Abstract: In this paper, we were introduces a skin detection
method using a histogram approximation based on the mean shift
algorithm. The proposed method applies the mean shift procedure to a
histogram of a skin map of the input image, generated by comparison
with standard skin colors in the CbCr color space, and divides the
background from the skin region by selecting the maximum value
according to brightness level. The proposed method detects the skin
region using the mean shift procedure to determine a maximum value
that becomes the dividing point, rather than using a manually selected
threshold value, as in existing techniques. Even when skin color is
contaminated by illumination, the procedure can accurately segment
the skin region and the background region. The proposed method may
be useful in detecting facial regions as a pretreatment for face
recognition in various types of illumination.
Abstract: Sleep spindles are the most interesting hallmark of
stage 2 sleep EEG. Their accurate identification in a
polysomnographic signal is essential for sleep professionals to help
them mark Stage 2 sleep. Sleep Spindles are also promising objective
indicators for neurodegenerative disorders. Visual spindle scoring
however is a tedious workload. In this paper three different
approaches are used for the automatic detection of sleep spindles:
Short Time Fourier Transform, Wavelet Transform and Wave
Morphology for Spindle Detection. In order to improve the results, a
combination of the three detectors is presented and comparison with
human expert scorers is performed. The best performance is obtained
with a combination of the three algorithms which resulted in a
sensitivity and specificity of 94% when compared to human expert
scorers.
Abstract: Microtomographic images and thin section (TS)
images were analyzed and compared against some parameters of
geological interest such as porosity and its distribution along the
samples. The results show that microtomography ( CT) analysis,
although limited by its resolution, have some interesting information
about the distribution of porosity (homogeneous or not) and can also
quantify the connected and non-connected pores, i.e., total porosity.
TS have no limitations concerning resolution, but are limited by the
experimental data available in regards to a few glass sheets for
analysis and also can give only information about the connected
pores, i.e., effective porosity. Those two methods have their own
virtues and flaws but when paired together they are able to
complement one another, making for a more reliable and complete
analysis.
Abstract: Thirty three re-wetting tests were conducted at
different combinations of temperatures (5.7- 46.30C) and relative
humidites (48.2-88.6%) with barley. Two most commonly used thinlayer
drying and rewetting models i.e. Page and Diffusion were
compared for their ability to the fit the experimental re-wetting data
based on the standard error of estimate (SEE) of the measured and
simulated moisture contents. The comparison shows both the Page
and Diffusion models fit the re-wetting experimental data of barley
well. The average SEE values for the Page and Diffusion models
were 0.176 % d.b. and 0.199 % d.b., respectively. The Page and
Diffusion models were found to be most suitable equations, to
describe the thin-layer re-wetting characteristics of barley over a
typically five day re-wetting. These two models can be used for the
simulation of deep-bed re-wetting of barley occurring during
ventilated storage and deep bed drying.
Abstract: Recently, Genetic Algorithms (GA) and Differential
Evolution (DE) algorithm technique have attracted considerable
attention among various modern heuristic optimization techniques.
Since the two approaches are supposed to find a solution to a given
objective function but employ different strategies and computational
effort, it is appropriate to compare their performance. This paper
presents the application and performance comparison of DE and GA
optimization techniques, for flexible ac transmission system
(FACTS)-based controller design. The design objective is to enhance
the power system stability. The design problem of the FACTS-based
controller is formulated as an optimization problem and both the PSO
and GA optimization techniques are employed to search for optimal
controller parameters. The performance of both optimization
techniques has been compared. Further, the optimized controllers are
tested on a weekly connected power system subjected to different
disturbances, and their performance is compared with the
conventional power system stabilizer (CPSS). The eigenvalue
analysis and non-linear simulation results are presented and
compared to show the effectiveness of both the techniques in
designing a FACTS-based controller, to enhance power system
stability.
Abstract: Environmental performance of the U.S. States is investigated for the period of 1990 – 2007 using Stochastic Frontier Analysis (SFA). The SFA accounts for both efficiency measure and stochastic noise affecting a frontier. The frontier is formed using indicators of GDP, energy consumption, population, and CO2 emissions. For comparability, all indicators are expressed as ratios to total. Statistical information of the Energy Information Agency of the United States is used. Obtained results reveal the bell - shaped dynamics of environmental efficiency scores. The average efficiency scores rise from 97.6% in 1990 to 99.6% in 1999, and then fall to 98.4% in 2007. The main factor is insufficient decrease in the rate of growth of CO2 emissions with regards to the growth of GDP, population and energy consumption. Data for 2008 following the research period allow for an assumption that the environmental performance of the U.S. States has improved in the last years.
Abstract: Energy intensity(energy consumption intensity) is a
global index which computes the required energy for producing a
specific value of goods and services in each country. It is computed
in terms of initial energy supply or final energy consumption. In this
study (research) Divisia method is used to decompose energy
consumption and energy intensity. This method decomposes
consumption and energy intensity to production effects, structural
and net intensity and could be done as time series or two-periodical.
This study analytically investigates consumption changes and energy
intensity on economical sectors of Iran and more specific on road
transportation(rail road and road).Our results show that the
contribution of structural effect (change in economical activities
combination) is very low and the effect of net energy consumption
has the higher contribution in consumption changes and energy
intensity. In other words, the high consumption of energy is due to
Intensity of energy consumption and is not to structural effect of
transportation sector.
Abstract: A self-evolution algorithm for optimizing neural networks using a combination of PSO and JPSO is proposed. The algorithm optimizes both the network topology and parameters simultaneously with the aim of achieving desired accuracy with less complicated networks. The performance of the proposed approach is compared with conventional back-propagation networks using several synthetic functions, with better results in the case of the former. The proposed algorithm is also implemented on slope stability problem to estimate the critical factor of safety. Based on the results obtained, the proposed self evolving network produced a better estimate of critical safety factor in comparison to conventional BPN network.
Abstract: Modern applications realized onto FPGAs exhibit high connectivity demands. Throughout this paper we study the routing constraints of Virtex devices and we propose a systematic methodology for designing a novel general-purpose interconnection network targeting to reconfigurable architectures. This network consists of multiple segment wires and SB patterns, appropriately selected and assigned across the device. The goal of our proposed methodology is to maximize the hardware utilization of fabricated routing resources. The derived interconnection scheme is integrated on a Virtex style FPGA. This device is characterized both for its high-performance, as well as for its low-energy requirements. Due to this, the design criterion that guides our architecture selections was the minimal Energy×Delay Product (EDP). The methodology is fully-supported by three new software tools, which belong to MEANDER Design Framework. Using a typical set of MCNC benchmarks, extensive comparison study in terms of several critical parameters proves the effectiveness of the derived interconnection network. More specifically, we achieve average Energy×Delay Product reduction by 63%, performance increase by 26%, reduction in leakage power by 21%, reduction in total energy consumption by 11%, at the expense of increase of channel width by 20%.
Abstract: The necessity of solving multi dimensional
complicated scientific problems beside the necessity of several
objective functions optimization are the most motive reason of born
of artificial intelligence and heuristic methods.
In this paper, we introduce a new method for multiobjective
optimization based on learning automata. In the proposed method,
search space divides into separate hyper-cubes and each cube is
considered as an action. After gathering of all objective functions
with separate weights, the cumulative function is considered as the
fitness function. By the application of all the cubes to the cumulative
function, we calculate the amount of amplification of each action and
the algorithm continues its way to find the best solutions. In this
Method, a lateral memory is used to gather the significant points of
each iteration of the algorithm. Finally, by considering the
domination factor, pareto front is estimated. Results of several
experiments show the effectiveness of this method in comparison
with genetic algorithm based method.
Abstract: The effect of wood vinegar, entomopathogenic
nematodes ((Steinernema thailandensis n. sp.) and fermented organic
substances from four plants such as: Derris elliptica Roxb, Stemona
tuberosa Lour, Tinospora crispa Mier and Azadirachta indica J. were
tested on the five varieties of sweetpotato with potential for
bioethanol production ie. Taiwan, China, PROC No.65-16, Phichit
166-5, and Phichit 129-6. The experimental plots were located at
Faculty of Agriculture, Natural Resources and Environment,
Naresuan University, Phitsanulok, Thailand. The aim of this study
was to compare the efficiency of the five treatments for growth, yield
and insect infestation on the five varieties of sweetpotato. Treatment
with entomopathogenic nematodes gave the highest average weight
of sweetpotato tubers (1.3 kg/tuber), followed by wood vinegar,
fermented organic substances and mixed treatment with yields of
0.88, 0.46 and 0.43 kg/tuber, respectively. Also the
entomopathogenic nematode treatment gave significantly higher
average width and length of sweet potato (9.82 cm and 9.45 cm,
respectively). Additionally, the entomopathogenic nematode
provided the best control of insect infestation on sweetpotato leaves
and tubers. Comparison among the varieties of sweetpotato, PROC
NO.65-16 showed the highest weight and length. However, Phichit
129-6 gave significantly higher weight of 0.94 kg/tuber. Lastly, the
lowest sweet potato weevil infestation on leaves and tubers occurred
on Taiwan and Phichit 129-6.
Abstract: An Artificial Neural Network based modeling
technique has been used to study the influence of different
combinations of meteorological parameters on evaporation from a
reservoir. The data set used is taken from an earlier reported study.
Several input combination were tried so as to find out the importance
of different input parameters in predicting the evaporation. The
prediction accuracy of Artificial Neural Network has also been
compared with the accuracy of linear regression for predicting
evaporation. The comparison demonstrated superior performance of
Artificial Neural Network over linear regression approach. The
findings of the study also revealed the requirement of all input
parameters considered together, instead of individual parameters
taken one at a time as reported in earlier studies, in predicting the
evaporation. The highest correlation coefficient (0.960) along with
lowest root mean square error (0.865) was obtained with the input
combination of air temperature, wind speed, sunshine hours and
mean relative humidity. A graph between the actual and predicted
values of evaporation suggests that most of the values lie within a
scatter of ±15% with all input parameters. The findings of this study
suggest the usefulness of ANN technique in predicting the
evaporation losses from reservoirs.
Abstract: In digital signal processing it is important to
approximate multi-dimensional data by the method called rank
reduction, in which we reduce the rank of multi-dimensional data from
higher to lower. For 2-dimennsional data, singular value
decomposition (SVD) is one of the most known rank reduction
techniques. Additional, outer product expansion expanded from SVD
was proposed and implemented for multi-dimensional data, which has
been widely applied to image processing and pattern recognition.
However, the multi-dimensional outer product expansion has behavior
of great computation complex and has not orthogonally between the
expansion terms. Therefore we have proposed an alterative method,
Third-order Orthogonal Tensor Product Expansion short for 3-OTPE.
3-OTPE uses the power method instead of nonlinear optimization
method for decreasing at computing time. At the same time the group
of B. D. Lathauwer proposed Higher-Order SVD (HOSVD) that is
also developed with SVD extensions for multi-dimensional data.
3-OTPE and HOSVD are similarly on the rank reduction of
multi-dimensional data. Using these two methods we can obtain
computation results respectively, some ones are the same while some
ones are slight different. In this paper, we compare 3-OTPE to
HOSVD in accuracy of calculation and computing time of resolution,
and clarify the difference between these two methods.
Abstract: This work presents the highly accurate numerical calculation
of the natural frequencies for functionally graded beams with
simply supported boundary conditions. The Timoshenko first order
shear deformation beam theory and the higher order shear deformation
beam theory of Reddy have been applied to the functionally
graded beams analysis. The material property gradient is assumed
to be in the thickness direction. The Hamilton-s principle is utilized
to obtain the dynamic equations of functionally graded beams. The
influences of the volume fraction index and thickness-to-length ratio
on the fundamental frequencies are discussed. Comparison of the
numerical results for the homogeneous beam with Euler-Bernoulli
beam theory results show that the derived model is satisfactory.
Abstract: Prestressing in structure increases ratio of load-bearing capacity to weight. Suspendomes are single-layer braced domes reinforced with cable and strut. Prestressing of cables alter value and distribution of stress in structure. In this study two configuration, diamatic and lamella domes is selected. Investigated domes have span of 100m with rise-to-span ratios of 0.1, 0.2, and 0.3. Single layer domes loaded under service load combinations according to ISO code. After geometric nonlinear analysis, models are designed with tubular and I-shaped sections then reinforced with cable and strut and converted to suspendomes. Displacements and stresses of some groups of nodes and elements in all of single-layer domes and suspendomes for three load combinations, symmetric snow, asymmetric snow and wind are compared. Variation due to suspending system is investigated. Suspendomes are redesigned and minimum possible weight after addition of cable and strut is obtained.
Abstract: In this work the numerical simulation of transient heat
transfer in a cylindrical probe is done. An experiment was conducted
introducing a steel cylinder in a heating chamber and registering its
surface temperature along the time during one hour. In parallel, a
mathematical model was solved for one dimension transient heat
transfer in cylindrical coordinates, considering the boundary
conditions of the test. The model was solved using finite difference
method, because the thermal conductivity in the cylindrical steel bar
and the convection heat transfer coefficient used in the model are
considered temperature dependant functions, and both conditions
prevent the use of the analytical solution. The comparison between
theoretical and experimental results showed the average deviation is
below 2%. It was concluded that numerical methods are useful in
order to solve engineering complex problems. For constant k and h,
the experimental methodology used here can be used as a tool for
teaching heat transfer in mechanical engineering, using mathematical
simplified models with analytical solutions.
Abstract: This paper discusses coordinated reactive power -
voltage (Q-V) control in a multi machine steam power plant. The
drawbacks of manual Q-V control are briefly listed, and the design
requirements for coordinated Q-V controller are specified.
Theoretical background and mathematical model of the new
controller are presented next followed by validation of developed
Matlab/Simulink model through comparison with recorded
responses in real steam power plant and description of practical
realisation of the controller. Finally, the performance of
commissioned controller is illustrated on several examples of
coordinated Q-V control in real steam power plant and compared
with manual control.
Abstract: Many recent electrophysiological studies have
revealed the importance of investigating meditation state in order to
achieve an increased understanding of autonomous control of
cardiovascular functions. In this paper, we characterize heart rate
variability (HRV) time series acquired during meditation using
nonlinear dynamical parameters. We have computed minimum
embedding dimension (MED), correlation dimension (CD), largest
Lyapunov exponent (LLE), and nonlinearity scores (NLS) from HRV
time series of eight Chi and four Kundalini meditation practitioners.
The pre-meditation state has been used as a baseline (control) state to
compare the estimated parameters. The chaotic nature of HRV during
both pre-meditation and meditation is confirmed by MED. The
meditation state showed a significant decrease in the value of CD and
increase in the value of LLE of HRV, in comparison with premeditation
state, indicating a less complex and less predictable nature
of HRV. In addition, it was shown that the HRV of meditation state
is having highest NLS than pre-meditation state. The study indicated
highly nonlinear dynamic nature of cardiac states as revealed by
HRV during meditation state, rather considering it as a quiescent
state.
Abstract: Arrack is one of the forms of alcoholic beverage or
liquor which is produced from palm or date juice and commonly
consumed by the lower social class of all religious/ethnic
communities in the north-western villages of Bangladesh. The
purpose of the study was to compare arrack drinking patterns
associated with socio-demographic status among the Muslim, Hindu,
Santal, and Oraon communities in the Rasulpur union of Bangladesh.
A total of 391 respondents (Muslim n-109, Hindu n-103, Santal n-89,
Oraon n-90) selected by cluster random sampling were interviewed
by ADP (Arrack Drinking Pattern) questionnaire. The results of
Pearson Chi-Squire test revealed that arrack drinking patterns were
significantly differed among the Muslim, Hindu, Santal, and Oraon
communities- drinkers. In addition, the results of Spearman-s
bivariate correlation coefficients also revealed that sociodemographic
characteristics of the communities- drinkers were the
significantly positive and negative associations with the arrack
drinking patterns in the Rasulpur union, Bangladesh. The study
suggests that further cross-cultural researches should be conducted
on the consequences of arrack drinking patterns on the communities-
drinkers.
Abstract: The purpose of this study is to review representative
cases of green space development in order to compare the Garden City
concept and Green Belt concept as applied and to examine its direction
in major Asian and Oceanic cities. The results of previous studies and
this study show that there are two major directions in such
green-oriented city planning. One direction is toward Multi-Regional
Development, and the other focuses on an Environmentally Symbiotic
City based on the Garden City concept. In large cities and the suburbs
where extremely strong pressure to urbanize makes it impossible to
keep Green Belts, it is essential to strictly control land use and adopt
the Garden City concept to conserve the urban environment.