Abstract: The effect of nano Co3O4 addition on the
superconducting properties of (Bi, Pb)-2223 system was studied. The
samples were prepared by the acetate coprecipitation method. The
Co3O4 with different sizes (10-30 nm and 30-50 nm) from x=0.00 to
0.05 was added to Bi1.6Pb0.4Sr2Ca2Cu3Oy(Co3O4)x. Phase analysis by
XRD method, microstructural examination by SEM and dc electrical
resistivity by four point probe method were done to characterize the
samples. The X-ray diffraction patterns of all the samples indicated
the majority Bi-2223 phase along with minor Bi-2212 and Bi-2201
phases. The volume fraction was estimated from the intensities of Bi-
2223, Bi-2212 and Bi-2201 phase. The sample with x=0.01 wt% of
the added Co3O4 (10-30 nm size) showed the highest volume fraction
of Bi-2223 phase (72%) and the highest superconducting transition
temperature, Tc (~102 K). The non-added sample showed the highest
Tc(~103 K) compared to added samples with nano Co3O4 (30-50 nm
size) added samples. Both the onset critical temperature Tc(onset)
and zero electrical resistivity temperature Tc(R=0) were in the range
of 103-115 ±1K and 91-103 ±1K respectively for samples with added
Co3O4 (10-30 nm and 30-50 nm).
Abstract: This work presents a recursive identification algorithm. This algorithm relates to the identification of closed loop system with Variable Structure Controller. The approach suggested includes two stages. In the first stage a genetic algorithm is used to obtain the parameters of switching function which gives a control signal rich in commutations (i.e. a control signal whose spectral characteristics are closest possible to those of a white noise signal). The second stage consists in the identification of the system parameters by the instrumental variable method and using the optimal switching function parameters obtained with the genetic algorithm. In order to test the validity of this algorithm a simulation example is presented.
Abstract: The relation between taxation states and foreign direct
investment has been studied for several perspectives and with states
of different levels of development. Usually it's only considered the
impact of tax level on the foreign direct investment volume. This
paper enhances this view by assuming that multinationals companies
(MNC) can use transfer prices systems and have got investment
timing flexibility. Thus, it evaluates the impact of the use of
international transfer pricing systems on the states- policy and on the
investment timing of the multinational companies. In uncertain
business environments (with periodical release of news), the
investment can increase if MNC detain investment delay options.
This paper shows how tax differentials can attract foreign direct
investments (FDI) and influence MNC behavior. The equilibrium is
set in a global environment where MNC can shift their profits
between states depending on the corporate tax rates. Assuming the
use of transfer pricing schemes, this paper confirms the relationship
between MNC behavior and the release of new business news.
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: This study examined the effects of 8-week Pilates training program on limits of stability (LOS) and abdominal muscle strength in young dancers. Twenty-four female volunteered and randomly assigned as experimental group (EG) or control group (CG). All subjects received the same dance lessons but the EG underwent an extra Pilates mat exercises for 40 minutes, three times a week, for 8 weeks. LOS was evaluated by the Biodex Balance System and the abdominal strength was measured by 30/60 seconds sit-ups test. One factor ANCOVA was used to examine the differences between groups after training. The results showed that the overall LOS scores at levels 2/8 and the 30/60 seconds sit-ups for the EG group pre- and post-training were changed from 22/38 % to 31/51 % and 20/33 times to 24/42 times, respectively. The study demonstrated that 8-week Pilates training can improve the LOS performance and abdominal strength in young dancers.
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 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: 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 investigates the problem of sampling from transactional data streams. We introduce CFISDS as a content based sampling algorithm that works on a landmark window model of data streams and preserve more informed sample in sample space. This algorithm that work based on closed frequent itemset mining tasks, first initiate a concept lattice using initial data, then update lattice structure using an incremental mechanism.Incremental mechanism insert, update and delete nodes in/from concept lattice in batch manner. Presented algorithm extracts the final samples on demand of user. Experimental results show the accuracy of CFISDS on synthetic and real datasets, despite on CFISDS algorithm is not faster than exist sampling algorithms such as Z and DSS.
Abstract: Using the quantum hydrodynamic (QHD) model for quantum plasma at finite temperature the modulational instability of electron plasma waves is investigated by deriving a nonlinear Schrodinger equation. It was found that the electron degeneracy parameter significantly affects the linear and nonlinear properties of electron plasma waves in quantum plasma.
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: The Wind Turbine Modeling in Wind Energy Conversion System (WECS) using Doubly-Fed Induction Generator (DFIG) PI Controller based design is presented. To study about the variable wind speed. The PI controller performs responding to the dynamic performance. The objective is to study the characteristic of wind turbine and finding the optimum wind speed suitable for wind turbine performance. This system will allow the specification setting (2.5MW). The output active power also corresponding same the input is given. And the reactive power produced by the wind turbine is regulated at 0 Mvar. Variable wind speed is optimum for drive train performance at 12.5 m/s (at maximum power coefficient point) from the simulation of DFIG by Simulink is described.
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.