Abstract: Detection, feature extraction and pose estimation of
people in images and video is made challenging by the variability of
human appearance, the complexity of natural scenes and the high
dimensionality of articulated body models and also the important
field in Image, Signal and Vision Computing in recent years. In this
paper, four types of people in 2D dimension image will be tested and
proposed. The system will extract the size and the advantage of them
(such as: tall fat, short fat, tall thin and short thin) from image. Fat
and thin, according to their result from the human body that has been
extract from image, will be obtained. Also the system extract every
size of human body such as length, width and shown them in output.
Abstract: The Bayesian Optimization Algorithm (BOA) is an algorithm based on the estimation of distributions. It uses techniques from modeling data by Bayesian networks to estimating the joint distribution of promising solutions. To obtain the structure of Bayesian network, different search algorithms can be used. The key point that BOA addresses is whether the constructed Bayesian network could generate new and useful solutions (strings), which could lead the algorithm in the right direction to solve the problem. Undoubtedly, this ability is a crucial factor of the efficiency of BOA. Varied search algorithms can be used in BOA, but their performances are different. For choosing better ones, certain suitable method to present their ability difference is needed. In this paper, a greedy search algorithm and a stochastic search algorithm are used in BOA to solve certain optimization problem. A method using Kullback-Leibler (KL) Divergence to reflect their difference is described.
Abstract: In this paper, mathematical modeling of detonation in the ground is studied. Estimation of flow parameters such as velocity, maximum velocity, acceleration, maximum acceleration, shock pressure as a result of an explosion in the ground have been computed in an appropriate dynamic model approach. The variation of these parameters with the diameter of detonation place (L), density of earth or stone (¤ü), time decay of detonation (T), peak pressure (Pm), and time (t) have been analyzed. The model has been developed from the concept of underwater explosions [Refs. [1]-[3]] with appropriate changes to the present model requirements.
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: Radio frequency identification (RFID) applications have grown rapidly in many industries, especially in indoor location identification. The advantage of using received signal strength indicator (RSSI) values as an indoor location measurement method is a cost-effective approach without installing extra hardware. Because the accuracy of many positioning schemes using RSSI values is limited by interference factors and the environment, thus it is challenging to use RFID location techniques based on integrating positioning algorithm design. This study proposes the location estimation approach and analyzes a scheme relying on RSSI values to minimize location errors. In addition, this paper examines different factors that affect location accuracy by integrating the backpropagation neural network (BPN) with the LANDMARC algorithm in a training phase and an online phase. First, the training phase computes coordinates obtained from the LANDMARC algorithm, which uses RSSI values and the real coordinates of reference tags as training data for constructing an appropriate BPN architecture and training length. Second, in the online phase, the LANDMARC algorithm calculates the coordinates of tracking tags, which are then used as BPN inputs to obtain location estimates. The results show that the proposed scheme can estimate locations more accurately compared to LANDMARC without extra devices.
Abstract: This paper presents a new stable robust adaptive controller and observer design for a class of nonlinear systems that contain i. Coupling of unmeasured states and unknown parameters ii. Unknown dead zone at the system actuator. The system is firstly cast into a modified form in which the observer and parameter estimation become feasible. Then a stable robust adaptive controller, state observer, parameter update laws are derived that would provide global adaptive system stability and desirable performance. To validate the approach, simulation was performed to a single-link mechanical system with a dynamic friction model and unknown dead zone exists at the system actuation. Then a comparison is presented with the results when there is no dead zone at the system actuation.
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 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: Estimation of natural frequency of structures is very
important and isn-t usually calculated simply and sometimes
complicated. Lack of knowledge about that caused hard damage and
hazardous effects.
In this paper, with using from two different models in FEM
method and based on hydrodynamic mass of fluids, natural frequency
of an especial bearing (Fig. 1) in an electric field (or, a periodic
force) is calculated in different stiffness and different geometric. In
final, the results of two models and analytical solution are compared.
Abstract: In recent years, copulas have become very popular in
financial research and actuarial science as they are more flexible in
modelling the co-movements and relationships of risk factors as compared
to the conventional linear correlation coefficient by Pearson.
However, a precise estimation of the copula parameters is vital in
order to correctly capture the (possibly nonlinear) dependence structure
and joint tail events. In this study, we employ two optimization
heuristics, namely Differential Evolution and Threshold Accepting to
tackle the parameter estimation of multivariate t distribution models
in the EML approach. Since the evolutionary optimizer does not rely
on gradient search, the EML approach can be applied to estimation of
more complicated copula models such as high-dimensional copulas.
Our experimental study shows that the proposed method provides
more robust and more accurate estimates as compared to the IFM
approach.
Abstract: The present study was designed to demonstrate the seasonal variations in physico-chemical parameters of fish farm at Govt. Nursery Unit, Muzaffargarh, Department of Fisheries Govt. of Punjab, Pakistan for a period of eight months from January to August 2008. Water samples were collected on fifteen days basis and have been analyzed for estimation of Air temperature, Water temperature, Light penetration, pH, Total dissolved oxygen, Clouds, Carbonates, Bicarbonates, Total carbonates, Total dissolved solids, Chlorides, Calcium and Hardness. Seasonal fluctuations were observed in all the physico-chemical parameters of fish farm. The overall physicochemical parameters of fish pond water remained within the tolerable range throughout the study period.
Abstract: Quality control charts are very effective in detecting
out of control signals but when a control chart signals an out of
control condition of the process mean, searching for a special cause
in the vicinity of the signal time would not always lead to prompt
identification of the source(s) of the out of control condition as the
change point in the process parameter(s) is usually different from the
signal time. It is very important to manufacturer to determine at what
point and which parameters in the past caused the signal. Early
warning of process change would expedite the search for the special
causes and enhance quality at lower cost. In this paper the quality
variables under investigation are assumed to follow a multivariate
normal distribution with known means and variance-covariance
matrix and the process means after one step change remain at the new
level until the special cause is being identified and removed, also it is
supposed that only one variable could be changed at the same time.
This research applies artificial neural network (ANN) to identify the
time the change occurred and the parameter which caused the change
or shift. The performance of the approach was assessed through a
computer simulation experiment. The results show that neural
network performs effectively and equally well for the whole shift
magnitude which has been considered.
Abstract: In this paper, based on the estimation of the Cauchy matrix of linear impulsive differential equations, by using Banach fixed point theorem and Gronwall-Bellman-s inequality, some sufficient conditions are obtained for the existence and exponential stability of almost periodic solution for Cohen-Grossberg shunting inhibitory cellular neural networks (SICNNs) with continuously distributed delays and impulses. An example is given to illustrate the main results.
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: The problem of estimating time-varying regression is
inevitably concerned with the necessity to choose the appropriate
level of model volatility - ranging from the full stationarity of instant
regression models to their absolute independence of each other. In the
stationary case the number of regression coefficients to be estimated
equals that of regressors, whereas the absence of any smoothness
assumptions augments the dimension of the unknown vector by the
factor of the time-series length. The Akaike Information Criterion
is a commonly adopted means of adjusting a model to the given
data set within a succession of nested parametric model classes,
but its crucial restriction is that the classes are rigidly defined by
the growing integer-valued dimension of the unknown vector. To
make the Kullback information maximization principle underlying the
classical AIC applicable to the problem of time-varying regression
estimation, we extend it onto a wider class of data models in which
the dimension of the parameter is fixed, but the freedom of its values
is softly constrained by a family of continuously nested a priori
probability distributions.
Abstract: In this paper, we present a novel approach to location
system under indoor environment. The key idea of our work is
accurate distance estimation with cricket-based location system using
A* algorithm. We also use magnetic sensor for detecting obstacles in
indoor environment. Finally, we suggest how this system can be used
in various applications such as asset tracking and monitoring.
Abstract: The development of the signal compression
algorithms is having compressive progress. These algorithms are
continuously improved by new tools and aim to reduce, an average,
the number of bits necessary to the signal representation by means of
minimizing the reconstruction error. The following article proposes
the compression of Arabic speech signal by a hybrid method
combining the wavelet transform and the linear prediction. The
adopted approach rests, on one hand, on the original signal
decomposition by ways of analysis filters, which is followed by the
compression stage, and on the other hand, on the application of the
order 5, as well as, the compression signal coefficients. The aim of
this approach is the estimation of the predicted error, which will be
coded and transmitted. The decoding operation is then used to
reconstitute the original signal. Thus, the adequate choice of the
bench of filters is useful to the transform in necessary to increase the
compression rate and induce an impercevable distortion from an
auditive point of view.
Abstract: In this research, we propose to use the discrete cosine
transform to approximate the cumulative distributions of data cube
cells- values. The cosine transform is known to have a good energy
compaction property and thus can approximate data distribution
functions easily with small number of coefficients. The derived
estimator is accurate and easy to update. We perform experiments to
compare its performance with a well-known technique - the (Haar)
wavelet. The experimental results show that the cosine transform
performs much better than the wavelet in estimation accuracy, speed,
space efficiency, and update easiness.
Abstract: Natural resources management including water resources requires reliable estimations of time variant environmental parameters. Small improvements in the estimation of environmental parameters would result in grate effects on managing decisions. Noise reduction using wavelet techniques is an effective approach for preprocessing of practical data sets. Predictability enhancement of the river flow time series are assessed using fractal approaches before and after applying wavelet based preprocessing. Time series correlation and persistency, the minimum sufficient length for training the predicting model and the maximum valid length of predictions were also investigated through a fractal assessment.
Abstract: Modeling of Panel Zone (PZ) seismic behavior,
because of its role in overall ductility and lateral stiffness of steel
moment frames, has been considered a challenge for years. There are
some studies regarding the effects of different doubler plates
thicknesses and geometric properties of PZ on its seismic behavior.
However, there is not much investigation on the effects of number of
provided continuity plates in case of presence of one triangular
haunch, two triangular haunches and rectangular haunch (T shape
haunches) for exterior columns. In this research first detailed finite
element models of 12tested connection of SAC joint venture were
created and analyzed then obtained cyclic behavior backbone curves
of these models besides other FE models for similar tests were used
for neural network training. Then seismic behavior of these data is
categorized according to continuity plate-s arrangements and
differences in type of haunches. PZ with one-sided haunches have
little plastic rotation. As the number of continuity plates increases
due to presence of two triangular haunches (four continuity plate),
there will be no plastic rotation, in other words PZ behaves in its
elastic range. In the case of rectangular haunch, PZ show more plastic
rotation in comparison with one-sided triangular haunch and
especially double-sided triangular haunches. Moreover, the models
that will be presented in case of triangular one-sided and double-
sided haunches and rectangular haunches as a result of this study
seem to have a proper estimation of PZ seismic behavior.