Abstract: The purpose of this research is to study motivation
factors and also to study factors relation to job performance to
compare motivation factors under the personal factor classification
such as gender, age, income, educational level, marital status, and
working duration; and to study the relationship between Motivation
Factors and Job Performance with job satisfactions. The sample
groups utilized in this research were 400 Suan Sunandha Rajabhat
University employees. This research is a quantitative research using
questionnaires as research instrument. The statistics applied for data
analysis including percentage, mean, and standard deviation. In
addition, the difference analysis was conducted by t value computing,
one-way analysis of variance and Pearson’s correlation coefficient
computing. The findings of the study results were as follows the
findings showed that the aspects of job promotion and salary were at
the moderate levels. Additionally, the findings also showed that the
motivations that affected the revenue branch chiefs’ job performance
were job security, job accomplishment, policy and management, job
promotion, and interpersonal relation.
Abstract: In this paper, a novel deinterlacing algorithm is
proposed. The proposed algorithm approximates the distribution of the
luminance into a polynomial function. Instead of using one
polynomial function for all pixels, different polynomial functions are
used for the uniform, texture, and directional edge regions. The
function coefficients for each region are computed by matrix
multiplications. Experimental results demonstrate that the proposed
method performs better than the conventional algorithms.
Abstract: This study investigated the use of modified
atmosphere packaging (MAP) and different packaging to extend the
shelf life of Barbari flat bread. Three atmospheres including 70%CO2
and 30%N2, 50% CO2 and 50%N2 and a normal air as control were
used. The bread samples were packaged in three type pouches. The
shelf life was determined by appearance of mold and yeast (M +Y) in
Barbari bread samples stored at 25 ± 1°C and 38 ± 2% relative
humidity. The results showed that it is possible to prolong the shelf
life of Barbari bread from four days to about 21 days by using
modified atmosphere packaging with high carbon dioxide
concentration and high-barrier laminated and vacuum bags packages.
However, the hardness of samples kept in MAP increase significantly
by increase of carbon dioxide concentration. The correlation
coefficient (r) between headspace CO2 concentration and hardness
was 0.997, 0.997 and 0.599 for A, B and C packaging respectively.
High negative correlation coefficients were found between the crumb
moisture and the hardness values in various packaging. There were
significant negative correlation coefficients between sensory
parameters and hardness of texture.
Abstract: This study compared socio-economic status attainment between the Muslim and Santal couples in rural Bangladesh. For this we hypothesized that socio-economic status attainment (occupation, education and income) of the Muslim couples was higher than the Santal ones in rural Bangladesh. In order to examine the hypothesis 288 couples (145 couples for Muslim and 143 couples for Santal) selected by cluster random sampling from Kalna village, Bangladesh were individually interviewed with semistructured questionnaire method. The results of Pearson Chi-Squire test suggest that there were significant differences in socio-economic status attainment between the two communities- couples. In addition, Pearson correlation coefficients also suggest that there were significant associations between the socio-economic statuses attained by the two communities- couples in rural Bangladesh. Further crosscultural study should conduct on how inter-community relations in rural social structure of Bangladesh influence the differences among the couples- socio-economic status attainment
Abstract: Maximal Ratio Combining (MRC) is considered the most complex combining technique as it requires channel coefficients estimation. It results in the lowest bit error rate (BER) compared to all other combining techniques. However the BER starts to deteriorate as errors are introduced in the channel coefficients estimation. A novel combining technique, termed Generalized Maximal Ratio Combining (GMRC) with a polynomial kernel, yields an identical BER as MRC with perfect channel estimation and a lower BER in the presence of channel estimation errors. We show that GMRC outperforms the optimal MRC scheme in general and we hereinafter introduce it to the scientific community as a new “supraoptimal" algorithm. Since diversity combining is especially effective in small femto- and pico-cells, internet-associated wireless peripheral systems are to benefit most from GMRC. As a result, many spinoff applications can be made to IP-based 4th generation networks.
Abstract: Nowadays, without the awareness of consumer
behavior and correct understanding of it, it is not possible for organizations to take appropriate measures to meet the consumer
needs and demands. The aim of this paper is the identification and
prioritization of the factors affecting the consumer behavior based on
the product value. The population of the study includes all the
consumers of furniture producing firms in East Azarbaijan province,
Iran. The research sample includes 93 people selected by the sampling formula in unlimited population. The data collection
instrument was a questionnaire, the validity of which was confirmed
through face validity and the reliability of which was determined,
using Cronbach's alpha coefficient. The Kolmogorov-Smironov test
was used to test data normality, the t-test for identification of factors
affecting the product value, and Friedman test for prioritizing the
factors. The results show that quality, satisfaction, styling, price, finishing operation, performance, safety, worth, shape, use, and
excellence are placed from 1 to 11 priorities, respectively.
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: Measurement of the quality of image compression is important for image processing application. In this paper, we propose an objective image quality assessment to measure the quality of gray scale compressed image, which is correlation well with subjective quality measurement (MOS) and least time taken. The new objective image quality measurement is developed from a few fundamental of objective measurements to evaluate the compressed image quality based on JPEG and JPEG2000. The reliability between each fundamental objective measurement and subjective measurement (MOS) is found. From the experimental results, we found that the Maximum Difference measurement (MD) and a new proposed measurement, Structural Content Laplacian Mean Square Error (SCLMSE), are the suitable measurements that can be used to evaluate the quality of JPEG200 and JPEG compressed image, respectively. In addition, MD and SCLMSE measurements are scaled to make them equivalent to MOS, given the rate of compressed image quality from 1 to 5 (unacceptable to excellent quality).
Abstract: In this paper, image compression using hybrid vector
quantization scheme such as Multistage Vector Quantization
(MSVQ) and Pyramid Vector Quantization (PVQ) are introduced. A
combined MSVQ and PVQ are utilized to take advantages provided
by both of them. In the wavelet decomposition of the image, most of
the information often resides in the lowest frequency subband.
MSVQ is applied to significant low frequency coefficients. PVQ is
utilized to quantize the coefficients of other high frequency
subbands. The wavelet coefficients are derived using lifting scheme.
The main aim of the proposed scheme is to achieve high compression
ratio without much compromise in the image quality. The results are
compared with the existing image compression scheme using MSVQ.
Abstract: In this work, the primary compressive strength
components of human femur trabecular bone are qualitatively
assessed using image processing and wavelet analysis. The Primary
Compressive (PC) component in planar radiographic femur trabecular
images (N=50) is delineated by semi-automatic image processing
procedure. Auto threshold binarization algorithm is employed to
recognize the presence of mineralization in the digitized images. The
qualitative parameters such as apparent mineralization and total area
associated with the PC region are derived for normal and abnormal
images.The two-dimensional discrete wavelet transforms are utilized
to obtain appropriate features that quantify texture changes in medical
images .The normal and abnormal samples of the human femur are
comprehensively analyzed using Harr wavelet.The six statistical
parameters such as mean, median, mode, standard deviation, mean
absolute deviation and median absolute deviation are derived at level
4 decomposition for both approximation and horizontal wavelet
coefficients. The correlation coefficient of various wavelet derived
parameters with normal and abnormal for both approximated and
horizontal coefficients are estimated. It is seen that in almost all cases
the abnormal show higher degree of correlation than normals. Further
the parameters derived from approximation coefficient show more
correlation than those derived from the horizontal coefficients. The
parameters mean and median computed at the output of level 4 Harr
wavelet channel was found to be a useful predictor to delineate the
normal and the abnormal groups.
Abstract: The clinical usefulness of heart rate variability is
limited to the range of Holter monitoring software available. These
software algorithms require a normal sinus rhythm to accurately
acquire heart rate variability (HRV) measures in the frequency
domain. Premature ventricular contractions (PVC) or more
commonly referred to as ectopic beats, frequent in heart failure,
hinder this analysis and introduce ambiguity. This investigation
demonstrates an algorithm to automatically detect ectopic beats by
analyzing discrete wavelet transform coefficients. Two techniques
for filtering and replacing the ectopic beats from the RR signal are
compared. One technique applies wavelet hard thresholding
techniques and another applies linear interpolation to replace ectopic
cycles. The results demonstrate through simulation, and signals
acquired from a 24hr ambulatory recorder, that these techniques can
accurately detect PVC-s and remove the noise and leakage effects
produced by ectopic cycles retaining smooth spectra with the
minimum of error.
Abstract: Video-on-demand (VOD) is designed by using content delivery networks (CDN) to minimize the overall operational cost and to maximize scalability. Estimation of the viewing pattern (i.e., the relationship between the number of viewings and the ranking of VOD contents) plays an important role in minimizing the total operational cost and maximizing the performance of the VOD systems. In this paper, we have analyzed a large body of commercial VOD viewing data and found that the viewing rank distribution fits well with the parabolic fractal distribution. The weighted linear model fitting function is used to estimate the parameters (coefficients) of the parabolic fractal distribution. This paper presents an analytical basis for designing an optimal hierarchical VOD contents distribution system in terms of its cost and performance.
Abstract: There have been various methods created based on the regression ideas to resolve the problem of data set containing censored observations, i.e. the Buckley-James method, Miller-s method, Cox method, and Koul-Susarla-Van Ryzin estimators. Even though comparison studies show the Buckley-James method performs better than some other methods, it is still rarely used by researchers mainly because of the limited diagnostics analysis developed for the Buckley-James method thus far. Therefore, a diagnostic tool for the Buckley-James method is proposed in this paper. It is called the renovated Cook-s Distance, (RD* i ) and has been developed based on the Cook-s idea. The renovated Cook-s Distance (RD* i ) has advantages (depending on the analyst demand) over (i) the change in the fitted value for a single case, DFIT* i as it measures the influence of case i on all n fitted values Yˆ∗ (not just the fitted value for case i as DFIT* i) (ii) the change in the estimate of the coefficient when the ith case is deleted, DBETA* i since DBETA* i corresponds to the number of variables p so it is usually easier to look at a diagnostic measure such as RD* i since information from p variables can be considered simultaneously. Finally, an example using Stanford Heart Transplant data is provided to illustrate the proposed diagnostic tool.
Abstract: This study proposes a basic molecular formula for all
proteins. A total of 10,739 proteins belonging to 9 different protein
groups classified on the basis of their functions were selected
randomly. They included enzymes, storage proteins, hormones,
signalling proteins, structural proteins, transport proteins,
immunoglobulins or antibodies, motor proteins and receptor proteins.
After obtaining the protein molecular formula using the ProtParam
tool, the H/C, N/C, O/C, and S/C ratios were determined for each
randomly selected sample. In this case, H, N, O, and S coefficients
were specified per carbon atom. Surprisingly, the results
demonstrated that H, N, O, and S coefficients for all 10,739 proteins
are similar and highly correlated. This study demonstrates that
despite differences in the structure and function, all known proteins
have a similar basic molecular formula CnH1.58 ± 0.015nN0.28 ± 0.005nO0.30
± 0.007nS0.01 ± 0.002n. The total correlation between all coefficients was
found to be 0.9999.
Abstract: The study investigated the hydrophilic to hydrophobic
transition of modified polyacrylamide hydrogel with the inclusion of
N-isopropylacrylamide (NIAM). The modification was done by
mimicking micellar polymerization, which resulted in better
arrangement of NIAM chains in the polyacrylamide network. The
degree of NIAM arrangement is described by NH number. The
hydrophilic to hydrophobic transition was measured through the
partition coefficient, K, of Orange II and Methylene Blue in hydrogel
and in water. These dyes were chosen as a model for solutes with
different degree of hydrophobicity. The study showed that the
hydrogel with higher NH values resulted in better solubility of both
dyes. Moreover, in temperature above the lower critical solution
temperature (LCST) of Poly(N-isopropylacrylamide) (PNIAM)also
caused the collapse of NIPAM chains which results in a more
hydrophobic environment that increases the solubility of Methylene
Blue and decreases the solubility of Orange II in the hydrogels with
NIPAM present.
Abstract: In this paper, an algorithm for detecting and attenuating
puff noises frequently generated under the mobile environment is
proposed. As a baseline system, puff detection system is designed
based on Gaussian Mixture Model (GMM), and 39th Mel Frequency
Cepstral Coefficient (MFCC) is extracted as feature parameters. To
improve the detection performance, effective acoustic features for puff
detection are proposed. In addition, detected puff intervals are
attenuated by high-pass filtering. The speech recognition rate was
measured for evaluation and confusion matrix and ROC curve are used
to confirm the validity of the proposed system.
Abstract: Hypersonic flows around spatial vehicles during their
reentry phase in planetary atmospheres are characterized by intense
aerothermal phenomena. The aim of this work is to analyze high
temperature flows around an axisymmetric blunt body taking into
account chemical and vibrational non-equilibrium for air mixture
species. For this purpose, a finite volume methodology is employed
to determine the supersonic flow parameters around the axisymmetric
blunt body, especially at the stagnation point and along the wall of
spacecraft for several altitudes. This allows the capture shock wave
before a blunt body placed in supersonic free stream. The numerical
technique uses the Flux Vector Splitting method of Van Leer. Here,
adequate time stepping parameter, along with CFL coefficient and
mesh size level are selected to ensure numerical convergence, sought
with an order of 10-8
Abstract: Despite the fact that Arabic language is currently one
of the most common languages worldwide, there has been only a
little research on Arabic speech recognition relative to other
languages such as English and Japanese. Generally, digital speech
processing and voice recognition algorithms are of special
importance for designing efficient, accurate, as well as fast automatic
speech recognition systems. However, the speech recognition process
carried out in this paper is divided into three stages as follows: firstly,
the signal is preprocessed to reduce noise effects. After that, the
signal is digitized and hearingized. Consequently, the voice activity
regions are segmented using voice activity detection (VAD)
algorithm. Secondly, features are extracted from the speech signal
using Mel-frequency cepstral coefficients (MFCC) algorithm.
Moreover, delta and acceleration (delta-delta) coefficients have been
added for the reason of improving the recognition accuracy. Finally,
each test word-s features are compared to the training database using
dynamic time warping (DTW) algorithm. Utilizing the best set up
made for all affected parameters to the aforementioned techniques,
the proposed system achieved a recognition rate of about 98.5%
which outperformed other HMM and ANN-based approaches
available in the literature.
Abstract: In this paper, a novel approach is presented
for designing multiplier-free state-space digital filters. The
multiplier-free design is obtained by finding power-of-2 coefficients
and also quantizing the state variables to power-of-2
numbers. Expressions for the noise variance are derived for the
quantized state vector and the output of the filter. A “structuretransformation
matrix" is incorporated in these expressions. It
is shown that quantization effects can be minimized by properly
designing the structure-transformation matrix. Simulation
results are very promising and illustrate the design algorithm.
Abstract: The current methods of predictive controllers are
utilized for those processes in which the rate of output variations is
not high. For such processes, therefore, stability can be achieved by
implementing the constrained predictive controller or applying
infinite prediction horizon. When the rate of the output growth is
high (e.g. for unstable nonminimum phase process) the stabilization
seems to be problematic. In order to avoid this, it is suggested to
change the method in the way that: first, the prediction error growth
should be decreased at the early stage of the prediction horizon, and
second, the rate of the error variation should be penalized. The
growth of the error is decreased through adjusting its weighting
coefficients in the cost function. Reduction in the error variation is
possible by adding the first order derivate of the error into the cost
function. By studying different examples it is shown that using these
two remedies together, the closed-loop stability of unstable
nonminimum phase process can be achieved.