Abstract: Von Willebrand-s disease is the most common
inherited bleeding disorder in humans, it
caused by qualitative abnormalities of the von Willebrand factor
(vWF). Our objective is to determine the prevalence of this disease at
part of the Algerian population in the East and the South by a
biological diagnosis based on specific biological tests (automated
platelet count, the bleeding time (TS), the time of cephalin + activator
(TCA), measure of the prothrombin rate (TP), vWF rate and factor
VIII rate, Molecular electrophoresis of vWF multimers in agarose gel
in the presence of SDS). Four patients of type III or severe
Willebrand-s disease were found on 200 suspect cases. All cases are
showed a deficit in vWF rate (< 5%), and factor VIII (P
Abstract: The talks about technological convergence had been
around for almost twenty years. Today Internet made it possible. And
this is not only technical evolution. The way it changed our lives
reflected in variety of applications, services and technologies used in
day-to-day life. Such benefits imposed even more requirements on
heterogeneous and unreliable IP networks.
Current paper outlines QoS management system developed in the
NetQoS [1] project. It describes an overall architecture of
management system for heterogeneous networks and proposes
automated multi-layer QoS management. Paper focuses on the
structure of the most crucial modules of the system that enable
autonomous and multi-layer provisioning and dynamic adaptation.
Abstract: Virtual Reality Modelling Language (VRML) is description language, which belongs to a field Window on World virtual reality system. The file, which is in VRML format, can be interpreted by VRML explorer in three-dimensional scene. VRML was created with aim to represent virtual reality on Internet easier. Development of 3D graphic is connected with Silicon Graphic Corporation. VRML 2.0 is the file format for describing interactive 3D scenes and objects. It can be used in collaboration with www, can be used for 3D complex representations creating of scenes, products or VR applications VRML 2.0 enables represent static and animated objects too. Interesting application of VRML is in area of manufacturing systems presentation.
Abstract: Retinal vascularity assessment plays an important role in diagnosis of ophthalmic pathologies. The employment of digital images for this purpose makes possible a computerized approach and has motivated development of many methods for automated vascular tree segmentation. Metrics based on contingency tables for binary classification have been widely used for evaluating performance of these algorithms and, concretely, the accuracy has been mostly used as measure of global performance in this topic. However, this metric shows very poor matching with human perception as well as other notable deficiencies. Here, a new similarity function for measuring quality of retinal vessel segmentations is proposed. This similarity function is based on characterizing the vascular tree as a connected structure with a measurable area and length. Tests made indicate that this new approach shows better behaviour than the current one does. Generalizing, this concept of measuring descriptive properties may be used for designing functions for measuring more successfully segmentation quality of other complex structures.
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: System testing is actually done to the entire system
against the Functional Requirement Specification and/or the System
Requirement Specification. Moreover, it is an investigatory testing
phase, where the focus is to have almost a destructive attitude and
test not only the design, but also the behavior and even the believed
expectations of the customer. It is also intended to test up to and
beyond the bounds defined in the software/hardware requirements
specifications. In Motorola®, Automated Testing is one of the testing
methodologies uses by GSG-iSGT (Global Software Group - iDEN
TM
Subcriber Group-Test) to increase the testing volume, productivity
and reduce test cycle-time in iDEN
TM
phones testing. Testing is able
to produce more robust products before release to the market. In this
paper, iHopper is proposed as a tool to perform stress test on iDEN
TM
phonse. We will discuss the value that automation has brought to
iDEN
TM
Phone testing such as improving software quality in the
iDEN
TM
phone together with some metrics. We will also look into
the advantages of the proposed system and some discussion of the
future work as well.
Abstract: Construction projects generally take place in
uncontrolled and dynamic environments where construction waste is
a serious environmental problem in many large cities. The total
amount of waste and carbon dioxide emissions from transportation
vehicles are still out of control due to increasing construction
projects, massive urban development projects and the lack of
effective tools for minimizing adverse environmental impacts in
construction. This research is about utilization of the integrated
applications of automated advanced tracking and data storage
technologies in the area of environmental management to monitor
and control adverse environmental impacts such as construction
waste and carbon dioxide emissions. Radio Frequency Identification
(RFID) integrated with the Global Position System (GPS) provides
an opportunity to uniquely identify materials, components, and
equipments and to locate and track them using minimal or no worker
input. The transmission of data to the central database will be carried
out with the help of Global System for Mobile Communications
(GSM).
Abstract: The theory of Groebner Bases, which has recently been
honored with the ACM Paris Kanellakis Theory and Practice Award,
has become a crucial building block to computer algebra, and is
widely used in science, engineering, and computer science. It is wellknown
that Groebner bases computation is EXP-SPACE in a general
setting. In this paper, we give an algorithm to show that Groebner
bases computation is P-SPACE in Boolean rings. We also show that
with this discovery, the Groebner bases method can theoretically be
as efficient as other methods for automated verification of hardware
and software. Additionally, many useful and interesting properties of
Groebner bases including the ability to efficiently convert the bases
for different orders of variables making Groebner bases a promising
method in automated verification.
Abstract: One important problem in today organizations is the
existence of non-integrated information systems, inconsistency and
lack of suitable correlations between legacy and modern systems.
One main solution is to transfer the local databases into a global one.
In this regards we need to extract the data structures from the legacy
systems and integrate them with the new technology systems. In
legacy systems, huge amounts of a data are stored in legacy
databases. They require particular attention since they need more
efforts to be normalized, reformatted and moved to the modern
database environments. Designing the new integrated (global)
database architecture and applying the reverse engineering requires
data normalization. This paper proposes the use of database reverse
engineering in order to integrate legacy and modern databases in
organizations. The suggested approach consists of methods and
techniques for generating data transformation rules needed for the
data structure normalization.
Abstract: The ElectroEncephaloGram (EEG) is useful for
clinical diagnosis and biomedical research. EEG signals often
contain strong ElectroOculoGram (EOG) artifacts produced
by eye movements and eye blinks especially in EEG recorded
from frontal channels. These artifacts obscure the underlying
brain activity, making its visual or automated inspection
difficult. The goal of ocular artifact removal is to remove
ocular artifacts from the recorded EEG, leaving the underlying
background signals due to brain activity. In recent times,
Independent Component Analysis (ICA) algorithms have
demonstrated superior potential in obtaining the least
dependent source components. In this paper, the independent
components are obtained by using the JADE algorithm (best
separating algorithm) and are classified into either artifact
component or neural component. Neural Network is used for
the classification of the obtained independent components.
Neural Network requires input features that exactly represent
the true character of the input signals so that the neural
network could classify the signals based on those key
characters that differentiate between various signals. In this
work, Auto Regressive (AR) coefficients are used as the input
features for classification. Two neural network approaches
are used to learn classification rules from EEG data. First, a
Polynomial Neural Network (PNN) trained by GMDH (Group
Method of Data Handling) algorithm is used and secondly,
feed-forward neural network classifier trained by a standard
back-propagation algorithm is used for classification and the
results show that JADE-FNN performs better than JADEPNN.
Abstract: Electrocardiogram (ECG) segmentation is necessary to help reduce the time consuming task of manually annotating ECG's. Several algorithms have been developed to segment the ECG automatically. We first review several of such methods, and then present a new single lead segmentation method based on Adaptive piecewise constant approximation (APCA) and Piecewise derivative dynamic time warping (PDDTW). The results are tested on the QT database. We compared our results to Laguna's two lead method. Our proposed approach has a comparable mean error, but yields a slightly higher standard deviation than Laguna's method.
Abstract: In this paper we describe a computer-aided diagnosis (CAD) system for automated detection of pulmonary nodules in computed-tomography (CT) images. After extracting the pulmonary parenchyma using a combination of image processing techniques, a region growing method is applied to detect nodules based on 3D geometric features. We applied the CAD system to CT scans collected in a screening program for lung cancer detection. Each scan consists of a sequence of about 300 slices stored in DICOM (Digital Imaging and Communications in Medicine) format. All malignant nodules were detected and a low false-positive detection rate was achieved.
Abstract: Y chromosome microdeletions are the most common
genetic cause of male infertility and screening for these
microdeletions in azoospermic or severely oligospermic men is now
standard practice. Analysis of the Y chromosome in men with
azoospermia or severe oligozoospermia has resulted in the
identification of three regions in the euchromatic part of the long arm
of the human Y chromosome (Yq11) that are frequently deleted in
men with otherwise unexplained spermatogenic failure. PCR analysis
of microdeletions in the AZFa, AZFb and AZFc regions of the
human Y chromosome is an important screening tool. The aim of this
study was to analyse the type of microdeletions in men with fertility
disorders in Slovakia. We evaluated 227 patients with azoospermia
and with normal karyotype. All patient samples were analyzed
cytogenetically. For PCR amplification of sequence-tagged sites
(STS) of the AZFa, AZFb and AZFc regions of the Y chromosome
was used Devyser AZF set. Fluorescently labeled primers for all
markers in one multiplex PCR reaction were used and for automated
visualization and identification of the STS markers we used genetic
analyzer ABi 3500xl (Life Technologies). We reported 13 cases of
deletions in the AZF region 5,73%. Particular types of deletions were
recorded in each region AZFa,b,c .The presence of microdeletions in
the AZFc region was the most frequent. The study confirmed that
percentage of microdeletions in the AZF region is low in Slovak
azoospermic patients, but important from a prognostic view.
Abstract: Image mosaicing is a technique that permits to enlarge the field of view of a camera. For instance, it is employed to achieve panoramas with common cameras or even in scientific applications, to achieve the image of a whole culture in microscopical imaging. Usually, a mosaic of cell cultures is achieved through using automated microscopes. However, this is often performed in batch, through CPU intensive minimization algorithms. In addition, live stem cells are studied in phase contrast, showing a low contrast that cannot be improved further. We present a method to study the flat field from live stem cells images even in case of 100% confluence, this permitting to build accurate mosaics on-line using high performance algorithms.
Abstract: Texture classification is a trendy and a catchy
technology in the field of texture analysis. Textures, the repeated
patterns, have different frequency components along different
orientations. Our work is based on Texture Classification and its
applications. It finds its applications in various fields like Medical
Image Classification, Computer Vision, Remote Sensing,
Agricultural Field, and Textile Industry. Weed control has a major
effect on agriculture. A large amount of herbicide has been used for
controlling weeds in agriculture fields, lawns, golf courses, sport
fields, etc. Random spraying of herbicides does not meet the exact
requirement of the field. Certain areas in field have more weed
patches than estimated. So, we need a visual system that can
discriminate weeds from the field image which will reduce or even
eliminate the amount of herbicide used. This would allow farmers to
not use any herbicides or only apply them where they are needed. A
machine vision precision automated weed control system could
reduce the usage of chemicals in crop fields. In this paper, an
intelligent system for automatic weeding strategy Multi Resolution
Combined Statistical & spatial Frequency is used to discriminate the
weeds from the crops and to classify them as narrow, little and broad
weeds.
Abstract: In this work the design and characterization of an optoelectronic automated measurement system it is presented. The optoelectronic devices of this system are an optical transmitter, the optical components and the optical receiver, which were selected for a great precision of the system. The mechanical system allows free displacement of the components as well as the devices that generate the movement. The results, length and profile of the objects are display in Lab View.
Abstract: This paper describes the development of an
autonomous robot for painting the interior walls of buildings. The
robot consists of a painting arm with an end effector roller that scans
the walls vertically and a mobile platform to give horizontal feed to
paint the whole area of the wall. The painting arm has a planar twolink
mechanism with two joints. Joints are driven from a stepping
motor through a ball screw-nut mechanism. Four ultrasonic sensors
are attached to the mobile platform and used to maintain a certain
distance from the facing wall and to avoid collision with side walls.
When settled on adjusted distance from the wall, the controller starts
the painting process autonomously. Simplicity, relatively low weight
and short painting time were considered in our design. Different
modules constituting the robot have been separately tested then
integrated. Experiments have shown successfulness of the robot in its
intended tasks.
Abstract: In this paper, an automated algorithm to estimate and remove the continuous baseline from measured spectra containing both continuous and discontinuous bands is proposed. The algorithm uses previous information contained in a Continuous Database Spectra (CDBS) to obtain a linear basis, with minimum number of sampled vectors, capable of representing a continuous baseline. The proposed algorithm was tested by using a CDBS of flame spectra where Principal Components Analysis and Non-negative Matrix Factorization were used to obtain linear bases. Thus, the radical emissions of natural gas, oil and bio-oil flames spectra at different combustion conditions were obtained. In order to validate the performance in the baseline estimation process, the Goodness-of-fit Coefficient and the Root Mean-squared Error quality metrics were evaluated between the estimated and the real spectra in absence of discontinuous emission. The achieved results make the proposed method a key element in the development of automatic monitoring processes strategies involving discontinuous spectral bands.
Abstract: The pipe inspection operation is the difficult detective
performance. Almost applications are mainly relies on a manual
recognition of defective areas that have carried out detection by an
engineer. Therefore, an automation process task becomes a necessary
in order to avoid the cost incurred in such a manual process. An
automated monitoring method to obtain a complete picture of the
sewer condition is proposed in this work. The focus of the research is
the automated identification and classification of discontinuities in
the internal surface of the pipe. The methodology consists of several
processing stages including image segmentation into the potential
defect regions and geometrical characteristic features. Automatic
recognition and classification of pipe defects are carried out by means
of using an artificial neural network technique (ANN) based on
Radial Basic Function (RBF). Experiments in a realistic environment
have been conducted and results are presented.
Abstract: A new approach based on the consideration that electroencephalogram (EEG) signals are chaotic signals was presented for automated diagnosis of electroencephalographic changes. This consideration was tested successfully using the nonlinear dynamics tools, like the computation of Lyapunov exponents. This paper presented the usage of statistics over the set of the Lyapunov exponents in order to reduce the dimensionality of the extracted feature vectors. Since classification is more accurate when the pattern is simplified through representation by important features, feature extraction and selection play an important role in classifying systems such as neural networks. Multilayer perceptron neural network (MLPNN) architectures were formulated and used as basis for detection of electroencephalographic changes. Three types of EEG signals (EEG signals recorded from healthy volunteers with eyes open, epilepsy patients in the epileptogenic zone during a seizure-free interval, and epilepsy patients during epileptic seizures) were classified. The selected Lyapunov exponents of the EEG signals were used as inputs of the MLPNN trained with Levenberg- Marquardt algorithm. The classification results confirmed that the proposed MLPNN has potential in detecting the electroencephalographic changes.