Abstract: the article analyzes the development prospects of
education system in Kazakhstan. Education is among key sources of
culture and social mobility. Modern education must become civic
which means availability of high quality education to all people
irrespective of their racial, ethnic, religious, social, gender and any
other differences. Socially focused nature of modernization of
Kazakhstan-s society is predicated upon formation of a civic
education model in the future. Kazakhstan-s education system
undergoes intensive reforms first of all intended to achieve
international education standards and integration into the global
educational and information space.
Abstract: We discuss a theoretical conceptual framework to help
understand how the new business analytics technologies have
diffused in firms. We draw on three theoretical perspectives for this
purpose. They are innovation diffusion theory, IT Business Value
and the technology-organization-environment theory. We develop a
conceptual framework that helps understand the interlinkages among
factors affecting diffusion of business analytics and its impact on
performance.
Abstract: The design of a complete expansion that allows for
compact representation of certain relevant classes of signals is a
central problem in signal processing applications. Achieving such a
representation means knowing the signal features for the purpose of
denoising, classification, interpolation and forecasting. Multilayer
Neural Networks are relatively a new class of techniques that are
mathematically proven to approximate any continuous function
arbitrarily well. Radial Basis Function Networks, which make use of
Gaussian activation function, are also shown to be a universal
approximator. In this age of ever-increasing digitization in the
storage, processing, analysis and communication of information,
there are numerous examples of applications where one needs to
construct a continuously defined function or numerical algorithm to
approximate, represent and reconstruct the given discrete data of a
signal. Many a times one wishes to manipulate the data in a way that
requires information not included explicitly in the data, which is
done through interpolation and/or extrapolation.
Tidal data are a very perfect example of time series and many
statistical techniques have been applied for tidal data analysis and
representation. ANN is recent addition to such techniques. In the
present paper we describe the time series representation capabilities
of a special type of ANN- Radial Basis Function networks and
present the results of tidal data representation using RBF. Tidal data
analysis & representation is one of the important requirements in
marine science for forecasting.
Abstract: The purpose of this paper is to describe the process of
setting up a learning community within an elementary school in
Ontario, Canada. The description is provided through reflection and
examination of field notes taken during the yearlong training and
implementation process. Specifically the impact of teachers- capacity
on the creation of a learning community was of interest. This paper is
intended to inform and add to the debate around the tensions that
exist in implementing a bottom-up professional development model
like the learning community in a top-down organizational structure.
My reflections of the process illustrate that implementation of the
learning community professional development model may be
difficult and yet transformative in the professional lives of the
teachers, students, and administration involved in the change process.
I conclude by suggesting the need for a new model of professional
development that requires a transformative shift in power dynamics
and a shift in the view of what constitutes effective professional
learning.
Abstract: Using plug flow model in conjunction with
experimental solute concentration profiles, overall volumetric mass
transfer coefficient based on continuous phase (Koca), in a packed
liquid-liquid extraction column has been optimized. Number of 12
experiments has been done using standard system of water/acid
acetic/toluene in a 6 cm diameter, 120 cm height column. Thorough
consideration of influencing parameters we intended to correlate
dimensionless parameters in term of overall Sherwood number which
has an acceptable average error of about 15.8%.
Abstract: This paper presents a systematic procedure for modelling and simulation of a power system installed with a power system stabilizer (PSS) and a flexible ac transmission system (FACTS)-based controller. For the design purpose, the model of example power system which is a single-machine infinite-bus power system installed with the proposed controllers is developed in MATLAB/SIMULINK. In the developed model synchronous generator is represented by model 1.1. which includes both the generator main field winding and the damper winding in q-axis so as to evaluate the impact of PSS and FACTS-based controller on power system stability. The model can be can be used for teaching the power system stability phenomena, and also for research works especially to develop generator controllers using advanced technologies. Further, to avoid adverse interactions, PSS and FACTS-based controller are simultaneously designed employing genetic algorithm (GA). The non-linear simulation results are presented for the example power system under various disturbance conditions to validate the effectiveness of the proposed modelling and simultaneous design approach.
Abstract: Prickly pear fruit (Opuntia ficus indica L. Miller) belongs to the Cactaceae family. This species is very sensitive to low storage temperatures (< 5°C) which cause damages. The fruits can be peeled, suitably packaged and successfully commercialized as a ready-to-eat product. The main limit to the extension of the shelf life is the production of off-flavors due to different factors, the growth of microorganisms and the action of endogenous enzymes. Lipoxygenase (LOX) and Pectinesterase (PE) are involved in fruit degradation. In particular, LOX pathway is directly responsible for lipid oxidation, and the subsequent production of off-flavours, while PE causes the softening of fruit during maturation. They act on the texture and shelf-life of post-harvest, packaged fruits, as a function of the the grown of microorganisms and packaging technologies used. The aim of this work is to compare the effect of different packaging technologies on the shelf life extension of ready-to-eat prickly pear fruits with regards for the enzymes activities.
Abstract: In the present work, we have developed a symmetric electrochemical capacitor based on the nanostructured iron oxide (Fe3O4)-activated carbon (AC) nanocomposite materials. The physical properties of the nanocomposites were characterized by Scanning Electron Microscopy (SEM) and Brunauer-Emmett-Teller (BET) analysis. The electrochemical performances of the composite electrode in 1.0 M Na2SO3 and 1.0 M Na2SO4 aqueous solutions were evaluated using cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). The composite electrode with 4 wt% of iron oxide nanomaterials exhibits the highest capacitance of 86 F/g. The experimental results clearly indicate that the incorporation of iron oxide nanomaterials at low concentration to the composite can improve the capacitive performance, mainly attributed to the contribution of the pseudocapacitance charge storage mechanism and the enhancement on the effective surface area of the electrode. Nevertheless, there is an optimum threshold on the amount of iron oxide that needs to be incorporated into the composite system. When this optimum threshold is exceeded, the capacitive performance of the electrode starts to deteriorate, as a result of the undesired particle aggregation, which is clearly indicated in the SEM analysis. The electrochemical performance of the composite electrode is found to be superior when Na2SO3 is used as the electrolyte, if compared to the Na2SO4 solution. It is believed that Fe3O4 nanoparticles can provide favourable surface adsorption sites for sulphite (SO3 2-) anions which act as catalysts for subsequent redox and intercalation reactions.
Abstract: In this paper, we explore a new scheme for filtering spoofed packets (DDOS attack) which is a combination of path fingerprint and client puzzle concepts. In this each IP packet has a unique fingerprint is embedded that represents, the route a packet has traversed. The server maintains a mapping table which contains the client IP address and its corresponding fingerprint. In ingress router, client puzzle is placed. For each request, the puzzle issuer provides a puzzle which the source has to solve. Our design has the following advantages over prior approaches, 1) Reduce the network traffic, as we place a client puzzle at the ingress router. 2) Mapping table at the server is lightweight and moderate.
Abstract: The scope of this paper is to describe a real electrical
installation of renewable energy using photovoltaic cells. The
displayed power grid connected network was established in 2007 at
area of Northern Greece. The photovoltaic park is composed of 6120
photovoltaic cells able to deliver a total power of 1.101.600 Wp. For
the transformation of DC voltage to AC voltage have been used 25
stand alone three phases inverters and for the connection at the
medium voltage network of Greek Power Authority have been
installed two oil immersed transformer of 630 kVA each one. Due to
the wide space area of installation a specific external lightning
protection system has been designed. Additionally, due to the
sensitive electronics of the control and protection systems of park,
surge protection, equipotent bonding and shielding were also of
major importance.
Abstract: Digital watermarking is a way to provide the facility of secure multimedia data communication besides its copyright protection approach. The Spread Spectrum modulation principle is widely used in digital watermarking to satisfy the robustness of multimedia signals against various signal-processing operations. Several SS watermarking algorithms have been proposed for multimedia signals but very few works have discussed on the issues responsible for secure data communication and its robustness improvement. The current paper has critically analyzed few such factors namely properties of spreading codes, proper signal decomposition suitable for data embedding, security provided by the key, successive bit cancellation method applied at decoder which have greater impact on the detection reliability, secure communication of significant signal under camouflage of insignificant signals etc. Based on the analysis, robust SS watermarking scheme for secure data communication is proposed in wavelet domain and improvement in secure communication and robustness performance is reported through experimental results. The reported result also shows improvement in visual and statistical invisibility of the hidden data.
Abstract: In this study, the use of silicon NAM (Non-Audible
Murmur) microphone in automatic speech recognition is presented.
NAM microphones are special acoustic sensors, which are attached
behind the talker-s ear and can capture not only normal (audible)
speech, but also very quietly uttered speech (non-audible murmur).
As a result, NAM microphones can be applied in automatic speech
recognition systems when privacy is desired in human-machine communication.
Moreover, NAM microphones show robustness against
noise and they might be used in special systems (speech recognition,
speech conversion etc.) for sound-impaired people. Using a small
amount of training data and adaptation approaches, 93.9% word
accuracy was achieved for a 20k Japanese vocabulary dictation
task. Non-audible murmur recognition in noisy environments is also
investigated. In this study, further analysis of the NAM speech has
been made using distance measures between hidden Markov model
(HMM) pairs. It has been shown the reduced spectral space of NAM
speech using a metric distance, however the location of the different
phonemes of NAM are similar to the location of the phonemes
of normal speech, and the NAM sounds are well discriminated.
Promising results in using nonlinear features are also introduced,
especially under noisy conditions.
Abstract: Contamination of heavy metals represents one of the
most pressing threats to water and soil resources as well as human
health. Phytoremediation can be potentially used to remediate metalcontaminated
sites. A major step towards the development of
phytoremediation of heavy metal impacted soils is the discovery of
the heavy metal hyperaccumulation in plants. In this study, the
several established criteria to define a hyperaccumulator plant were
applied. The case study was represented by a mining area in
Hamedan province in the central west part of Iran. Obtained results
showed that the most of sampled species were able to grow on
heavily metal-contaminated soils and also were able to accumulate
extraordinarily high concentrations of some metals such as Zn, Mn,
Cu, Pb and Fe. Using the most common criteria, Euphorbia
macroclada and Centaurea virgata can be classified as
hyperaccumulators of some measured heavy metals and, therefore,
they have suitable potential for phytoremediation of contaminated
soils.
Abstract: The purpose of this study is to review representative
cases of green space development in order to compare the Garden City
concept and Green Belt concept as applied and to examine its direction
in major Asian and Oceanic cities. The results of previous studies and
this study show that there are two major directions in such
green-oriented city planning. One direction is toward Multi-Regional
Development, and the other focuses on an Environmentally Symbiotic
City based on the Garden City concept. In large cities and the suburbs
where extremely strong pressure to urbanize makes it impossible to
keep Green Belts, it is essential to strictly control land use and adopt
the Garden City concept to conserve the urban environment.
Abstract: Knowledge is indispensable but voluminous knowledge becomes a bottleneck for efficient processing. A great challenge for data mining activity is the generation of large number of potential rules as a result of mining process. In fact sometimes result size is comparable to the original data. Traditional data mining pruning activities such as support do not sufficiently reduce the huge rule space. Moreover, many practical applications are characterized by continual change of data and knowledge, thereby making knowledge voluminous with each change. The most predominant representation of the discovered knowledge is the standard Production Rules (PRs) in the form If P Then D. Michalski & Winston proposed Censored Production Rules (CPRs), as an extension of production rules, that exhibit variable precision and supports an efficient mechanism for handling exceptions. A CPR is an augmented production rule of the form: If P Then D Unless C, where C (Censor) is an exception to the rule. Such rules are employed in situations in which the conditional statement 'If P Then D' holds frequently and the assertion C holds rarely. By using a rule of this type we are free to ignore the exception conditions, when the resources needed to establish its presence, are tight or there is simply no information available as to whether it holds or not. Thus the 'If P Then D' part of the CPR expresses important information while the Unless C part acts only as a switch changes the polarity of D to ~D. In this paper a scheme based on Dempster-Shafer Theory (DST) interpretation of a CPR is suggested for discovering CPRs from the discovered flat PRs. The discovery of CPRs from flat rules would result in considerable reduction of the already discovered rules. The proposed scheme incrementally incorporates new knowledge and also reduces the size of knowledge base considerably with each episode. Examples are given to demonstrate the behaviour of the proposed scheme. The suggested cumulative learning scheme would be useful in mining data streams.
Abstract: The uniform Roe C*-algebra (also called uniform translation)C^*- algebra provides a link between coarse geometry and C^*- algebra theory. The uniform Roe algebra has a great importance in geometry, topology and analysis. We consider some of the elementary concepts associated with coarse spaces.
Abstract: Evolutionary robotics is concerned with the design of
intelligent systems with life-like properties by means of simulated
evolution. Approaches in evolutionary robotics can be categorized
according to the control structures that represent the behavior and the
parameters of the controller that undergo adaptation. The basic idea
is to automatically synthesize behaviors that enable the robot to
perform useful tasks in complex environments. The evolutionary
algorithm searches through the space of parameterized controllers
that map sensory perceptions to control actions, thus realizing a
specific robotic behavior. Further, the evolutionary algorithm
maintains and improves a population of candidate behaviors by
means of selection, recombination and mutation. A fitness function
evaluates the performance of the resulting behavior according to the
robot-s task or mission. In this paper, the focus is in the use of
genetic algorithms to solve a multi-objective optimization problem
representing robot behaviors; in particular, the A-Compander Law is
employed in selecting the weight of each objective during the
optimization process. Results using an adaptive fitness function show
that this approach can efficiently react to complex tasks under
variable environments.
Abstract: The ubiquitous payment problems within construction
industry of China are notoriously hard to be resolved, thus lead to a
series of impacts to the industry chain. Among of them, the most direct
result is affecting the normal operation of contractors negatively. A
wealth of research has already discussed reasons of the payment
problems by introducing a number of possible improvement strategies.
But the causalities of these problems are still far from harsh reality. In
this paper, the authors propose a model for cash flow system of
construction projects by introducing System Dynamics techniques to
explore causal facets of the payment problem. The effects of payment
arrears on both cash flow and profitability of project are simulated into
four scenarios by using data from real projects. Simulating results
show visible clues to help contractors quantitatively determining the
consequences for the construction project that arise from payment
delay.
Abstract: The paper presents the applications of artificial
intelligence technique called adaptive tabu search to design the
controller of a buck converter. The averaging model derived from the
DQ and generalized state-space averaging methods is applied to
simulate the system during a searching process. The simulations
using such averaging model require the faster computational time
compared with that of the full topology model from the software
packages. The reported model is suitable for the work in the paper in
which the repeating calculation is needed for searching the best
solution. The results will show that the proposed design technique
can provide the better output waveforms compared with those
designed from the classical method.
Abstract: Heuristics-based search methodologies normally
work on searching a problem space of possible solutions toward
finding a “satisfactory" solution based on “hints" estimated from the
problem-specific knowledge. Research communities use different
types of methodologies. Unfortunately, most of the times, these hints
are immature and can lead toward hindering these methodologies by
a premature convergence. This is due to a decrease of diversity in
search space that leads to a total implosion and ultimately fitness
stagnation of the population. In this paper, a novel Decision Maturity
framework (DMF) is introduced as a solution to this problem. The
framework simply improves the decision on the direction of the
search by materializing hints enough before using them. Ideas from
this framework are injected into the particle swarm optimization
methodology. Results were obtained under both static and dynamic
environment. The results show that decision maturity prevents
premature converges to a high degree.