Abstract: This paper introduces a novel approach to estimate the
clique potentials of Gibbs Markov random field (GMRF) models
using the Support Vector Machines (SVM) algorithm and the Mean
Field (MF) theory. The proposed approach is based on modeling the
potential function associated with each clique shape of the GMRF
model as a Gaussian-shaped kernel. In turn, the energy function of
the GMRF will be in the form of a weighted sum of Gaussian
kernels. This formulation of the GMRF model urges the use of the
SVM with the Mean Field theory applied for its learning for
estimating the energy function. The approach has been tested on
synthetic texture images and is shown to provide satisfactory results
in retrieving the synthesizing parameters.
Abstract: Image coding based on clustering provides immediate
access to targeted features of interest in a high quality decoded
image. This approach is useful for intelligent devices, as well as for
multimedia content-based description standards. The result of image
clustering cannot be precise in some positions especially on pixels
with edge information which produce ambiguity among the clusters.
Even with a good enhancement operator based on PDE, the quality of
the decoded image will highly depend on the clustering process. In
this paper, we introduce an ambiguity cluster in image coding to
represent pixels with vagueness properties. The presence of such
cluster allows preserving some details inherent to edges as well for
uncertain pixels. It will also be very useful during the decoding phase
in which an anisotropic diffusion operator, such as Perona-Malik,
enhances the quality of the restored image. This work also offers a
comparative study to demonstrate the effectiveness of a fuzzy
clustering technique in detecting the ambiguity cluster without losing
lot of the essential image information. Several experiments have been
carried out to demonstrate the usefulness of ambiguity concept in
image compression. The coding results and the performance of the
proposed algorithms are discussed in terms of the peak signal-tonoise
ratio and the quantity of ambiguous pixels.
Abstract: Basic ingredients of concrete are cement, fine aggregate, coarse aggregate and water. To produce a concrete of certain specific properties, optimum proportion of these ingredients are mixed. The important factors which govern the mix design are grade of concrete, type of cement and size, shape and grading of aggregates. Concrete mix design method is based on experimentally evolved empirical relationship between the factors in the choice of mix design. Basic draw backs of this method are that it does not produce desired strength, calculations are cumbersome and a number of tables are to be referred for arriving at trial mix proportion moreover, the variation in attainment of desired strength is uncertain below the target strength and may even fail. To solve this problem, a lot of cubes of standard grades were prepared and attained 28 days strength determined for different combination of cement, fine aggregate, coarse aggregate and water. An artificial neural network (ANN) was prepared using these data. The input of ANN were grade of concrete, type of cement, size, shape and grading of aggregates and output were proportions of various ingredients. With the help of these inputs and outputs, ANN was trained using feed forward back proportion model. Finally trained ANN was validated, it was seen that it gave the result with/ error of maximum 4 to 5%. Hence, specific type of concrete can be prepared from given material properties and proportions of these materials can be quickly evaluated using the proposed ANN.
Abstract: This paper presents the results of enhancing images from a left and right stereo pair in order to increase the resolution of a 3D representation of a scene generated from that same pair. A new neural network structure known as a Self Delaying Dynamic Network (SDN) has been used to perform the enhancement. The advantage of SDNs over existing techniques such as bicubic interpolation is their ability to cope with motion and noise effects. SDNs are used to generate two high resolution images, one based on frames taken from the left view of the subject, and one based on the frames from the right. This new high resolution stereo pair is then processed by a disparity map generator. The disparity map generated is compared to two other disparity maps generated from the same scene. The first is a map generated from an original high resolution stereo pair and the second is a map generated using a stereo pair which has been enhanced using bicubic interpolation. The maps generated using the SDN enhanced pairs match more closely the target maps. The addition of extra noise into the input images is less problematic for the SDN system which is still able to out perform bicubic interpolation.
Abstract: According to the interaction of inflation and
unemployment, expectation of the rate of inflation in Croatia is
estimated. The interaction between inflation and unemployment is
shown by model based on three first-order differential i.e. difference
equations: Phillips relation, adaptive expectations equation and
monetary-policy equation. The resulting equation is second order
differential i.e. difference equation which describes the time path of
inflation. The data of the rate of inflation and the rate of
unemployment are used for parameters estimation. On the basis of
the estimated time paths, the stability and convergence analysis is
done for the rate of inflation.
Abstract: This paper develops an unscented grid-based filter
and a smoother for accurate nonlinear modeling and analysis
of time series. The filter uses unscented deterministic sampling
during both the time and measurement updating phases, to approximate
directly the distributions of the latent state variable. A
complementary grid smoother is also made to enable computing
of the likelihood. This helps us to formulate an expectation
maximisation algorithm for maximum likelihood estimation of
the state noise and the observation noise. Empirical investigations
show that the proposed unscented grid filter/smoother compares
favourably to other similar filters on nonlinear estimation tasks.
Abstract: In this paper, we use a one-step iteration scheme to approximate common fixed points of two quasi-asymptotically nonexpansive mappings. We prove weak and strong convergence theorems in a uniformly convex Banach space. Our results generalize the corresponding results of Yao and Chen [15] to a wider class of mappings while extend those of Khan, Abbas and Khan [4] to an improved one-step iteration scheme without any condition and improve upon many others in the literature.
Abstract: We here propose improved version of elastic graph matching (EGM) as a face detector, called the multi-scale EGM (MS-EGM). In this improvement, Gabor wavelet-based pyramid reduces computational complexity for the feature representation often used in the conventional EGM, but preserving a critical amount of information about an image. The MS-EGM gives us higher detection performance than Viola-Jones object detection algorithm of the AdaBoost Haar-like feature cascade. We also show rapid detection speeds of the MS-EGM, comparable to the Viola-Jones method. We find fruitful benefits in the MS-EGM, in terms of topological feature representation for a face.
Abstract: The proof of concept experiments were conducted to
determine the feasibility of using small amounts of Dissolved
Sulphur (DS) from the gaseous phase to precipitate platinum ions in
chloride media. Two sets of precipitation experiments were
performed in which the source of sulphur atoms was either a
thiosulphate solution (Na2S2O3) or a sulphur dioxide gas (SO2). In
liquid-liquid (L-L) system, complete precipitation of Pt was achieved
at small dosages of Na2S2O3 (0.01 – 1.0 M) in a time interval of 3-5
minutes. On the basis of this result, gas absorption tests were carried
out mainly to achieve sulphur solubility equivalent to 0.018 M. The
idea that huge amounts of precious metals could be recovered
selectively from their dilute solutions by utilizing the waste SO2
streams at low pressure seemed attractive from the economic and
environmental point of views. Therefore, mass transfer characteristics
of SO2 gas associated with reactive absorption across the gas-liquid
(G-L) interface were evaluated under different conditions of pressure
(0.5 – 2 bar), solution temperature ranges from 20 – 50 oC and acid
strength (1 – 4 M, HCl). This paper concludes with information about
selective precipitation of Pt in the presence of cations (Fe2+, Co2+,
and Cr3+) in a CSTR and recommendation to scale up laboratory data
to industrial pilot scale operations.
Abstract: In recent years, most of the regions in the world are
exposed to degradation and erosion caused by increasing
population and over use of land resources. The understanding of
the most important factors on soil erosion and sediment yield are
the main keys for decision making and planning. In this study, the
sediment yield and soil erosion were estimated and the priority of
different soil erosion factors used in the MPSIAC method of soil
erosion estimation is evaluated in AliAbad watershed in southwest
of Isfahan Province, Iran. Different information layers of the
parameters were created using a GIS technique. Then, a
multivariate procedure was applied to estimate sediment yield and
to find the most important factors of soil erosion in the model. The
results showed that land use, geology, land and soil cover are the
most important factors describing the soil erosion estimated by
MPSIAC model.
Abstract: This work focuses on the remediation of polycyclic
aromatic hydrocarbons (PAHs)-contaminated soil via Fenton
treatment coupled with novel chelating agent (CA). The feasibility of
chelated modified Fenton (MF) treatment to promote PAH oxidation
in artificially contaminated soils was investigated in laboratory scale
batch experiments at natural pH. The effects of adding inorganic and
organic CA are discussed. Experiments using different iron catalyst
to CA ratios were conducted, resulting in hydrogen peroxide: soil:
iron: CA weight ratios that varied from 0.049: 1: 0.072: 0.008 to
0.049: 1: 0.072: 0.067. The results revealed that (1) inorganic CA
could provide much higher PAH removal efficiency and (2) most of
the proposed CAs were more efficient than commonly utilised CAs
even at mild ratio. This work highlights the potential of novel
chelating agents in maintaining a suitable environment throughout
the Fenton treatment, particularly in soils with high buffer capacity.
Abstract: This paper examines predictability in stock return in
developed and emergingmarkets by testing long memory in stock
returns using wavelet approach. Wavelet-based maximum likelihood
estimator of the fractional integration estimator is superior to the
conventional Hurst exponent and Geweke and Porter-Hudak
estimator in terms of asymptotic properties and mean squared error.
We use 4-year moving windows to estimate the fractional integration
parameter. Evidence suggests that stock return may not be predictable
indeveloped countries of the Asia-Pacificregion. However,
predictability of stock return insome developing countries in this
region such as Indonesia, Malaysia and Philippines may not be ruled
out. Stock return in the Thailand stock market appears to be not
predictable after the political crisis in 2008.
Abstract: The Goursat partial differential equation arises in
linear and non linear partial differential equations with mixed
derivatives. This equation is a second order hyperbolic partial
differential equation which occurs in various fields of study such as
in engineering, physics, and applied mathematics. There are many
approaches that have been suggested to approximate the solution of
the Goursat partial differential equation. However, all of the
suggested methods traditionally focused on numerical differentiation
approaches including forward and central differences in deriving the
scheme. An innovation has been done in deriving the Goursat partial
differential equation scheme which involves numerical integration
techniques. In this paper we have developed a new scheme to solve
the Goursat partial differential equation based on the Adomian
decomposition (ADM) and associated with Boole-s integration rule to
approximate the integration terms. The new scheme can easily be
applied to many linear and non linear Goursat partial differential
equations and is capable to reduce the size of computational work.
The accuracy of the results reveals the advantage of this new scheme
over existing numerical method.
Abstract: The present study was conducted to investigate the
response of plants exposed to lignite-based thermal power plant
emission. For this purpose, five plant species were collected from 1.0
km distance (polluted site) and control plants were collected from
20.0 km distance (control site) to thermal power plant. The common
tree species Cassia siamea Lamk., Polyalthia longifolia. Sonn,
Acacia longifolia (Andrews) Wild., Azadirachta indica A.Juss, Ficus
religiosa L. were selected as test plants. Photosynthetic pigments
changes (chlorophyll a, chlorophyll b and carotenoids) and rubisco
enzyme modifications were studied. Reduction was observed in the
photosynthetic pigments of plants growing in polluted site and also
large sub unit of the rubisco enzyme was degraded in Azadirachta
indica A. Juss collected from polluted site.
Abstract: The paper deals with calculation of the parameters of
ceramic material from a set of destruction tests of ceramic heads of
total hip joint endoprosthesis. The standard way of calculation of the
material parameters consists in carrying out a set of 3 or 4 point
bending tests of specimens cut out from parts of the ceramic material
to be analysed. In case of ceramic heads, it is not possible to cut out
specimens of required dimensions because the heads are too small (if
the cut out specimens were smaller than the normalised ones, the
material parameters derived from them would exhibit higher strength
values than those which the given ceramic material really has). On
that score, a special testing jig was made, in which 40 heads were
destructed. From the measured values of circumferential strains of the
head-s external spherical surface under destruction, the state of stress
in the head under destruction was established using the final elements
method (FEM). From the values obtained, the sought for parameters
of the ceramic material were calculated using Weibull-s weakest-link
theory.
Abstract: The characterization of κ-carrageenan could provide a
better understanding of its functions in biological, medical and
industrial applications. Chemical and physical analyses of
carrageenan from seaweeds, Euchema cottonii L., were done to offer
information on its properties and the effects of Co-60 γ-irradiation on
its thermochemical characteristics. The structural and morphological
characteristics of κ-carrageenan were determined using scanning
electron microscopy (SEM) while the composition, molecular weight
and thermal properties were determined using attenuated total
reflectance Fourier transform infrared spectroscopy (ATR-FTIR), gel
permeation chromatography (GPC), thermal gravimetric analysis
(TGA) and differential scanning calorimetry (DSC). Further chemical
analysis was done using hydrogen-1 nuclear magnetic resonance (1H
NMR) and functional characteristics in terms of biocompatibility
were evaluated using cytotoxicity test.
Abstract: In this paper the neural network-based controller is
designed for motion control of a mobile robot. This paper treats the
problems of trajectory following and posture stabilization of the
mobile robot with nonholonomic constraints. For this purpose the
recurrent neural network with one hidden layer is used. It learns
relationship between linear velocities and error positions of the
mobile robot. This neural network is trained on-line using the
backpropagation optimization algorithm with an adaptive learning
rate. The optimization algorithm is performed at each sample time to
compute the optimal control inputs. The performance of the proposed
system is investigated using a kinematic model of the mobile robot.
Abstract: We propose a decoy-pulse protocol for frequency-coded implementation of B92 quantum key distribution protocol. A direct extension of decoy-pulse method to frequency-coding scheme results in security loss as an eavesdropper can distinguish between signal and decoy pulses by measuring the carrier photon number without affecting other statistics. We overcome this problem by optimizing the ratio of carrier photon number of decoy-to-signal pulse to be as close to unity as possible. In our method the switching between signal and decoy pulses is achieved by changing the amplitude of RF signal as opposed to modulating the intensity of optical signal thus reducing system cost. We find an improvement by a factor of 100 approximately in the key generation rate using decoy-state protocol. We also study the effect of source fluctuation on key rate. Our simulation results show a key generation rate of 1.5×10-4/pulse for link lengths up to 70km. Finally, we discuss the optimum value of average photon number of signal pulse for a given key rate while also optimizing the carrier ratio.
Abstract: The Chinese Postman Problem (CPP) is one of the
classical problems in graph theory and is applicable in a wide range
of fields. With the rapid development of hybrid systems and model
based testing, Chinese Postman Problem with Time Dependent Travel
Times (CPPTDT) becomes more realistic than the classical problems.
In the literature, we have proposed the first integer programming
formulation for the CPPTDT problem, namely, circuit formulation,
based on which some polyhedral results are investigated and a cutting
plane algorithm is also designed. However, there exists a main drawback:
the circuit formulation is only available for solving the special
instances with all circuits passing through the origin. Therefore, this
paper proposes a new integer programming formulation for solving
all the general instances of CPPTDT. Moreover, the size of the circuit
formulation is too large, which is reduced dramatically here. Thus, it
is possible to design more efficient algorithm for solving the CPPTDT
in the future research.
Abstract: As the Computed Tomography(CT) requires normally
hundreds of projections to reconstruct the image, patients are exposed
to more X-ray energy, which may cause side effects such as cancer.
Even when the variability of the particles in the object is very less,
Computed Tomography requires many projections for good quality
reconstruction. In this paper, less variability of the particles in an
object has been exploited to obtain good quality reconstruction.
Though the reconstructed image and the original image have same
projections, in general, they need not be the same. In addition
to projections, if a priori information about the image is known,
it is possible to obtain good quality reconstructed image. In this
paper, it has been shown by experimental results why conventional
algorithms fail to reconstruct from a few projections, and an efficient
polynomial time algorithm has been given to reconstruct a bi-level
image from its projections along row and column, and a known sub
image of unknown image with smoothness constraints by reducing the
reconstruction problem to integral max flow problem. This paper also
discusses the necessary and sufficient conditions for uniqueness and
extension of 2D-bi-level image reconstruction to 3D-bi-level image
reconstruction.