Abstract: This paper proposes a hybrid method for eyes localization
in facial images. The novelty is in combining techniques
that utilise colour, edge and illumination cues to improve accuracy.
The method is based on the observation that eye regions have dark
colour, high density of edges and low illumination as compared
to other parts of face. The first step in the method is to extract
connected regions from facial images using colour, edge density and
illumination cues separately. Some of the regions are then removed
by applying rules that are based on the general geometry and shape
of eyes. The remaining connected regions obtained through these
three cues are then combined in a systematic way to enhance the
identification of the candidate regions for the eyes. The geometry
and shape based rules are then applied again to further remove the
false eye regions. The proposed method was tested using images from
the PICS facial images database. The proposed method has 93.7%
and 87% accuracies for initial blobs extraction and final eye detection
respectively.
Abstract: The Aggregate Production Plan (APP) is a schedule of
the organization-s overall operations over a planning horizon to
satisfy demand while minimizing costs. It is the baseline for any
further planning and formulating the master production scheduling,
resources, capacity and raw material planning. This paper presents a
methodology to model the Aggregate Production Planning problem,
which is combinatorial in nature, when optimized with Genetic
Algorithms. This is done considering a multitude of constraints of
contradictory nature and the optimization criterion – overall cost,
made up of costs with production, work force, inventory, and
subcontracting. A case study of substantial size, used to develop the
model, is presented, along with the genetic operators.
Abstract: This research aims to study the lead pollution in the air of Babylon governorate that resulted generally from vehicles exhausts in addition to industrial and human activities.Vehicles number in Babylon governorate increased significantly after year 2003 that resulted with increase in lead emissions into the air.Measurement of lead emissions was done in seven stations distributed randomly in Babylon governorate. These stations where located in Industrial (Al-Sena'ay) Quarter, 60 street (near to Babylon sewer directorate), 40 Street (near to the first intersection), Al-Hashmia city, Al-Mahaweel city, , Al- Musayab city in addition to another station in Sayd Idris village belong to Abugharaq district (Agricultural station for comparison). The measured concentrations in these stations were compared with the standard limits of Environmental Protection Agency EPA (2 μg /m3). The results of this study showed that the average of lead concentrations ,in Babylon governorate during year 2010, was (3.13 μg/m3) which was greater than standard limits (2 μg/m3). The maximum concentration of lead was (6.41 μg / m3) recorded in the Industrial (Al-Sena'ay) Quarter during April month, while the minimum concentrations was (0.36 μg / m3) recorded in the agricultural station (Abugharaq) during December month.
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: In this paper , by using fixed point theorem , upper and lower solution-s method and monotone iterative technique , we prove the existence of maximum and minimum solutions of differential equations with delay , which improved and generalize the result of related paper.
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: Sparse representation which can represent high dimensional
data effectively has been successfully used in computer vision
and pattern recognition problems. However, it doesn-t consider the
label information of data samples. To overcome this limitation,
we develop a novel dimensionality reduction algorithm namely
dscriminatively regularized sparse subspace learning(DR-SSL) in this
paper. The proposed DR-SSL algorithm can not only make use of
the sparse representation to model the data, but also can effective
employ the label information to guide the procedure of dimensionality
reduction. In addition,the presented algorithm can effectively deal
with the out-of-sample problem.The experiments on gene-expression
data sets show that the proposed algorithm is an effective tool for
dimensionality reduction and gene-expression data classification.
Abstract: Nowadays there are several grid connected converter
in the grid system. These grid connected converters are generally the
converters of renewable energy sources, industrial four quadrant
drives and other converters with DC link. These converters are
connected to the grid through a three phase bridge. The standards
prescribe the maximal harmonic emission which could be easily
limited with high switching frequency. The increased switching
losses can be reduced to the half with the utilization of the wellknown
Flat-top modulation. The suggested control method is the
expansion of the Flat-top modulation with which the losses could be
also reduced to the half compared to the Flat-top modulation.
Comparing to traditional control these requirements can be
simultaneously satisfied much better with the DLF (DC Link
Floating) method.
Abstract: The present work encounters the solution of the defect identification problem with the use of an evolutionary algorithm combined with a simplex method. In more details, a Matlab implementation of Genetic Algorithms is combined with a Simplex method in order to lead to the successful identification of the defect. The influence of the location and the orientation of the depressed ellipsoidal flaw was investigated as well as the use of different amount of static data in the cost function. The results were evaluated according to the ability of the simplex method to locate the global optimum in each test case. In this way, a clear impression regarding the performance of the novel combination of the optimization algorithms, and the influence of the geometrical parameters of the flaw in defect identification problems was obtained.
Abstract: In this paper, we present an experimental testing for
a new algorithm that determines an optimal controller-s coefficients
for output variance reduction related to Linear Time Invariant (LTI)
Systems. The algorithm features simplicity in calculation, generalization
to minimal and non-minimal phase systems, and could be
configured to achieve reference tracking as well as variance reduction
after compromising with the output variance. An experiment of DCmotor
velocity control demonstrates the application of this new
algorithm in designing the controller. The results show that the
controller achieves minimum variance and reference tracking for a
preset velocity reference relying on an identified model of the motor.
Abstract: A hybrid Photovoltaic/Thermal (PV/T) solar system integrates photovoltaic and solar thermal technologies into one single solar energy device, with dual generation of electricity and heat energy. The aim of the present study is to evaluate the potential for introduction of the PV/T technology into Northern China. For this purpose, outdoor experiments were conducted on a prototype of a PV/T water-heating system. The annual thermal and electrical performances were investigated under the climatic conditions of Beijing. An economic analysis of the system was then carried out, followed by a sensitivity study. The analysis revealed that the hybrid system is not economically attractive with the current market and energy prices. However, considering the continuous commitment of the Chinese government towards policy development in the renewable energy sector, and technological improvements like the increasing cost-effectiveness of PV cells, PV/Thermal technology may become economically viable in the near future.
Abstract: Transcription factors are a group of proteins that
helps for interpreting the genetic information in DNA.
Protein-protein interactions play a major role in the execution
of key biological functions of a cell. These interactions are
represented in the form of a graph with nodes and edges.
Studies have showed that some nodes have high degree of
connectivity and such nodes, known as hub nodes, are the
inevitable parts of the network. In the present paper a method
is proposed to identify hub transcription factor proteins using
sequence information. On a complete data set of transcription
factor proteins available from the APID database, the
proposed method showed an accuracy of 77%, sensitivity of
79% and specificity of 76%.
Abstract: This paper proposes an improvement method of classification
efficiency in a classification model. The model is used
in a risk search system and extracts specific labels from articles
posted at bulletin board sites. The system can analyze the important
discussions composed of the articles. The improvement method
introduces ensemble learning methods that use multiple classification
models. Also, it introduces expressions related to the specific labels
into generation of word vectors. The paper applies the improvement
method to articles collected from three bulletin board sites selected
by users and verifies the effectiveness of the improvement method.
Abstract: The objective of this research is to calculate the
optimal inventory lot-sizing for each supplier and minimize the total
inventory cost which includes joint purchase cost of the products,
transaction cost for the suppliers, and holding cost for remaining
inventory. Genetic algorithms (GAs) are applied to the multi-product
and multi-period inventory lot-sizing problems with supplier
selection under storage space. Also a maximum storage space for the
decision maker in each period is considered. The decision maker
needs to determine what products to order in what quantities with
which suppliers in which periods. It is assumed that demand of
multiple products is known over a planning horizon. The problem is
formulated as a mixed integer programming and is solved with the
GAs. The detailed computation results are presented.
Abstract: Cenozoic basalts found in Jiangsu province of eastern
China include tholeiites and alkali basalts. The present paper analyzed
the major, trace elements, rare earth elements of these Cenozoic
basalts and combined with Sr-Nd isotopic compositions proposed by
Chen et al. (1990)[1] in the literatures to discuss the petrogenesis of
these basalts and the geochemical characteristics of the source mantle.
Based on major, trace elements and fractional crystallization model
established by Brooks and Nielsen (1982)[2] we suggest that the
basaltic magma has experienced olivine + clinopyroxene fractionation
during its evolution. The chemical compositions of basaltic rocks from
Jiangsu province indicate that these basalts may belong to the same
magmatic system. Spidergrams reveal that Cenozoic basalts from
Jiangsu province have geochemical characteristics similar to those of
ocean island basalts(OIB). The slight positive Nb and Ti anomalies
found in basaltic rocks of this study suggest the presence of Ti-bearing
minerals in the mantle source and these Ti-bearing minerals had
contributed to basaltic magma during partial melting, indicating a
metasomatic event might have occurred before the partial melting.
Based on the Sr vs. Nd isotopic ratio plots, we suggest that Jiangsu
basalts may be derived from partial melting of mantle source which
may represent two-end members mixing of DMM and EM-I. Some
Jiangsu basaltic magma may be derived from partial melting of EM-I
heated by the upwelling asthenospheric mantle or asthenospheric
diapirism.
Abstract: Gene, principal unit of inheritance, is an ordered
sequence of nucleotides. The genes of eukaryotic organisms include
alternating segments of exons and introns. The region of
Deoxyribonucleic acid (DNA) within a gene containing instructions
for coding a protein is called exon. On the other hand, non-coding
regions called introns are another part of DNA that regulates gene
expression by removing from the messenger Ribonucleic acid (RNA)
in a splicing process. This paper proposes to determine splice
junctions that are exon-intron boundaries by analyzing DNA
sequences. A splice junction can be either exon-intron (EI) or intron
exon (IE). Because of the popularity and compatibility of the
artificial neural network (ANN) in genetic fields; various ANN
models are applied in this research. Multi-layer Perceptron (MLP),
Radial Basis Function (RBF) and Generalized Regression Neural
Networks (GRNN) are used to analyze and detect the splice junctions
of gene sequences. 10-fold cross validation is used to demonstrate
the accuracy of networks. The real performances of these networks
are found by applying Receiver Operating Characteristic (ROC)
analysis.
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: This article experimentally investigates the
thermal performance of thermoelectric air-cooling module
which comprises a thermoelectric cooler (TEC) and an
air-cooling heat sink. The influences of input current and heat
load are determined. And performances under each situation
are quantified by thermal resistance analysis. Since TEC
generates Joule heat, this nature makes construction of thermal
resistance network difficult. To simplify the analysis, this
article emphasizes on the resistance heat load might meet when
passing through the device. Therefore, the thermal resistances
in this paper are to divide temperature differences by heat load.
According to the result, there exists an optimum input current
under every heating power. In this case, the optimum input
current is around 6A or 7A. The performance of the heat sink
would be improved with TEC under certain heating power and
input current, especially at a low heat load. According to the
result, the device can even make the heat source cooler than the
ambient. However, TEC is not always effective at every heat
load and input current. In some situation, the device works
worse than the heat sink without TEC. To determine the
availability of TEC, this study figures out the effective
operating region in which the TEC air-cooling module works
better than the heat sink without TEC. The result shows that
TEC is more effective at a lower heat load. If heat load is too
high, heat sink with TEC will perform worse than without TEC.
The limit of this device is 57W. Besides, TEC is not helpful if
input current is too high or too low. There is an effective range
of input current, and the range becomes narrower when the heat
load grows.
Abstract: The three-time-scale plant model of a wind power
generator, including a wind turbine, a flexible vertical shaft, a Variable
Inertia Flywheel (VIF) module, an Active Magnetic Bearing (AMB)
unit and the applied wind sequence, is constructed. In order to make
the wind power generator be still able to operate as the spindle speed
exceeds its rated speed, the VIF is equipped so that the spindle speed
can be appropriately slowed down once any stronger wind field is
exerted. To prevent any potential damage due to collision by shaft
against conventional bearings, the AMB unit is proposed to regulate
the shaft position deviation. By singular perturbation order-reduction
technique, a lower-order plant model can be established for the
synthesis of feedback controller. Two major system parameter
uncertainties, an additive uncertainty and a multiplicative uncertainty,
are constituted by the wind turbine and the VIF respectively.
Frequency Shaping Sliding Mode Control (FSSMC) loop is proposed
to account for these uncertainties and suppress the unmodeled
higher-order plant dynamics. At last, the efficacy of the FSSMC is
verified by intensive computer and experimental simulations for
regulation on position deviation of the shaft and counter-balance of
unpredictable wind disturbance.
Abstract: Magnesium is used implant material potentially for
non-toxicity to the human body. Due to the excellent
bio-compatibility, Mg alloys is applied to implants avoiding removal
second surgery. However, it is found commercial magnesium alloys
including aluminum has low corrosion resistance, resulting
subcutaneous gas bubbles and consequently the approach as
permanent bio-materials. Generally, Aluminum is known to pollution
substance, and it raises toxicity to nervous system. Therefore
especially Mg-35Zn-3Ca alloy is prepared for new biodegradable
materials in this study. And the pulsed power is used in
constant-current mode of DC power kinds of anodization. Based on
the aforementioned study, it examines corrosion resistance and
biocompatibility by effect of current and frequency variation. The
surface properties and thickness were compared using scanning
electronic microscopy. Corrosion resistance was assessed via
potentiodynamic polarization and the effect of oxide layer on the body
was assessed cell viability. Anodized Mg-35Zn-3Ca alloy has good
biocompatibility in vitro by current and frequency variation.