Abstract: Wide applicability of concurrent programming
practices in developing various software applications leads to
different concurrency errors amongst which data race is the most
important. Java provides greatest support for concurrent
programming by introducing various concurrency packages. Aspect
oriented programming (AOP) is modern programming paradigm
facilitating the runtime interception of events of interest and can be
effectively used to handle the concurrency problems. AspectJ being
an aspect oriented extension to java facilitates the application of
concepts of AOP for data race detection. Volatile variables are
usually considered thread safe, but they can become the possible
candidates of data races if non-atomic operations are performed
concurrently upon them. Various data race detection algorithms have
been proposed in the past but this issue of volatility and atomicity is
still unaddressed. The aim of this research is to propose some
suggestions for incorporating certain conditions for data race
detection in java programs at the volatile fields by taking into account
support for atomicity in java concurrency packages and making use
of pointcuts. Two simple test programs will demonstrate the results
of research. The results are verified on two different Java
Development Kits (JDKs) for the purpose of comparison.
Abstract: Our objective in this paper is to propose an approach
capable of clustering web messages. The clustering is carried out by
assigning, with a certain probability, texts written by the same web
user to the same cluster based on Stylometric features and using
fuzzy clustering algorithms. Focus in the present work is on
comparing the most popular algorithms in fuzzy clustering theory
namely, Fuzzy C-means, Possibilistic C-means and Fuzzy
Possibilistic C-Means.
Abstract: Automatic determination of blood in less bright or
noisy capsule endoscopic images is difficult due to low S/N ratio.
Especially it may not be accurate to analyze these images due to the
influence of external disturbance. Therefore, we proposed detection
methods that are not dependent only on color bands. In locating
bleeding regions, the identification of object outlines in the frame and
features of their local colors were taken into consideration. The results
showed that the capability of detecting bleeding was much improved.
Abstract: The nature of wireless ad hoc and sensor networks
make them very attractive to attackers. One of the most popular and
serious attacks in wireless ad hoc networks is wormhole attack and
most proposed protocols to defend against this attack used
positioning devices, synchronized clocks, or directional antennas.
This paper analyzes the nature of wormhole attack and existing
methods of defending mechanism and then proposes round trip time
(RTT) and neighbor numbers based wormhole detection mechanism.
The consideration of proposed mechanism is the RTT between two
successive nodes and those nodes- neighbor number which is needed
to compare those values of other successive nodes. The identification
of wormhole attacks is based on the two faces. The first consideration
is that the transmission time between two wormhole attack affected
nodes is considerable higher than that between two normal neighbor
nodes. The second detection mechanism is based on the fact that by
introducing new links into the network, the adversary increases the
number of neighbors of the nodes within its radius. This system does
not require any specific hardware, has good performance and little
overhead and also does not consume extra energy. The proposed
system is designed in ad hoc on-demand distance vector (AODV)
routing protocol and analysis and simulations of the proposed system
are performed in network simulator (ns-2).
Abstract: The processing of the electrocardiogram (ECG) signal consists essentially in the detection of the characteristic points of
signal which are an important tool in the diagnosis of heart diseases. The most suitable are the detection of R waves. In this paper, we
present various mathematical tools used for filtering ECG using digital filtering and Discreet Wavelet Transform (DWT) filtering. In
addition, this paper will include two main R peak detection methods
by applying a windowing process: The first method is based on calculations derived, the second is a time-frequency method based on
Dyadic Wavelet Transform DyWT.
Abstract: The Virtual Reality (VR) is becoming increasingly
important for business, education, and entertainment, therefore VR
technology have been applied for training purposes in the areas of
military, safety training and flying simulators. In particular, the
superior and high reliability VR training system is very important in
immersion. Manipulation training in immersive virtual environments
is difficult partly because users must do without the hap contact with
real objects they rely on in the real world to orient themselves and
their manipulated.
In this paper, we create a convincing questionnaire of immersion
and an experiment to assess the influence of immersion on
performance in VR training system. The Immersion Questionnaire
(IQ) included spatial immersion, Psychological immersion, and
Sensory immersion. We show that users with a training system
complete visual attention and detection of signals. Twenty subjects
were allocated to a factorial design consisting of two different VR
systems (Desktop VR and Projector VR). The results indicated that
different VR representation methods significantly affected the
participants- Immersion dimensions.
Abstract: An optical fault monitoring in FTTH-PON using ACS
is demonstrated. This device can achieve real-time fault monitoring
for protection feeder fiber. In addition, the ACS can distinguish
optical fiber fault from the transmission services to other customers
in the FTTH-PON. It is essential to use a wavelength different from
the triple-play services operating wavelengths for failure detection.
ACS is using the operating wavelength 1625 nm for monitoring and
failure detection control. Our solution works on a standard local area
network (LAN) using a specially designed hardware interfaced with a
microcontroller integrated Ethernet.
Abstract: The objective of this article is to discuss the potential
of economic analysis as a tool for identification and evaluation of
corruption in legislative acts. We propose that corruption be
perceived as a risk variable within the legislative process. Therefore
we find it appropriate to employ risk analysis methods, used in
various fields of economics, for the evaluation of corruption in
legislation. Furthermore we propose the incorporation of these
methods into the so called corruption impact assessment (CIA), the
general framework for detection of corruption in legislative acts. The
applications of the risk analysis methods are demonstrated on
examples of implementation of proposed CIA in the Czech Republic.
Abstract: Monitoring lightning electromagnetic pulses (sferics)
and other terrestrial as well as extraterrestrial transient radiation signals
is of considerable interest for practical and theoretical purposes
in astro- and geophysics as well as meteorology. Managing a continuous
flow of data, automisation of the detection and classification
process is important. Features based on a combination of wavelet and
statistical methods proved efficient for analysis and characterisation
of transients and as input into a radial basis function network that is
trained to discriminate transients from pulse like to wave like.
Abstract: A simple method for the simultaneous determination
of hippuric acid and benzoic acid in urine using reversed-phase high
performance liquid chromatography was described. Chromatography
was performed on a Nova-Pak C18 (3.9 x 150 mm) column with a
mobile phase of mixed solution methanol: water: acetic acid
(20:80:0.2) and UV detection at 254 nm. The calibration curve was
linear within concentration range at 0.125 to 6.0 mg/ml of hippuric
acid and benzoic acid. The recovery, accuracy and coefficient
variance of hippuric acid were 104.54%, 0.2% and 0.2% respectively
and for benzoic acid were 98.48%, 1.25% and 0.60% respectively.
The detection limit of this method was 0.01ng/l for hippuric acid and
0.06ng/l for benzoic acid. This method has been applied to the
analysis of urine samples from the suspected of toluene abuser or
glue sniffer among secondary school students at Johor Bahru.
Abstract: The standard investigational method for obstructive
sleep apnea syndrome (OSAS) diagnosis is polysomnography (PSG),
which consists of a simultaneous, usually overnight recording of
multiple electro-physiological signals related to sleep and
wakefulness. This is an expensive, encumbering and not a readily
repeated protocol, and therefore there is need for simpler and easily
implemented screening and detection techniques. Identification of
apnea/hypopnea events in the screening recordings is the key factor
for the diagnosis of OSAS. The analysis of a solely single-lead
electrocardiographic (ECG) signal for OSAS diagnosis, which may
be done with portable devices, at patient-s home, is the challenge of
the last years. A novel artificial neural network (ANN) based
approach for feature extraction and automatic identification of
respiratory events in ECG signals is presented in this paper. A
nonlinear principal component analysis (NLPCA) method was
considered for feature extraction and support vector machine for
classification/recognition. An alternative representation of the
respiratory events by means of Kohonen type neural network is
discussed. Our prospective study was based on OSAS patients of the
Clinical Hospital of Pneumology from Iaşi, Romania, males and
females, as well as on non-OSAS investigated human subjects. Our
computed analysis includes a learning phase based on cross signal
PSG annotation.
Abstract: In this paper an approaches for increasing the
effectiveness of error detection in computer network channels with
Pulse-Amplitude Modulation (PAM) has been proposed. Proposed
approaches are based on consideration of special feature of errors,
which are appearances in line with PAM. The first approach consists
of CRC modification specifically for line with PAM. The second
approach is base of weighted checksums using. The way for
checksum components coding has been developed. It has been shown
that proposed checksum modification ensure superior digital data
control transformation reliability for channels with PAM in compare
to CRC.
Abstract: The submitted paper deals with the problems of
trapping and enriching the gases and aerosols of the substances to be
determined in the ambient atmosphere. Further, the paper is focused
on the working principle of the miniaturized portable continuous
concentrator we have designed and the possibilities of its
application in air sampling and accumulation of organic and
inorganic substances with which the air is contaminated. The stress is
laid on trapping vapours and aerosols of solid substances with the
comparatively low vapour tension such as explosive compounds.
Abstract: Taking into account the link between the efficiency of
a detector and the complexity of a stealth mechanism, we propose in
this paper a new formalism for stealth using graph theory.
Abstract: In this paper a novel scheme for watermarking digital
audio during its compression to MPEG-1 Layer III format is
proposed. For this purpose we slightly modify some of the selected
MDCT coefficients, which are used during MPEG audio
compression procedure. Due to the possibility of modifying different
MDCT coefficients, there will be different choices for embedding the
watermark into audio data, considering robustness and transparency
factors. Our proposed method uses a genetic algorithm to select the
best coefficients to embed the watermark. This genetic selection is
done according to the parameters that are extracted from the
perceptual content of the audio to optimize the robustness and
transparency of the watermark. On the other hand the watermark
security is increased due to the random nature of the genetic
selection. The information of the selected MDCT coefficients that
carry the watermark bits, are saves in a database for future extraction
of the watermark. The proposed method is suitable for online MP3
stores to pursue illegal copies of musical artworks. Experimental
results show that the detection ratio of the watermarks at the bitrate
of 128kbps remains above 90% while the inaudibility of the
watermark is preserved.
Abstract: We propose a novel graphical technique (SVision) for
intrusion detection, which pictures the network as a community of
hosts independently roaming in a 3D space defined by the set of
services that they use. The aim of SVision is to graphically cluster
the hosts into normal and abnormal ones, highlighting only the ones
that are considered as a threat to the network. Our experimental
results using DARPA 1999 and 2000 intrusion detection and
evaluation datasets show the proposed technique as a good candidate
for the detection of various threats of the network such as vertical
and horizontal scanning, Denial of Service (DoS), and Distributed
DoS (DDoS) attacks.
Abstract: Recently, as the scale of construction projects has
increases, more ground excavation for foundations is carried out than ever before. Consequently, damage to underground ducts (gas, water/sewage or oil pipelines, communication cables or power cable ducts) or superannuated pipelines frequently cause serious accidents
resulting in damage to life and property. (In Korea, the total length of city water pipelines was approximately 2,000 km as of the end of 2009.) In addition, large amounts of damage caused by fractures, water
and gas leakage caused by superannuation or damage to underground
ducts in construction has been reported. Therefore, a system is required to precisely detect defects and deterioration in underground
pipelines and the locations of such defects, for timely and accurate
maintenance or replacement of the ducts. In this study, a system was
developed which can locate underground structures (gas and water
pipelines, power cable ducts, etc.) in 3D-coordinates and monitor the
degree and position of defects using an Inertial Measurement Unit
(IMU) sensing technique. The system can prevent damage to underground ducts and superannuated pipelines during construction,
and provide reliable data for maintenance. The utility of the IMU sensing technique used in aircraft and ships in civil applications was
verified.
Abstract: The general idea behind the filter is to average a pixel
using other pixel values from its neighborhood, but simultaneously to
take care of important image structures such as edges. The main
concern of the proposed filter is to distinguish between any variations
of the captured digital image due to noise and due to image structure.
The edges give the image the appearance depth and sharpness. A
loss of edges makes the image appear blurred or unfocused.
However, noise smoothing and edge enhancement are traditionally
conflicting tasks. Since most noise filtering behaves like a low pass
filter, the blurring of edges and loss of detail seems a natural
consequence. Techniques to remedy this inherent conflict often
encompass generation of new noise due to enhancement.
In this work a new fuzzy filter is presented for the noise reduction
of images corrupted with additive noise. The filter consists of three
stages. (1) Define fuzzy sets in the input space to computes a fuzzy
derivative for eight different directions (2) construct a set of IFTHEN
rules by to perform fuzzy smoothing according to
contributions of neighboring pixel values and (3) define fuzzy sets in
the output space to get the filtered and edged image.
Experimental results are obtained to show the feasibility of the
proposed approach with two dimensional objects.
Abstract: Extracting in-play scenes in sport videos is essential for
quantitative analysis and effective video browsing of the sport
activities. Game analysis of badminton as of the other racket sports
requires detecting the start and end of each rally period in an
automated manner. This paper describes an automatic serve scene
detection method employing cubic higher-order local auto-correlation
(CHLAC) and multiple regression analysis (MRA). CHLAC can
extract features of postures and motions of multiple persons without
segmenting and tracking each person by virtue of shift-invariance and
additivity, and necessitate no prior knowledge. Then, the specific
scenes, such as serve, are detected by linear regression (MRA) from
the CHLAC features. To demonstrate the effectiveness of our method,
the experiment was conducted on video sequences of five badminton
matches captured by a single ceiling camera. The averaged precision
and recall rates for the serve scene detection were 95.1% and 96.3%,
respectively.
Abstract: The purpose of this paper is to detect human in images.
This paper proposes a method for extracting human body feature descriptors consisting of projected edge component series. The feature descriptor can express appearances and shapes of human with local
and global distribution of edges. Our method evaluated with a linear SVM classifier on Daimler-Chrysler pedestrian dataset, and test with
various sub-region size. The result shows that the accuracy level of
proposed method similar to Histogram of Oriented Gradients(HOG)
feature descriptor and feature extraction process is simple and faster than existing methods.