Abstract: Scripts are one of the basic text resources to understand
broadcasting contents. Topic modeling is the method to get the
summary of the broadcasting contents from its scripts. Generally,
scripts represent contents descriptively with directions and speeches,
and provide scene segments that can be seen as semantic units.
Therefore, a script can be topic modeled by treating a scene segment
as a document. Because scene segments consist of speeches mainly,
however, relatively small co-occurrences among words in the scene
segments are observed. This causes inevitably the bad quality of
topics by statistical learning method. To tackle this problem, we
propose a method to improve topic quality with additional word
co-occurrence information obtained using scene similarities. The
main idea of improving topic quality is that the information that
two or more texts are topically related can be useful to learn high
quality of topics. In addition, more accurate topical representations
lead to get information more accurate whether two texts are related
or not. In this paper, we regard two scene segments are related
if their topical similarity is high enough. We also consider that
words are co-occurred if they are in topically related scene segments
together. By iteratively inferring topics and determining semantically
neighborhood scene segments, we draw a topic space represents
broadcasting contents well. In the experiments, we showed the
proposed method generates a higher quality of topics from Korean
drama scripts than the baselines.
Abstract: River Hindon is an important river catering the
demand of highly populated rural and industrial cluster of western
Uttar Pradesh, India. Water quality of river Hindon is deteriorating at
an alarming rate due to various industrial, municipal and agricultural
activities. The present study aimed at identifying the pollution
sources and quantifying the degree to which these sources are
responsible for the deteriorating water quality of the river. Various
water quality parameters, like pH, temperature, electrical
conductivity, total dissolved solids, total hardness, calcium, chloride,
nitrate, sulphate, biological oxygen demand, chemical oxygen
demand, and total alkalinity were assessed. Water quality data
obtained from eight study sites for one year has been subjected to the
two multivariate techniques, namely, principal component analysis
and cluster analysis. Principal component analysis was applied with
the aim to find out spatial variability and to identify the sources
responsible for the water quality of the river. Three Varifactors were
obtained after varimax rotation of initial principal components using
principal component analysis. Cluster analysis was carried out to
classify sampling stations of certain similarity, which grouped eight
different sites into two clusters. The study reveals that the
anthropogenic influence (municipal, industrial, waste water and
agricultural runoff) was the major source of river water pollution.
Thus, this study illustrates the utility of multivariate statistical
techniques for analysis and elucidation of multifaceted data sets,
recognition of pollution sources/factors and understanding
temporal/spatial variations in water quality for effective river water
quality management.
Abstract: Selling has changed. Selling has taken on aspects of
relationship marketing and sales force play a critical role in
developing long-term relationships between buyers and sellers which
is seen to serve the company’s targets and create success for a long
run. The purpose of this study was to examine what really matters in
buyer-seller encounters and determine what expectations business
buyers have. We studied 17 business buyers by a qualitative
interview. We found that buyers appreciate encounters where the
salesperson face the buyer as a way he or she is as a person, map the
real needs to improve buyers’ business and build up cooperation for
long-term relationship. This study show that personality matters are a
key elements when satisfying business buyers’ expectations.
Abstract: Liver segmentation from medical images poses more
challenges than analogous segmentations of other organs. This
contribution introduces a liver segmentation method from a series of
computer tomography images. Overall, we present a novel method for
segmenting liver by coupling density matching with shape priors.
Density matching signifies a tracking method which operates via
maximizing the Bhattacharyya similarity measure between the
photometric distribution from an estimated image region and a model
photometric distribution. Density matching controls the direction of
the evolution process and slows down the evolving contour in regions
with weak edges. The shape prior improves the robustness of density
matching and discourages the evolving contour from exceeding liver’s
boundaries at regions with weak boundaries. The model is
implemented using a modified distance regularized level set (DRLS)
model. The experimental results show that the method achieves a
satisfactory result. By comparing with the original DRLS model, it is
evident that the proposed model herein is more effective in addressing
the over segmentation problem. Finally, we gauge our performance of
our model against matrices comprising of accuracy, sensitivity, and
specificity.
Abstract: This article proposes a hybrid algorithm for spectrum
allocation in cognitive radio networks based on the algorithms
Analytical Hierarchical Process (AHP) and Technique for Order of
Preference by Similarity to Ideal Solution (TOPSIS) to improve the
performance of the spectrum mobility of secondary users in cognitive
radio networks. To calculate the level of performance of the proposed algorithm a
comparative analysis between the proposed AHP-TOPSIS, Grey
Relational Analysis (GRA) and Multiplicative Exponent Weighting
(MEW) algorithm is performed. Four evaluation metrics are used.
These metrics are accumulative average of failed handoffs,
accumulative average of handoffs performed, accumulative average
of transmission bandwidth, and accumulative average of the
transmission delay. The results of the comparison show that AHP-TOPSIS Algorithm
provides 2.4 times better performance compared to a GRA Algorithm
and, 1.5 times better than the MEW Algorithm.
Abstract: Obturator Foramen is a specific structure in Pelvic
bone images and recognition of it is a new concept in medical image
processing. Moreover, segmentation of bone structures such as
Obturator Foramen plays an essential role for clinical research in
orthopedics. In this paper, we present a novel method to analyze the
similarity between the substructures of the imaged region and a hand
drawn template as a preprocessing step for computation of Pelvic
bone rotation on hip radiographs. This method consists of integrated
usage of Marker-controlled Watershed segmentation and Zernike
moment feature descriptor and it is used to detect Obturator Foramen
accurately. Marker-controlled Watershed segmentation is applied to
separate Obturator Foramen from the background effectively. Then,
Zernike moment feature descriptor is used to provide matching
between binary template image and the segmented binary image for
final extraction of Obturator Foramens. Finally, Pelvic bone rotation
rate calculation for each hip radiograph is performed automatically to
select and eliminate hip radiographs for further studies which depend
on Pelvic bone angle measurements. The proposed method is tested
on randomly selected 100 hip radiographs. The experimental results
demonstrated that the proposed method is able to segment Obturator
Foramen with 96% accuracy.
Abstract: This study focuses on the hydro-geology and chemical
constituents analysis of Ikogosi Warm Spring waters in South West
Nigeria. Ikogosi warm spring is a global tourist attraction because it
has both warm and cold spring sources. Water samples from the cold
spring, warm spring and the meeting point were collected, analyzed
and the result shows close similarity in temperature, hydrogen iron
concentration (pH), alkalinity, hardness, Calcium, Magnesium,
Sodium, Iron, total dissolved solid and heavy metals. The measured
parameters in the water samples are within World Health
Organisation standards for fresh water. The study of the geology of
the warm spring reveals that the study area is underlain by a group of
slightly migmatised to non-migmatised paraschists and meta-igneous
rocks. Also, concentration levels of selected heavy metals, (Copper,
Cadmium, Zinc, Arsenic and Cromium) were determined in the water
(ppm) samples. Chromium had the highest concentration value of
1.52ppm (an average of 49.67%) and Cadmium had the lowest
concentration with value of 0.15ppm (an average of 4.89%).
Comparison of these results showed that, their mean levels are within
the standard values obtained in Nigeria. It can be concluded that both
warm and spring water are safe for drinking.
Abstract: One of the most important challenging factors in
medical images is nominated as noise. Image denoising refers to the
improvement of a digital medical image that has been infected by
Additive White Gaussian Noise (AWGN). The digital medical image
or video can be affected by different types of noises. They are
impulse noise, Poisson noise and AWGN. Computed tomography
(CT) images are subjects to low quality due to the noise. Quality of
CT images is dependent on absorbed dose to patients directly in such
a way that increase in absorbed radiation, consequently absorbed
dose to patients (ADP), enhances the CT images quality. In this
manner, noise reduction techniques on purpose of images quality
enhancement exposing no excess radiation to patients is one the
challenging problems for CT images processing. In this work, noise
reduction in CT images was performed using two different
directional 2 dimensional (2D) transformations; i.e., Curvelet and
Contourlet and Discrete Wavelet Transform (DWT) thresholding
methods of BayesShrink and AdaptShrink, compared to each other
and we proposed a new threshold in wavelet domain for not only
noise reduction but also edge retaining, consequently the proposed
method retains the modified coefficients significantly that result good
visual quality. Data evaluations were accomplished by using two
criterions; namely, peak signal to noise ratio (PSNR) and Structure
similarity (Ssim).
Abstract: This survey paper shows the recent state of model
comparison as it’s applies to Model Driven engineering. In Model
Driven Engineering to calculate the difference between the models is
a very important and challenging task. There are number of tasks
involved in model differencing that firstly starts with identifying and
matching the elements of the model. In this paper, we discuss how
model matching is accomplished, the strategies, techniques and the
types of the model. We also discuss the future direction. We found
out that many of the latest model comparison strategies are geared
near enabling Meta model and similarity based matching. Therefore
model versioning is the most dominant application of the model
comparison. Recently to work on comparison for versioning has
begun to deteriorate, giving way to different applications. Ultimately
there is wide change among the tools in the measure of client exertion
needed to perform model comparisons, as some require more push to
encourage more sweeping statement and expressive force.
Abstract: DNA Barcode provides good sources of needed
information to classify living species. The classification problem has
to be supported with reliable methods and algorithms. To analyze
species regions or entire genomes, it becomes necessary to use the
similarity sequence methods. A large set of sequences can be
simultaneously compared using Multiple Sequence Alignment which
is known to be NP-complete. However, all the used methods are still
computationally very expensive and require significant computational
infrastructure. Our goal is to build predictive models that are highly
accurate and interpretable. In fact, our method permits to avoid the
complex problem of form and structure in different classes of
organisms. The empirical data and their classification performances
are compared with other methods. Evenly, in this study, we present
our system which is consisted of three phases. The first one, is called
transformation, is composed of three sub steps; Electron-Ion
Interaction Pseudopotential (EIIP) for the codification of DNA
Barcodes, Fourier Transform and Power Spectrum Signal Processing.
Moreover, the second phase step is an approximation; it is
empowered by the use of Multi Library Wavelet Neural Networks
(MLWNN). Finally, the third one, is called the classification of DNA
Barcodes, is realized by applying the algorithm of hierarchical
classification.
Abstract: In this study, one dimensional phase change problem
(a Stefan problem) is considered and a numerical solution of this
problem is discussed. First, we use similarity transformation to
convert the governing equations into ordinary differential equations
with its boundary conditions. The solutions of ordinary differential
equation with the associated boundary conditions and interface
condition (Stefan condition) are obtained by using a numerical
approach based on operational matrix of differentiation of shifted
second kind Chebyshev wavelets. The obtained results are compared
with existing exact solution which is sufficiently accurate.
Abstract: In this paper, we propose a new method for threedimensional
object indexing based on D.A.M.C-S.H.C descriptor
(Direct and Analytical Method for Calculating the Spherical
Harmonics Coefficients). For this end, we propose a direct
calculation of the coefficients of spherical harmonics with perfect
precision. The aims of the method are to minimize, the processing
time on the 3D objects database and the searching time of similar
objects to a request object.
Firstly we start by defining the new descriptor using a new
division of 3-D object in a sphere. Then we define a new distance
which will be tested and prove his efficiency in the search for similar
objects in the database in which we have objects with very various
and important size.
Abstract: In this paper, we are interested in the problem of
finding similar images in a large database. For this purpose we
propose a new algorithm based on a combination of the 2-D
histogram intersection in the HSV space and statistical moments. The
proposed histogram is based on a 3x3 window and not only on the
intensity of the pixel. This approach overcome the drawback of the
conventional 1-D histogram which is ignoring the spatial distribution
of pixels in the image, while the statistical moments are used to
escape the effects of the discretisation of the color space which is
intrinsic to the use of histograms. We compare the performance of
our new algorithm to various methods of the state of the art and we
show that it has several advantages. It is fast, consumes little memory
and requires no learning. To validate our results, we apply this
algorithm to search for similar images in different image databases.
Abstract: The present study was aimed to examine the structure
of children’s adaptation during school transition and to identify a
commonality and dissimilarity at the elementary and junior high
school. 1,983 students in the 6th grade and 2,051 students in the 7th
grade were extracted by stratified two-stage random sampling and
completed the ASSESS that evaluated the school adaptation from the
view point of ‘general satisfaction’, ‘teachers’ support’, ‘friends’
support’, ‘anti-bullying relationship’, ‘prosocial skills’, and ‘academic
adaptation’. The 7th graders tend to be worse adaptation than the 6th
graders. A structural equation modeling showed the goodness of fit for
each grades. Both models were very similar but the 7th graders’ model
showed a lower coefficient at the pass from ‘teachers’ support’ to
‘friends’ support’. The role of ‘teachers’ support’ was decreased to
keep a good relation in junior high school. We also discussed how we
provide a continuous assistance for prevention of the 7th graders’ gap.
Abstract: Methicillin/multiple-resistant Staphylococcus aureus
(MRSA) are infectious bacteria that are resistant to common
antibiotics. A previous in silico study in our group has identified a
hypothetical protein SAV1226 as one of the potential drug targets. In
this study, we reported the bioinformatics characterization, as well as
cloning, expression, purification and kinetic assays of hypothetical
protein SAV1226 from methicillin/vancomycin-resistant
Staphylococcus aureus Mu50 strain. MALDI-TOF/MS analysis
revealed a low degree of structural similarity with known proteins.
Kinetic assays demonstrated that hypothetical protein SAV1226 is
neither a domain of an ATP dependent dihydroxyacetone kinase nor
of a phosphotransferase system (PTS) dihydroxyacetone kinase,
suggesting that the function of hypothetical protein SAV1226 might
be misannotated on public databases such as UniProt and
InterProScan 5.
Abstract: Image compression based on fractal coding is a lossy
compression method and normally used for gray level images range
and domain blocks in rectangular shape. Fractal based digital image
compression technique provide a large compression ratio and in this
paper, it is proposed using YUV colour space and the fractal theory
which is based on iterated transformation. Fractal geometry is mainly
applied in the current study towards colour image compression
coding. These colour images possesses correlations among the colour
components and hence high compression ratio can be achieved by
exploiting all these redundancies. The proposed method utilises the
self-similarity in the colour image as well as the cross-correlations
between them. Experimental results show that the greater
compression ratio can be achieved with large domain blocks but more
trade off in image quality is good to acceptable at less than 1 bit per
pixel.
Abstract: A total of 115 yeast strains isolated from local cassava
processing wastes were measured for crude protein content. Among
these strains, the strain MSY-2 possessed the highest protein
concentration (>3.5 mg protein/mL). By using molecular
identification tools, it was identified to be a strain of Pichia
kudriavzevii based on similarity of D1/D2 domain of 26S rDNA
region. In this study, to optimize the protein production by MSY-2
strain, Response Surface Methodology (RSM) was applied. The
tested parameters were the carbon content, nitrogen content, and
incubation time. Here, the value of regression coefficient (R2) =
0.7194 could be explained by the model which is high to support the
significance of the model. Under the optimal condition, the protein
content was produced up to 3.77 g per L of the culture and MSY-2
strain contains 66.8 g protein per 100 g of cell dry weight. These
results revealed the plausibility of applying the novel strain of yeast
in single-cell protein production.
Abstract: A cold, thin film of liquid impinging on an isothermal
hot, horizontal surface has been investigated. An approximate
solution for the velocity and temperature distributions in the flow
along the horizontal surface is developed, which exploits the
hydrodynamic similarity solution for thin film flow. The approximate
solution may provide a valuable basis for assessing flow and heat
transfer in more complex settings.
Abstract: In this article, the antibiogram and heavy metal
resistance profile of the bacteria isolated from total 34 studied
animals (Pelophylax ridibundus = 12; Mauremys rivulata = 14;
Natrix natrix = 8) captured around the Biga Stream, are described.
There was no database information on antibiogram and heavy metal
resistance profile of bacteria from these area’s amphibians and
reptiles.
A total of 200 bacteria were successfully isolated from cloaca and
oral samples of the aquatic amphibians and reptiles as well as from
the water sample. According to Jaccard’s similarity index, the degree
of similarity in the bacterial flora was quite high among the
amphibian and reptile species under examination, whereas it was
different from the bacterial diversity in the water sample. The most
frequent isolates were A. hydrophila (31.5%), B. pseudomallei
(8.5%), and C. freundii (7%). The total numbers of bacteria obtained
were as follows: 45 in P. ridibundus, 45 in N. natrix 30 in M.
rivulata, and 80 in the water sample. The result showed that
cefmetazole was the most effective antibiotic to control the bacteria
isolated in this study and that approximately 93.33% of the bacterial
isolates were sensitive to this antibiotic. The multiple antibiotic
resistances (MAR) index indicated that P. ridibundus (0.95) > N.
natrix (0.89) > M. rivulata (0.39). Furthermore, all the tested heavy
metals (Pb+2, Cu+2, Cr+3, and Mn+2) inhibit the growth of the bacterial
isolates at different rates. Therefore, it indicated that the water source
of the animals was contaminated with both antibiotic residues and
heavy metals.
Abstract: In this paper, the problem of steady laminar boundary
layer flow and heat transfer over a permeable exponentially
stretching/shrinking sheet with generalized slip velocity is
considered. The similarity transformations are used to transform the
governing nonlinear partial differential equations to a system of
nonlinear ordinary differential equations. The transformed equations
are then solved numerically using the bvp4c function in MATLAB.
Dual solutions are found for a certain range of the suction and
stretching/shrinking parameters. The effects of the suction parameter,
stretching/shrinking parameter, velocity slip parameter, critical shear
rate and Prandtl number on the skin friction and heat transfer
coefficients as well as the velocity and temperature profiles are
presented and discussed.