Abstract: The paper presents the results of research on trends in shaping of multifamily buildings in Poland on the example of Wrocław, after Polish accession to the European Union. The study is conducted within the research project: “Trends in creating of multifamily housing development since 2004, on the Wrocław study case" supported by Polish Ministry of Science and Higher Education and will be completed in November 2011. The research involves multifamily buildings completed in the last decade, in term of fundamental urbanization factors such as: building-s coefficient area, useable area, green area (biologically active surface), intensity of building development, amount of dwellings, dwelling area, amount of parking places, numbers of floors, etc. The analysis of these indicators was conducted based on the date obtained in the study of approximately one hundred new housing units, completed in Wroclaw. The analysis attempts to formulate the main trends in creating of housing policy in Poland during the last 10 years in reference to local urban policy.
Abstract: In this paper, we focus on the fusion of images from
different sources using multiresolution wavelet transforms. Based on
reviews of popular image fusion techniques used in data analysis,
different pixel and energy based methods are experimented. A novel
architecture with a hybrid algorithm is proposed which applies pixel
based maximum selection rule to low frequency approximations and
filter mask based fusion to high frequency details of wavelet
decomposition. The key feature of hybrid architecture is the
combination of advantages of pixel and region based fusion in a
single image which can help the development of sophisticated
algorithms enhancing the edges and structural details. A Graphical
User Interface is developed for image fusion to make the research
outcomes available to the end user. To utilize GUI capabilities for
medical, industrial and commercial activities without MATLAB
installation, a standalone executable application is also developed
using Matlab Compiler Runtime.
Abstract: In present work are considered the scheme of
evaluation the transition probability in quantum system. It is based on
path integral representation of transition probability amplitude and its
evaluation by means of a saddle point method, applied to the part of
integration variables. The whole integration process is reduced to
initial value problem solutions of Hamilton equations with a random
initial phase point. The scheme is related to the semiclassical initial
value representation approaches using great number of trajectories. In
contrast to them from total set of generated phase paths only one path
for each initial coordinate value is selected in Monte Karlo process.
Abstract: The (sub)-optimal soolution of linear filtering problem
with correlated noises is considered. The special recursive form of
the class of filters and criteria for selecting the best estimator are
the essential elements of the design method. The properties of the
proposed filter are studied. In particular, for Markovian observation
noise, the approximate filter becomes an optimal Gevers-Kailath filter
subject to a special choice of the parameter in the class of given linear
recursive filters.
Abstract: In this paper, for the first time, a two-dimensional
(2D) analytical drain current model for sub-100 nm multi-layered
gate material engineered trapezoidal recessed channel (MLGMETRC)
MOSFET: a novel design is presented and investigated using
ATLAS and DEVEDIT device simulators, to mitigate the large gate
leakages and increased standby power consumption that arise due to
continued scaling of SiO2-based gate dielectrics. The twodimensional
(2D) analytical model based on solution of Poisson-s
equation in cylindrical coordinates, utilizing the cylindrical
approximation, has been developed which evaluate the surface
potential, electric field, drain current, switching metric: ION/IOFF
ratio and transconductance for the proposed design. A good
agreement between the model predictions and device simulation
results is obtained, verifying the accuracy of the proposed analytical
model.
Abstract: In this paper, a new dependable algorithm based on an adaptation of the standard variational iteration method (VIM) is used for analyzing the transition from steady convection to chaos for lowto-intermediate Rayleigh numbers convection in porous media. The solution trajectories show the transition from steady convection to chaos that occurs at a slightly subcritical value of Rayleigh number, the critical value being associated with the loss of linear stability of the steady convection solution. The VIM is treated as an algorithm in a sequence of intervals for finding accurate approximate solutions to the considered model and other dynamical systems. We shall call this technique as the piecewise VIM. Numerical comparisons between the piecewise VIM and the classical fourth-order Runge–Kutta (RK4) numerical solutions reveal that the proposed technique is a promising tool for the nonlinear chaotic and nonchaotic systems.
Abstract: In determining the electromagnetic properties of
magnetic materials, hysteresis modeling is of high importance. Many
models are available to investigate those characteristics but they tend
to be complex and difficult to implement. In this paper a new
qualitative hysteresis model for ferromagnetic core is presented,
based on the function approximation capabilities of adaptive neuro
fuzzy inference system (ANFIS). The proposed ANFIS model
combined the neural network adaptive capabilities and the fuzzy
logic qualitative approach can restored the hysteresis curve with a
little RMS error. The model accuracy is good and can be easily
adapted to the requirements of the application by extending or
reducing the network training set and thus the required amount of
measurement data.
Abstract: One of the most important parts of a cement factory is
the cement rotary kiln which plays a key role in quality and quantity of produced cement. In this part, the physical exertion and bilateral
movement of air and materials, together with chemical reactions take
place. Thus, this system has immensely complex and nonlinear dynamic equations. These equations have not worked out yet. Only
in exceptional case; however, a large number of the involved parameter were crossed out and an approximation model was
presented instead. This issue caused many problems for designing a
cement rotary kiln controller. In this paper, we presented nonlinear predictor and simulator models for a real cement rotary kiln by using
nonlinear identification technique on the Locally Linear Neuro-
Fuzzy (LLNF) model. For the first time, a simulator model as well as
a predictor one with a precise fifteen minute prediction horizon for a
cement rotary kiln is presented. These models are trained by
LOLIMOT algorithm which is an incremental tree-structure
algorithm. At the end, the characteristics of these models are expressed. Furthermore, we presented the pros and cons of these
models. The data collected from White Saveh Cement Company is used for modeling.
Abstract: In the Lost Foam Casting process, melting point
temperature of metal, as well as volume and rate of the foam
degradation have significant effect on the mold filling pattern.
Therefore, gas generation capacity and gas gap length are two
important parameters for modeling of mold filling time of the lost
foam casting processes. In this paper, the gas gap length at the liquidfoam
interface for a low melting point (aluminum) alloy and a high
melting point (Carbon-steel) alloy are investigated by the
photography technique. Results of the photography technique
indicated, that the gas gap length and the mold filling time are
increased with increased coating thickness and density of the foam.
The Gas gap lengths measured in aluminum and Carbon-steel,
depend on the foam density, and were approximately 4-5 and 25-60
mm, respectively. By using a new system, the gas generation
capacity for the aluminum and steel was measured. The gas
generation capacity measurements indicated that gas generation in
the Aluminum and Carbon-steel lost foam casting was about 50 CC/g
and 3200 CC/g polystyrene, respectively.
Abstract: This paper is an extension of a previous work where a diagonally implicit harmonic balance method was developed and applied to simulate oscillatory motions of pitching airfoil and wing. A more detailed study on the accuracy, convergence, and the efficiency of the method is carried out in the current paperby varying the number of harmonics in the solution approximation. As the main advantage of the method is itsusage for the design optimization of the unsteady problems, its application to more practical case of rotor flow analysis during forward flight is carried out and compared with flight test data and time-accurate computation results.
Abstract: Theobjective of this study was to evaluate the optimal
treatment condition of Fenton oxidation process to removal
contaminant in soil slurry contaminated by petroleum hydrocarbons.
This research studied somefactors that affect the removal efficiency
of petroleum hydrocarbons in soil slurry including molar ratio of
hydrogen peroxide (H2O2) to ferrous ion(Fe2+), pH condition and
reaction time.The resultsdemonstrated that the optimum condition
was that the molar ratio of H2O2:Fe3+ was 200:1,the pHwas 4.0and
the rate of reaction was increasing rapidly from starting point to 7th
hour and destruction kinetic rate (k) was 0.24 h-1. Approximately
96% of petroleum hydrocarbon was observed(initialtotal petroleum
hydrocarbon (TPH) concentration = 70±7gkg-1)
Abstract: A method for solving linear and non-linear Goursat
problem is given by using the two-dimensional differential transform
method. The approximate solution of this problem is calculated in
the form of a series with easily computable terms and also the exact
solutions can be achieved by the known forms of the series solutions.
The method can easily be applied to many linear and non-linear
problems and is capable of reducing the size of computational work.
Several examples are given to demonstrate the reliability and the
performance of the presented method.
Abstract: The aim of this work is to study the elastic transfer
phenomenon which takes place in the elastic scattering of 16O on 12C
at energies near the Coulomb barrier. Where, the angular distribution
decrease steadily with increasing the scattering angle, then the cross
section will increase at backward angles due to the α-transfer process.
This reaction was also studied at different energies for tracking the
nuclear rainbow phenomenon. The experimental data of the angular
distribution at these energies were compared to the calculation
predictions. The optical potential codes such as SPIVAL and
Distorted Wave Born Approximation (DWUCK5) were used in
analysis.
Abstract: In this paper an efficient incomplete factorization preconditioner is proposed for the Least Mean Squares (LMS) adaptive filter. The proposed preconditioner is approximated from a priori knowledge of the factors of input correlation matrix with an incomplete strategy, motivated by the sparsity patter of the upper triangular factor in the QRD-RLS algorithm. The convergence properties of IPLMS algorithm are comparable with those of transform domain LMS(TDLMS) algorithm. Simulation results show efficiency and robustness of the proposed algorithm with reduced computational complexity.
Abstract: In this paper, we suggest new product-type estimators for the population mean of the variable of interest exploiting the first or the third quartile of the auxiliary variable. We obtain mean square error equations and the bias for the estimators. We study the properties of these estimators using simple random sampling (SRS) and ranked set sampling (RSS) methods. It is found that, SRS and RSS produce approximately unbiased estimators of the population mean. However, the RSS estimators are more efficient than those obtained using SRS based on the same number of measured units for all values of the correlation coefficient.
Abstract: Most of the nonlinear equation solvers do not converge always or they use the derivatives of the function to approximate the
root of such equations. Here, we give a derivative-free algorithm that guarantees the convergence. The proposed two-step method, which
is to some extent like the secant method, is accompanied with some
numerical examples. The illustrative instances manifest that the rate of convergence in proposed algorithm is more than the quadratically
iterative schemes.
Abstract: The design of a gravity dam is performed through an
interactive process involving a preliminary layout of the structure
followed by a stability and stress analysis. This study presents a
method to define the optimal top width of gravity dam with genetic
algorithm. To solve the optimization task (minimize the cost of the
dam), an optimization routine based on genetic algorithms (GAs) was
implemented into an Excel spreadsheet. It was found to perform well
and GA parameters were optimized in a parametric study. Using the
parameters found in the parametric study, the top width of gravity
dam optimization was performed and compared to a gradient-based
optimization method (classic method). The accuracy of the results
was within close proximity. In optimum dam cross section, the ratio
of is dam base to dam height is almost equal to 0.85, and ratio of dam
top width to dam height is almost equal to 0.13. The computerized
methodology may provide the help for computation of the optimal
top width for a wide range of height of a gravity dam.
Abstract: A linear system is called a fully fuzzy linear system (FFLS) if quantities in this system are all fuzzy numbers. For the FFLS, we investigate its solution and develop a new approximate method for solving the FFLS. Observing the numerical results, we find that our method is accurate than the iterative Jacobi and Gauss- Seidel methods on approximating the solution of FFLS.
Abstract: Support vector machines (SVMs) are considered to be
the best machine learning algorithms for minimizing the predictive
probability of misclassification. However, their drawback is that for
large data sets the computation of the optimal decision boundary is a
time consuming function of the size of the training set. Hence several
methods have been proposed to speed up the SVM algorithm. Here
three methods used to speed up the computation of the SVM
classifiers are compared experimentally using a musical genre
classification problem. The simplest method pre-selects a random
sample of the data before the application of the SVM algorithm. Two
additional methods use proximity graphs to pre-select data that are
near the decision boundary. One uses k-Nearest Neighbor graphs and
the other Relative Neighborhood Graphs to accomplish the task.
Abstract: The posteroanterior manipulation technique is usually include in the procedure of the lumbar spine to evaluate the intervertebral motion according to mechanical resistance. The mechanical device with visual feedback was proposed that allows one to analysis the lumbar segments mobility “in vivo" facilitating for the therapist to take its treatment evolution. The measuring system uses load cell and displacement sensor to estimate spine stiffness. In this work, the device was tested by 2 therapists, female, applying posteroanterior force techniques to 5 volunteers, female, with frequency of approximately 1.2-1.8 Hz. A test-retest procedure was used for 2 periods of day. The visual feedback results small variation of forces and cycle time during 6 cycles rhythmic application. The stiffness values showed good agreement between test-retest procedures when used same order of maximum forces.