Abstract: There are little subjects in macroeconomics that are so
widely discussed, but at the same time controversial and without a
clear solution such as the choice of exchange rate regime. National
authorities need to take into consideration numerous fundamentals,
trying to fulfil goals of economic growth, low and stable inflation
and international stability. This paper focuses on the countries of ex-
Yugoslavia and their exchange rate history as independent states. We
follow the development of the regimes in 6 countries during the
transition through the financial crisis of the second part of the 2000s
to the prospects of their final goal: full membership in the European
Union. Main question is to what extent has the exchange regime
contributed to their economic success, considering other objective
factors.
Abstract: Morphological operators transform the original image
into another image through the interaction with the other image of
certain shape and size which is known as the structure element.
Mathematical morphology provides a systematic approach to analyze
the geometric characteristics of signals or images, and has been
applied widely too many applications such as edge detection,
objection segmentation, noise suppression and so on. Fuzzy
Mathematical Morphology aims to extend the binary morphological
operators to grey-level images. In order to define the basic
morphological operations such as fuzzy erosion, dilation, opening
and closing, a general method based upon fuzzy implication and
inclusion grade operators is introduced. The fuzzy morphological
operations extend the ordinary morphological operations by using
fuzzy sets where for fuzzy sets, the union operation is replaced by a
maximum operation, and the intersection operation is replaced by a
minimum operation.
In this work, it consists of two articles. In the first one, fuzzy set
theory, fuzzy Mathematical morphology which is based on fuzzy
logic and fuzzy set theory; fuzzy Mathematical operations and their
properties will be studied in details. As a second part, the application
of fuzziness in Mathematical morphology in practical work such as
image processing will be discussed with the illustration problems.
Abstract: This paper discusses a method for improving accuracy
of fuzzy-rule-based classifiers using particle swarm optimization
(PSO). Two different fuzzy classifiers are considered and optimized.
The first classifier is based on Mamdani fuzzy inference system
(M_PSO fuzzy classifier). The second classifier is based on Takagi-
Sugeno fuzzy inference system (TS_PSO fuzzy classifier). The
parameters of the proposed fuzzy classifiers including premise
(antecedent) parameters, consequent parameters and structure of
fuzzy rules are optimized using PSO. Experimental results show that
higher classification accuracy can be obtained with a lower number
of fuzzy rules by using the proposed PSO fuzzy classifiers. The
performances of M_PSO and TS_PSO fuzzy classifiers are compared
to other fuzzy based classifiers
Abstract: This paper presented the technique of robot control by event-related potentials (ERPs) of brain waves. Based on the proposed technique, severe physical disabilities can free browse outside world. A specific component of ERPs, N2P3, was found and used to control the movement of robot and the view of camera on the designed brain-computer interface (BCI). Users only required watching the stimuli of attended button on the BCI, the evoked potentials of brain waves of the target button, N2P3, had the greatest amplitude among all control buttons. An experimental scene had been constructed that the robot required walking to a specific position and move the view of camera to see the instruction of the mission, and then completed the task. Twelve volunteers participated in this experiment, and experimental results showed that the correct rate of BCI control achieved 80% and the average of execution time was 353 seconds for completing the mission. Four main contributions included in this research: (1) find an efficient component of ERPs, N2P3, for BCI control, (2) embed robot's viewpoint image into user interface for robot control, (3) design an experimental scene and conduct the experiment, and (4) evaluate the performance of the proposed system for assessing the practicability.
Abstract: The objective of this paper is to design a model of human vital sign prediction for decreasing prediction error by using two states mapping based time series neural network BP (back-propagation) model. Normally, lot of industries has been applying the neural network model by training them in a supervised manner with the error back-propagation algorithm for time series prediction systems. However, it still has a residual error between real value and prediction output. Therefore, we designed two states of neural network model for compensation of residual error which is possible to use in the prevention of sudden death and metabolic syndrome disease such as hypertension disease and obesity. We found that most of simulations cases were satisfied by the two states mapping based time series prediction model compared to normal BP. In particular, small sample size of times series were more accurate than the standard MLP model. We expect that this algorithm can be available to sudden death prevention and monitoring AGENT system in a ubiquitous homecare environment.
Abstract: Contemporary science and technologies largely widen
the gap between the spiritual and rational of the society. Industrial
and technological breakthroughs might radically affect most
processes in the society, thus losing the cultural heritage. The
thinkers recognized the dangers of the decadence in the first place. In
the present article the ways of preserving cultural heritage have been
investigated. Memory has always been a necessary condition for selfidentification,
- continuity is based on this. The authors have
supported the hypothesis that continuity and ethnic memory are the
very mechanisms that preserve cultural heritage. Such problemformulating
will facilitate another, new look at the material, spiritual
and arts spheres of the cultural heritage of numerous ethnic groups.
The fundamental works by major European and Kazakh scientists
have been taken as a basis for the research done.
Abstract: Thermal water hammer is a special type of water
hammer which rarely occurs in heat exchangers. In biphasic fluids, if
steam bubbles are surrounded by condensate, regarding lower
condensate temperature than steam, they will suddenly collapse. As a
result, the vacuum caused by an extreme change in volume lead to
movement of the condensates in all directions and their collision the
force produced by this collision leads to a severe stress in the pipe
wall. This phenomenon is a special type of water hammer. According
to fluid mechanics, this phenomenon is a particular type of transient
flows during which abrupt change of fluid leads to sudden pressure
change inside the tube. In this paper, the mechanism of abrupt failure
of 80 tubes of 481 tubes of a methanol heat exchanger is discussed.
Initially, due to excessive temperature differences between heat
transfer fluids and simultaneous failure of 80 tubes, thermal shock
was presupposed as the reason of failure. Deeper investigation on
cross-section of failed tubes showed that failure was, ductile type of
failure, so the first hypothesis was rejected. Further analysis and more
accurate experiments revealed that failure of tubes caused by thermal
water hammer. Finally, the causes of thermal water hammer and
various solutions to avoid such mechanism are discussed.
Abstract: The research focuses on the effects of polyphenols
extracted from Sambucus nigra fruit, using an experimental arterial
hypertension pattern, as well as their influence on the oxidative
stress. The results reveal the normalization of the reduced glutathion
concentration, as well as a considerable reduction in the
malondialdehide serum concentration by the polyphenolic protection.
The rat blood pressure values were recorded using a CODATM
system, which uses a non-invasive blood pressure measuring method.
All the measured blood pressure components revealed a biostatistically
significant (p
Abstract: In this paper, we propose a novel adaptive
spatiotemporal filter that utilizes image sequences in order to remove
noise. The consecutive frames include: current, previous and next
noisy frames. The filter proposed in this paper is based upon the
weighted averaging pixels intensity and noise variance in image
sequences. It utilizes the Appropriate Number of Consecutive Frames
(ANCF) based on the noisy pixels intensity among the frames. The
number of consecutive frames is adaptively calculated for each
region in image and its value may change from one region to another
region depending on the pixels intensity within the region. The
weights are determined by a well-defined mathematical criterion,
which is adaptive to the feature of spatiotemporal pixels of the
consecutive frames. It is experimentally shown that the proposed
filter can preserve image structures and edges under motion while
suppressing noise, and thus can be effectively used in image
sequences filtering. In addition, the AWA filter using ANCF is
particularly well suited for filtering sequences that contain segments
with abruptly changing scene content due to, for example, rapid
zooming and changes in the view of the camera.
Abstract: In reality, the process observations are away from the assumption that are normal distributed. The observations could be skew distributions which should use an asymmetric chart rather than symmetric chart. Consequently, this research aim to study the robustness of the asymmetric Tukey’s control chart for skew and non-skew distributions as Lognormal and Laplace distributions. Furthermore, the performances in detecting of a change in parameter of asymmetric and symmetric Tukey’s control charts are compared by Average ARL (AARL). The results found that the asymmetric performs better than symmetric Tukey’s control chart for both cases of skew and non-skew process observation.
Abstract: From year to year, the incidence of different diseases is increasing in humans, and the cause is inadequate intake of dietary fibre, vitamins, and minerals. One of the possibilities to take care of your health preventively is including in the diet products with increased dietary fibre, vitamin, and mineral content.Jerusalem artichoke powder (JAP) made from Jerusalem artichoke (Helianthus tuberosus L) roots is a valuable product. By adding it to pastry goods, we can obtain a fibre-rich food that could be healthier and an excellent alternative to the classical pastry products of this kind.Experiments were carried out at the Faculty of Food Technology of Latvia University of Agriculture (LLU). Results of experiments showed that addition of Jerusalem artichoke powder has significant impact on all the studied pastry products nutritional value (p
Abstract: The paper presents an applied study of a multivariate AR(p) process fitted to daily data from U.S. commodity futures markets with the use of Bayesian statistics. In the first part a detailed description of the methods used is given. In the second part two BVAR models are chosen one with assumption of lognormal, the second with normal distribution of prices conditioned on the parameters. For a comparison two simple benchmark models are chosen that are commonly used in todays Financial Mathematics. The article compares the quality of predictions of all the models, tries to find an adequate rate of forgetting of information and questions the validity of Efficient Market Hypothesis in the semi-strong form.
Abstract: Autoregressive Moving average (ARMA) is a parametric based method of signal representation. It is suitable for problems in which the signal can be modeled by explicit known source functions with a few adjustable parameters. Various methods have been suggested for the coefficients determination among which are Prony, Pade, Autocorrelation, Covariance and most recently, the use of Artificial Neural Network technique. In this paper, the method of using Artificial Neural network (ANN) technique is compared with some known and widely acceptable techniques. The comparisons is entirely based on the value of the coefficients obtained. Result obtained shows that the use of ANN also gives accurate in computing the coefficients of an ARMA system.
Abstract: In this study, an experimental investigation was carried
out to fix CO2 into the electronic arc furnace (EAF) reducing slag from
stainless steelmaking process under wet grinding. The slag was ground
by the vibrating ball mill with the CO2 and pure water. The reaction
behavior was monitored with constant pressure method, and the
change of CO2 volume in the experimental system with grinding time
was measured. It was found that the CO2 absorption occurred as soon
as the grinding started. The CO2 absorption under wet grinding was
significantly larger than that under dry grinding. Generally, the
amount of CO2 absorption increased as the amount of water, the
amount of slag, the diameter of alumina ball and the initial pressure of
CO2 increased. However, the initial absorption rate was scarcely
influenced by the experimental conditions except for the initial CO2
pressure. According to this research, the CO2 reacted with the CaO
inside the slag to form CaCO3.
Abstract: In this paper, we rely on the story of the late British
weapons inspector David Kelly to illustrate how sensemaking can
inform the study of the ethics of suppression of dissent. Using
archival data, we reconstruct Dr. Kelly-s key responsibilities as a
weapons inspector and government employee. We begin by clarifying
the concept of dissent and how it is a useful organizational process.
We identify the various ways that dissent has been discussed in the
organizational literature and reconsider the process of sensemaking.
We conclude that suppression of opinions that deviate from the
majority is part of the identity maintenance of the sensemaking
process. We illustrate the prevention of dissent in organizations
consists of a set of unsatisfactory trade-offs.
Abstract: In this study, a robust intelligent backstepping tracking control (RIBTC) system combined with adaptive output recurrent cerebellar model articulation control (AORCMAC) and H∞ control technique is proposed for wheeled inverted pendulums (WIPs) real-time control with exact system dynamics unknown. Moreover, a robust H∞ controller is designed to attenuate the effect of the residual approximation errors and external disturbances with desired attenuation level. The experimental results indicate that the WIPs can stand upright stably when using the proposed RIBTC.
Abstract: In this paper, we propose a multiple objective optimization model with respect to portfolio selection problem for investors looking forward to diversify their equity investments in a number of equity markets. Based on Markowitz-s M-V model we developed a Fuzzy Mixed Integer Multi-Objective Nonlinear Programming Problem (FMIMONLP) to maximize the investors- future gains on equity markets, reach the optimal proportion of the budget to be invested in different equities. A numerical example with a comprehensive analysis on artificial data from several equity markets is presented in order to illustrate the proposed model and its solution method. The model performed well compared with the deterministic version of the model.
Abstract: We propose a novel prioritized limited
processor-sharing (PS) rule and a simulation algorithm for the performance evaluation of this rule. The performance measures of practical interest are evaluated using this algorithm. Suppose that there
are two classes and that an arriving (class-1 or class-2) request encounters n1 class-1 and n2 class-2 requests (including the arriving
one) in a single-server system. According to the proposed rule, class-1
requests individually and simultaneously receive m / (m * n1+ n2) of the service-facility capacity, whereas class-2 requests receive 1 / (m *n1 + n2) of it, if m * n1 + n2 ≤ C. Otherwise (m * n1 + n2 > C), the arriving request will be queued in the corresponding class waiting
room or rejected. Here, m (1) denotes the priority ratio, and C ( ∞), the service-facility capacity. In this rule, when a request arrives at [or
departs from] the system, the extension [shortening] of the remaining
sojourn time of each request receiving service can be calculated using
the number of requests of each class and the priority ratio. Employing
a simulation program to execute these events and calculations enables
us to analyze the performance of the proposed prioritized limited PS
rule, which is realistic in a time-sharing system (TSS) with a
sufficiently small time slot. Moreover, this simulation algorithm is
expanded for the evaluation of the prioritized limited PS system with
N 3 priority classes.
Abstract: The proper selection of the AC-side passive filter
interconnecting the voltage source converter to the power supply is
essential to obtain satisfactory performances of an active power filter
system. The use of the LCL-type filter has the advantage of
eliminating the high frequency switching harmonics in the current
injected into the power supply. This paper is mainly focused on
analyzing the influence of the interface filter parameters on the active
filtering performances. Some design aspects are pointed out. Thus,
the design of the AC interface filter starts from transfer functions by
imposing the filter performance which refers to the significant current
attenuation of the switching harmonics without affecting the
harmonics to be compensated. A Matlab/Simulink model of the entire
active filtering system including a concrete nonlinear load has been
developed to examine the system performances. It is shown that a
gamma LC filter could accomplish the attenuation requirement of the
current provided by converter. Moreover, the existence of an optimal
value of the grid-side inductance which minimizes the total harmonic
distortion factor of the power supply current is pointed out.
Nevertheless, a small converter-side inductance and a damping
resistance in series with the filter capacitance are absolutely needed
in order to keep the ripple and oscillations of the current at the
converter side within acceptable limits. The effect of change in the
LCL-filter parameters is evaluated. It is concluded that good active
filtering performances can be achieved with small values of the
capacitance and converter-side inductance.
Abstract: Artificial Intelligence (AI) methods are increasingly being used for problem solving. This paper concerns using AI-type learning machines for power quality problem, which is a problem of general interest to power system to provide quality power to all appliances. Electrical power of good quality is essential for proper operation of electronic equipments such as computers and PLCs. Malfunction of such equipment may lead to loss of production or disruption of critical services resulting in huge financial and other losses. It is therefore necessary that critical loads be supplied with electricity of acceptable quality. Recognition of the presence of any disturbance and classifying any existing disturbance into a particular type is the first step in combating the problem. In this work two classes of AI methods for Power quality data mining are studied: Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs). We show that SVMs are superior to ANNs in two critical respects: SVMs train and run an order of magnitude faster; and SVMs give higher classification accuracy.