Abstract: Metropolitan areas have suffered from traffic problems, which have steadily increased in many monocentric cities. Urban expansion, population growth, and road network development have resulted in a structural shift toward urban sprawl, increasing commuters’ dependence on private modes of transport. This paper aims to model the influence of socioeconomic and land-use factors on mode choice using a multinomial and nested logit model. Land-use patterns—such as residential, commercial, retail, educational and employment related—affect the choice of mode and destination in the short and medium term. Socioeconomic factors—such as age, gender, income, household size, and house type—also affect choice, while residential location is affected in the long term. Riyadh in Saudi Arabia and Melbourne in Australia were chosen as case studies. Riyadh is a car-dependent city with limited public transport, whereas Melbourne has good public transport but an increase in car dependence. Aggregate level land-use data and disaggregate level individual, household, and journey-to-work data are used to determine the effects of land use and socioeconomic factors on mode choice. The model results determined that urban sprawl is the main factor that affects mode choice, income, and house type.
Abstract: The antioxidant compounds are needed for the food, beverages, and pharmaceuticals industry. For this purpose, an appropriate method is required to measure the antioxidant properties in various types of samples. Spectrophotometric method usually used has some weaknesses, including the high price, long sample preparation time, and less sensitivity. Among the alternative methods developed to overcome these weaknesses is antioxidant biosensor based on superoxide dismutase (SOD) enzyme. Therefore, this study was carried out to measure the SOD activity originating from Deinococcus radiodurans and to determine its kinetics properties. Carbon paste electrode modified with ferrocene and immobilized SOD exhibited anode and cathode current peak at potential of +400 and +300mv respectively, in both pure SOD and SOD of D. radiodurans. This indicated that the current generated was from superoxide catalytic dismutation reaction by SOD. Optimum conditions for SOD activity was at pH 9 and temperature of 27.50C for D. radiodurans SOD, and pH 11 and temperature of 200C for pure SOD. Dismutation reaction kinetics of superoxide catalyzed by SOD followed the Lineweaver-Burk kinetics with D. radiodurans SOD KMapp value was smaller than pure SOD. The result showed that D. radiodurans SOD had higher enzyme-substrate affinity and specificity than pure SOD. It concluded that D. radiodurans SOD had a great potential as biological recognition component for antioxidant biosensor.
Abstract: Beginning from the creator of integro-differential
equations Volterra, many scientists have investigated these
equations. Classic method for solving integro-differential
equations is the quadratures method that is successfully applied up
today. Unlike these methods, Makroglou applied hybrid methods
that are modified and generalized in this paper and applied to the
numerical solution of Volterra integro-differential equations. The
way for defining the coefficients of the suggested method is also
given.
Abstract: Modes of occurrence of Pb, As, Cr, Co, Cu, and Ni in bituminous coal and lignite were determined by means of sequential extraction using NH4OAc, HCl, HF and HNO3 extraction solutions. Elemental affinities obtained were then evaluated in relation to volatility of these elements during the combustion of these coals in two circulating fluidised-bed power stations. It was found out that higher percentage of the elements bound in silicates brought about lower volatility, while higher elemental proportion with monosulphides association (or bound as exchangeable ion) resulted in higher volatility. The only exception was the behavior of arsenic, whose volatility depended on amount of limestone added during the combustion process (as desulphurisation additive) rather than to its association in coal.
Abstract: We present a theory for optimal filtering of infinite sets of random signals. There are several new distinctive features of the proposed approach. First, we provide a single optimal filter for processing any signal from a given infinite signal set. Second, the filter is presented in the special form of a sum with p terms where each term is represented as a combination of three operations. Each operation is a special stage of the filtering aimed at facilitating the associated numerical work. Third, an iterative scheme is implemented into the filter structure to provide an improvement in the filter performance at each step of the scheme. The final step of the concerns signal compression and decompression. This step is based on the solution of a new rank-constrained matrix approximation problem. The solution to the matrix problem is described in this paper. A rigorous error analysis is given for the new filter.
Abstract: This article presents the development of a neural
network cognitive model for the classification and detection of
different frequency signals. The basic structure of the implemented
neural network was inspired on the perception process that humans
generally make in order to visually distinguish between high and low
frequency signals. It is based on the dynamic neural network concept,
with delays. A special two-layer feedforward neural net structure was
successfully implemented, trained and validated, to achieve
minimum target error. Training confirmed that this neural net
structure descents and converges to a human perception classification
solution, even when far away from the target.
Abstract: In order to provide accurate heart rate variability
indices of sympathetic and parasympathetic activity, the low
frequency and high frequency components of an RR heart rate signal
must be adequately separated. This is not always possible by just
applying spectral analysis, as power from the high and low frequency
components often leak into their adjacent bands. Furthermore,
without the respiratory spectra it is not obvious that the low
frequency component is not another respiratory component, which
can appear in the lower band. This paper describes an adaptive filter,
which aids the separation of the low frequency sympathetic and high
frequency parasympathetic components from an ECG R-R interval
signal, enabling the attainment of more accurate heart rate variability
measures. The algorithm is applied to simulated signals and heart rate
and respiratory signals acquired from an ambulatory monitor
incorporating single lead ECG and inductive plethysmography
sensors embedded in a garment. The results show an improvement
over standard heart rate variability spectral measurements.
Abstract: The theory of rough sets is generalized by using a
filter. The filter is induced by binary relations and it is used to
generalize the basic rough set concepts. The knowledge
representations and processing of binary relations in the style of
rough set theory are investigated.
Abstract: Solution of some practical problems is reduced to the
solution of the integro-differential equations. But for the numerical
solution of such equations basically quadrature methods or its
combination with multistep or one-step methods are used. The
quadrature methods basically is applied to calculation of the integral
participating in right hand side of integro-differential equations. As
this integral is of Volterra type, it is obvious that at replacement with
its integrated sum the upper limit of the sum depends on a current
point in which values of the integral are defined. Thus we receive the
integrated sum with variable boundary, to work with is hardly.
Therefore multistep method with the constant coefficients, which is
free from noted lack and gives the way for finding it-s coefficients is
present.
Abstract: Most integrated inertial navigation systems (INS) and
global positioning systems (GPS) have been implemented using the
Kalman filtering technique with its drawbacks related to the need for
predefined INS error model and observability of at least four
satellites. Most recently, a method using a hybrid-adaptive network
based fuzzy inference system (ANFIS) has been proposed which is
trained during the availability of GPS signal to map the error
between the GPS and the INS. Then it will be used to predict the
error of the INS position components during GPS signal blockage.
This paper introduces a genetic optimization algorithm that is used to
update the ANFIS parameters with respect to the INS/GPS error
function used as the objective function to be minimized. The results
demonstrate the advantages of the genetically optimized ANFIS for
INS/GPS integration in comparison with conventional ANFIS
specially in the cases of satellites- outages. Coping with this problem
plays an important role in assessment of the fusion approach in land
navigation.
Abstract: This paper proposes a new technique based on nonlinear Minmax Detector Based (MDB) filter for image restoration. The aim of image enhancement is to reconstruct the true image from the corrupted image. The process of image acquisition frequently leads to degradation and the quality of the digitized image becomes inferior to the original image. Image degradation can be due to the addition of different types of noise in the original image. Image noise can be modeled of many types and impulse noise is one of them. Impulse noise generates pixels with gray value not consistent with their local neighborhood. It appears as a sprinkle of both light and dark or only light spots in the image. Filtering is a technique for enhancing the image. Linear filter is the filtering in which the value of an output pixel is a linear combination of neighborhood values, which can produce blur in the image. Thus a variety of smoothing techniques have been developed that are non linear. Median filter is the one of the most popular non-linear filter. When considering a small neighborhood it is highly efficient but for large window and in case of high noise it gives rise to more blurring to image. The Centre Weighted Mean (CWM) filter has got a better average performance over the median filter. However the original pixel corrupted and noise reduction is substantial under high noise condition. Hence this technique has also blurring affect on the image. To illustrate the superiority of the proposed approach, the proposed new scheme has been simulated along with the standard ones and various restored performance measures have been compared.
Abstract: To determine if the murine insulinoma, β-TC-6, is a
suitable substitute for primary pancreatic β-cells in the study of β-
cell functional heterogeneity, we used three distinct functional assays
to ascertain the cell line-s response to glucose or a glucose analog.
These assays include: (i) a 2-NBDG uptake assay; (ii) a calcium
influx assay, and; (iii) a quinacrine secretion assay. We show that a
population of β-TC-6 cells endocytoses the glucose analog, 2-
NBDG, at different rates, has non-uniform intracellular calcium ion
concentrations and releases quinacrine at different rates when
challenged with glucose. We also measured the Km for β-TC-6
glucose uptake to be 46.9 mM and the Vm to be 8.36 x 10-5
mmole/million cells/min. These data suggest that β-TC-6 might be
used as an alternative to primary pancreatic β-cells for the study of
glucose-dependent β-cell functional heterogeneity.
Abstract: A new estimator for evolutionary spectrum (ES) based
on short time Fourier transform (STFT) and modified group delay
function (MGDF) by signal decomposition (SD) is proposed. The
STFT due to its built-in averaging, suppresses the cross terms and the
MGDF preserves the frequency resolution of the rectangular window
with the reduction in the Gibbs ripple. The present work overcomes
the magnitude distortion observed in multi-component non-stationary
signals with STFT and MGDF estimation of ES using SD. The SD is
achieved either through discrete cosine transform based harmonic
wavelet transform (DCTHWT) or perfect reconstruction filter banks
(PRFB). The MGDF also improves the signal to noise ratio by
removing associated noise. The performance of the present method is
illustrated for cross chirp and frequency shift keying (FSK) signals,
which indicates that its performance is better than STFT-MGDF
(STFT-GD) alone. Further its noise immunity is better than STFT.
The SD based methods, however cannot bring out the frequency
transition path from band to band clearly, as there will be gap in the
contour plot at the transition. The PRFB based STFT-SD shows good
performance than DCTHWT decomposition method for STFT-GD.
Abstract: This paper explores the social and political imperatives in the sphere of public policy relating to social justice. In India, the colonial legacy and post-colonial social and political pressures sustained the appropriation of 'caste' category in allocating public resources to the backward class of citizens. For several reasons, 'economic' category could not be placed in allocating resources. This paper examines the reasons behind the deliberative exercises and formulating policies and seeks an alternative framework in realizing social justice in terms of a unified category. This attempt can be viewed as a reconciliation of traditional and modern values for a viable alternative in public policy making.
Abstract: Segmentation of a color image composed of different
kinds of regions can be a hard problem, namely to compute for an
exact texture fields. The decision of the optimum number of
segmentation areas in an image when it contains similar and/or un
stationary texture fields. A novel neighborhood-based segmentation
approach is proposed. A genetic algorithm is used in the proposed
segment-pass optimization process. In this pass, an energy function,
which is defined based on Markov Random Fields, is minimized. In
this paper we use an adaptive threshold estimation method for image
thresholding in the wavelet domain based on the generalized
Gaussian distribution (GGD) modeling of sub band coefficients. This
method called Normal Shrink is computationally more efficient and
adaptive because the parameters required for estimating the threshold
depend on sub band data energy that used in the pre-stage of
segmentation. A quad tree is employed to implement the multi
resolution framework, which enables the use of different strategies at
different resolution levels, and hence, the computation can be
accelerated. The experimental results using the proposed
segmentation approach are very encouraging.
Abstract: The binary phase-only filter digital watermarking
embeds the phase information of the discrete Fourier transform of the
image into the corresponding magnitudes for better image authentication.
The paper proposed an approach of how to implement watermark
embedding by quantizing the magnitude, with discussing how to
regulate the quantization steps based on the frequencies of the magnitude
coefficients of the embedded watermark, and how to embed the
watermark at low frequency quantization. The theoretical analysis and
simulation results show that algorithm flexibility, security, watermark
imperceptibility and detection performance of the binary phase-only
filter digital watermarking can be effectively improved with quantization
based watermark embedding, and the robustness against JPEG
compression will also be increased to some extent.
Abstract: A model based fault detection and diagnosis
technique for DC motor is proposed in this paper. Fault detection
using Kalman filter and its different variants are compared. Only
incipient faults are considered for the study. The Kalman Filter
iterations and all the related computations required for fault detection
and fault confirmation are presented. A second order linear state
space model of DC motor is used for this work. A comparative
assessment of the estimates computed from four different observers
and their relative performance is evaluated.
Abstract: Matrix metalloproteinases (MMP) are a class of
structural and functional related enzymes involved in altering the
natural elements of the extracellular matrix. Most of the MMP
structures are cristalographycally determined and published in
WorldWide ProteinDataBank, isolated, in full structure or bound to
natural or synthetic inhibitors. This study proposes an algorithm to
replace missing crystallographic structures in PDB database. We
have compared the results of a chosen docking algorithm with a
known crystallographic structure in order to validate enzyme sites
reconstruction there where crystallographic data are missing.
Abstract: Kojic acid is an organic acid that is widely used as an ingredient for dermatological products, precursor for flavor enhancer and also as anti-inflammatory drug. The present study was undertaken to test the feasibility of pineapple residues as substrate for kojic acid production by Aspergillus flavus Link 44-1 via solid-state fermentation. The effect of initial moisture content, pH and incubation time on kojic acid fermentation was investigated. The best initial moisture content for kojic acid production from pineapple residues was observed at 70% (v/w) whereas initial culture pH 2.5 was identified to give high production of kojic acid. The optimal range of incubation time was identified between 8 and 14 days of incubation which corresponded to highest range of kojic acid produced. The results from this study pronounce the promising usability of pineapple residues as alternative substrate for kojic acid production by A. flavus Link 44-1.
Abstract: In this paper, we propose an efficient hierarchical DNA
sequence search method to improve the search speed while the
accuracy is being kept constant. For a given query DNA sequence,
firstly, a fast local search method using histogram features is used as a
filtering mechanism before scanning the sequences in the database.
An overlapping processing is newly added to improve the robustness
of the algorithm. A large number of DNA sequences with low
similarity will be excluded for latter searching. The Smith-Waterman
algorithm is then applied to each remainder sequences. Experimental
results using GenBank sequence data show the proposed method
combining histogram information and Smith-Waterman algorithm is
more efficient for DNA sequence search.