Abstract: In field of Computer Science and Mathematics,
sorting algorithm is an algorithm that puts elements of a list in a
certain order i.e. ascending or descending. Sorting is perhaps the
most widely studied problem in computer science and is frequently
used as a benchmark of a system-s performance. This paper
presented the comparative performance study of four sorting
algorithms on different platform. For each machine, it is found that
the algorithm depends upon the number of elements to be sorted. In
addition, as expected, results show that the relative performance of
the algorithms differed on the various machines. So, algorithm
performance is dependent on data size and there exists impact of
hardware also.
Abstract: This study examines the use of the persuasive strategy
of deixis and personalization in advertising slogans. This rhetorical/
stylistic and linguistic strategy has been found to be widely used in
advertising slogans for over a century. A total of five hundred
advertising slogans of multinational companies in both product and
service sectors were obtained. The analysis reveals the 3 main
components of this strategy as being deictic words, absolute
uniqueness and personal pronouns. The percentage and mean of the
use of the 3 components are tabulated. The findings show that
advertisers have used this persuasive strategy in creative ways to
persuade consumers to buy their products and services.
Abstract: This paper proposes a bi-objective model for the
facility location problem under a congestion system. The idea of the
model is motivated by applications of locating servers in bank
automated teller machines (ATMS), communication networks, and so
on. This model can be specifically considered for situations in which
fixed service facilities are congested by stochastic demand within
queueing framework. We formulate this model with two perspectives
simultaneously: (i) customers and (ii) service provider. The
objectives of the model are to minimize (i) the total expected
travelling and waiting time and (ii) the average facility idle-time.
This model represents a mixed-integer nonlinear programming
problem which belongs to the class of NP-hard problems. In addition,
to solve the model, two metaheuristic algorithms including nondominated
sorting genetic algorithms (NSGA-II) and non-dominated
ranking genetic algorithms (NRGA) are proposed. Besides, to
evaluate the performance of the two algorithms some numerical
examples are produced and analyzed with some metrics to determine
which algorithm works better.
Abstract: In this paper we address a multi-objective scheduling problem for unrelated parallel machines. In unrelated parallel systems, the processing cost/time of a given job on different machines may vary. The objective of scheduling is to simultaneously determine the job-machine assignment and job sequencing on each machine. In such a way the total cost of the schedule is minimized. The cost function consists of three components, namely; machining cost, earliness/tardiness penalties and makespan related cost. Such scheduling problem is combinatorial in nature. Therefore, a Simulated Annealing approach is employed to provide good solutions within reasonable computational times. Computational results show that the proposed approach can efficiently solve such complicated problems.
Abstract: The objective this study was to characterize and
develop anthropomorphic liver phantoms in tomography hepatic
procedures for quality control and improvement professionals in
nuclear medicine. For the conformation of the anthropomorphic
phantom was used in plaster and acrylic. We constructed three
phantoms representing processes with liver cirrhosis. The phantoms
were filled with 99mTc diluted with water to obtain the scintigraphic
images. Tomography images were analyzed anterior and posterior
phantom representing a body with a greater degree cirrhotic. It was
noted that the phantoms allow the acquisition of images similar to
real liver with cirrhosis. Simulations of hemangiomas may contribute
to continued professional education of nuclear medicine, on the
question of image acquisition, allowing of the study parameters such
of the matrix, energy window and count statistics.
Abstract: Web sites are rapidly becoming the preferred media
choice for our daily works such as information search, company
presentation, shopping, and so on. At the same time, we live in a
period where visual appearances play an increasingly important
role in our daily life. In spite of designers- effort to develop a web
site which be both user-friendly and attractive, it would be difficult
to ensure the outcome-s aesthetic quality, since the visual
appearance is a matter of an individual self perception and opinion.
In this study, it is attempted to develop an automatic system for
web pages aesthetic evaluation which are the building blocks of
web sites. Based on the image processing techniques and artificial
neural networks, the proposed method would be able to categorize
the input web page according to its visual appearance and aesthetic
quality. The employed features are multiscale/multidirectional
textural and perceptual color properties of the web pages, fed to
perceptron ANN which has been trained as the evaluator. The
method is tested using university web sites and the results
suggested that it would perform well in the web page aesthetic
evaluation tasks with around 90% correct categorization.
Abstract: This paper presents a comparative analysis of a new
unsupervised PCA-based technique for steel plates texture segmentation
towards defect detection. The proposed scheme called Variance
Based Component Analysis or VBCA employs PCA for feature
extraction, applies a feature reduction algorithm based on variance of
eigenpictures and classifies the pixels as defective and normal. While
the classic PCA uses a clusterer like Kmeans for pixel clustering,
VBCA employs thresholding and some post processing operations to
label pixels as defective and normal. The experimental results show
that proposed algorithm called VBCA is 12.46% more accurate and
78.85% faster than the classic PCA.
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: The simulation of extrusion process is studied widely
in order to both increase products and improve quality, with broad
application in wire coating. The annular tube-tooling extrusion was
set up by a model that is termed as Navier-Stokes equation in
addition to a rheological model of differential form based on singlemode
exponential Phan-Thien/Tanner constitutive equation in a twodimensional
cylindrical coordinate system for predicting the
contraction point of the polymer melt beyond the die. Numerical
solutions are sought through semi-implicit Taylor-Galerkin pressurecorrection
finite element scheme. The investigation was focused on
incompressible creeping flow with long relaxation time in terms of
Weissenberg numbers up to 200. The isothermal case was considered
with surface tension effect on free surface in extrudate flow and no
slip at die wall. The Stream Line Upwind Petrov-Galerkin has been
proposed to stabilize solution. The structure of mesh after die exit
was adjusted following prediction of both top and bottom free
surfaces so as to keep the location of contraction point around one
unit length which is close to experimental results. The simulation of
extrusion process is studied widely in order to both increase products
and improve quality, with broad application in wire coating. The
annular tube-tooling extrusion was set up by a model that is termed
as Navier-Stokes equation in addition to a rheological model of
differential form based on single-mode exponential Phan-
Thien/Tanner constitutive equation in a two-dimensional cylindrical
coordinate system for predicting the contraction point of the polymer
melt beyond the die. Numerical solutions are sought through semiimplicit
Taylor-Galerkin pressure-correction finite element scheme.
The investigation was focused on incompressible creeping flow with
long relaxation time in terms of Weissenberg numbers up to 200. The
isothermal case was considered with surface tension effect on free
surface in extrudate flow and no slip at die wall. The Stream Line
Upwind Petrov-Galerkin has been proposed to stabilize solution. The
structure of mesh after die exit was adjusted following prediction of
both top and bottom free surfaces so as to keep the location of
contraction point around one unit length which is close to
experimental results.
Abstract: ECG contains very important clinical information about the cardiac activities of the heart. Often the ECG signal needs to be captured for a long period of time in order to identify abnormalities in certain situations. Such signal apart of a large volume often is characterised by low quality due to the noise and other influences. In order to extract features in the ECG signal with time-varying characteristics at first need to be preprocessed with the best parameters. Also, it is useful to identify specific parts of the long lasting signal which have certain abnormalities and to direct the practitioner to those parts of the signal. In this work we present a method based on wavelet transform, standard deviation and variable threshold which achieves 100% accuracy in identifying the ECG signal peaks and heartbeat as well as identifying the standard deviation, providing a quick reference to abnormalities.
Abstract: Wireless sensor networks (WSN) consists of many
sensor nodes that are placed on unattended environments such as
military sites in order to collect important information.
Implementing a secure protocol that can prevent forwarding forged
data and modifying content of aggregated data and has low delay
and overhead of communication, computing and storage is very
important. This paper presents a new protocol for concealed data
aggregation (CDA). In this protocol, the network is divided to
virtual cells, nodes within each cell produce a shared key to send
and receive of concealed data with each other. Considering to data
aggregation in each cell is locally and implementing a secure
authentication mechanism, data aggregation delay is very low and
producing false data in the network by malicious nodes is not
possible. To evaluate the performance of our proposed protocol, we
have presented computational models that show the performance
and low overhead in our protocol.
Abstract: This paper was aimed to survey the level of awareness
of traditional grocery stores in Bangkok in these categories: location,
service quality, risk, shopping, worthwhile, shopping satisfaction, and
future shopping intention. The paper was also aimed to survey factors
influencing the decision to shop at traditional grocery stores in
Bangkok in the future. The findings revealed that consumers had a
high level of awareness of traditional grocery stores in Bangkok.
Consumers were aware that the price was higher and it was riskier to
buy goods and services at traditional grocery stores but they still had
a high level of preference to patronage traditional grocery stores. This
was due to the reasons that there was a high level of satisfaction from
the factors of the friendliness of the owner, the ability to negotiate the
price, the ability to buy on credit, free delivery, and the enjoyment to
meet with other customers in the same neighborhood.
Abstract: In the Fe-3%Si sheets, grade Hi-B, with AlN and MnS
as inhibitors, the Goss grains which abnormally grow do not have a
size greater than the average size of the primary matrix. In this
heterogeneous microstructure, the size factor is not a required
condition for the secondary recrystallization. The onset of the small
Goss grain abnormal growth appears to be related to a particular
behavior of their grain boundaries, to the local texture and to the
distribution of the inhibitors. The presence and the evolution of
oriented clusters ensure to the small Goss grains a favorable
neighborhood to grow. The modified Monte-Carlo approach, which
is applied, considers the local environment of each grain. The grain
growth is dependent of its real spatial position; the matrix
heterogeneity is then taken into account. The grain growth conditions
are considered in the global matrix and in different matrixes
corresponding to A component clusters. The grain growth behaviour
is considered with introduction of energy only, energy and mobility,
energy and mobility and precipitates.
Abstract: The job shop scheduling problem (JSSP) is a
notoriously difficult problem in combinatorial optimization. This
paper presents a hybrid artificial immune system for the JSSP with the
objective of minimizing makespan. The proposed approach combines
the artificial immune system, which has a powerful global exploration
capability, with the local search method, which can exploit the optimal
antibody. The antibody coding scheme is based on the operation based
representation. The decoding procedure limits the search space to the
set of full active schedules. In each generation, a local search heuristic
based on the neighborhood structure proposed by Nowicki and
Smutnicki is applied to improve the solutions. The approach is tested
on 43 benchmark problems taken from the literature and compared
with other approaches. The computation results validate the
effectiveness of the proposed algorithm.
Abstract: The Indian subcontinent is facing a massive challenge with regards to the energy security in member countries, i.e. providing a reliable source of electricity to facilitate development across various sectors of the economy and thereby achieve the developmental targets it has set for itself. A highly precarious situation exists in the subcontinent which is observed in the series of system failures which most of the times leads to system collapses-blackouts. To mitigate the issues related with energy security as well as keep in check the increasing supply demand gap, a possible solution that stands in front of the subcontinent is the deployment of an interconnected electricity ‘Supergrid’ designed to carry huge quanta of power across the sub continent as well as provide the infra structure for RES integration. This paper assesses the need and conditions for a Supergrid deployment and consequently proposes a meshed topology based on VSC HVDC converters for the Supergrid modeling.
Abstract: Analysis and visualization of microarraydata is veryassistantfor biologists and clinicians in the field of diagnosis and treatment of patients. It allows Clinicians to better understand the structure of microarray and facilitates understanding gene expression in cells. However, microarray dataset is a complex data set and has thousands of features and a very small number of observations. This very high dimensional data set often contains some noise, non-useful information and a small number of relevant features for disease or genotype. This paper proposes a non-linear dimensionality reduction algorithm Local Principal Component (LPC) which aims to maps high dimensional data to a lower dimensional space. The reduced data represents the most important variables underlying the original data. Experimental results and comparisons are presented to show the quality of the proposed algorithm. Moreover, experiments also show how this algorithm reduces high dimensional data whilst preserving the neighbourhoods of the points in the low dimensional space as in the high dimensional space.
Abstract: As a vital activity for companies, new product
development (NPD) is also a very risky process due to the high
uncertainty degree encountered at every development stage and the
inevitable dependence on how previous steps are successfully
accomplished. Hence, there is an apparent need to evaluate new
product initiatives systematically and make accurate decisions under
uncertainty. Another major concern is the time pressure to launch a
significant number of new products to preserve and increase the
competitive power of the company. In this work, we propose an
integrated decision-making framework based on neural networks and
fuzzy logic to make appropriate decisions and accelerate the
evaluation process. We are especially interested in the two initial
stages where new product ideas are selected (go/no go decision) and
the implementation order of the corresponding projects are
determined. We show that this two-staged intelligent approach allows
practitioners to roughly and quickly separate good and bad product
ideas by making use of previous experiences, and then, analyze a
more shortened list rigorously.
Abstract: In this work, we present a comparison between
different techniques of image compression. First, the image is
divided in blocks which are organized according to a certain scan.
Later, several compression techniques are applied, combined or
alone. Such techniques are: wavelets (Haar's basis), Karhunen-Loève
Transform, etc. Simulations show that the combined versions are the
best, with minor Mean Squared Error (MSE), and higher Peak Signal
to Noise Ratio (PSNR) and better image quality, even in the presence
of noise.
Abstract: The heart tissue is an excitable media. A Cellular
Automata is a type of model that can be used to model cardiac action
potential propagation. One of the advantages of this approach against
the methods based on differential equations is its high speed in large
scale simulations. Recent cellular automata models are not able to
avoid flat edges in the result patterns or have large neighborhoods. In
this paper, we present a new model to eliminate flat edges by
minimum number of neighbors.
Abstract: In this study, structural, mechanical, thermal and
electrical properties of poly (lactic acid) (PLA) nanocomposites with
low-loaded (0-1.5 wt%) untreated, heat and nitric acid treated multiwalled
carbon nanotubes (MWCNTs) were studied. Among the
composites, untreated 0.5 wt % MWCNTs and acid-treated 1.0 wt%
MWCNTs reinforced PLA show the tensile strength and modulus
values higher than the others. These two samples along with pure
PLA exhibit the stable orthorhombic α-form, whilst other samples
reveal the less stable orthorhombic β-form, as demonstrated by X-ray
diffraction study. Differential scanning calorimetry reveals the
evolution of the mentioned different phases by controlled cooling and
discloses an enhancement of PLA crystallization by nanotubes
incorporation. Thermogravimetric analysis shows that the MWCNTs
loaded sample degraded faster than PLA. Surface resistivity of the
nanocomposites is found to be dropped drastically by a factor of 1013
with a low loading of MWCNTs (1.5 wt%).