Abstract: Control of commutation of switched reluctance (SR)
motor has been an area of interest for researchers for sometime now
with mixed successes in addressing the inherent challenges. New
technologies, processing schemes and methods have been adopted to
make sensorless SR drive a reality. There are a number of
conceptual, offline, analytical and online solutions in literature that
have varying complexities and achieved equally varying degree of
robustness and accuracies depending on the method used to address
the challenges and the SR drive application. Magnetic coupling is
one such challenge when using active probing techniques to
determine rotor position of a SR motor from stator winding. This
paper studies the effect of back-of-core saturation on the detected
rotor position and presents results on measurement made on a 4-
phase SR motor. The results shows that even for a four phase motor
which is excited one phase at a time and using the electrically
opposite phase for active position probing, the back-of-core
saturation effects should not be ignored.
Abstract: Association rules are an important problem in data
mining. Massively increasing volume of data in real life databases
has motivated researchers to design novel and incremental algorithms
for association rules mining. In this paper, we propose an incremental
association rules mining algorithm that integrates shocking
interestingness criterion during the process of building the model. A
new interesting measure called shocking measure is introduced. One
of the main features of the proposed approach is to capture the user
background knowledge, which is monotonically augmented. The
incremental model that reflects the changing data and the user beliefs
is attractive in order to make the over all KDD process more
effective and efficient. We implemented the proposed approach and
experiment it with some public datasets and found the results quite
promising.
Abstract: Whilst there is growing evidence that activity across
the lifespan is beneficial for improved health, there are also many
changes involved with the aging process and subsequently the
potential for reduced indices of health. The nexus between all forms
of health, physical activity and aging is complex and has raised much
interest in recent times due to the realization that a multifaceted
approached is necessary in order to counteract a growing obesity
epidemic. By investigating age based trends within a population
adherring to competitive sport at older ages, further insight might be
gleaned to assist in understanding one of many factors influencing
this relationship. This study evaluated those sport psychological
constructs of health, physical fitness, mental health states, and social
dimension factors in sport that were associated with factors to
participate in sport and physical activity based on responses from the
2009 World Masters Games in Sydney. The sample consisted of
7846 athletes who competed at the games and who completed a 56
item sports participation survey using a 7-point Likert response (1 -
not important to 7 - very important). Questions focuses on factors
thought to promote participation, such as weight control, living
longer, improving mental health (self-esteem, mood states),
improving physical health and factors related to the athlete-s
competitive perspective. The most significant factors related to
participation with this cohort of masters athletes were the socializing
environment of sport, getting physically fit and improving
competitive personal best performances. Strategies to increase
participation in masters sport should focus on these factors as other
factors such as weight loss, improving mental health and living
longer were not identified as important determinates of sports
participation at the World Masters level.
Abstract: Most of the drugs used for pharmaceutical purposes
are poorly water-soluble drugs. About 40% of all newly discovered
drugs are lipophilic and the numbers of lipophilic drugs seem to
increase more and more. Drug delivery systems such as
nanoparticles, micelles or liposomes are applied to improve their
solubility and thus their bioavailability. Besides various techniques of
solubilization, oil-in-water emulsions are often used to incorporate
lipophilic drugs into the oil phase. To stabilize emulsions surface
active substances (surfactants) are generally used. An alternative
method to avoid the application of surfactants was of great interest.
One possibility is to develop O/W-emulsion without any addition of
surface active agents or the so called “surfactant-free emulsion or
SFE”. The aim of this study was to develop and characterize SFE as a
drug carrier by varying the production conditions. Lidocaine base
was used as a model drug. The injection method was developed.
Effects of ultrasound as well as of temperature on the properties of
the emulsion were studied. Particle sizes and release were
determined. The long-term stability up to 30 days was performed.
The results showed that the surfactant-free O/W emulsions with
pharmaceutical oil as drug carrier can be produced.
Abstract: Three service providers in competition, try to optimize
their quality of service / content level and their service access
price. But, they have to deal with uncertainty on the consumers-
preferences. To reduce their uncertainty, they have the opportunity
to buy information and to build alliances. We determine the Shapley
value which is a fair way to allocate the grand coalition-s revenue
between the service providers. Then, we identify the values of β
(consumers- sensitivity coefficient to the quality of service / contents)
for which allocating the grand coalition-s revenue using the Shapley
value guarantees the system stability. For other values of β, we prove
that it is possible for the regulator to impose a per-period interest rate
maximizing the market coverage under equal allocation rules.
Abstract: Nowadays there is a growing interest in biofuel production in most countries because of the increasing concerns about hydrocarbon fuel shortage and global climate changes, also for enhancing agricultural economy and producing local needs for transportation fuel. Ethanol can be produced from biomass by the hydrolysis and sugar fermentation processes. In this study ethanol was produced without using expensive commercial enzymes from sugarcane bagasse. Alkali pretreatment was used to prepare biomass before enzymatic hydrolysis. The comparison between NaOH, KOH and Ca(OH)2 shows NaOH is more effective on bagasse. The required enzymes for biomass hydrolysis were produced from sugarcane solid state fermentation via two fungi: Trichoderma longibrachiatum and Aspergillus niger. The results show that the produced enzyme solution via A. niger has functioned better than T. longibrachiatum. Ethanol was produced by simultaneous saccharification and fermentation (SSF) with crude enzyme solution from T. longibrachiatum and Saccharomyces cerevisiae yeast. To evaluate this procedure, SSF of pretreated bagasse was also done using Celluclast 1.5L by Novozymes. The yield of ethanol production by commercial enzyme and produced enzyme solution via T. longibrachiatum was 81% and 50% respectively.
Abstract: Metal matrix composites (MMC) are generating
extensive interest in diverse fields like defense, aerospace, electronics
and automotive industries. In this present investigation, material
removal rate (MRR) modeling has been carried out using an
axisymmetric model of Al-SiC composite during electrical discharge
machining (EDM). A FEA model of single spark EDM was
developed to calculate the temperature distribution.Further, single
spark model was extended to simulate the second discharge. For
multi-discharge machining material removal was calculated by
calculating the number of pulses. Validation of model has been done
by comparing the experimental results obtained under the same
process parameters with the analytical results. A good agreement was
found between the experimental results and the theoretical value.
Abstract: The visualization of geographic information on mobile devices has become popular as the widespread use of mobile Internet. The mobility of these devices brings about much convenience to people-s life. By the add-on location-based services of the devices, people can have an access to timely information relevant to their tasks. However, visual analysis of geographic data on mobile devices presents several challenges due to the small display and restricted computing resources. These limitations on the screen size and resources may impair the usability aspects of the visualization applications. In this paper, a variable-scale visualization method is proposed to handle the challenge of small mobile display. By merging multiple scales of information into a single image, the viewer is able to focus on the interesting region, while having a good grasp of the surrounding context. This is essentially visualizing the map through a fisheye lens. However, the fisheye lens induces undesirable geometric distortion in the peripheral, which renders the information meaningless. The proposed solution is to apply map generalization that removes excessive information around the peripheral and an automatic smoothing process to correct the distortion while keeping the local topology consistent. The proposed method is applied on both artificial and real geographical data for evaluation.
Abstract: Graph transformation has recently become more and
more popular as a general visual modeling language to formally state
the dynamic semantics of the designed models. Especially, it is a
very natural formalism for languages which basically are graph (e.g.
UML). Using this technique, we present a highly understandable yet
precise approach to formally model and analyze the behavioral
semantics of UML 2.0 Activity diagrams. In our proposal, AGG is
used to design Activities, then using our previous approach to model
checking graph transformation systems, designers can verify and
analyze designed Activity diagrams by checking the interesting
properties as combination of graph rules and LTL (Linear Temporal
Logic) formulas on the Activities.
Abstract: A generalized Dirichlet to Neumann map is
one of the main aspects characterizing a recently introduced
method for analyzing linear elliptic PDEs, through which it
became possible to couple known and unknown components
of the solution on the boundary of the domain without
solving on its interior. For its numerical solution, a well conditioned
quadratically convergent sine-Collocation method
was developed, which yielded a linear system of equations
with the diagonal blocks of its associated coefficient matrix
being point diagonal. This structural property, among others,
initiated interest for the employment of iterative methods for
its solution. In this work we present a conclusive numerical
study for the behavior of classical (Jacobi and Gauss-Seidel)
and Krylov subspace (GMRES and Bi-CGSTAB) iterative
methods when they are applied for the solution of the Dirichlet
to Neumann map associated with the Laplace-s equation
on regular polygons with the same boundary conditions on
all edges.
Abstract: In general dynamic analyses, lower mode response is
of interest, however the higher modes of spatially discretized
equations generally do not represent the real behavior and not affects
to global response much. Some implicit algorithms, therefore, are
introduced to filter out the high-frequency modes using intended
numerical error. The objective of this study is to introduce the
P-method and PC α-method to compare that with dissipation method
and Newmark method through the stability analysis and numerical
example. PC α-method gives more accuracy than other methods
because it based on the α-method inherits the superior properties of the
implicit α-method. In finite element analysis, the PC α-method is more
useful than other methods because it is the explicit scheme and it
achieves the second order accuracy and numerical damping
simultaneously.
Abstract: Kazakhstan attaches the great importance to
cooperation with European countries within the framework of
multilateral security organizations such as NATO. Cooperation of
Kazakhstan with the NATO is a prominent aspect of strengthening of
regional security of republic. It covers a wide spectrum of areas, such
as reform of sector of defense and security, military operative
compatibility of armed forces of NATO member-countries and
Kazakhstan, civil emergency planning and scientific cooperation. The
cooperation between Kazakhstan and NATO is based on the mutual
interests of neighboring republics in the region so that the existing
forms of cooperation between Kazakhstan and NATO will not be
negatively perceived both in Asia as well as among CIS countries.
Kazakhstan tailors its participation in the PfP programme through an
annual Individual Partnership Programme, selecting those activities
that will help achieve the goals it has set in the IPAP. Level of
cooperation within the limits of PfP essentially differs on each
republic. Cooperation with Kazakhstan progressed most of all since
has been signed IPAP from the NATO
Abstract: In the recent past, there has been an increasing interest
in applying evolutionary methods to Knowledge Discovery in
Databases (KDD) and a number of successful applications of Genetic
Algorithms (GA) and Genetic Programming (GP) to KDD have been
demonstrated. The most predominant representation of the
discovered knowledge is the standard Production Rules (PRs) in the
form If P Then D. The PRs, however, are unable to handle
exceptions and do not exhibit variable precision. The Censored
Production Rules (CPRs), an extension of PRs, were proposed by
Michalski & Winston 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
and changes the polarity of D to ~D.
This paper presents a classification algorithm based on evolutionary
approach that discovers comprehensible rules with exceptions in the
form of CPRs.
The proposed approach has flexible chromosome encoding, where
each chromosome corresponds to a CPR. Appropriate genetic
operators are suggested and a fitness function is proposed that
incorporates the basic constraints on CPRs. Experimental results are
presented to demonstrate the performance of the proposed algorithm.
Abstract: Rule Discovery is an important technique for mining
knowledge from large databases. Use of objective measures for
discovering interesting rules leads to another data mining problem,
although of reduced complexity. Data mining researchers have
studied subjective measures of interestingness to reduce the volume
of discovered rules to ultimately improve the overall efficiency of
KDD process.
In this paper we study novelty of the discovered rules as a
subjective measure of interestingness. We propose a hybrid approach
based on both objective and subjective measures to quantify novelty
of the discovered rules in terms of their deviations from the known
rules (knowledge). We analyze the types of deviation that can arise
between two rules and categorize the discovered rules according to
the user specified threshold. We implement the proposed framework
and experiment with some public datasets. The experimental results
are promising.
Abstract: Knowledge about the magnetic quantities in a magnetic circuit is always of great interest. On the one hand, this information is needed for the simulation of a transformer. On the other hand, parameter studies are more reliable, if the magnetic quantities are derived from a well established model. One possibility to model the 3-phase transformer is by using a magnetic equivalent circuit (MEC). Though this is a well known system, it is often not an easy task to set up such a model for a large number of lumped elements which additionally includes the nonlinear characteristic of the magnetic material. Here we show the setup of a solver for a MEC and the results of the calculation in comparison to measurements taken. The equations of the MEC are based on a rearranged system of the nodal analysis. Thus it is possible to achieve a minimum number of equations, and a clear and simple structure. Hence, it is uncomplicated in its handling and it supports the iteration process. Additional helpful tasks are implemented within the solver to enhance the performance. The electric circuit is described by an electric equivalent circuit (EEC). Our results for the 3-phase transformer demonstrate the computational efficiency of the solver, and show the benefit of the application of a MEC.
Abstract: The values of managers and employees in organizations are phenomena that have captured the interest of researchers at large. Despite this attention, there continues to be a lack of agreement on what values are and how they influence individuals, or how they are constituted in individuals- mind. In this article content-based approach is presented as alternative reference frame for exploring values. In content-based approach human thinking in different contexts is set at the focal point. Differences in valuations can be explained through the information contents of mental representations. In addition to the information contents, attention is devoted to those cognitive processes through which mental representations of values are constructed. Such informational contents are in decisive role for understanding human behavior. By applying content-based analysis to an examination of values as mental representations, it is possible to reach a deeper to the motivational foundation of behaviors, such as decision making in organizational procedures, through understanding the structure and meanings of specific values at play.
Abstract: The growth of open networks created the interest to commercialise it. The establishment of an electronic business mechanism must be accompanied by a digital-electronic payment system to transfer the value of transactions. Financial organizations are requested to offer a secure e-payment synthesis with equivalent levels of trust and security served in conventional paper-based payment transactions. The paper addresses the challenge of the first trade problem in e-commerce, provides a brief literature review on electronic payment and attempts to explain the underlying concept and method of trust in relevance to electronic payment.
Abstract: The present study deals with the modeling and simulation of flow through an annular reactor at different hydrodynamic conditions using computational fluid dynamics (CFD) to investigate the flow behavior. CFD modeling was utilized to predict velocity distribution and average velocity in the annular geometry. The results of CFD simulations were compared with the mathematically derived equations and already developed correlations for validation purposes. CFD modeling was found suitable for predicting the flow characteristics in annular geometry under laminar flow conditions. It was observed that CFD also provides local values of the parameters of interest in addition to the average values for the simulated geometry.
Abstract: This paper generalizes Yeh Lam-s shock model for
renewal shock arrivals and random threshold. Several interesting
statistical measures are explicitly obtained. A few special cases and
an optimal replacement problem are also discussed.
Abstract: A clustering is process to identify a homogeneous
groups of object called as cluster. Clustering is one interesting topic
on data mining. A group or class behaves similarly characteristics.
This paper discusses a robust clustering process for data images with
two reduction dimension approaches; i.e. the two dimensional
principal component analysis (2DPCA) and principal component
analysis (PCA). A standard approach to overcome this problem is
dimension reduction, which transforms a high-dimensional data into
a lower-dimensional space with limited loss of information. One of
the most common forms of dimensionality reduction is the principal
components analysis (PCA). The 2DPCA is often called a variant of
principal component (PCA), the image matrices were directly treated
as 2D matrices; they do not need to be transformed into a vector so
that the covariance matrix of image can be constructed directly using
the original image matrices. The decomposed classical covariance
matrix is very sensitive to outlying observations. The objective of
paper is to compare the performance of robust minimizing vector
variance (MVV) in the two dimensional projection PCA (2DPCA)
and the PCA for clustering on an arbitrary data image when outliers
are hiden in the data set. The simulation aspects of robustness and
the illustration of clustering images are discussed in the end of
paper