Abstract: Detection of player identity is challenging task in sport video content analysis. In case of soccer video player number recognition is effective and precise solution. Jersey numbers can be considered as scene text and difficulties in localization and recognition appear due to variations in orientation, size, illumination, motion etc. This paper proposed new method for player number localization and recognition. By observing hue, saturation and value for 50 different jersey examples we noticed that most often combination of low and high saturated pixels is used to separate number and jersey region. Image segmentation method based on this observation is introduced. Then, novel method for player number localization based on internal contours is proposed. False number candidates are filtered using area and aspect ratio. Before OCR processing extracted numbers are enhanced using image smoothing and rotation normalization.
Abstract: In this paper we propose a method for recognition of
adult video based on support vector machine (SVM). Different kernel
features are proposed to classify adult videos. SVM has an advantage
that it is insensitive to the relative number of training example in
positive (adult video) and negative (non adult video) classes. This
advantage is illustrated by comparing performance between different
SVM kernels for the identification of adult video.
Abstract: In this paper, we propose a new modular approach called neuroglial consisting of two neural networks slow and fast which emulates a biological reality recently discovered. The implementation is based on complex multi-time scale systems; validation is performed on the model of the asynchronous machine. We applied the geometric approach based on the Gerschgorin circles for the decoupling of fast and slow variables, and the method of singular perturbations for the development of reductions models.
This new architecture allows for smaller networks with less complexity and better performance in terms of mean square error and convergence than the single network model.
Abstract: The design of chaos-based secure communication
via synchronized modified Chua-s systems is investigated in
this paper. A continuous control law is proposed to ensure
synchronization of the master and slave modified Chua-s
systems by using the variable structure control technique.
Particularly, the concept of extended systems is introduced
such that a continuous control input is obtained to avoid
chattering phenomenon. Then, it becomes possible to ensure
that the message signal embedded in the transmitter can be
recovered in the receiver.
Abstract: The Kansei engineering is a technology which
converts human feelings into quantitative terms and helps designers
develop new products that meet customers- expectation. Standard
Kansei engineering procedure involves finding relationships between
human feelings and design elements of which many researchers have
found forward and backward relationship through various soft
computing techniques. In this paper, we proposed the framework of
Kansei engineering linking relationship not only between human
feelings and design elements, but also the whole part of product, by
constructing association rules. In this experiment, we obtain input
from emotion score that subjects rate when they see the whole part of
the product by applying semantic differentials. Then, association
rules are constructed to discover the combination of design element
which affects the human feeling. The results of our experiment
suggest the pattern of relationship of design elements according to
human feelings which can be derived from the whole part of product.
Abstract: Diagnostic goal of transformers in service is to detect the winding or the core in fault. Transformers are valuable equipment which makes a major contribution to the supply security of a power system. Consequently, it is of great importance to minimize the frequency and duration of unwanted outages of power transformers. So, Frequency Response Analysis (FRA) is found to be a useful tool for reliable detection of incipient mechanical fault in a transformer, by finding winding or core defects. The authors propose as first part of this article, the coupled circuits method, because, it gives most possible exhaustive modelling of transformers. And as second part of this work, the application of FRA in low frequency in order to improve and simplify the response reading. This study can be useful as a base data for the other transformers of the same categories intended for distribution grid.
Abstract: Iodine radionuclides in accident releases under severe
accident conditions at NPP with VVER are the most radiationimportant
with a view to population dose generation at the beginning
of the accident. To decrease radiation consequences of severe
accidents the technical solutions for severe accidents management
have been proposed in MIR.1200 project, with consideration of the
measures for suppression of volatile iodine forms generation in the
containment. Behavior dynamics of different iodine forms in the
containment under severe accident conditions has been analyzed for
the purpose of these technical solutions justification.
Abstract: This paper proposes a Wavelength Division
Multiplexing (WDM) technology based Storage Area Network
(SAN) for all type of Disaster recovery operation. It considers
recovery when all paths failure in the network as well as the main
SAN site failure also the all backup sites failure by the effect of
natural disasters such as earthquakes, fires and floods, power outage,
and terrorist attacks, as initially SAN were designed to work within
distance limited environments[2]. Paper also presents a NEW PATH
algorithm when path failure occurs. The simulation result and
analysis is presented for the proposed architecture with performance
consideration.
Abstract: In this paper, the dam-reservoir interaction is
analyzed using a finite element approach. The fluid is assumed to be
incompressible, irrotational and inviscid. The assumed boundary
conditions are that the interface of the dam and reservoir is vertical
and the bottom of reservoir is rigid and horizontal. The governing
equation for these boundary conditions is implemented in the
developed finite element code considering the horizontal and vertical
earthquake components. The weighted residual standard Galerkin
finite element technique with 8-node elements is used to discretize
the equation that produces a symmetric matrix equation for the damreservoir
system. A new boundary condition is proposed for
truncating surface of unbounded fluid domain to show the energy
dissipation in the reservoir, through radiation in the infinite upstream
direction. The Sommerfeld-s and perfect damping boundary
conditions are also implemented for a truncated boundary to compare
with the proposed far end boundary. The results are compared with
an analytical solution to demonstrate the accuracy of the proposed
formulation and other truncated boundary conditions in modeling the
hydrodynamic response of an infinite reservoir.
Abstract: In this work the effects of uniaxial mechanical stress on a pixel readout circuit are theoretically analyzed. It is the effects of mechanical stress on the in-pixel transistors do not arise at the output, when a correlated double sampling circuit is used. However, mechanical stress effects on the photodiode will directly appear at the readout chain output. Therefore, compensation techniques are needed to overcome this situation. Moreover simulation technique of mechanical stress is proposed and diverse layout as well as design recommendations are put forward, in order to minimize stress related effects on the output of a circuit. he shown, that wever, Moreover, a out
Abstract: Outlier detection in streaming data is very challenging because streaming data cannot be scanned multiple times and also new concepts may keep evolving. Irrelevant attributes can be termed as noisy attributes and such attributes further magnify the challenge of working with data streams. In this paper, we propose an unsupervised outlier detection scheme for streaming data. This scheme is based on clustering as clustering is an unsupervised data mining task and it does not require labeled data, both density based and partitioning clustering are combined for outlier detection. In this scheme partitioning clustering is also used to assign weights to attributes depending upon their respective relevance and weights are adaptive. Weighted attributes are helpful to reduce or remove the effect of noisy attributes. Keeping in view the challenges of streaming data, the proposed scheme is incremental and adaptive to concept evolution. Experimental results on synthetic and real world data sets show that our proposed approach outperforms other existing approach (CORM) in terms of outlier detection rate, false alarm rate, and increasing percentages of outliers.
Abstract: The worldwide prevalence of H3N2 influenza virus
and its increasing resistance to the existing drugs necessitates for the
development of an improved/better targeting anti-influenza drug.
H3N2 influenza neuraminidase is one of the two membrane-bound
proteins belonging to group-2 neuraminidases. It acts as key player
involved in viral pathogenicity and hence, is an important target of
anti-influenza drugs. Oseltamivir is one of the potent drugs targeting
this neuraminidase. In the present work, we have taken subtype N2
neuraminidase as the receptor and probable analogs of oseltamivir as
drug molecules to study the protein-drug interaction in anticipation of
finding efficient modified candidate compound. Oseltamivir analogs
were made by modifying the functional groups using Marvin Sketch
software and were docked using Schrodinger-s Glide. Oseltamivir
analog 10 was detected to have significant energy value (16% less
compared to Oseltamivir) and could be the probable lead molecule. It
infers that some of the modified compounds can interact in a novel
manner with increased hydrogen bonding at the active site of
neuraminidase and it might be better than the original drug. Further
work can be carried out such as enzymatic inhibition studies;
synthesis and crystallizing the drug-target complex to analyze the
interactions biologically.
Abstract: Scarcity of resources for biodiversity conservation gives rise to the need of strategic investment with priorities given to the cost of conservation. While the literature provides abundant methodological options for biodiversity conservation; estimating true cost of conservation remains abstract and simplistic, without recognising dynamic nature of the cost. Some recent works demonstrate the prominence of economic theory to inform biodiversity decisions, particularly on the costs and benefits of biodiversity however, the integration of the concept of true cost into biodiversity actions and planning are very slow to come by, and specially on a farm level. Conservation planning studies often use area as a proxy for costs neglecting different land values as well as protected areas. These literature consider only heterogeneous benefits while land costs are considered homogenous. Analysis with the assumption of cost homogeneity results in biased estimation; since not only it doesn’t address the true total cost of biodiversity actions and plans, but also it fails to screen out lands that are more (or less) expensive and/or difficult (or more suitable) for biodiversity conservation purposes, hindering validity and comparability of the results. Economies of scope” is one of the other most neglected aspects in conservation literature. The concept of economies of scope introduces the existence of cost complementarities within a multiple output production system and it suggests a lower cost during the concurrent production of multiple outputs by a given farm. If there are, indeed, economies of scope then simplistic representation of costs will tend to overestimate the true cost of conservation leading to suboptimal outcomes. The aim of this paper, therefore, is to provide first road review of the various theoretical ways in which economies of scope are likely to occur of how they might occur in conservation. Consequently, the paper addresses gaps that have to be filled in future analysis.
Abstract: In this paper, we proposed the robust mobile object
detection method for light effect in the night street image block based
updating reference background model using block state analysis.
Experiment image is acquired sequence color video from steady
camera. When suddenly appeared artificial illumination, reference
background model update this information such as street light, sign
light. Generally natural illumination is change by temporal, but
artificial illumination is suddenly appearance. So in this paper for
exactly detect artificial illumination have 2 state process. First process
is compare difference between current image and reference
background by block based, it can know changed blocks. Second
process is difference between current image-s edge map and reference
background image-s edge map, it possible to estimate illumination at
any block. This information is possible to exactly detect object,
artificial illumination and it was generating reference background
more clearly. Block is classified by block-state analysis. Block-state
has a 4 state (i.e. transient, stationary, background, artificial
illumination). Fig. 1 is show characteristic of block-state respectively
[1]. Experimental results show that the presented approach works well
in the presence of illumination variance.
Abstract: Oil debris signal generated from the inductive oil
debris monitor (ODM) is useful information for machine condition
monitoring but is often spoiled by background noise. To improve the
reliability in machine condition monitoring, the high-fidelity signal
has to be recovered from the noisy raw data. Considering that the noise
components with large amplitude often have higher frequency than
that of the oil debris signal, the integral transform is proposed to
enhance the detectability of the oil debris signal. To cancel out the
baseline wander resulting from the integral transform, the empirical
mode decomposition (EMD) method is employed to identify the trend
components. An optimal reconstruction strategy including both
de-trending and de-noising is presented to detect the oil debris signal
with less distortion. The proposed approach is applied to detect the oil
debris signal in the raw data collected from an experimental setup. The
result demonstrates that this approach is able to detect the weak oil
debris signal with acceptable distortion from noisy raw data.
Abstract: Investigating language acquisition is one of the most
challenging problems in the area of studying language. Syllable
learning as a level of language acquisition has a considerable
significance since it plays an important role in language acquisition.
Because of impossibility of studying language acquisition directly
with children, especially in its developmental phases, computer
models will be useful in examining language acquisition. In this
paper a computer model of early language learning for syllable
learning is proposed. It is guided by a conceptual model of syllable
learning which is named Directions Into Velocities of Articulators
model (DIVA). The computer model uses simple associational and
reinforcement learning rules within neural network architecture
which are inspired by neuroscience. Our simulation results verify the
ability of the proposed computer model in producing phonemes
during babbling and early speech. Also, it provides a framework for
examining the neural basis of language learning and communication
disorders.
Abstract: In this study three commercial semiconductor devices
were characterized in the laboratory for computed tomography
dosimetry: one photodiode and two phototransistors. It was evaluated
four responses to the irradiation: dose linearity, energy dependence,
angular dependence and loss of sensitivity after X ray exposure. The
results showed that the three devices have proportional response with
the air kerma; the energy dependence displayed for each device
suggests that some calibration factors would be applied for each one;
the angular dependence showed a similar pattern among the three
electronic components. In respect to the fourth parameter analyzed,
one phototransistor has the highest sensitivity however it also showed
the greatest loss of sensitivity with the accumulated dose. The
photodiode was the device with the smaller sensitivity to radiation,
on the other hand, the loss of sensitivity after irradiation is negligible.
Since high accuracy is a desired feature for a dosimeter, the
photodiode can be the most suitable of the three devices for
dosimetry in tomography. The phototransistors can also be used for
CT dosimetry, however it would be necessary a correction factor due
to loss of sensitivity with accumulated dose.
Abstract: The aim of this paper is to investigate twodimensional unsteady flow of a viscous incompressible fluid about stagnation point on permeable stretching sheet in presence of time dependent free stream velocity. Fluid is considered in the influence of transverse magnetic field in the presence of radiation effect. Rosseland approximation is use to model the radiative heat transfer. Using time-dependent stream function, partial differential equations corresponding to the momentum and energy equations are converted into non-linear ordinary differential equations. Numerical solutions of these equations are obtained by using Runge-Kutta Fehlberg method with the help of Newton-Raphson shooting technique. In the present work the effect of unsteadiness parameter, magnetic field parameter, radiation parameter, stretching parameter and the Prandtl number on flow and heat transfer characteristics have been discussed. Skin-friction coefficient and Nusselt number at the sheet are computed and discussed. The results reported in the paper are in good agreement with published work in literature by other researchers.
Abstract: Tailor-welded Blanks (TWBs) are tailor made for
different complex component designs by welding multiple metal
sheets with different thicknesses, shapes, coatings or strengths prior
to forming. In this study the Hemispherical Die Stretching (HDS) test
(out-of-plane stretching) of TWBs were simulated via
ABAQUS/Explicit to obtain the Forming Limit Diagrams (FLDs) of
Stainless steel (AISI 304) laser welded blanks with different
thicknesses. Two criteria were used to detect the start of necking to
determine the FLD for TWBs and parent sheet metals. These two
criteria are the second derivatives of the major and thickness strains
that are given from the strain history of simulation. In the other word,
in these criteria necking starts when the second derivative of
thickness or major strain reaches its maximum. With having the time
of onset necking, one can measure the major and minor strains at the
critical area and determine the forming limit curve.
Abstract: DNA microarray technology is widely used by
geneticists to diagnose or treat diseases through gene expression.
This technology is based on the hybridization of a tissue-s DNA
sequence into a substrate and the further analysis of the image
formed by the thousands of genes in the DNA as green, red or yellow
spots. The process of DNA microarray image analysis involves
finding the location of the spots and the quantification of the
expression level of these. In this paper, a tool to perform DNA
microarray image analysis is presented, including a spot addressing
method based on the image projections, the spot segmentation
through contour based segmentation and the extraction of relevant
information due to gene expression.