Abstract: The winding hot-spot temperature is one of the most
critical parameters that affect the useful life of the power
transformers. The winding hot-spot temperature can be calculated as
function of the top-oil temperature that can estimated by using the
ambient temperature and transformer loading measured data. This
paper proposes the estimation of the top-oil temperature by using a
method based on Least Squares Support Vector Machines approach.
The estimated top-oil temperature is compared with measured data of
a power transformer in operation. The results are also compared with
methods based on the IEEE Standard C57.91-1995/2000 and
Artificial Neural Networks. It is shown that the Least Squares
Support Vector Machines approach presents better performance than
the methods based in the IEEE Standard C57.91-1995/2000 and
artificial neural networks.
Abstract: Time interleaved sigma-delta (TIΣΔ) architecture is a
potential candidate for high bandwidth analog to digital converters
(ADC) which remains a bottleneck for software and cognitive radio
receivers. However, the performance of the TIΣΔ architecture is
limited by the unavoidable gain and offset mismatches resulting
from the manufacturing process. This paper presents a novel digital
calibration method to compensate the gain and offset mismatch
effect. The proposed method takes advantage of the reconstruction
digital signal processing on each channel and requires only few logic
components for implementation. The run time calibration is estimated
to 10 and 15 clock cycles for offset cancellation and gain mismatch
calibration respectively.
Abstract: Performance of any continuous speech recognition system is highly dependent on performance of the acoustic models. Generally, development of the robust spoken language technology relies on the availability of large amounts of data. Common way to cope with little data for training each state of Markov models is treebased state tying. This tying method applies contextual questions to tie states. Manual procedure for question generation suffers from human errors and is time consuming. Various automatically generated questions are used to construct decision tree. There are three approaches to generate questions to construct HMMs based on decision tree. One approach is based on misrecognized phonemes, another approach basically uses feature table and the other is based on state distributions corresponding to context-independent subword units. In this paper, all these methods of automatic question generation are applied to the decision tree on FARSDAT corpus in Persian language and their results are compared with those of manually generated questions. The results show that automatically generated questions yield much better results and can replace manually generated questions in Persian language.
Abstract: Lattice Monte Carlo methods are an excellent
choice for the simulation of non-linear thermal diffusion
problems. In this paper, and for the first time, Lattice Monte
Carlo analysis is performed on thermal diffusion combined
with convective heat transfer. Laminar flow of water modeled
as an incompressible fluid inside a copper pipe with a constant
surface temperature is considered. For the simulation of
thermal conduction, the temperature dependence of the
thermal conductivity of the water is accounted for. Using the
novel Lattice Monte Carlo approach, temperature distributions
and energy fluxes are obtained.
Abstract: The paper presents a new hybridization methodology involving Neural, Fuzzy and Rough Computing. A Rough Sets based approximation technique has been proposed based on a certain Neuro – Fuzzy architecture. A New Rough Neuron composition consisting of a combination of a Lower Bound neuron and a Boundary neuron has also been described. The conventional convergence of error in back propagation has been given away for a new framework based on 'Output Excitation Factor' and an inverse input transfer function. The paper also presents a brief comparison of performances, of the existing Rough Neural Networks and ANFIS architecture against the proposed methodology. It can be observed that the rough approximation based neuro-fuzzy architecture is superior to its counterparts.
Abstract: Small-scale RC models of both piles and tunnel ducts
were produced as mockups of reality and loaded under soil
confinement conditionsto investigate the damage evolution of
structural RC interacting with soil. Experimental verifications usinga
3D nonlinear FE analysis program called COM3D, which was
developed at the University of Tokyo, are introduced. This analysis
has been used in practice for seismic performance assessment of
underground ducts and in-ground LNG storage tanks in consideration
of soil-structure interactionunder static and dynamic loading. Varying
modes of failure of RCpilessubjected to different magnitudes of soil
confinement were successfully reproduced in the proposed small-scale
experiments and numerically simulated as well. Analytical simulation
was applied to RC tunnel mockups under a wide variety of depth and
soil confinement conditions, and reasonable matching was confirmed.
Abstract: In this paper, four carbazole-based D-D-π-A organic
dyes code as CCT2A, CCT3A, CCT1PA and CCT2PA were reported.
A series of these organic dyes containing identical donor and
acceptor group but different π-system. The effect of replacing of
thiophene by phenyl thiophene as π-system on the physical
properties has been focused. The structural, energetic properties and
absorption spectra were theoretically investigated by means of
Density Functional Theory (DFT) and Time-Dependent Density
Functional Theory (TD-DFT). The results show that nonplanar
conformation due to steric hindrance in donor part (cabazolecarbazole
unit) of dye molecule can prevent unfavorable dye
aggregation. By means of the TD-DFT method, the absorption
spectra were calculated by B3LYP and BHandHLYP to study the
affect of hybrid functional on the excitation energy (Eg). The results
revealed the increasing of thiophene units not only resulted in
decreasing of Eg, but also found the shifting of absorption spectra to
higher wavelength. TD-DFT/BHandHLYP calculated results are
more strongly agreed with the experimental data than B3LYP
functions. Furthermore, the adsorptions of CCT2A and CCT3A on the
TiO2 anatase (101) surface were carried out by mean of the chemical
periodic calculation. The result exhibit the strong adsorption energy.
The calculated results provide our new organic dyes can be
effectively used as dye for Dye Sensitized Solar Cell (DSC).
Abstract: The interaction between wakes of bluff body and
airfoil have profound influences on system performance in many
industrial applications, e.g., turbo-machinery and cooling fan. The
present work investigates the effect of configuration include; airfoil-s
angle of attack, transverse and inline spacing of the models, on
frequency behavior of the cylinder-s near-wake. The experiments
carried on under subcritical flow regime, using the hot-wire
anemometry (HWA). The relationship between the Strouhal numbers
and arrangements provide an insight into the global physical
processes of wake interaction and vortex shedding.
Abstract: Developers need to evaluate software's performance to make software efficient. This paper suggests a performance evaluation system for embedded software. The suggested system consists of code analyzer, testing agents, data analyzer, and report viewer. The code analyzer inserts additional code dependent on target system into source code and compiles the source code. The testing agents execute performance test. The data analyzer translates raw-level results data to class-level APIs for reporting viewer. The report viewer offers users graphical report views by using the APIs. We hope that the suggested tool will be useful for embedded-related software development,because developers can easily and intuitively analyze software's performance and resource utilization.
Abstract: Activity-Based Costing (ABC) which has become an important aspect of manufacturing/service organizations can be defined as a methodology that measures the cost and performance of activities, resources and cost objects. It can be considered as an alternative paradigm to traditional cost-based accounting systems. The objective of this paper is to illustrate an application of ABC method and to compare the results of ABC with traditional costing methods. The results of the application highlight the weak points of traditional costing methods and an S-Curve obtained is used to identify the undercosted and overcosted products of the firm.
Abstract: Non-stationary trend in R-R interval series is
considered as a main factor that could highly influence the evaluation
of spectral analysis. It is suggested to remove trends in order to obtain
reliable results. In this study, three detrending methods, the
smoothness prior approach, the wavelet and the empirical mode
decomposition, were compared on artificial R-R interval series with
four types of simulated trends. The Lomb-Scargle periodogram was
used for spectral analysis of R-R interval series. Results indicated that
the wavelet method showed a better overall performance than the other
two methods, and more time-saving, too. Therefore it was selected for
spectral analysis of real R-R interval series of thirty-seven healthy
subjects. Significant decreases (19.94±5.87% in the low frequency
band and 18.97±5.78% in the ratio (p
Abstract: In the paper, the energetic features of the loaded gait
are newly analyzed depending on the trunk flexion change. To
investigate the loaded gait, walking experiments are performed for five
subjects and, the ground reaction forces and kinematic data are
measured. Based on these information, we compute the impulse,
momentum and mechanical works done on the center of body mass,
through the trunk flexion change. As a result, it is shown that the trunk
flexion change does not affect the impulses and momentums during
the step-to-step transition as well. However, the direction of the
pre-collision momentum does change depending on the trunk flexion
change, which is degenerated just after (or during) the collision period.
Abstract: This paper represents the results of long term strength of mortar incorporating Rice Husk Ash (RHA). For these work mortar samples were made according to ASTM standard C 109/C. OPC cement was partially replaced by RHA at 0, 10, 15, 20, 25 and 30 percent replacement level. After casting all samples were kept in controlled environment and curing was done up to 90 days. Test of mortar was performed on 3, 7, 28, 90, 365 and 700 days. It is noticed that OPC mortar shows better strength at early age than mortar having RHA but at 90 days and onward the picture is different. At 700 days it is observed that mortar containing 20% RHA shows better result than any other samples.
Abstract: This paper explores the opportunity of using tri-axial
wireless accelerometers for supervised monitoring of sports
movements. A motion analysis system for the upper extremities of
lawn bowlers in particular is developed. Accelerometers are placed
on parts of human body such as the chest to represent the shoulder
movements, the back to capture the trunk motion, back of the hand,
the wrist and one above the elbow, to capture arm movements. These
sensors placement are carefully designed in order to avoid restricting
bowler-s movements. Data is acquired from these sensors in soft-real
time using virtual instrumentation; the acquired data is then
conditioned and converted into required parameters for motion
regeneration. A user interface was also created to facilitate in the
acquisition of data, and broadcasting of commands to the wireless
accelerometers. All motion regeneration in this paper deals with the
motion of the human body segment in the X and Y direction, looking
into the motion of the anterior/ posterior and lateral directions
respectively.
Abstract: In this paper, we present a novel approach to accurately
detect text regions including shop name in signboard images with
complex background for mobile system applications. The proposed
method is based on the combination of text detection using edge
profile and region segmentation using fuzzy c-means method. In the
first step, we perform an elaborate canny edge operator to extract all
possible object edges. Then, edge profile analysis with vertical and
horizontal direction is performed on these edge pixels to detect
potential text region existing shop name in a signboard. The edge
profile and geometrical characteristics of each object contour are
carefully examined to construct candidate text regions and classify the
main text region from background. Finally, the fuzzy c-means
algorithm is performed to segment and detected binarize text region.
Experimental results show that our proposed method is robust in text
detection with respect to different character size and color and can
provide reliable text binarization result.
Abstract: In this work a software simulation model has been
proposed for two driven wheels mobile robot path planning; that can
navigate in dynamic environment with static distributed obstacles.
The work involves utilizing Bezier curve method in a proposed N
order matrix form; for engineering the mobile robot path. The Bezier
curve drawbacks in this field have been diagnosed. Two directions:
Up and Right function has been proposed; Probability Recursive
Function (PRF) to overcome those drawbacks.
PRF functionality has been developed through a proposed;
obstacle detection function, optimization function which has the
capability of prediction the optimum path without comparison
between all feasible paths, and N order Bezier curve function that
ensures the drawing of the obtained path.
The simulation results that have been taken showed; the mobile
robot travels successfully from starting point and reaching its goal
point. All obstacles that are located in its way have been avoided.
This navigation is being done successfully using the proposed PRF
techniques.
Abstract: This paper developed the c-Chart based on a Zero- Inflated Poisson (ZIP) processes that approximated by a geometric distribution with parameter p. The p estimated that fit for ZIP distribution used in calculated the mean, median, and variance of geometric distribution for constructed the c-Chart by three difference methods. For cg-Chart, developed c-Chart by used the mean and variance of the geometric distribution constructed control limits. For cmg-Chart, the mean used for constructed the control limits. The cme- Chart, developed control limits of c-Chart from median and variance values of geometric distribution. The performance of charts considered from the Average Run Length and Average Coverage Probability. We found that for an in-control process, the cg-Chart is superior for low level of mean at all level of proportion zero. For an out-of-control process, the cmg-Chart and cme-Chart are the best for mean = 2, 3 and 4 at all level of parameter.
Abstract: The aim of this study is to identify the conditions of
implementation for reconfigurability in summarizing past flexible
manufacturing systems (FMS) research by drawing overall
conclusions from many separate High Performance Manufacturing
(HPM) studies. Meta-analysis will be applied to links between HPM
programs and their practices related to FMS and manufacturing
performance with particular reference to responsiveness performance.
More specifically, an application of meta-analysis will be made with
reference to two of the main steps towards the development of an
empirically-tested theory: testing the adequacy of the measurement of
variables and testing the linkages between the variables.
Abstract: This paper proposes two novel schemes for pilot-aided
integer frequency offset (IFO) estimation in orthogonal frequency
division multiplexing (OFDM)-based digital video broadcastingterrestrial
(DVB-T) systems. The conventional scheme proposed for
estimating the IFO uses only partial information of combinations
that pilots can provide, which stems from a rigorous assumption
that the channel responses of pilots used for estimating the IFO
change very rapidly. Thus, in this paper, we propose the novel IFO
estimation schemes exploiting all information of combinations that
pilots can provide to improve the performance of IFO estimation.
The simulation results show that the proposed schemes are highly
accurate in terms of the IFO detection probability.
Abstract: A new dynamic clustering approach (DCPSO), based
on Particle Swarm Optimization, is proposed. This approach is
applied to unsupervised image classification. The proposed approach
automatically determines the "optimum" number of clusters and
simultaneously clusters the data set with minimal user interference.
The algorithm starts by partitioning the data set into a relatively large
number of clusters to reduce the effects of initial conditions. Using
binary particle swarm optimization the "best" number of clusters is
selected. The centers of the chosen clusters is then refined via the Kmeans
clustering algorithm. The experiments conducted show that
the proposed approach generally found the "optimum" number of
clusters on the tested images.