Abstract: In this paper, the least-squares design of variable fractional-delay (VFD) finite impulse response (FIR) digital differentiators is proposed. The used transfer function is formulated so that Farrow structure can be applied to realize the designed system. Also, the symmetric characteristics of filter coefficients are derived, which leads to the complexity reduction by saving almost a half of the number of coefficients. Moreover, all the elements of related vectors or matrices for the optimal process can be represented in closed forms, which make the design easier. Design example is also presented to illustrate the effectiveness of the proposed method.
Abstract: In this research a comparison between k-epsilon and
LES model for a deoiling hydrocyclone is conducted. Flow field of
hydrocyclone is obtained by three-dimensional simulations with
OpenFOAM code. Potential of prediction for both methods of this
complex swirl flow is discussed. Large eddy simulation method
results have more similarity to experiment and its results are
presented in figures from different hydrocyclone cross sections.
Abstract: This study examined a habitat-suitability assessment method namely the Ecological Niche Factor Analysis (ENFA). A virtual species was created and then dispatched in a geographic information system model of a real landscape in three historic scenarios: (1) spreading, (2) equilibrium, and (3) overabundance. In each scenario, the virtual species was sampled and these simulated data sets were used as inputs for the ENFA to reconstruct the habitat suitability model. The 'equilibrium' scenario gives the highest quantity and quality among three scenarios. ENFA was sensitive to the distribution scenarios but not sensitive to sample sizes. The use of a virtual species proved to be a very efficient method, allowing one to fully control the quality of the input data as well as to accurately evaluate the predictive power of the analyses.
Abstract: Mammographic images and data analysis to
facilitate modelling or computer aided diagnostic (CAD) software development should best be done using a common database that can handle various mammographic image file
formats and relate these to other patient information.
This would optimize the use of the data as both primary
reporting and enhanced information extraction of research data could be performed from the single dataset. One desired
improvement is the integration of DICOM file header information into the database, as an efficient and reliable source of supplementary patient information intrinsically
available in the images.
The purpose of this paper was to design a suitable database to link and integrate different types of image files and gather common information that can be further used for research
purposes. An interface was developed for accessing, adding,
updating, modifying and extracting data from the common
database, enhancing the future possible application of the data in CAD processing.
Technically, future developments envisaged include the creation of an advanced search function to selects image files
based on descriptor combinations. Results can be further used for specific CAD processing and other research. Design of a
user friendly configuration utility for importing of the required fields from the DICOM files must be done.
Abstract: Noise level has critical effects on the diagnostic
performance of signal-averaged electrocardiogram (SAECG), because
the true starting and end points of QRS complex would be masked by
the residual noise and sensitive to the noise level. Several studies and
commercial machines have used a fixed number of heart beats
(typically between 200 to 600 beats) or set a predefined noise level
(typically between 0.3 to 1.0 μV) in each X, Y and Z lead to perform
SAECG analysis. However different criteria or methods used to
perform SAECG would cause the discrepancies of the noise levels
among study subjects. According to the recommendations of 1991
ESC, AHA and ACC Task Force Consensus Document for the use of
SAECG, the determinations of onset and offset are related closely to
the mean and standard deviation of noise sample. Hence this study
would try to perform SAECG using consistent root-mean-square
(RMS) noise levels among study subjects and analyze the noise level
effects on SAECG. This study would also evaluate the differences
between normal subjects and chronic renal failure (CRF) patients in
the time-domain SAECG parameters.
The study subjects were composed of 50 normal Taiwanese and 20
CRF patients. During the signal-averaged processing, different RMS
noise levels were adjusted to evaluate their effects on three time
domain parameters (1) filtered total QRS duration (fQRSD), (2) RMS
voltage of the last QRS 40 ms (RMS40), and (3) duration of the low
amplitude signals below 40 μV (LAS40). The study results
demonstrated that the reduction of RMS noise level can increase
fQRSD and LAS40 and decrease the RMS40, and can further increase
the differences of fQRSD and RMS40 between normal subjects and
CRF patients. The SAECG may also become abnormal due to the
reduction of RMS noise level. In conclusion, it is essential to establish
diagnostic criteria of SAECG using consistent RMS noise levels for
the reduction of the noise level effects.
Abstract: Canola is a specific edible type of rapeseed, developed
in the 1970s, which contains about 40 percent oil. This research was
carried out to determine the yield and some quality characteristics of
some winter canola cultivars during the 2010-2011 vegetation period
in Central Anatolia of Turkey. In this research; Oase, Dante,
Californium, Excalibur, Elvis, ES Hydromel, Licord, Orkan, Vectra,
Nelson, Champlain and NK Petrol winter canola varieties were used
as material. The field experiment was set up in a “Randomized
Complete Block Design” with three replications on 21 September
2010. In this research; seed yield, oil content, protein content, oil
yield and protein yield were examined.
As a result of this research; seed yield, oil content, oil yield and
protein yield (except protein content) were significant differences
between the cultivars. The highest seed yield (6348 kg ha-1) was
obtained from the NK Petrol, while the lowest seed yield (3949 kg
ha-1) was determined from the Champlain cultivar was obtained. The
highest oil content (46.73%) was observed from Oase and the lowest
value was obtained from Vectra (41.87%) cultivar. The highest oil
yield (2950 kg ha-1) was determined from NK Petrol while the least
value (1681 kg ha-1) was determined from Champlain cultivar. The
highest protein yield (1539.3 kg ha-1) was obtained from NK Petrol
and the lowest protein yield (976.5 kg ha-1) was obtained from
Champlain cultivar.
The main purpose of the cultivation of oil crops, to increase the
yield of oil per unit area. According the result of this research, NK
Petrol cultivar which ranks first with regard to both seed yield and oil
yield between cultivars as the most suitable winter canola cultivar of
local conditions.
Abstract: The new programming technologies allow for the
creation of components which can be automatically or manually
assembled to reach a new experience in knowledge understanding
and mastering or in getting skills for a specific knowledge area. The
project proposes an interactive framework that permits the creation,
combination and utilization of components that are specific to
mathematical training in high schools.
The main framework-s objectives are:
• authoring lessons by the teacher or the students; all they need
are simple operating skills for Equation Editor (or something
similar, or Latex); the rest are just drag & drop operations,
inserting data into a grid, or navigating through menus
• allowing sonorous presentations of mathematical texts and
solving hints (easier understood by the students)
• offering graphical representations of a mathematical function
edited in Equation
• storing of learning objects in a database
• storing of predefined lessons (efficient for expressions and
commands, the rest being calculations; allows a high
compression)
• viewing and/or modifying predefined lessons, according to the
curricula
The whole thing is focused on a mathematical expressions minicompiler,
storing the code that will be later used for different
purposes (tables, graphics, and optimisations).
Programming technologies used. A Visual C# .NET
implementation is proposed. New and innovative digital learning
objects for mathematics will be developed; they are capable to
interpret, contextualize and react depending on the architecture
where they are assembled.
Abstract: Religion revival including Islam in Kazakhstan represents reaction, first of all on internal social and political change, events after disintegration of the USSR. Process of revival of Kazakhstan Islam was accompanied as positive, so by negative tendencies. Old mosques were restored, were under construction new, Islamic schools and high schools were created, was widely studied religious the dogmatic person, the corresponding literature was published, expanded contacts with foreign Muslim brothers in the faith, the centers of the Arab-Muslim culture extended. At the same time in Kazakhstan, there are religious-political parties and movements, pursuing radical goals down to change the spiritual and cultural identity of Muslims of Kazakhstan by the forcible introduction of non-traditional religious and political, ethnic and cultural values.
Abstract: The purpose of this study was to determine the
influence of physical activity and dietary fat intake on Body Mass
Index (BMI) of lecturers within a higher learning institutionalized
setting. The study adopted a Cross-sectional Correlational Design
and included 120 lecturers selected proportionately by simple
random sampling techniques from a population of 600 lecturers. Data
was collected using questionnaires, which had sections including
physical activity checklist adopted from the international physical
activity questionnaire (IPAQ), 24-hour food recall, anthropometric
measurements mainly weight and height. Analysis involved the use
of bivariate correlations and linear regression. A significant inverse
association was registered between BMI and duration (in minutes)
spent doing moderate intense physical activity per day (r=-0.322,
p
Abstract: The stem cells have ability to differentiated
themselves through mitotic cell division and various range of
specialized cell types. Cellular differentiation is a way by which few
specialized cell develops into more specialized.This paper studies the
fundamental problem of computational schema for an artificial neural
network based on chemical, physical and biological variables of
state. By doing this type of study system could be model for a viable
propagation of various economically important stem cells
differentiation. This paper proposes various differentiation outcomes
of artificial neural network into variety of potential specialized cells
on implementing MATLAB version 2009. A feed-forward back
propagation kind of network was created to input vector (five input
elements) with single hidden layer and one output unit in output
layer. The efficiency of neural network was done by the assessment
of results achieved from this study with that of experimental data
input and chosen target data. The propose solution for the efficiency
of artificial neural network assessed by the comparatative analysis of
“Mean Square Error" at zero epochs. There are different variables of
data in order to test the targeted results.
Abstract: The influence of extrusion parameters on surface
quality and properties of AA6061+x% vol. SiC (x = 0; 2,5; 5; 7,5;10)
composites was discussed in this paper. The averages size of
AA6061 and SiC particles were 10.6 μm and 0.42 μm, respectively.
Two series of composites (I - compacts were preheated at extrusion
temperature through 0.5 h and cooled by water directly after process;
II - compacts were preheated through 3 hours and were not cooled)
were consolidated via powder metallurgy processing and extruded by
KoBo method. High values of density for both series of composites
were achieved. Better surface quality was observed for II series of
composites. Moreover, for these composites lower (compared to I
series) but more uniform strength properties over the cross-section of
the bar were noticed. Microstructure and Young-s modulus
investigations were made.
Abstract: Appropriate ventilation in a classroom is helpful for
enhancing air exchange rate and student concentration. This study
focuses on the effects of fenestration in a four-story school building by
performing numerical simulation of a building when considering
indoor and outdoor environments simultaneously. The wind profile
function embedded in PHOENICS code was set as the inlet boundary
condition in a suburban environment. Sixteen fenestration
combinations were compared in a classroom containing thirty seats.
This study evaluates mean age of air (AGE) and airflow pattern of a
classroom on different floors. Considering both wind profile and
fenestration effects, the airflow on higher floors is channeled toward
the area near ceiling in a room and causes older mean age of air in the
breathing zone. The results in this study serve as a useful guide for
enhancing natural ventilation in a typical school building.
Abstract: The dispersion of heavy particles line in an isotropic
and incompressible three-dimensional turbulent flow has been
studied using the Kinematic Simulation techniques to find out the
evolution of the line fractal dimension. In this study, the fractal
dimension of the line is found for different cases of heavy particles
inertia (different Stokes numbers) in the absence of the particle
gravity with a comparison with the fractal dimension obtained in the
diffusion case of material line at the same Reynolds number. It can
be concluded for the dispersion of heavy particles line in turbulent
flow that the particle inertia affect the fractal dimension of a line
released in a turbulent flow for Stokes numbers 0.02 < St < 2. At the
beginning for small times, most of the different cases are not affected
by the inertia until a certain time, the particle response time τa, with
larger time as the particles inertia increases, the fractal dimension of
the line increases owing to the particles becoming more sensitive to
the small scales which cause the change in the line shape during its
journey.
Abstract: Optical Bursts Switching (OBS) is a relatively new
optical switching paradigm. Contention and burst loss in OBS
networks are major concerns. To resolve contentions, an interesting
alternative to discarding the entire data burst is to partially drop the
burst. Partial burst dropping is based on burst segmentation concept
that its implementation is constrained by some technical challenges,
besides the complexity added to the algorithms and protocols on both
edge and core nodes. In this paper, the burst segmentation concept is
investigated, and an implementation scheme is proposed and
evaluated. An appropriate dropping policy that effectively manages
the size of the segmented data bursts is presented. The dropping
policy is further supported by a new control packet format that
provides constant transmission overhead.
Abstract: This paper intends to identify the ethnic Kazakhstani
Koreans- political process of identity formation by exploring their
narrative and practice about the state language represented in the
course of their becoming the new citizens of a new independent state.
The Russophone Kazakhstani Koreans- inability to speak the official
language of their affiliated state is considered there as dissatisfying the
basic requirement of citizens of the independent state, so that they are
becoming marginalized from the public sphere. Their contradictory
attitude that at once demonstrates nominal reception and practical
rejection of the obligatory state language unveils a high barrier inside
between their self-language and other-language. In this paper, the
ethnic Korean group-s conflicting linguistic identity is not seen as a
free and simple choice, but as a dynamic struggle and political process
in which the subject-s past experiences and memories intersect with
the external elements of pressure.
Abstract: This study has investigated a vehicle Lumped
Parameter Model (LPM) in frontal crash. There are several ways for
determining spring and damper characteristics and type of problem
shall be considered as system identification. This study use Genetic
Algorithm (GA) procedure, being an effective procedure in case of
optimization issues, for optimizing errors, between target data
(experimental data) and calculated results (being obtained by
analytical solving). In this study analyzed model in 5-DOF then
compared our results with 5-DOF serial model. Finally, the response
of model due to external excitement is investigated.
Abstract: This paper proposes improved delay-dependent stability conditions of the linear time-delay systems of neutral type. The proposed methods employ a suitable Lyapunov-Krasovskii’s functional and a new form of the augmented system. New delay-dependent stability criteria for the systems are established in terms of Linear matrix inequalities (LMIs) which can be easily solved by various effective optimization algorithms. Numerical examples showed that the proposed method is effective and can provide less conservative results.
Abstract: Reverse engineering of full-genomic interaction networks based on compendia of expression data has been successfully applied for a number of model organisms. This study adapts these approaches for an important non-model organism: The major human fungal pathogen Candida albicans. During the infection process, the pathogen can adapt to a wide range of environmental niches and reversibly changes its growth form. Given the importance of these processes, it is important to know how they are regulated. This study presents a reverse engineering strategy able to infer fullgenomic interaction networks for C. albicans based on a linear regression, utilizing the sparseness criterion (LASSO). To overcome the limited amount of expression data and small number of known interactions, we utilize different prior-knowledge sources guiding the network inference to a knowledge driven solution. Since, no database of known interactions for C. albicans exists, we use a textmining system which utilizes full-text research papers to identify known regulatory interactions. By comparing with these known regulatory interactions, we find an optimal value for global modelling parameters weighting the influence of the sparseness criterion and the prior-knowledge. Furthermore, we show that soft integration of prior-knowledge additionally improves the performance. Finally, we compare the performance of our approach to state of the art network inference approaches.
Abstract: The response of growth and yield of rainfed-chickpea
to population density should be evaluated based on long-term
experiments to include the climate variability. This is achievable just
by simulation. In this simulation study, this evaluation was done by
running the CYRUS model for long-term daily weather data of five
locations in Iran. The tested population densities were 7 to 59 (with
interval of 2) stands per square meter. Various functions, including
quadratic, segmented, beta, broken linear, and dent-like functions,
were tested. Considering root mean square of deviations and linear
regression statistics [intercept (a), slope (b), and correlation
coefficient (r)] for predicted versus observed variables, the quadratic
and broken linear functions appeared to be appropriate for describing
the changes in biomass and grain yield, and in harvest index,
respectively. Results indicated that in all locations, grain yield tends
to show increasing trend with crowding the population, but
subsequently decreases. This was also true for biomass in five
locations. The harvest index appeared to have plateau state across
low population densities, but decreasing trend with more increasing
density. The turning point (optimum population density) for grain
yield was 30.68 stands per square meter in Isfahan, 30.54 in Shiraz,
31.47 in Kermanshah, 34.85 in Tabriz, and 32.00 in Mashhad. The
optimum population density for biomass ranged from 24.6 (in
Tabriz) to 35.3 stands per square meter (Mashhad). For harvest index
it varied between 35.87 and 40.12 stands per square meter.
Abstract: One of the determinants of a firm-s prosperity is the
customers- perceived service quality and satisfaction. While service
quality is wide in scope, and consists of various dimensions, there
may be differences in the relative importance of these dimensions in
affecting customers- overall satisfaction of service quality.
Identifying the relative rank of different dimensions of service quality
is very important in that it can help managers to find out which
service dimensions have a greater effect on customers- overall
satisfaction. Such an insight will consequently lead to more effective
resource allocation which will finally end in higher levels of
customer satisfaction. This issue – despite its criticality- has not
received enough attention so far. Therefore, using a sample of 240
bank customers in Iran, an artificial neural network is developed to
address this gap in the literature. As customers- evaluation of service
quality is a subjective process, artificial neural networks –as a brain
metaphor- may appear to have a potentiality to model such a
complicated process. Proposing a neural network which is able to
predict the customers- overall satisfaction of service quality with a
promising level of accuracy is the first contribution of this study. In
addition, prioritizing the service quality dimensions in affecting
customers- overall satisfaction –by using sensitivity analysis of
neural network- is the second important finding of this paper.