Abstract: Scripts are one of the basic text resources to understand
broadcasting contents. Topic modeling is the method to get the
summary of the broadcasting contents from its scripts. Generally,
scripts represent contents descriptively with directions and speeches,
and provide scene segments that can be seen as semantic units.
Therefore, a script can be topic modeled by treating a scene segment
as a document. Because scene segments consist of speeches mainly,
however, relatively small co-occurrences among words in the scene
segments are observed. This causes inevitably the bad quality of
topics by statistical learning method. To tackle this problem, we
propose a method to improve topic quality with additional word
co-occurrence information obtained using scene similarities. The
main idea of improving topic quality is that the information that
two or more texts are topically related can be useful to learn high
quality of topics. In addition, more accurate topical representations
lead to get information more accurate whether two texts are related
or not. In this paper, we regard two scene segments are related
if their topical similarity is high enough. We also consider that
words are co-occurred if they are in topically related scene segments
together. By iteratively inferring topics and determining semantically
neighborhood scene segments, we draw a topic space represents
broadcasting contents well. In the experiments, we showed the
proposed method generates a higher quality of topics from Korean
drama scripts than the baselines.
Abstract: This paper aims to analysis the behavior of DC corona
discharge in wire-to-plate electrostatic precipitators (ESP). Currentvoltage
curves are particularly analyzed. Experimental results show
that discharge current is strongly affected by the applied voltage. The proposed method of current identification is to use the method
of least squares. Least squares problems that of into two categories:
linear or ordinary least squares and non-linear least squares,
depending on whether or not the residuals are linear in all unknowns.
The linear least-squares problem occurs in statistical regression
analysis; it has a closed-form solution. A closed-form solution (or
closed form expression) is any formula that can be evaluated in a
finite number of standard operations. The non-linear problem has no
closed-form solution and is usually solved by iterative.
Abstract: By using a fixed point theorem of a sum operator, the
existence and uniqueness of positive solution for a class of
boundary value problem of nonlinear fractional differential equation
is studied. An iterative scheme is constructed to approximate it.
Finally, an example is given to illustrate the main result.
Abstract: In this paper, according to the classical algorithm
LSQR for solving the least-squares problem, an iterative method is
proposed for least-squares solution of constrained matrix equation. By
using the Kronecker product, the matrix-form LSQR is presented to
obtain the like-minimum norm and minimum norm solutions in a
constrained matrix set for the symmetric arrowhead matrices. Finally,
numerical examples are also given to investigate the performance.
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: As computing technology advances, smartphone
applications can assist student learning in a pervasive way. For
example, the idea of using mobile apps for the PA Common Trees,
Pests, Pathogens, in the field as a reference tool allows middle school
students to learn about trees and associated pests/pathogens without
bringing a textbook. While working on the development of three heterogeneous mobile
apps, we ran into numerous challenges. Both the traditional waterfall
model and the more modern agile methodologies failed in practice.
The waterfall model emphasizes the planning of the duration for each
phase. When the duration of each phase is not consistent with the
availability of developers, the waterfall model cannot be employed.
When applying Agile Methodologies, we cannot maintain the high
frequency of the iterative development review process, known as
‘sprints’. In this paper, we discuss the challenges and solutions. We
propose a hybrid model known as the Relay Race Methodology to
reflect the concept of racing and relaying during the process of
software development in practice. Based on the development project,
we observe that the modeling of the relay race transition between any
two phases is manifested naturally. Thus, we claim that the RRM
model can provide a de fecto rather than a de jure basis for the core
concept in the software development model. In this paper, the background of the project is introduced first.
Then, the challenges are pointed out followed by our solutions.
Finally, the experiences learned and the future works are presented.
Abstract: Annihilations, phase shifts, scattering lengths and
elastic cross sections of low energy positrons scattering from
magnesium atoms were studied using the least-squares variational
method (LSVM). The possibility of positron binding to the
magnesium atoms is investigated. A trial wave function is suggested
to represent e+-Mg elastic scattering and scattering parameters were
derived to estimate the binding energy and annihilation rates. The
trial function is taken to depend on several adjustable parameters, and
is improved iteratively by increasing the number of terms. The
present results have the same behavior as reported semi-empirical,
theoretical and experimental results. Especially, the estimated
positive scattering length supports the possibility of positronmagnesium
bound state system that was confirmed in previous
experimental and theoretical work.
Abstract: This study and the field test comparisons were carried
out on the Algerian Derguna – Setif transmission systems. The
transmission line of normal voltage 225 kV is 65 km long,
transported and uses twin bundle conductors protected with two
shield wires of transposed galvanized steel. An iterative finite-element method is used to solve Poisons
equation. Two algorithms are proposed for satisfying the current
continuity condition and updating the space-charge density. A new approach to the problem of corona discharge in
transmission system has been described in this paper. The effect of
varying the configurations and wires number is also investigated. The
analysis of this steady is important in the design of HVDC
transmission lines. The potential and electric field have been
calculating in locations singular points of the system.
Abstract: This study was carried out for an underground subway station at Seoul Metro, Korea. The optimal set-points of the ventilation control system are determined every 3 hours, then, the ventilation controller adjusts the ventilation fan speed according to the optimal set-point changes. Compared to manual ventilation system which is operated irrespective of the OAQ, the IDP-based ventilation control system saves 3.7% of the energy consumption. Compared to the fixed set-point controller which is operated irrespective of the IAQ diurnal variation, the IDP-based controller shows better performance with a 2% decrease in energy consumption, maintaining the comfortable IAQ range inside the station.
Abstract: In this paper, analysis of an infinite beam resting on
multilayer tensionless extensible geosynthetic reinforced granular
fill-poor soil system overlying soft soil strata under moving load with
constant velocity is presented. The beam is subjected to a
concentrated load moving with constant velocity. The upper
reinforced granular bed is modeled by a rough membrane embedded
in Pasternak shear layer overlying a series of compressible nonlinear
winkler springs representing the underlying the very poor soil. The
multilayer tensionless extensible geosynthetic layer has been
assumed to deform such that at interface the geosynthetic and the soil
have some deformation. Nonlinear behaviour of granular fill and the
very poor soil has been considered in the analysis by means of
hyperbolic constitutive relationships. Governing differential
equations of the soil foundation system have been obtained and
solved with the help of appropriate boundary conditions. The solution
has been obtained by employing finite difference method by means of
Gauss-Siedal iterative scheme. Detailed parametric study has been
conducted to study the influence of various parameters on the
response of soil–foundation system under consideration by means of
deflection and bending moment in the beam and tension mobilized in
the geosynthetic layer. These parameters include magnitude of
applied load, velocity of load, damping, ultimate resistance of poor
soil and granular fill layer. Range of values of parameters has been
considered as per Indian Railway conditions. This study clearly
observed that the comparisons of multilayer tensionless extensible
geosynthetic reinforcement with poor foundation soil and magnitude
of applied load, relative compressibility of granular fill and ultimate
resistance of poor soil has significant influence on the response of
soil–foundation system.
Abstract: Due to the continuous increment of the load demand,
identification of weaker buses, improvement of voltage profile and
power losses in the context of the voltage stability problems has
become one of the major concerns for the larger, complex,
interconnected power systems. The objective of this paper is to
review the impact of Flexible AC Transmission System (FACTS)
controller in Wind generators connected electrical network for
maintaining voltage stability. Wind energy could be the growing
renewable energy due to several advantages. The influence of wind
generators on power quality is a significant issue; non uniform power
production causes variations in system voltage and frequency.
Therefore, wind farm requires high reactive power compensation; the
advances in high power semiconducting devices have led to the
development of FACTS. The FACTS devices such as for example
SVC inject reactive power into the system which helps in maintaining
a better voltage profile. The performance is evaluated on an IEEE 14
bus system, two wind generators are connected at low voltage buses
to meet the increased load demand and SVC devices are integrated at
the buses with wind generators to keep voltage stability. Power
flows, nodal voltage magnitudes and angles of the power network are
obtained by iterative solutions using MIPOWER.
Abstract: Microscopic simulation tool kits allow for
consideration of the two processes of railway operations and the
previous timetable production. Block occupation conflicts on both
process levels are often solved by using defined train priorities. These
conflict resolutions (dispatching decisions) generate reactionary
delays to the involved trains. The sum of reactionary delays is
commonly used to evaluate the quality of railway operations, which
describes the timetable robustness. It is either compared to an
acceptable train performance or the delays are appraised
economically by linear monetary functions. It is impossible to
adequately evaluate dispatching decisions without a well-founded
objective function. This paper presents a new approach for the
evaluation of dispatching decisions. The approach uses mode choice
models and considers the behaviour of the end-customers. These
models evaluate the reactionary delays in more detail and consider
other competing modes of transport. The new approach pursues the
coupling of a microscopic model of railway operations with the
macroscopic choice mode model. At first, it will be implemented for
railway operations process but it can also be used for timetable
production. The evaluation considers the possibility for the customer
to interchange to other transport modes. The new approach starts to
look at rail and road, but it can also be extended to air travel. The
result of mode choice models is the modal split. The reactions by the
end-customers have an impact on the revenue of the train operating
companies. Different purposes of travel have different payment
reserves and tolerances towards late running. Aside from changes to
revenues, longer journey times can also generate additional costs.
The costs are either time- or track-specific and arise from required
changes to rolling stock or train crew cycles. Only the variable values
are summarised in the contribution margin, which is the base for the
monetary evaluation of delays. The contribution margin is calculated
for different possible solutions to the same conflict. The conflict
resolution is optimised until the monetary loss becomes minimal. The
iterative process therefore determines an optimum conflict resolution
by monitoring the change to the contribution margin. Furthermore, a
monetary value of each dispatching decision can also be derived.
Abstract: One of the main challenges in using the Discrete
Element Method (DEM) is to specify the correct input parameter
values. In general, the models are sensitive to the input parameter
values and accurate results can only be achieved if the correct values
are specified. For the linear contact model, micro-parameters such as
the particle density, stiffness, coefficient of friction, as well as the
particle size and shape distributions are required. There is a need for
a procedure to accurately calibrate these parameters before any
attempt can be made to accurately model a complete bulk materials
handling system. Since DEM is often used to model applications in
the mining and quarrying industries, a calibration procedure was
developed for materials that consist of relatively large (up to 40 mm
in size) particles. A coarse crushed aggregate was used as the test
material. Using a specially designed large shear box with a diameter
of 590 mm, the confined Young’s modulus (bulk stiffness) and
internal friction angle of the material were measured by means of the
confined compression test and the direct shear test respectively. DEM
models of the experimental setup were developed and the input
parameter values were varied iteratively until a close correlation
between the experimental and numerical results was achieved. The
calibration process was validated by modelling the pull-out of an
anchor from a bed of material. The model results compared well with
experimental measurement.
Abstract: This paper presents a study of SIW circuits (Substrate
Integrated Waveguide) with a rigorous and fast original approach
based on Iterative process (WCIP). The theoretical suggested study is
validated by the simulation of two different examples of SIW
circuits. The obtained results are in good agreement with those of
measurement and with software HFSS.
Abstract: The Cone Penetration Test (CPT) is a common in-situ
test which generally investigates a much greater volume of soil more
quickly than possible from sampling and laboratory tests. Therefore,
it has the potential to realize both cost savings and assessment of soil
properties rapidly and continuously. The principle objective of this
paper is to demonstrate the feasibility and efficiency of using
artificial neural networks (ANNs) to predict the soil angle of internal
friction (Φ) and the soil modulus of elasticity (E) from CPT results
considering the uncertainties and non-linearities of the soil. In
addition, ANNs are used to study the influence of different
parameters and recommend which parameters should be included as
input parameters to improve the prediction. Neural networks discover
relationships in the input data sets through the iterative presentation
of the data and intrinsic mapping characteristics of neural topologies.
General Regression Neural Network (GRNN) is one of the powerful
neural network architectures which is utilized in this study. A large
amount of field and experimental data including CPT results, plate
load tests, direct shear box, grain size distribution and calculated data
of overburden pressure was obtained from a large project in the
United Arab Emirates. This data was used for the training and the
validation of the neural network. A comparison was made between
the obtained results from the ANN's approach, and some common
traditional correlations that predict Φ and E from CPT results with
respect to the actual results of the collected data. The results show
that the ANN is a very powerful tool. Very good agreement was
obtained between estimated results from ANN and actual measured
results with comparison to other correlations available in the
literature. The study recommends some easily available parameters
that should be included in the estimation of the soil properties to
improve the prediction models. It is shown that the use of friction
ration in the estimation of Φ and the use of fines content in the
estimation of E considerable improve the prediction models.
Abstract: The planning of geological survey works is an
iterative process which involves planner, geologist, civil engineer and
other stakeholders, who perform different roles and have different
points of view. Traditionally, the team used paper maps or CAD
drawings to present the proposal which is not an efficient way to
present and share idea on the site investigation proposal such as
sitting of borehole location or seismic survey lines. This paper
focuses on how a GIS approach can be utilised to develop a webbased
system to support decision making process in the planning of
geological survey works and also to plan site activities carried out by
Singapore Geological Office (SGO). The authors design a framework
of building an interactive web-based GIS system, and develop a
prototype, which enables the users to obtain rapidly existing
geological information and also to plan interactively borehole
locations and seismic survey lines via a web browser. This prototype
system is used daily by SGO and has shown to be effective in
increasing efficiency and productivity as the time taken in the
planning of geological survey works is shortened. The prototype
system has been developed using the ESRI ArcGIS API 3.7 for Flex
which is based on the ArcGIS 10.2.1 platform.
Abstract: In this paper, the improvement by deconvolution of
the depth resolution in Secondary Ion Mass Spectrometry (SIMS)
analysis is considered. Indeed, we have developed a new Tikhonov-
Miller deconvolution algorithm where a priori model of the solution
is included. This is a denoisy and pre-deconvoluted signal obtained
from: firstly, by the application of wavelet shrinkage algorithm,
secondly by the introduction of the obtained denoisy signal in an
iterative deconvolution algorithm. In particular, we have focused the
light on the effect of the iterations number on the evolution of the
deconvoluted signals. The SIMS profiles are multilayers of Boron in
Silicon matrix.
Abstract: High Peak to Average Power Ratio (PAPR) of the
transmitted signal is a serious problem in multicarrier systems (MC),
such as Orthogonal Frequency Division Multiplexing (OFDM), or in
Multi-Carrier Code Division Multiple Access (MC-CDMA) systems,
due to large number of subcarriers. This effect is possible reduce with
some PAPR reduction techniques. Spreading sequences at the
presence of Saleh and Rapp models of high power amplifier (HPA)
have big influence on the behavior of system. In this paper we
investigate the bit-error-rate (BER) performance of MC-CDMA
systems. Basically we can see from simulations that the MC-CDMA
system with Iterative algorithm can be providing significantly better
results than the MC-CDMA system. The results of our analyses are
verified via simulation.
Abstract: An inversion-free iterative algorithm is presented for
solving nonlinear matrix equation with a stepsize parameter t. The
existence of the maximal solution is discussed in detail, and the
method for finding it is proposed. Finally, two numerical examples
are reported that show the efficiency of the method.
Abstract: Analysis of real life problems often results in linear
systems of equations for which solutions are sought. The method to
employ depends, to some extent, on the properties of the coefficient
matrix. It is not always feasible to solve linear systems of equations
by direct methods, as such the need to use an iterative method
becomes imperative. Before an iterative method can be employed
to solve a linear system of equations there must be a guaranty that
the process of solution will converge. This guaranty, which must
be determined apriori, involve the use of some criterion expressible
in terms of the entries of the coefficient matrix. It is, therefore,
logical that the convergence criterion should depend implicitly on the
algebraic structure of such a method. However, in deference to this
view is the practice of conducting convergence analysis for Gauss-
Seidel iteration on a criterion formulated based on the algebraic
structure of Jacobi iteration. To remedy this anomaly, the Gauss-
Seidel iteration was studied for its algebraic structure and contrary
to the usual assumption, it was discovered that some property of the
iteration matrix of Gauss-Seidel method is only diagonally dominant
in its first row while the other rows do not satisfy diagonal dominance.
With the aid of this structure we herein fashion out an improved
version of Gauss-Seidel iteration with the prospect of enhancing
convergence and robustness of the method. A numerical section is
included to demonstrate the validity of the theoretical results obtained
for the improved Gauss-Seidel method.