Abstract: Most integrated inertial navigation systems (INS) and
global positioning systems (GPS) have been implemented using the
Kalman filtering technique with its drawbacks related to the need for
predefined INS error model and observability of at least four
satellites. Most recently, a method using a hybrid-adaptive network
based fuzzy inference system (ANFIS) has been proposed which is
trained during the availability of GPS signal to map the error
between the GPS and the INS. Then it will be used to predict the
error of the INS position components during GPS signal blockage.
This paper introduces a genetic optimization algorithm that is used to
update the ANFIS parameters with respect to the INS/GPS error
function used as the objective function to be minimized. The results
demonstrate the advantages of the genetically optimized ANFIS for
INS/GPS integration in comparison with conventional ANFIS
specially in the cases of satellites- outages. Coping with this problem
plays an important role in assessment of the fusion approach in land
navigation.
Abstract: The comparative analysis of different taxonomic
groups of microorganisms isolated from dark chernozem soils under
different agricultures (alfalfa, melilot, sainfoin, soybean, rapeseed) at
Almaty region of Kazakhstan was conducted. It was shown that the
greatest number of micromycetes was typical to the soil planted with
alfalfa and canola. Species diversity of micromycetes markedly
decreases as it approaches the surface of the root, so that the species
composition in the rhizosphere is much more uniform than in the
virgin soil. Promising strains of microscopic fungi and yeast with
plant growth-promoting activity to agricultures were selected. Among
the selected fungi there are representatives of Penicillium bilaiae,
Trichoderma koningii, Fusarium equiseti, Aspergillus ustus. The
highest rates of growth and development of seedlings of plants
observed under the influence of yeasts Aureobasidium pullulans,
Rhodotorula mucilaginosa, Metschnikovia pulcherrima. Using
molecular - genetic techniques confirmation of the identification
results of selected micromycetes was conducted.
Abstract: The studies concerned an effect of six variants of ion
exchange substrate (nutrient carriers with a different potential impact
on pH of soil solution) on vegetation of orchard grass during two
different periods (42 and 84 days). In the pot experiment plants were
grown on sand (model of degraded soil) and six mixtures of sand and
2% (v/v) additions of particular variants of ion exchange substrate
(with pH ranged from 5.5 to 8.0). The study results showed that the
addition of the substrate at pH=6.5 caused the highest increase in
plant yield after shorter vegetation period whereas the addition of the
substrate at pH=5.5 increased dry stem and root biomass of orchard
grass after longer vegetation period. Thus, the ion exchange substrate
at pH=6.5 can be recommended for restoration of exhausted soils
when shorter vegetation period is planned; the ion exchange substrate
at pH=5.5 can be used for the same purpose when longer periods of
vegetative growth are considered.
Abstract: Automated discovery of Rule is, due to its applicability, one of the most fundamental and important method in KDD. It has been an active research area in the recent past. Hierarchical representation allows us to easily manage the complexity of knowledge, to view the knowledge at different levels of details, and to focus our attention on the interesting aspects only. One of such efficient and easy to understand systems is Hierarchical Production rule (HPRs) system. A HPR, a standard production rule augmented with generality and specificity information, is of the following form: Decision If < condition> Generality Specificity . HPRs systems are capable of handling taxonomical structures inherent in the knowledge about the real world. This paper focuses on the issue of mining Quantified rules with crisp hierarchical structure using Genetic Programming (GP) approach to knowledge discovery. The post-processing scheme presented in this work uses Quantified production rules as initial individuals of GP and discovers hierarchical structure. In proposed approach rules are quantified by using Dempster Shafer theory. Suitable genetic operators are proposed for the suggested encoding. Based on the Subsumption Matrix(SM), an appropriate fitness function is suggested. Finally, Quantified Hierarchical Production Rules (HPRs) are generated from the discovered hierarchy, using Dempster Shafer theory. Experimental results are presented to demonstrate the performance of the proposed algorithm.
Abstract: To determine if the murine insulinoma, β-TC-6, is a
suitable substitute for primary pancreatic β-cells in the study of β-
cell functional heterogeneity, we used three distinct functional assays
to ascertain the cell line-s response to glucose or a glucose analog.
These assays include: (i) a 2-NBDG uptake assay; (ii) a calcium
influx assay, and; (iii) a quinacrine secretion assay. We show that a
population of β-TC-6 cells endocytoses the glucose analog, 2-
NBDG, at different rates, has non-uniform intracellular calcium ion
concentrations and releases quinacrine at different rates when
challenged with glucose. We also measured the Km for β-TC-6
glucose uptake to be 46.9 mM and the Vm to be 8.36 x 10-5
mmole/million cells/min. These data suggest that β-TC-6 might be
used as an alternative to primary pancreatic β-cells for the study of
glucose-dependent β-cell functional heterogeneity.
Abstract: Near-infrared (NIR) spectroscopy is a widely used
method for material identification for laboratory and industrial applications.
While standard spectrometers only allow measurements at
one sampling point at a time, NIR Spectral Imaging techniques can
measure, in real-time, both the size and shape of an object as well as
identify the material the object is made of. The online classification
and sorting of recovered paper with NIR Spectral Imaging (SI)
is used with success in the paper recycling industry throughout
Europe. Recently, the globalisation of the recycling material streams
caused that water-based flexographic-printed newspapers mainly from
UK and Italy appear also in central Europe. These flexo-printed
newspapers are not sufficiently de-inkable with the standard de-inking
process originally developed for offset-printed paper. This de-inking
process removes the ink from recovered paper and is the fundamental
processing step to produce high-quality paper from recovered paper.
Thus, the flexo-printed newspapers are a growing problem for the
recycling industry as they reduce the quality of the produced paper
if their amount exceeds a certain limit within the recovered paper
material.
This paper presents the results of a research project for the
development of an automated entry inspection system for recovered
paper that was jointly conducted by CTR AG (Austria) and PTS
Papiertechnische Stiftung (Germany). Within the project an NIR
SI prototype for the identification of flexo-printed newspaper has
been developed. The prototype can identify and sort out flexoprinted
newspapers in real-time and achieves a detection accuracy
for flexo-printed newspaper of over 95%. NIR SI, the technology the
prototype is based on, allows the development of inspection systems
for incoming goods in a paper production facility as well as industrial
sorting systems for recovered paper in the recycling industry in the
near future.
Abstract: This paper explores transformation of higher
education system in Kazakhstan since 1991. The research unravels
successful experience in the field and challenges. It covers issues of institutional change, faculty, research, university, funding, standards
and leadership. The paper offers recommendations in improving state of art in higher educational institutions of Kazakhstan based on
international approaches and local realities.
Abstract: A new estimator for evolutionary spectrum (ES) based
on short time Fourier transform (STFT) and modified group delay
function (MGDF) by signal decomposition (SD) is proposed. The
STFT due to its built-in averaging, suppresses the cross terms and the
MGDF preserves the frequency resolution of the rectangular window
with the reduction in the Gibbs ripple. The present work overcomes
the magnitude distortion observed in multi-component non-stationary
signals with STFT and MGDF estimation of ES using SD. The SD is
achieved either through discrete cosine transform based harmonic
wavelet transform (DCTHWT) or perfect reconstruction filter banks
(PRFB). The MGDF also improves the signal to noise ratio by
removing associated noise. The performance of the present method is
illustrated for cross chirp and frequency shift keying (FSK) signals,
which indicates that its performance is better than STFT-MGDF
(STFT-GD) alone. Further its noise immunity is better than STFT.
The SD based methods, however cannot bring out the frequency
transition path from band to band clearly, as there will be gap in the
contour plot at the transition. The PRFB based STFT-SD shows good
performance than DCTHWT decomposition method for STFT-GD.
Abstract: An approach of design of stable of control systems with ultimately wide ranges of uncertainly disturbed parameters is offered. The method relies on using of nonlinear structurally stable functions from catastrophe theory as controllers. Theoretical part presents an analysis of designed nonlinear second-order control systems. As more important the integrators in series, canonical controllable form and Jordan forms are considered. The analysis resumes that due to added controllers systems become stable and insensitive to any disturbance of parameters. Experimental part presents MATLAB simulation of design of control systems of epidemic spread, aircrafts angular motion and submarine depth. The results of simulation confirm the efficiency of offered method of design. KeywordsCatastrophes, robust control, simulation, uncertain parameters.
Abstract: Segmentation of a color image composed of different
kinds of regions can be a hard problem, namely to compute for an
exact texture fields. The decision of the optimum number of
segmentation areas in an image when it contains similar and/or un
stationary texture fields. A novel neighborhood-based segmentation
approach is proposed. A genetic algorithm is used in the proposed
segment-pass optimization process. In this pass, an energy function,
which is defined based on Markov Random Fields, is minimized. In
this paper we use an adaptive threshold estimation method for image
thresholding in the wavelet domain based on the generalized
Gaussian distribution (GGD) modeling of sub band coefficients. This
method called Normal Shrink is computationally more efficient and
adaptive because the parameters required for estimating the threshold
depend on sub band data energy that used in the pre-stage of
segmentation. A quad tree is employed to implement the multi
resolution framework, which enables the use of different strategies at
different resolution levels, and hence, the computation can be
accelerated. The experimental results using the proposed
segmentation approach are very encouraging.
Abstract: increased competition and increased costs of
designing made it important for the firms to identify the right
products and the right methods for manufacturing the products. Firms
should focus on customers and identify customer demands directly to
design the right products. Several management methods and
techniques that are currently available improve one or more functions
or processes in an industry and do not take the complete product life
cycle into consideration. On the other hand target costing is a method
/ philosophy that takes financial, manufacturing and customer aspects
into consideration during designing phase and helps firms in making
product design decisions to increase the profit / value of the
company. It uses various techniques to identify customer demands, to
decrease costs of manufacturing and finally to achieve strategic goals.
Target Costing forms an integral part of total product design /
redesign based on strategic plans.
Abstract: The efficient use of available licensed spectrum is
becoming more and more critical with increasing demand and usage
of the radio spectrum. This paper shows how the use of spectrum as
well as dynamic spectrum management can be effectively managed
and spectrum allocation schemes in the wireless communication
systems be implemented and used, in future. This paper would be an
attempt towards better utilization of the spectrum. This research will
focus on the decision-making process mainly, with an
assumption that the radio environment has already been sensed and
the QoS requirements for the application have been specified either
by the sensed radio environment or by the secondary user itself. We
identify and study the characteristic parameters of Cognitive Radio
and use Genetic Algorithm for spectrum allocation. Performance
evaluation is done using MATLAB toolboxes.
Abstract: An optimal control of Reverse Osmosis (RO) plant is
studied in this paper utilizing the auto tuning concept in conjunction
with PID controller. A control scheme composing an auto tuning
stochastic technique based on an improved Genetic Algorithm (GA) is
proposed. For better evaluation of the process in GA, objective
function defined newly in sense of root mean square error has been
used. Also in order to achieve better performance of GA, more
pureness and longer period of random number generation in operation
are sought. The main improvement is made by replacing the uniform
distribution random number generator in conventional GA technique
to newly designed hybrid random generator composed of Cauchy
distribution and linear congruential generator, which provides
independent and different random numbers at each individual steps in
Genetic operation. The performance of newly proposed GA tuned
controller is compared with those of conventional ones via simulation.
Abstract: Early Intervention Program (EIP) is required to
improve the overall development of children with Trisomy 21 (Down
syndrome). In order to help trainer and parent in the implementation
of EIP, a support system has been developed. The support system is
able to screen data automatically, store and analyze data, generate
individual EIP (curriculum) with optimal training duration and to
generate training automatically. The system consists of hardware and
software where the software has been implemented using Java
language and Linux Fedora. The software has been tested to ensure the
functionality and reliability. The prototype has been also tested in
Down syndrome centers. Test result shows that the system is reliable
to be used for generation of an individual curriculum which includes
the training program to improve the motor, cognitive, and combination
abilities of Down syndrome children under 6 years.
Abstract: Matrix metalloproteinases (MMP) are a class of
structural and functional related enzymes involved in altering the
natural elements of the extracellular matrix. Most of the MMP
structures are cristalographycally determined and published in
WorldWide ProteinDataBank, isolated, in full structure or bound to
natural or synthetic inhibitors. This study proposes an algorithm to
replace missing crystallographic structures in PDB database. We
have compared the results of a chosen docking algorithm with a
known crystallographic structure in order to validate enzyme sites
reconstruction there where crystallographic data are missing.
Abstract: To judge whether the memristor can be interpreted as
the fourth fundamental circuit element, we propose a variable-relation
criterion of fundamental circuit elements. According to the criterion,
we investigate the nature of three fundamental circuit elements and the
memristor. From the perspective of variables relation, the memristor
builds a direct relation between the voltage across it and the current
through it, instead of a direct relation between the magnetic flux and
the charge. Thus, it is better to characterize the memristor and the
resistor as two special cases of the same fundamental circuit element,
which is the memristive system in Chua-s new framework. Finally, the
definition of memristor is refined according to the difference between
the magnetic flux and the flux linkage.
Abstract: This paper aims to study the methodology of building the knowledge of planning adequate punches in order to complete the task of strip layout for shearing processes, using progressive dies. The proposed methodology uses die design rules and characteristics of different types of punches to classify them into five groups: prior use (the punches must be used first), posterior use (must be used last), compatible use (may be used together), sequential use (certain punches must precede some others) and simultaneous use (must be used together). With these five groups of punches, the searching space of feasible designs will be greatly reduced, and superimposition becomes a more effective method of punch layout. The superimposition scheme will generate many feasible solutions, an evaluation function based on number of stages, moment balancing and strip stability is developed for helping designers to find better solutions.
Abstract: The objective of this paper is to develop a neural
network-based residual generator to detect the fault in the actuators
for a specific communication satellite in its attitude control system
(ACS). First, a dynamic multilayer perceptron network with dynamic
neurons is used, those neurons correspond a second order linear
Infinite Impulse Response (IIR) filter and a nonlinear activation
function with adjustable parameters. Second, the parameters from the
network are adjusted to minimize a performance index specified by
the output estimated error, with the given input-output data collected
from the specific ACS. Then, the proposed dynamic neural network
is trained and applied for detecting the faults injected to the wheel,
which is the main actuator in the normal mode for the communication
satellite. Then the performance and capabilities of the proposed
network were tested and compared with a conventional model-based
observer residual, showing the differences between these two
methods, and indicating the benefit of the proposed algorithm to
know the real status of the momentum wheel. Finally, the application
of the methods in a satellite ground station is discussed.
Abstract: In this paper, based on almost periodic functional hull theory and M-matrix theory, some sufficient conditions are established for the existence and uniqueness of positive almost periodic solution for a class of BAM neural networks with time-varying delays. An example is given to illustrate the main results.
Abstract: Until recently it would have been unusual to consider classifying population movements and refugees as security problem. However, efforts at shaping our world to make ourselves secure have paradoxically led to ever greater insecurity. The feeling of uncertainty, pertinent throughout all discourses of security, has led to the creation of security production into seemingly benign routines of everyday life. Yet, the paper argues, neither of security discourses accounted for, disclosed and challenged the fundamental aporias embedded in Western security narratives. In turn, the paper aims to unpick the conventional security wisdom, which is haunted with strong ontologies, embedded in the politics of Orientalism, and (in)security nexus. The paper concludes that current security affair conceals the integral impossibility of fulfilling its very own promise of assured security. The paper also provides suggestions about alternative security discourse based on mutual dialogue.