Abstract: The article considers religious aspects of Kazakh
society pre-Soviet times. Studying the mental, political and spiritual
content of Islam, the reasons for its wide distribution among the ancestors of the Kazakhs is analyzed. Interested Russians since the
accession of the Kazakh Khanate to the Russian Empire more than
once pointed out that Islam is a synthesis of Islam and Shamanism.
But shamanism is a generalization of the name of religion, which
took place prior to Islam in the land of the Kazakh people. Here we can see the elements of Zoroastrianism, Tengrianism, etc. This shows
that the ancestors of the Kazakhs - Turkic people - not renounced the
ancient beliefs completely and leave some portion of these religions
as an integral part of the worldview of the people, by the device.
Therefore, the founder of the Turkic Sufi Yasaui still has a huge impact on the religiosity of the Kazakhs. He managed elements of the
ancient religion, which formed the basis of the Kazakhs world, interpreted in the Muslim perspective. The Russian authorities tried
to quell by Islamization Kazakh people. But it was Islam that has
revived the national consciousness of the Kazakh people.
Abstract: Due to the constant increase in the volume of information available to applications in fields varying from medical diagnosis to web search engines, accurate support of similarity becomes an important task. This is also the case of spam filtering techniques where the similarities between the known and incoming messages are the fundaments of making the spam/not spam decision. We present a novel approach to filtering based solely on layout, whose goal is not only to correctly identify spam, but also warn about major emerging threats. We propose a mathematical formulation of the email message layout and based on it we elaborate an algorithm to separate different types of emails and find the new, numerically relevant spam types.
Abstract: We present the induced generalized hybrid
averaging (IGHA) operator. It is a new aggregation operator
that generalizes the hybrid averaging (HA) by using
generalized means and order inducing variables. With this
formulation, we get a wide range of mean operators such as
the induced HA (IHA), the induced hybrid quadratic
averaging (IHQA), the HA, etc. The ordered weighted
averaging (OWA) operator and the weighted average (WA)
are included as special cases of the HA operator. Therefore,
with this generalization we can obtain a wide range of
aggregation operators such as the induced generalized OWA
(IGOWA), the generalized OWA (GOWA), etc. We further
generalize the IGHA operator by using quasi-arithmetic
means. Then, we get the Quasi-IHA operator. Finally, we also
develop an illustrative example of the new approach in a
financial decision making problem. The main advantage of the
IGHA is that it gives a more complete view of the decision
problem to the decision maker because it considers a wide
range of situations depending on the operator used.
Abstract: The purpose of this paper is to propose a text mining
approach to evaluate companies- practices on affective management.
Affective management argues that it is critical to take stakeholders-
affects into consideration during decision-making process, along with
the traditional numerical and rational indices. CSR reports published
by companies were collected as source information. Indices were
proposed based on the frequency and collocation of words relevant to
affective management concept using text mining approach to analyze
the text information of CSR reports. In addition, the relationships
between the results obtained using proposed indices and traditional
indicators of business performance were investigated using
correlation analysis. Those correlations were also compared between
manufacturing and non-manufacturing companies. The results of this
study revealed the possibility to evaluate affective management
practices of companies based on publicly available text documents.
Abstract: Air pollution is still considered as one of the major
environmental and health issues. There is enough research evidence
to show a strong relationship between exposure to air contaminants
and respiratory illnesses among children and adults. In this paper we
used the Copula approach to study a potential relationship between
selected air pollutants (PM10 and NO2) and hospital admissions for
respiratory diseases. Kendall-s tau and Spearman-s rho rank
correlation coefficients are calculated and used in Copula method.
This paper demonstrates that copulas can be used to provide
additional information as a measure of an association when compared
to the standard correlation coefficients. The results find a significant
correlation between the selected air pollutants and hospital
admissions for most of the selected respiratory illnesses.
Abstract: Abai Kunanbayev (1845-1904) was a great Kazakh
poet, composer and philosopher. Abai's main contribution to Kazakh
culture and folklore lies in his poetry, which expresses great
nationalism and grew out of Kazakh folk culture. Before him, most
Kazakh poetry was oral, echoing the nomadic habits of the people of
the Kazakh steppes. We want to introduce to abroad our country, its
history, tradition and culture. We can introduce it only through
translations. Only by reading the Kazakh works can foreign people
know who are kazakhs, the style of their life, their thoughts and so
on. All information comes only through translation. The main
requirement to a good translation is that it should be natural or that it
should read as smoothly as the original. Literary translation should
be adequate, should follow the original to the fullest. Translators
have to be loyal to original text, they shouldn-t give the way to
liberty.
Abstract: A new approach to predict the 3D structures of proteins by combining the knowledge-based method and Molecular Dynamics Simulation is presented on the chicken villin headpiece subdomain (HP-36). Comparative modeling is employed as the knowledge-based method to predict the core region (Ala9-Asn28) of the protein while the remaining residues are built as extended regions (Met1-Lys8; Leu29-Phe36) which then further refined using Molecular Dynamics Simulation for 120 ns. Since the core region is built based on a high sequence identity to the template (65%) resulting in RMSD of 1.39 Å from the native, it is believed that this well-developed core region can act as a 'nucleation center' for subsequent rapid downhill folding. Results also demonstrate that the formation of the non-native contact which tends to hamper folding rate can be avoided. The best 3D model that exhibits most of the native characteristics is identified using clustering method which then further ranked based on the conformational free energies. It is found that the backbone RMSD of the best model compared to the NMR-MDavg is 1.01 Å and 3.53 Å, for the core region and the complete protein, respectively. In addition to this, the conformational free energy of the best model is lower by 5.85 kcal/mol as compared to the NMR-MDavg. This structure prediction protocol is shown to be effective in predicting the 3D structure of small globular protein with a considerable accuracy in much shorter time compared to the conventional Molecular Dynamics simulation alone.
Abstract: The management of the health-care wastes is one of
the most important problems in Istanbul, a city with more than 12
million inhabitants, as it is in most of the developing countries.
Negligence in appropriate treatment and final disposal of the healthcare
wastes can lead to adverse impacts to public health and to the
environment. This paper employs a fuzzy multi-criteria group
decision making approach, which is based on the principles of fusion
of fuzzy information, 2-tuple linguistic representation model, and
technique for order preference by similarity to ideal solution
(TOPSIS), to evaluate health-care waste (HCW) treatment
alternatives for Istanbul. The evaluation criteria are determined
employing nominal group technique (NGT), which is a method of
systematically developing a consensus of group opinion. The
employed method is apt to manage information assessed using multigranularity
linguistic information in a decision making problem with
multiple information sources. The decision making framework
employs ordered weighted averaging (OWA) operator that
encompasses several operators as the aggregation operator since it
can implement different aggregation rules by changing the order
weights. The aggregation process is based on the unification of
information by means of fuzzy sets on a basic linguistic term set
(BLTS). Then, the unified information is transformed into linguistic
2-tuples in a way to rectify the problem of loss information of other
fuzzy linguistic approaches.
Abstract: Recent fifteen years witnessed fast improvements in the field of humanoid robotics. The human-like robot structure is
more suitable to human environment with its supreme obstacle avoidance properties when compared with wheeled service robots.
However, the walking control for bipedal robots is a challenging task
due to their complex dynamics. Stable reference generation plays a very important role in control.
Linear Inverted Pendulum Model (LIPM) and the Zero Moment Point (ZMP) criterion are applied in a number of studies for stable
walking reference generation of biped walking robots. This paper follows this main approach too. We propose a natural and continuous ZMP reference trajectory for a stable and human-like walk. The ZMP reference trajectories move forward under the sole of the support foot when the robot body is supported by a single leg. Robot center of mass trajectory is obtained
from predefined ZMP reference trajectories by a Fourier series
approximation method. The Gibbs phenomenon problem common with Fourier approximations of discontinuous functions is avoided by employing continuous ZMP references. Also, these ZMP reference
trajectories possess pre-assigned single and double support phases,
which are very useful in experimental tuning work.
The ZMP based reference generation strategy is tested via threedimensional
full-dynamics simulations of a 12-degrees-of-freedom
biped robot model. Simulation results indicate that the proposed reference trajectory generation technique is successful.
Abstract: This paper will present the implementation of QoS
policy based system by utilizing rules on Access Control List (ACL)
over Layer 3 (L3) switch. Also presented is the architecture on that
implementation; the tools being used and the result were gathered.
The system architecture has an ability to control ACL rules which are
installed inside an external L3 switch. ACL rules used to instruct the
way of access control being executed, in order to entertain all traffics
through that particular switch. The main advantage of using this
approach is that the single point of failure could be prevented when
there are any changes on ACL rules inside L3 switches. Another
advantage is that the agent could instruct ACL rules automatically
straight away based on the changes occur on policy database without
configuring them one by one. Other than that, when QoS policy
based system was implemented in distributed environment, the
monitoring process can be synchronized easily due to the automate
process running by agent over external policy devices.
Abstract: Learning using labeled and unlabelled data has
received considerable amount of attention in the machine learning
community due its potential in reducing the need for expensive
labeled data. In this work we present a new method for combining
labeled and unlabeled data based on classifier ensembles. The model
we propose assumes each classifier in the ensemble observes the
input using different set of features. Classifiers are initially trained
using some labeled samples. The trained classifiers learn further
through labeling the unknown patterns using a teaching signals that is
generated using the decision of the classifier ensemble, i.e. the
classifiers self-supervise each other. Experiments on a set of object
images are presented. Our experiments investigate different classifier
models, different fusing techniques, different training sizes and
different input features. Experimental results reveal that the proposed
self-supervised ensemble learning approach reduces classification
error over the single classifier and the traditional ensemble classifier
approachs.
Abstract: Spatial understanding and the understanding of
dynamic change in the spatial structure of molecules during a
reaction is essential for designing new molecules. Knowing the
physical processes in the reactions helps to speed up the designing
process. To support the designer with the correct representation of
the designed molecule as well as showing the dynamic behavior of
the whole reacting system is the goal of our application. Our system
shows the spatial deformation of the molecules at every time interval
by minimizing the energy level of the molecules. The position and
orientation of the molecules can be intuitively controlled by
manipulating objects of the real world using Augmented Reality
techniques. Our approach has the potential to speed up the design of
new molecules and help students to understand the chemical
processes better.
Abstract: The most important property of the Gene Ontology is
the terms. These control vocabularies are defined to provide
consistent descriptions of gene products that are shareable and
computationally accessible by humans, software agent, or other
machine-readable meta-data. Each term is associated with
information such as definition, synonyms, database references, amino
acid sequences, and relationships to other terms. This information has
made the Gene Ontology broadly applied in microarray and
proteomic analysis. However, the process of searching the terms is
still carried out using traditional approach which is based on keyword
matching. The weaknesses of this approach are: ignoring semantic
relationships between terms, and highly depending on a specialist to
find similar terms. Therefore, this study combines semantic similarity
measure and genetic algorithm to perform a better retrieval process
for searching semantically similar terms. The semantic similarity
measure is used to compute similitude strength between two terms.
Then, the genetic algorithm is employed to perform batch retrievals
and to handle the situation of the large search space of the Gene
Ontology graph. The computational results are presented to show the
effectiveness of the proposed algorithm.
Abstract: Electronic banking must be secure and easy to use and
many banks heavily advertise an apparent of 100% secure system
which is contestable in many points. In this work, an alternative
approach to the design of e-banking system, through a new solution
for user authentication and security with digital certificate called
LumaCert is introduced. The certificate applies new algorithm for
asymmetric encryption by utilizing two mathematical operators
called Pentors and UltraPentors. The public and private key in this
algorithm represent a quadruple of parameters which are directly
dependent from the above mentioned operators. The strength of the
algorithm resides in the inability to find the respective Pentor and
UltraPentor operator from the mentioned parameters.
Abstract: A new design approach for three-stage operational
amplifiers (op-amps) is proposed. It allows to actually implement a
symmetrical push-pull class-AB amplifier output stage for wellestablished
three-stage amplifiers using a feedforward
transconductance stage. Compared with the conventional design
practice, the proposed approach leads to a significant
improvement of the symmetry between the positive and the
negative op-amp step response, resulting in similar values of the
positive/negative settling time. The new approach proves to be very
useful in order to fully exploit the potentiality allowed by the op-amp
in terms of speed performances. Design examples in a commercial
0.35-μm CMOS prove the effectiveness of theproposed strategy.
Abstract: The primary aim of the e-government applications is
the fast citizen service and the accomplishment of governmental
functions. This paper discusses the knowledge management for egovernment
development in the needs and role. The paper focused
on analyzing the advantages of using knowledge management by
using the existing IT technologies to maximize the government
functions efficiency. The proposed new approach of providing
government services is based on using Knowledge management as a
part of e-government system.
Abstract: The novelty proposed in this study is twofold and consists in the developing of a new color similarity metric based on the human visual system and a new color indexing based on a textual approach. The new color similarity metric proposed is based on the color perception of the human visual system. Consequently the results returned by the indexing system can fulfill as much as possibile the user expectations. We developed a web application to collect the users judgments about the similarities between colors, whose results are used to estimate the metric proposed in this study. In order to index the image's colors, we used a text indexing engine to facilitate the integration of visual features in a database of text documents. The textual signature is build by weighting the image's colors in according to their occurrence in the image. The use of a textual indexing engine, provide us a simple, fast and robust solution to index images. A typical usage of the system proposed in this study, is the development of applications whose data type is both visual and textual. In order to evaluate the proposed method we chose a price comparison engine as a case of study, collecting a series of commercial offers containing the textual description and the image representing a specific commercial offer.
Abstract: Economic models are complex dynamic systems with a lot of uncertainties and fuzzy data. Conventional modeling approaches using well known methods and techniques cannot provide realistic and satisfactory answers to today-s challenging economic problems. Qualitative modeling using fuzzy logic and intelligent system theories can be used to model macroeconomic models. Fuzzy Cognitive maps (FCM) is a new method been used to model the dynamic behavior of complex systems. For the first time FCMs and the Mamdani Model of Intelligent control is used to model macroeconomic models. This new model is referred as the Mamdani Rule-Based Fuzzy Cognitive Map (MBFCM) and provides the academic and research community with a new promising integrated advanced computational model. A new economic model is developed for a qualitative approach to Macroeconomic modeling. Fuzzy Controllers for such models are designed. Simulation results for an economic scenario are provided and extensively discussed
Abstract: This paper presents a new approach in the identification of the quadrotor dynamic model using a black-box system for identification. Also the paper considers the problems which appear during the identification in the closed-loop and offers a technical solution for overcoming the correlation between the input noise present in the output
Abstract: In this paper, a new design technique for enhancing
bandwidth that improves the performance of a conventional
microstrip patch antenna is proposed. This paper presents a novel
wideband probe fed inverted slotted microstrip patch antenna. The
design adopts contemporary techniques; coaxial probe feeding,
inverted patch structure and slotted patch. The composite effect of
integrating these techniques and by introducing the proposed patch,
offer a low profile, broadband, high gain, and low cross-polarization
level. The results for the VSWR, gain and co-and cross-polarization
patterns are presented. The antenna operating the band of 1.80-2.36
GHz shows an impedance bandwidth (2:1 VSWR) of 27% and a gain
of 10.18 dBi with a gain variation of 1.12 dBi. Good radiation
characteristics, including a cross-polarization level in xz-plane less
than -42 dB, have been obtained.