Abstract: In this study, it was tried to identify some heart rhythm disorders by electrocardiography (ECG) data that is taken from MIT-BIH arrhythmia database by subtracting the required features, presenting to artificial neural networks (ANN), artificial immune systems (AIS), artificial neural network based on artificial immune system (AIS-ANN) and particle swarm optimization based artificial neural network (PSO-NN) classifier systems. The main purpose of this study is to evaluate the performance of hybrid AIS-ANN and PSO-ANN classifiers with regard to the ANN and AIS. For this purpose, the normal sinus rhythm (NSR), atrial premature contraction (APC), sinus arrhythmia (SA), ventricular trigeminy (VTI), ventricular tachycardia (VTK) and atrial fibrillation (AF) data for each of the RR intervals were found. Then these data in the form of pairs (NSR-APC, NSR-SA, NSR-VTI, NSR-VTK and NSR-AF) is created by combining discrete wavelet transform which is applied to each of these two groups of data and two different data sets with 9 and 27 features were obtained from each of them after data reduction. Afterwards, the data randomly was firstly mixed within themselves, and then 4-fold cross validation method was applied to create the training and testing data. The training and testing accuracy rates and training time are compared with each other.
As a result, performances of the hybrid classification systems, AIS-ANN and PSO-ANN were seen to be close to the performance of the ANN system. Also, the results of the hybrid systems were much better than AIS, too. However, ANN had much shorter period of training time than other systems. In terms of training times, ANN was followed by PSO-ANN, AIS-ANN and AIS systems respectively. Also, the features that extracted from the data affected the classification results significantly.
Abstract: We consider the biggest challenge in speech recognition – noise reduction. Traditionally detected transient noise pulses are removed with the corrupted speech using pulse models. In this paper we propose to cope with the problem directly in Dynamic Time Warping domain. Bidirectional Dynamic Time Warping algorithm for the recognition of isolated words impacted by transient noise pulses is proposed. It uses simple transient noise pulse detector, employs bidirectional computation of dynamic time warping and directly manipulates with warping results. Experimental investigation with several alternative solutions confirms effectiveness of the proposed algorithm in the reduction of impact of noise on recognition process – 3.9% increase of the noisy speech recognition is achieved.
Abstract: Numerous studies carried out in the developed
western democratic countries have shown that the ideological
framework of the governing party has a significant influence on the
monetary policy. The executive authority consisting of a left-wing
party gives a higher weight to unemployment suppression and central
bank implements a more expansionary monetary policy. On the other
hand, right-wing governing party considers the monetary stability to
be more important than unemployment suppression and in such a
political framework the main macroeconomic objective becomes the
inflation rate reduction. The political framework conditions in the
transition countries which are new European Union (EU) members
are still highly specific in relation to the other EU member countries.
In the focus of this paper is the question whether the same
monetary policy principles are valid in these transitional countries as
well as they apply in developed western democratic EU member
countries. The data base consists of inflation rate and unemployment
rate for 11 transitional EU member countries covering the period
from 2001 to 2012. The essential information for each of these 11
countries and for each year of the observed period is right or left
political orientation of the ruling party.
In this paper we use t-statistics to test our hypothesis that there are
differences in inflation and unemployment between right and left
political orientation of the governing party. To explore the influence
of different countries, through years and different political
orientations descriptive statistics is used. Inflation and unemployment
should be strongly negatively correlated through time, which is tested
using Pearson correlation coefficient.
Regarding the fact whether the governing authority is consisted
from left or right politically oriented parties, monetary authorities
will adjust its policy setting the higher priority on lower inflation or
unemployment reduction.
Abstract: Control flow graphs are a well-known representation of
the sequential control flow structure of programs with a multitude
of applications. Not only single functions but also sets of functions
or complete programs can be modeled by control flow graphs. In
this case the size of the graphs can grow considerably and thus
makes it difficult for software engineers to analyze the control flow.
Graph reductions are helpful in this situation. In this paper we define
reductions to subsets of nodes. Since executions of programs are
represented by paths through the control flow graphs, paths should
be preserved. Furthermore, the composition of reductions makes a
stepwise analysis approach possible.
Abstract: Tsunami disaster poses a great threat to coastal infrastructures. Bridges without adequate provisions for earthquake and tsunami loading is generally vulnerable to tsunami attack. During the last two disastrous tsunami event (i.e. Indian Ocean and Japan Tsunami) a number of bridges were observed subsequent damages by tsunami waves. In this study, laboratory experiments were conducted to study the effects of perforations in bridge girder in force reduction. Results showed that significant amount of forces were reduced using perforations in girder. Approximately 10% to 18% force reductions were achieved by using about 16% perforations in bridge girder. Subsequent amount of force reductions revealed that perforations in girder are effective in reducing tsunami forces as perforations in girder let water to be passed through. Thus, less bridge damages are expected with the presence of perforations in girder during tsunami period.
Abstract: This paper describes optimal thinning of an Elliptical
Cylindrical Array (ECA) of uniformly excited isotropic antennas
which can generate directive beam with minimum relative Side Lobe
Level (SLL). The Particle Swarm Optimization (PSO) method, which
represents a new approach for optimization problems in
electromagnetic, is used in the optimization process. The PSO is used
to determine the optimal set of ‘ON-OFF’ elements that provides a
radiation pattern with maximum SLL reduction. Optimization is done
without prefixing the value of First Null Beam Width (FNBW). The
variation of SLL with element spacing of thinned array is also
reported. Simulation results show that the number of array elements
can be reduced by more than 50% of the total number of elements in
the array with a simultaneous reduction in SLL to less than -27dB.
Abstract: This study was designed for assessment of 3 types of Cysteine protease inhibitors (CPIs) fluromethylketone (FMK), vinyl sulfone (VS) and sodium nitro prussid (SNP), to define which of them is the best for curing S. mansoni infection in mice? In vitro, treated S. mansoni adult worms recorded a mortality rate after 1 hr of exposure to 500 ppm of FMK, VS and SNP as 75, 70 and 60%, respectively. FMK+PZQ treatment recorded the maximum reduction in worm burden (97.2% at 5 wk PI). VS treatment alone or combined with PZQ increases IgM, total IgG, IgG2 and IgG4 levels. In EM study, the completely implanted spines were reported in the degenerated tegument of adult worms in all groups treated with CPIs. VS+PZQ Treatment increased Igs levels but, its effect was different on worm reduction. So, it is not enough to eliminate the infection and FMK+PZQ considered the antischistosomicidal drug of choice.
Abstract: This paper proposes a particle swarm optimization (PSO) technique to solve the economic load dispatch (ELD) problems. For the ELD problem in this work, the objective function is to minimize the total fuel cost of all generator units for a given daily load pattern while the main constraints are power balance and generation output of each units. Case study in the test system of 40-generation units with 6 load patterns is presented to demonstrate the performance of PSO in solving the ELD problem. It can be seen that the optimal solution given by PSO provides the minimum total cost of generation while satisfying all the constraints and benefiting greatly from saving in power loss reduction.
Abstract: Experimental study was conducted to assess personal welding fumes exposure toward welders during an aluminum metal inert gas (MIG) process. The welding process was carried out by a welding machine attached to a Computer Numerical Control (CNC) workbench. A dummy welder was used to replicate welder during welding works and was attached with sampling pumps and filter cassettes for welding fumes sampling. Direct reading instruments to measure air velocity, humidity, temperature and particulate matter with diameter size 10µm or less (PM10) were located behind the dummy welder and parallel to the neck collar level to make sure the measured welding fumes exposure were not being influenced by other factors. Welding fumes exposure during standing and sitting position with and without the usage of local exhaust ventilation (LEV) was investigated. Welding fume samples were then digested and analyzed by using inductively coupled plasma mass spectroscopy (ICP-MS) according to ASTM D7439-08 method. The results of the study showed the welding fume exposure during sitting was lower compared to standing position. LEV helped reduce aluminum and lead exposure to acceptable levels during standing position. However during sitting position reduction of exposure was smaller. It can be concluded that welder position and the correct positioning of LEV should be implemented for effective exposure reduction.
Abstract: The gap between the selection of risk-reduction options in the railway industry and the task of their effective implementation results in compromised safety and substantial losses. An effective risk management must necessarily integrate the evaluation phases with the implementation phase. This paper proposes an essential categorisation of risk reduction measures that best addresses a standard railway industry portfolio. By categorising the risk reduction options into design, operational, procedural and technical options, it is guaranteed that the efforts of the implementation facilitators (people, processes and supporting systems) are systematically harmonised. The classification is based on an integration of fundamental principles of risk reduction in the railway industry with the systems engineering approach.
This paper argues that the use of a similar classification approach is an attribute of organisations possessing a superior level of risk-reduction readiness. The integration of the proposed rational classification structure provides a solid ground for effective risk reduction.
Abstract: In this paper, an overview of the radio over fiber (RoF) technology is provided. Obstacles for reducing the capital and operational expenses in the existing systems are discussed in various perspectives. Some possible RoF deployment scenarios for WiMAX
data transmission are proposed as a means for capital and operational
expenses reduction. IEEE 802.16a standard based end-to-end physical layer model is simulated including intensity modulated direct detection RoF technology. Finally the feasibility of RoF
technology to carry WiMAX signals between the base station and the
remote antenna units is demonstrated using the simulation results.
Abstract: In this paper we introduced new wavelet based algorithm for speckle reduction of synthetic aperture radar images, which uses combination of undecimated wavelet transformation, wiener filter (which is an adaptive filter) and mean filter. Further more instead of using existing thresholding techniques such as sure shrinkage, Bayesian shrinkage, universal thresholding, normal thresholding, visu thresholding, soft and hard thresholding, we use brute force thresholding, which iteratively run the whole algorithm for each possible candidate value of threshold and saves each result in array and finally selects the value for threshold that gives best possible results. That is why it is slow as compared to existing thresholding techniques but gives best results under the given algorithm for speckle reduction.
Abstract: Although the Vietnamese catfish farming has grown
at very high rates in recent years, the industry has also faced many
problems affecting its sustainability. This paper studies the
perceptions of catfish farmers regarding risk and risk management
strategies in their production activities. Specifically, the study aims
to measure the consequences, likelihoods, and levels of risks as well
as the efficacy of risk management in Vietnamese catfish farming.
Data for the study were collected through a sample of 261 catfish
farmers in the Mekong Delta, Vietnam using a questionnaire survey
in 2008. Results show that, in general, price and production risks
were perceived as the most important risks. Farm management and
technical measures were perceived more effective than other kinds of
risk management strategies in risk reduction. Although price risks
were rated as important risks, price risk management strategies were
not perceived as important measures for risk mitigation. The results
of the study are discussed to provide implications for various
industry stakeholders, including policy makers, processors, advisors,
and developers of new risk management strategies.
Abstract: This paper presents an algorithm of particle swarm
optimization with reduction for global optimization problems. Particle
swarm optimization is an algorithm which refers to the collective
motion such as birds or fishes, and a multi-point search algorithm
which finds a best solution using multiple particles. Particle
swarm optimization is so flexible that it can adapt to a number
of optimization problems. When an objective function has a lot of
local minimums complicatedly, the particle may fall into a local
minimum. For avoiding the local minimum, a number of particles are
initially prepared and their positions are updated by particle swarm
optimization. Particles sequentially reduce to reach a predetermined
number of them grounded in evaluation value and particle swarm
optimization continues until the termination condition is met. In order
to show the effectiveness of the proposed algorithm, we examine the
minimum by using test functions compared to existing algorithms.
Furthermore the influence of best value on the initial number of
particles for our algorithm is discussed.
Abstract: This paper features the modeling and design of a
Robust Decentralized Fast Output Sampling (RDFOS) Feedback
control technique for the active vibration control of a smart flexible
multimodel Euler-Bernoulli cantilever beams for a multivariable
(MIMO) case by retaining the first 6 vibratory modes. The beam
structure is modeled in state space form using the concept of
piezoelectric theory, the Euler-Bernoulli beam theory and the Finite
Element Method (FEM) technique by dividing the beam into 4 finite
elements and placing the piezoelectric sensor / actuator at two finite
element locations (positions 2 and 4) as collocated pairs, i.e., as
surface mounted sensor / actuator, thus giving rise to a multivariable
model of the smart structure plant with two inputs and two outputs.
Five such multivariable models are obtained by varying the
dimensions (aspect ratios) of the aluminium beam. Using model
order reduction technique, the reduced order model of the higher
order system is obtained based on dominant Eigen value retention
and the Davison technique. RDFOS feedback controllers are
designed for the above 5 multivariable-multimodel plant. The closed
loop responses with the RDFOS feedback gain and the magnitudes of
the control input are obtained and the performance of the proposed
multimodel smart structure system is evaluated for vibration control.
Abstract: For a given specific problem an efficient algorithm has been the matter of study. However, an alternative approach orthogonal to this approach comes out, which is called a reduction. In general for a given specific problem this reduction approach studies how to convert an original problem into subproblems. This paper proposes a formal modeling language to support this reduction approach in order to make a solver quickly. We show three examples from the wide area of learning problems. The benefit is a fast prototyping of algorithms for a given new problem. It is noted that our formal modeling language is not intend for providing an efficient notation for data mining application, but for facilitating a designer who develops solvers in machine learning.
Abstract: Rounding of coefficients is a common practice in
hardware implementation of digital filters. Where some coefficients
are very close to zero or one, as assumed in this paper, this rounding
action also leads to some computation reduction. Furthermore, if the
discarded coefficient is of high order, a reduced order filter is
obtained, otherwise the order does not change but computation is
reduced. In this paper, the Least Squares approximation to rounded
(or discarded) coefficient FIR filter is investigated. The result also
succinctly extended to general type of FIR filters.
Abstract: Single Minute Exchange of Dies (SMED) mainly focuses on recognition of internal and external activities. It is concerned particularly with transferring internal activities into external ones in as many numbers as possible, by also minimizing the internal ones. The validity of the method and procedures are verified by an application a Styrofoam manufacturing process where setup times are critical for time reduction. Significant time savings have been achieved with minimum investment. Further, the issues related with employer safety and ergonomics principles during die exchange are noted.
Abstract: Single crystals of Magnesium alloys such as pure Mg,
Mg-1Zn-0.5Y, Mg-0.1Y, and Mg-0.1Ce alloys were successfully
fabricated in this study by employing the modified Bridgman method.
To determine the exact orientation of crystals, pole figure
measurement using X-ray diffraction were carried out on each single
crystal. Hardness and compression tests were conducted followed by
subsequent recrysatllization annealing. Recrystallization kinetics of
Mg alloy single crystals has been investigated. Fabricated single
crystals were cut into rectangular shaped specimen and solution
treated at 400oC for 24 hrs, and then deformed in compression mode
by 30% reduction. Annealing treatment for recrystallization has been
conducted on these cold-rolled plates at temperatures of 300oC for
various times from 1 to 20 mins. The microstructure observation and
hardness measurement conducted on the recrystallized specimens
revealed that static recrystallization of ternary alloy single crystal was
very slow, while recrystallization behavior of binary alloy single
crystals appeared to be very fast.
Abstract: Pre-germinated parboiled brown rice or Khao hang (in Thai) is paddy which undergoing the processes of soaking, steaming, drying and dehusking to obtain the edible form for consumption. The objectives of this research were to study the kinetic of pre-germinated parboiled brown rice drying using fluidization technique and to study the properties of pre-germinated parboiled brown rice after drying. The dryings were performed at the different temperatures of 110, 120 and 130 oC at the bed depth of 2 cm with the air velocity of 1.98 m/s. The results found that the higher drying temperature led to the faster moisture reduction. After drying until the moisture content of pre-germinated parboiled brown rice was lower than 14%wet basis, samples were taken to determine various qualities such as percentage of head rice and L* a* b* color values. The shade drying was used as a control. The results found that the higher drying temperature resulted in the decrease of head rice percentage. For the color assessment, the trend of L* and a* values was increased with the drying temperature, while the b* value was not significantly difference (p › 0.05) by drying temperatures. However, the b value of drying by fluidized bed dryer was higher than the control.