Abstract: Emerging adulthood, between the ages of 18 and 25, as a distinct developmental stage extending from adolescence to young adulthood. The proportions composing the five-factor model are neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness. In the literature, there is any study which includes the relationship between emerging adults loneliness and personality traits. Therefore, the relationship between emerging adults loneliness and personality traits have to be investigated. This study examines the association between the Big Five personality traits, and loneliness among Turkish emerging adults. A total of 220 emerging adults completed the NEO Five Factor Inventory (NEO-FFI), and the The UCLA Loneliness Scale (UCLALS). Correlation analysis showed that three Big Five personality dimensions which are Neuroticism (positively), and Extraversion and Aggreableness (negatively) are moderately correlated with emerging adults loneliness. Regression analysis shows that Extraversion, Aggreableness and Neuroticism are the most important predictors of emerging adults loneliness. Results can be discussed in the context of emerging adulthood theory.
Abstract: The finite-difference time-domain (FDTD) method is
one of the most widely used computational methods in
electromagnetic. This paper describes the design of two-dimensional
(2D) FDTD simulation software for transverse magnetic (TM)
polarization using Berenger's split-field perfectly matched layer
(PML) formulation. The software is developed using Matlab
programming language. Numerical examples validate the software.
Abstract: Because of the reservoir effect, dynamic analysis of concrete dams is more involved than other common structures. This problem is mostly sourced by the differences between reservoir water, dam body and foundation material behaviors. To account for the reservoir effect in dynamic analysis of concrete gravity dams, two methods are generally employed. Eulerian method in reservoir modeling gives rise to a set of coupled equations, whereas in Lagrangian method, the same equations for dam and foundation structure are used. The Purpose of this paper is to evaluate and study possible advantages and disadvantages of both methods. Specifically, application of the above methods in the analysis of dam-foundationreservoir systems is leveraged to calculate the hydrodynamic pressure on dam faces. Within the frame work of dam- foundationreservoir systems, dam displacement under earthquake for various dimensions and characteristics are also studied. The results of both Lagrangian and Eulerian methods in effects of loading frequency, boundary condition and foundation elasticity modulus are quantitatively evaluated and compared. Our analyses show that each method has individual advantages and disadvantages. As such, in any particular case, one of the two methods may prove more suitable as presented in the results section of this study.
Abstract: Chemical reaction and diffusion are important phenomena in quantitative neurobiology and biophysics. The knowledge of the dynamics of calcium Ca2+ is very important in cellular physiology because Ca2+ binds to many proteins and regulates their activity and interactions Calcium waves propagate inside cells due to a regenerative mechanism known as calcium-induced calcium release. Buffer-mediated calcium diffusion in the cytosol plays a crucial role in the process. A mathematical model has been developed for calcium waves by assuming the buffers are in equilibrium with calcium i.e., the rapid buffering approximation for a one dimensional unsteady state case. This model incorporates important physical and physiological parameters like dissociation rate, diffusion rate, total buffer concentration and influx. The finite difference method has been employed to predict [Ca2+] and buffer concentration time course regardless of the calcium influx. The comparative studies of the effect of the rapid buffered diffusion and kinetic parameters of the model on the concentration time course have been performed.
Abstract: Square pipes (pipes with square cross sections) are
being used for various industrial objectives, such as machine
structure components and housing/building elements. The utilization
of them is extending rapidly and widely. Hence, the out-put of those
pipes is increasing and new application fields are continually
developing.
Due to various demands in recent time, the products have to
satisfy difficult specifications with high accuracy in dimensions. The
reshaping process design of pipes with square cross sections;
however, is performed by trial and error and based on expert-s
experience.
In this paper, a computer-aided simulation is developed based on
the 2-D elastic-plastic method with consideration of the shear
deformation to analyze the reshaping process. Effect of various
parameters such as diameter of the circular pipe and mechanical
properties of metal on product dimension and quality can be
evaluated by using this simulation. Moreover, design of reshaping
process include determination of shrinkage of cross section,
necessary number of stands, radius of rolls and height of pipe at each
stand, are investigated. Further, it is shown that there are good
agreements between the results of the design method and the
experimental results.
Abstract: The objective of this research is to develop the
performance indicators (PIs) in operational level for the Pre-hospital Emergency Medical Service (EMS) system employing in Thailand. This research started with ascertaining the current pre-hospital care
system. The team analyzed the strategies of Narerthorn, a government unit under the ministry of public health, and the existing PIs of the pre-hospital care. Afterwards, the current National Strategic Plan of EMS development (2008-2012) of the Emergency
Medical Institute of Thailand (EMIT) was considered using strategic
analysis to developed Strategy Map (SM) and identified the Success
Factors (SFs). The analysis results from strategy map and SFs were used to develop the Performance Indicators (PIs). To verify the set of
PIs, the team has interviewed with the relevant practitioners for the possibilities to implement the PIs. To this paper, it was to ascertain
that all the developed PIs support the objectives of the strategic plan. Nevertheless, the results showed that the operational level PIs suited
only with the first dimension of National Strategic Plan
(infrastructure and information technology development). Besides,
the SF was the infrastructure development (to contribute the EMS system to people throughout with standard and efficiency both in normally and disaster conditions). Finally, twenty-nine indicators
were developed from the analysis results of SM and SFs.
Abstract: The objective of this paper is to study the electrical
resistivity complexity between field and laboratory measurement, in
order to improve the effectiveness of data interpretation for
geophysical ground resistivity survey. The geological outcrop in
Penang, Malaysia with an obvious layering contact was chosen as the
study site. Two dimensional geoelectrical resistivity imaging were
used in this study to maps the resistivity distribution of subsurface,
whereas few subsurface sample were obtained for laboratory
advance. In this study, resistivity of samples in original conditions is
measured in laboratory by using time domain low-voltage technique,
particularly for granite core sample and soil resistivity measuring set
for soil sample. The experimentation results from both schemes are
studied, analyzed, calibrated and verified, including basis and
correlation, degree of tolerance and characteristics of substance.
Consequently, the significant different between both schemes is
explained comprehensively within this paper.
Abstract: Blood pulse is an important human physiological signal commonly used for the understanding of the individual physical health. Current methods of non-invasive blood pulse sensing require direct contact or access to the human skin. As such, the performances of these devices tend to vary with time and are subjective to human body fluids (e.g. blood, perspiration and skin-oil) and environmental contaminants (e.g. mud, water, etc). This paper proposes a simulation model for the novel method of non-invasive acquisition of blood pulse using the disturbance created by blood flowing through a localized magnetic field. The simulation model geometry represents a blood vessel, a permanent magnet, a magnetic sensor, surrounding tissues and air in 2-dimensional. In this model, the velocity and pressure fields in the blood stream are described based on Navier-Stroke equations and the walls of the blood vessel are assumed to have no-slip condition. The blood assumes a parabolic profile considering a laminar flow for blood in major artery near the skin. And the inlet velocity follows a sinusoidal equation. This will allow the computational software to compute the interactions between the magnetic vector potential generated by the permanent magnet and the magnetic nanoparticles in the blood. These interactions are simulated based on Maxwell equations at the location where the magnetic sensor is placed. The simulated magnetic field at the sensor location is found to assume similar sinusoidal waveform characteristics as the inlet velocity of the blood. The amplitude of the simulated waveforms at the sensor location are compared with physical measurements on human subjects and found to be highly correlated.
Abstract: Statistical learning theory was developed by Vapnik. It
is a learning theory based on Vapnik-Chervonenkis dimension. It also
has been used in learning models as good analytical tools. In general, a
learning theory has had several problems. Some of them are local
optima and over-fitting problems. As well, statistical learning theory
has same problems because the kernel type, kernel parameters, and
regularization constant C are determined subjectively by the art of
researchers. So, we propose an evolutionary statistical learning theory
to settle the problems of original statistical learning theory.
Combining evolutionary computing into statistical learning theory,
our theory is constructed. We verify improved performances of an
evolutionary statistical learning theory using data sets from KDD cup.
Abstract: Nanocrystals (NC) alloyed composite CdSxSe1-x(x=0
to 1) have been prepared using the chemical solution deposition
technique. The energy band gap of these alloyed nanocrystals of
approximately the same size, have been determined by scanning
tunneling spectroscopy (STS) technique at room temperature. The
values of the energy band gap obtained directly using STS are
compared to those measured by optical spectroscopy. Increasing the
molar fraction ratio x from 0 to 1 causes clearly observed increase in
the band gap of the alloyed composite nanocrystal. Vegard-s law was
applied to calculate the parameters of the effective mass
approximation (EMA) model and the dimension obtained were
compared to the values measured by STM. The good agreement of
the calculated and measured values is a direct result of applying
Vegard's law in the nanocomposites.
Abstract: This paper present the implementation of a new ordering strategy on Successive Overrelaxation scheme on two dimensional boundary value problems. The strategy involve two directions alternatingly; from top and bottom of the solution domain. The method shows to significantly reduce the iteration number to converge. Four numerical experiments were carried out to examine the performance of the new strategy.
Abstract: Multi-dimensional principal component analysis
(PCA) is the extension of the PCA, which is used widely as the
dimensionality reduction technique in multivariate data analysis, to
handle multi-dimensional data. To calculate the PCA the singular
value decomposition (SVD) is commonly employed by the reason of
its numerical stability. The multi-dimensional PCA can be calculated
by using the higher-order SVD (HOSVD), which is proposed by
Lathauwer et al., similarly with the case of ordinary PCA. In this
paper, we apply the multi-dimensional PCA to the multi-dimensional
medical data including the functional independence measure (FIM)
score, and describe the results of experimental analysis.
Abstract: Several works regarding facial recognition have dealt with methods which identify isolated characteristics of the face or with templates which encompass several regions of it. In this paper a new technique which approaches the problem holistically dispensing with the need to identify geometrical characteristics or regions of the face is introduced. The characterization of a face is achieved by randomly sampling selected attributes of the pixels of its image. From this information we construct a set of data, which correspond to the values of low frequencies, gradient, entropy and another several characteristics of pixel of the image. Generating a set of “p" variables. The multivariate data set with different polynomials minimizing the data fitness error in the minimax sense (L∞ - Norm) is approximated. With the use of a Genetic Algorithm (GA) it is able to circumvent the problem of dimensionality inherent to higher degree polynomial approximations. The GA yields the degree and values of a set of coefficients of the polynomials approximating of the image of a face. By finding a family of characteristic polynomials from several variables (pixel characteristics) for each face (say Fi ) in the data base through a resampling process the system in use, is trained. A face (say F ) is recognized by finding its characteristic polynomials and using an AdaBoost Classifier from F -s polynomials to each of the Fi -s polynomials. The winner is the polynomial family closer to F -s corresponding to target face in data base.
Abstract: Modeling transfer phenomena in several chemical
engineering operations leads to the resolution of partial differential
equations systems. According to the complexity of the operations
mechanisms, the equations present a nonlinear form and analytical
solution became difficult, we have then to use numerical methods
which are based on approximations in order to transform a
differential system to an algebraic one.Finite element method is one
of numerical methods which can be used to obtain an accurate
solution in many complex cases of chemical engineering.The packed
columns find a large application like contactor for liquid-liquid
systems such solvent extraction. In the literature, the modeling of this
type of equipment received less attention in comparison with the
plate columns.A mathematical bidimensionnal model with radial and
axial dispersion, simulating packed tower extraction behavior was
developed and a partial differential equation was solved using the
finite element method by adopting the Galerkine model. We
developed a Mathcad program, which can be used for a similar
equations and concentration profiles are obtained along the column.
The influence of radial dispersion was prooved and it can-t be
neglected, the results were compared with experimental concentration
at the top of the column in the extraction system:
acetone/toluene/water.
Abstract: Faults in a network may take various forms such as hardware/software errors, vertex/edge faults, etc. Folded hypercube is a well-known variation of the hypercube structure and can be constructed from a hypercube by adding a link to every pair of nodes with complementary addresses. Let FFv (respectively, FFe) be the set of faulty nodes (respectively, faulty links) in an n-dimensional folded hypercube FQn. Hsieh et al. have shown that FQn - FFv - FFe for n ≥ 3 contains a fault-free cycle of length at least 2n -2|FFv|, under the constraints that (1) |FFv| + |FFe| ≤ 2n - 4 and (2) every node in FQn is incident to at least two fault-free links. In this paper, we further consider the constraints |FFv| + |FFe| ≤ 2n - 3. We prove that FQn - FFv - FFe for n ≥ 5 still has a fault-free cycle of length at least 2n - 2|FFv|, under the constraints : (1) |FFv| + |FFe| ≤ 2n - 3, (2) |FFe| ≥ n + 2, and (3) every vertex is still incident with at least two links.
Abstract: We report on a high-speed quantum cryptography
system that utilizes simultaneous entanglement in polarization and in
“time-bins". With multiple degrees of freedom contributing to the
secret key, we can achieve over ten bits of random entropy per detected coincidence. In addition, we collect from multiple spots o
the downconversion cone to further amplify the data rate, allowing usto achieve over 10 Mbits of secure key per second.
Abstract: Optimization is often a critical issue for most system
design problems. Evolutionary Algorithms are population-based,
stochastic search techniques, widely used as efficient global
optimizers. However, finding optimal solution to complex high
dimensional, multimodal problems often require highly
computationally expensive function evaluations and hence are
practically prohibitive. The Dynamic Approximate Fitness based
Hybrid EA (DAFHEA) model presented in our earlier work [14]
reduced computation time by controlled use of meta-models to
partially replace the actual function evaluation by approximate
function evaluation. However, the underlying assumption in
DAFHEA is that the training samples for the meta-model are
generated from a single uniform model. Situations like model
formation involving variable input dimensions and noisy data
certainly can not be covered by this assumption. In this paper we
present an enhanced version of DAFHEA that incorporates a
multiple-model based learning approach for the SVM approximator.
DAFHEA-II (the enhanced version of the DAFHEA framework) also
overcomes the high computational expense involved with additional
clustering requirements of the original DAFHEA framework. The
proposed framework has been tested on several benchmark functions
and the empirical results illustrate the advantages of the proposed
technique.
Abstract: In this paper we introduce an efficient solution
method for the Eigen-decomposition of bisymmetric and per
symmetric matrices of symmetric structures. Here we decompose
adjacency and Laplacian matrices of symmetric structures to submatrices
with low dimension for fast and easy calculation of
eigenvalues and eigenvectors. Examples are included to show the
efficiency of the method.
Abstract: The solitary wave solution of the quadratic nonlinear Schrdinger equation is determined by the iterative method called Petviashvili method. This solution is also used for the initial condition for the time evolution to study the stability analysis. The spectral method is applied for the time evolution.
Abstract: Three-dimensional reconstruction of small objects has
been one of the most challenging problems over the last decade.
Computer graphics researchers and photography professionals have
been working on improving 3D reconstruction algorithms to fit the
high demands of various real life applications. Medical sciences,
animation industry, virtual reality, pattern recognition, tourism
industry, and reverse engineering are common fields where 3D
reconstruction of objects plays a vital role. Both lack of accuracy and
high computational cost are the major challenges facing successful
3D reconstruction. Fringe projection has emerged as a promising 3D
reconstruction direction that combines low computational cost to both
high precision and high resolution. It employs digital projection,
structured light systems and phase analysis on fringed pictures.
Research studies have shown that the system has acceptable
performance, and moreover it is insensitive to ambient light.
This paper presents an overview of fringe projection approaches. It
also presents an experimental study and implementation of a simple
fringe projection system. We tested our system using two objects
with different materials and levels of details. Experimental results
have shown that, while our system is simple, it produces acceptable
results.