Abstract: In this paper, we present the region based hidden Markov random field model (RBHMRF), which encodes the characteristics of different brain regions into a probabilistic framework for brain MR image segmentation. The recently proposed TV+L1 model is used for region extraction. By utilizing different spatial characteristics in different brain regions, the RMHMRF model performs beyond the current state-of-the-art method, the hidden Markov random field model (HMRF), which uses identical spatial information throughout the whole brain. Experiments on both real and synthetic 3D MR images show that the segmentation result of the proposed method has higher accuracy compared to existing algorithms.
Abstract: In this paper, a novel and fast algorithm for segmental
and subsegmental lung vessel segmentation is introduced using
Computed Tomography Angiography images. This process is quite
important especially at the detection of pulmonary embolism, lung
nodule, and interstitial lung disease. The applied method has been
realized at five steps. At the first step, lung segmentation is achieved.
At the second one, images are threshold and differences between the
images are detected. At the third one, left and right lungs are gathered
with the differences which are attained in the second step and Exact
Lung Image (ELI) is achieved. At the fourth one, image, which is
threshold for vessel, is gathered with the ELI. Lastly, identifying and
segmentation of segmental and subsegmental lung vessel have been
carried out thanks to image which is obtained in the fourth step. The
performance of the applied method is found quite well for
radiologists and it gives enough results to the surgeries medically.
Abstract: In this paper, a new learning approach for network
intrusion detection using naïve Bayesian classifier and ID3 algorithm
is presented, which identifies effective attributes from the training
dataset, calculates the conditional probabilities for the best attribute
values, and then correctly classifies all the examples of training and
testing dataset. Most of the current intrusion detection datasets are
dynamic, complex and contain large number of attributes. Some of
the attributes may be redundant or contribute little for detection
making. It has been successfully tested that significant attribute
selection is important to design a real world intrusion detection
systems (IDS). The purpose of this study is to identify effective
attributes from the training dataset to build a classifier for network
intrusion detection using data mining algorithms. The experimental
results on KDD99 benchmark intrusion detection dataset demonstrate
that this new approach achieves high classification rates and reduce
false positives using limited computational resources.
Abstract: Most simple nonlinear thresholding rules for
wavelet- based denoising assume that the wavelet coefficients are independent. However, wavelet coefficients of natural images have significant dependencies. This paper attempts to give a recipe for selecting one of the popular image-denoising algorithms based
on VisuShrink, SureShrink, OracleShrink, BayesShrink and BiShrink and also this paper compares different Bivariate models used for image denoising applications. The first part of the paper
compares different Shrinkage functions used for image-denoising.
The second part of the paper compares different bivariate models
and the third part of this paper uses the Bivariate model with modified marginal variance which is based on Laplacian assumption. This paper gives an experimental comparison on six 512x512 commonly used images, Lenna, Barbara, Goldhill,
Clown, Boat and Stonehenge. The following noise powers 25dB,26dB, 27dB, 28dB and 29dB are added to the six standard images and the corresponding Peak Signal to Noise Ratio (PSNR) values
are calculated for each noise level.
Abstract: One of the popular methods for recognition of facial
expressions such as happiness, sadness and surprise is based on
deformation of facial features. Motion vectors which show these
deformations can be specified by the optical flow. In this method, for
detecting emotions, the resulted set of motion vectors are compared
with standard deformation template that caused by facial expressions.
In this paper, a new method is introduced to compute the quantity of
likeness in order to make decision based on the importance of
obtained vectors from an optical flow approach. For finding the
vectors, one of the efficient optical flow method developed by
Gautama and VanHulle[17] is used. The suggested method has been
examined over Cohn-Kanade AU-Coded Facial Expression Database,
one of the most comprehensive collections of test images available.
The experimental results show that our method could correctly
recognize the facial expressions in 94% of case studies. The results
also show that only a few number of image frames (three frames) are
sufficient to detect facial expressions with rate of success of about
83.3%. This is a significant improvement over the available methods.
Abstract: Oxidative stress makes up common incidents in
eukaryotic metabolism. The presence of diverse components
disturbing the equilibrium during oxygen metabolism increases
oxidative damage unspecifically in living cells. Body´s own
ubiquinone (Q10) seems to be a promising drug in defending the
heightened appearance of reactive oxygen species (ROS). Though, its
lipophilic properties require a new strategy in drug formulation to
overcome their low bioavailability. Consequently, the manufacture of
heterogeneous nanodispersions is in focus for medical applications.
The composition of conventional nanodispersions is made up of a
drug-consisting core and a surfactive agent, also named as surfactant.
Long-termed encapsulation of the surfactive components into tissues
might be the consequence of the use during medical therapeutics. The
potential of provoking side-effects is given by their nonbiodegradable
properties. Further improvements during fabrication
process use the incorporation of biodegradable components such as
modified γ-polyglutamic acid which decreases the potential of
prospective side-effects.
Abstract: This document describes an electronic speed control designed to drive two DC motors from a 6 V battery pack to be controlled by a commercial universal infrared remote control hand set. Conceived for a tank-like vehicle, one motor drives the left side wheels or tracks and the other motor drives the right side. As it is shown here, there is a left-right steering input and a forward– backward throttles input, like would be used on a model car. It is designed using a microcontroller PIC16F873A.
Abstract: This paper explores steady-state characteristics of
grid-connected doubly fed induction motor (DFIM) in case of unity
power factor operation. Based on the synchronized mathematical
model, analytic determination of the control laws is presented and
illustrated by various figures to understand the effect of the applied
rotor voltage on the speed and the active power. On other hand,
unlike previous works where the stator resistance was neglected, in
this work, stator resistance is included such that the equations can be
applied to small wind turbine generators which are becoming more
popular. Finally the work is crowned by integration of the studied
induction generator in a wind system where an open loop control is
proposed confers a remarkable simplicity of implementation
compared to the known methods.
Abstract: Lanthanide-doped upconversion nanoparticles which can convert near-infrared lights to visible lights have attracted growing interest because of their great potentials in fluorescence imaging. Upconversion fluorescence imaging technique with excitation in the near-infrared (NIR) region has been used for imaging of biological cells and tissues. However, improving the detection sensitivity and decreasing the absorption and scattering in biological tissues are as yet unresolved problems. In this present study, a novel NIR-reflected multispectral imaging system was developed for upconversion fluorescent imaging in small animals. Based on this system, we have obtained the high contrast images without the autofluorescence when biocompatible UCPs were injected near the body surface or deeply into the tissue. Furthermore, we have extracted respective spectra of the upconversion fluorescence and relatively quantify the fluorescence intensity with the multispectral analysis. To our knowledge, this is the first time to analyze and quantify the upconversion fluorescence in the small animal imaging.
Abstract: This paper provides an introduction into the evolution
of information and communication technology and illustrates its
usage in the work domain. The paper is sub-divided into two parts.
The first part gives an overview over the different phases of
information processing in the work domain. It starts by charting the
past and present usage of computers in work environments and shows
current technological trends, which are likely to influence future
business applications. The second part starts by briefly describing,
how the usage of computers changed business processes in the past,
and presents first Ambient Intelligence applications based on
identification and localization information, which are already used in
the production and retail sector. Based on current systems and
prototype applications, the paper gives an outlook of how Ambient
Intelligence technologies could change business processes in the
future.
Abstract: Using spatial models as a shared common basis of
information about the environment for different kinds of contextaware
systems has been a heavily researched topic in the last years.
Thereby the research focused on how to create, to update, and to
merge spatial models so as to enable highly dynamic, consistent and
coherent spatial models at large scale. In this paper however, we
want to concentrate on how context-aware applications could use this
information so as to adapt their behavior according to the situation
they are in. The main idea is to provide the spatial model
infrastructure with a situation recognition component based on
generic situation templates. A situation template is – as part of a
much larger situation template library – an abstract, machinereadable
description of a certain basic situation type, which could be
used by different applications to evaluate their situation. In this
paper, different theoretical and practical issues – technical, ethical
and philosophical ones – are discussed important for understanding
and developing situation dependent systems based on situation
templates. A basic system design is presented which allows for the
reasoning with uncertain data using an improved version of a
learning algorithm for the automatic adaption of situation templates.
Finally, for supporting the development of adaptive applications, we
present a new situation-aware adaptation concept based on
workflows.
Abstract: This paper compares Hilditch, Rosenfeld, Zhang-
Suen, dan Nagendraprasad Wang Gupta (NWG) thinning algorithms
for Javanese character image recognition. Thinning is an effective
process when the focus in not on the size of the pattern, but rather on
the relative position of the strokes in the pattern. The research
analyzes the thinning of 60 Javanese characters.
Time-wise, Zhang-Suen algorithm gives the best results with the
average process time being 0.00455188 seconds. But if we look at
the percentage of pixels that meet one-pixel thickness, Rosenfelt
algorithm gives the best results, with a 99.98% success rate. From the
number of pixels that are erased, NWG algorithm gives the best
results with the average number of pixels erased being 84.12%. It can
be concluded that the Hilditch algorithm performs least successfully
compared to the other three algorithms.
Abstract: Lactic acid alone and its combined application with
nisin were evaluated for reducing population of naturally occurring
microorganisms on chilled shrimp. Fresh shrimps were dipped in 0,
1.0% and 2.0% (v/v) lactic acid alone and their combined application
with 0.04 (g/L/kg) nisin solution for 10 min. Total plate counts of
aerobic bacteria (TPCs), Psychrotrophic counts, population of
Pseudomonas spp., H2S producing bacteria and Lactic acid bacteria
(LAB) on shrimps were determined during storage at 4 °C. The
results indicated that total plate counts were 2.91 and 2.63 log CFU/g
higher on untreated shrimps after 7 and 14 days of storage,
respectively, than on shrimps treated with 2.0% lactic acid combined
with 0.04 (g/L/kg) nisin. Both concentrations of lactic acid indicated
significant reduction on Pseudomonas counts during storage, while
2.0% lactic acid combined with nisin indicated the highest reduction.
In addition, H2S producing bacteria were more sensitive to high
concentration of lactic acid combined with nisin during storage.
Abstract: Protection and proper management of archaeological heritage are an essential process of studying and interpreting the generations present and future. Protecting the archaeological heritage is based upon multidiscipline professional collaboration. This study aims to gather data by different sources (Photogrammetry and Geographic Information System (GIS)) integrated for the purpose of documenting one the of significant archeological sites (Ahl-Alkahf, Jordan). 3D modeling deals with the actual image of the features, shapes and texture to represent reality as realistically as possible by using texture. The 3D coordinates that result of the photogrammetric adjustment procedures are used to create 3D-models of the study area. Adding Textures to the 3D-models surfaces gives a 'real world' appearance to the displayed models. GIS system combined all data, including boundary maps, indicating the location of archeological sites, transportation layer, digital elevation model and orthoimages. For realistic representation of the study area, 3D - GIS model prepared, where efficient generation, management and visualization of such special data can be achieved.
Abstract: We consider linear regression models where both input data (the values of independent variables) and output data (the observations of the dependent variable) are interval-censored. We introduce a possibilistic generalization of the least squares estimator, so called OLS-set for the interval model. This set captures the impact of the loss of information on the OLS estimator caused by interval censoring and provides a tool for quantification of this effect. We study complexity-theoretic properties of the OLS-set. We also deal with restricted versions of the general interval linear regression model, in particular the crisp input – interval output model. We give an argument that natural descriptions of the OLS-set in the crisp input – interval output cannot be computed in polynomial time. Then we derive easily computable approximations for the OLS-set which can be used instead of the exact description. We illustrate the approach by an example.
Abstract: The wireless sensor networks have been extensively
deployed and researched. One of the major issues in wireless sensor
networks is a developing energy-efficient clustering protocol.
Clustering algorithm provides an effective way to prolong the lifetime
of a wireless sensor networks. In the paper, we compare several
clustering protocols which significantly affect a balancing of energy
consumption. And we propose an Energy-Efficient Distributed
Unequal Clustering (EEDUC) algorithm which provides a new way of
creating distributed clusters. In EEDUC, each sensor node sets the
waiting time. This waiting time is considered as a function of residual
energy, number of neighborhood nodes. EEDUC uses waiting time to
distribute cluster heads. We also propose an unequal clustering
mechanism to solve the hot-spot problem. Simulation results show that
EEDUC distributes the cluster heads, balances the energy
consumption well among the cluster heads and increases the network
lifetime.
Abstract: This paper proposes a methodology for analysis of
the dynamic behavior of a robotic manipulator in continuous
time. Initially this system (nonlinear system) will be decomposed
into linear submodels and analyzed in the context of the Linear
and Parameter Varying (LPV) Systems. The obtained linear
submodels, which represent the local dynamic behavior of the
robotic manipulator in some operating points were grouped in
a Takagi-Sugeno fuzzy structure. The obtained fuzzy model was
analyzed and validated through analog simulation, as universal
approximator of the robotic manipulator.
Abstract: Electromyography (EMG) is the study of muscles function through analysis of electrical activity produced from muscles. This electrical activity which is displayed in the form of signal is the result of neuromuscular activation associated with muscle contraction. The most common techniques of EMG signal recording are by using surface and needle/wire electrode where the latter is usually used for interest in deep muscle. This paper will focus on surface electromyogram (SEMG) signal. During SEMG recording, several problems had to been countered such as noise, motion artifact and signal instability. Thus, various signal processing techniques had been implemented to produce a reliable signal for analysis. SEMG signal finds broad application particularly in biomedical field. It had been analyzed and studied for various interests such as neuromuscular disease, enhancement of muscular function and human-computer interface.
Abstract: This paper discusses the novel graphical approach for
stability analysis of multi induction motor drive controlled by a single
inverter. Stability issue arises in parallel connected induction motors
under unbalanced load conditions. The two powerful globally
accepted modeling and simulation software packages such as
MATLAB and LabVIEW are selected to perform the stability
analysis. The stability investigation is performed for different load
conditions and difference in stator and rotor resistances among the
two motors. It is very simple and effective than the techniques
presented to obtain the stability of the parallel connected induction
motor drive under unbalanced load conditions. Approximate transfer
functions are considered to model the induction motors, load
dynamics, speed controllers and inverter. Simulink library tools are
utilized to model the entire drive scheme in MATLAB. Stability
study is discussed in LabVIEW using control design and simulation
toolkits. Simulation results are illustrated for various running
conditions to demonstrate the effectiveness of the transfer function
method.
Abstract: The proximate composition, physical traits and
sensory properties of beef and chicken patties incorporated with
various level of dried cornsilk (Maydis stigma) were studied. The
beef and chicken patties were formulated with either 2%, 4% or 6%
of cornsilk. Both cooked beef and chicken patties incorporated with
6% cornsilk recorded the highest protein concentration at 23.3% and
28.42%, respectively. Both cooked beef and chicken patties
containing 6% cornsilk significantly recorded the lowest
concentration of fat at 11.4% and 14.60%, respectively. Beef and
chicken patties formulated with 6% cornsilk recorded the highest
cooking yield at 80.13% and 83.03% compared to other treatments.
The inclusion of cornsilk did not change the sensory properties and
consumer acceptability of cornsilk-based beef and chicken patties.
Cornsilk fibre has been effective in improving cooking yield,
moisture and fat retention of beef and chicken patties