Abstract: IETF RFC 2002 originally introduced the wireless
Mobile-IP protocol to support portable IP addresses for mobile
devices that often change their network access points to the Internet.
The inefficiency of this protocol mainly within the handoff
management produces large end-to-end packet delays, during
registration process, and further degrades the system efficiency due to
packet losses between subnets. The criterion to initiate a simple and
fast full-duplex connection between the home agent and foreign
agent, to reduce the roaming duration, is a very important issue to be
considered by a work in this paper. State-transition Petri-Nets of the
modeling scenario-based CIA: communication inter-agents procedure
as an extension to the basic Mobile-IP registration process was
designed and manipulated. The heuristic of configuration file during
practical Setup session for registration parameters, on Cisco platform
Router-1760 using IOS 12.3 (15)T is created. Finally, stand-alone
performance simulations results from Simulink Matlab, within each
subnet and also between subnets, are illustrated for reporting better
end-to-end packet delays. Results verified the effectiveness of our
Mathcad analytical manipulation and experimental implementation. It
showed lower values of end-to-end packet delay for Mobile-IP using
CIA procedure. Furthermore, it reported packets flow between
subnets to improve packet losses between subnets.
Abstract: In recent years with the rapid development of Internet and the Web, more and more web applications have been deployed in many fields and organizations such as finance, military, and government. Together with that, hackers have found more subtle ways to attack web applications. According to international statistics, SQL Injection is one of the most popular vulnerabilities of web applications. The consequences of this type of attacks are quite dangerous, such as sensitive information could be stolen or authentication systems might be by-passed. To mitigate the situation, several techniques have been adopted. In this research, a security solution is proposed using Artificial Neural Network to protect web applications against this type of attacks. The solution has been experimented on sample datasets and has given promising result. The solution has also been developed in a prototypic web application firewall called ANNbWAF.
Abstract: Computation of facility location problem for every
location in the country is not easy simultaneously. Solving the
problem is described by using cluster computing. A technique is to
design parallel algorithm by using local search with single swap
method in order to solve that problem on clusters. Parallel
implementation is done by the use of portable parallel programming,
Message Passing Interface (MPI), on Microsoft Windows Compute
Cluster. In this paper, it presents the algorithm that used local search
with single swap method and implementation of the system of a
facility to be opened by using MPI on cluster. If large datasets are
considered, the process of calculating a reasonable cost for a facility
becomes time consuming. The result shows parallel computation of
facility location problem on cluster speedups and scales well as
problem size increases.
Abstract: Urbanization and related anthropogenic modifications
cause extent of habitat fragmentation and directly lead to decline of
local biodiversity. Conservation biologists advocate corridor creation
as one approach to rescue biodiversity. Here we examine the utility of
roads as corridors in preserving plant diversity by investigating
roadside vegetation in Yellow River Delta (YRD), China. We
examined the spatio-temporal distribution pattern of plant species
richness, diversity and composition along roadside. The results
suggest that roads, as dispersal conduits, increase occurrence
probability of new settlers to a new area, meanwhile, roads accumulate
the greater propagule pressure and favourable survival condition
during operation phase. As a result, more species, including native and
alien plants, non- halophyte and halophyte species, threatened and
cosmopolitic species, were found prosperous at roadside. Roadside
may be a refuge for more species, and the pattern of vegetation
distribution is affected by road age and the distance from road verge.
Abstract: Instead of traditional (nominal) classification we investigate
the subject of ordinal classification or ranking. An enhanced
method based on an ensemble of Support Vector Machines (SVM-s)
is proposed. Each binary classifier is trained with specific weights
for each object in the training data set. Experiments on benchmark
datasets and synthetic data indicate that the performance of our
approach is comparable to state of the art kernel methods for
ordinal regression. The ensemble method, which is straightforward
to implement, provides a very good sensitivity-specificity trade-off
for the highest and lowest rank.
Abstract: Automatic methods of detecting changes through
satellite imaging are the object of growing interest, especially
beca²use of numerous applications linked to analysis of the Earth’s
surface or the environment (monitoring vegetation, updating maps,
risk management, etc...). This work implemented spatial analysis
techniques by using images with different spatial and spectral
resolutions on different dates. The work was based on the principle
of control charts in order to set the upper and lower limits beyond
which a change would be noted. Later, the a contrario approach was
used. This was done by testing different thresholds for which the
difference calculated between two pixels was significant. Finally,
labeled images were considered, giving a particularly low difference
which meant that the number of “false changes” could be estimated
according to a given limit.
Abstract: The aim of this article is to assess the existing
business models used by the banks operating in the CEE countries in
the time period from 2006 till 2011.
In order to obtain research results, the authors performed
qualitative analysis of the scientific literature on bank business
models, which have been grouped into clusters that consist of such
components as: 1) capital and reserves; 2) assets; 3) deposits, and 4)
loans.
In their turn, bank business models have been developed based on
the types of core activities of the banks, and have been divided into
four groups: Wholesale, Investment, Retail and Universal Banks.
Descriptive statistics have been used to analyse the models,
determining mean, minimal and maximal values of constituent
cluster components, as well as standard deviation. The analysis of
the data is based on such bank variable indices as Return on Assets
(ROA) and Return on Equity (ROE).
Abstract: Data mining incorporates a group of statistical
methods used to analyze a set of information, or a data set. It operates
with models and algorithms, which are powerful tools with the great
potential. They can help people to understand the patterns in certain
chunk of information so it is obvious that the data mining tools have
a wide area of applications. For example in the theoretical chemistry
data mining tools can be used to predict moleculeproperties or
improve computer-assisted drug design. Classification analysis is one
of the major data mining methodologies. The aim of thecontribution
is to create a classification model, which would be able to deal with a
huge data set with high accuracy. For this purpose logistic regression,
Bayesian logistic regression and random forest models were built
using R software. TheBayesian logistic regression in Latent GOLD
software was created as well. These classification methods belong to
supervised learning methods.
It was necessary to reduce data matrix dimension before construct
models and thus the factor analysis (FA) was used. Those models
were applied to predict the biological activity of molecules, potential
new drug candidates.
Abstract: Diffuse viral encephalitis may lack fever and other cardinal signs of infection and hence its distinction from other acute encephalopathic illnesses is challenging. Often, the EEG changes seen routinely are nonspecific and reflect diffuse encephalopathic changes only. The aim of this study was to use nonlinear dynamic mathematical techniques for analyzing the EEG data in order to look for any characteristic diagnostic patterns in diffuse forms of encephalitis.It was diagnosed on clinical, imaging and cerebrospinal fluid criteria in three young male patients. Metabolic and toxic encephalopathies were ruled out through appropriate investigations. Digital EEGs were done on the 3rd to 5th day of onset. The digital EEGs of 5 male and 5 female age and sex matched healthy volunteers served as controls.Two sample t-test indicated that there was no statistically significant difference between the average values in amplitude between the two groups. However, the standard deviation (or variance) of the EEG signals at FP1-F7 and FP2-F8 are significantly higher for the patients than the normal subjects. The regularisation dimension is significantly less for the patients (average between 1.24-1.43) when compared to the normal persons (average between 1.41-1.63) for the EEG signals from all locations except for the Fz-Cz signal. Similarly the wavelet dimension is significantly less (P = 0.05*) for the patients (1.122) when compared to the normal person (1.458). EEGs are subdued in the case of the patients with presence of uniform patterns, manifested in the values of regularisation and wavelet dimensions, when compared to the normal person, indicating a decrease in chaotic nature.
Abstract: Terminal localization for indoor Wireless Local Area
Networks (WLANs) is critical for the deployment of location-aware
computing inside of buildings. A major challenge is obtaining high
localization accuracy in presence of fluctuations of the received signal
strength (RSS) measurements caused by multipath fading. This paper
focuses on reducing the effect of the distance-varying noise by spatial
filtering of the measured RSS. Two different survey point geometries
are tested with the noise reduction technique: survey points arranged
in sets of clusters and survey points uniformly distributed over the
network area. The results show that the location accuracy improves
by 16% when the filter is used and by 18% when the filter is applied
to a clustered survey set as opposed to a straight-line survey set.
The estimated locations are within 2 m of the true location, which
indicates that clustering the survey points provides better localization
accuracy due to superior noise removal.
Abstract: This paper proposes a novel frequency offset (FO) estimator for orthogonal frequency division multiplexing. Simplicity is most significant feature of this algorithm and can be repeated to achieve acceptable accuracy. Also fractional and integer part of FO is estimated jointly with use of the same algorithm. To do so, instead of using conventional algorithms that usually use correlation function, we use DFT of received signal. Therefore, complexity will be reduced and we can do synchronization procedure by the same hardware that is used to demodulate OFDM symbol. Finally, computer simulation shows that the accuracy of this method is better than other conventional methods.
Abstract: In this paper, we develop a Spatio-Temporal graph as
of a key component of our knowledge representation Scheme. We
design an integrated representation Scheme to depict not only present
and past but future in parallel with the spaces in an effective and
intuitive manner. The resulting multi-dimensional comprehensive
knowledge structure accommodates multi-layered virtual world
developing in the time to maximize the diversity of situations in the
historical context. This knowledge representation Scheme is to be used
as the basis for simulation of situations composing the virtual world
and for implementation of virtual agents' knowledge used to judge and
evaluate the situations in the virtual world. To provide natural contexts
for situated learning or simulation games, the virtual stage set by this
Spatio-Temporal graph is to be populated by agents and other objects
interrelated and changing which are abstracted in the ontology.
Abstract: Information regarding early onset neonatal sepsis
(EONS) pathogens may vary between regions. Global perspectives
showed Group B Streptococcal (GBS) as the most common causative
pathogens, but the widespread use of intrapartum antibiotics has
changed the pathogens pattern towards gram negative
microorganisms, especially E. coli. Objective of this study is to
describe the pathogens isolated, to assess current treatment and risk
of EONS. Records of 899 neonates born in three General Hospitals
between 2009 until 2012 were retrospectively reviewed. Proven was
found in 22 (3%) neonates. The majority was isolated with gram
positive organisms, 17 (2.3%). All grams positive and most gram
negative organisms showed sensitivity to the tested antibiotics. Only
two rare gram negative organisms showed total resistant. Male was
possible risk of proven EONS. Although proven EONS remains
uncommon in Malaysia, nonetheless, the effect of intrapartum
antibiotics still required continuous surveillance.
Abstract: This paper presents the effects of migration at the
urban sites with an integrated model under the sustainable local
development policies for the conservation and revitalization of the
site areas as a case at Reyhan heritage site in Bursa. It is known as
the “City of immigrants" because of its richness of cultural plurality.
The city has always regarded the dynamic impact of immigration as a
positive contribution. As a result of this situation, the city created the
earliest urbanization practices: being the first capital city of the
Ottoman Empire. Bursa created the first modern movement practices
and set the first Organized Industrial Zone. The most important aim
of the study is to be offer a model for the similar areas with the
context of conservation and revitalization of the historical areas,
subjected to the local integrated sustainable development policies of
local goverments.
Abstract: Due to the deregulation of the Electric Supply
Industry and the resulting emergence of electricity market, the
volumes of power purchases are on the rise all over the world. In a
bid to meet the customer-s demand in a reliable and yet economic
manner, utilities purchase power from the energy market over and
above its own production. This paper aims at developing an optimal
power purchase model with two objectives viz economy and
environment ,taking various functional operating constraints such as
branch flow limits, load bus voltage magnitudes limits, unit capacity
constraints and security constraints into consideration.The price of
purchased power being an uncertain variable is modeled using fuzzy
logic. DEMO (Differential Evolution For Multi-objective
Optimization) is used to obtain the pareto-optimal solution set of the
multi-objective problem formulated. Fuzzy set theory has been
employed to extract the best compromise non-dominated solution.
The results obtained on IEEE 30 bus system are presented and
compared with that of NSGAII.
Abstract: The clustering ensembles combine multiple partitions
generated by different clustering algorithms into a single clustering
solution. Clustering ensembles have emerged as a prominent method
for improving robustness, stability and accuracy of unsupervised
classification solutions. So far, many contributions have been done to
find consensus clustering. One of the major problems in clustering
ensembles is the consensus function. In this paper, firstly, we
introduce clustering ensembles, representation of multiple partitions,
its challenges and present taxonomy of combination algorithms.
Secondly, we describe consensus functions in clustering ensembles
including Hypergraph partitioning, Voting approach, Mutual
information, Co-association based functions and Finite mixture
model, and next explain their advantages, disadvantages and
computational complexity. Finally, we compare the characteristics of
clustering ensembles algorithms such as computational complexity,
robustness, simplicity and accuracy on different datasets in previous
techniques.
Abstract: A specially designed flat plate was mounted vertically
over the axial line in the wind tunnel of the Aerospace Department of
the Pusan National University. The plate is 2 m long, 0.8 m high and 8
cm thick. The measurements were performed in velocity range from
15 to 60 m/s. A sand paper turbulizer was placed close to the plate nose
to provide fully developed turbulent boundary layer over the most part
of the plate. Strain balances were mounted in the trailing part of the
plate to measure the skin friction drag over removable insertions of
0.55×0.25m2 size. A set of the insertions was designed and
manufactured: 3mm thick polished metal surface and three compliant
surfaces. The compliant surfaces were manufactured of a silicone
rubber Silastic® S2 (Dow Corning company). To modify the
viscoelastic properties of the rubber, its composition was varied: 90%
of the rubber + 10% catalyst (standard), 92.5% + 7.5% (weak), 85% +
15% (strong). Modulus of elasticity and the loss tangent were
measured accurately for these materials in the frequency range from
40 Hz to 3 KHz using the unique proposed technique.
Abstract: Clustering is a very well known technique in data mining. One of the most widely used clustering techniques is the kmeans algorithm. Solutions obtained from this technique depend on the initialization of cluster centers and the final solution converges to local minima. In order to overcome K-means algorithm shortcomings, this paper proposes a hybrid evolutionary algorithm based on the combination of PSO, SA and K-means algorithms, called PSO-SA-K, which can find better cluster partition. The performance is evaluated through several benchmark data sets. The simulation results show that the proposed algorithm outperforms previous approaches, such as PSO, SA and K-means for partitional clustering problem.
Abstract: A DEA model can generally evaluate the performance
using multiple inputs and outputs for the same period. However, it is
hard to avoid the production lead time phenomenon some times, such
as long-term project or marketing activity. A couple of models have
been suggested to capture this time lag issue in the context of DEA.
This paper develops a dual-MPO model to deal with time lag effect in
evaluating efficiency. A numerical example is also given to show that
the proposed model can be used to get efficiency and reference set of
inefficient DMUs and to obtain projected target value of input
attributes for inefficient DMUs to be efficient.
Abstract: An attempt has been made to determine the strength
and impact properties of Cr-Mo steel weld and base materials by
varying the current during manual metal arc welding. Toughness over
a temperature range from -32 to 100°C of base, heat affected zone
(HAZ) and weld zones at three current settings are made. It is
observed that the deterioration in notch toughness at any zone with
the temperature decreases. The values of notch toughness for all
zones at -32°C are almost same for any current settings. The values
of notch toughness at HAZ area are higher than that of weld area due
to the coarsening of ferrite grain of HAZ occurs with higher heat
input. From microhardness and microstructure result, it can be
concluded that large inclusion content in weld deposit is the cause of
lower notch toughness value.