Abstract: Script identification is one of the challenging steps in the development of optical character recognition system for bilingual or multilingual documents. In this paper an attempt is made for identification of English numerals at word level from Punjabi documents by using Gabor features. The support vector machine (SVM) classifier with five fold cross validation is used to classify the word images. The results obtained are quite encouraging. Average accuracy with RBF kernel, Polynomial and Linear Kernel functions comes out to be greater than 99%.
Abstract: To reveal the temperature field distribution of disc
brake in downward belt conveyor, mathematical models of heat
transfer for disc brake were established combined with heat transfer
theory. Then, the simulation process was stated in detail and the
temperature field of disc brake under conditions of dynamic speed and
dynamic braking torque was numerically simulated by using ANSYS
software. Finally the distribution and variation laws of temperature
field in the braking process were analyzed. Results indicate that the
maximum surface temperature occurs at a time before the brake end
and there exist large temperature gradients in both radial and axial
directions, while it is relatively small in the circumferential direction.
Abstract: Scale Invariant Feature Transform (SIFT) has been
widely applied, but extracting SIFT feature is complicated and
time-consuming. In this paper, to meet the demand of the real-time
applications, SIFT is parallelized and optimized on cluster system,
which is named pSIFT. Redundancy storage and communication are
used for boundary data to improve the performance, and before
representation of feature descriptor, data reallocation is adopted to
keep load balance in pSIFT. Experimental results show that pSIFT
achieves good speedup and scalability.
Abstract: The objective of this research was to study the
influence of marketing mix on customers purchasing behavior. A
total of 397 respondents were collected from customers who were the
patronages of the Chatuchak Plaza market. A questionnaire was
utilized as a tool to collect data. Statistics utilized in this research
included frequency, percentage, mean, standard deviation, and
multiple regression analysis. Data were analyzed by using Statistical
Package for the Social Sciences. The findings revealed that the
majority of respondents were male with the age between 25-34 years
old, hold undergraduate degree, married and stay together. The
average income of respondents was between 10,001-20,000 baht. In
terms of occupation, the majority worked for private companies. The
research analysis disclosed that there were three variables of
marketing mix which included price (X2), place (X3), and product
(X1) which had an influence on the frequency of customer
purchasing. These three variables can predict a purchase about 30
percent of the time by using the equation; Y1 = 6.851 + .921(X2) +
.949(X3) + .591(X1). It also found that in terms of marketing mixed,
there were two variables had an influence on the amount of customer
purchasing which were physical characteristic (X6), and the process
(X7). These two variables are 17 percent predictive of a purchasing
by using the equation: Y2 = 2276.88 + 2980.97(X6) + 2188.09(X7).
Abstract: This paper presents a novel method for inferring the
odor based on neural activities observed from rats- main olfactory
bulbs. Multi-channel extra-cellular single unit recordings were done
by micro-wire electrodes (tungsten, 50μm, 32 channels) implanted in
the mitral/tufted cell layers of the main olfactory bulb of anesthetized
rats to obtain neural responses to various odors. Neural response
as a key feature was measured by substraction of neural firing rate
before stimulus from after. For odor inference, we have developed a
decoding method based on the maximum likelihood (ML) estimation.
The results have shown that the average decoding accuracy is about
100.0%, 96.0%, 84.0%, and 100.0% with four rats, respectively. This
work has profound implications for a novel brain-machine interface
system for odor inference.
Abstract: Persuasive technology has been applied in marketing,
health, environmental conservation, safety and other domains and is
found to be quite effective in changing people-s attitude and
behaviours. This research extends the application domains of
persuasive technology to information security awareness and uses a
theory-driven approach to evaluate the effectiveness of a web-based
program developed based on the principles of persuasive technology
to improve the information security awareness of end users. The
findings confirm the existence of a very strong effect of the webbased
program in raising users- attitude towards information security
aware behavior. This finding is useful to the IT researchers and
practitioners in developing appropriate and effective education
strategies for improving the information security attitudes for endusers.
Abstract: Image compression plays a vital role in today-s
communication. The limitation in allocated bandwidth leads to
slower communication. To exchange the rate of transmission in the
limited bandwidth the Image data must be compressed before
transmission. Basically there are two types of compressions, 1)
LOSSY compression and 2) LOSSLESS compression. Lossy
compression though gives more compression compared to lossless
compression; the accuracy in retrievation is less in case of lossy
compression as compared to lossless compression. JPEG, JPEG2000
image compression system follows huffman coding for image
compression. JPEG 2000 coding system use wavelet transform,
which decompose the image into different levels, where the
coefficient in each sub band are uncorrelated from coefficient of
other sub bands. Embedded Zero tree wavelet (EZW) coding exploits
the multi-resolution properties of the wavelet transform to give a
computationally simple algorithm with better performance compared
to existing wavelet transforms. For further improvement of
compression applications other coding methods were recently been
suggested. An ANN base approach is one such method. Artificial
Neural Network has been applied to many problems in image
processing and has demonstrated their superiority over classical
methods when dealing with noisy or incomplete data for image
compression applications. The performance analysis of different
images is proposed with an analysis of EZW coding system with
Error Backpropagation algorithm. The implementation and analysis
shows approximately 30% more accuracy in retrieved image
compare to the existing EZW coding system.
Abstract: The method of gait identification based on the nearest neighbor classification technique with motion similarity assessment by the dynamic time warping is proposed. The model based kinematic motion data, represented by the joints rotations coded by Euler angles and unit quaternions is used. The different pose distance functions in Euler angles and quaternion spaces are considered. To evaluate individual features of the subsequent joints movements during gait cycle, joint selection is carried out. To examine proposed approach database containing 353 gaits of 25 humans collected in motion capture laboratory is used. The obtained results are promising. The classifications, which takes into consideration all joints has accuracy over 91%. Only analysis of movements of hip joints allows to correctly identify gaits with almost 80% precision.
Abstract: The performance of high-resolution schemes is investigated for unsteady, inviscid and compressible multiphase flows. An Eulerian diffuse interface approach has been chosen for the simulation of multicomponent flow problems. The reduced fiveequation and seven equation models are used with HLL and HLLC approximation. The authors demonstrated the advantages and disadvantages of both seven equations and five equations models studying their performance with HLL and HLLC algorithms on simple test case. The seven equation model is based on two pressure, two velocity concept of Baer–Nunziato [10], while five equation model is based on the mixture velocity and pressure. The numerical evaluations of two variants of Riemann solvers have been conducted for the classical one-dimensional air-water shock tube and compared with analytical solution for error analysis.
Abstract: Determining depth of anesthesia is a challenging problem
in the context of biomedical signal processing. Various methods
have been suggested to determine a quantitative index as depth of
anesthesia, but most of these methods suffer from high sensitivity
during the surgery. A novel method based on energy scattering of
samples in the wavelet domain is suggested to represent the basic
content of electroencephalogram (EEG) signal. In this method, first
EEG signal is decomposed into different sub-bands, then samples
are squared and energy of samples sequence is constructed through
each scale and time, which is normalized and finally entropy of the
resulted sequences is suggested as a reliable index. Empirical Results
showed that applying the proposed method to the EEG signals can
classify the awake, moderate and deep anesthesia states similar to
BIS.
Abstract: Lighvan cheese is basically made from sheep milk in
the area of Sahand mountainside which is located in the North West
of Iran. The main objective of this study was to investigate the effect
of enterococci isolated from traditional Lighvan cheese on the quality
of Iranian UF white during ripening. The experimental design was
split plot based on randomized complete blocks, main plots were four
types of starters and subplots were different ripening durations.
Addition of Enterococcus spp. did not significantly (P
Abstract: In high bitrate information hiding techniques, 1 bit is
embedded within each 4 x 4 Discrete Cosine Transform (DCT)
coefficient block by means of vector quantization, then the hidden bit
can be effectively extracted in terminal end. In this paper high bitrate
information hiding algorithms are summarized, and the scheme of
video in video is implemented. Experimental result shows that the host
video which is embedded numerous auxiliary information have little
visually quality decline. Peak Signal to Noise Ratio (PSNR)Y of host
video only degrades 0.22dB in average, while the hidden information
has a high percentage of survives and keeps a high robustness in
H.264/AVC compression, the average Bit Error Rate(BER) of hiding
information is 0.015%.
Abstract: Three novel and significant contributions are made in
this paper Firstly, non-recursive formulation of Haar connection
coefficients, pioneered by the present authors is presented, which
can be computed very efficiently and avoid stack and memory
overflows. Secondly, the generalized approach for state analysis of
singular bilinear time-invariant (TI) and time-varying (TV) systems
is presented; vis-˜a-vis diversified and complex works reported by
different authors. Thirdly, a generalized approach for parameter
estimation of bilinear TI and TV systems is also proposed. The unified
framework of the proposed method is very significant in that the
digital hardware once-designed can be used to perform the complex
tasks of state analysis and parameter estimation of different types
of bilinear systems single-handedly. The simplicity, effectiveness and
generalized nature of the proposed method is established by applying
it to different types of bilinear systems for the two tasks.
Abstract: Software development has experienced remarkable progress in the past decade. However, due to the rising complexity and magnitude of the project the development productivity has not been consistently improved. By analyzing the latest ISBSG data repository with 4106 projects, we discovered that software development productivity has actually undergone irregular variations between the years 1995 and 2005. Considering the factors significant to the productivity, we found its variations are primarily caused by the variations of average team size and the unbalanced uses of the less productive language 3GL.
Abstract: This paper focuses on a critical component of the situational awareness (SA), the neural control of depth flight of an autonomous underwater vehicle (AUV). Constant depth flight is a challenging but important task for AUVs to achieve high level of autonomy under adverse conditions. With the SA strategy, we proposed a multirate neural control of an AUV trajectory using neural network model reference controller for a nontrivial mid-small size AUV "r2D4" stochastic model. This control system has been demonstrated and evaluated by simulation of diving maneuvers using software package Simulink. From the simulation results it can be seen that the chosen AUV model is stable in the presence of high noise, and also can be concluded that the fast SA of similar AUV systems with economy in energy of batteries can be asserted during the underwater missions in search-and-rescue operations.
Abstract: This paper presents a longitudinal quasi-linear model for the ADMIRE model. The ADMIRE model is a nonlinear model of aircraft flying in the condition of high angle of attack. So it can-t be considered to be a linear system approximately. In this paper, for getting the longitudinal quasi-linear model of the ADMIRE, a state transformation based on differentiable functions of the nonscheduling states and control inputs is performed, with the goal of removing any nonlinear terms not dependent on the scheduling parameter. Since it needn-t linear approximation and can obtain the exact transformations of the nonlinear states, the above-mentioned approach is thought to be appropriate to establish the mathematical model of ADMIRE. To verify this conclusion, simulation experiments are done. And the result shows that this quasi-linear model is accurate enough.
Abstract: People detection from images has a variety of applications such as video surveillance and driver assistance system, but is still a challenging task and more difficult in crowded environments such as shopping malls in which occlusion of lower parts of human body often occurs. Lack of the full-body information requires more effective features than common features such as HOG. In this paper, new features are introduced that exploits global self-symmetry (GSS) characteristic in head-shoulder patterns. The features encode the similarity or difference of color histograms and oriented gradient histograms between two vertically symmetric blocks. The domain-specific features are rapid to compute from the integral images in Viola-Jones cascade-of-rejecters framework. The proposed features are evaluated with our own head-shoulder dataset that, in part, consists of a well-known INRIA pedestrian dataset. Experimental results show that the GSS features are effective in reduction of false alarmsmarginally and the gradient GSS features are preferred more often than the color GSS ones in the feature selection.
Abstract: Using one dimensional Quantum hydrodynamic
(QHD) model Korteweg de Vries (KdV) solitary excitations of
electron-acoustic waves (EAWs) have been examined in twoelectron-
populated relativistically degenerate super dense plasma. It
is found that relativistic degeneracy parameter influences the
conditions of formation and properties of solitary structures.
Abstract: This study was initiated with a three prong objective.
One, to identify the relationship between Technological
Competencies factors (Technical Capability, Firm Innovativeness
and E-Business Practices and professional service firms- business
performance. To investigate the predictors of professional service
firms business performance and finally to evaluate the predictors of
business performance according to the type of professional service
firms, a survey questionnaire was deployed to collect empirical data.
The questionnaire was distributed to the owners of the professional
small medium size enterprises services in the Accounting, Legal,
Engineering and Architecture sectors. Analysis showed that all three
Technology Competency factors have moderate effect on business
performance. In addition, the regression models indicate that
technical capability is the most highly influential that could
determine business performance, followed by e-business practices
and firm innovativeness. Subsequently, the main predictor of
business performance for all types of firms is Technical capability.
Abstract: This paper deals with a high-order accurate Runge
Kutta Discontinuous Galerkin (RKDG) method for the numerical
solution of the wave equation, which is one of the simple case of a
linear hyperbolic partial differential equation. Nodal DG method is
used for a finite element space discretization in 'x' by discontinuous
approximations. This method combines mainly two key ideas which
are based on the finite volume and finite element methods. The
physics of wave propagation being accounted for by means of
Riemann problems and accuracy is obtained by means of high-order
polynomial approximations within the elements. High order accurate
Low Storage Explicit Runge Kutta (LSERK) method is used for
temporal discretization in 't' that allows the method to be nonlinearly
stable regardless of its accuracy. The resulting RKDG
methods are stable and high-order accurate. The L1 ,L2 and L∞ error
norm analysis shows that the scheme is highly accurate and effective.
Hence, the method is well suited to achieve high order accurate
solution for the scalar wave equation and other hyperbolic equations.