Abstract: Nowadays there are many methods for representing
knowledge such as semantic network, neural network, and conceptual
graphs. Nonetheless, these methods are not sufficiently efficient
when applied to perform and deduce on knowledge domains about
supporting in general education such as algebra, analysis or plane
geometry. This leads to the introduction of computational network
which is a useful tool for representation knowledge base, especially
for computational knowledge, especially knowledge domain about
general education. However, when dealing with a practical problem,
we often do not immediately find a new solution, but we search
related problems which have been solved before and then proposing
an appropriate solution for the problem. Besides that, when finding
related problems, we have to determine whether the result of them
can be used to solve the practical problem or not. In this paper, the
extension model of computational network has been presented. In this
model, Sample Problems, which are related problems, will be used
like the experience of human about practical problem, simulate the
way of human thinking, and give the good solution for the practical
problem faster and more effectively. This extension model is applied
to construct an automatic system for solving algebraic problems in
middle school.
Abstract: Time interleaved sigma-delta (TIΣΔ) architecture is a
potential candidate for high bandwidth analog to digital converters
(ADC) which remains a bottleneck for software and cognitive radio
receivers. However, the performance of the TIΣΔ architecture is
limited by the unavoidable gain and offset mismatches resulting
from the manufacturing process. This paper presents a novel digital
calibration method to compensate the gain and offset mismatch
effect. The proposed method takes advantage of the reconstruction
digital signal processing on each channel and requires only few logic
components for implementation. The run time calibration is estimated
to 10 and 15 clock cycles for offset cancellation and gain mismatch
calibration respectively.
Abstract: In this paper, we present a novel approach to accurately
detect text regions including shop name in signboard images with
complex background for mobile system applications. The proposed
method is based on the combination of text detection using edge
profile and region segmentation using fuzzy c-means method. In the
first step, we perform an elaborate canny edge operator to extract all
possible object edges. Then, edge profile analysis with vertical and
horizontal direction is performed on these edge pixels to detect
potential text region existing shop name in a signboard. The edge
profile and geometrical characteristics of each object contour are
carefully examined to construct candidate text regions and classify the
main text region from background. Finally, the fuzzy c-means
algorithm is performed to segment and detected binarize text region.
Experimental results show that our proposed method is robust in text
detection with respect to different character size and color and can
provide reliable text binarization result.
Abstract: Since 2004, we have been developing an in-situ storage image sensor (ISIS) that captures more than 100 consecutive images at a frame rate of 10 Mfps with ultra-high sensitivity as well as the video camera for use with this ISIS. Currently, basic research is continuing in an attempt to increase the frame rate up to 100 Mfps and above. In order to suppress electro-magnetic noise at such high frequency, a digital-noiseless imaging transfer scheme has been developed utilizing solely sinusoidal driving voltages. This paper presents highly efficient-yet-accurate expressions to estimate attenuation as well as phase delay of driving voltages through RC networks of an ultra-high-speed image sensor. Elmore metric for a fundamental RC chain is employed as the first-order approximation. By application of dimensional analysis to SPICE data, we found a simple expression that significantly improves the accuracy of the approximation. Similarly, another simple closed-form model to estimate phase delay through fundamental RC networks is also obtained. Estimation error of both expressions is much less than previous works, only less 2% for most of the cases . The framework of this analysis can be extended to address similar issues of other VLSI structures.
Abstract: In this paper we propose a new traffic simulation
package, TDMSim, which supports both macroscopic and
microscopic simulation on free-flowing and regulated traffic systems.
Both simulators are based on travel demands, which specify the
numbers of vehicles departing from origins to arrive at different
destinations. The microscopic simulator implements the carfollowing
model given the pre-defined routes of the vehicles but also
supports the rerouting of vehicles. We also propose a macroscopic
simulator which is built in integration with the microscopic simulator
to allow the simulation to be scaled for larger networks without
sacrificing the precision achievable through the microscopic
simulator. The macroscopic simulator also enables the reuse of
previous simulation results when simulating traffic on the same
networks at later time. Validations have been conducted to show the
correctness of both simulators.
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: Presented herein is an assessment of current nonlinear
static procedures (NSPs) for seismic evaluation of bucklingrestrained
braced frames (BRBFs) which have become a favorable
lateral-force resisting system for earthquake resistant buildings. The
bias and accuracy of modal, improved modal pushover analysis
(MPA, IMPA) and mass proportional pushover (MPP) procedures
are comparatively investigated when they are applied to BRBF
buildings subjected to two sets of strong ground motions. The
assessment is based on a comparison of seismic displacement
demands such as target roof displacements, peak floor/roof
displacements and inter-story drifts. The NSP estimates are compared
to 'exact' results from nonlinear response history analysis (NLRHA).
The response statistics presented show that the MPP
procedure tends to significantly overestimate seismic demands of
lower stories of tall buildings considered in this study while MPA
and IMPA procedures provide reasonably accurate results in
estimating maximum inter-story drift over all stories of studied BRBF
systems.
Abstract: We present an explicit expression to estimate driving voltage attenuation through RC networks representation of an ultrahigh- speed image sensor. Elmore delay metric for a fundamental RC chain is employed as the first-order approximation. By application of dimensional analysis to SPICE simulation data, we found a simple expression that significantly improves the accuracy of the approximation. Estimation error of the resultant expression for uniform RC networks is less than 2%. Similarly, another simple closed-form model to estimate 50 % delay through fundamental RC networks is also derived with sufficient accuracy. The framework of this analysis can be extended to address delay or attenuation issues of other VLSI structures.
Abstract: In this work, we present a novel active learning approach
for learning a visual object detection system. Our system
is composed of an active learning mechanism as wrapper around
a sub-algorithm which implement an online boosting-based learning
object detector. In the core is a combination of a bootstrap procedure
and a semi automatic learning process based on the online boosting
procedure. The idea is to exploit the availability of classifier during
learning to automatically label training samples and increasingly
improves the classifier. This addresses the issue of reducing labeling
effort meanwhile obtain better performance. In addition, we propose
a verification process for further improvement of the classifier.
The idea is to allow re-update on seen data during learning for
stabilizing the detector. The main contribution of this empirical study
is a demonstration that active learning based on an online boosting
approach trained in this manner can achieve results comparable or
even outperform a framework trained in conventional manner using
much more labeling effort. Empirical experiments on challenging data
set for specific object deteciton problems show the effectiveness of
our approach.
Abstract: Distributed denial-of-service (DDoS) attacks pose a
serious threat to network security. There have been a lot of
methodologies and tools devised to detect DDoS attacks and reduce
the damage they cause. Still, most of the methods cannot
simultaneously achieve (1) efficient detection with a small number of
false alarms and (2) real-time transfer of packets. Here, we introduce
a method for proactive detection of DDoS attacks, by classifying the
network status, to be utilized in the detection stage of the proposed
anti-DDoS framework. Initially, we analyse the DDoS architecture
and obtain details of its phases. Then, we investigate the procedures
of DDoS attacks and select variables based on these features. Finally,
we apply the k-nearest neighbour (k-NN) method to classify the
network status into each phase of DDoS attack. The simulation result
showed that each phase of the attack scenario is classified well and
we could detect DDoS attack in the early stage.
Abstract: Project selection problems on management
information system (MIS) are often considered a multi-criteria
decision-making (MCDM) for a solving method. These problems
contain two aspects, such as interdependencies among criteria and
candidate projects and qualitative and quantitative factors of projects.
However, most existing methods reported in literature consider these
aspects separately even though these two aspects are simultaneously
incorporated. For this reason, we proposed a hybrid method using
analytic network process (ANP) and fuzzy logic in order to represent
both aspects. We then propose a goal programming model to conduct
an optimization for the project selection problems interpreted by a
hybrid concept. Finally, a numerical example is conducted as
verification purposes.
Abstract: Polymer melt compressibility and mold surface roughness, which are generally ignored during the filling stage of the conventional injection molding, may become increasingly significant in micro injection molding where the parts become smaller. By employing the 2.5D generalized Hele-Shaw model, we presented here the effects of polymer compressibility and mold surface roughness on mold-filling in a micro-thickness cavity. To elucidate the effects of surface roughness, numerical investigations were conducted using a cavity flat plate which has two halves with different surface roughness. This allows the comparison of flow field on two different halves under identical processing conditions but with different roughness. Results show that polymer compressibility and mold surface roughness have effects on mold filling in micro injection molding. There is in shrinkage reduction as the density is increased due to polymer melt compressibility during the filling stage.
Abstract: In this study, numerical simulations on laminar flow in
sinusoidal wavy shaped tubes were conducted for mean Reynolds
number of 250, which is in the range of physiological flow-rate and
investigated flow structures, pressure distribution and particle
trajectories both in steady and periodic inflow conditions. For
extensive comparisons, various wave lengths and amplitudes of sine
function for geometry of tube models were employed. The results
showed that small amplitude secondary curvature has significant
influence on the nature of flow patterns and particle mixing
mechanism. This implies that characterizing accurate geometry is
essential in accurate predicting of in vivo hemodynamics and may
motivate further study on any possibility of reflection of secondary
flow on vascular remodeling and pathophysiology.
Abstract: The study was performed to evaluate the effect of Sgirdling,
fruit thinning plus bagging with 2,4-D application, fruit
thinning plus bagging on growth and quality of wax apple fruit.
Girdling was applied three week before flowering. The 2,4-D was
sprayed at the small bud and petal fall stage. The effect of all
treatments on fruit growth was measured weekly. The physical and
biochemical quality characteristics of the fruits were recorded. The
results showed that no significant effect on number of bud among
treatments. S-girdling, 2,4-D application produced the lowest bud
drop, fruit drop compared to untreated control. Moreover, S-girdling
enhanced faster fruit growth producing the best final fruit length and
diameter than the control treatment. It was also observed that Sgirdling
greatly increased fruit set, fruit weight as well as total
soluble solid, reduced fruit crack, and titratable acidity. In
conclusion, S-girdling had a distinctive and significant effect on most
of the fruit quality characteristics assessed. Application 2,4-D was
also recommended as the industry norm to increase fruit set, and fruit
quality in wax apple.
Abstract: In order to explore the relationship of promotion activities, destination attribute and destination image of Vietnam and find possible solutions, this study uses decision system analysis (DSA) method to develop flowcharts based on three rounds of expert interviews. The interviews were conducted with the experts who were confirmed to directly participate or influence on the decision making that drives the promotion of Vietnam tourism process. This study identifies three models and describes specific decisions on promotion activities, destination attributes and destination images. This study finally derives a general model for promoting the Tourism Industrial Service Network (TISN) in Vietnam. This study finds that the coordination with all sectors and industries of tourism to facilitate favorable condition and improving destination attributes in linking with the efficient promotion activities is highly recommended in order to make visitors satisfied and improve the destination image.
Abstract: In this paper, we represent protein structure by using
graph. A protein structure database will become a graph database.
Each graph is represented by a spectral vector. We use Jacobi
rotation algorithm to calculate the eigenvalues of the normalized
Laplacian representation of adjacency matrix of graph. To measure
the similarity between two graphs, we calculate the Euclidean
distance between two graph spectral vectors. To cluster the graphs,
we use M-tree with the Euclidean distance to cluster spectral vectors.
Besides, M-tree can be used for graph searching in graph database.
Our proposal method was tested with graph database of 100 graphs
representing 100 protein structures downloaded from Protein Data
Bank (PDB) and we compare the result with the SCOP hierarchical
structure.
Abstract: To solve the problem of multisensor data fusion under
non-Gaussian channel noise. The advanced M-estimates are known
to be robust solution while trading off some accuracy. In order to
improve the estimation accuracy while still maintaining the equivalent
robustness, a two-stage robust fusion algorithm is proposed using
preliminary rejection of outliers then an optimal linear fusion. The
numerical experiments show that the proposed algorithm is equivalent
to the M-estimates in the case of uncorrelated local estimates and
significantly outperforms the M-estimates when local estimates are
correlated.
Abstract: A new deployment of the multiple criteria decision
making (MCDM) techniques: the Simple Additive Weighting
(SAW), and the Technique for Order Preference by Similarity to
Ideal Solution (TOPSIS) for portfolio allocation, is demonstrated in
this paper. Rather than exclusive reference to mean and variance as in
the traditional mean-variance method, the criteria used in this
demonstration are the first four moments of the portfolio distribution.
Each asset is evaluated based on its marginal impacts to portfolio
higher moments that are characterized by trapezoidal fuzzy numbers.
Then centroid-based defuzzification is applied to convert fuzzy
numbers to the crisp numbers by which SAW and TOPSIS can be
deployed. Experimental results suggest the similar efficiency of these
MCDM approaches to selecting dominant assets for an optimal
portfolio under higher moments. The proposed approaches allow
investors flexibly adjust their risk preferences regarding higher
moments via different schemes adapting to various (from
conservative to risky) kinds of investors. The other significant
advantage is that, compared to the mean-variance analysis, the
portfolio weights obtained by SAW and TOPSIS are consistently
well-diversified.
Abstract: In this paper, we propose a new model of English-
Vietnamese bilingual Information Retrieval system. Although there
are so many CLIR systems had been researched and built, the accuracy of searching results in different languages that the CLIR
system supports still need to improve, especially in finding bilingual documents. The problems identified in this paper are the limitation of
machine translation-s result and the extra large collections of document to be found. So we try to establish a different model to overcome these problems.
Abstract: The study was carried out to evaluated effect of S-gridling on fruit growth and quality of wax apple. The study was laid in Random completed block design with four replicated. Four treatment were applied as follows: S-girdling, fruit thinning plus bagging with 2,4-D sprayed, fruit thinning plus bagging and the control treatment. 2,4D was sprayed at the small bud and petal fall stage. Girdling was applied three week before flowering. The effect of all treatments on fruit growth was measured weekly. Number of flower, fruit set, fruit drop, fruit crack, and fruit quality were recorded. The result indicated that S-girdling, 2,4D application produced the lowest bud drop, fruit drop compared to untreated control. S-girdling improved faster fruit growth producing the best final fruit length and diameter compared to untreated control. S-girdling also markedly enhanced fruit set, fruit weight, and total soluble solid, reduced fruit crack, titratable acidity. On the other hand, it was noticed that with 2,4-D application also increased the fruit growth rate, improved physiological and biochemical characters of fruit than control treatment. It was concluded that S-girdling was recommended as the industry norm to increase fruit set, fruit quality in wax apple. 2,4D application had a distinctive and significant effect on most of the fruit quality characteristics assessed.