Abstract: Comparisons of financial development across
countries are central to answering many of the questions on factors
leading to economic development. For this reason this study analyzes
the implications of financial system’s development on country’s
economic development. The aim of the article: to analyze the impact
of financial system’s development on economic development. The
following research methods were used: systemic, logical and
comparative analysis of scientific literature, analysis of statistical
data, time series model (Autoregressive Distributed Lag (ARDL)
Model). The empirical results suggest about positive short and long
term effect of stock market development on GDP per capita.
Abstract: Our goal is development of an algorithm capable of
predicting the directional trend of the Standard and Poor’s 500 index
(S&P 500). Extensive research has been published attempting to
predict different financial markets using historical data testing on an
in-sample and trend basis, with many authors employing excessively
complex mathematical techniques. In reviewing and evaluating these
in-sample methodologies, it became evident that this approach was
unable to achieve sufficiently reliable prediction performance for
commercial exploitation. For these reasons, we moved to an out-ofsample
strategy based on linear regression analysis of an extensive
set of financial data correlated with historical closing prices of the
S&P 500. We are pleased to report a directional trend accuracy of
greater than 55% for tomorrow (t+1) in predicting the S&P 500.
Abstract: In recent years, the hair building fiber has become
popular, in other words, it is an effective method which helps people
who suffer hair loss or sparse hair since the hair building fiber is
capable to create a natural look of simulated hair rapidly. In the
markets, there are a lot of hair fiber brands that have been designed to
formulate an intense bond with hair strands and make the hair appear
more voluminous instantly. However, those products have their own
set of properties. Thus, in this report, some measurement techniques
are proposed to identify those products. Up to five different brands of
hair fiber are tested. The electrostatic and dielectric properties of the
hair fibers are macroscopically tested using design DC and high
frequency microwave techniques. Besides, the hair fibers are
microscopically analysis by magnifying the structures of the fiber
using scanning electron microscope (SEM). From the SEM photos,
the comparison of the uniformly shaped and broken rate of the hair
fibers in the different bulk samples can be observed respectively.
Abstract: This paper presents a methodology using
Gravitational Search Algorithm for optimal placement of Phasor
Measurement Units (PMUs) in order to achieve complete
observability of the power system. The objective of proposed
algorithm is to minimize the total number of PMUs at the power
system buses, which in turn minimize installation cost of the PMUs.
In this algorithm, the searcher agents are collection of masses which
interact with each other using Newton’s laws of gravity and motion.
This new Gravitational Search Algorithm based method has been
applied to the IEEE 14-bus, IEEE 30-bus and IEEE 118-bus test
systems. Case studies reveal optimal number of PMUs with better
observability by proposed method.
Abstract: The characteristic requirement for producing
rectangular shape bottles was a uniform thickness of the plastic bottle
wall. Die shaping was a good technique which controlled the wall
thickness of bottles. An advance technology which was the finite
element method (FEM) for blowing parison to be a rectangular shape
bottle was conducted to reduce waste plastic from a trial and error
method of a die shaping and parison control method. The artificial
intelligent (AI) comprised of artificial neural network and genetic
algorithm was selected to optimize the die gap shape from the FEM
results. The application of AI technique could optimize the suitable
die gap shape for the parison blow molding which did not depend on
the parison control method to produce rectangular bottles with the
uniform wall. Particularly, this application can be used with cheap
blow molding machines without a parison controller therefore it will
reduce cost of production in the bottle blow molding process.
Abstract: Non-linear FEM calculations are indispensable when
important technical information like operating performance of a
rubber component is desired. For example rubber bumpers built into
air-spring structures may undergo large deformations under load,
which in itself shows non-linear behavior. The changing contact
range between the parts and the incompressibility of the rubber
increases this non-linear behavior further. The material
characterization of an elastomeric component is also a demanding
engineering task.
The shape optimization problem of rubber parts led to the study of
FEM based calculation processes. This type of problems was posed
and investigated by several authors. In this paper the time demand of
certain calculation methods are studied and the possibilities of time
reduction is presented.
Abstract: Composite material based on Fe3Si micro-particles
and Mn-Zn nano-ferrite was prepared using powder metallurgy
technology. The sol-gel followed by autocombustion process was
used for synthesis of Mn0.8Zn0.2Fe2O4 ferrite. 3 wt.% of mechanically
milled ferrite was mixed with Fe3Si powder alloy. Mixed micro-nano
powder system was homogenized by the Resonant Acoustic Mixing
using ResodynLabRAM Mixer. This non-invasive homogenization
technique was used to preserve spherical morphology of Fe3Si
powder particles. Uniaxial cold pressing in the closed die at pressure
600 MPa was applied to obtain a compact sample. Microwave
sintering of green compact was realized at 800°C, 20 minutes, in air.
Density of the powders and composite was measured by
Hepycnometry. Impulse excitation method was used to measure
elastic properties of sintered composite. Mechanical properties were
evaluated by measurement of transverse rupture strength (TRS) and
Vickers hardness (HV). Resistivity was measured by 4 point probe
method. Ferrite phase distribution in volume of the composite was
documented by metallographic analysis.
It has been found that nano-ferrite particle distributed among
micro- particles of Fe3Si powder alloy led to high relative density
(~93%) and suitable mechanical properties (TRS >100 MPa, HV
~1GPa, E-modulus ~140 GPa) of the composite. High electric
resistivity (R~6.7 ohm.cm) of prepared composite indicate their
potential application as soft magnetic material at medium and high
frequencies.
Abstract: This paper introduces an original method of
parametric optimization of the structure for multimodal decisionlevel
fusion scheme which combines the results of the partial solution
of the classification task obtained from assembly of the mono-modal
classifiers. As a result, a multimodal fusion classifier which has the
minimum value of the total error rate has been obtained.
Abstract: Microbial fuel cells (MFCs) represent a promising
technology for simultaneous bioelectricity generation and wastewater
treatment. Catalysts are significant portions of the cost of microbial
fuel cell cathodes. Many materials have been tested as aqueous
cathodes, but air-cathodes are needed to avoid energy demands for
water aeration. The sluggish oxygen reduction reaction (ORR) rate at
air cathode necessitates efficient electrocatalyst such as carbon
supported platinum catalyst (Pt/C) which is very costly. Manganese
oxide (MnO2) was a representative metal oxide which has been
studied as a promising alternative electrocatalyst for ORR and has
been tested in air-cathode MFCs. However the single MnO2 has poor
electric conductivity and low stability. In the present work, the MnO2
catalyst has been modified by doping Pt nanoparticle. The goal of the
work was to improve the performance of the MFC with minimum Pt
loading. MnO2 and Pt nanoparticles were prepared by hydrothermal
and sol gel methods, respectively. Wet impregnation method was
used to synthesize Pt/MnO2 catalyst. The catalysts were further used
as cathode catalysts in air-cathode cubic MFCs, in which anaerobic
sludge was inoculated as biocatalysts and palm oil mill effluent
(POME) was used as the substrate in the anode chamber. The asprepared
Pt/MnO2 was characterized comprehensively through field
emission scanning electron microscope (FESEM), X-Ray diffraction
(XRD), X-ray photoelectron spectroscopy (XPS), and cyclic
voltammetry (CV) where its surface morphology, crystallinity,
oxidation state and electrochemical activity were examined,
respectively. XPS revealed Mn (IV) oxidation state and Pt (0)
nanoparticle metal, indicating the presence of MnO2 and Pt.
Morphology of Pt/MnO2 observed from FESEM shows that the
doping of Pt did not cause change in needle-like shape of MnO2
which provides large contacting surface area. The electrochemical
active area of the Pt/MnO2 catalysts has been increased from 276 to
617 m2/g with the increase in Pt loading from 0.2 to 0.8 wt%. The
CV results in O2 saturated neutral Na2SO4 solution showed that
MnO2 and Pt/MnO2 catalysts could catalyze ORR with different
catalytic activities. MFC with Pt/MnO2 (0.4 wt% Pt) as air cathode
catalyst generates a maximum power density of 165 mW/m3, which
is higher than that of MFC with MnO2 catalyst (95 mW/m3). The
open circuit voltage (OCV) of the MFC operated with MnO2 cathode
gradually decreased during 14 days of operation, whereas the MFC
with Pt/MnO2 cathode remained almost constant throughout the
operation suggesting the higher stability of the Pt/MnO2 catalyst.
Therefore, Pt/MnO2 with 0.4 wt% Pt successfully demonstrated as an
efficient and low cost electrocatalyst for ORR in air cathode MFC with higher electrochemical activity, stability and hence enhanced
performance.
Abstract: In this paper, we propose an automatic verification
technology of software patches for user virtual environments on IaaS
Cloud to decrease verification costs of patches. In these days, IaaS
services have been spread and many users can customize virtual
machines on IaaS Cloud like their own private servers. Regarding to
software patches of OS or middleware installed on virtual machines,
users need to adopt and verify these patches by themselves. This task
increases operation costs of users. Our proposed method replicates
user virtual environments, extracts verification test cases for user
virtual environments from test case DB, distributes patches to virtual
machines on replicated environments and conducts those test cases
automatically on replicated environments. We have implemented the
proposed method on OpenStack using Jenkins and confirmed the
feasibility. Using the implementation, we confirmed the effectiveness
of test case creation efforts by our proposed idea of 2-tier abstraction
of software functions and test cases. We also evaluated the automatic
verification performance of environment replications, test cases
extractions and test cases conductions.
Abstract: The web’s increased popularity has included a huge
amount of information, due to which automated web page
classification systems are essential to improve search engines’
performance. Web pages have many features like HTML or XML
tags, hyperlinks, URLs and text contents which can be considered
during an automated classification process. It is known that Webpage
classification is enhanced by hyperlinks as it reflects Web page
linkages. The aim of this study is to reduce the number of features to
be used to improve the accuracy of the classification of web pages. In
this paper, a novel feature selection method using an improved
Particle Swarm Optimization (PSO) using principle of evolution is
proposed. The extracted features were tested on the WebKB dataset
using a parallel Neural Network to reduce the computational cost.
Abstract: The main aim of this research was to investigate a
prototype bamboo shading device. There were two objectives to this
study: first, to investigate the effects of non-chemical treatments on
bamboo shading devices damaged by powder-post beetles and fungi,
and second to develop a prototype bamboo shading device. This
study of the effects of non-chemical treatments on bamboo shading
devices damage by powder-post beetles in the laboratory showed
that, among seven treatments tested, wood vinegar treatment can
protect powder-post beetles better than the original method by up to
92.91%. It was also found that wood vinegar treatment shows the
best performance in fungi protection and works better than the
original method by up to 40%. A second experiment was carried out
by constructing four bamboo shading devices and installing them on
a building for 28 days. All aspects of shading device were
investigated in terms of their beauty, durability, and ease of
construction and assembly. The final prototype was developed from
the lessons learned from the test results. In conclusion, this study
showed the effectiveness of some natural preservatives against insect
and fungi damage, and it also illustrated the characteristics of a
prototype bamboo shading device that can be constructed by rural
workers within one week.
Abstract: The organizations in the knowledge economy era have
recognized the importance of building knowledge assets for
sustainable growth and development. In comparison to other
industries, Information Technology (IT) enterprises, holds an edge in
developing an effective Knowledge Management (KM) programmethanks
to their in-house technological abilities. This paper tries to
study the various knowledge based incentive programmes and its
effect on Knowledge Sharing and Learning in the context of the
Indian IT sector. A conceptual model is developed linking KM
Incentives, Knowledge Sharing and Learning. A questionnaire study
is conducted to collect primary data from the knowledge workers of
the IT organizations located in India. The data was analysed using
Structural Equation Modeling using Partial Least Square method. The
results show a strong influence of knowledge management incentives
on knowledge sharing and an indirect influence on learning.
Abstract: Environmental impact assessment techniques have
been developed as a result of the worldwide efforts to reduce the
environmental impact of global warming. By using the quantification
method in the construction industry, it is now possible to manage the
greenhouse gas is to systematically evaluate the impact on the
environment over the entire construction process. In particular, the
proportion of greenhouse gas emissions at the production stage of
construction material occupied is high, and efforts are needed in
particular in the construction field.
In this research, intended for concrete products for the construction
materials, by using the LCA method, we compared the results of
environmental impact assessment and carbon emissions of developing
products that have been applied low-carbon technologies compared to
existing products. As a results, by introducing a raw material of
industrial waste, showed carbon reduction. Through a comparison of
the carbon emission reduction effect of low carbon technologies, it is
intended to provide academic data for the evaluation of greenhouse
gases in the construction sector and the development of low carbon
technologies of the future.
Abstract: Large-scale data stream analysis has become one of
the important business and research priorities lately. Social networks
like Twitter and other micro-blogging platforms hold an enormous
amount of data that is large in volume, velocity and variety.
Extracting valuable information and trends out of these data would
aid in a better understanding and decision-making. Multiple analysis
techniques are deployed for English content. Moreover, one of the
languages that produce a large amount of data over social networks
and is least analyzed is the Arabic language. The proposed paper is a
survey on the research efforts to analyze the Arabic content in
Twitter focusing on the tools and methods used to extract the
sentiments for the Arabic content on Twitter.
Abstract: In this paper, an analysis of some model order
reduction techniques is presented. A new hybrid algorithm for model
order reduction of linear time invariant systems is compared with the
conventional techniques namely Balanced Truncation, Hankel Norm
reduction and Dominant Pole Algorithm (DPA). The proposed hybrid
algorithm is known as Clustering Dominant Pole Algorithm (CDPA),
is able to compute the full set of dominant poles and its cluster center
efficiently. The dominant poles of a transfer function are specific
eigenvalues of the state space matrix of the corresponding dynamical
system. The effectiveness of this novel technique is shown through
the simulation results.
Abstract: In order to study the aerodynamic performance of a
semi-flexible membrane wing, Fluid-Structure Interaction simulations
have been performed. The fluid problem has been modeled using
two different approaches which are the vortex panel method and the
numerical solution of the Navier-Stokes equations. Nonlinear analysis
of the structural problem is performed using the Finite Element
Method. Comparison between the two fluid solvers has been made.
Aerodynamic performance of the wing is discussed regarding its
lift and drag coefficients and they are compared with those of the
equivalent rigid wing.
Abstract: This paper presents a method of hardening the 8051
micro-controller, able to assure reliable operation in the presence of
bit flips caused by radiation. Aiming at avoiding such faults in the
8051 micro-controller, Hamming code protection was used in its
SRAM memory and registers. A VHDL code has been used for this
hamming code protection.
Abstract: Estimation of model parameters is necessary to predict
the behavior of a system. Model parameters are estimated using
optimization criteria. Most algorithms use historical data to estimate
model parameters. The known target values (actual) and the output
produced by the model are compared. The differences between the
two form the basis to estimate the parameters. In order to compare
different models developed using the same data different criteria are
used. The data obtained for short scale projects are used here. We
consider software effort estimation problem using radial basis
function network. The accuracy comparison is made using various
existing criteria for one and two predictors. Then, we propose a new
criterion based on linear least squares for evaluation and compared
the results of one and two predictors. We have considered another
data set and evaluated prediction accuracy using the new criterion.
The new criterion is easy to comprehend compared to single statistic.
Although software effort estimation is considered, this method is
applicable for any modeling and prediction.
Abstract: Biofuels production has come forth as a future
technology to combat the problem of depleting fossil fuels. Bio-based
ethanol production from enzymatic lignocellulosic biomass
degradation serves an efficient method and catching the eye of
scientific community. High cost of the enzyme is the major obstacle
in preventing the commercialization of this process. Thus main
objective of the present study was to optimize composition of
medium components for enhancing cellulase production by newly
isolated strain of Bacillus tequilensis. Nineteen factors were taken
into account using statistical Plackett-Burman Design. The significant
variables influencing the cellulose production were further employed
in statistical Response Surface Methodology using Central
Composite Design for maximizing cellulase production. The
optimum medium composition for cellulase production was: peptone
(4.94 g/L), ammonium chloride (4.99 g/L), yeast extract (2.00 g/L),
Tween-20 (0.53 g/L), calcium chloride (0.20 g/L) and cobalt chloride
(0.60 g/L) with pH 7, agitation speed 150 rpm and 72 h incubation at
37oC. Analysis of variance (ANOVA) revealed high coefficient of
determination (R2) of 0.99. Maximum cellulase productivity of 11.5
IU/ml was observed against the model predicted value of 13 IU/ml.
This was found to be optimally active at 60oC and pH 5.5.