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: Brand loyalty is a strategic asset of the company. In
the era of competition to have loyal customers decides on the market
superiority of enterprises. Creating the loyalty of buyers, however, is
a lengthy process and requires the appropriate business strategy,
preceded by the proper market research. The purpose of the paper is
to present the concept of brand loyalty, the creation of loyalty of
customers, the benefits and determinants of loyalty on the example of
brewery market in Poland.
Abstract: This study aims to identify the current situation and
problems of environmental statement for major four home appliances
(refrigerators, washing machines, air conditioners and television
receivers) sold at online stores in Japan, and then to suggest how to
improve the situation, through a questionnaire survey conducted
among businesses that operate online stores and online malls with
multiple online stores. Results of the study boil down to:
(1) It is found out that environmental statement for the home
appliances at online stores have four problems; (i) less information
on “three Rs" and “chemical substances" than the one on “energy
conservation", (ii) cost for providing environmental statement, (iii)
issues associated with a label and mark placement, and (iv) issues
associated with energy conservation statement.
(2) Improvements are suggested for each of the four problems listed
above, and shown are (i) the effectiveness of, and need to promote, a
label and mark placement, (ii) cost burden on buyers, and (iii) need
of active efforts made by businesses and of dissemination of legal
regulations to businesses.
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: Luxury is an identity, a philosophy and a culture
which requires understanding before the adoption of e-business
practices because of its intricacies and output are essentially different
from other types of goods. Factors such as culture, personal
characteristics, website quality, and vendor characteristics influence
the online purchasing behavior of consumers thus making it a
complex area of study. This paper explores the scope of e-retail for
luxury consumption in the U.A.E. by identifying what motivates and
de-motivates online purchase behavior of U.A.E. consumers and
necessary hypotheses have been drawn to reflect behavior between
online luxury preference consumers and non-online luxury preference
consumers.
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: It is important to predict yield in semiconductor test process in order to increase yield. In this study, yield prediction means finding out defective die, wafer or lot effectively. Semiconductor test process consists of some test steps and each test includes various test items. In other world, test data has a big and complicated characteristic. It also is disproportionably distributed as the number of data belonging to FAIL class is extremely low. For yield prediction, general data mining techniques have a limitation without any data preprocessing due to eigen properties of test data. Therefore, this study proposes an under-sampling method using support vector machine (SVM) to eliminate an imbalanced characteristic. For evaluating a performance, randomly under-sampling method is compared with the proposed method using actual semiconductor test data. As a result, sampling method using SVM is effective in generating robust model for yield prediction.
Abstract: Route bus system is one of fundamental transportation device for aged people and students, and has an important role in every province. However, passengers decrease year by year, therefore the authors have developed the system called "Bus-Net" as a web application to sustain the public transport. But there are two problems in Bus-Net. One is the user interface that does not consider the variety of the device, and the other is the path planning system that dose not correspond to the on-demand bus. Then, Bus-Net was improved to be able to utilize the variety of the device, and a new function corresponding to the on-demand bus was developed.
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: Transesterified vegetable oils (biodiesel) are promising alternative fuel for diesel engines. Used vegetable oils are disposed from restaurants in large quantities. But higher viscosity restricts their direct use in diesel engines. In this study, used cooking oil was dehydrated and then transesterified using an alkaline catalyst. The combustion, performance and emission characteristics of Used Cooking oil Methyl Ester (UCME) and its blends with diesel oil are analysed in a direct injection C.I. engine. The fuel properties and the combustion characteristics of UCME are found to be similar to those of diesel. A minor decrease in thermal efficiency with significant improvement in reduction of particulates, carbon monoxide and unburnt hydrocarbons is observed compared to diesel. The use of transesterified used cooking oil and its blends as fuel for diesel engines will reduce dependence on fossil fuels and also decrease considerably the environmental pollution.
Abstract: In this paper, we propose a novel frequency offset
estimation scheme for orthogonal frequency division multiplexing
(OFDM) systems. By correlating the OFDM signals within the coherence
phase bandwidth and employing a threshold in the frequency
offset estimation process, the proposed scheme is not only robust to
the timing offset but also has a reduced complexity compared with
that of the conventional scheme. Moreover, a timing offset estimation
scheme is also proposed as the next stage of the proposed frequency
offset estimation. Numerical results show that the proposed scheme
can estimate frequency offset with lower computational complexity
and does not require additional memory while maintaining the same
level of estimation performance.
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: 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 examines the problem of designing robust H controllers for for HIV/AIDS infection system with dual drug dosages described by a Takagi-Sugeno (S) fuzzy model. Based on a linear matrix inequality (LMI) approach, we develop an H controller which guarantees the L2-gain of the mapping from the exogenous input noise to the regulated output to be less than some prescribed value for the system. A sufficient condition of the controller for this system is given in term of Linear Matrix Inequalities (LMIs). The effectiveness of the proposed controller design methodology is finally demonstrated through simulation results. It has been shown that the anti-HIV vaccines are critically important in reducing the infected cells.
Abstract: Functional Magnetic Resonance Imaging(fMRI) is a
noninvasive imaging technique that measures the hemodynamic
response related to neural activity in the human brain. Event-related
functional magnetic resonance imaging (efMRI) is a form of
functional Magnetic Resonance Imaging (fMRI) in which a series of
fMRI images are time-locked to a stimulus presentation and averaged
together over many trials. Again an event related potential (ERP) is a
measured brain response that is directly the result of a thought or
perception. Here the neuronal response of human visual cortex in
normal healthy patients have been studied. The patients were asked
to perform a visual three choice reaction task; from the relative
response of each patient corresponding neuronal activity in visual
cortex was imaged. The average number of neurons in the adult
human primary visual cortex, in each hemisphere has been estimated
at around 140 million. Statistical analysis of this experiment was
done with SPM5(Statistical Parametric Mapping version 5) software.
The result shows a robust design of imaging the neuronal activity of
human visual cortex.
Abstract: Employee-s task performance has been recognized as a
core contributor to overall organizational effectiveness. Hence,
verifying the determinants of task performance is one of the most
important research issues. This study tests the influence of perceived
organizational support, abusive supervision, and exchange ideology
on employee-s task performance. We examined our hypotheses by
collecting self-reported data from 413 Korean employees in different
organizations. Our all hypotheses gained support from the results.
Implications for research and directions for future research are
discussed.
Abstract: Economic dispatch problem is an optimization problem where objective function is highly non linear, non-convex, non-differentiable and may have multiple local minima. Therefore, classical optimization methods may not converge or get trapped to any local minima. This paper presents a comparative study of four different evolutionary algorithms i.e. genetic algorithm, bacteria foraging optimization, ant colony optimization and particle swarm optimization for solving the economic dispatch problem. All the methods are tested on IEEE 30 bus test system. Simulation results are presented to show the comparative performance of these methods.
Abstract: The performance of a sucrose-based H2 production in
a completely stirred tank reactor (CSTR) was modeled by neural
network back-propagation (BP) algorithm. The H2 production was
monitored over a period of 450 days at 35±1 ºC. The proposed model
predicts H2 production rates based on hydraulic retention time
(HRT), recycle ratio, sucrose concentration and degradation, biomass
concentrations, pH, alkalinity, oxidation-reduction potential (ORP),
acids and alcohols concentrations. Artificial neural networks (ANNs)
have an ability to capture non-linear information very efficiently. In
this study, a predictive controller was proposed for management and
operation of large scale H2-fermenting systems. The relevant control
strategies can be activated by this method. BP based ANNs modeling
results was very successful and an excellent match was obtained
between the measured and the predicted rates. The efficient H2
production and system control can be provided by predictive control
method combined with the robust BP based ANN modeling tool.
Abstract: Understanding of how and where NOx formation
occurs in industrial burner is very important for efficient and clean
operation of utility burners. Also the importance of this problem is
mainly due to its relation to the pollutants produced by more burners
used widely of gas turbine in thermal power plants and glass and steel
industry.
In this article, a numerical model of an industrial burner operating
in MILD combustion is validated with experimental data.. Then
influence of air flow rate and air temperature on combustor
temperature profiles and NOX product are investigated. In order to
modification this study reports on the effects of fuel and air dilution
(with inert gases H2O, CO2, N2), and also influence of lean-premixed
of fuel, on the temperature profiles and NOX emission.
Conservation equations of mass, momentum and energy, and
transport equations of species concentrations, turbulence, combustion
and radiation modeling in addition to NO modeling equations were
solved together to present temperature and NO distribution inside the
burner.
The results shows that dilution, cause to a reduction in value of
temperature and NOX emission, and suppresses any flame
propagation inside the furnace and made the flame inside the furnace
invisible. Dilution with H2O rather than N2 and CO2 decreases further
the value of the NOX. Also with raise of lean-premix level, local
temperature of burner and the value of NOX product are decreases
because of premixing prevents local “hot spots" within the combustor
volume that can lead to significant NOx formation. Also leanpremixing
of fuel with air cause to amount of air in reaction zone is
reach more than amount that supplied as is actually needed to burn
the fuel and this act lead to limiting NOx formation