Abstract: One problem of synthetic sunflower cultivation is an
erratic germination of the seeds. To improve the germination, presowing
seed treatment with an ultrasound was tested. All treatments
were carried out at 40 kHz frequency with the intensities of 40, 60,
80 and 100% of the ultrasonic generator total power (250 W) for the
durations of 5, 10, 15 and 20 minutes. Data on seed germination
percentage, seed vigor index (SVI), root and shoot lengths of
seedlings were collected. The results showed that germination, SVI,
root and shoot lengths of ultrasonic treated seedlings were different
from the control, depending on intensity of the ultrasound. The
effects of ultrasonic treatment were significant on germination,
resulting in a maximum increase of 43% at 40 and 60% intensities
compared to that of the control seeds. In addition, seedlings of these 2
treatments had higher SVI and longer root and shoot lengths than that
of the control seedlings. All treatment durations resulted in higher
germination and SVI, longer root and higher shoot lenghts of
seedlings than the control. Among the duration treatments, only SVI
and seedling root length were significantly different.
Abstract: Current research has explored the impact of
instructional immediacy, defined as those behaviors that help build
close relationships or feelings of closeness, both on cognition and
motivation in the traditional classroom and online classroom;
however, online courses continue to suffer from higher dropout rates.
Based on Albert Bandura-s Social Cognitive Theory, four primary
relationships or interactions in an online course will be explored in
light of how they can provide immediacy thereby reducing student
attrition and improving cognitive learning. The four relationships are
teacher-student, student-student, and student-content, and studentcomputer.
Results of a study conducted with inservice teachers
completing a 14-week online professional development technology
course will be examined to demonstrate immediacy strategies that
improve cognitive learning and reduce student attrition. Results of
the study reveal that students can be motivated through various
interactions and instructional immediacy behaviors which lead to
higher completion rates, improved self-efficacy, and cognitive
learning.
Abstract: Pakistani doctors (MBBS) are emigrating towards developed countries for professional adjustments. This study aims to highlight causes and consequences of doctors- brain drain from Pakistan. Primary data was collected from Mayo Hospital, Lahore by interviewing doctors (n=100) through systematic random sampling technique. It found that various socio-economic and political conditions are working as push and pull factors for brain drain of doctors in Pakistan. Majority of doctors (83%) declared poor remunerations and professional infrastructure of health department as push factor of doctors- brain drain. 81% claimed that continuous instability in political situation and threats of terrorism are responsible for emigration of doctors. 84% respondents considered fewer opportunities of further studies responsible for their emigration. Brain drain of doctors is affecting health sector-s policies / programs, standard doctor-patient ratios and quality of health services badly.
Abstract: It-s known that incorporating prior knowledge into support
vector regression (SVR) can help to improve the approximation
performance. Most of researches are concerned with the incorporation
of knowledge in the form of numerical relationships. Little work,
however, has been done to incorporate the prior knowledge on the
structural relationships among the variables (referred as to Structural
Prior Knowledge, SPK). This paper explores the incorporation of SPK
in SVR by constructing appropriate admissible support vector kernel
(SV kernel) based on the properties of reproducing kernel (R.K).
Three-levels specifications of SPK are studied with the corresponding
sub-levels of prior knowledge that can be considered for the method.
These include Hierarchical SPK (HSPK), Interactional SPK (ISPK)
consisting of independence, global and local interaction, Functional
SPK (FSPK) composed of exterior-FSPK and interior-FSPK. A
convenient tool for describing the SPK, namely Description Matrix
of SPK is introduced. Subsequently, a new SVR, namely Motivated
Support Vector Regression (MSVR) whose structure is motivated
in part by SPK, is proposed. Synthetic examples show that it is
possible to incorporate a wide variety of SPK and helpful to improve
the approximation performance in complex cases. The benefits of
MSVR are finally shown on a real-life military application, Air-toground
battle simulation, which shows great potential for MSVR to
the complex military applications.
Abstract: As nanotechnology advances, the use of nanotechnology for medical purposes in the field of nanomedicine seems more promising; the rise of nanorobots for medical diagnostics and treatments could be arriving in the near future. This study proposes a swarm intelligence based control mechanism for swarm nanorobots that operate as artificial platelets to search for wounds. The canonical particle swarm optimization algorithm is employed in this study. A simulation in the circulatory system is constructed and used for demonstrating the movement of nanorobots with essential characteristics to examine the performance of proposed control mechanism. The effects of three nanorobot capabilities including their perception range, maximum velocity and respond time are investigated. The results show that canonical particle swarm optimization can be used to control the early version nanorobots with simple behaviors and actions.
Abstract: Text-based game is supposed to be a low resource
consumption application that delivers good performances when
compared to graphical-intensive type of games. But, nowadays, some
of the online text-based games are not offering performances that are
acceptable to the users. Therefore, an online text-based game called
Star_Quest has been developed in order to analyze its behavior under
different performance measurements. Performance metrics such as
throughput, scalability, response time and page loading time are
captured to yield the performance of the game. The techniques in
performing the load testing are also disclosed to exhibit the viability
of our work. The comparative assessment between the results
obtained and the accepted level of performances are conducted as to
determine the performance level of the game. The study reveals that
the developed game managed to meet all the performance objectives
set forth.
Abstract: Gold passbook is an investing tool that is especially
suitable for investors to do small investment in the solid gold. The gold
passbook has the lower risk than other ways investing in gold, but its
price is still affected by gold price. However, there are many factors
can cause influences on gold price. Therefore, building a model to
predict the price of gold passbook can both reduce the risk of
investment and increase the benefits. This study investigates the
important factors that influence the gold passbook price, and utilize
the Group Method of Data Handling (GMDH) to build the predictive
model. This method can not only obtain the significant variables but
also perform well in prediction. Finally, the significant variables of
gold passbook price, which can be predicted by GMDH, are US dollar
exchange rate, international petroleum price, unemployment rate,
whole sale price index, rediscount rate, foreign exchange reserves,
misery index, prosperity coincident index and industrial index.
Abstract: In this study thermodynamic performance analysis of a
combined organic Rankine cycle and ejector refrigeration cycle is
carried out for use of low-grade heat source in the form of sensible
energy. Special attention is paid to the effects of system parameters
including the turbine inlet temperature and turbine inlet pressure on the
characteristics of the system such as ratios of mass flow rate, net work
production, and refrigeration capacity as well as the coefficient of
performance and exergy efficiency of the system. Results show that
for a given source the coefficient of performance increases with
increasing of the turbine inlet pressure. However, the exergy
efficiency has an optimal condition with respect to the turbine inlet
pressure.
Abstract: Many footbridges have natural frequencies that
coincide with the dominant frequencies of the pedestrian-induced
load and therefore they have a potential to suffer excessive vibrations
under dynamic loads induced by pedestrians. Some of the design
standards introduce load models for pedestrian loads applicable for
simple structures. Load modeling for more complex structures, on the
other hand, is most often left to the designer. The main focus of this
paper is on the human induced forces transmitted to a footbridge and
on the ways these loads can be modeled to be used in the dynamic
design of footbridges. Also design criteria and load models proposed
by widely used standards were introduced and a comparison was
made. The dynamic analysis of the suspension bridge in Kolin in the
Czech Republic was performed on detailed FEM model using the
ANSYS program system. An attempt to model the load imposed by a
single person and a crowd of pedestrians resulted in displacements
and accelerations that are compared with serviceability criteria.
Abstract: This paper proposes a fast code acquisition scheme for
optical code division multiple access (O-CDMA) systems. Unlike the
conventional scheme, the proposed scheme employs multiple thresholds
providing a shorter mean acquisition time (MAT) performance.
The simulation results show that the MAT of the proposed scheme
is shorter than that of the conventional scheme.
Abstract: The purpose of this study is i) to investigate the driving factors and barriers of the adoption of Information and Communication Technology (ICT) in Halal logistic and ii) to develop an ICT adoption framework for Halal logistic service provider. The Halal LSPs selected for the study currently used ICT service platforms, such as accounting and management system for Halal logistic business. The study categorizes the factors influencing the adoption decision and process by LSPs into four groups: technology related factors, organizational and environmental factors, Halal assurance related factors, and government related factors. The major contribution in this study is the discovery that technology related factors (ICT compatibility with Halal requirement) and Halal assurance related factors are the most crucial factors among the Halal LSPs applying ICT for Halal control in transportation-s operation. Among the government related factors, ICT requirement for monitoring Halal included in Halal Logistic Standard on Transportation (MS2400:2010) are the most influencing factors in the adoption of ICT with the support of the government. In addition, the government related factors are very important in the reducing the main barriers and the creation of the atmosphere of ICT adoption in Halal LSP sector.
Abstract: Camera calibration is an indispensable step for augmented
reality or image guided applications where quantitative information
should be derived from the images. Usually, a camera
calibration is obtained by taking images of a special calibration object
and extracting the image coordinates of projected calibration marks
enabling the calculation of the projection from the 3d world coordinates
to the 2d image coordinates. Thus such a procedure exhibits
typical steps, including feature point localization in the acquired
images, camera model fitting, correction of distortion introduced by
the optics and finally an optimization of the model-s parameters. In
this paper we propose to extend this list by further step concerning
the identification of the optimal subset of images yielding the smallest
overall calibration error. For this, we present a Monte Carlo based
algorithm along with a deterministic extension that automatically
determines the images yielding an optimal calibration. Finally, we
present results proving that the calibration can be significantly
improved by automated image selection.
Abstract: Evolutionary Algorithms are population-based,
stochastic search techniques, widely used as efficient global
optimizers. However, many real life optimization problems often
require finding optimal solution to complex high dimensional,
multimodal problems involving computationally very expensive
fitness function evaluations. Use of evolutionary algorithms in such
problem domains is thus practically prohibitive. An attractive
alternative is to build meta models or use an approximation of the
actual fitness functions to be evaluated. These meta models are order
of magnitude cheaper to evaluate compared to the actual function
evaluation. Many regression and interpolation tools are available to
build such meta models. This paper briefly discusses the
architectures and use of such meta-modeling tools in an evolutionary
optimization context. We further present two evolutionary algorithm
frameworks which involve use of meta models for fitness function
evaluation. The first framework, namely the Dynamic Approximate
Fitness based Hybrid EA (DAFHEA) model [14] reduces
computation time by controlled use of meta-models (in this case
approximate model generated by Support Vector Machine
regression) to partially replace the actual function evaluation by
approximate function evaluation. However, the underlying
assumption in DAFHEA is that the training samples for the metamodel
are generated from a single uniform model. This does not take
into account uncertain scenarios involving noisy fitness functions.
The second model, DAFHEA-II, an enhanced version of the original
DAFHEA framework, incorporates a multiple-model based learning
approach for the support vector machine approximator to handle
noisy functions [15]. Empirical results obtained by evaluating the
frameworks using several benchmark functions demonstrate their
efficiency
Abstract: The conjugate gradient optimization algorithm
usually used for nonlinear least squares is presented and is
combined with the modified back propagation algorithm yielding
a new fast training multilayer perceptron (MLP) algorithm
(CGFR/AG). The approaches presented in the paper consist of
three steps: (1) Modification on standard back propagation
algorithm by introducing gain variation term of the activation
function, (2) Calculating the gradient descent on error with
respect to the weights and gains values and (3) the determination
of the new search direction by exploiting the information
calculated by gradient descent in step (2) as well as the previous
search direction. The proposed method improved the training
efficiency of back propagation algorithm by adaptively modifying
the initial search direction. Performance of the proposed method
is demonstrated by comparing to the conjugate gradient algorithm
from neural network toolbox for the chosen benchmark. The
results show that the number of iterations required by the
proposed method to converge is less than 20% of what is required
by the standard conjugate gradient and neural network toolbox
algorithm.
Abstract: This paper deals with the conceptual design of the
new aeroelastic demonstrator for the whirl flutter simulation. The
paper gives a theoretical background of the whirl flutter phenomenon
and describes the events of the whirl flutter occurrence in the
aerospace practice. The second part is focused on the experimental
research of the whirl flutter on aeroelastic similar models. Finally the
concept of the new aeroelastic demonstrator is described. The
demonstrator represents the wing and engine of the twin turboprop
commuter aircraft including a driven propeller. It allows the changes
of the main structural parameters influencing the whirl flutter
stability characteristics. It is intended for the experimental
investigation of the whirl flutter in the wind tunnel. The results will
be utilized for validation of analytical methods and software tools.
Abstract: Using mini modules of Tmotes, it is possible to automate a small personal area network. This idea can be extended to large networks too by implementing multi-hop routing. Linking the various Tmotes using Programming languages like Nesc, Java and having transmitter and receiver sections, a network can be monitored. It is foreseen that, depending on the application, a long range at a low data transfer rate or average throughput may be an acceptable trade-off. To reduce the overall costs involved, an optimum number of Tmotes to be used under various conditions (Indoor/Outdoor) is to be deduced. By analyzing the data rates or throughputs at various locations of Tmotes, it is possible to deduce an optimal number of Tmotes for a specific network. This paper deals with the determination of optimum distances to reduce the cost and increase the reliability of the entire sensor network with Wireless Local Loop (WLL) capability.
Abstract: In present work, drying characteristics of fresh papaya (Carica papaya L.) was studied to understand the dehydration process and its behavior. Drying experiments were carried out by a laboratory scaled microwave-vacuum oven. The parameters affecting drying characteristics including operating modes (continuous, pulsed), microwave power (400 and 800 W), and vacuum pressure (20, 30, and 40 cmHg) were investigated. For pulsed mode, two levels of power-off time (60 and 120 s) were used while the power-on time was fixed at 60 s and the vacuum pressure was fixed at 40 cmHg. For both operating modes, the effects of drying conditions on drying time, drying rate, and effective diffusivity were investigated. The results showed high microwave power, high vacuum, and pulsed mode of 60 s-on/60 s-off favored drying rate as shown by the shorten drying time and increased effective diffusivity. The drying characteristics were then described by Page-s model, which showed a good agreement with experimental data.
Abstract: Computations with higher than the IEEE 754 standard double-precision (about 16 significant digits) are required recently. Although there are available software routines in Fortran and C for high-precision computation, users are required to implement such routines in their own computers with detailed knowledges about them. We have constructed an user-friendly online system for octupleprecision computation. In our Web system users with no knowledges about high-precision computation can easily perform octupleprecision computations, by choosing mathematical functions with argument(s) inputted, by writing simple mathematical expression(s) or by uploading C program(s). In this paper we enhance the Web system above by adding the facility of uploading Fortran programs, which have been widely used in scientific computing. To this end we construct converter routines in two stages.
Abstract: In this paper we present a method for gene ranking
from DNA microarray data. More precisely, we calculate the correlation
networks, which are unweighted and undirected graphs, from
microarray data of cervical cancer whereas each network represents
a tissue of a certain tumor stage and each node in the network
represents a gene. From these networks we extract one tree for
each gene by a local decomposition of the correlation network. The
interpretation of a tree is that it represents the n-nearest neighbor
genes on the n-th level of a tree, measured by the Dijkstra distance,
and, hence, gives the local embedding of a gene within the correlation
network. For the obtained trees we measure the pairwise similarity
between trees rooted by the same gene from normal to cancerous
tissues. This evaluates the modification of the tree topology due to
progression of the tumor. Finally, we rank the obtained similarity
values from all tissue comparisons and select the top ranked genes.
For these genes the local neighborhood in the correlation networks
changes most between normal and cancerous tissues. As a result
we find that the top ranked genes are candidates suspected to be
involved in tumor growth and, hence, indicates that our method
captures essential information from the underlying DNA microarray
data of cervical cancer.
Abstract: It is known that if harmonic spectra are decreased, then
acoustic noise also decreased. Hence, this paper deals with a new
random switching strategy using DSP TMS320F2812 to decrease the
harmonics spectra of single phase switched reluctance motor. The
proposed method which combines random turn-on, turn-off angle
technique and random pulse width modulation technique is shown. A
harmonic spread factor (HSF) is used to evaluate the random
modulation scheme. In order to confirm the effectiveness of the new
method, the experimental results show that the harmonic intensity of
output voltage for the proposed method is better than that for
conventional methods.