Abstract: In this paper back-propagation artificial neural
network (BPANN) is employed to predict the limiting drawing ratio
(LDR) of the deep drawing process. To prepare a training set for
BPANN, some finite element simulations were carried out. die and
punch radius, die arc radius, friction coefficient, thickness, yield
strength of sheet and strain hardening exponent were used as the
input data and the LDR as the specified output used in the training of
neural network. As a result of the specified parameters, the program
will be able to estimate the LDR for any new given condition.
Comparing FEM and BPANN results, an acceptable correlation was
found.
Abstract: In this manuscript, we discuss the problem of determining the optimum stratification of a study (or main) variable based on the auxiliary variable that follows a uniform distribution. If the stratification of survey variable is made using the auxiliary variable it may lead to substantial gains in precision of the estimates. This problem is formulated as a Nonlinear Programming Problem (NLPP), which turn out to multistage decision problem and is solved using dynamic programming technique.
Abstract: This paper presents an analytical model to estimate
the cost of an optimized design of reinforced concrete isolated
footing base on structural safety. Flexural and optimized formulas for
square and rectangular footingare derived base on ACI building code
of design, material cost and optimization. The optimization
constraints consist of upper and lower limits of depth and area of
steel. Footing depth and area of reinforcing steel are to be minimized
to yield the optimal footing dimensions. Optimized footing materials
cost of concrete, reinforcing steel and formwork of the designed
sections are computed. Total cost factor TCF and other cost factors
are developed to generalize and simplify the calculations of footing
material cost. Numerical examples are presented to illustrate the
model capability of estimating the material cost of the footing for a
desired axial load.
Abstract: This paper presents a new and efficient approach for
capacitor placement in radial distribution systems that determine
the optimal locations and size of capacitor with an objective of
improving the voltage profile and reduction of power loss. The
solution methodology has two parts: in part one the loss sensitivity
factors are used to select the candidate locations for the capacitor
placement and in part two a new algorithm that employs Plant growth
Simulation Algorithm (PGSA) is used to estimate the optimal size
of capacitors at the optimal buses determined in part one. The main
advantage of the proposed method is that it does not require any
external control parameters. The other advantage is that it handles the
objective function and the constraints separately, avoiding the trouble
to determine the barrier factors. The proposed method is applied to 9
and 34 bus radial distribution systems. The solutions obtained by the
proposed method are compared with other methods. The proposed
method has outperformed the other methods in terms of the quality
of solution.
Abstract: A direct connection between ElectroEncephaloGram
(EEG) and the genetic information of individuals has been
investigated by neurophysiologists and psychiatrists since 1960-s;
and it opens a new research area in the science. This paper focuses on
the person identification based on feature extracted from the EEG
which can show a direct connection between EEG and the genetic
information of subjects. In this work the full EO EEG signal of
healthy individuals are estimated by an autoregressive (AR) model
and the AR parameters are extracted as features. Here for feature
vector constitution, two methods have been proposed; in the first
method the extracted parameters of each channel are used as a
feature vector in the classification step which employs a competitive
neural network and in the second method a combination of different
channel parameters are used as a feature vector. Correct classification
scores at the range of 80% to 100% reveal the potential of our
approach for person classification/identification and are in agreement
to the previous researches showing evidence that the EEG signal
carries genetic information. The novelty of this work is in the
combination of AR parameters and the network type (competitive
network) that we have used. A comparison between the first and the
second approach imply preference of the second one.
Abstract: Topological changes in mobile ad hoc networks
frequently render routing paths unusable. Such recurrent path failures
have detrimental effects on quality of service. A suitable technique
for eliminating this problem is to use multiple backup paths between
the source and the destination in the network. This paper proposes an
effective and efficient protocol for backup and disjoint path set in ad
hoc wireless network. This protocol converges to a highly reliable
path set very fast with no message exchange overhead. The paths
selection according to this algorithm is beneficial for mobile ad hoc
networks, since it produce a set of backup paths with more high
reliability. Simulation experiments are conducted to evaluate the
performance of our algorithm in terms of route numbers in the path
set and its reliability. In order to acquire link reliability estimates, we
use link expiration time (LET) between two nodes.
Abstract: Estimation of stature is an important step in developing a biological profile for human identification. It may provide a valuable indicator for unknown individual in a population. The aim of this study was to analyses the relationship between stature and lower limb dimensions in the Malaysian population. The sample comprised 100 corpses, which included 69 males and 31 females between age ranges of 20 to 90 years old. The parameters measured were stature, thigh length, lower leg length, leg length, foot length, foot height and foot breadth. Results showed that mean values in males were significantly higher than those in females (P < 0.05). There were significant correlations between lower limb dimensions and stature. Cross-validation of the equation on 100 individuals showed close approximation between known stature and estimated stature. It was concluded that lower limb dimensions were useful for estimation of stature, which should be validated in future studies.
Abstract: Semnan is a city in semnan province, northern Iran
with a population estimated at 119,778 inhabitants. It is the
provincial capital of semnan province. Iran is a developing country
and construction is a basic factor of developing too. Hence, Semnan
city needs to a special programming for construction of buildings,
structures and infrastructures. Semnan municipality tries to begin this
program. In addition to, city has some historical monuments which
can be interesting for tourists. Hence, Semnan inhabitants can benefit
from tourist industry. Optimization of Energy in construction
industry is another activity of this municipality and the inhabitants
who execute these regulations receive some discounts. Many parts of
Iran such as semnan are located in highly seismic zones and
structures must be constructed safe e.g., according to recent seismic
codes. In this paper opportunities of IT in construction industry of
Iran are investigated in three categories. Pre-construction phase,
construction phase and earthquake disaster mitigation are studied.
Studies show that information technology can be used in these items
for reducing the losses and increasing the benefits. Both government
and private sectors must contribute to this strategic project for
obtaining the best result.
Abstract: The distribution of macrobenthic polychaetes along
the coastal waters of Penang National Park was surveyed to estimate
the effect of various environmental parameters at three stations
(200m, 600m and 1200m) from the shoreline, during six sampling
months, from June 2010 to April 2011.The use of polychaetes in
descriptive ecology is surveyed in the light of a recent investigation
particularly concerning the soft bottom biota environments.
Polychaetes, often connected in the former to the notion of
opportunistic species able to proliferate after an enhancement in
organic matter, had performed a momentous role particularly with
regard to effected soft-bottom habitats. The objective of this survey
was to investigate different environment stress over soft bottom
polychaete community along Teluk Ketapang and Pantai Acheh
(Penang National Park) over a year period. Variations in the
polychaete community were evaluated using univariate and
multivariate methods. The results of PCA analysis displayed a
positive relation between macrobenthic community structures and
environmental parameters such as sediment particle size and organic
matter in the coastal water. A total of 604 individuals were examined
which was grouped into 23 families. Family Nereidae was the most
abundant (22.68%), followed by Spionidae (22.02%), Hesionidae
(12.58%), Nephtylidae (9.27%) and Orbiniidae (8.61%). It is
noticeable that good results can only be obtained on the basis of good
taxonomic resolution. We proposed that, in monitoring surveys,
operative time could be optimized not only by working at a highertaxonomic
level on the entire macrobenthic data set, but by also
choosing an especially indicative group and working at lower
taxonomic and good level.
Abstract: In this paper, we extend the compound binomial model to the case where the premium income process, based on a binomial process, is no longer a linear function. First, a mathematically recursive formula is derived for non ruin probability, and then, we examine the expected discounted penalty function, satisfy a defect renewal equation. Third, the asymptotic estimate for the expected discounted penalty function is then given. Finally, we give two examples of ruin quantities to illustrate applications of the recursive formula and the asymptotic estimate for penalty function.
Abstract: Newton-Raphson State Estimation method using bus
admittance matrix remains as an efficient and most popular method to
estimate the state variables. Elements of Jacobian matrix are computed
from standard expressions which lack physical significance. In this
paper, elements of the state estimation Jacobian matrix are obtained
considering the power flow measurements in the network elements.
These elements are processed one-by-one and the Jacobian matrix H is
updated suitably in a simple manner. The constructed Jacobian matrix
H is integrated with Weight Least Square method to estimate the state
variables. The suggested procedure is successfully tested on IEEE
standard systems.
Abstract: In this paper, novel statistical sampling based equalization techniques and CNN based detection are proposed to increase the spectral efficiency of multiuser communication systems over fading channels. Multiuser communication combined with selective fading can result in interferences which severely deteriorate the quality of service in wireless data transmission (e.g. CDMA in mobile communication). The paper introduces new equalization methods to combat interferences by minimizing the Bit Error Rate (BER) as a function of the equalizer coefficients. This provides higher performance than the traditional Minimum Mean Square Error equalization. Since the calculation of BER as a function of the equalizer coefficients is of exponential complexity, statistical sampling methods are proposed to approximate the gradient which yields fast equalization and superior performance to the traditional algorithms. Efficient estimation of the gradient is achieved by using stratified sampling and the Li-Silvester bounds. A simple mechanism is derived to identify the dominant samples in real-time, for the sake of efficient estimation. The equalizer weights are adapted recursively by minimizing the estimated BER. The near-optimal performance of the new algorithms is also demonstrated by extensive simulations. The paper has also developed a (Cellular Neural Network) CNN based approach to detection. In this case fast quadratic optimization has been carried out by t, whereas the task of equalizer is to ensure the required template structure (sparseness) for the CNN. The performance of the method has also been analyzed by simulations.
Abstract: In this paper, the vessel inscribed trigonometry (VITM) for the vessel progression orientation (VPO) is proposed in the two-dimensional fundus image. The VPO is a major factor in the optic disc (OD) detection which is a basic process in the retina analysis. To measure the VPO, skeletons of vessel are used. First, the vessels are classified into three classes as vessel end, vessel branch and vessel stem. And the chain code maps of VS are generated. Next, two farthest neighborhoods of each point on VS are searched by the proposed angle restriction. Lastly, a gradient of the straight line between two farthest neighborhoods is estimated to measure the VPO. VITM is validated by comparing with manual results and 2D Gaussian templates. It is confirmed that VPO of the proposed mensuration is correct enough to detect OD from the results of experiment which applied VITM to detect OD in fundus images.
Abstract: In this paper, we propose improved versions of DVHop
algorithm as QDV-Hop algorithm and UDV-Hop algorithm for
better localization without the need for additional range measurement
hardware. The proposed algorithm focuses on third step of DV-Hop,
first error terms from estimated distances between unknown node and
anchor nodes is separated and then minimized. In the QDV-Hop
algorithm, quadratic programming is used to minimize the error to
obtain better localization. However, quadratic programming requires
a special optimization tool box that increases computational
complexity. On the other hand, UDV-Hop algorithm achieves
localization accuracy similar to that of QDV-Hop by solving
unconstrained optimization problem that results in solving a system
of linear equations without much increase in computational
complexity. Simulation results show that the performance of our
proposed schemes (QDV-Hop and UDV-Hop) is superior to DV-Hop
and DV-Hop based algorithms in all considered scenarios.
Abstract: The performance of sensor-less controlled induction
motor drive depends on the accuracy of the estimated speed.
Conventional estimation techniques being mathematically complex
require more execution time resulting in poor dynamic response. The
nonlinear mapping capability and powerful learning algorithms of
neural network provides a promising alternative for on-line speed
estimation. The on-line speed estimator requires the NN model to be
accurate, simpler in design, structurally compact and computationally
less complex to ensure faster execution and effective control in real
time implementation. This in turn to a large extent depends on the
type of Neural Architecture. This paper investigates three types of
neural architectures for on-line speed estimation and their
performance is compared in terms of accuracy, structural
compactness, computational complexity and execution time. The
suitable neural architecture for on-line speed estimation is identified
and the promising results obtained are presented.
Abstract: Fractal analyses of successive event of explosion
earthquake and harmonic tremor recorded at Semeru volcano were
carried out to investigate the dynamical system regarding to their
generating mechanism. The explosive eruptions accompanied by
explosion earthquakes and following volcanic tremor which are
generated by continuous emission of volcanic ash. The fractal
dimension of successive event of explosion and harmonic tremor was
estimated by Critical Exponent Method (CEM). It was found that the
method yield a higher fractal dimension of explosion earthquakes and
gradually decrease during the occurrence of harmonic tremor, and can
be considerably as correlated complexity of the source mechanism
from the variance of fractal dimension.
Abstract: Monitoring and control of cane sugar crystallization
processes depend on the stability of the supersaturation (σ ) state.
The most widely used information to represent σ is the electrical
conductivity κ of the solutions. Nevertheless, previous studies point
out the shortcomings of this approach: κ may be regarded as
inappropriate to guarantee an accurate estimation of σ in impure
solutions. To improve the process control efficiency, additional
information is necessary. The mass of crystals in the solution ( c m )
and the solubility (mass ratio of sugar to water / s w m m ) are relevant
to complete information. Indeed, c m inherently contains information
about the mass balance and / s w m m contains information about the
supersaturation state of the solution. The main problem is that c m
and / s w m m are not available on-line. In this paper, a model based
soft-sensor is presented for a final crystallization stage (C sugar).
Simulation results obtained on industrial data show the reliability of
this approach, c m and the crystal content ( cc ) being estimated with
a sufficient accuracy for achieving on-line monitoring in industry
Abstract: Knowledge is the foundation for growth and development. Investment in knowledge improves new method for originate knowledge society and knowledge economy. Investment in knowledge embraces expenditure on education and R&D and software. Measuring of investment in knowledge is characteristically complicated. We examine the influence of investment in knowledge in multifactor productivity growth and numbers of patent. We analyze the annual growth of investment in knowledge and we estimate portion of each country intended for produce total investment in knowledge on the whole OECD. We determine the relative efficiency of average patent numbers with average investment in knowledge and we compare GDP growth rates and growth of knowledge investment. The main purpose in this paper is to study to evaluate different aspect, influence and output of investment in knowledge in OECD countries.
Abstract: The objective of this study was to determine the accuracy to estimation fetal weight by Johnson-s method and compares it with actual birth weight. The sample group was 126 infants delivered in Dan KhunThot hospital from January March 2012. Fetal weight was estimated by measuring fundal height according to Johnson-s method. The information was collected by studying historical delivery records and then analyzed by using the statistics of frequency, percentage, mean, and standard deviation. Finally, the difference was analyzed by a paired t-test.The results showed had an average birth weight was 3093.57 ± 391.03 g (mean ± SD) and 3,455 ± 454.55 g average estimated fetal weight by Johnson-s method higher than average actual birth weight was 384.09 grams. When classifying the infants according to birth weight found that low birth weight ( 4000 g) actual birth weight was more than estimated fetal weight. The difference was found between actual birth weight and estimation fetal weight of the minimum weight in high birth weight ( > 4000 g) , the appropriate birth weight (2500-3999g) and low birth weight (
Abstract: This paper presents a study of laminar to turbulent transition on a profile specifically designed for wind turbine blades, the DU91-W2-250, which belongs to a class of wind turbine dedicated airfoils, developed by Delft University of Technology. A comparison between the experimental behavior of the airfoil studied at Delft wind tunnel and the numerical predictions of the commercial CFD solver ANSYS FLUENT® has been performed. The prediction capabilities of the Spalart-Allmaras turbulence model and of the γ-θ Transitional model have been tested. A sensitivity analysis of the numerical results to the spatial domain discretization has also been performed using four different computational grids, which have been created using the mesher GAMBIT®. The comparison between experimental measurements and CFD results have allowed to determine the importance of the numerical prediction of the laminar to turbulent transition, in order not to overestimate airfoil friction drag due to a fully turbulent-regime flow computation.