Abstract: In large datasets, identifying exceptional or rare cases
with respect to a group of similar cases is considered very significant
problem. The traditional problem (Outlier Mining) is to find
exception or rare cases in a dataset irrespective of the class label of
these cases, they are considered rare events with respect to the whole
dataset. In this research, we pose the problem that is Class Outliers
Mining and a method to find out those outliers. The general
definition of this problem is “given a set of observations with class
labels, find those that arouse suspicions, taking into account the
class labels". We introduce a novel definition of Outlier that is Class
Outlier, and propose the Class Outlier Factor (COF) which measures
the degree of being a Class Outlier for a data object. Our work
includes a proposal of a new algorithm towards mining of the Class
Outliers, presenting experimental results applied on various domains
of real world datasets and finally a comparison study with other
related methods is performed.
Abstract: Color image segmentation plays an important role in
computer vision and image processing areas. In this paper, the
features of Volterra filter are utilized for color image segmentation.
The discrete Volterra filter exhibits both linear and nonlinear
characteristics. The linear part smoothes the image features in
uniform gray zones and is used for getting a gross representation of
objects of interest. The nonlinear term compensates for the blurring
due to the linear term and preserves the edges which are mainly used
to distinguish the various objects. The truncated quadratic Volterra
filters are mainly used for edge preserving along with Gaussian noise
cancellation. In our approach, the segmentation is based on K-means
clustering algorithm in HSI space. Both the hue and the intensity
components are fully utilized. For hue clustering, the special cyclic
property of the hue component is taken into consideration. The
experimental results show that the proposed technique segments the
color image while preserving significant features and removing noise
effects.
Abstract: The present paper is an experimental investigation of
roughness effects on nucleate pool boiling of refrigerant R113 on
horizontal circular copper surfaces. The copper samples were treated
by different sand paper grit sizes to achieve different surface
roughness. The average surface roughness of the four samples was
0.901, 0.735, 0.65, and 0.09, respectively. The experiments were
performed in the heat flux range of 8 to 200kW/m2. The heat transfer
coefficient was calculated by measuring wall superheat of the
samples and the input heat flux. The results show significant
improvement of heat transfer coefficient as the surface roughness is
increased. It is found that the heat transfer coefficient of the sample
with Ra=0.901 is 3.4, 10.5, and 38.5% higher in comparison with
surfaces with Ra of 0.735, 0.65, and 0.09 at heat flux of 170 kW/m2.
Moreover, the results are compared with literature data and the well
known Cooper correlation.
Abstract: Ability of accurate and reliable location estimation in
indoor environment is the key issue in developing great number of
context aware applications and Location Based Services (LBS).
Today, the most viable solution for localization is the Received
Signal Strength (RSS) fingerprinting based approach using wireless
local area network (WLAN). This paper presents two RSS
fingerprinting based approaches – first we employ widely used
WLAN based positioning as a reference system and then investigate
the possibility of using GSM signals for positioning. To compare
them, we developed a positioning system in real world environment,
where realistic RSS measurements were collected. Multi-Layer
Perceptron (MLP) neural network was used as the approximation
function that maps RSS fingerprints and locations. Experimental
results indicate advantage of WLAN based approach in the sense of
lower localization error compared to GSM based approach, but GSM
signal coverage by far outreaches WLAN coverage and for some
LBS services requiring less precise accuracy our results indicate that
GSM positioning can also be a viable solution.
Abstract: Periphyton development and composition were
studied in three different treatments: (i) two fishpond units of
wetland-type wastewater treatment pond systems, (ii) two fishponds
in combined intensive-extensive fish farming systems and (iii) three
traditional polyculture fishponds. Results showed that amounts of
periphyton developed in traditional polyculture fishponds (iii) were
different compared to the other treatments (i and ii), where the main
function of ponds was stated wastewater treatment. Negative
correlation was also observable between water quality parameters
and periphyton production. The lower trophity, halobity and
saprobity level of ponds indicated higher amount of periphyton. The
dry matter content of periphyton was significantly higher in the
samples, which were developed in traditional polyculture fishponds
(2.84±3.02 g m-2 day-1, whereby the ash content in dry matter 74%),
than samples taken from (i) (1.60±2.32 g m-2 day-1, 61%) and (ii)
fishponds (0.65±0.45 g m-2 day-1, 81%).
Abstract: Scaffolds play a key role in tissue engineering and can be produced in many different ways depending on the applications and the materials used. Most researchers used an experimental trialand- error approach into new biomaterials but computer simulation applied to tissue engineering can offer a more exhaustive approach to test and screen out biomaterials. This paper develops the model of scaffolds and Computational Fluid Dynamics that show the value of computer simulations in determining the influence of the geometrical scaffold parameter porosity, pore size and shape on the permeability of scaffolds, magnitude of velocity, drop pressure, shear stress distribution and level and the proper design of the geometry of the scaffold. This creates a need for more advanced studies that include aspects of dynamic conditions of a micro fluid passing through the scaffold were characterized for tissue engineering applications and differentiation of tissues within scaffolds.
Abstract: In this note, a theoretical model for analyzing of
normal penetration of the ogive – nose projectile into metallic targets
is presented .The failure is assumed to be asymmetry petalling and
the analysis is performed by using the energy balance and work done
.The work done consist of the work required for plastic deformation
Wp, the work for transferring the matter to new position Wd and the
work for bending of the petals Wb. In several studies, it has been
shown that we can neglect the loss of energy by temperature.
In this present study, in first, by assuming the crater formation
after perforation, the value of work done is calculated during the
normal penetration of conical projectiles into thin metallic targets.
Then the value of residual velocity and ballistic limit of the projectile
is predicated by using the energy balance. In final, theoretical and
experimental results is compared.
Abstract: In this paper, a simple heuristic genetic algorithm is
used for Multistage Multiuser detection in fast fading environments.
Multipath channels, multiple access interference (MAI) and near far
effect cause the performance of the conventional detector to degrade.
Heuristic Genetic algorithms, a rapidly growing area of artificial
intelligence, uses evolutionary programming for initial search, which
not only helps to converge the solution towards near optimal
performance efficiently but also at a very low complexity as
compared with optimal detector. This holds true for Additive White
Gaussian Noise (AWGN) and multipath fading channels.
Experimental results are presented to show the superior performance
of the proposed techque over the existing methods.
Abstract: Complex assemblies of interacting proteins carry out
most of the interesting jobs in a cell, such as metabolism, DNA
synthesis, mitosis and cell division. These physiological properties
play out as a subtle molecular dance, choreographed by underlying
regulatory networks that control the activities of cyclin-dependent
kinases (CDK). The network can be modeled by a set of nonlinear
differential equations and its behavior predicted by numerical
simulation. In this paper, an innovative approach has been proposed
that uses genetic algorithms to mine a set of behavior data output by
a biological system in order to determine the kinetic parameters of
the system. In our approach, the machine learning method is
integrated with the framework of existent biological information in a
wiring diagram so that its findings are expressed in a form of system
dynamic behavior. By numerical simulations it has been illustrated
that the model is consistent with experiments and successfully shown
that such application of genetic algorithms will highly improve the
performance of mathematical model of the cell division cycle to
simulate such a complicated bio-system.
Abstract: Image clustering is a process of grouping images
based on their similarity. The image clustering usually uses the color
component, texture, edge, shape, or mixture of two components, etc.
This research aims to explore image clustering using color
composition. In order to complete this image clustering, three main
components should be considered, which are color space, image
representation (feature extraction), and clustering method itself. We
aim to explore which composition of these factors will produce the
best clustering results by combining various techniques from the
three components. The color spaces use RGB, HSV, and L*a*b*
method. The image representations use Histogram and Gaussian
Mixture Model (GMM), whereas the clustering methods use KMeans
and Agglomerative Hierarchical Clustering algorithm. The
results of the experiment show that GMM representation is better
combined with RGB and L*a*b* color space, whereas Histogram is
better combined with HSV. The experiments also show that K-Means
is better than Agglomerative Hierarchical for images clustering.
Abstract: Factor analysis was applied to two stages biogas
production from banana stem waste allowing a screening of the
experimental variables second stage temperature (T), organic loading
rates (OLR) and hydraulic retention times (HRT). Biogas production
was found to be strongly influenced by all the above experimental
variables. Results from factorial analysis have shown that all
variables which were HRT, OLR and T have significant effect to
biogas production. Increased in HRT and OLR could increased the
biogas yield. The performance was tested under the conditions of
various T (35oC-60oC), OLR (0.3 g TS/l.d–1.9 gTS/l.d), and HRT (3
d–15 d). Conditions for temperature, OLR and HRT in this study
were based on the best range obtained from literature review.
Abstract: Selecting the routes and the assignment of link flow in a computer communication networks are extremely complex combinatorial optimization problems. Metaheuristics, such as genetic or simulated annealing algorithms, are widely applicable heuristic optimization strategies that have shown encouraging results for a large number of difficult combinatorial optimization problems. This paper considers the route selection and hence the flow assignment problem. A genetic algorithm and simulated annealing algorithm are used to solve this problem. A new hybrid algorithm combining the genetic with the simulated annealing algorithm is introduced. A modification of the genetic algorithm is also introduced. Computational experiments with sample networks are reported. The results show that the proposed modified genetic algorithm is efficient in finding good solutions of the flow assignment problem compared with other techniques.
Abstract: Real world Speaker Identification (SI) application
differs from ideal or laboratory conditions causing perturbations that
leads to a mismatch between the training and testing environment
and degrade the performance drastically. Many strategies have been
adopted to cope with acoustical degradation; wavelet based Bayesian
marginal model is one of them. But Bayesian marginal models
cannot model the inter-scale statistical dependencies of different
wavelet scales. Simple nonlinear estimators for wavelet based
denoising assume that the wavelet coefficients in different scales are
independent in nature. However wavelet coefficients have significant
inter-scale dependency. This paper enhances this inter-scale
dependency property by a Circularly Symmetric Probability Density
Function (CS-PDF) related to the family of Spherically Invariant
Random Processes (SIRPs) in Log Gabor Wavelet (LGW) domain
and corresponding joint shrinkage estimator is derived by Maximum
a Posteriori (MAP) estimator. A framework is proposed based on
these to denoise speech signal for automatic speaker identification
problems. The robustness of the proposed framework is tested for
Text Independent Speaker Identification application on 100 speakers
of POLYCOST and 100 speakers of YOHO speech database in three
different noise environments. Experimental results show that the
proposed estimator yields a higher improvement in identification
accuracy compared to other estimators on popular Gaussian Mixture
Model (GMM) based speaker model and Mel-Frequency Cepstral
Coefficient (MFCC) features.
Abstract: A new, combinatorial model for analyzing and inter-
preting an electrocardiogram (ECG) is presented. An application of
the model is QRS peak detection. This is demonstrated with an
online algorithm, which is shown to be space as well as time efficient.
Experimental results on the MIT-BIH Arrhythmia database show that
this novel approach is promising. Further uses for this approach are
discussed, such as taking advantage of its small memory requirements
and interpreting large amounts of pre-recorded ECG data.
Abstract: The Spalart and Allmaras turbulence model has been
implemented in a numerical code to study the compressible turbulent
flows, which the system of governing equations is solved with a
finite volume approach using a structured grid. The AUSM+ scheme
is used to calculate the inviscid fluxes. Different benchmark
problems have been computed to validate the implementation and
numerical results are shown. A special Attention is paid to wall jet
applications. In this study, the jet is submitted to various wall
boundary conditions (adiabatic or uniform heat flux) in forced
convection regime and both two-dimensional and axisymmetric wall
jets are considered. The comparison between the numerical results
and experimental data has given the validity of this turbulence model
to study the turbulent wall jets especially in engineering applications.
Abstract: In this paper, a novel corner detection method is
presented to stably extract geometrically important corners.
Intensity-based corner detectors such as the Harris corner can detect
corners in noisy environments but has inaccurate corner position and
misses the corners of obtuse angles. Edge-based corner detectors such
as Curvature Scale Space can detect structural corners but show
unstable corner detection due to incomplete edge detection in noisy
environments. The proposed image-based direct curvature estimation
can overcome limitations in both inaccurate structural corner detection
of the Harris corner detector (intensity-based) and the unstable corner
detection of Curvature Scale Space caused by incomplete edge
detection. Various experimental results validate the robustness of the
proposed method.
Abstract: The effects of commercial or bovine yeasts on the
performance and blood variables of broiler chickens intoxicated with
aflatoxin were investigated in broilers. Four hundred eighty broilers
(Arbor Acres; 3-wk-old) were randomly assigned to 4 groups. Each
group (120 broiler chickens) was further randomly divided into 6
replicates of 20 chickens. The treatments were control diet without
additives (treatment 1), 250 ppb AFB1 (treatment 2), commercial
yeast, Saccharomyces cerevisiae, (CY 2.5 x 107 CFU/g) + 250 ppb
AFB1 (treatment 3) and bovine yeast, Saccharomyces cerevisiae,
(BY 2.5 x 107 CFU/g + 250 ppb AFB1 (treatment 4). Complete
randomized design (CRD) was used in the experiment. Feed
consumption and body weight were recorded at every five-day
period. On day 42, carcass compositions were determined from 30
birds per treatment. While chicks were sacrificed, 3-4 ml blood
sample was taken and stored frozen at (-20°C) for serum chemical
analysis to determine effects of consumption of diets on blood
chemistry (total protein, albumin, glucose, urea, cholesterol and
triglycerides). There were no significant differences in ADFI among
the treatments(P>0.05). However, BWG, FCR and mortality were
highly significantly different (P
Abstract: The experiment was performed to study the
relationship between excreta viscosity and Nitrogen-corrected true
metabolisable energy quantities of soybean meals using conventional
addition method (CAM) in adult cockerels for 7 d: a 3-d preexperiment
and a 4-d experiment period. Results indicated that
differences between the excreta viscosity values were (P
Abstract: As the fossil fuels kept on depleting, intense research in developing hydrogen (H2) as the alternative fuel has been done to cater our tremendous demand for fuel. The potential of H2 as the ultimate clean fuel differs with the fossil fuel that releases significant amounts of carbon dioxide (CO2) into the surrounding and leads to the global warming. The experimental work was carried out to study the production of H2 from palm kernel shell steam gasification at different variables such as heating rate, steam to biomass ratio and adsorbent to biomass ratio. Maximum H2 composition which is 61% (volume basis) was obtained at heating rate of 100oCmin-1, steam/biomass of 2:1 ratio, and adsorbent/biomass of 1:1 ratio. The commercial adsorbent had been modified by utilizing the alcoholwater mixture. Characteristics of both adsorbents were investigated and it is concluded that flowability and floodability of modified CaO is significantly improved.
Abstract: In this paper we propose a novel approach for ascertaining human identity based on fusion of profile face and gait biometric cues The identification approach based on feature learning in PCA-LDA subspace, and classification using multivariate Bayesian classifiers allows significant improvement in recognition accuracy for low resolution surveillance video scenarios. The experimental evaluation of the proposed identification scheme on a publicly available database [2] showed that the fusion of face and gait cues in joint PCA-LDA space turns out to be a powerful method for capturing the inherent multimodality in walking gait patterns, and at the same time discriminating the person identity..