Abstract: The paper presents a part of the results obtained in a
complex research project on Romanian Grey Steppe breed, owner of
some remarkable qualities such as hardiness, longevity, adaptability,
special resistance to ban weather and diseases and included in the
genetic fund (G.D. no. 822/2008.) from Romania.
Following the researches effectuated, we identified alleles of six
loci, codifying the six types of major milk proteins: alpha-casein S1
(α S1-cz); beta-casein (β-cz); kappa-casein (K-cz); beta-lactoglobulin
(β-lg); alpha-lactalbumin (α-la) and alpha-casein S2 (α S2-cz). In
system αS1-cz allele αs1-Cn B has the highest frequency (0.700), in
system β-cz allele β-Cn A2 ( 0.550 ), in system K-cz allele k-CnA2 (
0.583 ) and heterozygote genotype AB ( 0.416 ) and BB (0.375), in
system β-lg allele β-lgA1 has the highest frequency (0.542 ) and
heterozygote genotype AB ( 0.500 ), in system α-la there is
monomorphism for allele α-la B and similarly in system αS2-cz for
allele αs2-Cn A.
The milk analysis by the isoelectric focalization technique (I.E.F.)
allowed the identification of a new allele for locus αS1-casein, for two
of the individuals under analysis, namely allele called αS1-casein
IRV. When experiments were repeated, we noticed that this is not a
proteolysis band and it really was a new allele that has not been
registered in the specialized literature so far. We identified two
heterozygote individuals, carriers of this allele, namely: BIRV and
CIRV. This discovery is extremely important if focus is laid on the
national genetic patrimony.
Abstract: This paper proposes new algorithms for the computeraided
design and manufacture (CAD/CAM) of 3D woven multi-layer
textile structures. Existing commercial CAD/CAM systems are often
restricted to the design and manufacture of 2D weaves. Those
CAD/CAM systems that do support the design and manufacture of
3D multi-layer weaves are often limited to manual editing of design
paper grids on the computer display and weave retrieval from stored
archives. This complex design activity is time-consuming, tedious
and error-prone and requires considerable experience and skill of a
technical weaver. Recent research reported in the literature has
addressed some of the shortcomings of commercial 3D multi-layer
weave CAD/CAM systems. However, earlier research results have
shown the need for further work on weave specification, weave
generation, yarn path editing and layer binding. Analysis of 3D
multi-layer weaves in this research has led to the design and
development of efficient and robust algorithms for the CAD/CAM of
3D woven multi-layer textile structures. The resulting algorithmically
generated weave designs can be used as a basis for lifting plans that
can be loaded onto looms equipped with electronic shedding
mechanisms for the CAM of 3D woven multi-layer textile structures.
Abstract: The neural network's performance can be measured by efficiency and accuracy. The major disadvantages of neural network approach are that the generalization capability of neural networks is often significantly low, and it may take a very long time to tune the weights in the net to generate an accurate model for a highly complex and nonlinear systems. This paper presents a novel Neuro-fuzzy architecture based on Extended Kalman filter. To test the performance and applicability of the proposed neuro-fuzzy model, simulation study of nonlinear complex dynamic system is carried out. The proposed method can be applied to an on-line incremental adaptive learning for the prediction of financial time series. A benchmark case studie is used to demonstrate that the proposed model is a superior neuro-fuzzy modeling technique.
Abstract: Real-time 3D applications have to guarantee
interactive rendering speed. There is a restriction for the number of
polygons which is rendered due to performance of a graphics hardware
or graphics algorithms. Generally, the rendering performance will be
drastically increased when handling only the dynamic 3d models,
which is much fewer than the static ones. Since shapes and colors of
the static objects don-t change when the viewing direction is fixed, the
information can be reused. We render huge amounts of polygon those
cannot handled by conventional rendering techniques in real-time by
using a static object image and merging it with rendering result of the
dynamic objects. The performance must be decreased as a
consequence of updating the static object image including removing
an static object that starts to move, re-rending the other static objects
being overlapped by the moving ones. Based on visibility of the object
beginning to move, we can skip the updating process. As a result, we
enhance rendering performance and reduce differences of rendering
speed between each frame. Proposed method renders total
200,000,000 polygons that consist of 500,000 dynamic polygons and
the rest are static polygons in about 100 frames per second.
Abstract: The authors present a mixed method for reducing the order of the large-scale dynamic systems. In this method, the denominator polynomial of the reduced order model is obtained by using the modified pole clustering technique while the coefficients of the numerator are obtained by Pade approximations. This method is conceptually simple and always generates stable reduced models if the original high-order system is stable. The proposed method is illustrated with the help of the numerical examples taken from the literature.
Abstract: Proteins levels produced by bacteria may be increased
in stressful surroundings, such as in the presence of antibiotics. It
appears that many antimicrobial agents or antibiotics, when used at
low concentrations, have in common the ability to activate or repress
gene transcription, which is distinct from their inhibitory effect.
There have been comparatively few studies on the potential of
antibiotics or natural compounds in nature as a specific chemical
signal that can trigger a variety of biological functions. Therefore,
this study was focusing on the effect of essential oils from
Cymbopogon flexuosus and C. nardus in regulating proteins
production by Bacillus subtilis ATCC 21332. The Minimum
Inhibition Concentrations (MICs) of both essential oils on B. subtilis
were determined by using microdilution assay, resulting 0.2% and
1.56% for each C. flexuosus and C. nardus subsequently. The
bacteria were further exposed to each essential oils at concentration
of 0.01XMIC for 2 days. The proteins were then isolated and
analyzed by sodium dodecyl sulfate polyacrylamide gel
electrophoresis (SDS-PAGE). Protein profile showed that a band
with approximate size of 250 kD was appeared for the treated
bacteria with essential oils. Thus, Bacillus subtilis ATCC 21332 in
stressful condition with the presence of essential oils at low
concentration could induce the protein production.
Abstract: In pattern recognition applications the low level
segmentation and the high level object recognition are generally
considered as two separate steps. The paper presents a method that
bridges the gap between the low and the high level object
recognition. It is based on a Bayesian network representation and
network propagation algorithm. At the low level it uses hierarchical
structure of quadratic spline wavelet image bases. The method is
demonstrated for a simple circuit diagram component identification
problem.
Abstract: In the project FleGSens, a wireless sensor network
(WSN) for the surveillance of critical areas and properties is currently developed which incorporates mechanisms to ensure information
security. The intended prototype consists of 200 sensor nodes for
monitoring a 500m long land strip. The system is focused on ensuring
integrity and authenticity of generated alarms and availability in the
presence of an attacker who may even compromise a limited number
of sensor nodes. In this paper, two of the main protocols developed
in the project are presented, a tracking protocol to provide secure
detection of trespasses within the monitored area and a protocol for secure detection of node failures. Simulation results of networks
containing 200 and 2000 nodes as well as the results of the first prototype comprising a network of 16 nodes are presented. The focus of the simulations and prototype are functional testing of the protocols
and particularly demonstrating the impact and cost of several attacks.
Abstract: We present analysis of spatial patterns of generic
disease spread simulated by a stochastic long-range correlation SIR
model, where individuals can be infected at long distance in a power
law distribution. We integrated various tools, namely perimeter,
circularity, fractal dimension, and aggregation index to characterize
and investigate spatial pattern formations. Our primary goal was to
understand for a given model of interest which tool has an advantage
over the other and to what extent. We found that perimeter and
circularity give information only for a case of strong correlation–
while the fractal dimension and aggregation index exhibit the growth
rule of pattern formation, depending on the degree of the correlation
exponent (β). The aggregation index method used as an alternative
method to describe the degree of pathogenic ratio (α). This study may
provide a useful approach to characterize and analyze the pattern
formation of epidemic spreading
Abstract: The spectral action balance equation is an equation that
used to simulate short-crested wind-generated waves in shallow water
areas such as coastal regions and inland waters. This equation consists
of two spatial dimensions, wave direction, and wave frequency which
can be solved by finite difference method. When this equation with
dominating propagation velocity terms are discretized using central
differences, stability problems occur when the grid spacing is chosen
too coarse. In this paper, we introduce the splitting modified donorcell
scheme for avoiding stability problems and prove that it is
consistent to the modified donor-cell scheme with same accuracy. The
splitting modified donor-cell scheme was adopted to split the wave
spectral action balance equation into four one-dimensional problems,
which for each small problem obtains the independently tridiagonal
linear systems. For each smaller system can be solved by direct or
iterative methods at the same time which is very fast when performed
by a multi-cores computer.
Abstract: In article are analyzed value of audiovisual sources which possesses high integrative potential and allows studying movement of information in the history - information movement from generation to the generation, in essence providing continuity of historical development and inheritance of traditions. Information thus fixed in them is considered as a source not only about last condition of society, but also significant for programming of its subsequent activity.
Abstract: In this paper we present a new method for coin
identification. The proposed method adopts a hybrid scheme using
Eigenvalues of covariance matrix, Circular Hough Transform (CHT)
and Bresenham-s circle algorithm. The statistical and geometrical
properties of the small and large Eigenvalues of the covariance
matrix of a set of edge pixels over a connected region of support are
explored for the purpose of circular object detection. Sparse matrix
technique is used to perform CHT. Since sparse matrices squeeze
zero elements and contain only a small number of non-zero elements,
they provide an advantage of matrix storage space and computational
time. Neighborhood suppression scheme is used to find the valid
Hough peaks. The accurate position of the circumference pixels is
identified using Raster scan algorithm which uses geometrical
symmetry property. After finding circular objects, the proposed
method uses the texture on the surface of the coins called texton,
which are unique properties of coins, refers to the fundamental micro
structure in generic natural images. This method has been tested on
several real world images including coin and non-coin images. The
performance is also evaluated based on the noise withstanding
capability.
Abstract: When the profile information of an existing road is
missing or not up-to-date and the parameters of the vertical
alignment are needed for engineering analysis, the engineer has to recreate
the geometric design features of the road alignment using
collected profile data. The profile data may be collected using
traditional surveying methods, global positioning systems, or digital
imagery. This paper develops a method that estimates the parameters
of the geometric features that best characterize the existing vertical
alignments in terms of tangents and the expressions of the curve, that
may be symmetrical, asymmetrical, reverse, and complex vertical
curves. The method is implemented using an Excel-based
optimization method that minimizes the differences between the
observed profile and the profiles estimated from the equations of the
vertical curve. The method uses a 'wireframe' representation of the
profile that makes the proposed method applicable to all types of
vertical curves. A secondary contribution of this paper is to introduce
the properties of the equal-arc asymmetrical curve that has been
recently developed in the highway geometric design field.
Abstract: In this paper, real-coded genetic algorithm (RCGA) optimization technique has been applied for large-scale linear dynamic multi-input-multi-output (MIMO) system. The method is based on error minimization technique where the integral square error between the transient responses of original and reduced order models has been minimized by RCGA. The reduction procedure is simple computer oriented and the approach is comparable in quality with the other well-known reduction techniques. Also, the proposed method guarantees stability of the reduced model if the original high-order MIMO system is stable. The proposed approach of MIMO system order reduction is illustrated with the help of an example and the results are compared with the recently published other well-known reduction techniques to show its superiority.
Abstract: In this work Artificial Intelligence (AI) techniques like Fuzzy logic, Genetic Algorithms and Particle Swarm Optimization have been used to improve the performance of the Automatic Generation Control (AGC) system. Instead of applying Genetic Algorithms and Particle swarm optimization independently for optimizing the parameters of the conventional AGC with PI controller, an intelligent tuned Fuzzy logic controller (acting as the secondary controller in the AGC system) has been designed. The controller gives an improved dynamic performance for both hydrothermal and thermal-thermal power systems under a variety of operating conditions.
Abstract: In the real application of active control systems to
mitigate the response of structures subjected to sever external
excitations such as earthquake and wind induced vibrations, since the
capacity of actuators is limited then the actuators saturate. Hence, in
designing controllers for linear and nonlinear structures under sever
earthquakes, the actuator saturation should be considered as a
constraint. In this paper optimal design of active controllers for
nonlinear structures by considering the actuator saturation has been
studied. To this end a method has been proposed based on defining
an optimization problem which considers the minimizing of the
maximum displacement of the structure as objective when a limited
capacity for actuator has been used as a constraint in optimization
problem. To evaluate the effectiveness of the proposed method, a
single degree of freedom (SDF) structure with a bilinear hysteretic
behavior has been simulated under a white noise ground acceleration
of different amplitudes. Active tendon control mechanism, comprised
of pre-stressed tendons and an actuator, and extended nonlinear
Newmark method based instantaneous optimal control algorithm
have been used as active control mechanism and algorithm. To
enhance the efficiency of the controllers, the weights corresponding
to displacement, velocity, acceleration and control force in the
performance index have been found by using the Distributed Genetic
Algorithm (DGA). According to the results it has been concluded
that the proposed method has been effective in considering the
actuator saturation in designing optimal controllers for nonlinear
frames. Also it has been shown that the actuator capacity and the
average value of required control force are two important factors in
designing nonlinear controllers for considering the actuator
saturation.
Abstract: The Linear discriminant analysis (LDA) can be
generalized into a nonlinear form - kernel LDA (KLDA) expediently
by using the kernel functions. But KLDA is often referred to a general
eigenvalue problem in singular case. To avoid this complication, this
paper proposes an iterative algorithm for the two-class KLDA. The
proposed KLDA is used as a nonlinear discriminant classifier, and the
experiments show that it has a comparable performance with SVM.
Abstract: The successful use of CDMA technology is based on
the construction of large families of encoding sequences with good
correlation properties. This paper discusses PN sequence generation
based on Residue Arithmetic with an effort to improve the performance
of existing interference-limited CDMA technology for mobile
cellular systems. All spreading codes with residual number system
proposed earlier did not consider external interferences, multipath
propagation, Doppler effect etc. In literature the use of residual
arithmetic in DS-CDMA was restricted to encoding of already spread
sequence; where spreading of sequence is done by some existing
techniques. The novelty of this paper is the use of residual number
system in generation of the PN sequences which is used to spread
the message signal. The significance of cross-correlation factor in
alleviating multi-access interference is also discussed. The RNS based
PN sequence has superior performance than most of the existing
codes that are widely used in DS-CDMA applications. Simulation
results suggest that the performance of the proposed system is
superior to many existing systems.
Abstract: Many medical devices are driven by motor pumps. Some researchers reported that the vibration mainly affected medical devices using a motor pump. The purpose of this study was to examine the effect of stiffness and damping coefficient in a 3-dimensional (3D) model of a motor pump and spring. In the present paper, experimental and mathematical tests for the moments of inertia of the 3D model and the material properties were investigated by an INSTRON machine. The response surfaces could be generated by using 3D multi-body analysis and the design of experiment method. It showed that differences in contours of the response surface were clearly found for the particular area. Displacement of the center of the motor pump was decreased at K≈2000 N/M, C≈12.5 N-sec/M. However, the frequency was increased at K≈2000 N/M, C≈15 N-sec/M. In this study, this study suggested experimental technique for vibration reduction for a motor pump in medical device. The combined method suggested in this study will greatly contribute to design of medical devices concerning vibration and noise intervention.
Abstract: Due to the non- intuitive nature of Quantum
algorithms, it becomes difficult for a classically trained person to
efficiently construct new ones. So rather than designing new
algorithms manually, lately, Genetic algorithms (GA) are being
implemented for this purpose. GA is a technique to automatically
solve a problem using principles of Darwinian evolution. This has
been implemented to explore the possibility of evolving an n-qubit
circuit when the circuit matrix has been provided using a set of
single, two and three qubit gates. Using a variable length population
and universal stochastic selection procedure, a number of possible
solution circuits, with different number of gates can be obtained for
the same input matrix during different runs of GA. The given
algorithm has also been successfully implemented to obtain two and
three qubit Boolean circuits using Quantum gates. The results
demonstrate the effectiveness of the GA procedure even when the
search spaces are large.