Abstract: This paper presents the design and implementation of CASTE, a Cloud-based automatic software test environment. We first present the architecture of CASTE, then the main packages and classes of it are described in detail. CASTE is built upon a private Infrastructure as a Service platform. Through concentrated resource management of virtualized testing environment and automatic execution control of test scripts, we get a better solution to the testing resource utilization and test automation problem. Experiments on CASTE give very appealing results.
Abstract: In this research study, an intelligent detection system
to support medical diagnosis and detection of abnormal lesions by
processing endoscopic images is presented. The images used in this
study have been obtained using the M2A Swallowable Imaging
Capsule - a patented, video color-imaging disposable capsule.
Schemes have been developed to extract texture features from the
fuzzy texture spectra in the chromatic and achromatic domains for a
selected region of interest from each color component histogram of
endoscopic images. The implementation of an advanced fuzzy
inference neural network which combines fuzzy systems and
artificial neural networks and the concept of fusion of multiple
classifiers dedicated to specific feature parameters have been also
adopted in this paper. The achieved high detection accuracy of the
proposed system has provided thus an indication that such intelligent
schemes could be used as a supplementary diagnostic tool in
endoscopy.
Abstract: In Public Wireless LANs(PWLANs), user anonymity
is an essential issue. Recently, Juang et al. proposed an anonymous
authentication and key exchange protocol using smart cards in
PWLANs. They claimed that their proposed scheme provided identity
privacy, mutual authentication, and half-forward secrecy. In this paper,
we point out that Juang et al.'s protocol is vulnerable to the
stolen-verifier attack and does not satisfy user anonymity.
Abstract: The environment pollution with pesticides and heavy
metals is a recognized problem nowadays, with extension to the
global scale the tendency of amplification. Even with all the progress
in the environmental field, both in the emphasize of the effect of the
pollutants upon health, the linked studies environment-health are
insufficient, not only in Romania but all over the world also. We aim
to describe the particular situation in Romania regarding the
uncontrolled use of pesticides, to identify and evaluate the risk zones
for health and the environment in Romania, with the final goal of
designing adequate programs for reduction and control of the risk
sources. An exploratory study was conducted to determine the
magnitude of the pesticide use problem in a population living in
Saliste, a rural setting in Transylvania, Romania. The significant
stakeholders in Saliste region were interviewed and a sample from
the population living in Saliste area was selected to fill in a designed
questionnaire. All the selected participants declared that they used
pesticides in their activities for more than one purpose. They
declared they annually applied pesticides for a period of time
between 11 and 30 years, from 5 to 9 days per year on average,
mainly on crops situated at some distance from the houses but high
risk behavior was identified as the volunteers declared the use of
pesticides in the backyard gardens, near their homes, where children
were playing. The pesticide applicators did not have the necessary
knowledge about safety and exposure. The health data must be
correlated with exposure biomarkers in attempt to identify the
possible health effects of the pesticides exposure. Future plans
include educational campaigns to raise the awareness of the
population on the danger of uncontrolled use of pesticides.
Abstract: Existing ground movement surveillance technologies
at airports are subjected to limitations due to shadowing effects or
multiple reflections. Therefore, there is a strong demand for a new
sensing technology, which will be cost effective and will provide
detection of non-cooperative targets under any weather conditions.
This paper aims to present a new intelligent system, developed
within the framework of the EC-funded ISMAEL project, which is
based on a new magnetic sensing technology and provides detection,
tracking and automatic classification of targets moving on the airport
surface. The system is currently being installed at two European
airports. Initial experimental results under real airport traffic
demonstrate the great potential of the proposed system.
Abstract: Everyday the usages of the Internet increase and simply a world of the data become accessible. Network providers do not want to let the provided services to be used in harmful or terrorist affairs, so they used a variety of methods to protect the special regions from the harmful data. One of the most important methods is supposed to be the firewall. Firewall stops the transfer of such packets through several ways, but in some cases they do not use firewall because of its blind packet stopping, high process power needed and expensive prices. Here we have proposed a method to find a discriminate function to distinguish between usual packets and harmful ones by the statistical processing on the network router logs. So an administrator can alarm to the user. This method is very fast and can be used simply in adjacent with the Internet routers.
Abstract: In this paper, we propose a supervised method for
color image classification based on a multilevel sigmoidal neural
network (MSNN) model. In this method, images are classified into
five categories, i.e., “Car", “Building", “Mountain", “Farm" and
“Coast". This classification is performed without any segmentation
processes. To verify the learning capabilities of the proposed method,
we compare our MSNN model with the traditional Sigmoidal Neural
Network (SNN) model. Results of comparison have shown that the
MSNN model performs better than the traditional SNN model in the
context of training run time and classification rate. Both color
moments and multi-level wavelets decomposition technique are used
to extract features from images. The proposed method has been
tested on a variety of real and synthetic images.
Abstract: This research adapts experimental design to investigate
the effect of conditioning or not and pre-exposure or not on brand
attitude, so it is a 2×2=4 factorial design. The results show that the
brand attitude of conditioning group is significantly higher than that of
unconditioning group. The brand attitude with pre-exposure is
significantly higher than that without pre-exposure. Conditioning or
not and pre-exposure or not have significant interaction. No matter the
celebrity is pre-exposure or not, the brand attitude is higher under
conditioning process.
Abstract: In this paper, estimation of the linear regression
model is made by ordinary least squares method and the
partially linear regression model is estimated by penalized
least squares method using smoothing spline. Then, it is
investigated that differences and similarity in the sum of
squares related for linear regression and partial linear
regression models (semi-parametric regression models). It is
denoted that the sum of squares in linear regression is reduced
to sum of squares in partial linear regression models.
Furthermore, we indicated that various sums of squares in the
linear regression are similar to different deviance statements in
partial linear regression. In addition to, coefficient of the
determination derived in linear regression model is easily
generalized to coefficient of the determination of the partial
linear regression model. For this aim, it is made two different
applications. A simulated and a real data set are considered to
prove the claim mentioned here. In this way, this study is
supported with a simulation and a real data example.
Abstract: MultiProtocol Label Switching (MPLS) is an
emerging technology that aims to address many of the existing issues
associated with packet forwarding in today-s Internetworking
environment. It provides a method of forwarding packets at a high
rate of speed by combining the speed and performance of Layer 2
with the scalability and IP intelligence of Layer 3. In a traditional IP
(Internet Protocol) routing network, a router analyzes the destination
IP address contained in the packet header. The router independently
determines the next hop for the packet using the destination IP
address and the interior gateway protocol. This process is repeated at
each hop to deliver the packet to its final destination. In contrast, in
the MPLS forwarding paradigm routers on the edge of the network
(label edge routers) attach labels to packets based on the forwarding
Equivalence class (FEC). Packets are then forwarded through the
MPLS domain, based on their associated FECs , through swapping
the labels by routers in the core of the network called label switch
routers. The act of simply swapping the label instead of referencing
the IP header of the packet in the routing table at each hop provides
a more efficient manner of forwarding packets, which in turn allows
the opportunity for traffic to be forwarded at tremendous speeds and
to have granular control over the path taken by a packet. This paper
deals with the process of MPLS forwarding mechanism,
implementation of MPLS datapath , and test results showing the
performance comparison of MPLS and IP routing. The discussion
will focus primarily on MPLS IP packet networks – by far the
most common application of MPLS today.
Abstract: The Integrated Management of Child illnesses (IMCI) and the surveillance Health Information Systems (HIS) are related strategies that are designed to manage child illnesses and community practices of diseases. However, both strategies do not function well together because of classification incompatibilities and, as such, are difficult to use by health care personnel in rural areas where a majority of people lack the basic knowledge of interpreting disease classification from these methods. This paper discusses a single approach on how a stand-alone expert system can be used as a prompt diagnostic tool for all cases of illnesses presented. The system combines the action-oriented IMCI and the disease-oriented HIS approaches to diagnose malaria and typhoid fever in the rural areas of the Niger-delta region.
Abstract: To investigates the effect of fiberglass clamping
process improvement on drape simulation prediction. This has
great effect on the mould and the fiber during manufacturing
process. This also, improves the fiber strain, the quality of the
fiber orientation in the area of folding and wrinkles formation
during the press-forming process. Drape simulation software
tool was used to digitalize the process, noting the formation
problems on the contour sensitive part. This was compared
with the real life clamping processes using single and double
frame set-ups to observe the effects. Also, restrains are
introduced by using clips, and the G-clamps with predetermine
revolution to; restrain the fabric deformation during the
forming process.The incorporation of clamping and fabric
restrain deformation improved on the prediction of the
simulation tool. Therefore, for effective forming process,
incorporation of clamping process into the drape simulation
process will assist in the development of fiberglass application
in manufacturing process.
Abstract: In this paper, we use a one-step iteration scheme to approximate common fixed points of two quasi-asymptotically nonexpansive mappings. We prove weak and strong convergence theorems in a uniformly convex Banach space. Our results generalize the corresponding results of Yao and Chen [15] to a wider class of mappings while extend those of Khan, Abbas and Khan [4] to an improved one-step iteration scheme without any condition and improve upon many others in the literature.
Abstract: In process control applications, above 90% of the
controllers are of PID type. This paper proposed a robust PI
controller with fractional-order integrator. The PI parameters were
obtained using classical Ziegler-Nichols rules but enhanced with the
application of error filter cascaded to the fractional-order PI. The
controller was applied on steam temperature process that was
described by FOPDT transfer function. The process can be classified
as lag dominating process with very small relative dead-time. The
proposed control scheme was compared with other PI controller
tuned using Ziegler-Nichols and AMIGO rules. Other PI controller
with fractional-order integrator known as F-MIGO was also
considered. All the controllers were subjected to set point change and
load disturbance tests. The performance was measured using Integral
of Squared Error (ISE) and Integral of Control Signal (ICO). The
proposed controller produced best performance for all the tests with
the least ISE index.
Abstract: In this paper, a pipelined version of genetic algorithm,
called PLGA, and a corresponding hardware platform are described.
The basic operations of conventional GA (CGA) are made pipelined
using an appropriate selection scheme. The selection operator, used
here, is stochastic in nature and is called SA-selection. This helps
maintaining the basic generational nature of the proposed pipelined
GA (PLGA). A number of benchmark problems are used to compare
the performances of conventional roulette-wheel selection and the
SA-selection. These include unimodal and multimodal functions with
dimensionality varying from very small to very large. It is seen that
the SA-selection scheme is giving comparable performances with
respect to the classical roulette-wheel selection scheme, for all the
instances, when quality of solutions and rate of convergence are considered.
The speedups obtained by PLGA for different benchmarks
are found to be significant. It is shown that a complete hardware
pipeline can be developed using the proposed scheme, if parallel
evaluation of the fitness expression is possible. In this connection
a low-cost but very fast hardware evaluation unit is described.
Results of simulation experiments show that in a pipelined hardware
environment, PLGA will be much faster than CGA. In terms of
efficiency, PLGA is found to outperform parallel GA (PGA) also.
Abstract: This paper proposes new hybrid approaches for face
recognition. Gabor wavelets representation of face images is an
effective approach for both facial action recognition and face
identification. Perform dimensionality reduction and linear
discriminate analysis on the down sampled Gabor wavelet faces can
increase the discriminate ability. Nearest feature space is extended to
various similarity measures. In our experiments, proposed Gabor
wavelet faces combined with extended neural net feature space
classifier shows very good performance, which can achieve 93 %
maximum correct recognition rate on ORL data set without any preprocessing
step.
Abstract: The Chinese Postman Problem (CPP) is one of the
classical problems in graph theory and is applicable in a wide range
of fields. With the rapid development of hybrid systems and model
based testing, Chinese Postman Problem with Time Dependent Travel
Times (CPPTDT) becomes more realistic than the classical problems.
In the literature, we have proposed the first integer programming
formulation for the CPPTDT problem, namely, circuit formulation,
based on which some polyhedral results are investigated and a cutting
plane algorithm is also designed. However, there exists a main drawback:
the circuit formulation is only available for solving the special
instances with all circuits passing through the origin. Therefore, this
paper proposes a new integer programming formulation for solving
all the general instances of CPPTDT. Moreover, the size of the circuit
formulation is too large, which is reduced dramatically here. Thus, it
is possible to design more efficient algorithm for solving the CPPTDT
in the future research.
Abstract: Environment both endowed and built are essential for
tourism. However tourism and environment maintains a complex
relationship, where in most cases environment is at the receiving end.
Many tourism development activities have adverse environmental
effects, mainly emanating from construction of general infrastructure
and tourism facilities. These negative impacts of tourism can lead to
the destruction of precious natural resources on which it depends.
These effects vary between locations; and its effect on a hill
destination is highly critical. This study aims at developing a
Sustainable Tourism Planning Model for an environmentally
sensitive tourism destination in Kerala, India. Being part of the
Nilgiri mountain ranges, Munnar falls in the Western Ghats, one of
the biological hotspots in the world. Endowed with a unique high
altitude environment Munnar inherits highly significant ecological
wealth. Giving prime importance to the protection of this ecological
heritage, the study proposes a tourism planning model with resource
conservation and sustainability as the paramount focus. Conceiving a
novel approach towards sustainable tourism planning, the study
proposes to assess tourism attractions using Ecological Sensitivity
Index (ESI) and Tourism Attractiveness Index (TAI). Integration of
these two indices will form the Ecology – Tourism Matrix (ETM),
outlining the base for tourism planning in an environmentally
sensitive destination. The ETM Matrix leads to a classification of
tourism nodes according to its Conservation Significance and
Tourism Significance. The spatial integration of such nodes based on
the Hub & Spoke Principle constitutes sub – regions within the STZ.
Ensuing analyses lead to specific guidelines for the STZ as a whole,
specific tourism nodes, hubs and sub-regions. The study results in a
multi – dimensional output, viz., (1) Classification system for tourism
nodes in an environmentally sensitive region/ destination (2)
Conservation / Tourism Development Strategies and Guidelines for
the micro and macro regions and (3) A Sustainable Tourism Planning
Tool particularly for Ecologically Sensitive Destinations, which can
be adapted for other destinations as well.
Abstract: This paper focuses on analyzing medical diagnostic data using classification rules in data mining and context reduction in formal concept analysis. It helps in finding redundancies among the various medical examination tests used in diagnosis of a disease. Classification rules have been derived from positive and negative association rules using the Concept lattice structure of the Formal Concept Analysis. Context reduction technique given in Formal Concept Analysis along with classification rules has been used to find redundancies among the various medical examination tests. Also it finds out whether expensive medical tests can be replaced by some cheaper tests.
Abstract: A new SUZ-4 zeolite membrane with
tetraethlyammonium hydroxide as the template was fabricated on
mullite tube via hydrothermal sol-gel synthesis in a rotating
autoclave reactor. The suitable synthesis condition was SiO2:Al2O3
ratio of 21.2 for 4 days at 155 °C crystallization under autogenous
pressure. The obtained SUZ-4 possessed a high BET surface area of
396.4 m2/g, total pore volume at 2.611 cm3/g, and narrow pore size
distribution with 97 nm mean diameter and 760 nm long of needle
crystal shape. The SUZ-4 layer obtained from seeding crystallization
was thicker than that of without seeds or in situ crystallization.