Abstract: In this paper, we propose a method to extract the road
signs. Firstly, the grabbed image is converted into the HSV color space
to detect the road signs. Secondly, the morphological operations are
used to reduce noise. Finally, extract the road sign using the geometric
property. The feature extraction of road sign is done by using the color
information. The proposed method has been tested for the real
situations. From the experimental results, it is seen that the proposed
method can extract the road sign features effectively.
Abstract: The Major Depressive Disorder has been a burden of
medical expense in Taiwan as well as the situation around the world.
Major Depressive Disorder can be defined into different categories by
previous human activities. According to machine learning, we can
classify emotion in correct textual language in advance. It can help
medical diagnosis to recognize the variance in Major Depressive
Disorder automatically. Association language incremental is the
characteristic and relationship that can discovery words in sentence.
There is an overlapping-category problem for classification. In this
paper, we would like to improve the performance in classification in
principle of no overlapping-category problems. We present an
approach that to discovery words in sentence and it can find in high
frequency in the same time and can-t overlap in each category, called
Association Language Features by its Category (ALFC).
Experimental results show that ALFC distinguish well in Major
Depressive Disorder and have better performance. We also compare
the approach with baseline and mutual information that use single
words alone or correlation measure.
Abstract: How to effectively allocate system resource to process
the Client request by Gateway servers is a challenging problem. In
this paper, we propose an improved scheme for autonomous
performance of Gateway servers under highly dynamic traffic loads.
We devise a methodology to calculate Queue Length and Waiting
Time utilizing Gateway Server information to reduce response time
variance in presence of bursty traffic. The most widespread
contemplation is performance, because Gateway Servers must offer
cost-effective and high-availability services in the elongated period,
thus they have to be scaled to meet the expected load. Performance
measurements can be the base for performance modeling and
prediction. With the help of performance models, the performance
metrics (like buffer estimation, waiting time) can be determined at
the development process. This paper describes the possible queue
models those can be applied in the estimation of queue length to
estimate the final value of the memory size. Both simulation and
experimental studies using synthesized workloads and analysis of
real-world Gateway Servers demonstrate the effectiveness of the
proposed system.
Abstract: This research investigates the effects of the opening
shape and location on the structural behavior of reinforced concrete
deep beam with openings, while keeping the opening size unchanged.
The software ANSYS 12.1 is used to handle the nonlinear finite
element analysis. The ultimate strength of reinforced concrete deep
beam with opening obtained by ANSYS 12.1 shows fair agreement
with the experimental results, with a difference of no more than 20%. The present work concludes that the opening location has much more effect on the structural strength than the opening shape. It was
concluded that placing the openings near the upper corners of the
deep beam may double the strength, and the use of a rectangular
narrow opening, with the long sides in the horizontal direction, can save up to 40% of structural strength of the deep beam.
Abstract: In order to investigate water deficit stress on 24 of
soybean (Glycine Max. L) cultivars and lines in temperate climate, an
experiment was conducted in Iran Seed and Plant Improvement
Institute. Stress levels were irrigation after evaporation of 50, 100,
150 mm water from pan, class A. Randomized Completely Block
Design was arranged for each stress levels. Some traits such as, node
number, plant height, pod number per area, grain number per pod,
grain number per area, 1000 grains weight, grain yield and harvest
index were measured. Results showed that water deficit stress had
significant effect on node number, plant height, pod number per area,
grain number per pod, grain number per area, 1000 grains weight and
harvest index. Also all of agronomic traits except harvest index
influenced significantly by cultivars and lines. The least and most
grain yield was belonged to Ronak X Williams and M41 x Clark
respectively.
Abstract: A wireless sensor network with a large number of tiny sensor nodes can be used as an effective tool for gathering data in various situations. One of the major issues in wireless sensor networks is developing an energy-efficient routing protocol which has a significant impact on the overall lifetime of the sensor network. In this paper, we propose a novel hierarchical with static clustering routing protocol called Energy-Efficient Protocol with Static Clustering (EEPSC). EEPSC, partitions the network into static clusters, eliminates the overhead of dynamic clustering and utilizes temporary-cluster-heads to distribute the energy load among high-power sensor nodes; thus extends network lifetime. We have conducted simulation-based evaluations to compare the performance of EEPSC against Low-Energy Adaptive Clustering Hierarchy (LEACH). Our experiment results show that EEPSC outperforms LEACH in terms of network lifetime and power consumption minimization.
Abstract: Weather systems use enormously complex
combinations of numerical tools for study and forecasting.
Unfortunately, due to phenomena in the world climate, such
as the greenhouse effect, classical models may become
insufficient mostly because they lack adaptation. Therefore,
the weather forecast problem is matched for heuristic
approaches, such as Evolutionary Algorithms.
Experimentation with heuristic methods like Particle Swarm
Optimization (PSO) algorithm can lead to the development of
new insights or promising models that can be fine tuned with
more focused techniques. This paper describes a PSO
approach for analysis and prediction of data and provides
experimental results of the aforementioned method on realworld
meteorological time series.
Abstract: In this paper, an artificial intelligent technique for
robust digital image watermarking in multiwavelet domain is
proposed. The embedding technique is based on the quantization
index modulation technique and the watermark extraction process
does not require the original image. We have developed an
optimization technique using the genetic algorithms to search for
optimal quantization steps to improve the quality of watermarked
image and robustness of the watermark. In addition, we construct a
prediction model based on image moments and back propagation
neural network to correct an attacked image geometrically before the
watermark extraction process begins. The experimental results show
that the proposed watermarking algorithm yields watermarked image
with good imperceptibility and very robust watermark against various
image processing attacks.
Abstract: This work presents a fusion of Log Gabor Wavelet
(LGW) and Maximum a Posteriori (MAP) estimator as a speech
enhancement tool for acoustical background noise reduction. The
probability density function (pdf) of the speech spectral amplitude is
approximated by a Generalized Laplacian Distribution (GLD).
Compared to earlier estimators the proposed method estimates the
underlying statistical model more accurately by appropriately
choosing the model parameters of GLD. Experimental results show
that the proposed estimator yields a higher improvement in
Segmental Signal-to-Noise Ratio (S-SNR) and lower Log-Spectral
Distortion (LSD) in two different noisy environments compared to
other estimators.
Abstract: This present paper proposes the modified Elastic Strip
method for mobile robot to avoid obstacles with a real time system in
an uncertain environment. The method deals with the problem of
robot in driving from an initial position to a target position based on
elastic force and potential field force. To avoid the obstacles, the
robot has to modify the trajectory based on signal received from the
sensor system in the sampling times. It was evident that with the
combination of Modification Elastic strip and Pseudomedian filter to
process the nonlinear data from sensor uncertainties in the data
received from the sensor system can be reduced. The simulations and
experiments of these methods were carried out.
Abstract: Radial flow reactor was focused for large scale
methanol synthesis and in which the heat transfer type was cross-flow.
The effects of operating conditions including the reactor inlet air
temperature, the heating pipe temperature and the air flow rate on the
cross-flow heat transfer was investigated and the results showed that
the temperature profile of the area in front of the heating pipe was
slightly affected by all the operating conditions. The main area whose
temperature profile was influenced was the area behind the heating
pipe. The heat transfer direction according to the air flow directions. In
order to provide the basis for radial flow reactor design calculation, the
dimensionless number group method was used for data fitting of the
bed effective thermal conductivity and the wall heat transfer
coefficient which was calculated by the mathematical model with the
product of Reynolds number and Prandtl number. The comparison of
experimental data and calculated value showed that the calculated
value fit the experimental data very well and the formulas could be
used for reactor designing calculation.
Abstract: This paper proposes a new approach to offer a private
cloud service in HPC clusters. In particular, our approach relies on
automatically scheduling users- customized environment request as a
normal job in batch system. After finishing virtualization request jobs,
those guest operating systems will dismiss so that compute nodes will
be released again for computing. We present initial work on the
innovative integration of HPC batch system and virtualization tools
that aims at coexistence such that they suffice for meeting the
minimizing interference required by a traditional HPC cluster. Given
the design of initial infrastructure, the proposed effort has the potential
to positively impact on synergy model. The results from the
experiment concluded that goal for provisioning customized cluster
environment indeed can be fulfilled by using virtual machines, and
efficiency can be improved with proper setup and arrangements.
Abstract: The pavement constructions on soft and expansive soils are not durable and unable to sustain heavy traffic loading. As a result, pavement failures and settlement problems will occur very often even under light traffic loading due to cyclic and rolling effects. Geotechnical engineers have dwelled deeply into this matter, and adopt various methods to improve the engineering characteristics of soft fine-grained soils and expansive soils. The problematic soils are either replaced by good and better quality material or treated by using chemical stabilization with various binding materials. Increased the strength and durability are also the part of the sustainability drive to reduce the environment footprint of the built environment by the efficient use of resources and waste recycle materials. This paper presents a series of laboratory tests and evaluates the effect of cement and fly ash on the strength and drainage characteristics of soil in Miri. The tests were performed at different percentages of cement and fly ash by dry weight of soil. Additional tests were also performed on soils treated with the combinations of fly ash with cement and lime. The results of this study indicate an increase in unconfined compression strength and a decrease in hydraulic conductivity of the treated soil.
Abstract: Cerium-doped lanthanum bromide LaBr3:Ce(5%)
crystals are considered to be one of the most advanced scintillator
materials used in PET scanning, combining a high light yield, fast
decay time and excellent energy resolution. Apart from the correct
choice of scintillator, it is also important to optimise the detector
geometry, not least in terms of source-to-detector distance in order to
obtain reliable measurements and efficiency. In this study a
commercially available 25 mm x 25 mm BrilLanCeTM 380 LaBr3: Ce
(5%) detector was characterised in terms of its efficiency at varying
source-to-detector distances. Gamma-ray spectra of 22Na, 60Co, and
137Cs were separately acquired at distances of 5, 10, 15, and 20cm. As
a result of the change in solid angle subtended by the detector, the
geometric efficiency reduced in efficiency with increasing distance.
High efficiencies at low distances can cause pulse pile-up when
subsequent photons are detected before previously detected events
have decayed. To reduce this systematic error the source-to-detector
distance should be balanced between efficiency and pulse pile-up
suppression as otherwise pile-up corrections would need to be
necessary at short distances. In addition to the experimental
measurements Monte Carlo simulations have been carried out for the
same setup, allowing a comparison of results. The advantages and
disadvantages of each approach have been highlighted.
Abstract: The state-of-the-art Bag of Words model in Content-
Based Image Retrieval has been used for years but the relevance
feedback strategies for this model are not fully investigated. Inspired
from text retrieval, the Bag of Words model has the ability to use the
wealth of knowledge and practices available in text retrieval. We
study and experiment the relevance feedback model in text retrieval
for adapting it to image retrieval. The experiments show that the
techniques from text retrieval give good results for image retrieval
and that further improvements is possible.
Abstract: Recently, lots of researchers are attracted to retrieving
multimedia database by using some impression words and their values.
Ikezoe-s research is one of the representatives and uses eight pairs of
opposite impression words. We had modified its retrieval interface and
proposed '2D-RIB'. In '2D-RIB', after a retrieval person selects a
single basic music, the system visually shows some other music
around the basic one along relative position. He/she can select one of
them fitting to his/her intention, as a retrieval result. The purpose of
this paper is to improve his/her satisfaction level to the retrieval result
in 2D-RIB. One of our extensions is to define and introduce the
following two measures: 'melody goodness' and 'general acceptance'.
We implement them in different five combinations. According to an
evaluation experiment, both of these two measures can contribute to
the improvement. Another extension is three types of customization.
We have implemented them and clarified which customization is
effective.
Abstract: Images of human iris contain specular highlights due
to the reflective properties of the cornea. This corneal reflection
causes many errors not only in iris and pupil center estimation but
also to locate iris and pupil boundaries especially for methods that
use active contour. Each iris recognition system has four steps:
Segmentation, Normalization, Encoding and Matching. In order to
address the corneal reflection, a novel reflection removal method is
proposed in this paper. Comparative experiments of two existing
methods for reflection removal method are evaluated on CASIA iris
image databases V3. The experimental results reveal that the
proposed algorithm provides higher performance in reflection
removal.
Abstract: In this paper, we propose a Perceptually Optimized Embedded ZeroTree Image Coder (POEZIC) that introduces a perceptual weighting to wavelet transform coefficients prior to control SPIHT encoding algorithm in order to reach a targeted bit rate with a perceptual quality improvement with respect to the coding quality obtained using the SPIHT algorithm only. The paper also, introduces a new objective quality metric based on a Psychovisual model that integrates the properties of the HVS that plays an important role in our POEZIC quality assessment. Our POEZIC coder is based on a vision model that incorporates various masking effects of human visual system HVS perception. Thus, our coder weights the wavelet coefficients based on that model and attempts to increase the perceptual quality for a given bit rate and observation distance. The perceptual weights for all wavelet subbands are computed based on 1) luminance masking and Contrast masking, 2) the contrast sensitivity function CSF to achieve the perceptual decomposition weighting, 3) the Wavelet Error Sensitivity WES used to reduce the perceptual quantization errors. The new perceptually optimized codec has the same complexity as the original SPIHT techniques. However, the experiments results show that our coder demonstrates very good performance in terms of quality measurement.
Abstract: The mechanical quadrature methods for solving the boundary integral equations of the anisotropic Darcy-s equations with Dirichlet conditions in smooth domains are presented. By applying the collectively compact theory, we prove the convergence and stability of approximate solutions. The asymptotic expansions for the error show that the methods converge with the order O (h3), where h is the mesh size. Based on these analysis, extrapolation methods can be introduced to achieve a higher convergence rate O (h5). An a posterior asymptotic error representation is derived in order to construct self-adaptive algorithms. Finally, the numerical experiments show the efficiency of our methods.
Abstract: There are two common methodologies to verify
signatures: the functional approach and the parametric approach. This
paper presents a new approach for dynamic handwritten signature
verification (HSV) using the Neural Network with verification by the
Conjugate Gradient Neural Network (NN). It is yet another avenue in
the approach to HSV that is found to produce excellent results when
compared with other methods of dynamic. Experimental results show
the system is insensitive to the order of base-classifiers and gets a
high verification ratio.