Abstract: Volume rendering is widely used in medical CT image
visualization. Applying 3D image visualization to diagnosis
application can require accurate volume rendering with high
resolution. Interpolation is important in medical image processing
applications such as image compression or volume resampling.
However, it can distort the original image data because of edge
blurring or blocking effects when image enhancement procedures
were applied. In this paper, we proposed adaptive tension control
method exploiting gradient information to achieve high resolution
medical image enhancement in volume visualization, where restored
images are similar to original images as much as possible. The
experimental results show that the proposed method can improve
image quality associated with the adaptive tension control efficacy.
Abstract: The source voltage of high-power fuel cell shows strong load dependence at comparatively low voltage levels. In order to provide the voltage of 750V on the DC-link for feeding electrical energy into the mains via a three phase inverter a step-up converter with a large step-up ratio is required. The output voltage of this DC/DC-converter must be stabile during variations of the load current and the voltage of the fuel cell. This paper presents the methods and results of the calculation of the efficiency and the expense for the realization for the circuits of the DC/DC-converter that meet these requirements.
Abstract: In this work, the condensation fraction and transition
temperature of neutral many bosonic system are studied within the
static fluctuation approximation (SFA). The effect of the potential
parameters such as the strength and range on the condensate fraction
was investigated. A model potential consisting of a repulsive step
potential and an attractive potential well was used. As the potential
strength or the core radius of the repulsive part increases, the
condensation fraction is found to be decreased at the same
temperature. Also, as the potential depth or the range of the attractive
part increases, the condensation fraction is found to be increased. The
transition temperature is decreased as the potential strength or the
core radius of the repulsive part increases, and it increases as the
potential depth or the range of the attractive part increases.
Abstract: The effects of seawater and slurry ice bleeding methods on the sensory, microbiological and chemical quality changes of cod fillets during chilled storage were examined in this study. The results from sensory evaluation showed that slurry ice bleeding method prolonged the shelf life of cod fillets up to 13-14 days compared to 10-11 days for fish bled in seawater. Slurry ice bleeding method also led to a slower microbial growth and biochemical developments, resulting lower total plate count (TPC), H2S-producing bacteria count, total volatile basic nitrogen (TVB-N), trimethylamine (TMA), free fatty acid (FFA) content and higher phospholipid content (PL) compared to those of samples bled in seawater. The results of principle component analysis revealed that TPC, H2S-producing bacteria, TVB-N, TMA and FFA were in significant correlation. They were also in negative correlation with sensory evaluation (Torry score), PL and water holding capacity (WHC).
Abstract: Weblogs are resource of social structure to discover and track the various type of information written by blogger. In this paper, we proposed to use mining weblogs technique for identifying the trends of influenza where blogger had disseminated their opinion for the anomaly disease. In order to identify the trends, web crawler is applied to perform a search and generated a list of visited links based on a set of influenza keywords. This information is used to implement the analytics report system for monitoring and analyzing the pattern and trends of influenza (H1N1). Statistical and graphical analysis reports are generated. Both types of the report have shown satisfactory reports that reflect the awareness of Malaysian on the issue of influenza outbreak through blogs.
Abstract: This paper proposes a delay-dependent leader-following consensus condition of multi-agent systems with both communication delay and probabilistic self-delay. The proposed methods employ a suitable piecewise Lyapunov-Krasovskii functional and the average dwell time approach. New consensus criterion for the systems are established in terms of linear matrix inequalities (LMIs) which can be easily solved by various effective optimization algorithms. Numerical example showed that the proposed method is effective.
Abstract: Recommender Systems act as personalized decision
guides, aiding users in decisions on matters related to personal taste.
Most previous research on Recommender Systems has focused on the
statistical accuracy of the algorithms driving the systems, with no
emphasis on the trustworthiness of the user. RS depends on
information provided by different users to gather its knowledge. We
believe, if a large group of users provide wrong information it will
not be possible for the RS to arrive in an accurate conclusion. The
system described in this paper introduce the concept of Testing the
knowledge of user to filter out these “bad users".
This paper emphasizes on the mechanism used to provide robust
and effective recommendation.
Abstract: This research tries to analyze the role that knowledge
about foreign markets has in increasing firms- exports in clustered
spaces. We consider two interrelated sources of knowledge: firms-
direct experience and indirect experience from other clustered firms –
export externalities. In particular, it is proposed that firms would
improve their export performance by accessing to export externalities
if they have some previous direct experience that allows them to
identify, understand and exploit them. Also, we propose that this
positive influence of previous direct experience on export
externalities keeps only up to a point, where it becomes negative,
creating an inverted “U" shape. Empirical evidence gathered among
wine producers located in La Rioja tends to confirm that firms enjoy
of export externalities if they have export experience along several
years and countries increase their export performance. While this
relationship becomes less relevant as they develop a higher
experience, we could not confirm the existence of a curvilinear
relationship in their influence on export externalities and export
performance.
Abstract: Computer modeling has played a unique role in
understanding electrocardiography. Modeling and simulating cardiac
action potential propagation is suitable for studying normal and
pathological cardiac activation. This paper presents a 2-D Cellular
Automata model for simulating action potential propagation in
cardiac tissue. We demonstrate a novel algorithm in order to use
minimum neighbors. This algorithm uses the summation of the
excitability attributes of excited neighboring cells. We try to
eliminate flat edges in the result patterns by inserting probability to
the model. We also preserve the real shape of action potential by
using linear curve fitting of one well known electrophysiological
model.
Abstract: Landslide susceptibility map delineates the potential
zones for landslide occurrence. Previous works have applied
multivariate methods and neural networks for mapping landslide
susceptibility. This study proposed a new approach to integrate
decision tree model and spatial cluster statistic for assessing landslide
susceptibility spatially. A total of 2057 landslide cells were digitized
for developing the landslide decision tree model. The relationships of
landslides and instability factors were explicitly represented by using
tree graphs in the model. The local Getis-Ord statistics were used to
cluster cells with high landslide probability. The analytic result from
the local Getis-Ord statistics was classed to create a map of landslide
susceptibility zones. The map was validated using new landslide data
with 482 cells. Results of validation show an accuracy rate of 86.1% in
predicting new landslide occurrence. This indicates that the proposed
approach is useful for improving landslide susceptibility mapping.
Abstract: In the last years, the computers have increased their capacity of calculus and networks, for the interconnection of these machines. The networks have been improved until obtaining the actual high rates of data transferring. The programs that nowadays try to take advantage of these new technologies cannot be written using the traditional techniques of programming, since most of the algorithms were designed for being executed in an only processor,in a nonconcurrent form instead of being executed concurrently ina set of processors working and communicating through a network.This paper aims to present the ongoing development of a new system for the reconfiguration of grouping of computers, taking into account these new technologies.
Abstract: In this study the mixed convection heat transfer in a
coil-in-shell heat exchanger for various Reynolds numbers and
various dimensionless coil pitch was experimentally investigated.
The experiments were conducted for both laminar and turbulent flow
inside coil and the effects of coil pitch on shell-side heat transfer
coefficient of the heat exchanger were studied. The particular
difference in this study in comparison with the other similar studies
was the boundary conditions for the helical coils. The results indicate
that with the increase of coil pitch, shell-side heat transfer coefficient
is increased.
Abstract: In this paper, we have compared the performance of a Turbo and Trellis coded optical code division multiple access (OCDMA) system. The comparison of the two codes has been accomplished by employing optical orthogonal codes (OOCs). The Bit Error Rate (BER) performances have been compared by varying the code weights of address codes employed by the system. We have considered the effects of optical multiple access interference (OMAI), thermal noise and avalanche photodiode (APD) detector noise. Analysis has been carried out for the system with and without double optical hard limiter (DHL). From the simulation results it is observed that a better and distinct comparison can be drawn between the performance of Trellis and Turbo coded systems, at lower code weights of optical orthogonal codes for a fixed number of users. The BER performance of the Turbo coded system is found to be better than the Trellis coded system for all code weights that have been considered for the simulation. Nevertheless, the Trellis coded OCDMA system is found to be better than the uncoded OCDMA system. Trellis coded OCDMA can be used in systems where decoding time has to be kept low, bandwidth is limited and high reliability is not a crucial factor as in local area networks. Also the system hardware is less complex in comparison to the Turbo coded system. Trellis coded OCDMA system can be used without significant modification of the existing chipsets. Turbo-coded OCDMA can however be employed in systems where high reliability is needed and bandwidth is not a limiting factor.
Abstract: In this paper, a simulated annealing algorithm has been developed to optimize machining parameters in turning operation on cylindrical workpieces. The turning operation usually includes several passes of rough machining and a final pass of finishing. Seven different constraints are considered in a non-linear model where the goal is to achieve minimum total cost. The weighted total cost consists of machining cost, tool cost and tool replacement cost. The computational results clearly show that the proposed optimization procedure has considerably improved total operation cost by optimally determining machining parameters.
Abstract: The intelligent fuzzy input estimator is used to estimate
the input force of the rigid bar structural system in this study. The
fuzzy Kalman filter without the input term and the fuzzy weighting
recursive least square estimator are two main portions of this method.
The practicability and accuracy of the proposed method were verified
with numerical simulations from which the input forces of a rigid bar
structural system were estimated from the output responses. In order to
examine the accuracy of the proposed method, a rigid bar structural
system is subjected to periodic sinusoidal dynamic loading. The
excellent performance of this estimator is demonstrated by comparing
it with the use of difference weighting function and improper the
initial process noise covariance. The estimated results have a good
agreement with the true values in all cases tested.
Abstract: This paper presents dynamic voltage collapse prediction on an actual power system using support vector machines.
Dynamic voltage collapse prediction is first determined based on the PTSI calculated from information in dynamic simulation output. Simulations were carried out on a practical 87 bus test system by considering load increase as the contingency. The data collected from the time domain simulation is then used as input to the SVM in which support vector regression is used as a predictor to determine the
dynamic voltage collapse indices of the power system. To reduce training time and improve accuracy of the SVM, the Kernel function type and Kernel parameter are considered. To verify the
effectiveness of the proposed SVM method, its performance is compared with the multi layer perceptron neural network (MLPNN). Studies show that the SVM gives faster and more accurate results for dynamic voltage collapse prediction compared with the MLPNN.
Abstract: The aim of this contribution is to present a new
approach in modeling the electrical activity of the human heart. A
recurrent artificial neural network is being used in order to exhibit a
subset of the dynamics of the electrical behavior of the human heart.
The proposed model can also be used, when integrated, as a
diagnostic tool of the human heart system.
What makes this approach unique is the fact that every model is
being developed from physiological measurements of an individual.
This kind of approach is very difficult to apply successfully in many
modeling problems, because of the complexity and entropy of the
free variables describing the complex system. Differences between
the modeled variables and the variables of an individual, measured at
specific moments, can be used for diagnostic purposes. The sensor
fusion used in order to optimize the utilization of biomedical sensors
is another point that this paper focuses on. Sensor fusion has been
known for its advantages in applications such as control and
diagnostics of mechanical and chemical processes.
Abstract: Proteomics is one of the largest areas of research for
bioinformatics and medical science. An ambitious goal of proteomics
is to elucidate the structure, interactions and functions of all proteins
within cells and organisms. Predicting Protein-Protein Interaction
(PPI) is one of the crucial and decisive problems in current research.
Genomic data offer a great opportunity and at the same time a lot of
challenges for the identification of these interactions. Many methods
have already been proposed in this regard. In case of in-silico
identification, most of the methods require both positive and negative
examples of protein interaction and the perfection of these examples
are very much crucial for the final prediction accuracy. Positive
examples are relatively easy to obtain from well known databases. But
the generation of negative examples is not a trivial task. Current PPI
identification methods generate negative examples based on some
assumptions, which are likely to affect their prediction accuracy.
Hence, if more reliable negative examples are used, the PPI prediction
methods may achieve even more accuracy. Focusing on this issue, a
graph based negative example generation method is proposed, which
is simple and more accurate than the existing approaches. An
interaction graph of the protein sequences is created. The basic
assumption is that the longer the shortest path between two
protein-sequences in the interaction graph, the less is the possibility of
their interaction. A well established PPI detection algorithm is
employed with our negative examples and in most cases it increases
the accuracy more than 10% in comparison with the negative pair
selection method in that paper.
Abstract: Urbanization and regionalization are two different
approaches when it comes to economical structures and development,
infrastructure and mobility, quality of life and living, education,
social cohesion and many other topics. At first glance, the structures
associated with urbanization and regionalization seems to be
contradicting. This paper discusses possibilities of transfer and
cooperation between rural and urban structures. An empirical
investigation contributed to reveal scenarios of supposable forms of
exchange and cooperation of remote rural areas and big cities.
Abstract: In this paper; we are interested principally in dynamic modelling of quadrotor while taking into account the high-order nonholonomic constraints in order to develop a new control scheme as well as the various physical phenomena, which can influence the dynamics of a flying structure. These permit us to introduce a new state-space representation. After, the use of Backstepping approach for the synthesis of tracking errors and Lyapunov functions, a sliding mode controller is developed in order to ensure Lyapunov stability, the handling of all system nonlinearities and desired tracking trajectories. Finally simulation results are also provided in order to illustrate the performances of the proposed controller.