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: The objective of this study was to identify the optimal
level of partial replacement of Portland cement by the ashes
originating from burning straw and bagasse from sugar cane (ASB).
Order to this end, were made five series of flat plates and cylindrical
bodies: control and others with the partial replacement in 20, 30, 40
and 50% of ASB in relation to the mass of the Ordinary Portland
cement, and conducted a mechanical testing of simple axial
compression (cylindrical bodies) and the four-point bending (flat
plates) and determined water absorption (WA), bulk density (BD)
and apparent void volume (AVV) on both types of specimens. Based
on the data obtained, it may be noted that the control treatment
containing only Portland cement, obtained the best results. However,
the cylindrical bodies with 20% ashes showed better results
compared to the other treatments. And in the formulations plates, the
treatment which showed the best results was 30% cement
replacement by ashes.
Abstract: Neurons in the nervous system communicate with
each other by producing electrical signals called spikes. To
investigate the physiological function of nervous system it is essential
to study the activity of neurons by detecting and sorting spikes in the
recorded signal. In this paper a method is proposed for considering
the spike sorting problem which is based on the nonlinear modeling
of spikes using exponential autoregressive model. The genetic
algorithm is utilized for model parameter estimation. In this regard
some selected model coefficients are used as features for sorting
purposes. For optimal selection of model coefficients, self-organizing
feature map is used. The results show that modeling of spikes with
nonlinear autoregressive model outperforms its linear counterpart.
Also the extracted features based on the coefficients of exponential
autoregressive model are better than wavelet based extracted features
and get more compact and well-separated clusters. In the case of
spikes different in small-scale structures where principal component
analysis fails to get separated clouds in the feature space, the
proposed method can obtain well-separated cluster which removes
the necessity of applying complex classifiers.
Abstract: This paper presents the details of a numerical study of
buckling and post buckling behaviour of laminated carbon fiber
reinforced plastic (CFRP) thin-walled cylindrical shell under axial
compression using asymmetric meshing technique (AMT) by
ABAQUS. AMT is considered to be a new perturbation method to
introduce disturbance without changing geometry, boundary
conditions or loading conditions. Asymmetric meshing affects both
predicted buckling load and buckling mode shapes. Cylindrical shell
having lay-up orientation [0^o/+45^o/-45^o/0^o] with radius to thickness
ratio (R/t) equal to 265 and length to radius ratio (L/R) equal to 1.5 is
analysed numerically. A series of numerical simulations
(experiments) are carried out with symmetric and asymmetric
meshing to study the effect of asymmetric meshing on predicted
buckling behaviour. Asymmetric meshing technique is employed in
both axial direction and circumferential direction separately using
two different methods, first by changing the shell element size and
varying the total number elements, and second by varying the shell
element size and keeping total number of elements constant. The
results of linear analysis (Eigenvalue analysis) and non-linear
analysis (Riks analysis) using symmetric meshing agree well with
analytical results. The results of numerical analysis are presented in
form of non-dimensional load factor, which is the ratio of buckling
load using asymmetric meshing technique to buckling load using
symmetric meshing technique. Using AMT, load factor has about 2%
variation for linear eigenvalue analysis and about 2% variation for
non-linear Riks analysis. The behaviour of load end-shortening curve
for pre-buckling is same for both symmetric and asymmetric meshing
but for asymmetric meshing curve behaviour in post-buckling
becomes extraordinarily complex. The major conclusions are:
different methods of AMT have small influence on predicted
buckling load and significant influence on load displacement curve
behaviour in post buckling; AMT in axial direction and AMT in
circumferential direction have different influence on buckling load
and load displacement curve in post-buckling.
Abstract: In this report we have discussed the theoretical aspects
of the flow transformation, occurring through a series of bifurcations.
The parameters and their continuous diversion, the intermittent bursts
in the transition zone, variation of velocity and pressure with time,
effect of roughness in turbulent zone, and changes in friction factor
and head loss coefficient as a function of Reynolds number for a
transverse flow across a cylinder have been discussed. An analysis of
the variation in the wake length with Reynolds number was done in
FORTRAN.
Abstract: Recent research in neural networks science and
neuroscience for modeling complex time series data and statistical
learning has focused mostly on learning from high input space and
signals. Local linear models are a strong choice for modeling local
nonlinearity in data series. Locally weighted projection regression is
a flexible and powerful algorithm for nonlinear approximation in
high dimensional signal spaces. In this paper, different learning
scenario of one and two dimensional data series with different
distributions are investigated for simulation and further noise is
inputted to data distribution for making different disordered
distribution in time series data and for evaluation of algorithm in
locality prediction of nonlinearity. Then, the performance of this
algorithm is simulated and also when the distribution of data is high
or when the number of data is less the sensitivity of this approach to
data distribution and influence of important parameter of local
validity in this algorithm with different data distribution is explained.
Abstract: The development, operation and maintenance of
Integrated Waste Management Systems (IWMS) affects essentially
the sustainable concern of every region. The features of such systems
have great influence on all of the components of sustainability. In
order to reach the optimal way of processes, a comprehensive
mapping of the variables affecting the future efficiency of the system
is needed such as analysis of the interconnections among the
components and modeling of their interactions. The planning of a
IWMS is based fundamentally on technical and economical
opportunities and the legal framework. Modeling the sustainability
and operation effectiveness of a certain IWMS is not in the scope of
the present research. The complexity of the systems and the large
number of the variables require the utilization of a complex approach
to model the outcomes and future risks. This complex method should
be able to evaluate the logical framework of the factors composing
the system and the interconnections between them. The authors of
this paper studied the usability of the Fuzzy Cognitive Map (FCM)
approach modeling the future operation of IWMS’s. The approach
requires two input data set. One is the connection matrix containing
all the factors affecting the system in focus with all the
interconnections. The other input data set is the time series, a
retrospective reconstruction of the weights and roles of the factors.
This paper introduces a novel method to develop time series by
content analysis.
Abstract: In this paper, Bayesian online inference in models of
data series are constructed by change-points algorithm, which
separated the observed time series into independent series and study
the change and variation of the regime of the data with related
statistical characteristics. variation of statistical characteristics of time
series data often represent separated phenomena in the some
dynamical system, like a change in state of brain dynamical reflected
in EEG signal data measurement or a change in important regime of
data in many dynamical system. In this paper, prediction algorithm
for studying change point location in some time series data is
simulated. It is verified that pattern of proposed distribution of data
has important factor on simpler and smother fluctuation of hazard
rate parameter and also for better identification of change point
locations. Finally, the conditions of how the time series distribution
effect on factors in this approach are explained and validated with
different time series databases for some dynamical system.
Abstract: Validity, integrity, and impacts of the IT systems of
the US federal courts have been studied as part of the Human Rights
Alert-NGO (HRA) submission for the 2015 Universal Periodic
Review (UPR) of human rights in the United States by the Human
Rights Council (HRC) of the United Nations (UN). The current
report includes overview of IT system analysis, data-mining and case
studies. System analysis and data-mining show: Development and
implementation with no lawful authority, servers of unverified
identity, invalidity in implementation of electronic signatures,
authentication instruments and procedures, authorities and
permissions; discrimination in access against the public and
unrepresented (pro se) parties and in favor of attorneys; widespread
publication of invalid judicial records and dockets, leading to their
false representation and false enforcement. A series of case studies
documents the impacts on individuals' human rights, on banking
regulation, and on international matters. Significance is discussed in
the context of various media and expert reports, which opine
unprecedented corruption of the US justice system today, and which
question, whether the US Constitution was in fact suspended. Similar
findings were previously reported in IT systems of the State of
California and the State of Israel, which were incorporated, subject to
professional HRC staff review, into the UN UPR reports (2010 and
2013). Solutions are proposed, based on the principles of publicity of
the law and the separation of power: Reliance on US IT and legal
experts under accountability to the legislative branch, enhancing
transparency, ongoing vigilance by human rights and internet
activists. IT experts should assume more prominent civic duties in the
safeguard of civil society in our era.
Abstract: One of the major difficulties introduced with wind
power penetration is the inherent uncertainty in production originating
from uncertain wind conditions. This uncertainty impacts many
different aspects of power system operation, especially the balancing
power requirements. For this reason, in power system development
planing, it is necessary to evaluate the potential uncertainty in future
wind power generation. For this purpose, simulation models are
required, reproducing the performance of wind power forecasts.
This paper presents a wind power forecast error simulation models
which are based on the stochastic process simulation. Proposed
models capture the most important statistical parameters recognized
in wind power forecast error time series. Furthermore, two distinct
models are presented based on data availability. First model uses
wind speed measurements on potential or existing wind power plant
locations, while the seconds model uses statistical distribution of wind
speeds.
Abstract: Climate change confronts the built environment with
many new challenges in the form of more severe and frequent hydrometeorological
events. A series of strategies is proposed whereby the
various aspects of buildings and their sites can be made more resilient
to the effects of such events.
Abstract: Periventricular Leukomalacia (PVL) is a White Matter
Injury (WMI) of preterm neonatal brain. Objectives of the study were
to assess the neuro-developmental outcome at one year of age and to
determine a good protocol of cranial ultrasonography to detect PVL.
Two hundred and sixty four preterm neonates were included in the
study. Series of cranial ultrasound scans were done by using a
dedicated neonatal head probe 4-10 MHz of Logic e portable
ultrasound scanner. Clinical history of seizures, abnormal head
growth (hydrocephalus or microcephaly) and developmental
milestones were assessed and neurological examinations were done
until one year of age. Among live neonates, 57% who had cystic PVL
(Grades 2 and 3) manifested as cerebral palsy. In conclusion cystic
PVL has permanent neurological disabilities like cerebral palsy.
Good protocol of real time cranial ultrasonography to detect PVL is
to perform scans at least once a week until one month and at term (40
weeks of gestation).
Abstract: Cloud computing has provided the impetus for change
in the demand, sourcing, and consumption of IT-enabled services.
The technology developed from an emerging trend towards a ‘musthave’.
Many organizations harnessed on the quick-wins of cloud
computing within the last five years but nowadays reach a plateau
when it comes to sustainable savings and performance. This study
aims to investigate what is needed from an organizational perspective
to make cloud computing a sustainable success. The study was
carried out in Germany among senior IT professionals, both in
management and delivery positions. Our research shows that IT
executives must be prepared to realign their IT workforce to sustain
the advantage of cloud computing for today and the near future.
While new roles will undoubtedly emerge, roles alone cannot ensure
the success of cloud deployments. What is needed is a change in the
IT workforce’s business behaviour, or put more simply, the ways in
which the IT personnel works. It gives clear guidance on which
dimensions of an employees’ working behaviour need to be adapted.
The practical implications are drawn from a series of semi-structured
interviews, resulting in a high-level workforce enablement plan.
Lastly, it elaborates on tools and gives clear guidance on which
pitfalls might arise along the proposed workforce enablement
process.
Abstract: Carbon nanotube is one of the most attractive materials
for the potential applications of nanotechnology due to its excellent
mechanical, thermal, electrical and optical properties. In this paper we
report a supercapacitor made of nickel foil electrodes, coated with
multiwall carbon nanotubes (MWCNTs) thin film using
electrophoretic deposition (EPD) method. Chemical vapor deposition
method was used for the growth of MWCNTs and ethanol was used as
a hydrocarbon source. High graphitic multiwall carbon nanotube was
found at 750oC analyzing by Raman spectroscopy. We observed the
electrochemical performance of supercapacitor by cyclic
voltammetry. The electrodes of supercapacitor fabricated from
MWCNTs exhibit considerably small equivalent series resistance
(ESR), and a high specific power density. Electrophoretic deposition
is an easy method in fabricating MWCNT electrodes for high
performance supercapacitor.
Abstract: Today’s modern interconnected power system is
highly complex in nature. In this, one of the most important
requirements during the operation of the electric power system is the
reliability and security. Power and frequency oscillation damping
mechanism improve the reliability. Because of power system
stabilizer (PSS) low speed response against of major fault such as
three phase short circuit, FACTs devise that can control the network
condition in very fast time, are becoming popular. But FACTs
capability can be seen in a major fault present when nonlinear models
of FACTs devise and power system equipment are applied. To realize
this aim, the model of multi-machine power system with FACTs
controller is developed in MATLAB/SIMULINK using Sim Power
System (SPS) blockiest. Among the FACTs device, Static
synchronous series compensator (SSSC) due to high speed changes
its reactance characteristic inductive to capacitive, is effective power
flow controller. Tuning process of controller parameter can be
performed using different method. But Genetic Algorithm (GA)
ability tends to use it in controller parameter tuning process. In this
paper firstly POD controller is used to power oscillation damping.
But in this station, frequency oscillation dos not has proper damping
situation. So FOD controller that is tuned using GA is using that
cause to damp out frequency oscillation properly and power
oscillation damping has suitable situation.
Abstract: In this paper, we study the rainfall using a time series
for weather stations in Nakhon Ratchasima province in Thailand by
various statistical methods to enable us to analyse the behaviour of
rainfall in the study areas. Time-series analysis is an important tool in
modelling and forecasting rainfall. The ARIMA and Holt-Winter
models were built on the basis of exponential smoothing. All the
models proved to be adequate. Therefore it is possible to give
information that can help decision makers establish strategies for the
proper planning of agriculture, drainage systems and other water
resource applications in Nakhon Ratchasima province. We obtained
the best performance from forecasting with the ARIMA
Model(1,0,1)(1,0,1)12.
Abstract: The dramatic rise in the use of Social Media (SM)
platforms such as Facebook and Twitter provide access to an
unprecedented amount of user data. Users may post reviews on
products and services they bought, write about their interests, share
ideas or give their opinions and views on political issues. There is a
growing interest in the analysis of SM data from organisations for
detecting new trends, obtaining user opinions on their products and
services or finding out about their online reputations. A recent
research trend in SM analysis is making predictions based on
sentiment analysis of SM. Often indicators of historic SM data are
represented as time series and correlated with a variety of real world
phenomena like the outcome of elections, the development of
financial indicators, box office revenue and disease outbreaks. This
paper examines the current state of research in the area of SM mining
and predictive analysis and gives an overview of the analysis
methods using opinion mining and machine learning techniques.
Abstract: This paper describes a logical method to enhance
security on the grid computing to restrict the misuse of the grid
resources. This method is an economic and efficient one to avoid the
usage of the special devices. The security issues, techniques and
solutions needed to provide a secure grid computing environment are
described. A well defined process for security management among
the resource accesses and key holding algorithm is also proposed. In
this method, the identity management, access control and
authorization and authentication are effectively handled.
Abstract: Comprehensive numerical studies have been carried
out to examine the best aerodynamic performance of subsonic aircraft
at different winglet cant angles using a validated 3D k-ω SST model.
In the parametric analytical studies NACA series of airfoils are
selected. Basic design of the winglet is selected from the literature
and flow features of the entire wing including the winglet tip effects
have been examined with different cant angles varying from 150 to
600 at different angles of attack up to 140. We have observed, among
the cases considered in this study that a case, with 150 cant angle the
aerodynamics performance of the subsonic aircraft during takeoff
was found better up to an angle of attack of 2.80 and further its
performance got diminished at higher angles of attack. Analyses
further revealed that increasing the winglet cant angle from 150 to 600
at higher angles of attack could negate the performance deterioration
and additionally it could enhance the peak CL/CD on the order of
3.5%. The investigated concept of variable-cant-angle winglets
appears to be a promising alternative for improving the aerodynamic
efficiency of aircraft.
Abstract: Predicting earthquakes is an important issue in the
study of geography. Accurate prediction of earthquakes can help
people to take effective measures to minimize the loss of personal
and economic damage, such as large casualties, destruction of
buildings and broken of traffic, occurred within a few seconds.
United States Geological Survey (USGS) science organization
provides reliable scientific information about Earthquake Existed
throughout history & the Preliminary database from the National
Center Earthquake Information (NEIC) show some useful factors to
predict an earthquake in a seismic area like Aleutian Arc in the U.S.
state of Alaska. The main advantage of this prediction method that it
does not require any assumption, it makes prediction according to the
future evolution of the object's time series. The article compares
between simulation data result from trained BP and RBF neural
network versus actual output result from the system calculations.
Therefore, this article focuses on analysis of data relating to real
earthquakes. Evaluation results show better accuracy and higher
speed by using radial basis functions (RBF) neural network.