Abstract: Estimation of stormwater pollutants is a pre-requisite
for the protection and improvement of the aquatic environment and
for appropriate management options. The usual practice for the
stormwater quality prediction is performed through water quality
modeling. However, the accuracy of the prediction by the models
depends on the proper estimation of model parameters. This paper
presents the estimation of model parameters for a catchment water
quality model developed for the continuous simulation of stormwater
pollutants from a catchment to the catchment outlet. The model is
capable of simulating the accumulation and transportation of the
stormwater pollutants; suspended solids (SS), total nitrogen (TN) and
total phosphorus (TP) from a particular catchment. Rainfall and water
quality data were collected for the Hotham Creek Catchment (HTCC),
Gold Coast, Australia. Runoff calculations from the developed model
were compared with the calculated discharges from the widely used
hydrological models, WBNM and DRAINS. Based on the measured
water quality data, model water quality parameters were calibrated
for the above-mentioned catchment. The calibrated parameters are
expected to be helpful for the best management practices (BMPs)
of the region. Sensitivity analyses of the estimated parameters were
performed to assess the impacts of the model parameters on overall
model estimations of runoff water quality.
Abstract: The hydro-mechanical model for unsaturated soils has
been presented based on the effective stress principle taking into
account effects of drying-wetting process. The elasto-plastic
constitutive equations for stress-strain relations of the soil skeleton
have been established. A plasticity model is modified from modified
Cam-Clay model. The hardening rule has been established by
considering the isotropic consolidation paths. The effect of dryingwetting
process is introduced through the ¤ç parameter. All model
coefficients are identified in terms of measurable parameters. The
simulations from the proposed model are compared with the
experimental results. The model calibration was performed to extract
the model parameter from the experimental results. Good agreement
between the results predicted using proposed model and the
experimental results was obtained.
Abstract: In this paper, the processing of sonar signals has been
carried out using Minimal Resource Allocation Network (MRAN)
and a Probabilistic Neural Network (PNN) in differentiation of
commonly encountered features in indoor environments. The
stability-plasticity behaviors of both networks have been
investigated. The experimental result shows that MRAN possesses
lower network complexity but experiences higher plasticity than
PNN. An enhanced version called parallel MRAN (pMRAN) is
proposed to solve this problem and is proven to be stable in
prediction and also outperformed the original MRAN.
Abstract: Geographic Profiling has successfully assisted investigations for serial crimes. Considering the multi-cluster feature of serial criminal spots, we propose a Multi-point Centrography model as a natural extension of Single-point Centrography for geographic profiling. K-means clustering is first performed on the data samples and then Single-point Centrography is adopted to derive a probability distribution on each cluster. Finally, a weighted combinations of each distribution is formed to make next-crime spot prediction. Experimental study on real cases demonstrates the effectiveness of our proposed model.
Abstract: The objective of this work was to examine the changes
in non destructive properties caused by carbonation of CEM II
mortar. Samples of CEM II mortar were prepared and subjected to
accelerated carbonation at 20°C, 65% relative humidity and 20% CO2
concentration. We examined the evolutions of the gas permeability,
the thermal conductivity, the thermal diffusivity, the volume of the
solid phase by helium pycnometry, the longitudinal and transverse
ultrasonic velocities. The principal contribution of this work is that,
apart of the gas permeability, changes in other non destructive
properties have never been studied during the carbonation of cement
materials. These properties are important in predicting/measuring the
durability of reinforced concrete in CO2 environment. The
carbonation depth and the porosity accessible to water were also
reported in order to explain comprehensively the changes in non
destructive parameters.
Abstract: Soil erosion is the most serious problem faced at
global and local level. So planning of soil conservation measures has
become prominent agenda in the view of water basin managers. To
plan for the soil conservation measures, the information on soil
erosion is essential. Universal Soil Loss Equation (USLE), Revised
Universal Soil Loss Equation 1 (RUSLE1or RUSLE) and Modified
Universal Soil Loss Equation (MUSLE), RUSLE 1.06, RUSLE1.06c,
RUSLE2 are most widely used conventional erosion estimation
methods. The essential drawbacks of USLE, RUSLE1 equations are
that they are based on average annual values of its parameters and so
their applicability to small temporal scale is questionable. Also these
equations do not estimate runoff generated soil erosion. So
applicability of these equations to estimate runoff generated soil
erosion is questionable. Data used in formation of USLE, RUSLE1
equations was plot data so its applicability at greater spatial scale
needs some scale correction factors to be induced. On the other hand
MUSLE is unsuitable for predicting sediment yield of small and large
events. Although the new revised forms of USLE like RUSLE 1.06,
RUSLE1.06c and RUSLE2 were land use independent and they have
almost cleared all the drawbacks in earlier versions like USLE and
RUSLE1, they are based on the regional data of specific area and
their applicability to other areas having different climate, soil, land
use is questionable. These conventional equations are applicable for
sheet and rill erosion and unable to predict gully erosion and spatial
pattern of rills. So the research was focused on development of nonconventional
(other than conventional) methods of soil erosion
estimation. When these non-conventional methods are combined with
GIS and RS, gives spatial distribution of soil erosion. In the present
paper the review of literature on non- conventional methods of soil
erosion estimation supported by GIS and RS is presented.
Abstract: This paper presents a CFD analysis of the flow field
around a thin flat plate of infinite span inclined at 90° to a fluid
stream of infinite extent. Numerical predictions have been compared
to experimental measurements, in order to assess the potential of the
finite volume code of determining the aerodynamic forces acting on a
bluff body invested by a fluid stream of infinite extent.
Several turbulence models and spatial node distributions have
been tested. Flow field characteristics in the neighborhood of the flat
plate have been investigated, allowing the development of a
preliminary procedure to be used as guidance in selecting the
appropriate grid configuration and the corresponding turbulence
model for the prediction of the flow field over a two-dimensional
vertical flat plate.
Abstract: In this paper, a Neural Network based predictive
DTC algorithm is proposed .This approach is used as an
alternative to classical approaches .An appropriate riate Feed -
forward network is chosen and based on its value of
derivative electromagnetic torque ; optimal stator voltage
vector is determined to be applied to the induction motor (by
inverter). Moreover, an appropriate torque and flux observer
is proposed.
Abstract: In this paper, we propose a high capacity image hiding
technology based on pixel prediction and the difference of modified histogram. This approach is used the pixel prediction and the
difference of modified histogram to calculate the best embedding point.
This approach can improve the predictive accuracy and increase the pixel difference to advance the hiding capacity. We also use the
histogram modification to prevent the overflow and underflow. Experimental results demonstrate that our proposed method within the
same average hiding capacity can still keep high quality of image and low distortion
Abstract: The paper shows how the perceptions of five organizational virtuousness dimensions (optimism, trust, compassion, integrity, and forgiveness) explain organizational citizenship behaviors (altruism, sportsmanship, courtesy, conscientiousness, and civic virtue). A sample comprising 216 individuals from 14 industrial organizations was collected. Individuals reported their perceptions of organizational virtuousness, their organizational citizenship behaviors (OCB) being reported by their supervisors. The main findings are the following: (a) the perceptions of trust predict altruism; (b) the perceptions of integrity predict civic virtue.
Abstract: This paper deals with behavior and capacity of
punching shear force for flat slabs produced from steel fiber
reinforced self compacting concrete (SFRSCC) by application
nonlinear finite element method. Nonlinear finite element analysis on
nine slab specimens was achieved by using ANSYS software. A
general description of the finite element method, theoretical modeling
of concrete and reinforcement are presented. The nonlinear finite
element analysis program ANSYS is utilized owing to its capabilities
to predict either the response of reinforced concrete slabs in the post
elastic range or the ultimate strength of a flat slabs produced from
steel fiber reinforced self compacting concrete (SFRSCC). In order to
verify the analytical model used in this research using test results of
the experimental data, the finite element analysis were performed
then a parametric study of the effect ratio of flexural reinforcement,
ratio of the upper reinforcement, and volume fraction of steel fibers
were investigated. A comparison between the experimental results
and those predicted by the existing models are presented. Results and
conclusions may be useful for designers, have been raised, and
represented.
Abstract: This study presents the application of artificial
neural network for modeling the phenolic compound
migration through vertical soil column. A three layered feed
forward neural network with back propagation training
algorithm was developed using forty eight experimental data
sets obtained from laboratory fixed bed vertical column tests.
The input parameters used in the model were the influent
concentration of phenol(mg/L) on the top end of the soil
column, depth of the soil column (cm), elapsed time after
phenol injection (hr), percentage of clay (%), percentage of
silt (%) in soils. The output of the ANN was the effluent
phenol concentration (mg/L) from the bottom end of the soil
columns. The ANN predicted results were compared with the
experimental results of the laboratory tests and the accuracy of
the ANN model was evaluated.
Abstract: This paper presented the results of an experimental
investigation into the axial fatigue behavior of a 5086 aluminum
alloy which have several notch-aspect ratios a0/c0 and notch
thickness ratio a/t with semi-elliptical surface cracks. Tests were
conducted in la b air for stress levels of 50 % of their yield
strength. Experiments were carried out for various notch to
thickness ratios. Crack growth rates of test specimens both in
surface and depth directions were determined by using die
penetration method. Fuzzy Logic method was used to predict the
deep direction crack growth because the dept of the crack is
considerably difficult to measure.
Abstract: This paper present a new way to find the aerodynamic
characteristic equation of missile for the numerical trajectories
prediction more accurate. The goal is to obtain the polynomial
equation based on two missile characteristic parameters, angle of
attack (α ) and flight speed (ν ). First, the understudied missile is
modeled and used for flow computational model to compute
aerodynamic force and moment. Assume that performance range of
understudied missile where range -10< α
Abstract: The paper compares different channel models used for
modeling Broadband Power-Line Communication (BPLC) system.
The models compared are Zimmermann and Dostert, Philipps,
Anatory et al and Anatory et al generalized Transmission Line (TL)
model. The validity of each model was compared in time domain
with ATP-EMTP software which uses transmission line approach. It
is found that for a power-line network with minimum number of
branches all the models give similar signal/pulse time responses
compared with ATP-EMTP software; however, Zimmermann and
Dostert model indicates the same amplitude but different time delay.
It is observed that when the numbers of branches are increased only
generalized TL theory approach results are comparable with ATPEMTP
results. Also the Multi-Carrier Spread Spectrum (MC-SS)
system was applied to check the implication of such behavior on the
modulation schemes. It is observed that using Philipps on the
underground cable can predict the performance up to 25dB better
than other channel models which can misread the actual performance
of the system. Also modified Zimmermann and Dostert under
multipath can predict a better performance of about 5dB better than
the actual predicted by Generalized TL theory. It is therefore
suggested for a realistic BPLC system design and analyses the model
based on generalized TL theory be used.
Abstract: Amount of dissolve oxygen in a river has a great direct affect on aquatic macroinvertebrates and this would influence on the region ecosystem indirectly. In this paper it is tried to predict dissolved oxygen in rivers by employing an easy Fuzzy Logic Modeling, Wang Mendel method. This model just uses previous records to estimate upcoming values. For this purpose daily and hourly records of eight stations in Au Sable watershed in Michigan, United States are employed for 12 years and 50 days period respectively. Calculations indicate that for long period prediction it is better to increase input intervals. But for filling missed data it is advisable to decrease the interval. Increasing partitioning of input and output features influence a little on accuracy but make the model too time consuming. Increment in number of input data also act like number of partitioning. Large amount of train data does not modify accuracy essentially, so, an optimum training length should be selected.
Abstract: Importance of software quality is increasing leading to development of new sophisticated techniques, which can be used in constructing models for predicting quality attributes. One such technique is Artificial Neural Network (ANN). This paper examined the application of ANN for software quality prediction using Object- Oriented (OO) metrics. Quality estimation includes estimating maintainability of software. The dependent variable in our study was maintenance effort. The independent variables were principal components of eight OO metrics. The results showed that the Mean Absolute Relative Error (MARE) was 0.265 of ANN model. Thus we found that ANN method was useful in constructing software quality model.
Abstract: In this paper, a methodology of a model based on
predicting the tool forces oblique machining are introduced by
adopting the orthogonal technique. The applied analytical calculation
is mostly based on Devries model and some parts of the methodology
are employed from Amareggo-Brown model. Model validation is
performed by comparing experimental data with the prediction results
on machining titanium alloy (Ti-6Al-4V) based on micro-cutting tool
perspective. Good agreements with the experiments are observed. A
detailed friction form that affected the tool forces also been examined
with reasonable results obtained.
Abstract: Moisture is an important consideration in many
aspects ranging from irrigation, soil chemistry, golf course, corrosion
and erosion, road conditions, weather predictions, livestock feed
moisture levels, water seepage etc. Vegetation and crops always
depend more on the moisture available at the root level than on
precipitation occurrence. In this paper, design of an instrument is
discussed which tells about the variation in the moisture contents of
soil. This is done by measuring the amount of water content in soil by
finding the variation in capacitance of soil with the help of a
capacitive sensor. The greatest advantage of soil moisture sensor is
reduced water consumption. The sensor is also be used to set lower
and upper threshold to maintain optimum soil moisture saturation and
minimize water wilting, contributes to deeper plant root growth
,reduced soil run off /leaching and less favorable condition for insects
and fungal diseases. Capacitance method is preferred because, it
provides absolute amount of water content and also measures water
content at any depth.
Abstract: In this paper, the requirement for Coke quality
prediction, its role in Blast furnaces, and the model output is
explained. By applying method of Artificial Neural Networking
(ANN) using back propagation (BP) algorithm, prediction model has
been developed to predict CSR. Important blast furnace functions
such as permeability, heat exchanging, melting, and reducing
capacity are mostly connected to coke quality. Coke quality is further
dependent upon coal characterization and coke making process
parameters. The ANN model developed is a useful tool for process
experts to adjust the control parameters in case of coke quality
deviations. The model also makes it possible to predict CSR for new
coal blends which are yet to be used in Coke Plant. Input data to the
model was structured into 3 modules, for tenure of past 2 years and
the incremental models thus developed assists in identifying the
group causing the deviation of CSR.