Abstract: In this study a neural network (NN) was proposed to
predict the sorption of binary mixture of copper-cobalt ions into
clinoptilolite as ion-exchanger. The configuration of the
backpropagation neural network giving the smallest mean square
error was three-layer NN with tangent sigmoid transfer function at
hidden layer with 10 neurons, linear transfer function at output layer
and Levenberg-Marquardt backpropagation training algorithm.
Experiments have been carried out in the batch reactor to obtain
equilibrium data of the individual sorption and the mixture of coppercobalt
ions. The obtained modeling results have shown that the used
of neural network has better adjusted the equilibrium data of the
binary system when compared with the conventional sorption
isotherm models.
Abstract: An unstructured finite volume numerical model is
presented here for simulating shallow-water flows with wetting and
drying fronts. The model is based on the Green-s theorem in
combination with Chorin-s projection method. A 2nd-order upwind
scheme coupled with a Least Square technique is used to handle
convection terms. An Wetting and drying treatment is used in the
present model to ensures the total mass conservation. To test it-s
capacity and reliability, the present model is used to solve the
Parabolic Bowl problem. We compare our numerical solutions with
the corresponding analytical and existing standard numerical results.
Excellent agreements are found in all the cases.
Abstract: This paper presents a video matting method, which extracts the foreground and alpha matte from a video sequence. The objective of video matting is finding the foreground and compositing it with the background that is different from the one in the original image. By finding the motion vectors (MVs) using a sliced block matching algorithm (SBMA), we can extract moving regions from the video sequence under the assumption that the foreground is moving and the background is stationary. In practice, foreground areas are not moving through all frames in an image sequence, thus we accumulate moving regions through the image sequence. The boundaries of moving regions are found by Canny edge detector and the foreground region is separated in each frame of the sequence. Remaining regions are defined as background regions. Extracted backgrounds in each frame are combined and reframed as an integrated single background. Based on the estimated background, we compute the frame difference (FD) of each frame. Regions with the FD larger than the threshold are defined as foreground regions, boundaries of foreground regions are defined as unknown regions and the rest of regions are defined as backgrounds. Segmentation information that classifies an image into foreground, background, and unknown regions is called a trimap. Matting process can extract an alpha matte in the unknown region using pixel information in foreground and background regions, and estimate the values of foreground and background pixels in unknown regions. The proposed video matting approach is adaptive and convenient to extract a foreground automatically and to composite a foreground with a background that is different from the original background.
Abstract: Since straightness error of linear motor stage is hardly
dependent upon machining accuracy and assembling accuracy, there is
limit on maximum realizable accuracy. To cope with this limitation,
this paper proposed a servo system to compensate straightness error of
a linear motor stage. The servo system is mounted on the slider of the
linear motor stage and moves in the direction of the straightness error
so as to compensate the error. From position dependency and
repeatability of the straightness error of the slider, a feedforward
compensation control is applied to the platform servo control. In the
consideration of required fine positioning accuracy, a platform driven
by an electro-magnetic actuator is suggested and a sliding mode
control was applied. The effectiveness of the sliding mode control was
verified along with some experimental results.
Abstract: Recently there has been a growing interest in the field
of bio-mimetic robots that resemble the behaviors of an insect or an
aquatic animal, among many others. One of various bio-mimetic robot
applications is to explore pipelines, spotting any troubled areas or
malfunctions and reporting its data. Moreover, the robot is able to
prepare for and react to any abnormal routes in the pipeline. Special
types of mobile robots are necessary for the pipeline monitoring tasks.
In order to move effectively along a pipeline, the robot-s movement
will resemble that of insects or crawling animals. When situated in
massive pipelines with complex routes, the robot places fixed sensors
in several important spots in order to complete its monitoring. This
monitoring task is to prevent a major system failure by preemptively
recognizing any minor or partial malfunctions. Areas uncovered by
fixed sensors are usually impossible to provide real-time observation
and examination, and thus are dependent on periodical offline
monitoring. This paper proposes a monitoring system that is able to
monitor the entire area of pipelines–with and without fixed
sensors–by using the bio-mimetic robot.
Abstract: In this paper, we propose a face recognition algorithm
using AAM and Gabor features. Gabor feature vectors which are well
known to be robust with respect to small variations of shape, scaling,
rotation, distortion, illumination and poses in images are popularly
employed for feature vectors for many object detection and
recognition algorithms. EBGM, which is prominent among face
recognition algorithms employing Gabor feature vectors, requires
localization of facial feature points where Gabor feature vectors are
extracted. However, localization method employed in EBGM is based
on Gabor jet similarity and is sensitive to initial values. Wrong
localization of facial feature points affects face recognition rate. AAM
is known to be successfully applied to localization of facial feature
points. In this paper, we devise a facial feature point localization
method which first roughly estimate facial feature points using AAM
and refine facial feature points using Gabor jet similarity-based facial
feature localization method with initial points set by the rough facial
feature points obtained from AAM, and propose a face recognition
algorithm using the devised localization method for facial feature
localization and Gabor feature vectors. It is observed through
experiments that such a cascaded localization method based on both
AAM and Gabor jet similarity is more robust than the localization
method based on only Gabor jet similarity. Also, it is shown that the
proposed face recognition algorithm using this devised localization
method and Gabor feature vectors performs better than the
conventional face recognition algorithm using Gabor jet
similarity-based localization method and Gabor feature vectors like
EBGM.
Abstract: Corporate credit rating prediction using statistical and
artificial intelligence (AI) techniques has been one of the attractive
research topics in the literature. In recent years, multiclass
classification models such as artificial neural network (ANN) or
multiclass support vector machine (MSVM) have become a very
appealing machine learning approaches due to their good
performance. However, most of them have only focused on classifying
samples into nominal categories, thus the unique characteristic of the
credit rating - ordinality - has been seldom considered in their
approaches. This study proposes new types of ANN and MSVM
classifiers, which are named OMANN and OMSVM respectively.
OMANN and OMSVM are designed to extend binary ANN or SVM
classifiers by applying ordinal pairwise partitioning (OPP) strategy.
These models can handle ordinal multiple classes efficiently and
effectively. To validate the usefulness of these two models, we applied
them to the real-world bond rating case. We compared the results of
our models to those of conventional approaches. The experimental
results showed that our proposed models improve classification
accuracy in comparison to typical multiclass classification techniques
with the reduced computation resource.
Abstract: Bio-chips are used for experiments on genes and
contain various information such as genes, samples and so on. The
two-dimensional bio-chips, in which one axis represent genes and the
other represent samples, are widely being used these days. Instead of
experimenting with real genes which cost lots of money and much
time to get the results, bio-chips are being used for biological
experiments. And extracting data from the bio-chips with high
accuracy and finding out the patterns or useful information from such
data is very important. Bio-chip analysis systems extract data from
various kinds of bio-chips and mine the data in order to get useful
information. One of the commonly used methods to mine the data is
classification. The algorithm that is used to classify the data can be
various depending on the data types or number characteristics and so
on. Considering that bio-chip data is extremely large, an algorithm that
imitates the ecosystem such as the ant algorithm is suitable to use as an
algorithm for classification. This paper focuses on finding the
classification rules from the bio-chip data using the Ant Colony
algorithm which imitates the ecosystem. The developed system takes
in consideration the accuracy of the discovered rules when it applies it
to the bio-chip data in order to predict the classes.
Abstract: Polynomial bases and normal bases are both used for
elliptic curve cryptosystems, but field arithmetic operations such as
multiplication, inversion and doubling for each basis are implemented
by different methods. In general, it is said that normal bases, especially
optimal normal bases (ONB) which are special cases on normal bases,
are efficient for the implementation in hardware in comparison with
polynomial bases. However there seems to be more examined by
implementing and analyzing these systems under similar condition. In
this paper, we designed field arithmetic operators for each basis over
GF(2233), which field has a polynomial basis recommended by SEC2
and a type-II ONB both, and analyzed these implementation results.
And, in addition, we predicted the efficiency of two elliptic curve
cryptosystems using these field arithmetic operators.
Abstract: The Internet has become an indispensable part of our lives. Witnessing recent web-based mass collaboration, e.g. Wikipedia, people are questioning whether the Internet has made fundamental changes to the society or whether it is merely a hyperbolic fad. It has long been assumed that collective action for a certain goal yields the problem of free-riding, due to its non-exclusive and non-rival characteristics. Then, thanks to recent technological advances, the on-line space experienced the following changes that enabled it to produce public goods: 1) decrease in the cost of production or coordination 2) externality from networked structure 3) production function which integrates both self-interest and altruism. However, this research doubts the homogeneity of on-line mass collaboration and argues that a more sophisticated and systematical approach is required. The alternative that we suggest is to connect the characteristics of the goal to the motivation. Despite various approaches, previous literature fails to recognize that motivation can be structurally restricted by the characteristic of the goal. First we draw a typology of on-line mass collaboration with 'the extent of expected beneficiary' and 'the existence of externality', and then we examine each combination of motivation using Benkler-s framework. Finally, we explore and connect such typology with its possible dominant participating motivation.
Abstract: Orthogonal frequency division multiplexing (OFDM)
has developed into a popular scheme for wideband digital
communications used in consumer applications such as digital broadcasting, wireless networking and broadband internet access. In
the OFDM system, carrier frequency offset (CFO) causes intercarrier
interference (ICI) which significantly degrades the system error performance. In this paper we provide an exact evaluation method for error performance analysis of arbitrary 2-D modulation OFDM systems with CFO, and analyze the effect of CFO on error performance.
Abstract: This paper proposes the authentication method using
ESA algorithm instead of using CAVE algorithm in the CDMA
mobile communication systems including IS-95 and CDMA2000 1x.
And, we analyze to apply ESA mechanism on behalf of CAVE
mechanism without the change of message format and air interface in
the existing CDMA systems. If ESA algorithm can be used as the
substitution of CAVE algorithm, security strength of authentication
algorithm is intensified without protocol change. An algorithm
replacement proposed in this paper is not to change an authentication
mechanism, but to configure input of ESA algorithm and to produce
output. Therefore, our proposal can be the compatible to the existing
systems.
Abstract: Eye localization is necessary for face recognition and
related application areas. Most of eye localization algorithms reported
so far still need to be improved about precision and computational
time for successful applications. In this paper, we propose an eye
location method based on multi-scale Gabor feature vectors, which is
more robust with respect to initial points. The eye localization based
on Gabor feature vectors first needs to constructs an Eye Model Bunch
for each eye (left or right eye) which consists of n Gabor jets and
average eye coordinates of each eyes obtained from n model face
images, and then tries to localize eyes in an incoming face image by
utilizing the fact that the true eye coordinates is most likely to be very
close to the position where the Gabor jet will have the best Gabor jet
similarity matching with a Gabor jet in the Eye Model Bunch. Similar
ideas have been already proposed in such as EBGM (Elastic Bunch
Graph Matching). However, the method used in EBGM is known to be
not robust with respect to initial values and may need extensive search
range for achieving the required performance, but extensive search
ranges will cause much more computational burden. In this paper, we
propose a multi-scale approach with a little increased computational
burden where one first tries to localize eyes based on Gabor feature
vectors in a coarse face image obtained from down sampling of the
original face image, and then localize eyes based on Gabor feature
vectors in the original resolution face image by using the eye
coordinates localized in the coarse scaled image as initial points.
Several experiments and comparisons with other eye localization
methods reported in the other papers show the efficiency of our
proposed method.
Abstract: Existing underground pipe jacking methods use a
reinforcing rod in a steel tube to obtain structural stiffness. However,
some problems such as inconvenience of works and expensive
materials resulted from limited working space and reinforcing works
are existed. To resolve these problems, a new pipe jacking method,
namely PST (Prestressed Segment Tunnel) method, was developed
which used joint to connect the steel segment and form erection
structure. For evaluating the flexural capacity of the PST method
structure, a experimental test was conducted. The parameters
considered in the test were span-to-depth ratio of segment, diameter of
steel tube at the corner, prestressing force, and welding of joint. The
flexural behaviours with the effect of load capacity in serviceability
state according to different parameters were examined.. The frame
with long segments could increase flexural stiffness and the specimen
with large diameter of concave corner showed excellent resistance
ability to the negative moment. In addition, welding of joints increased
the flexural capacity.
Abstract: This experiment was conducted in attempt of
improving hydrodynamic efficiency of the propulsion mechanism by
installing a spring to the wing so that the opening angle of the wing in
one stroke can be changed automatically, compared to the existing
method of fixed maximum opening angle in Weis-Fogh type ship
propulsion mechanism. Average thrust coefficient was almost fixed
with all velocity ratio with the prototype, but with the spring type,
thrust coefficient increased sharply as velocity ratio increased.
Average propulsive efficiency was larger with bigger opening angle in
the prototype, but in the spring type, the one with smaller spring
coefficient had larger value. In the range over 1.0 in velocity ratio
where big thrust can be generated, spring type had more than twice of
propulsive efficiency increase compared to the prototype.
Abstract: In this paper, the signal transmission analysis of the
semicircle-shaped via structure for the differential pairs is presented in
the frequency range up to 10 GHz. In order to improve the signal
transmission properties in the differential pairs, single via is separated
centrally into two semicircle-shaped sections, which are
interconnected with the traces of differential pairs respectively. This
via structure make possible to route differential pairs using only one
via. In addition, it can improve impedance discontinuity around its
region and then enhance the signal transmission properties in the
differential pairs. The electrical analysis such as S-parameter
calculation and eye diagram simulation has been performed to
investigate the improvement of the signal transmission property in the
differential pairs with new via structure.
Abstract: In this paper, we present a novel approach to location
system under indoor environment. The key idea of our work is
accurate distance estimation with cricket-based location system using
A* algorithm. We also use magnetic sensor for detecting obstacles in
indoor environment. Finally, we suggest how this system can be used
in various applications such as asset tracking and monitoring.
Abstract: Jacobs, A.B. (1993) stated that "When I think of a city,
the first thing that comes to mind is the street. If the street is
interesting, the rest of the city is interesting. If the street is mundane,
the city is also mundane." In this statement, he expresses the
importance of the streetscape and the street environment. The
objective of this paper is to analyze the spatial relationships of the
streetscape that affect the general public's preference of the cityscape.
Furthermore, this research focuses on the important role that
streetscape plays in public perception of the city by the pedestrians
who experience it daily. The subject of this paper is eight of the
"Design Seoul Street."The analysis and survey results show the
preference criteria that affect the streetscape and ultimately the
cityscape. This research endeavor shows that differences in physical
form, shape, size, color, locations, and context are important.
Abstract: This paper deals with a novel technique for the
fabrication of Spiral grooves in a dynamic thrust bearing. The main
scheme proposed in this paper is to fabricate the microgrooves using
desktop forming system. This process has advantages compared to the
conventional electro-chemical machining in the viewpoint of a higher
productivity. For this reason, a new testing apparatus is designed and
built for press forming microgrooves on a surface of the thrust bearing.
The material used in this study is sintered Cu-Fe alloy. The effects of
the forming load on the performance of micro press forming are
experimentally investigated. From the experimental results, formed
depths are closed to the target ones with increasing the forming load.
Abstract: There has been a growing interest in the field of
bio-mimetic robots that resemble the shape of an insect or an aquatic
animal, among many others. One bio-mimetic robot serves the
purpose of exploring pipelines, spotting any troubled areas or
malfunctions and reporting its data. Moreover, the robot is able to
prepare for and react to any abnormal routes in the pipeline. In order
to move effectively inside a pipeline, the robot-s movement will
resemble that of a lizard. When situated in massive pipelines with
complex routes, the robot places fixed sensors in several important
spots in order to complete its monitoring. This monitoring task is to
prevent a major system failure by preemptively recognizing any minor
or partial malfunctions. Areas uncovered by fixed sensors are usually
impossible to provide real-time observation and examination, and thus
are dependant on periodical offline monitoring. This paper provides
the Monitoring System that is able to monitor the entire area of
pipelines–with and without fixed sensors–by using the bio-mimetic
robot.