Abstract: An alternative approach to the use of Discrete Fourier
Transform (DFT) for Magnetic Resonance Imaging (MRI) reconstruction
is the use of parametric modeling technique. This method
is suitable for problems in which the image can be modeled by
explicit known source functions with a few adjustable parameters.
Despite the success reported in the use of modeling technique as an
alternative MRI reconstruction technique, two important problems
constitutes challenges to the applicability of this method, these are
estimation of Model order and model coefficient determination. In
this paper, five of the suggested method of evaluating the model
order have been evaluated, these are: The Final Prediction Error
(FPE), Akaike Information Criterion (AIC), Residual Variance (RV),
Minimum Description Length (MDL) and Hannan and Quinn (HNQ)
criterion. These criteria were evaluated on MRI data sets based on the
method of Transient Error Reconstruction Algorithm (TERA). The
result for each criterion is compared to result obtained by the use of a
fixed order technique and three measures of similarity were evaluated.
Result obtained shows that the use of MDL gives the highest measure
of similarity to that use by a fixed order technique.
Abstract: Methods for organizing web data into groups in order
to analyze web-based hypertext data and facilitate data availability
are very important in terms of the number of documents available
online. Thereby, the task of clustering web-based document structures
has many applications, e.g., improving information retrieval on the
web, better understanding of user navigation behavior, improving web
users requests servicing, and increasing web information accessibility.
In this paper we investigate a new approach for clustering web-based
hypertexts on the basis of their graph structures. The hypertexts will
be represented as so called generalized trees which are more general
than usual directed rooted trees, e.g., DOM-Trees. As a important
preprocessing step we measure the structural similarity between the
generalized trees on the basis of a similarity measure d. Then,
we apply agglomerative clustering to the obtained similarity matrix
in order to create clusters of hypertext graph patterns representing
navigation structures. In the present paper we will run our approach
on a data set of hypertext structures and obtain good results in
Web Structure Mining. Furthermore we outline the application of
our approach in Web Usage Mining as future work.
Abstract: Cluster analysis divides data into groups that are
meaningful, useful, or both. Analysis of biological data is creating a
new generation of epidemiologic, prognostic, diagnostic and
treatment modalities. Clustering of protein sequences is one of the
current research topics in the field of computer science. Linear
relation is valuable in rule discovery for a given data, such as if value
X goes up 1, value Y will go down 3", etc. The classical linear
regression models the linear relation of two sequences perfectly.
However, if we need to cluster a large repository of protein sequences
into groups where sequences have strong linear relationship with
each other, it is prohibitively expensive to compare sequences one by
one. In this paper, we propose a new technique named General
Regression Model Technique Clustering Algorithm (GRMTCA) to
benignly handle the problem of linear sequences clustering. GRMT
gives a measure, GR*, to tell the degree of linearity of multiple
sequences without having to compare each pair of them.
Abstract: This paper examines the forced convection flow of
incompressible, electrically conducting viscous fluid past a sharp
wedge in the presence of heat generation or absorption with an
applied magnetic field. The system of partial differential equations
governing Falkner - Skan wedge flow and heat transfer is first
transformed into a system of ordinary differential equations using
similarity transformations which is later solved using an implicit
finite - difference scheme, along with quasilinearization technique.
Numerical computations are performed for air (Pr = 0.7) and
displayed graphically to illustrate the influence of pertinent physical
parameters on local skin friction and heat transfer coefficients and,
also on, velocity and temperature fields. It is observed that the
magnetic field increases both the coefficients of skin friction and heat
transfer. The effect of heat generation or absorption is found to be
very significant on heat transfer, but its effect on the skin friction is
negligible. Indeed, the occurrence of overshoot is noticed in the
temperature profiles during heat generation process, causing the
reversal in the direction of heat transfer.
Abstract: Supplier selection, in real situation, is affected by
several qualitative and quantitative factors and is one of the most
important activities of purchasing department. Since at the time of
evaluating suppliers against the criteria or factors, decision makers
(DMS) do not have precise, exact and complete information, supplier
selection becomes more difficult. In this case, Grey theory helps us
to deal with this problem of uncertainty. Here, we apply Technique
for Order Preference by Similarity to Ideal Solution (TOPSIS)
method to evaluate and select the best supplier by using interval
fuzzy numbers. Through this article, we compare TOPSIS with some
other approaches and afterward demonstrate that the concept of
TOPSIS is very important for ranking and selecting right supplier.
Abstract: Acute disseminated encephalomyelitis (ADEM) has
been reported to develop after a hymenoptera sting, but its
pathogenesis is not known in detail. Myelin basic protein (MBP)-
specific T cells have been detected in the blood of patients with
ADEM, and a proportion of these patients develop multiple sclerosis
(MS). In an attempt to understand the mechanisms underlying
ADEM, molecular mimicry between hymenoptera venom peptides
and the human immunodominant MBP peptide was scrutinized,
based on the sequence and structural similarities, whether it was the
root of the disease. The results suggest that the three wasp venom
peptides have low sequence homology with the human
immunodominant MBP residues 85-99. Structural similarity analysis
among the three venom peptides and the MS-related HLA-DR2b
(DRA, DRB1*1501)-associated immunodominant MHC
binding/TCR contact residues 88-93, VVHFFK showed that
hyaluronidase residues 7-12, phospholipase A1 residues 98-103, and
antigen 5 residues 109-114 showed a high degree of similarity
83.3%, 100%, and 83.3% respectively. In conclusion, some wasp
venom peptides, particularly phospholipase A1, may potentially act
as the molecular motifs of the human 3HLA-DR2b-associated
immunodominant MBP88-93, and possibly present a mechanism for
induction of wasp sting-associated ADEM.
Abstract: In this paper we study different similarity based approaches for the development of QSAR model devoted to the prediction of activity of antiobesity drugs. Classical similarity approaches are compared regarding to dissimilarity models based on the consideration of the calculation of Euclidean distances between the nonisomorphic fragments extracted in the matching process. Combining the classical similarity and dissimilarity approaches into a new similarity measure, the Approximate Similarity was also studied, and better results were obtained. The application of the proposed method to the development of quantitative structure-activity relationships (QSAR) has provided reliable tools for predicting of inhibitory activity of drugs. Acceptable results were obtained for the models presented here.
Abstract: In the field of concepts, the measure of Wu and Palmer [1] has the advantage of being simple to implement and have good performances compared to the other similarity measures [2]. Nevertheless, the Wu and Palmer measure present the following disadvantage: in some situations, the similarity of two elements of an IS-A ontology contained in the neighborhood exceeds the similarity value of two elements contained in the same hierarchy. This situation is inadequate within the information retrieval framework. To overcome this problem, we propose a new similarity measure based on the Wu and Palmer measure. Our objective is to obtain realistic results for concepts not located in the same way. The obtained results show that compared to the Wu and Palmer approach, our measure presents a profit in terms of relevance and execution time.
Abstract: The goal of this paper is to segment the countries
based on the value of export from Iran during 14 years ending at 2005. To measure the dissimilarity among export baskets of different countries, we define Dissimilarity Export Basket (DEB) function and
use this distance function in K-means algorithm. The DEB function
is defined based on the concepts of the association rules and the
value of export group-commodities. In this paper, clustering quality
function and clusters intraclass inertia are defined to, respectively,
calculate the optimum number of clusters and to compare the
functionality of DEB versus Euclidean distance. We have also study
the effects of importance weight in DEB function to improve
clustering quality. Lastly when segmentation is completed, a
designated RFM model is used to analyze the relative profitability of
each cluster.
Abstract: Due to availability of powerful image processing software
and improvement of human computer knowledge, it becomes
easy to tamper images. Manipulation of digital images in different
fields like court of law and medical imaging create a serious problem
nowadays. Copy-move forgery is one of the most common types
of forgery which copies some part of the image and pastes it to
another part of the same image to cover an important scene. In
this paper, a copy-move forgery detection method proposed based
on Fourier transform to detect forgeries. Firstly, image is divided to
same size blocks and Fourier transform is performed on each block.
Similarity in the Fourier transform between different blocks provides
an indication of the copy-move operation. The experimental results
prove that the proposed method works on reasonable time and works
well for gray scale and colour images. Computational complexity
reduced by using Fourier transform in this method.
Abstract: Flexible macroblock ordering (FMO), adopted in the
H.264 standard, allows to partition all macroblocks (MBs) in a frame
into separate groups of MBs called Slice Groups (SGs). FMO can not
only support error-resilience, but also control the size of video packets
for different network types. However, it is well-known that the number
of bits required for encoding the frame is increased by adopting FMO.
In this paper, we propose a novel algorithm that can reduce the bitrate
overhead caused by utilizing FMO. In the proposed algorithm, all MBs
are grouped in SGs based on the similarity of the transform
coefficients. Experimental results show that our algorithm can reduce
the bitrate as compared with conventional FMO.
Abstract: In this paper we present a modification to existed model of threshold for shot cut detection, which is able to adapt itself to the sequence statistics and operate in real time, because it use for calculation only previously evaluated frames. The efficiency of proposed modified adaptive threshold scheme was verified through extensive test experiment with several similarity metrics and achieved results were compared to the results reached by the original model. According to results proposed threshold scheme reached higher accuracy than existed original model.
Abstract: The boundary layer flow and heat transfer on a
stretched surface moving with prescribed skin friction is studied for
permeable surface. The surface temperature is assumed to vary
inversely with the vertical direction x for n = -1. The skin friction at
the surface scales as (x-1/2) at m = 0. The constants m and n are the
indices of the power law velocity and temperature exponent
respectively. Similarity solutions are obtained for the boundary layer
equations subject to power law temperature and velocity variation.
The effect of various governing parameters, such as the buoyancy
parameter λ and the suction/injection parameter fw for air (Pr = 0.72)
are studied. The choice of n and m ensures that the used similarity
solutions are x independent. The results show that, assisting flow (λ >
0) enhancing the heat transfer coefficient along the surface for any
constant value of fw. Furthermore, injection increases the heat
transfer coefficient but suction reduces it at constant λ.
Abstract: Real-time hand tracking is a challenging task in many
computer vision applications such as gesture recognition. This paper
proposes a robust method for hand tracking in a complex environment
using Mean-shift analysis and Kalman filter in conjunction with 3D
depth map. The depth information solve the overlapping problem
between hands and face, which is obtained by passive stereo measuring
based on cross correlation and the known calibration data of
the cameras. Mean-shift analysis uses the gradient of Bhattacharyya
coefficient as a similarity function to derive the candidate of the hand
that is most similar to a given hand target model. And then, Kalman
filter is used to estimate the position of the hand target. The results
of hand tracking, tested on various video sequences, are robust to
changes in shape as well as partial occlusion.
Abstract: Many states are now committed to implementing
international human rights standards domestically. In terms of
practical governance, how might effectiveness be measured? A facevalue
answer can be found in domestic laws and institutions relating
to human rights. However, this article provides two further tools to
help states assess their status on the spectrum of robust to fragile
human rights governance. The first recognises that each state has its
own 'human rights history' and the ideal end stage is robust human
rights governance, and the second is developing criteria to assess
robustness. Although a New Zealand case study is used to illustrate
these tools, the widespread adoption of human rights standards by
many states inevitably means that the issues are relevant to other
countries. This is even though there will always be varying degrees of
similarity-difference in constitutional background and developed or
emerging human rights systems.
Abstract: Gaussian mixture background model is widely used in
moving target detection of the image sequences. However, traditional
Gaussian mixture background model usually considers the time
continuity of the pixels, and establishes background through statistical
distribution of pixels without taking into account the pixels- spatial
similarity, which will cause noise, imperfection and other problems.
This paper proposes a new Gaussian mixture modeling approach,
which combines the color and gradient of the spatial information, and
integrates the spatial information of the pixel sequences to establish
Gaussian mixture background. The experimental results show that the
movement background can be extracted accurately and efficiently, and
the algorithm is more robust, and can work in real time in tracking
applications.
Abstract: In this paper, estimation of the linear regression
model is made by ordinary least squares method and the
partially linear regression model is estimated by penalized
least squares method using smoothing spline. Then, it is
investigated that differences and similarity in the sum of
squares related for linear regression and partial linear
regression models (semi-parametric regression models). It is
denoted that the sum of squares in linear regression is reduced
to sum of squares in partial linear regression models.
Furthermore, we indicated that various sums of squares in the
linear regression are similar to different deviance statements in
partial linear regression. In addition to, coefficient of the
determination derived in linear regression model is easily
generalized to coefficient of the determination of the partial
linear regression model. For this aim, it is made two different
applications. A simulated and a real data set are considered to
prove the claim mentioned here. In this way, this study is
supported with a simulation and a real data example.
Abstract: This paper proposes new hybrid approaches for face
recognition. Gabor wavelets representation of face images is an
effective approach for both facial action recognition and face
identification. Perform dimensionality reduction and linear
discriminate analysis on the down sampled Gabor wavelet faces can
increase the discriminate ability. Nearest feature space is extended to
various similarity measures. In our experiments, proposed Gabor
wavelet faces combined with extended neural net feature space
classifier shows very good performance, which can achieve 93 %
maximum correct recognition rate on ORL data set without any preprocessing
step.
Abstract: In order to accelerate the similarity search in highdimensional database, we propose a new hierarchical indexing method. It is composed of offline and online phases. Our contribution concerns both phases. In the offline phase, after gathering the whole of the data in clusters and constructing a hierarchical index, the main originality of our contribution consists to develop a method to construct bounding forms of clusters to avoid overlapping. For the online phase, our idea improves considerably performances of similarity search. However, for this second phase, we have also developed an adapted search algorithm. Our method baptized NOHIS (Non-Overlapping Hierarchical Index Structure) use the Principal Direction Divisive Partitioning (PDDP) as algorithm of clustering. The principle of the PDDP is to divide data recursively into two sub-clusters; division is done by using the hyper-plane orthogonal to the principal direction derived from the covariance matrix and passing through the centroid of the cluster to divide. Data of each two sub-clusters obtained are including by a minimum bounding rectangle (MBR). The two MBRs are directed according to the principal direction. Consequently, the nonoverlapping between the two forms is assured. Experiments use databases containing image descriptors. Results show that the proposed method outperforms sequential scan and SRtree in processing k-nearest neighbors.
Abstract: In this paper we propose segmentation approach based
on Vector Quantization technique. Here we have used Kekre-s fast
codebook generation algorithm for segmenting low-altitude aerial
image. This is used as a preprocessing step to form segmented
homogeneous regions. Further to merge adjacent regions color
similarity and volume difference criteria is used. Experiments
performed with real aerial images of varied nature demonstrate that
this approach does not result in over segmentation or under
segmentation. The vector quantization seems to give far better results
as compared to conventional on-the-fly watershed algorithm.