Abstract: The given work is devoted to the description of
Information Technologies NAS of Azerbaijan created and
successfully maintained in Institute. On the basis of the decision of
board of the Supreme Certifying commission at the President of the
Azerbaijan Republic and Presidium of National Academy of
Sciences of the Azerbaijan Republic, the organization of training
courses on Computer Sciences for all post-graduate students and
dissertators of the republic, taking of examinations of candidate
minima, it was on-line entrusted to Institute of Information
Technologies of the National Academy of Sciences of Azerbaijan.
Therefore, teaching the computer sciences to post-graduate
students and dissertators a scientific - methodological manual on
effective application of new information technologies for research
works by post-graduate students and dissertators and taking of
candidate minima is carried out in the Educational Center.
Information and communication technologies offer new
opportunities and prospects of their application for teaching and
training. The new level of literacy demands creation of essentially
new technology of obtaining of scientific knowledge. Methods of
training and development, social and professional requirements,
globalization of the communicative economic and political projects
connected with construction of a new society, depends on a level of
application of information and communication technologies in the
educational process. Computer technologies develop ideas of
programmed training, open completely new, not investigated
technological ways of training connected to unique opportunities of
modern computers and telecommunications. Computer technologies
of training are processes of preparation and transfer of the
information to the trainee by means of computer. Scientific and
technical progress as well as global spread of the technologies
created in the most developed countries of the world is the main
proof of the leading role of education in XXI century. Information
society needs individuals having modern knowledge. In practice, all
technologies, using special technical information means (computer,
audio, video) are called information technologies of education.
Abstract: Construction project control attempts to obtain real-time information and effectively enhance dynamic control and management via information sharing and analysis among project participants to eliminate construction conflicts and project delays. However, survey results for Taiwan indicate that construction commercial project management software is not widely accepted for subcontractors and suppliers. To solve the project communications problems among participants, this study presents a novel system called the Construction Dynamic Teams Communication Management (Con-DTCM) system for small-to-medium sized subcontractors and suppliers in Taiwanese Construction industry, and demonstrates that the Con-DTCM system responds to the most recent project information efficiently and enhances management of project teams (general contractor, suppliers and subcontractors) through web-based environment. Web-based technology effectively enhances information sharing during construction project management, and generates cost savings via the Internet. The main unique characteristic of the proposed Con-DTCM system is extremely user friendly and easily design compared with current commercial project management applications. The Con-DTCM system is applied to a case study of construction of a building project in Taiwan to confirm the proposed methodology and demonstrate the effectiveness of information sharing during the construction phase. The advantages of the Con-DTCM system are in improving project control and management efficiency for general contractors, and in providing dynamic project tracking and management, which enables subcontractors and suppliers to acquire the most recent project-related information. Furthermore, this study presents and implements a generic system architecture.
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: 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: In this paper the optimal control strategy for
Permanent Magnet Synchronous Motor (PMSM) based drive system
is presented. The designed full optimal control is available for speed
operating range up to base speed. The optimal voltage space-vector
assures input energy reduction and stator loss minimization,
maintaining the output energy in the same limits with the
conventional PMSM electrical drive. The optimal control with three
components is based on the energetically criteria and it is applicable
in numerical version, being a nonrecursive solution. The simulation
results confirm the increased efficiency of the optimal PMSM drive.
The properties of the optimal voltage space vector are shown.
Abstract: Like any sentient organism, a smart environment
relies first and foremost on sensory data captured from the real
world. The sensory data come from sensor nodes of different
modalities deployed on different locations forming a Wireless Sensor
Network (WSN). Embedding smart sensors in humans has been a
research challenge due to the limitations imposed by these sensors
from computational capabilities to limited power. In this paper, we
first propose a practical WSN application that will enable blind
people to see what their neighboring partners can see. The challenge
is that the actual mapping between the input images to brain pattern
is too complex and not well understood. We also study the
connectivity problem in 3D/2D wireless sensor networks and propose
distributed efficient algorithms to accomplish the required
connectivity of the system. We provide a new connectivity algorithm
CDCA to connect disconnected parts of a network using cooperative
diversity. Through simulations, we analyze the connectivity gains
and energy savings provided by this novel form of cooperative
diversity in WSNs.
Abstract: This paper proposes a new technique based on nonlinear Minmax Detector Based (MDB) filter for image restoration. The aim of image enhancement is to reconstruct the true image from the corrupted image. The process of image acquisition frequently leads to degradation and the quality of the digitized image becomes inferior to the original image. Image degradation can be due to the addition of different types of noise in the original image. Image noise can be modeled of many types and impulse noise is one of them. Impulse noise generates pixels with gray value not consistent with their local neighborhood. It appears as a sprinkle of both light and dark or only light spots in the image. Filtering is a technique for enhancing the image. Linear filter is the filtering in which the value of an output pixel is a linear combination of neighborhood values, which can produce blur in the image. Thus a variety of smoothing techniques have been developed that are non linear. Median filter is the one of the most popular non-linear filter. When considering a small neighborhood it is highly efficient but for large window and in case of high noise it gives rise to more blurring to image. The Centre Weighted Mean (CWM) filter has got a better average performance over the median filter. However the original pixel corrupted and noise reduction is substantial under high noise condition. Hence this technique has also blurring affect on the image. To illustrate the superiority of the proposed approach, the proposed new scheme has been simulated along with the standard ones and various restored performance measures have been compared.
Abstract: Generalized Center String (GCS) problem are
generalized from Common Approximate Substring problem
and Common substring problems. GCS are known to be
NP-hard allowing the problems lies in the explosion of
potential candidates. Finding longest center string without
concerning the sequence that may not contain any motifs is
not known in advance in any particular biological gene
process. GCS solved by frequent pattern-mining techniques
and known to be fixed parameter tractable based on the
fixed input sequence length and symbol set size. Efficient
method known as Bpriori algorithms can solve GCS with
reasonable time/space complexities. Bpriori 2 and Bpriori
3-2 algorithm are been proposed of any length and any
positions of all their instances in input sequences. In this
paper, we reduced the time/space complexity of Bpriori
algorithm by Constrained Based Frequent Pattern mining
(CBFP) technique which integrates the idea of Constraint
Based Mining and FP-tree mining. CBFP mining technique
solves the GCS problem works for all center string of any
length, but also for the positions of all their mutated copies
of input sequence. CBFP mining technique construct TRIE
like with FP tree to represent the mutated copies of center
string of any length, along with constraints to restraint
growth of the consensus tree. The complexity analysis for
Constrained Based FP mining technique and Bpriori
algorithm is done based on the worst case and average case
approach. Algorithm's correctness compared with the
Bpriori algorithm using artificial data is shown.
Abstract: A virtualized and virtual approach is presented on
academically preparing students to successfully engage at a strategic
perspective to understand those concerns and measures that are both
structured and not structured in the area of cyber security and
information assurance. The Master of Science in Cyber Security and
Information Assurance (MSCSIA) is a professional degree for those
who endeavor through technical and managerial measures to ensure
the security, confidentiality, integrity, authenticity, control,
availability and utility of the world-s computing and information
systems infrastructure. The National University Cyber Security and
Information Assurance program is offered as a Master-s degree. The
emphasis of the MSCSIA program uniquely includes hands-on
academic instruction using virtual computers. This past year, 2011,
the NU facility has become fully operational using system
architecture to provide a Virtual Education Laboratory (VEL)
accessible to both onsite and online students. The first student cohort
completed their MSCSIA training this past March 2, 2012 after
fulfilling 12 courses, for a total of 54 units of college credits. The
rapid pace scheduling of one course per month is immensely
challenging, perpetually changing, and virtually multifaceted. This
paper analyses these descriptive terms in consideration of those
globalization penetration breaches as present in today-s world of
cyber security. In addition, we present current NU practices to
mitigate risks.
Abstract: Medical compression bandages are widely used in the
treatment of chronic venous disorder. In order to design effective
compression bandages, researchers have attempted to describe the
interface pressure applied by multi-layer bandages using mathematical
models. This paper reports on the work carried out to
compare and validate the mathematical models used to describe the
interface pressure applied by multi-layer bandages. Both analytical
and experimental results showed that using simple multiplication
of a number of bandage layers with the pressure applied by one
layer of bandage or ignoring the increase in the limb radius due to
former layers of bandage will result in overestimating the pressure.
Experimental results showed that the mathematical models, which
take into consideration the increase in the limb radius due to former
bandage layers, are more accurate than the one which does not.
Abstract: In Virtual organization, Knowledge Discovery (KD)
service contains distributed data resources and computing grid nodes.
Computational grid is integrated with data grid to form Knowledge
Grid, which implements Apriori algorithm for mining association
rule on grid network. This paper describes development of parallel
and distributed version of Apriori algorithm on Globus Toolkit using
Message Passing Interface extended with Grid Services (MPICHG2).
The creation of Knowledge Grid on top of data and
computational grid is to support decision making in real time
applications. In this paper, the case study describes design and
implementation of local and global mining of frequent item sets. The
experiments were conducted on different configurations of grid
network and computation time was recorded for each operation. We
analyzed our result with various grid configurations and it shows
speedup of computation time is almost superlinear.
Abstract: With the proliferation of the mobile device
technologies, mobile learning can be used to complement and
improve traditional learning problems. Both students and teachers
need a proper and handy system to monitor and keep track the
performance of the students. This paper presents an implementation
of M-learning for primary school in Malaysia by using an open
source technology. It focuses on learning mathematics using
handheld devices for primary schools- students aged 11 and 12 years
old. Main users for this system include students, teachers and the
administrator. This application suggests a new mobile learning
environment with mobile graph for tracking the students- progress
and performance. The purpose of this system is not to replace
traditional classroom but to complement the learning process. In a
testing conducted, students who used this system performed better in
their examination.
Abstract: This paper presents a comparison between two Pulse
Width Modulation (PWM) algorithms applied to a three-level Neutral
Point Clamped (NPC) Voltage Source Inverter (VSI). The first
algorithm applied is the triangular-sinusoidal strategy; the second is
the Space Vector Pulse Width Modulation (SVPWM) strategy. In the
first part, we present a topology of three-level NCP VSI. After that,
we develop the two PWM strategies to control this converter. At the
end the experimental results are presented.
Abstract: Signature represents an individual characteristic of a
person which can be used for his / her validation. For such application
proper modeling is essential. Here we propose an offline signature
recognition and verification scheme which is based on extraction of
several features including one hybrid set from the input signature
and compare them with the already trained forms. Feature points
are classified using statistical parameters like mean and variance.
The scanned signature is normalized in slant using a very simple
algorithm with an intention to make the system robust which is
found to be very helpful. The slant correction is further aided by the
use of an Artificial Neural Network (ANN). The suggested scheme
discriminates between originals and forged signatures from simple
and random forgeries. The primary objective is to reduce the two
crucial parameters-False Acceptance Rate (FAR) and False Rejection
Rate (FRR) with lesser training time with an intension to make the
system dynamic using a cluster of ANNs forming a multiple classifier
system.
Abstract: Hidden failure in a protection system has been
recognized as one of the main reasons which may cause to a power
system instability leading to a system cascading collapse. This paper
presents a computationally systematic approach used to obtain the
estimated average probability of a system cascading collapse by
considering the effect of probability hidden failure in a protection
system. The estimated average probability of a system cascading
collapse is then used to determine the severe loading condition
contributing to the higher risk of critical system cascading collapse.
This information is essential to the system utility since it will assist
the operator to determine the highest point of increased system
loading condition prior to the event of critical system cascading
collapse.
Abstract: The paper proposes and validates a new method of solving instances of the vehicle routing problem (VRP). The approach is based on a multiple agent system paradigm. The paper contains the VRP formulation, an overview of the multiple agent environment used and a description of the proposed implementation. The approach is validated experimentally. The experiment plan and the discussion of experiment results follow.
Abstract: The purposes of this research are 1) to study English language learning strategies used by the fourth-year students majoring in English and Business English, 2) to study the English language learning strategies which have an affect on English learning achievement, and 3) to compare the English language learning strategies used by the students majoring in English and Business English. The population and sampling comprise of 139 university students of the Suan Sunandha Rajabhat University. Research instruments are language learning strategies questionnaire which was constructed by the researcher and improved on by three experts and the transcripts that show the results of English learning achievement. The questionnaire includes 1) Language Practice Strategy 2)Memory Strategy 3) Communication Strategy 4)Making an Intelligent Guess or Compensation Strategy 5) Self-discipline in Learning Management Strategy 6) Affective Strategy 7)Self-Monitoring Strategy 8) Self-studySkill Strategy. Statistics used in the study are mean, standard deviation, T-test and One Way ANOVA, Pearson product moment correlation coefficient and Regression Analysis. The results of the findings reveal that the English language learning strategies most frequently used by the students are affective strategy, making an intelligent guess or compensation strategy, self-studyskill strategy and self-monitoring strategy respectively. The aspect of making an intelligent guess or compensation strategy had the most significant affect on English learning achievement. It is found that the English language learning strategies mostly used by the Business English major students and moderately used by the English major students. Their language practice strategies uses were significantly different at the 0.05 level and their communication strategies uses were significantly different at the 0.01 level. In addition, it is found that the poor students and the fair ones most frequently used affective strategy while the good ones most frequently used making an intelligent guess or compensation strategy. KeywordsEnglish language, language learning strategies, English learning achievement, and students majoring in English, Business English. Pranee Pathomchaiwat is an Assistant Professor in Business English Program, Suan Sunandha Rajabhat University, Bangkok, Thailand (e-mail: [email protected]).
Abstract: Collision is considered as a time-depended nonlinear
dynamic phenomenon. The majority of researchers have focused on
deriving the resultant damage of the ship collisions via analytical,
experimental, and finite element methods.In this paper, first, the
force-penetration curve of a head collision on a container ship with
rigid barrier based on Yang and Pedersen-s methods for internal
mechanic section is studied. Next, the obtained results from different
analytical methods are compared with each others. Then, through a
simulation of the container ship collision in Ansys Ls-Dyna, results
from finite element approach are compared with analytical methods
and the source of errors is discussed. Finally, the effects of
parameters such as velocity, and angle of collision on the forcepenetration
curve are investigated.
Abstract: In this paper, we study the multi-scenario knapsack problem, a variant of the well-known NP-Hard single knapsack problem. We investigate the use of an adaptive algorithm for solving heuristically the problem. The used method combines two complementary phases: a size reduction phase and a dynamic 2- opt procedure one. First, the reduction phase applies a polynomial reduction strategy; that is used for reducing the size problem. Second, the adaptive search procedure is applied in order to attain a feasible solution Finally, the performances of two versions of the proposed algorithm are evaluated on a set of randomly generated instances.