue incidence and to locate the hot spot of dengue cases. The results indicated that the dengue cases was clustered (p < 0.01) when analyze using Moran-s I with z scores 5.03. The results from ANN analysis showed that the average nearest neighbor ratio is less than 1 which is 0.518755 (p < 0.0001). From this result, we can expect the dengue cases pattern in Hulu Langat district is exhibiting a cluster pattern. The z-score for dengue incidence within the district is -13.0525 (p < 0.0001). It was also found that the significant spatial autocorrelation of dengue incidences occurs at an average distance of 380.81 meters (p < 0.0001). Several locations especially residential area also had been identified as the hot spots of dengue cases in the district.
Abstract: Although lots of experiments have been done in enhanced oil recovery, the number of experiments which consider the effects of local and global heterogeneity on efficiency of enhanced oil recovery based on the polymer-surfactant flooding is low and rarely done. In this research, we have done numerous experiments of water flooding and polymer-surfactant flooding on a five spot glass micromodel in different conditions such as different positions of layers. In these experiments, five different micromodels with three different pore structures are designed. Three models with different layer orientation, one homogenous model and one heterogeneous model are designed. In order to import the effect of heterogeneity of porous media, three types of pore structures are distributed accidentally and with equal ratio throughout heterogeneous micromodel network according to random normal distribution. The results show that maximum EOR recovery factor will happen in a situation where the layers are orthogonal to the path of mainstream and the minimum EOR recovery factor will happen in a situation where the model is heterogeneous. This experiments show that in polymer-surfactant flooding, with increase of angles of layers the EOR recovery factor will increase and this recovery factor is strongly affected by local heterogeneity around the injection zone.