Abstract: In this paper, we propose the variational EM inference
algorithm for the multi-class Gaussian process classification model
that can be used in the field of human behavior recognition. This
algorithm can drive simultaneously both a posterior distribution of a
latent function and estimators of hyper-parameters in a Gaussian
process classification model with multiclass. Our algorithm is based
on the Laplace approximation (LA) technique and variational EM
framework. This is performed in two steps: called expectation and
maximization steps. First, in the expectation step, using the Bayesian
formula and LA technique, we derive approximately the posterior
distribution of the latent function indicating the possibility that each
observation belongs to a certain class in the Gaussian process
classification model. Second, in the maximization step, using a derived
posterior distribution of latent function, we compute the maximum
likelihood estimator for hyper-parameters of a covariance matrix
necessary to define prior distribution for latent function. These two
steps iteratively repeat until a convergence condition satisfies.
Moreover, we apply the proposed algorithm with human action
classification problem using a public database, namely, the KTH
human action data set. Experimental results reveal that the proposed
algorithm shows good performance on this data set.
Abstract: The present research aimed at studying the awareness
and attitudes of teachers towards inclusive education. The sample
consisted of 60 teachers, teaching in the primary section (1st – 4th) of
regular schools affiliated to the SSC board in Mumbai. Sample was
selected by Multi-stage cluster sampling technique. A semi-structured
self-constructed interview schedule and a self-constructed attitude
scale was used to study the awareness of teachers about disability and
Inclusive education, and their attitudes towards inclusive education
respectively. Themes were extracted from the interview data and
quantitative data was analyzed using SPSS package. Results revealed
that teachers had some amount of awareness but an inadequate
amount of information on disabilities and inclusive education.
Disability to most (37) teachers meant “an inability to do something”.
The difference between disability and handicap was stated by most as
former being cognitive while handicap being physical in nature. With
regard to Inclusive education, a large number (46) stated that they
were unaware of the term and did not know what it meant. Majority
(52) of them perceived maximum challenges for themselves in an
inclusive set up, and emphasized on the role of teacher training
courses in the area of providing knowledge (49) and training in
teaching methodology (53). Although, 83.3% of teachers held a
moderately positive attitude towards inclusive education, a large
percentage (61.6%) of participants felt that being in inclusive set up
would be very challenging for both children with special needs and
without special needs. Though, most (49) of the teachers stated that
children with special needs should be educated in regular classroom
but they further clarified that only those should be in a regular
classroom who have physical impairments of mild or moderate
degree.
Abstract: Despite all the wide research and literature on the
subject, changing and challenging times often present themselves
with new objectives, fluid politics, and everlasting point of views.
Much is said about the subject and the trend nowadays is watching
every European Union (EU) intervention as a form of neo
colonialism or a form of establishing new markets. The paper will try to establish a perspective on EU influences,
policies and impacts analyzed from multidimensional point of view,
not limiting itself on a narrow external dimension, focusing on a
broader understanding of it diverse contribution to global governance
and peace keeping. Tending to be critical, this paper tends to fall out of extremes,
nether holding a Eurocentric position, nor falling for cheap critic to
the whole failures and impact of EU policies. The ambition is to
show EU as a contributing factor while keeping in mind its nature as
a multi layered actor and with not necessarily coinciding interests
among its member states.
Abstract: For the last decade, researchers have started to focus
their interest on Multicast Group Key Management Framework. The
central research challenge is secure and efficient group key
distribution. The present paper is based on the Bit model based
Secure Multicast Group key distribution scheme using the most
popular absolute encoder output type code named Gray Code. The
focus is of two folds. The first fold deals with the reduction of
computation complexity which is achieved in our scheme by
performing fewer multiplication operations during the key updating
process. To optimize the number of multiplication operations, an
O(1) time algorithm to multiply two N-bit binary numbers which
could be used in an N x N bit-model of reconfigurable mesh is used
in this proposed work. The second fold aims at reducing the amount
of information stored in the Group Center and group members while
performing the update operation in the key content. Comparative
analysis to illustrate the performance of various key distribution
schemes is shown in this paper and it has been observed that this
proposed algorithm reduces the computation and storage complexity
significantly. Our proposed algorithm is suitable for high
performance computing environment.
Abstract: Multiprocessor task scheduling problem for dependent
and independent tasks is computationally complex problem. Many
methods are proposed to achieve optimal running time. As the
multiprocessor task scheduling is NP hard in nature, therefore, many
heuristics are proposed which have improved the makespan of the
problem. But due to problem specific nature, the heuristic method
which provide best results for one problem, might not provide good
results for another problem. So, Simulated Annealing which is meta
heuristic approach is considered. It can be applied on all types of
problems. However, due to many runs, meta heuristic approach takes
large computation time. Hence, the hybrid approach is proposed by
combining the Duplication Scheduling Heuristic and Simulated
Annealing (SA) and the makespan results of Simple Simulated
Annealing and Hybrid approach are analyzed.
Abstract: Steel extended end plate bolted connections are
recommended to be widely utilized in special moment-resisting frame
subjected to monotonic loading. Improper design of steel beam to
column connection can lead to the collapse and fatality of structures.
Therefore comprehensive research studies of beam to column
connection design should be carried out. Also the performance and
effect of corrugated on the strength of beam column end plate
connection up to failure under monotonic loading in horizontal
direction is presented in this paper. The non-linear elastic–plastic
behavior has been considered through a finite element analysis using
the multi-purpose software package LUSAS. The effect of vertically
and horizontally types of corrugated web was also investigated.
Abstract: The aim of the study is to describe and analyze design
of mobile teaching for students collaborative learning in distance
higher education with a focus on mobile technologies as online
webinars (web-based seminars or conferencing) by using laptops,
smart phones, or tablets. These multimedia tools can provide face-toface
interactions, recorded flipped classroom videos and parallel chat
communications. The data collection consists of interviews with 22
students and observations of online face-to-face webinars, as well
two surveys. Theoretically, the study joins the research tradition of
Computer Supported Collaborative learning, CSCL, as well as
Computer Self-Efficacy, CSE concerned with individuals’ media and
information literacy. Important conclusions from the study
demonstrated mobile interactions increased student centered
learning. As the students were appreciating the working methods,
they became more engaged and motivated. The mobile technology
using among student also contributes to increased flexibility between
space and place, as well as media and information literacy.
Abstract: The objective of this work is to carryout critical
comparison of different actuation mechanisms like electrostatic,
thermal, piezoelectric, and magnetic with reference to a micro
cantilever. The relevant parameters like force generated,
displacement are compared in actuation methods. With these results,
helps in choosing the best actuation method for a particular
application. In this study, Comsol/Multiphysics software is used.
Modeling and simulation is done by considering the micro cantilever
of same dimensions as an actuator using all the above mentioned
actuation techniques. In addition to their small size, micro actuators
consume very little power and are capable of accurate results. In this
work, a comparison of actuation mechanisms is done to decide the
efficient system in micro domain.
Abstract: Routing in adhoc networks is a challenge as nodes are
mobile, and links are constantly created and broken. Present ondemand
adhoc routing algorithms initiate route discovery after a path
breaks, incurring significant cost to detect disconnection and
establish a new route. Specifically, when a path is about to be broken,
the source is warned of the likelihood of a disconnection. The source
then initiates path discovery early, avoiding disconnection totally. A
path is considered about to break when link availability decreases.
This study modifies Adhoc On-demand Multipath Distance Vector
routing (AOMDV) so that route handoff occurs through link
availability estimation.
Abstract: The analytical bright two soliton solution of the 3-
coupled nonlinear Schrödinger equations with variable coefficients in
birefringent optical fiber is obtained by Darboux transformation
method. To the design of ultra-speed optical devices, Soliton
interaction and control in birefringence fiber is investigated. Lax pair
is constructed for N coupled NLS system through AKNS method.
Using two-soliton solution, we demonstrate different interaction
behaviors of solitons in birefringent fiber depending on the choice of
control parameters. Our results shows that interactions of optical
solitons have some specific applications such as construction of logic
gates, optical computing, soliton switching, and soliton amplification
in wavelength division multiplexing (WDM) system.
Abstract: This study was aimed to measure effective transverse
relaxation rates (R2*) in the liver and muscle of normal New Zealand
White (NZW) rabbits. R2* relaxation rate has been widely used in
various hepatic diseases for iron overload by quantifying iron contents
in liver. R2* relaxation rate is defined as the reciprocal of T2*
relaxation time and mainly depends on the constituents of tissue.
Different tissues would have different R2* relaxation rates. The signal
intensity decay in Magnetic resonance imaging (MRI) may be
characterized by R2* relaxation rates. In this study, a 1.5T GE Signa
HDxt whole body MR scanner equipped with an 8-channel high
resolution knee coil was used to observe R2* values in NZW rabbit’s
liver and muscle. Eight healthy NZW rabbits weighted 2 ~ 2.5 kg were
recruited. After anesthesia using Zoletil 50 and Rompun 2% mixture,
the abdomen of rabbit was landmarked at the center of knee coil to
perform 3-plane localizer scan using fast spoiled gradient echo
(FSPGR) pulse sequence. Afterwards, multi-planar fast gradient echo
(MFGR) scans were performed with 8 various echo times (TEs) to
acquire images for R2* measurements. Regions of interest (ROIs) at
liver and muscle were measured using Advantage workstation.
Finally, the R2* was obtained by a linear regression of ln(sı) on TE.
The results showed that the longer the echo time, the smaller the signal
intensity. The R2* values of liver and muscle were 44.8 ± 10.9 s-1 and
37.4 ± 9.5 s-1, respectively. It implies that the iron concentration of
liver is higher than that of muscle. In conclusion, the more the iron
contents in tissue, the higher the R2*. The correlations between R2*
and iron content in NZW rabbits might be valuable for further
exploration.
Abstract: The practical efficient approach is suggested for
estimation of the seismoacoustic sources energy in C-OTDR
monitoring systems. This approach is represents the sequential plan
for confidence estimation both the seismoacoustic sources energy, as
well the absorption coefficient of the soil. The sequential plan
delivers the non-asymptotic guaranteed accuracy of obtained
estimates in the form of non-asymptotic confidence regions with
prescribed sizes. These confidence regions are valid for a finite
sample size when the distributions of the observations are unknown.
Thus, suggested estimates are non-asymptotic and nonparametric,
and also these estimates guarantee the prescribed estimation accuracy
in form of prior prescribed size of confidence regions, and prescribed
confidence coefficient value.
Abstract: Fading noise degrades the performance of cellular
communication, most notably in femto- and pico-cells in 3G and 4G
systems. When the wireless channel consists of a small number of
scattering paths, the statistics of fading noise is not analytically
tractable and poses a serious challenge to developing closed
canonical forms that can be analysed and used in the design of
efficient and optimal receivers. In this context, noise is multiplicative
and is referred to as stochastically local fading. In many analytical
investigation of multiplicative noise, the exponential or Gamma
statistics are invoked. More recent advances by the author of this
paper utilized a Poisson modulated-weighted generalized Laguerre
polynomials with controlling parameters and uncorrelated noise
assumptions. In this paper, we investigate the statistics of multidiversity
stochastically local area fading channel when the channel
consists of randomly distributed Rayleigh and Rician scattering
centers with a coherent Nakagami-distributed line of sight component
and an underlying doubly stochastic Poisson process driven by a
lognormal intensity. These combined statistics form a unifying triply
stochastic filtered marked Poisson point process model.
Abstract: Experience is what makes a man perfect. Though we
tend to learn many a different things in life through practice still we
need to go an extra mile to gain experience which would be profitable
only when it is integrated with regular practice. A clear phenomenal
idea is that every teacher is a learner. The centralized idea of this paper would focus on the integrated
practices carried out among the students of Jizan University which
enhances learning through experiences. Integrated practices like
student-directed activities, balanced curriculum, phonological based
activities and use of consistent language would enlarge the vision and
mission of students to earn experience through learning. Students
who receive explicit instruction and guidance could practice the skills
and strategies through student-directed activities such as peer tutoring
and cooperative learning. The second effective practice is to use
consistent language. Consistent language provides students a model
for talking about the new concepts which also enables them to
communicate without hindrances. Phonological awareness is an
important early reading skill for all students. Students generally have
phonemic awareness in their home language can often transfer that
knowledge to a second language. And also a balanced curriculum
requires instruction in all the elements of reading. Reading is the
most effective skill when both basic and higher-order skills are
included on a daily basis. Computer based reading and listening skills
will empower students to understand language in a better way.
English language learners can benefit from sound reading instruction
even before they are fully proficient in English as long as the
instruction is comprehensible. Thus, if students have to be well
equipped in learning they should foreground themselves in various
integrated practices through multifarious experience for which
teachers are moderators and trainers. This type of learning prepares
the students for a constantly changing society which helps them to
meet the competitive world around them for better employability
fulfilling the vision and mission of the institution.
Abstract: Recently, many users have begun to frequently share
their opinions on diverse issues using various social media. Therefore,
numerous governments have attempted to establish or improve
national policies according to the public opinions captured from
various social media. In this paper, we indicate several limitations of
the traditional approaches to analyze public opinion on science and
technology and provide an alternative methodology to overcome these
limitations. First, we distinguish between the science and technology
analysis phase and the social issue analysis phase to reflect the fact that
public opinion can be formed only when a certain science and
technology is applied to a specific social issue. Next, we successively
apply a start list and a stop list to acquire clarified and interesting
results. Finally, to identify the most appropriate documents that fit
with a given subject, we develop a new logical filter concept that
consists of not only mere keywords but also a logical relationship
among the keywords. This study then analyzes the possibilities for the
practical use of the proposed methodology thorough its application to
discover core issues and public opinions from 1,700,886 documents
comprising SNS, blogs, news, and discussions.
Abstract: This article proposes a hybrid algorithm for spectrum
allocation in cognitive radio networks based on the algorithms
Analytical Hierarchical Process (AHP) and Technique for Order of
Preference by Similarity to Ideal Solution (TOPSIS) to improve the
performance of the spectrum mobility of secondary users in cognitive
radio networks. To calculate the level of performance of the proposed algorithm a
comparative analysis between the proposed AHP-TOPSIS, Grey
Relational Analysis (GRA) and Multiplicative Exponent Weighting
(MEW) algorithm is performed. Four evaluation metrics are used.
These metrics are accumulative average of failed handoffs,
accumulative average of handoffs performed, accumulative average
of transmission bandwidth, and accumulative average of the
transmission delay. The results of the comparison show that AHP-TOPSIS Algorithm
provides 2.4 times better performance compared to a GRA Algorithm
and, 1.5 times better than the MEW Algorithm.
Abstract: A Multi-dimensional computational fluid dynamics
(CFD) two-phase model was developed with the aim to simulate
the in-core coolant circuit of a pressurized heavy water reactor
(PHWR) of a commercial nuclear power plant (NPP). Due to the
fact that this PHWR is a Reactor Pressure Vessel type (RPV),
three-dimensional (3D) detailed modelling of the large reservoirs of
the RPV (the upper and lower plenums and the downcomer) were
coupled with an in-house finite volume one-dimensional (1D) code
in order to model the 451 coolant channels housing the nuclear fuel.
Regarding the 1D code, suitable empirical correlations for taking into
account the in-channel distributed (friction losses) and concentrated
(spacer grids, inlet and outlet throttles) pressure losses were used.
A local power distribution at each one of the coolant channels
was also taken into account. The heat transfer between the coolant
and the surrounding moderator was accurately calculated using a
two-dimensional theoretical model. The implementation of subcooled
boiling and condensation models in the 1D code along with the use
of functions for representing the thermal and dynamic properties of
the coolant and moderator (heavy water) allow to have estimations
of the in-core steam generation under nominal flow conditions for a
generic fission power distribution. The in-core mass flow distribution
results for steady state nominal conditions are in agreement with the
expected from design, thus getting a first assessment of the coupled
1/3D model. Results for nominal condition were compared with
those obtained with a previous 1/3D single-phase model getting more
realistic temperature patterns, also allowing visualize low values of
void fraction inside the upper plenum. It must be mentioned that the
current results were obtained by imposing prescribed fission power
functions from literature. Therefore, results are showed with the aim
of point out the potentiality of the developed model.
Abstract: Non-linear dynamic time history analysis is
considered as the most advanced and comprehensive analytical
method for evaluating the seismic response and performance of
multi-degree-of-freedom building structures under the influence of
earthquake ground motions. However, effective and accurate
application of the method requires the implementation of advanced
hysteretic constitutive models of the various structural components
including masonry infill panels. Sophisticated computational research
tools that incorporate realistic hysteresis models for non-linear
dynamic time-history analysis are not popular among the professional
engineers as they are not only difficult to access but also complex and
time-consuming to use. In addition, commercial computer programs
for structural analysis and design that are acceptable to practicing
engineers do not generally integrate advanced hysteretic models
which can accurately simulate the hysteresis behavior of structural
elements with a realistic representation of strength degradation,
stiffness deterioration, energy dissipation and ‘pinching’ under cyclic
load reversals in the inelastic range of behavior. In this scenario,
push-over or non-linear static analysis methods have gained
significant popularity, as they can be employed to assess the seismic
performance of building structures while avoiding the complexities
and difficulties associated with non-linear dynamic time-history
analysis. “Push-over” or non-linear static analysis offers a practical
and efficient alternative to non-linear dynamic time-history analysis
for rationally evaluating the seismic demands. The present paper is
based on the analytical investigation of the effect of distribution of
masonry infill panels over the elevation of planar masonry infilled
reinforced concrete [R/C] frames on the seismic demands using the
capacity spectrum procedures implementing nonlinear static analysis
[pushover analysis] in conjunction with the response spectrum
concept. An important objective of the present study is to numerically
evaluate the adequacy of the capacity spectrum method using
pushover analysis for performance based design of masonry infilled
R/C frames for near-field earthquake ground motions.
Abstract: The paper is focused to the evaluation railway tracks
in the Slovakia by using Multi-Criteria method. Evaluation of railway
tracks has important impacts for the assessment of investment in
technical equipment. Evaluation of railway tracks also has an
important impact for the allocation of marshalling yards. Marshalling
yards are in transport model as centers for the operation assigned
catchment area. This model is one of the effective ways to meet the
development strategy of the European Community's railways. By
applying this model in practice, a transport company can guarantee a
higher quality of service and then expect an increase in performance.
The model is also applicable to other rail networks. This model
supplements a theoretical problem of train formation problem of new
ways of looking at evaluation of factors affecting the organization of
wagon flows.
Abstract: Brain-Computer Interfaces (BCIs) measure brain
signals activity, intentionally and unintentionally induced by users,
and provides a communication channel without depending on the
brain’s normal peripheral nerves and muscles output pathway.
Feature Selection (FS) is a global optimization machine learning
problem that reduces features, removes irrelevant and noisy data
resulting in acceptable recognition accuracy. It is a vital step
affecting pattern recognition system performance. This study presents
a new Binary Particle Swarm Optimization (BPSO) based feature
selection algorithm. Multi-layer Perceptron Neural Network
(MLPNN) classifier with backpropagation training algorithm and
Levenberg-Marquardt training algorithm classify selected features.