Abstract: In this paper, the robust exponential stability problem of discrete-time uncertain stochastic neural networks with timevarying delays is investigated. By introducing a new augmented Lyapunov function, some delay-dependent stable results are obtained in terms of linear matrix inequality (LMI) technique. Compared with some existing results in the literature, the conservatism of the new criteria is reduced notably. Three numerical examples are provided to demonstrate the less conservatism and effectiveness of the proposed method.
Abstract: This paper offers suggestions for educators at all levels about how to better prepare our students for the future, by building on the past. The discussion begins with a summary of changes in the World Wide Web, especially as the term Web 3.0 is being heard. The bulk of the discussion is retrospective and concerned with an overview of traditional teaching and research approaches as they evolved during the 20th century beginning with those grounded in the Cartesian reality of IA Richards- (1929) Practical Criticism. The paper concludes with a proposal of five strategies which incorporate timeless elements from the past as well as cutting-edge elements from today, in order to better prepare our students for the future.
Abstract: A mathematical model for the hydrodynamic
lubrication of parabolic slider bearings with couple stress lubricants
is presented. A numerical solution for the mathematical model using
finite element scheme is obtained using three nodes isoparametric
quadratic elements. Stiffness integrals obtained from the weak form
of the governing equations were solved using Gauss Quadrature to
obtain a finite number of stiffness matrices. The global system of
equations was obtained for the bearing and solved using Gauss Seidel
iterative scheme. The converged pressure solution was used to obtain
the load capacity of the bearing. Parametric studies were carried out
and it was shown that the effect of couple stresses and profile
parameter are to increase the load carrying capacity of the parabolic
slider bearing. Numerical experiments reveal that the magnitude of
the profile parameter at which maximum load is obtained increases
with decrease in couple stress parameter. The results are presented in
graphical form.
Abstract: We presented results of research aimed on findings
influence of social - psychological training (realized with students of
Constantine the Philosopher University- future teachers within their
undergraduate preparation) on the choice of intrapersonal and
interpersonal features. After social- psychological training using
Interpersonal Check List (ICL) we found out shift of behavior to
more adaptive forms in categories, which are characterized by
extroversive friendly behavior, willingness to cooperation,
conformity regard to social situation, responsible and regardful
behavior.
Using State-Trait Anxiety Inventory (STAI) we found out the cut
down of state anxiety and of trait anxiety. The report was processed
within grants KEGA 3/5269/07 and VEGA 1/3675/06.
Abstract: Wavelet transform has been extensively used in
machine fault diagnosis and prognosis owing to its strength to deal
with non-stationary signals. The existing Wavelet transform based
schemes for fault diagnosis employ wavelet decomposition of the
entire vibration frequency which not only involve huge
computational overhead in extracting the features but also increases
the dimensionality of the feature vector. This increase in the
dimensionality has the tendency to 'over-fit' the training data and
could mislead the fault diagnostic model. In this paper a novel
technique, envelope wavelet packet transform (EWPT) is proposed in
which features are extracted based on wavelet packet transform of the
filtered envelope signal rather than the overall vibration signal. It not
only reduces the computational overhead in terms of reduced number
of wavelet decomposition levels and features but also improves the
fault detection accuracy. Analytical expressions are provided for the
optimal frequency resolution and decomposition level selection in
EWPT. Experimental results with both actual and simulated machine
fault data demonstrate significant gain in fault detection ability by
EWPT at reduced complexity compared to existing techniques.
Abstract: Flight management system (FMS) is a specialized
computer system that automates a wide variety of in-flight tasks,
reducing the workload on the flight crew to the point that modern
aircraft no longer carry flight engineers or navigators. The primary
function of FMS is to perform the in-flight management of the flight
plan using various sensors (such as GPS and INS often backed up by
radio navigation) to determine the aircraft's position. From the
cockpit FMS is normally controlled through a Control Display Unit
(CDU) which incorporates a small screen and keyboard or touch
screen. This paper investigates the performance of GPS/ INS
integration techniques in which the data fusion process is done using
Kalman filtering. This will include the importance of sensors
calibration as well as the alignment of the strap down inertial
navigation system. The limitations of the inertial navigation systems
are investigated in order to understand why INS sometimes is
integrated with other navigation aids and not just operating in standalone
mode. Finally, both the loosely coupled and tightly coupled
configurations are analyzed for several types of situations and
operational conditions.
Abstract: Can biometrics do what everyone is expecting it will?
And more importantly, should it be doing it? Biometrics is the
buzzword “on the mouth" of everyone, who are trying to use this
technology in a variety of applications. But all this “hype" about
biometrics can be dangerous without a careful evaluation of the real
needs of each application. In this paper I-ll try to focus on the
dangers of using the right technology at the right time in the wrong
place.
Abstract: The data is available in abundance in any business
organization. It includes the records for finance, maintenance,
inventory, progress reports etc. As the time progresses, the data keep
on accumulating and the challenge is to extract the information from
this data bank. Knowledge discovery from these large and complex
databases is the key problem of this era. Data mining and machine
learning techniques are needed which can scale to the size of the
problems and can be customized to the application of business. For
the development of accurate and required information for particular
problem, business analyst needs to develop multidimensional models
which give the reliable information so that they can take right
decision for particular problem. If the multidimensional model does
not possess the advance features, the accuracy cannot be expected.
The present work involves the development of a Multidimensional
data model incorporating advance features. The criterion of
computation is based on the data precision and to include slowly
change time dimension. The final results are displayed in graphical
form.
Abstract: A sequential treatment of ozonation followed by a
Fenton or photo-Fenton process, using black light lamps (365 nm) in
this latter case, has been applied to remove a mixture of
pharmaceutical compounds and the generated by-products both in
ultrapure and secondary treated wastewater. The scientifictechnological
innovation of this study stems from the in situ
generation of hydrogen peroxide from the direct ozonation of
pharmaceuticals, and can later be used in the application of Fenton
and photo-Fenton processes. The compounds selected as models
were sulfamethoxazol and acetaminophen. It should be remarked that
the use of a second process is necessary as a result of the low
mineralization yield reached by the exclusive application of ozone.
Therefore, the influence of the water matrix has been studied in terms
of hydrogen peroxide concentration, individual compound
concentration and total organic carbon removed. Moreover, the
concentration of different iron species in solution has been measured.
Abstract: We introduce the notion of commuting regular Γ-
semiring and discuss some properties of commuting regular Γ-
semiring. We also obtain a necessary and sufficient condition for
Γ-semiring to possess commuting regularity.
Abstract: Interactive push VOD system is a new kind of system
that incorporates push technology and interactive technique. It can
push movies to users at high speeds at off-peak hours for optimal
network usage so as to save bandwidth. This paper presents effective
software-based solution for processing mass downstream data at
terminals of interactive push VOD system, where the service can
download movie according to a viewer-s selection. The downstream
data is divided into two catalogs: (1) the carousel data delivered
according to DSM-CC protocol; (2) IP data delivered according to
Euro-DOCSIS protocol. In order to accelerate download speed and
reduce data loss rate at terminals, this software strategy introduces
caching, multi-thread and resuming mechanisms. The experiments
demonstrate advantages of the software-based solution.
Abstract: What influences microsystems (MEMS) and nanosystems (NEMS) innovation teams apart from technology complexity? Based on in-depth interviews with innovators, this research explores the key influences on innovation teams in the early phases of MEMS/NEMS. Projects are rare and may last from 5 to 10 years or more from idea to concept. As fundamental technology development in MEMS/NEMS is highly complex and interdisciplinary by involving expertise from different basic and engineering disciplines, R&D is rather a 'testing of ideas' with many uncertainties than a clearly structured process. The purpose of this study is to explore the innovation teams- environment and give specific insights for future management practices. The findings are grouped into three major areas: people, know-how and experience, and market. The results highlight the importance and differences of innovation teams- composition, transdisciplinary knowledge, project evaluation and management compared to the counterparts from new product development teams.
Abstract: A series of experiments were carried out to study
unsteady behavior of the flow field as well as the boundary layer of
an airfoil oscillating in plunging motion in a subsonic wind tunnel.
The measurements involved surface pressure distribution
complimented with surface-mounted hot-films. The effect of leadingedge
roughness that simulates surface irregularities on the wind
turbine blades was also studied on variations of aerodynamic loads
and boundary layer behavior.
Abstract: The possibilities of mobile technology generate new
demands for vocational teacher trainers to transform their approach
to work and to incorporate its usage into their ordinary educational
practice. This paper presents findings of a focus discussion group
(FDG) session on the usage of iPads within a school of vocational
teacher education (SoVTE). It aims to clarify how the teacher
trainers are using iPads and what has changed in their work during
the usage of iPads. The analytical framework bases on content
analysis and expansive learning cycle. It was not only found what
kind of a role iPads played in their daily practices but it brought also
into attention how a cultural change regarding the usage of social
media and mobile technology was desperately needed in the whole
work community. Thus, the FGD was abducted for developing the
knowledge practices of the community of the SoVTE.
Abstract: We successfully developed a new straw combustion
technology that efficiently reduces problems with unmanageable deposits inside straw fueled boilers in Zluticka Heating Plant. The
deposits are mainly created by glass-forming melts. We plotted straw compositions in K2O-CaO-SiO2 phase diagram and illustrated
they are in the area of low-melting eutectic poi
melting of ash and the formation of deposits
compositions by injecting additives into biomass fuel
ueled points. To prevent the
deposits, we modified ash
fuel.
Abstract: The use of a Bayesian Hierarchical Model (BHM) to interpret breath measurements obtained during a 13C Octanoic Breath Test (13COBT) is demonstrated. The statistical analysis was implemented using WinBUGS, a commercially available computer package for Bayesian inference. A hierarchical setting was adopted where poorly defined parameters associated with a delayed Gastric Emptying (GE) were able to "borrow" strength from global distributions. This is proved to be a sufficient tool to correct model's failures and data inconsistencies apparent in conventional analyses employing a Non-linear least squares technique (NLS). Direct comparison of two parameters describing gastric emptying ng ( tlag -lag phase, t1/ 2 -half emptying time) revealed a strong correlation between the two methods. Despite our large dataset ( n = 164 ), Bayesian modeling was fast and provided a successful fitting for all subjects. On the contrary, NLS failed to return acceptable estimates in cases where GE was delayed.
Abstract: The existing information system (IS) developments
methods are not met the requirements to resolve the security related
IS problems and they fail to provide a successful integration of
security and systems engineering during all development process
stages. Hence, the security should be considered during the whole
software development process and identified with the requirements
specification. This paper aims to propose an integrated security and
IS engineering approach in all software development process stages
by using i* language. This proposed framework categorizes into three
separate parts: modelling business environment part, modelling
information technology system part and modelling IS security part.
The results show that considering security IS goals in the whole
system development process can have a positive influence on system
implementation and better meet business expectations.
Abstract: Panoramic view generation has always offered
novel and distinct challenges in the field of image processing.
Panoramic view generation is nothing but construction of bigger
view mosaic image from set of partial images of the desired view.
The paper presents a solution to one of the problems of image
seascape formation where some of the partial images are color and
others are grayscale. The simplest solution could be to convert all
image parts into grayscale images and fusing them to get grayscale
image panorama. But in the multihued world, obtaining the colored
seascape will always be preferred. This could be achieved by picking
colors from the color parts and squirting them in grayscale parts of
the seascape. So firstly the grayscale image parts should be colored
with help of color image parts and then these parts should be fused to
construct the seascape image.
The problem of coloring grayscale images has no exact solution.
In the proposed technique of panoramic view generation, the job of
transferring color traits from reference color image to grayscale
image is done by palette based method. In this technique, the color
palette is prepared using pixel windows of some degrees taken from
color image parts. Then the grayscale image part is divided into pixel
windows with same degrees. For every window of grayscale image
part the palette is searched and equivalent color values are found,
which could be used to color grayscale window. For palette
preparation we have used RGB color space and Kekre-s LUV color
space. Kekre-s LUV color space gives better quality of coloring. The
searching time through color palette is improved over the exhaustive
search using Kekre-s fast search technique.
After coloring the grayscale image pieces the next job is fusion of
all these pieces to obtain panoramic view. For similarity estimation
between partial images correlation coefficient is used.
Abstract: Leo Breimans Random Forests (RF) is a recent
development in tree based classifiers and quickly proven to be one of
the most important algorithms in the machine learning literature. It
has shown robust and improved results of classifications on standard
data sets. Ensemble learning algorithms such as AdaBoost and
Bagging have been in active research and shown improvements in
classification results for several benchmarking data sets with mainly
decision trees as their base classifiers. In this paper we experiment to
apply these Meta learning techniques to the random forests. We
experiment the working of the ensembles of random forests on the
standard data sets available in UCI data sets. We compare the
original random forest algorithm with their ensemble counterparts
and discuss the results.
Abstract: This study considers priorities of primary goals to increase policy efficiency of Green ICT. Recently several studies have been published that address how IT is linked to climate change. However, most of the previous studies are limited to Green ICT industrial statute and policy directions. This paper present Green ICT
policy making processes systematically. As a result of the analysis of
Korean Green ICT policy, the following emerged as important to accomplish for Green ICT policy: eco-friendliness, technology evolution, economic efficiency, energy efficiency, and stable supply
of energy. This is an initial study analyzing Green ICT policy, which provides an academic framework that can be used a guideline to
establish Green ICT policy.