Abstract: A neuron can emit spikes in an irregular time basis and by averaging over a certain time window one would ignore a lot of information. It is known that in the context of fast information processing there is no sufficient time to sample an average firing rate of the spiking neurons. The present work shows that the spiking neurons are capable of computing the radial basis functions by storing the relevant information in the neurons' delays. One of the fundamental findings of the this research also is that when using overlapping receptive fields to encode the data patterns it increases the network-s clustering capacity. The clustering algorithm that is discussed here is interesting from computer science and neuroscience point of view as well as from a perspective.
Abstract: In this paper, we propose a robust scheme to work face alignment and recognition under various influences. For face representation, illumination influence and variable expressions are the important factors, especially the accuracy of facial localization and face recognition. In order to solve those of factors, we propose a robust approach to overcome these problems. This approach consists of two phases. One phase is preprocessed for face images by means of the proposed illumination normalization method. The location of facial features can fit more efficient and fast based on the proposed image blending. On the other hand, based on template matching, we further improve the active shape models (called as IASM) to locate the face shape more precise which can gain the recognized rate in the next phase. The other phase is to process feature extraction by using principal component analysis and face recognition by using support vector machine classifiers. The results show that this proposed method can obtain good facial localization and face recognition with varied illumination and local distortion.
Abstract: Textures are replications, symmetries and
combinations of various basic patterns, usually with some random
variation one of the gray-level statistics. This article proposes a
new approach to Segment texture images. The proposed approach
proceeds in 2 stages. First, in this method, local texture information
of a pixel is obtained by fuzzy texture unit and global texture
information of an image is obtained by fuzzy texture spectrum.
The purpose of this paper is to demonstrate the usefulness of fuzzy
texture spectrum for texture Segmentation.
The 2nd Stage of the method is devoted to a decision process,
applying a global analysis followed by a fine segmentation,
which is only focused on ambiguous points. The above Proposed
approach was applied to brain image to identify the components
of brain in turn, used to locate the brain tumor and its Growth
rate.
Abstract: Prior to 1975, women in Laos suffered from having
reduced levels of power over decision-making in their families and in
their communities. This has had a negative impact on their ability to
develop their own identities. Their roles were identified as being
responsible for household activities and making preparations for their
marriage. Many women lost opportunities to get educated and access
the outdoor work that might have empowered them to improve their
situations. So far, no accurate figures of either emigrants or return
migrants have been compiled but it appears that most of them were
women, and it was women who most and more frequently remitted
money home. However, very few recent studies have addressed the
relationship between remittances and the roles of women in Laos.
This study, therefore, aims at redressing to some extent the
deficiencies in knowledge. Qualitative techniques were used to gather
data, including individual in-depth interviews and direct observation
in combination with the content analysis method. Forty women in
Vientiane Municipality and Savannakhet province were individually
interviewed. It was found that the monetary remittance was typically
used for family security and well-being; on fungible activities; on
economic and business activities; and on community development,
especially concerning hospitality and providing daily household
necessities. Remittances played important roles in improving many
respondents- livelihoods and positively changed their identities in
families and communities. Women became empowered as they were
able to start commercial businesses, rather than taking care of (just)
housework, children and elders. Interviews indicated that 92.5% of
the respondents their quality of lives improved, 90% felt happier in
their families and 82.5% felt conflicts in their families were reduced.
Abstract: This paper presents a novel iris recognition system
using 1D log polar Gabor wavelet and Euler numbers. 1D log polar
Gabor wavelet is used to extract the textural features, and Euler
numbers are used to extract topological features of the iris. The
proposed decision strategy uses these features to authenticate an
individual-s identity while maintaining a low false rejection rate. The
algorithm was tested on CASIA iris image database and found to
perform better than existing approaches with an overall accuracy of
99.93%.
Abstract: A fusion classifier composed of two modules, one made by a hidden Markov model (HMM) and the other by a support vector machine (SVM), is proposed to recognize faces with pose variations in open-set recognition settings. The HMM module captures the evolution of facial features across a subject-s face using the subject-s facial images only, without referencing to the faces of others. Because of the captured evolutionary process of facial features, the HMM module retains certain robustness against pose variations, yielding low false rejection rates (FRR) for recognizing faces across poses. This is, however, on the price of poor false acceptance rates (FAR) when recognizing other faces because it is built upon withinclass samples only. The SVM module in the proposed model is developed following a special design able to substantially diminish the FAR and further lower down the FRR. The proposed fusion classifier has been evaluated in performance using the CMU PIE database, and proven effective for open-set face recognition with pose variations. Experiments have also shown that it outperforms the face classifier made by HMM or SVM alone.
Abstract: While OCD is one of the most commonly occurring
psychiatric conditions experienced by older adults, there is a paucity
of research conducted into the treatment of older adults with OCD.
This case study represents the first published investigation of a
cognitive treatment for geriatric OCD. It describes the successful
treatment of an 86-year old man with a 63-year history of OCD using
Danger Ideation Reduction Therapy (DIRT). The client received 14
individual, 50-minute treatment sessions of DIRT over 13 weeks.
Clinician-based Y-BOCS scores reduced 84% from 25 (severe) at
pre-treatment, to 4 (subclinical) at 6-month post-treatment follow-up
interview, demonstrating the efficacy of DIRT for this client. DIRT
may have particular advantages over ERP and pharmacological
approaches, however further research is required in older adults with
OCD.
Abstract: Distant-talking voice-based HCI system suffers from
performance degradation due to mismatch between the acoustic
speech (runtime) and the acoustic model (training). Mismatch is
caused by the change in the power of the speech signal as observed at
the microphones. This change is greatly influenced by the change in
distance, affecting speech dynamics inside the room before reaching
the microphones. Moreover, as the speech signal is reflected, its
acoustical characteristic is also altered by the room properties. In
general, power mismatch due to distance is a complex problem. This
paper presents a novel approach in dealing with distance-induced
mismatch by intelligently sensing instantaneous voice power variation
and compensating model parameters. First, the distant-talking speech
signal is processed through microphone array processing, and the
corresponding distance information is extracted. Distance-sensitive
Gaussian Mixture Models (GMMs), pre-trained to capture both
speech power and room property are used to predict the optimal
distance of the speech source. Consequently, pre-computed statistic
priors corresponding to the optimal distance is selected to correct
the statistics of the generic model which was frozen during training.
Thus, model combinatorics are post-conditioned to match the power
of instantaneous speech acoustics at runtime. This results to an
improved likelihood in predicting the correct speech command at
farther distances. We experiment using real data recorded inside two
rooms. Experimental evaluation shows voice recognition performance
using our method is more robust to the change in distance compared
to the conventional approach. In our experiment, under the most
acoustically challenging environment (i.e., Room 2: 2.5 meters), our
method achieved 24.2% improvement in recognition performance
against the best-performing conventional method.
Abstract: Nowadays, with the emerging of the new applications
like robot control in image processing, artificial vision for visual
servoing is a rapidly growing discipline and Human-machine
interaction plays a significant role for controlling the robot. This
paper presents a new algorithm based on spatio-temporal volumes for
visual servoing aims to control robots. In this algorithm, after
applying necessary pre-processing on video frames, a spatio-temporal
volume is constructed for each gesture and feature vector is extracted.
These volumes are then analyzed for matching in two consecutive
stages. For hand gesture recognition and classification we tested
different classifiers including k-Nearest neighbor, learning vector
quantization and back propagation neural networks. We tested the
proposed algorithm with the collected data set and results showed the
correct gesture recognition rate of 99.58 percent. We also tested the
algorithm with noisy images and algorithm showed the correct
recognition rate of 97.92 percent in noisy images.
Abstract: Several works regarding facial recognition have dealt with methods which identify isolated characteristics of the face or with templates which encompass several regions of it. In this paper a new technique which approaches the problem holistically dispensing with the need to identify geometrical characteristics or regions of the face is introduced. The characterization of a face is achieved by randomly sampling selected attributes of the pixels of its image. From this information we construct a set of data, which correspond to the values of low frequencies, gradient, entropy and another several characteristics of pixel of the image. Generating a set of “p" variables. The multivariate data set with different polynomials minimizing the data fitness error in the minimax sense (L∞ - Norm) is approximated. With the use of a Genetic Algorithm (GA) it is able to circumvent the problem of dimensionality inherent to higher degree polynomial approximations. The GA yields the degree and values of a set of coefficients of the polynomials approximating of the image of a face. By finding a family of characteristic polynomials from several variables (pixel characteristics) for each face (say Fi ) in the data base through a resampling process the system in use, is trained. A face (say F ) is recognized by finding its characteristic polynomials and using an AdaBoost Classifier from F -s polynomials to each of the Fi -s polynomials. The winner is the polynomial family closer to F -s corresponding to target face in data base.
Abstract: Webcam systems now function as the new privileged
vantage points from which to view the city. This transformation of
CCTV technology from surveillance to promotional tool is significant
because its'scopic regime' presents, back to the public, a new virtual
'site' that sits alongside its real-time counterpart. Significantly,
thisraw 'image' data can, in fact,be co-optedand processed so as to
disrupt their original purpose. This paper will demonstrate this
disruptive capacity through an architectural project. It will reveal how
the adaption the webcam image offers a technical springboard by
which to initiate alternate urban form making decisions and subvert
the disciplinary reliance on the 'flat' orthographic plan. In so doing,
the paper will show how this 'digital material' exceeds the imagistic
function of the image; shiftingit from being a vehicle of signification
to a site of affect.
Abstract: The purpose of this study was to understand the main
sources of copper (Cu) accumulation in target organs of tilapia
(Oreochromis mossambicus) and to investigate how the organism
mediate the process of Cu accumulation under prolonged conditions.
By measuring both dietary and waterborne Cu accumulation and total
concentrations in tilapia with biokinetic modeling approach, we were
able to clarify the biokinetic coping mechanisms for the long term Cu
accumulation. This study showed that water and food are both the
major source of Cu for the muscle and liver of tilapia. This implied
that control the Cu concentration in these two routes will be correlated
to the Cu bioavailability for tilapia. We found that exposure duration
and level of waterborne Cu drove the Cu accumulation in tilapia. The
ability for Cu biouptake and depuration in organs of tilapia were
actively mediated under prolonged exposure conditions. Generally,
the uptake rate, depuration rate and net bioaccumulation ability in all
selected organs decreased with the increasing level of waterborne Cu
and extension of exposure duration.Muscle tissues accounted for over
50%of the total accumulated Cu and played a key role in buffering the
Cu burden in the initial period of exposure, alternatively, the liver
acted a more important role in the storage of Cu with the extension of
exposures. We concluded that assumption of the constant biokinetic
rates could lead to incorrect predictions with overestimating the
long-term Cu accumulation in ecotoxicological risk assessments.
Abstract: In the recent works related with mixture discriminant
analysis (MDA), expectation and maximization (EM) algorithm is
used to estimate parameters of Gaussian mixtures. But, initial values
of EM algorithm affect the final parameters- estimates. Also, when
EM algorithm is applied two times, for the same data set, it can be
give different results for the estimate of parameters and this affect the
classification accuracy of MDA. Forthcoming this problem, we use
Self Organizing Mixture Network (SOMN) algorithm to estimate
parameters of Gaussians mixtures in MDA that SOMN is more robust
when random the initial values of the parameters are used [5]. We
show effectiveness of this method on popular simulated waveform
datasets and real glass data set.
Abstract: In this article, while it is attempted to describe the
problem and its importance, transformational leadership is studied by considering leadership theories. Issues such as the definition of
transformational leadership and its aspects are compared on the basis of the ideas of various connoisseurs and then it (transformational leadership) is examined in successful and
unsuccessful companies. According to the methodology, the
method of research, hypotheses, population and statistical sample
are investigated and research findings are analyzed by using descriptive and inferential statistical methods in the framework of
analytical tables. Finally, our conclusion is provided by considering the results of statistical tests. The final result shows that
transformational leadership is significantly higher in successful companies than unsuccessful ones P
Abstract: In this paper, a decision aid method for preoptimization
is presented. The method is called “negotiation", and it
is based on the identification, formulation, modeling and use of
indicators defined as “negotiation indicators". These negotiation
indicators are used to explore the solution space by means of a classbased
approach. The classes are subdomains for the negotiation
indicators domain. They represent equivalent cognitive solutions in
terms of the negotiation indictors being used. By this method, we
reduced the size of the solution space and the criteria, thus aiding the
optimization methods. We present an example to show the method.
Abstract: As a part of the development of a numerical method of
close capture exhausts systems for machining devices, a test rig
recreating a situation similar to a grinding operation, but in a
perfectly controlled environment, is used. The properties of the
obtained spray of solid particles are initially characterized using
particle tracking velocimetry (PTV), in order to obtain input and
validation parameters for numerical simulations. The dispersion of a
tracer gas (SF6) emitted simultaneously with the particle jet is then
studied experimentally, as the dispersion of such a gas is
representative of that of finer particles, whose aerodynamic response
time is negligible. Finally, complete modeling of the test rig is
achieved to allow comparison with experimental results and thus to
progress towards validation of the models used to describe a twophase
flow generated by machining operation.
Abstract: Currently, the demand for marine and fisheries commodity in Yogyakarta, Indonesia continues to increase. The existing condition shows that the aquaculture supply cannot be supplied by Yogyakarta region itself, but still need to be supported by regions outside Yogyakarta. The effort to optimize the market is initiated by reviewing and designing the supply chain of production and trade of aquaculture commodity in order to create the implementation of aquaculture production and trade commodity optimally. This formulated supply chain model indicates 4 performance indicators of measurable success in terms of: (1) efficiency; (2) flexibility; (3) responsiveness; and (4) quality. These indicators had been exercised as the success benchmarks for priority marketing management in local level as well as national level. The result of this research indicates that if the catfish fishery system is managed as business as usual then the catfish demand in Yogyakarta region will experience to increase in the future. The increase of demand is inline with the increase of number of people in Yogyakarta and also the fluctuation of catfish consumption per capita. The highest production of catfish will experience in the third year approximately 30,118 tons. Other result of the research indicates that the catfish demand in Yogyakarta region cannot be supplied yet from the local region. Therefore, to fulfill the supply from outside Yogyakarta region, the local farmers should improve the supply through land extension. The fluctuation of commodity price will experience in the future annually and the catfish supply from outside Yogyakarta region will be lowering the price in the market.
Abstract: In this study, a 3D combustion chamber was simulated
using FLUENT 6.32. Aims to obtain accurate information about the
profile of the combustion in the furnace and also check the effect of
oxygen enrichment on the combustion process. Oxygen enrichment is
an effective way to reduce combustion pollutant. The flow rate of air
to fuel ratio is varied as 1.3, 3.2 and 5.1 and the oxygen enriched
flow rates are 28, 54 and 68 lit/min. Combustion simulations
typically involve the solution of the turbulent flows with heat
transfer, species transport and chemical reactions. It is common to
use the Reynolds-averaged form of the governing equation in
conjunction with a suitable turbulence model. The 3D Reynolds
Averaged Navier Stokes (RANS) equations with standard k-ε
turbulence model are solved together by Fluent 6.3 software. First
order upwind scheme is used to model governing equations and the
SIMPLE algorithm is used as pressure velocity coupling. Species
mass fractions at the wall are assumed to have zero normal
gradients.Results show that minimum mole fraction of CO2 happens
when the flow rate ratio of air to fuel is 5.1. Additionally, in a fixed
oxygen enrichment condition, increasing the air to fuel ratio will
increase the temperature peak. As a result, oxygen-enrichment can
reduce the CO2 emission at this kind of furnace in high air to fuel
rates.
Abstract: This paper reports on the results of experimental
investigations of flash evaporation from superheated jet issues
vertically upward from a round straight nozzle of 81.3 mm diameter.
For the investigated range of jet superheat degree and velocity, it was
shown that flash evaporation enhances with initial temperature
increase. Due to the increase of jet inertia and subsequently the delay
of jet shattering, increase of jet velocity was found to result in
increase of evaporation "delay period". An empirical equation
predicts the jet evaporation completion height was developed, this
equation is thought to be useful in designing the flash evaporation
chamber. In attempts for enhancement of flash evaporation, use of
steel wire mesh located at short distance downstream was found
effective with no consequent pressure drop.
Abstract: Client expectations and preferences about therapy
represent an important area of investigation as research shows they
are linked to engagement in therapy and therapy outcomes. Studies
examining young people-s expectations and preferences of therapy
remain a neglected area of research. The present study explored what
expectations and preferences young people seeking professional help
held regarding: their role as a client, their therapist-s role, their
therapeutic outcomes, and the processes of therapy. Gender and age
differences were also examined. Participants included 188 young
people aged 12-25 who completed a survey while attending their
initial session at a youth mental health service. Data were analysed
using quantitative methods. Results found the young people held
significantly more pessimistic expectations around therapy when
compared to what they had wanted therapy to be like. Few age and
gender differences were found. Results highlight the importance of a
collaborative therapy approach when working with young people.