Abstract: The Kumamoto area, Kyushu, Japan has 1,041km2 in
area and about 1milion in population. This area is a greatest area in Japan which depends on groundwater for all of drinking water. Quantity of this local groundwater use is about 200MCM during the
year. It is understood that the main recharging area of groundwater exist in the rice field zone which have high infiltrate height ahead of
100mm/ day of the irrigated water located in the middle area of the Shira-River Basin. However, by decrease of the paddy-rice planting
area by urbanization and an acreage reduction policy, the groundwater income and expenditure turned worse. Then Kumamoto city and four
companies expended financial support to increase recharging water to
underground by ponded water in the field from 2004.
In this paper, the author reported the situation of recovery of groundwater by recharge and estimates the efficiency of recharge by
statistical method.
Abstract: This paper describes the speed sensorless vector control method of the parallel connected induction motor drive fed by a single inverter. Speed and rotor fluxes of the induction motor are estimated by natural observer with load torque adaptation and adaptive rotor flux observer. The performance parameters speed and rotor fluxes are estimated from the measured terminal voltages and currents. Fourth order induction motor model is used and speed is considered as a parameter. The performance of the natural observer is similar to the conventional observer. The speed of an induction motor is estimated by MATLAB simulation under different speed and load conditions. Estimated values along with other measured states are used for closed loop control. The simulation results show that the natural observer is also effective for parallel connected induction motor drive.
Abstract: We constructed a method of phase unwrapping for a typical wave-front by utilizing the maximizer of the posterior marginal (MPM) estimate corresponding to equilibrium statistical mechanics of the three-state Ising model on a square lattice on the basis of an analogy between statistical mechanics and Bayesian inference. We investigated the static properties of an MPM estimate from a phase diagram using Monte Carlo simulation for a typical wave-front with synthetic aperture radar (SAR) interferometry. The simulations clarified that the surface-consistency conditions were useful for extending the phase where the MPM estimate was successful in phase unwrapping with a high degree of accuracy and that introducing prior information into the MPM estimate also made it possible to extend the phase under the constraint of the surface-consistency conditions with a high degree of accuracy. We also found that the MPM estimate could be used to reconstruct the original wave-fronts more smoothly, if we appropriately tuned hyper-parameters corresponding to temperature to utilize fluctuations around the MAP solution. Also, from the viewpoint of statistical mechanics of the Q-Ising model, we found that the MPM estimate was regarded as a method for searching the ground state by utilizing thermal fluctuations under the constraint of the surface-consistency condition.
Abstract: We provide a maximum norm analysis of a finite
element Schwarz alternating method for a nonlinear elliptic boundary
value problem of the form -Δu = f(u), on two overlapping sub
domains with non matching grids. We consider a domain which is
the union of two overlapping sub domains where each sub domain
has its own independently generated grid. The two meshes being
mutually independent on the overlap region, a triangle belonging to
one triangulation does not necessarily belong to the other one. Under
a Lipschitz assumption on the nonlinearity, we establish, on each sub
domain, an optimal L∞ error estimate between the discrete Schwarz
sequence and the exact solution of the boundary value problem.
Abstract: A challenging problem in radar signal processing is to
achieve reliable target detection in the presence of interferences. In
this paper, we propose a novel algorithm for automatic censoring of
radar interfering targets in log-normal clutter. The proposed
algorithm, termed the forward automatic censored cell averaging
detector (F-ACCAD), consists of two steps: removing the corrupted
reference cells (censoring) and the actual detection. Both steps are
performed dynamically by using a suitable set of ranked cells to
estimate the unknown background level and set the adaptive
thresholds accordingly. The F-ACCAD algorithm does not require
any prior information about the clutter parameters nor does it require
the number of interfering targets. The effectiveness of the F-ACCAD
algorithm is assessed by computing, using Monte Carlo simulations,
the probability of censoring and the probability of detection in
different background environments.
Abstract: Atlantic herring (Clupea harengus) is an important
commercial fish and shows to be more and more demanded for
human consumption. Therefore, it is very important to find good
methods for monitoring the freshness of the fish in order to keep it in
the best quality for human consumption. In this study, the fish was
stored in ice up to 2 weeks. Quality changes during storage were
assessed by the Quality Index Method (QIM), quantitative
descriptive analysis (QDA) and Torry scheme, by texture
measurements: puncture tests and Texture Profile Analysis (TPA)
tests on texture analyzer TA.XT2i, and by electronic nose (e-nose)
measurements using FreshSense instrument. Storage time of herring
in ice could be estimated by QIM with ± 2 days using 5 herring per
lot. No correlation between instrumental texture parameters and
storage time or between sensory and instrumental texture variables
was found. E-nose measurements could be use to detect the onset of
spoilage.
Abstract: Fast depth estimation from binocular vision is often
desired for autonomous vehicles, but, most algorithms could not easily
be put into practice because of the much time cost. We present an
image-processing technique that can fast estimate depth image from
binocular vision images. By finding out the lines which present the
best matched area in the disparity space image, the depth can be
estimated. When detecting these lines, an edge-emphasizing filter is
used. The final depth estimation will be presented after the smooth
filter. Our method is a compromise between local methods and global
optimization.
Abstract: The value of overall oxygen transfer Coefficient
(KLa), which is the best measure of oxygen transfer in water through
aeration, is obtained by a simple approach, which sufficiently
explains the utility of the method to eliminate the discrepancies due
to inaccurate assumption of saturation dissolved oxygen
concentration. The rate of oxygen transfer depends on number of
factors like intensity of turbulence, which in turns depends on the
speed of rotation, size, and number of blades, diameter and
immersion depth of the rotor, and size and shape of aeration tank, as
well as on physical, chemical, and biological characteristic of water.
An attempt is made in this paper to correlate the overall oxygen
transfer Coefficient (KLa), as an independent parameter with other
influencing parameters mentioned above. It has been estimated that
the simulation equation developed predicts the values of KLa and
power with an average standard error of estimation of 0.0164 and
7.66 respectively and with R2 values of 0.979 and 0.989 respectively,
when compared with experimentally determined values. The
comparison of this model is done with the model generated using
Computational fluid dynamics (CFD) and both the models were
found to be in good agreement with each other.
Abstract: This paper has presented research in progress
concerning the contribution of target costing approach to
achievement competitive price in the Iraqi firm. The title of the
paper is one of the subjects that get large concerns in the finance and
business world in the present time. That is because many competitive
firms have appeared in the regional and global markets and the rapid
changes that covered all fields of life. On the other hand, this paper
concentrated on lack knowledge of the industrial firms, regarding the
significant role of target cost for achieving the competitive prices.
The paper depends on the main supposition, using the competitive
price to get the target cost in the industrial firms. In order to achieve
competitive advantage in business world the firms should rely on
modern methods to manage cost and profit. From strategic
perspective the target cost achieves a so powerful competitive
advantage represented in cost reduction. Nevertheless the target cost
does not exclude the calculation and survey of costs during the
production process. Products- estimated costs are calculated and
compared with the target costs.
Abstract: This work explores blind image deconvolution by recursive function approximation based on supervised learning of neural networks, under the assumption that a degraded image is linear convolution of an original source image through a linear shift-invariant (LSI) blurring matrix. Supervised learning of neural networks of radial basis functions (RBF) is employed to construct an embedded recursive function within a blurring image, try to extract non-deterministic component of an original source image, and use them to estimate hyper parameters of a linear image degradation model. Based on the estimated blurring matrix, reconstruction of an original source image from a blurred image is further resolved by an annealed Hopfield neural network. By numerical simulations, the proposed novel method is shown effective for faithful estimation of an unknown blurring matrix and restoration of an original source image.
Abstract: The resistive-inductive-capacitive behavior of long
interconnects which are driven by CMOS gates are presented in this
paper. The analysis is based on the ¤Ç-model of a RLC load and is
developed for submicron devices. Accurate and analytical
expressions for the output load voltage, the propagation delay and the
short circuit power dissipation have been proposed after solving a
system of differential equations which accurately describe the
behavior of the circuit. The effect of coupling capacitance between
input and output and the short circuit current on these performance
parameters are also incorporated in the proposed model. The
estimated proposed delay and short circuit power dissipation are in
very good agreement with the SPICE simulation with average
relative error less than 6%.
Abstract: Cross sections of As radionuclides in the interaction of natGe with 14-30 MeV protons have been deduced by off-line y-ray spectroscopy to find optimal reaction channels leading to radiotracers for positron emission tomography. The experimental results were compared with the previous results and those estimated by the compound nucleus reaction model.
Abstract: A system for market identification (SMI) is presented.
The resulting representations are multivariable dynamic demand
models. The market specifics are analyzed. Appropriate models and
identification techniques are chosen. Multivariate static and dynamic
models are used to represent the market behavior. The steps of the
first stage of SMI, named data preprocessing, are mentioned. Next,
the second stage, which is the model estimation, is considered in more
details. Stepwise linear regression (SWR) is used to determine the
significant cross-effects and the orders of the model polynomials. The
estimates of the model parameters are obtained by a numerically stable
estimator. Real market data is used to analyze SMI performance.
The main conclusion is related to the applicability of multivariate
dynamic models for representation of market systems.
Abstract: Glomerular filtration rate (GFR) is a measure of
kidney function. It is usually estimated from serum concentrations of
cystatin C or creatinine although there has been considerable debate
in the literature about (i) the best equation to use and (ii) the
variability in the correlation between the concentrations of creatinine
and cystatin C. The equations for GFR can be written in a general
form and from these I calculate the error of the GFR estimates
associated with analyte measurement error. These show that the
error of the GFR estimates is such that it is not possible to distinguish
between the equations over much of the concentration range of either
analyte. The general forms of the equations are also used to derive
an expression for the concentration of cystatin C as a function of the
concentration of creatinine. This equation shows that these analyte
concentrations are not linearly related. Clinical reports of cystatin C
and creatinine concentration are consistent with the expression
derived.
Abstract: A framework to estimate the state of dynamically
varying environment where data are generated from heterogeneous
sources possessing partial knowledge about the environment is presented.
This is entirely derived within Dempster-Shafer and Evidence
Filtering frameworks. The belief about the current state is expressed
as belief and plausibility functions. An addition to Single Input
Single Output Evidence Filter, Multiple Input Single Output Evidence
Filtering approach is introduced. Variety of applications such as
situational estimation of an emergency environment can be developed
within the framework successfully. Fire propagation scenario is used
to justify the proposed framework, simulation results are presented.
Abstract: Matrix metalloproteinase-3 (MMP3) is key member
of the MMP family, and is known to be present in coronary
atherosclerotic. Several studies have demonstrated that MMP-3
5A/6A polymorphism modify each transcriptional activity in allele
specific manner. We hypothesized that this polymorphism may play
a role as risk factor for development of coronary stenosis. The aim of
our study was to estimate MMP-3 (5A/6A) gene polymorphism on
interindividual variability in risk for coronary stenosis in an Iranian
population.DNA was extracted from white blood cells and genotypes
were obtained from coronary stenosis cases (n=95) and controls
(n=100) by PCR (polymerase chain reaction) and restriction
fragment length polymorphism techniques. Significant differences
between cases and controls were observed for MMP3 genotype
frequencies (X2=199.305, p< 0.001); the 6A allele was less
frequently seen in the control group, compared to the disease group
(85.79 vs. 78%, 6A/6A+5A/6A vs. 5A/5A, P≤0.001). These data
imply the involvement of -1612 5A/6A polymorphism in coronary
stenosis, and suggest that probably the 6A/6A MMP-3 genotype is a
genetic susceptibility factor for coronary stenosis.
Abstract: In comparison to the original SVM, which involves a
quadratic programming task; LS–SVM simplifies the required
computation, but unfortunately the sparseness of standard SVM is
lost. Another problem is that LS-SVM is only optimal if the training
samples are corrupted by Gaussian noise. In Least Squares SVM
(LS–SVM), the nonlinear solution is obtained, by first mapping the
input vector to a high dimensional kernel space in a nonlinear
fashion, where the solution is calculated from a linear equation set. In
this paper a geometric view of the kernel space is introduced, which
enables us to develop a new formulation to achieve a sparse and
robust estimate.
Abstract: The purpose of this paper is to present two different
approaches of financial distress pre-warning models appropriate for
risk supervisors, investors and policy makers. We examine a sample
of the financial institutions and electronic companies of Taiwan
Security Exchange (TSE) market from 2002 through 2008. We
present a binary logistic regression with paned data analysis. With
the pooled binary logistic regression we build a model including
more variables in the regression than with random effects, while the
in-sample and out-sample forecasting performance is higher in
random effects estimation than in pooled regression. On the other
hand we estimate an Adaptive Neuro-Fuzzy Inference System
(ANFIS) with Gaussian and Generalized Bell (Gbell) functions and
we find that ANFIS outperforms significant Logit regressions in both
in-sample and out-of-sample periods, indicating that ANFIS is a
more appropriate tool for financial risk managers and for the
economic policy makers in central banks and national statistical
services.
Abstract: We consider a heterogeneously mixing SIR stochastic
epidemic process in populations described by a general graph.
Likelihood theory is developed to facilitate statistic inference for the
parameters of the model under complete observation. We show that
these estimators are asymptotically Gaussian unbiased estimates by
using a martingale central limit theorem.
Abstract: The influence of axial magnetic field (B=0.48 T) on
the variation of ionization efficiency coefficient h and secondary
electron emission coefficient g with respect to reduced electric field
E/P is studied at a new range of plane-parallel electrode spacing (0<
d< 20 cm) and different nitrogen working pressure between 0.5-20
Pa. The axial magnetic field is produced from an inductive copper
coil of radius 5.6 cm. The experimental data of breakdown voltage is
adopted to estimate the mean Paschen curves at different working
features. The secondary electron emission coefficient is calculated
from the mean Paschen curve and used to determine the minimum
breakdown voltage. A reduction of discharge voltage of about 25% is
investigated by the applied of axial magnetic field. At high interelectrode
spacing, the effect of axial magnetic field becomes more
significant for the obtained values of h but it was less for the values
of g.