Abstract: In this paper real money demand function is analyzed
within multivariate time-series framework. Cointegration approach is
used (Johansen procedure) assuming interdependence between
money demand determinants, which are nonstationary variables. This
will help us to understand the behavior of money demand in Croatia,
revealing the significant influence between endogenous variables in
vector autoregrression system (VAR), i.e. vector error correction
model (VECM). Exogeneity of the explanatory variables is tested.
Long-run money demand function is estimated indicating slow speed
of adjustment of removing the disequilibrium. Empirical results
provide the evidence that real industrial production and exchange
rate explains the most variations of money demand in the long-run,
while interest rate is significant only in short-run.
Abstract: Despite the fact that Arabic language is currently one
of the most common languages worldwide, there has been only a
little research on Arabic speech recognition relative to other
languages such as English and Japanese. Generally, digital speech
processing and voice recognition algorithms are of special
importance for designing efficient, accurate, as well as fast automatic
speech recognition systems. However, the speech recognition process
carried out in this paper is divided into three stages as follows: firstly,
the signal is preprocessed to reduce noise effects. After that, the
signal is digitized and hearingized. Consequently, the voice activity
regions are segmented using voice activity detection (VAD)
algorithm. Secondly, features are extracted from the speech signal
using Mel-frequency cepstral coefficients (MFCC) algorithm.
Moreover, delta and acceleration (delta-delta) coefficients have been
added for the reason of improving the recognition accuracy. Finally,
each test word-s features are compared to the training database using
dynamic time warping (DTW) algorithm. Utilizing the best set up
made for all affected parameters to the aforementioned techniques,
the proposed system achieved a recognition rate of about 98.5%
which outperformed other HMM and ANN-based approaches
available in the literature.
Abstract: It is not easy to imagine how the existing city can be
converted to the principles of sustainability, however, the need for
innovation, requires a pioneering phase which must address the main
problems of rehabilitation of the operating models of the city. Today,
however, there is a growing awareness that the identification and
implementation of policies and measures to promote the adaptation,
resilience and reversibility of the city, require the contribution of our
discipline. This breakthrough is present in some recent international
experiences of Climate Plans, in which the envisaged measures are
closely interwoven with those of urban planning. These experiences,
provide some answers principle questions, such as: how the strategies
to combat climate can be integrated in the instruments of the local
government; what new and specific analysis must be introduced in
urban planning in order to understand the issues of urban
sustainability, and how the project compares with different spatial
scales.
Abstract: A computational platform is presented in this
contribution. It has been designed as a virtual laboratory to be used
for exploring optimization algorithms in biological problems. This
platform is built on a blackboard-based agent architecture. As a test
case, the version of the platform presented here is devoted to the
study of protein folding, initially with a bead-like description of the
chain and with the widely used model of hydrophobic and polar
residues (HP model). Some details of the platform design are
presented along with its capabilities and also are revised some
explorations of the protein folding problems with different types of
discrete space. It is also shown the capability of the platform to
incorporate specific tools for the structural analysis of the runs in
order to understand and improve the optimization process.
Accordingly, the results obtained demonstrate that the ensemble of
computational tools into a single platform is worthwhile by itself,
since experiments developed on it can be designed to fulfill different
levels of information in a self-consistent fashion. By now, it is being
explored how an experiment design can be useful to create a
computational agent to be included within the platform. These
inclusions of designed agents –or software pieces– are useful for the
better accomplishment of the tasks to be developed by the platform.
Clearly, while the number of agents increases the new version of the
virtual laboratory thus enhances in robustness and functionality.
Abstract: There are two common types of operational research techniques, optimisation and metaheuristic methods. The latter may be defined as a sequential process that intelligently performs the exploration and exploitation adopted by natural intelligence and strong inspiration to form several iterative searches. An aim is to effectively determine near optimal solutions in a solution space. In this work, a type of metaheuristics called Ant Colonies Optimisation, ACO, inspired by a foraging behaviour of ants was adapted to find optimal solutions of eight non-linear continuous mathematical models. Under a consideration of a solution space in a specified region on each model, sub-solutions may contain global or multiple local optimum. Moreover, the algorithm has several common parameters; number of ants, moves, and iterations, which act as the algorithm-s driver. A series of computational experiments for initialising parameters were conducted through methods of Rigid Simplex, RS, and Modified Simplex, MSM. Experimental results were analysed in terms of the best so far solutions, mean and standard deviation. Finally, they stated a recommendation of proper level settings of ACO parameters for all eight functions. These parameter settings can be applied as a guideline for future uses of ACO. This is to promote an ease of use of ACO in real industrial processes. It was found that the results obtained from MSM were pretty similar to those gained from RS. However, if these results with noise standard deviations of 1 and 3 are compared, MSM will reach optimal solutions more efficiently than RS, in terms of speed of convergence.
Abstract: The purpose of this study is to determine the
circumstances affecting elementary school students in their family
and school lives and what kind of emotions children may feel
because of these circumstances. The study was carried out according
to the survey model. Four Turkish elementary schools provided 123
fourth grade students for participation in the study. The study-s data
were collected by using worksheets for the activity titled “Important
Days in Our Lives", which was part of the Elementary School Social
Sciences Course 4th Grade Education Program. Data analysis was
carried out according to the content analysis technique used in
qualitative research. The study detected that circumstances of their
family and school lives caused children to feel emotions such as
happiness, sadness, anger, fear and jealousy. The circumstances and
the emotions caused by these circumstances were analyzed according
to gender and interpreted by presenting them with their frequencies.
Abstract: Endovascular aneurysm repair is a new and minimally invasive repair for patients with abdominal aortic aneurysm (AAA). This method has potential advantages that are incomparable with other repair methods. However, the enlargement of aneurysm in the absence of endoleak, which is known as endotension, may occur as one of post-operative compliances of this method. Typically, endotension is mainly as a result of pressure transmitted to aneurysm sac by endovascular installed graft. After installation of graft the aneurysm sac reduces significantly but remains non-zero. There are some factors which affect this pressure transmitted. In this study, the geometry features of installed vascular graft have been considered. It is inferred that graft neck angle and iliac bifurcation angle are two factors which can affect the drag force on graft and consequently the pressure transmitted to aneurysm.
Abstract: In this paper, two centrifugal model tests (case 1: raft
foundation, case 2: 2x2 piled raft foundation) were conducted in
order to evaluate the effect of ground subsidence on load sharing
among piles and raft and settlement of raft and piled raft
foundations. For each case, two conditions consisting of undrained
(without groundwater pumping) and drained (with groundwater
pumping) conditions were considered. Vertical loads were applied
to the models after the foundations were completely consolidated by
selfweight at 50g. The results show that load sharing by the piles in
piled raft foundation (piled load share) for drained condition
decreases faster than that for undrained condition. Settlement of
both raft and piled raft foundations for drained condition increases
more quickly than that for undrained condition. In addition, the
settlement of raft foundation increases more largely than the
settlement of piled raft foundation for drained condition.
Abstract: The System Identification problem looks for a
suitably parameterized model, representing a given process. The
parameters of the model are adjusted to optimize a performance
function based on error between the given process output and
identified process output. The linear system identification field is
well established with many classical approaches whereas most of
those methods cannot be applied for nonlinear systems. The problem
becomes tougher if the system is completely unknown with only the
output time series is available. It has been reported that the
capability of Artificial Neural Network to approximate all linear and
nonlinear input-output maps makes it predominantly suitable for the
identification of nonlinear systems, where only the output time series
is available. [1][2][4][5]. The work reported here is an attempt to
implement few of the well known algorithms in the context of
modeling of nonlinear systems, and to make a performance
comparison to establish the relative merits and demerits.
Abstract: Ten lactating multiparous Holstein cows were used in
a cross-over design with two dietary treatments and 28-d periods
(with 14 d as an adaptation) to study the effect of restaurant fat on
milk production and composition. Each cow was offered 14.7 kg
DM /d of the basal concentrate diet based on barley and corn (crude
protein = 17.7%, neutral detergent fiber = 23.5%, and acid detergent
fiber = 5.8% of dry matter) with free access to alfalfa. Dietary
treatments were arranged as supplying each cow with 0 (CONTROL)
or 150 g/day (RF) of restaurant fat. Supplemental RF did not
significantly (P > 0.25) affect milk yield, composition, and
composition yields, except for milk fat contents. Milk fat contents
were depressed (P < 0.05) with supplemental RF. Our results indicate
that RF could depress milk fat without affecting milk yield and that
the depression in milk fat in response to RF precedes the depression
in milk yield.
Abstract: Six Sigma is a well known discipline that reduces
variation using complex statistical tools and the DMAIC model. By
integrating Goldratts-s Theory of Constraints, the Five Focusing
Points and System Thinking tools, Six Sigma projects can be selected
where it can cause more impact in the company. This research
defines an integrated model of six sigma and constraint management
that shows a step-by-step guide using the original methodologies
from each discipline and is evaluated in a case study from the
production line of a Automobile engine monoblock V8, resulting in
an increase in the line capacity from 18.7 pieces per hour to 22.4
pieces per hour, a reduction of 60% of Work-In-Process and a
variation decrease of 0.73%.
Abstract: In this contribution, the use of a new genetic operator is proposed. The main advantage of using this operator is that it is able to assist the evolution procedure to converge faster towards the optimal solution of a problem. This new genetic operator is called ''intuition'' operator. Generally speaking, one can claim that this operator is a way to include any heuristic or any other local knowledge, concerning the problem, that cannot be embedded in the fitness function. Simulation results show that the use of this operator increases significantly the performance of the classic Genetic Algorithm by increasing the convergence speed of its population.
Abstract: One of the purposes of the robust method of
estimation is to reduce the influence of outliers in the data, on the
estimates. The outliers arise from gross errors or contamination from
distributions with long tails. The trimmed mean is a robust estimate.
This means that it is not sensitive to violation of distributional
assumptions of the data. It is called an adaptive estimate when the
trimming proportion is determined from the data rather than being
fixed a “priori-.
The main objective of this study is to find out the robustness
properties of the adaptive trimmed means in terms of efficiency, high
breakdown point and influence function. Specifically, it seeks to find
out the magnitude of the trimming proportion of the adaptive
trimmed mean which will yield efficient and robust estimates of the
parameter for data which follow a modified Weibull distribution with
parameter λ = 1/2 , where the trimming proportion is determined by a
ratio of two trimmed means defined as the tail length. Secondly, the
asymptotic properties of the tail length and the trimmed means are
also investigated. Finally, a comparison is made on the efficiency of
the adaptive trimmed means in terms of the standard deviation for the
trimming proportions and when these were fixed a “priori".
The asymptotic tail lengths defined as the ratio of two trimmed
means and the asymptotic variances were computed by using the
formulas derived. While the values of the standard deviations for the
derived tail lengths for data of size 40 simulated from a Weibull
distribution were computed for 100 iterations using a computer
program written in Pascal language.
The findings of the study revealed that the tail lengths of the
Weibull distribution increase in magnitudes as the trimming
proportions increase, the measure of the tail length and the adaptive
trimmed mean are asymptotically independent as the number of
observations n becomes very large or approaching infinity, the tail
length is asymptotically distributed as the ratio of two independent
normal random variables, and the asymptotic variances decrease as
the trimming proportions increase. The simulation study revealed
empirically that the standard error of the adaptive trimmed mean
using the ratio of tail lengths is relatively smaller for different values
of trimming proportions than its counterpart when the trimming
proportions were fixed a 'priori'.
Abstract: A novel file splitting technique for the reduction of the nth-order entropy of text files is proposed. The technique is based on mapping the original text file into a non-ASCII binary file using a new codeword assignment method and then the resulting binary file is split into several subfiles each contains one or more bits from each codeword of the mapped binary file. The statistical properties of the subfiles are studied and it is found that they reflect the statistical properties of the original text file which is not the case when the ASCII code is used as a mapper. The nth-order entropy of these subfiles are determined and it is found that the sum of their entropies is less than that of the original text file for the same values of extensions. These interesting statistical properties of the resulting subfiles can be used to achieve better compression ratios when conventional compression techniques are applied to these subfiles individually and on a bit-wise basis rather than on character-wise basis.
Abstract: A combination of photosynthetic bacteria along with
anaerobic acidogenic bacteria is an ideal option for efficient
hydrogen production. In the present study, the optimum
concentration of substrates for the growth of Rhodobacter
sphaeroides was found by response surface methodology. The
optimum combination of three individual fatty acids was determined
by Box Behnken design. Increase of volatile fatty acid concentration
decreased the growth. Combination of sodium acetate and sodium
propionate was most significant for the growth of the organism. The
results showed that a maximum biomass concentration of 0.916 g/l
was obtained when the concentrations of acetate, propionate and
butyrate were 0.73g/l,0.99g/l and 0.799g/l, respectively. The growth
was studied under an optimum concentration of volatile fatty acids
and at a light intensity of 3000 lux, initial pH of 7 and a temperature
of 35°C.The maximum biomass concentration of 0.92g/l was
obtained which verified the practicability of this optimization.
Abstract: In this paper, the process of obtaining Q and R
matrices for optimal pitch aircraft control system has been described.
Since the innovation of optimal control method, the determination of
Q and R matrices for such system has not been fully specified. The
value of Q and R for optimal pitch aircraft control application, have
been simulated and calculated. The suitable results for Q and R have
been observed through the performance index (PI). If the PI is small
“enough", we would say the Q & R values are suitable for that
certain type of optimal control system. Moreover, for the same value
of PI, we could have different Q and R sets. Due to the rule-free
determination of Q and R matrices, a specific method is brought to
find out the rough value of Q and R referring to rather small value of
PI.
Abstract: The problem of wastewater treatment in Egypt is a two-fold problem; the first part concerning the existing rural areas, the second one dealing with new industrial/domestic areas. In Egypt several agricultural projects have been initiated by the government and the private sector as well, in order to change its infrastructure. As a reliable energy source, photovoltaic pumping systems have contributed to supply water for local rural communities worldwide; they can also be implemented to solve the problem “wastewater environment pollution". The solution of this problem can be categorised as recycle process. In addition, because of regional conditions past technologies are being reexamined to select a smallscale treatment system requiring low construction and maintenance costs. This paper gives the design guidelines of a Photovoltaic Small- Scale Wastewater Treatment Plant (PVSSWTP) based on technologies that can be transferred.
Abstract: Network coding has recently attracted attention as an efficient technique in multicast/broadcast services. The problem of finding the optimal network coding mechanism maximizing the bandwidth efficiency is hard to solve and hard to approximate. Lots of network coding-based schemes have been suggested in the literature to improve the bandwidth efficiency, especially network coding-based automatic repeat request (NCARQ) schemes. However, existing schemes have several limitations which cause the performance degradation in resource limited systems. To improve the performance in resource limited systems, we propose NCARQ with overlapping selection (OS-NCARQ) scheme. The advantages of OS-NCARQ scheme over the traditional ARQ scheme and existing NCARQ schemes are shown through the analysis and simulations.
Abstract: CloudSim is a useful tool to simulate the cloud
environment. It shows the service availability, the power consumption,
and the network traffic of services on the cloud environment.
Moreover, it supports to calculate a network communication delay
through a network topology data easily. CloudSim allows inputting a
file of topology data, but it does not provide any generating process.
Thus, it needs the file of topology data generated from some other
tools. The BRITE is typical network topology generator. Also, it
supports various type of topology generating algorithms. If CloudSim
can include the BRITE, network simulation for clouds is easier than
existing version. This paper shows the potential of connection between
BRITE and CloudSim. Also, it proposes the direction to link between
them.
Abstract: The machining performance is determined by the
frequency characteristics of the machine-tool structure and the
dynamics of the cutting process. Therefore, the prediction of dynamic
vibration behavior of spindle tool system is of great importance for the
design of a machine tool capable of high-precision and high-speed
machining. The aim of this study is to develop a finite element model
to predict the dynamic characteristics of milling machine tool and
hence evaluate the influence of the preload of the spindle bearings. To
this purpose, a three dimensional spindle bearing model of a high
speed engraving spindle tool was created. In this model, the rolling
interfaces with contact stiffness defined by Harris model were used to
simulate the spindle bearing components. Then a full finite element
model of a vertical milling machine was established by coupling the
spindle tool unit with the machine frame structure. Using this model,
the vibration mode that had a dominant influence on the dynamic
stiffness was determined. The results of the finite element simulations
reveal that spindle bearing with different preloads greatly affect the
dynamic behavior of the spindle tool unit and hence the dynamic
responses of the vertical column milling system. These results were
validated by performing vibration on the individual spindle tool unit
and the milling machine prototype, respectively. We conclude that
preload of the spindle bearings is an important component affecting
the dynamic characteristics and machining performance of the entire
vertical column structure of the milling machine.