Abstract: The Kansei engineering is a technology which
converts human feelings into quantitative terms and helps designers
develop new products that meet customers- expectation. Standard
Kansei engineering procedure involves finding relationships between
human feelings and design elements of which many researchers have
found forward and backward relationship through various soft
computing techniques. In this paper, we proposed the framework of
Kansei engineering linking relationship not only between human
feelings and design elements, but also the whole part of product, by
constructing association rules. In this experiment, we obtain input
from emotion score that subjects rate when they see the whole part of
the product by applying semantic differentials. Then, association
rules are constructed to discover the combination of design element
which affects the human feeling. The results of our experiment
suggest the pattern of relationship of design elements according to
human feelings which can be derived from the whole part of product.
Abstract: This work investigated the steady state and dynamic
simulation of a fixed bed industrial naphtha reforming reactors. The
performance of the reactor was investigated using a heterogeneous
model. For process simulation, the differential equations are solved
using the 4th order Runge-Kutta method .The models were validated
against measured process data of an existing naphtha reforming plant.
The results of simulation in terms of components yields and
temperature of the outlet were in good agreement with empirical data.
The simple model displays a useful tool for dynamic simulation,
optimization and control of naphtha reforming.
Abstract: Iodine radionuclides in accident releases under severe
accident conditions at NPP with VVER are the most radiationimportant
with a view to population dose generation at the beginning
of the accident. To decrease radiation consequences of severe
accidents the technical solutions for severe accidents management
have been proposed in MIR.1200 project, with consideration of the
measures for suppression of volatile iodine forms generation in the
containment. Behavior dynamics of different iodine forms in the
containment under severe accident conditions has been analyzed for
the purpose of these technical solutions justification.
Abstract: Carbon fibers have specific characteristics in
comparison with industrial and structural materials used in different
applications. Special properties of carbon fibers make them attractive
for reinforcing and fabrication of composites. These fibers have been
utilized for composites of metals, ceramics and plastics. However,
it-s mainly used in different forms to reinforce lightweight polymer
materials such as epoxy resin, polyesters or polyamides. The
composites of carbon fiber are stronger than steel, stiffer than
titanium, and lighter than aluminum and nowadays they are used in a
variety of applications. This study explains applications of carbon
fibers in different fields such as space, aviation, transportation,
medical, construction, energy, sporting goods, electronics, and the
other commercial/industrial applications. The last findings of
composites with polymer, metal and ceramic matrices containing
carbon fibers and their applications in the world investigated.
Researches show that carbon fibers-reinforced composites due to
unique properties (including high specific strength and specific
modulus, low thermal expansion coefficient, high fatigue strength,
and high thermal stability) can be replaced with common industrial
and structural materials.
Abstract: The approach based on the wavelet transform has
been widely used for image denoising due to its multi-resolution
nature, its ability to produce high levels of noise reduction and the
low level of distortion introduced. However, by removing noise, high
frequency components belonging to edges are also removed, which
leads to blurring the signal features. This paper proposes a new
method of image noise reduction based on local variance and edge
analysis. The analysis is performed by dividing an image into 32 x 32
pixel blocks, and transforming the data into wavelet domain. Fast
lifting wavelet spatial-frequency decomposition and reconstruction is
developed with the advantages of being computationally efficient and
boundary effects minimized. The adaptive thresholding by local
variance estimation and edge strength measurement can effectively
reduce image noise while preserve the features of the original image
corresponding to the boundaries of the objects. Experimental results
demonstrate that the method performs well for images contaminated
by natural and artificial noise, and is suitable to be adapted for
different class of images and type of noises. The proposed algorithm
provides a potential solution with parallel computation for real time
or embedded system application.
Abstract: Frequency domain independent component analysis has
a scaling indeterminacy and a permutation problem. The scaling
indeterminacy can be solved by use of a decomposed spectrum. For
the permutation problem, we have proposed the rules in terms of gain
ratio and phase difference derived from the decomposed spectra and
the source-s coarse directions.
The present paper experimentally clarifies that the gain ratio and
the phase difference work effectively in a real environment but their
performance depends on frequency bands, a microphone-space and
a source-microphone distance. From these facts it is seen that it is
difficult to attain a perfect solution for the permutation problem in a
real environment only by either the gain ratio or the phase difference.
For the perfect solution, this paper gives a solution to the problems
in a real environment. The proposed method is simple, the amount of
calculation is small. And the method has high correction performance
without depending on the frequency bands and distances from source
signals to microphones. Furthermore, it can be applied under the real
environment. From several experiments in a real room, it clarifies
that the proposed method has been verified.
Abstract: The optimal operation of proton exchange membrane fuel cell (PEMFC) requires good water management which is presented under two forms vapor and liquid. Moreover, fuel cells have to reach higher output require integration of some accessories which need electrical power. In order to analyze fuel cells operation and different species transport phenomena a biphasic mathematical model is presented by governing equations set. The numerical solution of these conservation equations is calculated by Matlab program. A multi-criteria optimization with weighting between two opposite objectives is used to determine the compromise solutions between maximum output and minimal stack size. The obtained results are in good agreement with available literature data.
Abstract: Outlier detection in streaming data is very challenging because streaming data cannot be scanned multiple times and also new concepts may keep evolving. Irrelevant attributes can be termed as noisy attributes and such attributes further magnify the challenge of working with data streams. In this paper, we propose an unsupervised outlier detection scheme for streaming data. This scheme is based on clustering as clustering is an unsupervised data mining task and it does not require labeled data, both density based and partitioning clustering are combined for outlier detection. In this scheme partitioning clustering is also used to assign weights to attributes depending upon their respective relevance and weights are adaptive. Weighted attributes are helpful to reduce or remove the effect of noisy attributes. Keeping in view the challenges of streaming data, the proposed scheme is incremental and adaptive to concept evolution. Experimental results on synthetic and real world data sets show that our proposed approach outperforms other existing approach (CORM) in terms of outlier detection rate, false alarm rate, and increasing percentages of outliers.
Abstract: The Principal component regression (PCR) is a
combination of principal component analysis (PCA) and multiple linear regression (MLR). The objective of this paper is to revise the
use of PCR in shortwave near infrared (SWNIR) (750-1000nm) spectral analysis. The idea of PCR was explained mathematically and
implemented in the non-destructive assessment of the soluble solid
content (SSC) of pineapple based on SWNIR spectral data. PCR achieved satisfactory results in this application with root mean
squared error of calibration (RMSEC) of 0.7611 Brix°, coefficient of determination (R2) of 0.5865 and root mean squared error of crossvalidation
(RMSECV) of 0.8323 Brix° with principal components
(PCs) of 14.
Abstract: This paper examines the factors, which determine
R&D outsourcing behaviour at Japanese firms, from the viewpoints of
transaction cost and strategic management, since the latter half of the
1990s. This study uses empirical analysis, which involves the
application of large-sample data. The principal findings of this paper
are listed below. Firms that belong to a wider corporate group are more
active in executing R&D outsourcing activities. Diversification
strategies such as the expansion of product and sales markets have a
positive effect on the R&D outsourcing behaviour of firms. Moreover,
while quantitative R&D resources have positive influences on R&D
outsourcing, qualitative indices have no effect. These facts suggest
that R&D outsourcing behaviour of Japanese firms are consistent with
the two perspectives of transaction cost and strategic management.
Specifically, a conventional corporate group network plays an
important role in R&D outsourcing behaviour. Firms that execute
R&D outsourcing leverage 'old' networks to construct 'new' networks
and use both networks properly.
Abstract: Artemisinin is a potential antimalarial drug effective
against the multidrug resistant forms of Malarial Parasites. The
current production of artemisinin is insufficient to meet the global
demand. In the present study microbial biotransformation of
arteannuin B, a biogenetic precursor of artemisinin to the later has
been investigated. Screening studies carried out on several soil borne
microorganisms have yielded one novel species with the
bioconversion ability. Crude cell free extract of 72h old culture of the
isolate had shown the bioconversion activity. On incubation with the
substrate arteannuin B, crude cell free extract of the isolate had
shown a bioconversion of 18.54% to artemisinin on molar basis with
a specific activity of 0.18 units/mg.
Abstract: Aim. We have introduced the notion of order to multinormed spaces and countable union spaces and their duals. The topology of bounded convergence is assigned to the dual spaces. The aim of this paper is to develop the theory of ordered topological linear
spaces La,b, L(w, z), the dual spaces of ordered multinormed spaces
La,b, ordered countable union spaces L(w, z), with the topology of bounded convergence assigned to the dual spaces. We apply Laplace transformation to the ordered linear space of Laplace transformable
generalized functions. We ultimately aim at finding solutions to nonhomogeneous
nth order linear differential equations with constant
coefficients in terms of generalized functions and comparing different
solutions evolved out of different initial conditions.
Method. The above aim is achieved by
• Defining the spaces La,b, L(w, z).
• Assigning an order relation on these spaces by identifying a
positive cone on them and studying the properties of the cone.
• Defining an order relation on the dual spaces La,b, L(w, z) of La,b, L(w, z) and assigning a topology to these dual spaces which makes the order dual and the topological dual the same. • Defining the adjoint of a continuous map on these spaces
and studying its behaviour when the topology of bounded
convergence is assigned to the dual spaces.
• Applying the two-sided Laplace Transformation on the ordered
linear space of generalized functions W and studying some
properties of the transformation which are used in solving
differential equations.
Result. The above techniques are applied to solve non-homogeneous
n-th order linear differential equations with constant coefficients in
terms of generalized functions and to compare different solutions of the differential equation.
Abstract: Nowadays due to globalization of economy and
competition environment, innovation and technology plays key role
at creation of wealth and economic growth of countries. In fact
prompt growth of practical and technologic knowledge may results in
social benefits for countries when changes into effective innovation.
Considering the importance of innovation for the development of
countries, this study addresses the radical technological innovation
introduced by nanopapers at different stages of producing paper
including stock preparation, using authorized additives, fillers and
pigments, using retention, calender, stages of producing conductive
paper, porous nanopaper and Layer by layer self-assembly. Research
results show that in coming years the jungle related products will lose
considerable portion of their market share, unless embracing radical
innovation. Although incremental innovations can make this industry
still competitive in mid-term, but to have economic growth and
competitive advantage in long term, radical innovations are
necessary. Radical innovations can lead to new products and
materials which their applications in packaging industry can produce
value added. However application of nanotechnology in this industry
can be costly, it can be done in cooperation with other industries to
make the maximum use of nanotechnology possible. Therefore this
technology can be used in all the production process resulting in the
mass production of simple and flexible papers with low cost and
special properties such as facility at shape, form, easy transportation,
light weight, recovery and recycle marketing abilities, and sealing.
Improving the resistance of the packaging materials without reducing
the performance of packaging materials enhances the quality and the
value added of packaging. Improving the cellulose at nano scale can
have considerable electron optical and magnetic effects leading to
improvement in packaging and value added. Comparing to the
specifications of thermoplastic products and ordinary papers,
nanopapers show much better performance in terms of effective
mechanical indexes such as the modulus of elasticity, tensile strength,
and strain-stress. In densities lower than 640 kgm -3, due to the
network structure of nanofibers and the balanced and randomized
distribution of NFC in flat space, these specifications will even
improve more. For nanopapers, strains are 1,4Gpa, 84Mpa and 17%,
13,3 Gpa, 214Mpa and 10% respectively. In layer by layer self
assembly method (LbL) the tensile strength of nanopaper with Tio3
particles and Sio2 and halloysite clay nanotube are 30,4 ±7.6Nm/g
and 13,6 ±0.8Nm/g and 14±0.3,3Nm/g respectively that fall within
acceptable range of similar samples with virgin fiber. The usage of
improved brightness and porosity index in nanopapers can create
more competitive advantages at packaging industry.
Abstract: For professions of high risk industries, simulation training has always been thought in terms of high degree of fidelity regarding the real operational situation. Due to the recent progress, this way of training is changing, modifying the human-computer and software interactions: the interactions between trainees during simulation training session tend to become virtual, transforming the social-based embodiness (the way subjects integrate social skills for interpersonal relationship with co-workers). On the basis of the analysis of eight different profession trainings, a categorization of interactions has help to produce an analytical tool, the social interactions table. This tool may be very valuable to point out the changes of social interactions when the training sessions are skipping from a high fidelity simulator to a virtual simulator. In this case, it helps the designers of professional training to analyze and to assess the consequences of the potential lack the social-based embodiness.
Abstract: In this paper, we propose a new robust and secure
system that is based on the combination between two different
transforms Discrete wavelet Transform (DWT) and Contourlet
Transform (CT). The combined transforms will compensate the
drawback of using each transform separately. The proposed
algorithm has been designed, implemented and tested successfully.
The experimental results showed that selecting the best sub-band for
embedding from both transforms will improve the imperceptibility
and robustness of the new combined algorithm. The evaluated
imperceptibility of the combined DWT-CT algorithm which gave a
PSNR value 88.11 and the combination DWT-CT algorithm
improves robustness since it produced better robust against Gaussian
noise attack. In addition to that, the implemented system shored a
successful extraction method to extract watermark efficiently.
Abstract: This paper derives some new sufficient conditions for
the stability of a class of neutral-type neural networks with discrete
time delays by employing a suitable Lyapunov functional. The
obtained conditions can be easily verified as they can be expressed
in terms of the network parameters only. It is shown that the results
presented in this paper for neutral-type delayed neural networks establish
a new set of stability criteria, and therefore can be considered
as the alternative results to the previously published literature results.
A numerical example is also given to demonstrate the applicability
of our proposed stability criterion.
Abstract: This paper employs a the variable returns to scale DEA
model to take account of risky assets and estimate the operating
efficiencies for the 21 domestic listed securities firms during the
period 2005-2009. Evidence is found that on average the brokerage
securities firms- operating efficiencies are better than integrated
securities firms. Evidence is also found that the technical inefficiency
from inappropriate management constitutes the main source of the
operating inefficiency for both types of securities firms. Moreover, the
scale economies prevail in brokerage and integrated securities firms,
in other words, which exhibit the characteristic of increasing returns to
scale.
Abstract: Prediction of highly non linear behavior of suspended
sediment flow in rivers has prime importance in the field of water
resources engineering. In this study the predictive performance of
two Artificial Neural Networks (ANNs) namely, the Radial Basis
Function (RBF) Network and the Multi Layer Feed Forward (MLFF)
Network have been compared. Time series data of daily suspended
sediment discharge and water discharge at Pari River was used for
training and testing the networks. A number of statistical parameters
i.e. root mean square error (RMSE), mean absolute error (MAE),
coefficient of efficiency (CE) and coefficient of determination (R2)
were used for performance evaluation of the models. Both the models
produced satisfactory results and showed a good agreement between
the predicted and observed data. The RBF network model provided
slightly better results than the MLFF network model in predicting
suspended sediment discharge.
Abstract: The present study is concerned with the free
convective two dimensional flow and heat transfer, within the
framework of Boussinesq approximation, in anisotropic fluid filled
porous rectangular enclosure subjected to end-to-end temperature
difference have been investigated using Lattice Boltzmann method
fornon-Darcy flow model. Effects of the moving lid direction (top,
bottom, left, and right wall moving in the negative and positive x&ydirections),
number of moving walls (one or two opposite walls), the
sliding wall velocity, and four different constant temperatures
opposite walls cases (two surfaces are being insulated and the
twoother surfaces areimposed to be at constant hot and cold
temperature)have been conducted. The results obtained are discussed
in terms of the Nusselt number, vectors, contours, and isotherms.
Abstract: Cardiac pulse-related artifacts in the EEG recorded
simultaneously with fMRI are complex and highly variable. Their
effective removal is an unsolved problem. Our aim is to develop an
adaptive removal algorithm based on the matching pursuit (MP)
technique and to compare it to established methods using a visual
evoked potential (VEP). We recorded the VEP inside the static
magnetic field of an MR scanner (with artifacts) as well as in an
electrically shielded room (artifact free). The MP-based artifact
removal outperformed average artifact subtraction (AAS) and
optimal basis set removal (OBS) in terms of restoring the EEG field
map topography of the VEP. Subsequently, a dipole model was fitted
to the VEP under each condition using a realistic boundary element
head model. The source location of the VEP recorded inside the MR
scanner was closest to that of the artifact free VEP after cleaning
with the MP-based algorithm as well as with AAS. While none of the
tested algorithms offered complete removal, MP showed promising
results due to its ability to adapt to variations of latency, frequency
and amplitude of individual artifact occurrences while still utilizing a
common template.