Abstract: Random and natural textures classification is still
one of the biggest challenges in the field of image processing and
pattern recognition. In this paper, texture feature extraction using
Slant Hadamard Transform was studied and compared to other
signal processing-based texture classification schemes. A
parametric SHT was also introduced and employed for natural
textures feature extraction. We showed that a subtly modified
parametric SHT can outperform ordinary Walsh-Hadamard
transform and discrete cosine transform. Experiments were carried
out on a subset of Vistex random natural texture images using a
kNN classifier.
Abstract: The field of polymeric biomaterials is very important
from the socio-economical viewpoint. Synthetic carbohydrate
polymers are being increasingly investigated as biodegradable,
biocompatible and biorenewable materials. The aim of this study was
to synthesize and characterize some derivatives based on D-mannose.
D-mannose was chemically modified to obtain 1-O-allyl-2,3:5,6-di-
O-isopropylidene-D-mannofuranose and 1-O-(2-,3--epoxy-propyl)-
2,3:5,6-di-O-isopropylidene-D-mannofuranose.
The chemical structure of the resulting compounds was
characterized by FT-IR and NMR spectroscopy, and by HPLC-MS.
Abstract: The paper proposes and validates a new method of solving instances of the vehicle routing problem (VRP). The approach is based on a multiple agent system paradigm. The paper contains the VRP formulation, an overview of the multiple agent environment used and a description of the proposed implementation. The approach is validated experimentally. The experiment plan and the discussion of experiment results follow.
Abstract: The purposes of this research are 1) to study English language learning strategies used by the fourth-year students majoring in English and Business English, 2) to study the English language learning strategies which have an affect on English learning achievement, and 3) to compare the English language learning strategies used by the students majoring in English and Business English. The population and sampling comprise of 139 university students of the Suan Sunandha Rajabhat University. Research instruments are language learning strategies questionnaire which was constructed by the researcher and improved on by three experts and the transcripts that show the results of English learning achievement. The questionnaire includes 1) Language Practice Strategy 2)Memory Strategy 3) Communication Strategy 4)Making an Intelligent Guess or Compensation Strategy 5) Self-discipline in Learning Management Strategy 6) Affective Strategy 7)Self-Monitoring Strategy 8) Self-studySkill Strategy. Statistics used in the study are mean, standard deviation, T-test and One Way ANOVA, Pearson product moment correlation coefficient and Regression Analysis. The results of the findings reveal that the English language learning strategies most frequently used by the students are affective strategy, making an intelligent guess or compensation strategy, self-studyskill strategy and self-monitoring strategy respectively. The aspect of making an intelligent guess or compensation strategy had the most significant affect on English learning achievement. It is found that the English language learning strategies mostly used by the Business English major students and moderately used by the English major students. Their language practice strategies uses were significantly different at the 0.05 level and their communication strategies uses were significantly different at the 0.01 level. In addition, it is found that the poor students and the fair ones most frequently used affective strategy while the good ones most frequently used making an intelligent guess or compensation strategy. KeywordsEnglish language, language learning strategies, English learning achievement, and students majoring in English, Business English. Pranee Pathomchaiwat is an Assistant Professor in Business English Program, Suan Sunandha Rajabhat University, Bangkok, Thailand (e-mail: [email protected]).
Abstract: Thermoacoustic instabilities in combustors have
remained a topic of investigation for over a few decades due to the
challenges it posses to the operation of low emission gas turbines.
For combustors burning liquid fuel, understanding the cause-andeffect
relationship between spray combustion dynamics and
thermoacoustic oscillations is imperative for the successful
development of any control methodology for its mitigation. The
paper presents some very unique operating characteristics of a
kerosene-fueled diffusion type combustor undergoing limit-cycle
oscillations. Combustor stability limits were mapped using three
different-sized injectors. The results show that combustor instability
depends on the characteristics of the fuel spray. A simple analytic
analysis is also reported in support of a plausible explanation for the
unique combustor behavior. The study indicates that high amplitude
acoustic pressure in the combustor may cause secondary breakdown
of fuel droplets resulting in premixed pre-vaporized type burning of
the diffusion type combustor.
Abstract: Within dental-guided surgery, there has been a lack
of analytical methods for optimizing the treatment of the
rehabilitation concepts regarding geometrical variation. The purpose
of this study is to find the source of the greatest geometrical variation
contributor and sensitivity contributor with the help of virtual
variation simulation of a dental drill- and implant-guided surgery
process using a methodical approach. It is believed that lower
geometrical variation will lead to better patient security and higher
quality of dental drill- and implant-guided surgeries. It was found
that the origin of the greatest contributor to the most variation, and
hence where the foci should be set, in order to minimize geometrical
variation was in the assembly category (surgery). This was also the
category that was the most sensitive for geometrical variation.
Abstract: Near-infrared (NIR) spectroscopy is a widely used
method for material identification for laboratory and industrial applications.
While standard spectrometers only allow measurements at
one sampling point at a time, NIR Spectral Imaging techniques can
measure, in real-time, both the size and shape of an object as well as
identify the material the object is made of. The online classification
and sorting of recovered paper with NIR Spectral Imaging (SI)
is used with success in the paper recycling industry throughout
Europe. Recently, the globalisation of the recycling material streams
caused that water-based flexographic-printed newspapers mainly from
UK and Italy appear also in central Europe. These flexo-printed
newspapers are not sufficiently de-inkable with the standard de-inking
process originally developed for offset-printed paper. This de-inking
process removes the ink from recovered paper and is the fundamental
processing step to produce high-quality paper from recovered paper.
Thus, the flexo-printed newspapers are a growing problem for the
recycling industry as they reduce the quality of the produced paper
if their amount exceeds a certain limit within the recovered paper
material.
This paper presents the results of a research project for the
development of an automated entry inspection system for recovered
paper that was jointly conducted by CTR AG (Austria) and PTS
Papiertechnische Stiftung (Germany). Within the project an NIR
SI prototype for the identification of flexo-printed newspaper has
been developed. The prototype can identify and sort out flexoprinted
newspapers in real-time and achieves a detection accuracy
for flexo-printed newspaper of over 95%. NIR SI, the technology the
prototype is based on, allows the development of inspection systems
for incoming goods in a paper production facility as well as industrial
sorting systems for recovered paper in the recycling industry in the
near future.
Abstract: Many electronic voting systems, classified mainly as homomorphic cryptography based, mix-net based and blind signature based, appear after the eighties when zero knowledge proofs were introduced. The common ground for all these three systems is that none of them works without real time cryptologic calculations that should be held on a server. As far as known, the agent-based approach has not been used in a secure electronic voting system. In this study, an agent-based electronic voting schema, which does not contain real time calculations on the server side, is proposed. Conventional cryptologic methods are used in the proposed schema and some of the requirements of an electronic voting system are constructed within the schema. The schema seems quite secure if the used cryptologic methods and agents are secure. In this paper, proposed schema will be explained and compared with already known electronic voting systems.
Abstract: A new estimator for evolutionary spectrum (ES) based
on short time Fourier transform (STFT) and modified group delay
function (MGDF) by signal decomposition (SD) is proposed. The
STFT due to its built-in averaging, suppresses the cross terms and the
MGDF preserves the frequency resolution of the rectangular window
with the reduction in the Gibbs ripple. The present work overcomes
the magnitude distortion observed in multi-component non-stationary
signals with STFT and MGDF estimation of ES using SD. The SD is
achieved either through discrete cosine transform based harmonic
wavelet transform (DCTHWT) or perfect reconstruction filter banks
(PRFB). The MGDF also improves the signal to noise ratio by
removing associated noise. The performance of the present method is
illustrated for cross chirp and frequency shift keying (FSK) signals,
which indicates that its performance is better than STFT-MGDF
(STFT-GD) alone. Further its noise immunity is better than STFT.
The SD based methods, however cannot bring out the frequency
transition path from band to band clearly, as there will be gap in the
contour plot at the transition. The PRFB based STFT-SD shows good
performance than DCTHWT decomposition method for STFT-GD.
Abstract: Flow around a flat tube is studied numerically. Reynolds number is defined base on equivalent circular tube and it is varied in range of 100 to 300. Equations are solved by using finite volume method and results are presented in form of drag and lift coefficient. Results show that drag coefficient of flat tube is up to 66% lower than circular tube with equivalent diameter. In addition, by increasing l/D from 1 to 2, the drag coefficient of flat tube is decreased about 14-27%.
Abstract: Authentication plays a vital role in many secure
systems. Most of these systems require user to log in with his or her
secret password or pass phrase before entering it. This is to ensure all
the valuables information is kept confidential guaranteeing also its
integrity and availability. However, to achieve this goal, users are
required to memorize high entropy passwords or pass phrases.
Unfortunately, this sometimes causes difficulty for user to remember
meaningless strings of data. This paper presents a new scheme which
assigns a weight to each personal question given to the user in
revealing the encrypted secrets or password. Concentration of this
scheme is to offer fault tolerance to users by allowing them to forget
the specific password to a subset of questions and still recover the
secret and achieve successful authentication. Comparison on level of
security for weight-based and weightless secret recovery scheme is
also discussed. The paper concludes with the few areas that requires
more investigation in this research.
Abstract: This paper explores the social and political imperatives in the sphere of public policy relating to social justice. In India, the colonial legacy and post-colonial social and political pressures sustained the appropriation of 'caste' category in allocating public resources to the backward class of citizens. For several reasons, 'economic' category could not be placed in allocating resources. This paper examines the reasons behind the deliberative exercises and formulating policies and seeks an alternative framework in realizing social justice in terms of a unified category. This attempt can be viewed as a reconciliation of traditional and modern values for a viable alternative in public policy making.
Abstract: Segmentation of a color image composed of different
kinds of regions can be a hard problem, namely to compute for an
exact texture fields. The decision of the optimum number of
segmentation areas in an image when it contains similar and/or un
stationary texture fields. A novel neighborhood-based segmentation
approach is proposed. A genetic algorithm is used in the proposed
segment-pass optimization process. In this pass, an energy function,
which is defined based on Markov Random Fields, is minimized. In
this paper we use an adaptive threshold estimation method for image
thresholding in the wavelet domain based on the generalized
Gaussian distribution (GGD) modeling of sub band coefficients. This
method called Normal Shrink is computationally more efficient and
adaptive because the parameters required for estimating the threshold
depend on sub band data energy that used in the pre-stage of
segmentation. A quad tree is employed to implement the multi
resolution framework, which enables the use of different strategies at
different resolution levels, and hence, the computation can be
accelerated. The experimental results using the proposed
segmentation approach are very encouraging.
Abstract: TiO2 nanoparticles were synthesized by hydrothermal
method at 180°C from TiOSO4 aqueous solution with1m/l
concentration. The obtained products were coated with silica by
means of a seeded polymerization technique for a coating time of
1440 minutes to obtain well defined TiO2@SiO2 core-shell structure.
The uncoated and coated nanoparticles were characterized by using
X-Ray diffraction technique (XRD), Fourier Transform Infrared
Spectroscopy (FT-IR) to study their physico-chemical properties.
Evidence from XRD and FTIR results show that SiO2 is
homogenously coated on the surface of titania particles. FTIR spectra
show that there exists an interaction between TiO2 and SiO2 and
results in the formation of Ti-O-Si chemical bonds at the interface of
TiO2 particles and SiO2 coating layer. The non linear optical limiting
properties of TiO2 and TiO2@SiO2 nanoparticles dispersed in
ethylene glycol were studied at 532nm using 5ns Nd:YAG laser
pulses. Three-photon absorption is responsible for optical limiting
characteristics in these nanoparticles and it is seen that the optical
nonlinearity is enhanced in core-shell structures when compared with
single counterparts. This effective three-photon type absorption at
this wavelength, is of potential application in fabricating optical
limiting devices.
Abstract: A model based fault detection and diagnosis
technique for DC motor is proposed in this paper. Fault detection
using Kalman filter and its different variants are compared. Only
incipient faults are considered for the study. The Kalman Filter
iterations and all the related computations required for fault detection
and fault confirmation are presented. A second order linear state
space model of DC motor is used for this work. A comparative
assessment of the estimates computed from four different observers
and their relative performance is evaluated.
Abstract: Team efficacy beliefs show promise in enhancing
team performance. Using a model-based quantitative research design,
we investigated the antecedents and performance consequences of
generalized team efficacy (potency) in a sample of 56 capital projects
executed by 15 Fortune 500 companies in the process industries.
Empirical analysis of our field survey identified that generalized
team efficacy beliefs were positively associated with an objective
measure of project cost performance. Regression analysis revealed
that team competence, empowering leadership, and performance
feedback all predicted generalized team efficacy beliefs. Tests of
mediation revealed that generalized team efficacy fully mediated
between these three inputs and project cost performance.
Abstract: Megalopolis is a group of densely populated metropolitan areas that combine to form an urban complex. Since China introduced the economic reforms in late 1970s, the Chinese urban system has experienced unprecedented growth. The process of urbanisation prevailed in the 1980s, and the process of predominantly large city growth appeared to continue through 1990s and 2000s. In this study, the magnitude and pattern of urbanisation in China during 1990s were examined using remotely sensed imagery acquired by TM/ETM+ sensor onboard the Landsat satellites. The development of megalopolis areas in China was also studied based on the GIS analysis of the increases of urban and built-up area from 1990 to 2000. The analysis suggests that in the traditional agricultural zones in China, e.g., Huang-Huai-Hai Plains, Changjiang River Delta, Pearl River Delta and Sichuan Basin, the urban and built-up areas increased by 1.76 million hectares, of which 0.82 million hectares are expansion of urban areas, an increase of 24.78% compared with 1990 at the national scale. The Yellow River Delta, Changjiang River Delta and Pearl River Delta also saw an increase of urban and built-up area by 63.9%, 66.2% and 83.0% respectively. As a result, three major megalopolises were developed in China: the Guangzhou-Shenzhen-Hong Kong- Macau (Pearl River Delta: PRD) megalopolis area, the Shanghai- Nanjing-Hangzhou (Changjiang River Delta: CRD) megalopolis area and the Beijing-Tianjing-Tangshan-Qinhuangdao (Yellow River Delta-Bohai Sea Ring: YRD) megalopolis area. The relationship between the processed of megalopolisation and the inter-provincial population flow was also explored in the context of social-economic and transport infrastructure development in Post-reform China.
Abstract: The objective of this paper is to develop a neural
network-based residual generator to detect the fault in the actuators
for a specific communication satellite in its attitude control system
(ACS). First, a dynamic multilayer perceptron network with dynamic
neurons is used, those neurons correspond a second order linear
Infinite Impulse Response (IIR) filter and a nonlinear activation
function with adjustable parameters. Second, the parameters from the
network are adjusted to minimize a performance index specified by
the output estimated error, with the given input-output data collected
from the specific ACS. Then, the proposed dynamic neural network
is trained and applied for detecting the faults injected to the wheel,
which is the main actuator in the normal mode for the communication
satellite. Then the performance and capabilities of the proposed
network were tested and compared with a conventional model-based
observer residual, showing the differences between these two
methods, and indicating the benefit of the proposed algorithm to
know the real status of the momentum wheel. Finally, the application
of the methods in a satellite ground station is discussed.
Abstract: CEMTool is a command style design and analyzing
package for scientific and technological algorithm and a matrix based
computation language. In this paper, we present new 2D & 3D
finite element method (FEM) packages for CEMTool. We discuss
the detailed structures and the important features of pre-processor,
solver, and post-processor of CEMTool 2D & 3D FEM packages. In
contrast to the existing MATLAB PDE Toolbox, our proposed FEM
packages can deal with the combination of the reserved words. Also,
we can control the mesh in a very effective way. With the introduction
of new mesh generation algorithm and fast solving technique, our
FEM packages can guarantee the shorter computational time than
MATLAB PDE Toolbox. Consequently, with our new FEM packages,
we can overcome some disadvantages or limitations of the existing
MATLAB PDE Toolbox.
Abstract: The paper proposes a unified model for multimedia data retrieval which includes data representatives, content representatives, index structure, and search algorithms. The multimedia data are defined as k-dimensional signals indexed in a multidimensional k-tree structure. The benefits of using the k-tree unified model were demonstrated by running the data retrieval application on a six networked nodes test bed cluster. The tests were performed with two retrieval algorithms, one that allows parallel searching using a single feature, the second that performs a weighted cascade search for multiple features querying. The experiments show a significant reduction of retrieval time while maintaining the quality of results.