Abstract: Phishing, or stealing of sensitive information on the
web, has dealt a major blow to Internet Security in recent times. Most
of the existing anti-phishing solutions fail to handle the fuzziness
involved in phish detection, thus leading to a large number of false
positives. This fuzziness is attributed to the use of highly flexible and
at the same time, highly ambiguous HTML language. We introduce a
new perspective against phishing, that tries to systematically prove,
whether a given page is phished or not, using the corresponding
original page as the basis of the comparison. It analyzes the layout of
the pages under consideration to determine the percentage distortion
between them, indicative of any form of malicious alteration. The
system design represents an intelligent system, employing dynamic
assessment which accurately identifies brand new phishing attacks
and will prove effective in reducing the number of false positives.
This framework could potentially be used as a knowledge base, in
educating the internet users against phishing.
Abstract: Visually impaired people find it extremely difficult to
acquire basic and vital information necessary for their living.
Therefore, they are at a very high risk of being socially excluded as a
result of poor access to information. In recent years, several attempts
have been made in improving the communication methods for
visually impaired people which involve tactile sensation such as
finger Braille, manual alphabets and the print on palm method and
several other electronic devices. But, there are some problems which
arise in such methods such as lack of privacy and lack of
compatibility to computer environment. This paper describes a low
cost Braille hand glove for blind people using slot sensors and
vibration motors with the help of which they can read and write emails,
text messages and read e-books. This glove allows the person
to type characters based on different Braille combination using six
slot sensors. The vibration in six different positions of the glove
which matches to the Braille code allows them to read characters.
Abstract: The consumption of lactose in acid cheese whey
anaerobic fermentation process under fed-batch conditions was
studied. During fermentation for 100 hours the biogas production
(CO2 and CH4) was analyzed online. Among the standard analyses
FT-IR spectroscopy was used to follow the consumption of lactose by
bacteria. The absorption bands at 990, 894 and 787 cm-1 in the 2nd
derivative spectra were shown to be characteristic for lactose and
were used to follow the lactose conversion. It was shown that acid
cheese whey lactose was converted by bacteria in first 7 hours. In the
spectra of 17, 18 and 95 hour fermentation samples lactose was not
identified and these results correlated with the HPLC data.
Abstract: In this paper we present a soft timing phase estimation (STPE) method for wireless mobile receivers operating in low signal to noise ratios (SNRs). Discrete Polyphase Matched (DPM) filters, a Log-maximum a posterior probability (MAP) and/or a Soft-output Viterbi algorithm (SOVA) are combined to derive a new timing recovery (TR) scheme. We apply this scheme to wireless cellular communication system model that comprises of a raised cosine filter (RCF), a bit-interleaved turbo-coded multi-level modulation (BITMM) scheme and the channel is assumed to be memory-less. Furthermore, no clock signals are transmitted to the receiver contrary to the classical data aided (DA) models. This new model ensures that both the bandwidth and power of the communication system is conserved. However, the computational complexity of ideal turbo synchronization is increased by 50%. Several simulation tests on bit error rate (BER) and block error rate (BLER) versus low SNR reveal that the proposed iterative soft timing recovery (ISTR) scheme outperforms the conventional schemes.
Abstract: Recently, an enhanced hexagon-based search (EHS)
algorithm was proposed to speedup the original hexagon-based search
(HS) by exploiting the group-distortion information of some evaluated
points. In this paper, a second version of the EHS is proposed with a
new point-oriented inner search technique which can further speedup
the HS in both large and small motion environments. Experimental
results show that the enhanced hexagon-based search version-2
(EHS2) is faster than the HS up to 34% with negligible PSNR
degradation.
Abstract: Sulfide ion (S2-) is one of the most important ions to be
monitored due to its high toxicity, especially for aquatic organisms. In
this work, [Ca(2,2'-bipyridine)3]2+-intercalated montmorillonite was
prepared and used as a sensor to construct a potentiometric electrode to
measure sulfide ion in solution. The formation of [Ca(2,2'-
bipyridine)3]2+ in montmorillonite was confirmed by Fourier Transform
Infrared spectra. The electrode worked well at pH 4-12 and 4-10 in
sulfide solution 10-2 M and 10-3 M, respectively, in terms of Nernstian
slope. The sensor gave good precision and low cost.
Abstract: Problem Statement:Rapid technological developments of the 21st century have advanced our daily lives in various ways. Particularly in education, students frequently utilize technological resources to aid their homework and to access information. listen to radio or watch television (26.9 %) and e-mails (34.2 %) [26]. Not surprisingly, the increase in the use of technologies also resulted in an increase in the use of e-mail, instant messaging, chat rooms, mobile phones, mobile phone cameras and web sites by adolescents to bully peers. As cyber bullying occurs in the cyber space, lesser access to technologies would mean lesser cyber-harm. Therefore, the frequency of technology use is a significant predictor of cyber bullying and cyber victims. Cyber bullies try to harm the victim using various media. These tools include sending derogatory texts via mobile phones, sending threatening e-mails and forwarding confidential emails to everyone on the contacts list. Another way of cyber bullying is to set up a humiliating website and invite others to post comments. In other words, cyber bullies use e-mail, chat rooms, instant messaging, pagers, mobile texts and online voting tools to humiliate and frighten others and to create a sense of helplessness. No matter what type of bullying it is, it negatively affects its victims. Children who bully exhibit more emotional inhibition and attribute themselves more negative self-statements compared to non-bullies. Students whose families are not sympathetic and who receive lower emotional support are more prone to bully their peers. Bullies have authoritarian families and do not get along well with them. The family is the place where the children-s physical, social and psychological needs are satisfied and where their personalities develop. As the use of the internet became prevalent so did parents- restrictions on their children-s internet use. However, parents are unaware of the real harm. Studies that explain the relationship between parental attitudes and cyber bullying are scarce in literature. Thus, this study aims to investigate the relationship between cyber bullying and parental attitudes in the primary school. Purpose of Study: This study aimed to investigate the relationship between cyber bullying and parental attitudes. A second aim was to determine whether parental attitudes could predict cyber bullying and if so which variables could predict it significantly. Methods:The study had a cross-sectional and relational survey model. A demographics information form, questions about cyber bullying and a Parental Attitudes Inventory were conducted with a total of 346 students (189 females and 157 males) registered at various primary schools. Data was analysed by multiple regression analysis using the software package SPSS 16.
Abstract: Schema matching plays a key role in many different
applications, such as schema integration, data integration, data
warehousing, data transformation, E-commerce, peer-to-peer data
management, ontology matching and integration, semantic Web,
semantic query processing, etc. Manual matching is expensive and
error-prone, so it is therefore important to develop techniques to
automate the schema matching process. In this paper, we present a
solution for XML schema automated matching problem which
produces semantic mappings between corresponding schema
elements of given source and target schemas. This solution
contributed in solving more comprehensively and efficiently XML
schema automated matching problem. Our solution based on
combining linguistic similarity, data type compatibility and structural
similarity of XML schema elements. After describing our solution,
we present experimental results that demonstrate the effectiveness of
this approach.
Abstract: Grid computing is growing rapidly in the distributed
heterogeneous systems for utilizing and sharing large-scale resources
to solve complex scientific problems. Scheduling is the most recent
topic used to achieve high performance in grid environments. It aims
to find a suitable allocation of resources for each job. A typical
problem which arises during this task is the decision of scheduling. It
is about an effective utilization of processor to minimize tardiness
time of a job, when it is being scheduled. This paper, therefore,
addresses the problem by developing a general framework of grid
scheduling using dynamic information and an ant colony
optimization algorithm to improve the decision of scheduling. The
performance of various dispatching rules such as First Come First
Served (FCFS), Earliest Due Date (EDD), Earliest Release Date
(ERD), and an Ant Colony Optimization (ACO) are compared.
Moreover, the benefit of using an Ant Colony Optimization for
performance improvement of the grid Scheduling is also discussed. It
is found that the scheduling system using an Ant Colony
Optimization algorithm can efficiently and effectively allocate jobs
to proper resources.
Abstract: The effects of equilibrium time, solution pH, and
sorption temperature of cationic methylene blue (MB) adsorption on nanoporous metallosilicoaluminophosphate ZnAPSO-34 was studied
using a batch equilibration method. UV–VIS spectroscopy was used
to obtain the adsorption isotherms at 20° C. The optimum period for
adsorption was 300 min. However, MB removal increased from
81,82 % to 94,81 %. The equilibrium adsorption data was analyzed
by using Langmuir, Freundlich and Temkin isotherm models.
Langmuir isotherm was found to be the better-fitting model and the process followed pseudo second–order kinetics. The results showed
that ZnAPSO-34 could be employed as an effective material and could be an attractive alternative for the removal of dyes and colors
from aqueous solutions.
Abstract: A numerical study is presented on buckling and post
buckling behaviour of laminated carbon fiber reinforced plastic
(CFRP) thin-walled cylindrical shells under axial compression using
asymmetric meshing technique (AMT). Asymmetric meshing
technique is a perturbation technique to introduce disturbance without
changing geometry, boundary conditions or loading conditions.
Asymmetric meshing affects predicted buckling load, buckling mode
shape and post-buckling behaviour. Linear (eigenvalue) and nonlinear
(Riks) analyses have been performed to study the effect of
asymmetric meshing in the form of a patch on buckling behaviour.
The reduction in the buckling load using Asymmetric meshing
technique was observed to be about 15%. An isolated dimple formed
near the bifurcation point and the size of which increased to reach a
stable state in the post-buckling region. The load-displacement curve
behaviour applying asymmetric meshing is quite similar to the curve
obtained using initial geometric imperfection in the shell model.
Abstract: It has been established that microRNAs (miRNAs) play
an important role in gene expression by post-transcriptional regulation
of messengerRNAs (mRNAs). However, the precise relationships
between microRNAs and their target genes in sense of numbers,
types and biological relevance remain largely unclear. Dissecting the
miRNA-target relationships will render more insights for miRNA
targets identification and validation therefore promote the understanding
of miRNA function. In miRBase, miRanda is the key
algorithm used for target prediction for Zebrafish. This algorithm
is high-throughput but brings lots of false positives (noise). Since
validation of a large scale of targets through laboratory experiments
is very time consuming, several computational methods for miRNA
targets validation should be developed. In this paper, we present an
integrative method to investigate several aspects of the relationships
between miRNAs and their targets with the final purpose of extracting
high confident targets from miRanda predicted targets pool. This is
achieved by using the techniques ranging from statistical tests to
clustering and association rules. Our research focuses on Zebrafish.
It was found that validated targets do not necessarily associate with
the highest sequence matching. Besides, for some miRNA families,
the frequency of their predicted targets is significantly higher in the
genomic region nearby their own physical location. Finally, in a case
study of dre-miR-10 and dre-miR-196, it was found that the predicted
target genes hoxd13a, hoxd11a, hoxd10a and hoxc4a of dre-miR-
10 while hoxa9a, hoxc8a and hoxa13a of dre-miR-196 have similar
characteristics as validated target genes and therefore represent high
confidence target candidates.
Abstract: The paper proposes a novel technique for iris
recognition using texture and phase features. Texture features are
extracted on the normalized iris strip using Haar Wavelet while phase
features are obtained using LOG Gabor Wavelet. The matching
scores generated from individual modules are combined using sum of
score technique. The system is tested on database obtained from Bath
University and Indian Institute of Technology Kanpur and is giving
an accuracy of 95.62% and 97.66% respectively. The FAR and FRR
of the combined system is also reduced comparatively.
Abstract: As emails communications have no consistent
authentication procedure to ensure the authenticity, we present an
investigation analysis approach for detecting forged emails based on
Random Forests and Naïve Bays classifiers. Instead of investigating
the email headers, we use the body content to extract a unique writing
style for all the possible suspects. Our approach consists of four main
steps: (1) The cybercrime investigator extract different effective
features including structural, lexical, linguistic, and syntactic
evidence from previous emails for all the possible suspects, (2) The
extracted features vectors are normalized to increase the accuracy
rate. (3) The normalized features are then used to train the learning
engine, (4) upon receiving the anonymous email (M); we apply the
feature extraction process to produce a feature vector. Finally, using
the machine learning classifiers the email is assigned to one of the
suspects- whose writing style closely matches M. Experimental
results on real data sets show the improved performance of the
proposed method and the ability of identifying the authors with a
very limited number of features.
Abstract: Estimation of stormwater pollutants is a pre-requisite
for the protection and improvement of the aquatic environment and
for appropriate management options. The usual practice for the
stormwater quality prediction is performed through water quality
modeling. However, the accuracy of the prediction by the models
depends on the proper estimation of model parameters. This paper
presents the estimation of model parameters for a catchment water
quality model developed for the continuous simulation of stormwater
pollutants from a catchment to the catchment outlet. The model is
capable of simulating the accumulation and transportation of the
stormwater pollutants; suspended solids (SS), total nitrogen (TN) and
total phosphorus (TP) from a particular catchment. Rainfall and water
quality data were collected for the Hotham Creek Catchment (HTCC),
Gold Coast, Australia. Runoff calculations from the developed model
were compared with the calculated discharges from the widely used
hydrological models, WBNM and DRAINS. Based on the measured
water quality data, model water quality parameters were calibrated
for the above-mentioned catchment. The calibrated parameters are
expected to be helpful for the best management practices (BMPs)
of the region. Sensitivity analyses of the estimated parameters were
performed to assess the impacts of the model parameters on overall
model estimations of runoff water quality.
Abstract: This paper presents an application of power line
carrier (PLC) for electrical power telemetering. This system has a
special capability of transmitting the measured values to a centralized
computer via power lines. The PLC modem as a passive high-pass
filter is designed for transmitting and receiving information. Its
function is to send the information carrier together with transmitted
data by superimposing it on the 50 Hz power frequency signal. A
microcontroller is employed to function as the main processing of the
modem. It is programmed for PLC control and interfacing with other
devices. Each power meter, connected via a PLC modem, is assigned
with a unique identification number (address) for distinguishing each
device from one another.
Abstract: Face Recognition is a field of multidimensional
applications. A lot of work has been done, extensively on the most of
details related to face recognition. This idea of face recognition using
PCA is one of them. In this paper the PCA features for Feature
extraction are used and matching is done for the face under
consideration with the test image using Eigen face coefficients. The
crux of the work lies in optimizing Euclidean distance and paving the
way to test the same algorithm using Matlab which is an efficient tool
having powerful user interface along with simplicity in representing
complex images.
Abstract: Although achieving zero-defect software release is
practically impossible, software industries should take maximum
care to detect defects/bugs well ahead in time allowing only bare
minimums to creep into released version. This is a clear indicator of
time playing an important role in the bug detection. In addition to
this, software quality is the major factor in software engineering
process. Moreover, early detection can be achieved only through
static code analysis as opposed to conventional testing.
BugCatcher.Net is a static analysis tool, which detects bugs in .NET®
languages through MSIL (Microsoft Intermediate Language)
inspection. The tool utilizes a Parser based on Finite State Automata
to carry out bug detection. After being detected, bugs need to be
corrected immediately. BugCatcher.Net facilitates correction, by
proposing a corrective solution for reported warnings/bugs to end
users with minimum side effects. Moreover, the tool is also capable
of analyzing the bug trend of a program under inspection.
Abstract: Eye localization is necessary for face recognition and
related application areas. Most of eye localization algorithms reported
so far still need to be improved about precision and computational
time for successful applications. In this paper, we propose an eye
location method based on multi-scale Gabor feature vectors, which is
more robust with respect to initial points. The eye localization based
on Gabor feature vectors first needs to constructs an Eye Model Bunch
for each eye (left or right eye) which consists of n Gabor jets and
average eye coordinates of each eyes obtained from n model face
images, and then tries to localize eyes in an incoming face image by
utilizing the fact that the true eye coordinates is most likely to be very
close to the position where the Gabor jet will have the best Gabor jet
similarity matching with a Gabor jet in the Eye Model Bunch. Similar
ideas have been already proposed in such as EBGM (Elastic Bunch
Graph Matching). However, the method used in EBGM is known to be
not robust with respect to initial values and may need extensive search
range for achieving the required performance, but extensive search
ranges will cause much more computational burden. In this paper, we
propose a multi-scale approach with a little increased computational
burden where one first tries to localize eyes based on Gabor feature
vectors in a coarse face image obtained from down sampling of the
original face image, and then localize eyes based on Gabor feature
vectors in the original resolution face image by using the eye
coordinates localized in the coarse scaled image as initial points.
Several experiments and comparisons with other eye localization
methods reported in the other papers show the efficiency of our
proposed method.
Abstract: One of the most important problems to solve is eye
location for a driver fatigue monitoring system. This paper presents an
efficient method to achieve fast and accurate eye location in grey level
images obtained in the real-word driving conditions. The structure of
eye region is used as a robust cue to find possible eye pairs. Candidates
of eye pair at different scales are selected by finding regions which
roughly match with the binary eye pair template. To obtain real one,
all the eye pair candidates are then verified by using support vector
machines. Finally, eyes are precisely located by using binary vertical
projection and eye classifier in eye pair images. The proposed method
is robust to deal with illumination changes, moderate rotations, glasses
wearing and different eye states. Experimental results demonstrate its
effectiveness.