Abstract: The paper deals with quality labels used in the food products market, especially with labels of quality, labels of origin, and labels of organic farming. The aim of the paper is to identify perception of these labels by consumers in the Czech Republic. The first part refers to the definition and specification of food quality labels that are relevant in the Czech Republic. The second part includes the discussion of marketing research results. Data were collected with personal questioning method. Empirical findings on 150 respondents are related to consumer awareness and perception of national and European food quality labels used in the Czech Republic, attitudes to purchases of labelled products, and interest in information regarding the labels. Statistical methods, in the concrete Pearson´s chi-square test of independence, coefficient of contingency, and coefficient of association are used to determinate if significant differences do exist among selected demographic categories of Czech consumers.
Abstract: The operation performance of a valveless micro-pump
is strongly dependent on the shape of connected nozzle/diffuser and
Reynolds number. The aims of present work are to compare the
performance curves of micropump with the original straight
nozzle/diffuser and contoured nozzle/diffuser under different back
pressure conditions. The tested valveless micropumps are assembled
of five pieces of patterned PMMA plates with hot-embracing
technique. The structures of central chamber, the inlet/outlet
reservoirs and the connected nozzle/diffuser are fabricated with laser
cutting machine. The micropump is actuated with circular-type PZT
film embraced on the bottom of central chamber. The deformation of
PZT membrane with various input voltages is measured with a
displacement laser probe. A simple testing facility is also constructed
to evaluate the performance curves for comparison.
In order to observe the evaluation of low Reynolds number
multiple vortex flow patterns within the micropump during suction
and pumping modes, the unsteady, incompressible laminar
three-dimensional Reynolds-averaged Navier-Stokes equations are
solved. The working fluid is DI water with constant thermo-physical
properties. The oscillating behavior of PZT film is modeled with the
moving boundary wall in way of UDF program. With the dynamic
mesh method, the instants pressure and velocity fields are obtained
and discussed.Results indicated that the volume flow rate is not
monotony increased with the oscillating frequency of PZT film,
regardless of the shapes of nozzle/diffuser. The present micropump
can generate the maximum volume flow rate of 13.53 ml/min when
the operation frequency is 64Hz and the input voltage is 140 volts.
The micropump with contoured nozzle/diffuser can provide 7ml/min
flow rate even when the back pressure is up to 400 mm-H2O. CFD
results revealed that the flow central chamber was occupied with
multiple pairs of counter-rotating vortices during suction and
pumping modes. The net volume flow rate over a complete
oscillating periodic of PZT
Abstract: In this paper we present a novel approach for human
Body configuration based on the Silhouette. We propose to address
this problem under the Bayesian framework. We use an effective
Model based MCMC (Markov Chain Monte Carlo) method to solve
the configuration problem, in which the best configuration could be
defined as MAP (maximize a posteriori probability) in Bayesian
model. This model based MCMC utilizes the human body model to
drive the MCMC sampling from the solution space. It converses the
original high dimension space into a restricted sub-space constructed
by the human model and uses a hybrid sampling algorithm. We
choose an explicit human model and carefully select the likelihood
functions to represent the best configuration solution. The
experiments show that this method could get an accurate
configuration and timesaving for different human from multi-views.
Abstract: This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear underlying phenomena contained in the data set and to partly eliminate the burden of having to specify completely the structure of the model. Two different types of neural networks were used for the application of pulping problem. A three layer feed forward neural networks, using the Preconditioned Conjugate Gradient (PCG) methods were used in this investigation. Preconditioning is a method to improve convergence by lowering the condition number and increasing the eigenvalues clustering. The idea is to solve the modified odified problem M-1 Ax= M-1b where M is a positive-definite preconditioner that is closely related to A. We mainly focused on Preconditioned Conjugate Gradient- based training methods which originated from optimization theory, namely Preconditioned Conjugate Gradient with Fletcher-Reeves Update (PCGF), Preconditioned Conjugate Gradient with Polak-Ribiere Update (PCGP) and Preconditioned Conjugate Gradient with Powell-Beale Restarts (PCGB). The behavior of the PCG methods in the simulations proved to be robust against phenomenon such as oscillations due to large step size.
Abstract: This work considered the thermodynamic feasibility
of scrubbing volatile organic compounds into biodiesel in view of
designing a gas treatment process with this absorbent. A detailed
vapour – liquid equilibrium investigation was performed using the
original UNIFAC group contribution method. The four biodiesels
studied in this work are methyl oleate, methyl palmitate, methyl
linolenate and ethyl stearate. The original UNIFAC procedure was
used to estimate the infinite dilution activity coefficients of 13
selected volatile organic compounds in the biodiesels. The
calculations were done at the VOC mole fraction of 9.213x10-8. Ethyl
stearate gave the most favourable phase equilibrium. A close
agreement was found between the infinite dilution activity coefficient
of toluene found in this work and those reported in literature.
Thermodynamic models can efficiently be used to calculate vast
amount of phase equilibrium behaviour using limited number of
experimental data.
Abstract: This paper focuses upon three such painters working in
France from this time and their representations both of their host
country in which they found themselves displaced, and of their
homeland which they represent through refracted memories from their
new perspective in Europe. What is their representation of France and
China´╝ÅTaiwan? Is it Otherness or an origin?
This paper also attempts to explore the three artists- diasporic lives
and to redefine their transnational identities. Hou Chin-lang, the
significance of his multiple-split images serve to highlight the intricate
relationships between his work and the surrounding family, and to
reveal his identity of his Taiwan “homeland". Yin Xin takes paintings
from the Western canon and subjects them to a process of
transformation through Chinese imagery. In the same period, Lin
Li-ling, transforms the transnational spirit of Yin Xin to symbolic
codes with neutered female bodies and tatoos, thus creates images that
challenge the boundaries of both gender and nationality.
Abstract: Champs Bourcin black grape originated from
Aquitaine, France and planted in Sapa, Lao cai provice, exhibited
high total acidity (11.72 g/L). After 9 days of alcoholic fermentation
at 25oC using Saccharomyces cerevisiae UP3OY5 strain, the ethanol
concentration of wine was 11.5% v/v, however the sharp sour taste of
wine has been found. The malolactic fermentation (MLF) was carried
out by Oenococcus oeni ATCCBAA-1163 strain which had been preadapted
to acid (pH 3-4) and ethanol (8-12%v/v) conditions. We
obtained the highest vivability (83.2%) upon malolactic fermentation
after 5 days at 22oC with early stationary phase O. oeni cells preadapted
to pH 3.5 and 8% v/v ethanol in MRS medium. The malic
acid content in wine was decreased from 5.82 g/L to 0.02 g/L after
MLF (21 days at 22oC). The sensory quality of wine was
significantly improved.
Abstract: This paper is to investigate the impplementation of security
mechanism in object oriented database system. Formal methods
plays an essential role in computer security due to its powerful expressiveness
and concise syntax and semantics. In this paper, both issues
of specification and implementation in database security environment
will be considered; and the database security is achieved through
the development of an efficient implementation of the specification
without compromising its originality and expressiveness.
Abstract: Results of Chilean wine classification based on the
information provided by an electronic nose are reported in this paper.
The classification scheme consists of two parts; in the first stage,
Principal Component Analysis is used as feature extraction method to
reduce the dimensionality of the original information. Then, Radial
Basis Functions Neural Networks is used as pattern recognition
technique to perform the classification. The objective of this study is
to classify different Cabernet Sauvignon, Merlot and Carménère wine
samples from different years, valleys and vineyards of Chile.
Abstract: Wood pyrolysis for Casuarina glauca, Casuarina cunninghamiana, Eucalyptus camaldulensis, Eucalyptus microtheca was made at 450°C with 2.5°C/min. in a flowing N2-atmosphere. The Eucalyptus genus wood gave higher values of specific gravity, ash , total extractives, lignin, N2-liquid trap distillate (NLTD) and water trap distillate (WSP) than those for Casuarina genus. The GHC of NLTD was higher for Casuarina genus than that for Eucalyptus genus with the highest value for Casuarina cunninghamiana. Guiacol, 4-ethyl-2-methoxyphenol and syringol were observed in the NLTD of all the four wood species reflecting their parent hardwood lignin origin. Eucalyptus camaldulensis wood had the highest lignin content (28.89%) and was pyrolyzed to the highest values of phenolics (73.01%), guaiacol (11.2%) and syringol (32.28%) contents in methylene chloride fraction (MCF) of NLTD. Accordingly, recoveries of syringol and guaiacol may become economically attractive from Eucalyptus camaldulensis.
Abstract: Color Image quantization (CQ) is an important
problem in computer graphics, image and processing. The aim of
quantization is to reduce colors in an image with minimum distortion.
Clustering is a widely used technique for color quantization; all
colors in an image are grouped to small clusters. In this paper, we
proposed a new hybrid approach for color quantization using firefly
algorithm (FA) and K-means algorithm. Firefly algorithm is a swarmbased
algorithm that can be used for solving optimization problems.
The proposed method can overcome the drawbacks of both
algorithms such as the local optima converge problem in K-means
and the early converge of firefly algorithm. Experiments on three
commonly used images and the comparison results shows that the
proposed algorithm surpasses both the base-line technique k-means
clustering and original firefly algorithm.
Abstract: Since the one-to-one word translator does not have the
facility to translate pragmatic aspects of Javanese, the parallel text
alignment model described uses a phrase pair combination. The
algorithm aligns the parallel text automatically from the beginning to
the end of each sentence. Even though the results of the phrase pair
combination outperform the previous algorithm, it is still inefficient.
Recording all possible combinations consume more space in the
database and time consuming. The original algorithm is modified by
applying the edit distance coefficient to improve the data-storage
efficiency. As a result, the data-storage consumption is 90% reduced
as well as its learning period (42s).
Abstract: The paper shows the necessity to increase the security
level for paper management in the cadastral field by using specific
graphical watermarks. Using the graphical watermarking will
increase the security in the cadastral content management;
furthermore any altered document will be validated afterwards of its
originality by checking the graphic watermark. If, by any reasons the
document is changed for counterfeiting, it is invalidated and found
that is an illegal copy due to the graphic check of the watermarking,
check made at pixel level
Abstract: An original Direct Numerical Simulation (DNS) method to tackle the problem of particulate flows at moderate to high concentration and finite Reynolds number is presented. Our method is built on the framework established by Glowinski and his coworkers [1] in the sense that we use their Distributed Lagrange Multiplier/Fictitious Domain (DLM/FD) formulation and their operator-splitting idea but differs in the treatment of particle collisions. The novelty of our contribution relies on replacing the simple artificial repulsive force based collision model usually employed in the literature by an efficient Discrete Element Method (DEM) granular solver. The use of our DEM solver enables us to consider particles of arbitrary shape (at least convex) and to account for actual contacts, in the sense that particles actually touch each other, in contrast with the simple repulsive force based collision model. We recently upgraded our serial code, GRIFF 1 [2], to full MPI capabilities. Our new code, PeliGRIFF 2, is developed under the framework of the full MPI open source platform PELICANS [3]. The new MPI capabilities of PeliGRIFF open new perspectives in the study of particulate flows and significantly increase the number of particles that can be considered in a full DNS approach: O(100000) in 2D and O(10000) in 3D. Results on the 2D/3D sedimentation/fluidization of isometric polygonal/polyedral particles with collisions are presented.
Abstract: This research paper deals with the implementation of face recognition using neural network (recognition classifier) on low-resolution images. The proposed system contains two parts, preprocessing and face classification. The preprocessing part converts original images into blurry image using average filter and equalizes the histogram of those image (lighting normalization). The bi-cubic interpolation function is applied onto equalized image to get resized image. The resized image is actually low-resolution image providing faster processing for training and testing. The preprocessed image becomes the input to neural network classifier, which uses back-propagation algorithm to recognize the familiar faces. The crux of proposed algorithm is its beauty to use single neural network as classifier, which produces straightforward approach towards face recognition. The single neural network consists of three layers with Log sigmoid, Hyperbolic tangent sigmoid and Linear transfer function respectively. The training function, which is incorporated in our work, is Gradient descent with momentum (adaptive learning rate) back propagation. The proposed algorithm was trained on ORL (Olivetti Research Laboratory) database with 5 training images. The empirical results provide the accuracy of 94.50%, 93.00% and 90.25% for 20, 30 and 40 subjects respectively, with time delay of 0.0934 sec per image.
Abstract: This paper addresses the problem of blind source separation
(BSS). To recover original signals, from linear instantaneous
mixtures, we propose a new contrast function based on the use of a
double referenced system. Our approach assumes statistical independence
sources. The reference vectors will be incrusted in the cumulant
to evaluate the independence. The estimation of the separating matrix
will be performed in two steps: whitening observations and joint
diagonalization of a set of referenced cumulant matrices. Computer
simulations are presented to demonstrate the effectiveness of the
suggested approach.
Abstract: In this work a new offline signature recognition system
based on Radon Transform, Fractal Dimension (FD) and Support Vector Machine (SVM) is presented. In the first step, projections of
original signatures along four specified directions have been performed using radon transform. Then, FDs of four obtained
vectors are calculated to construct a feature vector for each
signature. These vectors are then fed into SVM classifier for recognition of signatures. In order to evaluate the effectiveness of
the system several experiments are carried out. Offline signature
database from signature verification competition (SVC) 2004 is used
during all of the tests. Experimental result indicates that the proposed method achieved high accuracy rate in signature recognition.
Abstract: Logistics is part of the supply chain processes that
plans, implements, and controls the efficient and effective forward
and reverse flow and storage of goods, services, and related
information between the point of origin and the point of consumption
in order to meet customer requirements. This research aims to
investigate the current status and future direction of the use of
Information Technology (IT) for logistics, focusing on Supply Chain
Management (SCM) and E-Commerce adoption in Malaysia.
Therefore, this research stresses on the type of technology being
adopted, factors, benefits and barriers affecting the innovation in
SCM and E-Commerce technology adoption among Logistics
Service Providers (LSP). A mailed questionnaire survey was
conducted to collect data from 265 logistics companies in Johor. The
research revealed a high level of SCM technology adoption among
LSP as they had adopted SCM technology in various business
processes while they perceived a high level of benefits from SCM
adoption.
Abstract: In this paper we present a combined
hashing/watermarking method for image authentication. A robust
image hash, invariant to legitimate modifications, but fragile to
illegitimate modifications is generated from the local image
characteristics. To increase security of the system the watermark is
generated using the image hash as a key. Quantized Index
Modulation of DCT coefficients is used for watermark embedding.
Watermark detection is performed without use of the original image.
Experimental results demonstrate the effectiveness of the presented
method in terms of robustness and fragility.
Abstract: In Image processing the Image compression can improve
the performance of the digital systems by reducing the cost and
time in image storage and transmission without significant reduction
of the Image quality. This paper describes hardware architecture of
low complexity Discrete Cosine Transform (DCT) architecture for
image compression[6]. In this DCT architecture, common computations
are identified and shared to remove redundant computations
in DCT matrix operation. Vector processing is a method used for
implementation of DCT. This reduction in computational complexity
of 2D DCT reduces power consumption. The 2D DCT is performed
on 8x8 matrix using two 1-Dimensional Discrete cosine transform
blocks and a transposition memory [7]. Inverse discrete cosine
transform (IDCT) is performed to obtain the image matrix and
reconstruct the original image. The proposed image compression
algorithm is comprehended using MATLAB code. The VLSI design
of the architecture is implemented Using Verilog HDL. The proposed
hardware architecture for image compression employing DCT was
synthesized using RTL complier and it was mapped using 180nm
standard cells. . The Simulation is done using Modelsim. The
simulation results from MATLAB and Verilog HDL are compared.
Detailed analysis for power and area was done using RTL compiler
from CADENCE. Power consumption of DCT core is reduced to
1.027mW with minimum area[1].