Abstract: Thousands of organisations store important and
confidential information related to them, their customers, and their
business partners in databases all across the world. The stored data
ranges from less sensitive (e.g. first name, last name, date of birth) to
more sensitive data (e.g. password, pin code, and credit card
information). Losing data, disclosing confidential information or
even changing the value of data are the severe damages that
Structured Query Language injection (SQLi) attack can cause on a
given database. It is a code injection technique where malicious SQL
statements are inserted into a given SQL database by simply using a
web browser. In this paper, we propose an effective pattern
recognition neural network model for detection and classification of
SQLi attacks. The proposed model is built from three main elements
of: a Uniform Resource Locator (URL) generator in order to generate
thousands of malicious and benign URLs, a URL classifier in order
to: 1) classify each generated URL to either a benign URL or a
malicious URL and 2) classify the malicious URLs into different
SQLi attack categories, and a NN model in order to: 1) detect either a
given URL is a malicious URL or a benign URL and 2) identify the
type of SQLi attack for each malicious URL. The model is first
trained and then evaluated by employing thousands of benign and
malicious URLs. The results of the experiments are presented in
order to demonstrate the effectiveness of the proposed approach.
Abstract: Quantitative analyses of whisker movements provide a
means to study functional recovery and regeneration of mouse facial
nerve after an injury. However, accurate tracking of the mouse whisker
movement is challenging. Most methods for whisker tracking require
manual intervention, e.g. fixing the head of the mouse during a study.
Here we describe a semi-automated image processing method, which
is applied to high-speed video recordings of free-moving mice to track
the whisker movements. We first track the head movement of a mouse
by delineating the lower head contour frame-by-frame that allows for
detection of the location and orientation of the head. Then, a region of
interest is identified for each frame; the subsequent application of a
mask and the Hough transform detects the selected whiskers on each
side of the head. Our approach is used to examine the functional
recovery of damaged facial nerves in mice over a course of 21 days.
Abstract: Durian is the flagship fruit of Mindanao and there is
an abundance of several cultivars with many confusing identities/
names.
The project was conducted to develop procedure for reliable and
rapid detection and sorting of durian planting materials. Moreover, it
is also aimed to establish specific genetic or DNA markers for routine
testing and authentication of durian cultivars in question.
The project developed molecular procedures for routine testing.
SSR primers were also screened and identified for their utility in
discriminating durian cultivars collected.
Results of the study showed the following accomplishments:
1. Twenty (29) SSR primers were selected and identified based on
their ability to discriminate durian cultivars,
2. Optimized and established standard procedure for identification
and authentication of Durian cultivars
3. Genetic profile of durian is now available at Biotech Unit
Our results demonstrate the relevance of using molecular
techniques in evaluating and identifying durian clones. The most
polymorphic primers tested in this study could be useful tools for
detecting variation even at the early stage of the plant especially for
commercial purposes. The process developed combines the efficiency
of the microsatellites development process with the optimization of
non-radioactive detection process resulting in a user-friendly protocol
that can be performed in two (2) weeks and easily incorporated into
laboratories about to start microsatellite development projects. This
can be of great importance to extend microsatellite analyses to other
crop species where minimal genetic information is currently
available. With this, the University can now be a service laboratory
for routine testing and authentication of durian clones.
Abstract: Edge is variation of brightness in an image. Edge
detection is useful in many application areas such as finding forests,
rivers from a satellite image, detecting broken bone in a medical
image etc. The paper discusses about finding edge of multiple aerial
images in parallel. The proposed work tested on 38 images 37
colored and one monochrome image. The time taken to process N
images in parallel is equivalent to time taken to process 1 image in
sequential. Message Passing Interface (MPI) and Open Computing
Language (OpenCL) is used to achieve task and pixel level
parallelism respectively.
Abstract: A simple adaptive voice activity detector (VAD) is
implemented using Gabor and gammatone atomic decomposition of
speech for high Gaussian noise environments. Matching pursuit is
used for atomic decomposition, and is shown to achieve optimal
speech detection capability at high data compression rates for low
signal to noise ratios. The most active dictionary elements found by
matching pursuit are used for the signal reconstruction so that the
algorithm adapts to the individual speakers dominant time-frequency
characteristics. Speech has a high peak to average ratio enabling
matching pursuit greedy heuristic of highest inner products to isolate
high energy speech components in high noise environments. Gabor
and gammatone atoms are both investigated with identical
logarithmically spaced center frequencies, and similar bandwidths.
The algorithm performs equally well for both Gabor and gammatone
atoms with no significant statistical differences. The algorithm
achieves 70% accuracy at a 0 dB SNR, 90% accuracy at a 5 dB SNR
and 98% accuracy at a 20dB SNR using 30d B SNR as a reference
for voice activity.
Abstract: In more complex systems, such as automotive
gearbox, a rigorous treatment of the data is necessary because there
are several moving parts (gears, bearings, shafts, etc.), and in this
way, there are several possible sources of errors and also noise. The
basic objective of this work is the detection of damage in automotive
gearbox. The detection methods used are the wavelet method, the
bispectrum; advanced filtering techniques (selective filtering) of
vibrational signals and mathematical morphology. Gearbox vibration
tests were performed (gearboxes in good condition and with defects)
of a production line of a large vehicle assembler. The vibration
signals are obtained using five accelerometers in different positions
of the sample. The results obtained using the kurtosis, bispectrum,
wavelet and mathematical morphology showed that it is possible to
identify the existence of defects in automotive gearboxes.
Abstract: This paper presents the development of a robot car
that can track the motion of an object by detecting its color through
an Android device. The employed computer vision algorithm uses the
OpenCV library, which is embedded into an Android application of a
smartphone, for manipulating the captured image of the object. The
captured image of the object is subjected to color conversion and is
transformed to a binary image for further processing after color
filtering. The desired object is clearly determined after removing
pixel noise by applying image morphology operations and contour
definition. Finally, the area and the center of the object are
determined so that object’s motion to be tracked. The smartphone
application has been placed on a robot car and transmits by Bluetooth
to an Arduino assembly the motion directives so that to follow
objects of a specified color. The experimental evaluation of the
proposed algorithm shows reliable color detection and smooth
tracking characteristics.
Abstract: In order to avoid self-collision of space manipulators
during operation process, a real-time detection method is proposed in
this paper. The manipulator is fitted into a cylinder-enveloping
surface, and then, a kind of detection algorithm of collision between
cylinders is analyzed. The collision model of space manipulator
self-links can be detected by using this algorithm in real-time detection
during the operation process. To ensure security of the operation, a
safety threshold is designed. The simulation and experiment results
verify the effectiveness of the proposed algorithm for a 7-DOF space
manipulator.
Abstract: This study investigates the use of a time-series of
MODIS NDVI data to identify agricultural land cover change on an
annual time step (2007 - 2012) and characterize the trend. Following
an ISODATA classification of the MODIS imagery to selectively
mask areas not agriculture or semi-natural, NDVI signatures were
created to identify areas cereals and vineyards with the aid of
ancillary, pictometry and field sample data for 2010. The NDVI
signature curve and training samples were used to create a decision
tree model in WEKA 3.6.9 using decision tree classifier (J48)
algorithm; Model 1 including ISODATA classification and Model 2
not. These two models were then used to classify all data for the
study area for 2010, producing land cover maps with classification
accuracies of 77% and 80% for Model 1 and 2 respectively. Model 2
was subsequently used to create land cover classification and change
detection maps for all other years. Subtle changes and areas of
consistency (unchanged) were observed in the agricultural classes
and crop practices. Over the years as predicted by the land cover
classification. Forty one percent of the catchment comprised of
cereals with 35% possibly following a crop rotation system.
Vineyards largely remained constant with only one percent
conversion to vineyard from other land cover classes.
Abstract: An adaptive nonparametric method is proposed for
stable real-time detection of seismoacoustic sources in multichannel
C-OTDR systems with a significant number of channels. This
method guarantees given upper boundaries for probabilities of Type I
and Type II errors. Properties of the proposed method are rigorously
proved. The results of practical applications of the proposed method
in a real C-OTDR-system are presented in this report.
Abstract: The exponential growth of social media arouses much
attention on public opinion information. The online forums, blogs,
micro blogs are proving to be extremely valuable resources and are
having bulk volume of information. However, most of the social
media data is unstructured and semi structured form. So that it is
more difficult to decipher automatically. Therefore, it is very much
essential to understand and analyze those data for making a right
decision. The online forums hotspot detection is a promising research
field in the web mining and it guides to motivate the user to take right
decision in right time. The proposed system consist of a novel
approach to detect a hotspot forum for any given time period. It uses
aging theory to find the hot terms and E-K-means for detecting the
hotspot forum. Experimental results demonstrate that the proposed
approach outperforms k-means for detecting the hotspot forums with
the improved accuracy.
Abstract: In the past few years, the amount of malicious software
increased exponentially and, therefore, machine learning algorithms
became instrumental in identifying clean and malware files through
(semi)-automated classification. When working with very large
datasets, the major challenge is to reach both a very high malware
detection rate and a very low false positive rate. Another challenge
is to minimize the time needed for the machine learning algorithm to
do so. This paper presents a comparative study between different
machine learning techniques such as linear classifiers, ensembles,
decision trees or various hybrids thereof. The training dataset consists
of approximately 2 million clean files and 200.000 infected files,
which is a realistic quantitative mixture. The paper investigates the
above mentioned methods with respect to both their performance
(detection rate and false positive rate) and their practicability.
Abstract: Availability of different genetic tests after completion
of Human Genome Project increases the physicians’ responsibility to
keep themselves update on the potential implementation of these
genetic tests in their daily practice. However, due to numbers of
barriers, still many of physicians are not either aware of these tests or
are not willing to offer or refer their patients for genetic tests. This
study was conducted an anonymous, cross-sectional, mailed-based
survey to develop a primary data of Malaysian physicians’ level of
knowledge and perception of gene profiling. Questionnaire had 29
questions. Total scores on selected questions were used to assess the
level of knowledge. The highest possible score was 11. Descriptive
statistics, one way ANOVA and chi-squared test was used for
statistical analysis. Sixty three completed questionnaires were
returned by 27 general practitioners (GPs) and 36 medical specialists.
Responders’ age ranges from 24 to 55 years old (mean 30.2 ± 6.4).
About 40% of the participants rated themselves as having poor level
of knowledge in genetics in general whilst 60% believed that they
have fair level of knowledge; however, almost half (46%) of the
respondents felt that they were not knowledgeable about available
genetic tests. A majority (94%) of the responders were not aware of
any lab or company which is offering gene profiling services in
Malaysia. Only 4% of participants were aware of using gene profiling
for detection of dosage of some drugs. Respondents perceived greater
utility of gene profiling for breast cancer (38%) compared to the
colorectal familial cancer (3%). The score of knowledge ranged from
2 to 8 (mean 4.38 ± 1.67). Non- significant differences between score
of knowledge of GPs and specialists were observed, with score of
4.19 and 4.58 respectively. There was no significant association
between any demographic factors and level of knowledge. However,
those who graduated between years 2001 to 2005 had higher level of
knowledge. Overall, 83% of participants showed relatively high level
of perception on value of gene profiling to detect patient’s risk of
disease. However, low perception was observed for both statements
of using gene profiling for general population in order to alter their
lifestyle (25%) as well as having the full sequence of a patient
genome for the purpose of determining a patient’s best match for
treatment (18%). The lack of clinical guidelines, limited provider
knowledge and awareness, lack of time and resources to educate
patients, lack of evidence-based clinical information and cost of tests
were the most barriers of ordering gene profiling mentioned by
physicians. In conclusion Malaysian physicians who participate in
this study had mediocre level of knowledge and awareness in gene
profiling. The low exposure to the genetic questions and problems
might be a key predictor of lack of awareness and knowledge on
available genetic tests. Educational and training workshop might be useful in helping Malaysian physicians incorporate genetic profiling
into practice for eligible patients.
Abstract: The Aptima® HIV-1 Quant Dx Assay is a fully
automated assay on the Panther system. It is based on Transcription-
Mediated Amplification and real time detection technologies. This
assay is intended for monitoring HIV-1 viral load in plasma
specimens and for the detection of HIV-1 in plasma and serum
specimens.
Nine-hundred and seventy nine specimens selected at random
from routine testing at St Thomas’ Hospital, London were
anonymised and used to compare the performance of the Aptima
HIV-1 Quant Dx assay and Roche COBAS® AmpliPrep/COBAS®
TaqMan® HIV-1 Test, v2.0. Two-hundred and thirty four specimens
gave quantitative HIV-1 viral load results in both assays. The
quantitative results reported by the Aptima Assay were comparable to
those reported by the Roche COBAS AmpliPrep/COBAS TaqMan
HIV-1 Test, v2.0 with a linear regression slope of 1.04 and an
intercept on -0.097.
The Aptima assay detected HIV-1 in more samples than the
COBAS assay. This was not due to lack of specificity of the Aptima
assay because this assay gave 99.83% specificity on testing plasma
specimens from 600 HIV-1 negative individuals. To understand the
reason for this higher detection rate a side-by-side comparison of low
level panels made from the HIV-1 3rd international standard
(NIBSC10/152) and clinical samples of various subtypes were tested
in both assays. The Aptima assay was more sensitive than the
COBAS assay.
The good sensitivity, specificity and agreement with other
commercial assays make the HIV-1 Quant Dx Assay appropriate for
both viral load monitoring and detection of HIV-1 infections.
Abstract: Cortisol is essential to the regulation of the immune
system and yawning is a pathological symptom of multiple sclerosis
(MS). Electromyography activity (EMG) in the jaw muscles typically
rises when the muscles are moved and with yawning is highly
correlated with cortisol levels in healthy people. Saliva samples from
59 participants were collected at the start and after yawning, or at the
end of the presentation of yawning-provoking stimuli, in the absence
of a yawn, together with EMG data and questionnaire data: Hospital
Anxiety and Depression Scale, Yawning Susceptibility Scale,
General Health Questionnaire, demographic, health details. Exclusion
criteria: chronic fatigue, diabetes, fibromyalgia, heart condition, high
blood pressure, hormone replacement therapy, multiple sclerosis,
stroke. Significant differences were found between the saliva cortisol
samples for the yawners, t (23) = -4.263, p = 0.000, as compared with
the non-yawners between rest and post-stimuli, which was nonsignificant.
Significant evidence was found to support the Thompson
Cortisol Hypothesis suggesting that rises in cortisol levels are
associated with yawning. Further research is exploring the use of
cortisol as an early diagnostic tool for MS. Ethics approval granted
and professional code of conduct, confidentiality, and safety issues
are approved therein.
Abstract: Early diagnosis of infection like Hep-B virus in blood
is important for low cost medical treatment. For this purpose, it is
desirable to develop a point of care device which should be able to
detect trace quantities of the target molecule in blood. In this paper,
we report a nanoporous silicon oxide sensor which is capable of
detecting down to 1fM concentration of Hep-B surface antigen in
blood without the requirement of any centrifuge or pre-concentration.
This has been made possible by the presence of resonant peak in the
sensitivity characteristics. This peak is observed to be dependent only
on the concentration of the specific antigen and not on the interfering
species in blood serum. The occurrence of opposite impedance
change within the pores and at the bottom of the pore is responsible
for this effect. An electronic interface has also been designed to
provide a display of the virus concentration.
Abstract: Testability modeling is a commonly used method in
testability design and analysis of system. A dependency matrix will be
obtained from testability modeling, and we will give a quantitative
evaluation about fault detection and isolation.
Based on the dependency matrix, we can obtain the diagnosis tree.
The tree provides the procedures of the fault detection and isolation.
But the dependency matrix usually includes built-in test (BIT) and
manual test in fact. BIT runs the test automatically and is not limited
by the procedures. The method above cannot give a more efficient
diagnosis and use the advantages of the BIT.
A Comprehensive method of fault detection and isolation is
proposed. This method combines the advantages of the BIT and
Manual test by splitting the matrix. The result of the case study shows
that the method is effective.
Abstract: Optical radiation emitted from a metal-coated fiber tip apex at liquid-air interface was measured. The intensity of the output radiation was strongly depend on the relative position of the tip to a liquid-air interface and varied with surface fluctuations. This phenomenon permits in-situ real-time investigation of nano-metric vibrations of the liquid surface and provides a basis for development of various origin ultrasensitive vibration detecting sensors. The described method can be used for detection of week seismic vibrations.
Abstract: This paper presents a novel integrated hybrid
approach for fault diagnosis (FD) of nonlinear systems. Unlike most
FD techniques, the proposed solution simultaneously accomplishes
fault detection, isolation, and identification (FDII) within a unified
diagnostic module. At the core of this solution is a bank of adaptive
neural parameter estimators (NPE) associated with a set of singleparameter
fault models. The NPEs continuously estimate unknown
fault parameters (FP) that are indicators of faults in the system. Two
NPE structures including series-parallel and parallel are developed
with their exclusive set of desirable attributes. The parallel scheme is
extremely robust to measurement noise and possesses a simpler, yet
more solid, fault isolation logic. On the contrary, the series-parallel
scheme displays short FD delays and is robust to closed-loop system
transients due to changes in control commands. Finally, a fault
tolerant observer (FTO) is designed to extend the capability of the
NPEs to systems with partial-state measurement.
Abstract: The paper presents an innovative networked radar
system for detection of obstacles in a railway level crossing scenario.
This Monitoring System (MS) is able to detect moving or still
obstacles within the railway level crossing area automatically,
avoiding the need of human presence for surveillance. The MS is also
connected to the National Railway Information and Signaling System
to communicate in real-time the level crossing status. The
architecture is compliant with the highest Safety Integrity Level
(SIL4) of the CENELEC standard. The number of radar sensors used
is configurable at set-up time and depends on how large the level
crossing area can be. At least two sensors are expected and up four
can be used for larger areas. The whole processing chain that
elaborates the output sensor signals, as well as the communication
interface, is fully-digital, was designed in VHDL code and
implemented onto a Xilinx Virtex 6.