Abstract: Image compression based on fractal coding is a lossy
compression method and normally used for gray level images range
and domain blocks in rectangular shape. Fractal based digital image
compression technique provide a large compression ratio and in this
paper, it is proposed using YUV colour space and the fractal theory
which is based on iterated transformation. Fractal geometry is mainly
applied in the current study towards colour image compression
coding. These colour images possesses correlations among the colour
components and hence high compression ratio can be achieved by
exploiting all these redundancies. The proposed method utilises the
self-similarity in the colour image as well as the cross-correlations
between them. Experimental results show that the greater
compression ratio can be achieved with large domain blocks but more
trade off in image quality is good to acceptable at less than 1 bit per
pixel.
Abstract: Behavioral aspects of experience such as will power
are rarely subjected to quantitative study owing to the numerous
complexities involved. Will is a phenomenon that has puzzled
humanity for a long time. It is a belief that will power of an individual
affects the success achieved by them in life. It is also thought that a
person endowed with great will power can overcome even the most
crippling setbacks in life while a person with a weak will cannot make
the most of life even the greatest assets. This study is an attempt
to subject the phenomena of will to the test of an artificial neural
network through a computational model. The claim being tested is
that will power of an individual largely determines success achieved
in life. It is proposed that data pertaining to success of individuals
be obtained from an experiment and the phenomenon of will be
incorporated into the model, through data generated recursively using
a relation between will and success characteristic to the model.
An artificial neural network trained using part of the data, could
subsequently be used to make predictions regarding data points in
the rest of the model. The procedure would be tried for different
models and the model where the networks predictions are found to
be in greatest agreement with the data would be selected; and used
for studying the relation between success and will.
Abstract: The exponential growth of social media arouses much
attention on public opinion information. The online forums, blogs,
micro blogs are proving to be extremely valuable resources and are
having bulk volume of information. However, most of the social
media data is unstructured and semi structured form. So that it is
more difficult to decipher automatically. Therefore, it is very much
essential to understand and analyze those data for making a right
decision. The online forums hotspot detection is a promising research
field in the web mining and it guides to motivate the user to take right
decision in right time. The proposed system consist of a novel
approach to detect a hotspot forum for any given time period. It uses
aging theory to find the hot terms and E-K-means for detecting the
hotspot forum. Experimental results demonstrate that the proposed
approach outperforms k-means for detecting the hotspot forums with
the improved accuracy.
Abstract: Ulexite (Na2O.2CaO.5B2O3.16H2O) is boron mineral
that is found in large quantities in the Turkey and world. In this
study, the dissolution of this mineral in the disodium hydrogen
phosphate solutions has been studied. Temperature, concentration,
stirring speed, solid liquid ratio and particle size were selected as
parameters. The experimental results were successfully correlated by
linear regression using Statistica program. Dissolution curves were
evaluated shrinking core models for solid-fluid systems. It was
observed that increase in the reaction temperature and decrease in the
solid/liquid ratio causes an increase the dissolution rate of ulexite.
The activation energy was found to be 63.4 kJ/mol. The leaching of
ulexite was controlled by chemical reaction.
Abstract: This paper is part of a study to develop robots for
farming. As such power requirement to operate equipment attach to
such robots become an important factor. Soil-tool interaction plays
major role in power consumption, thus predicting accurately the
forces which act on the blade during the farming is very important for
optimal designing of farm equipment. In this paper, a finite element
investigation for tillage tools and soil interaction is described by
using an inelastic constitutive material law for agriculture
application. A 3-dimensional (3D) nonlinear finite element analysis
(FEA) is developed to examine behavior of a blade with different
rake angles moving in a block of soil, and to estimate the blade force.
The soil model considered is an elastic-plastic with non-associated
Drucker-Prager material model. Special use of contact elements are
employed to consider connection between soil-blade and soil-soil
surfaces. The FEA results are compared with experimental ones,
which show good agreement in accurately predicting draft forces
developed on the blade when it moves through the soil. Also a very
good correlation was obtained between FEA results and analytical
results from classical soil mechanics theories for straight blades.
These comparisons verified the FEA model developed. For analyzing
complicated soil-tool interactions and for optimum design of blades,
this method will be useful.
Abstract: Non contact evaluation of the thickness of paint
coatings can be attempted by different destructive and nondestructive
methods such as cross-section microscopy, gravimetric mass
measurement, magnetic gauges, Eddy current, ultrasound or
terahertz. Infrared thermography is a nondestructive and non-invasive
method that can be envisaged as a useful tool to measure the surface
thickness variations by analyzing the temperature response. In this
paper, the thermal quadrupole method for two layered samples heated
up with a pulsed excitation is firstly used. By analyzing the thermal
responses as a function of thermal properties and thicknesses of both
layers, optimal parameters for the excitation source can be identified.
Simulations show that a pulsed excitation with duration of ten
milliseconds allows obtaining a substrate-independent thermal
response. Based on this result, an experimental setup consisting of a
near-infrared laser diode and an Infrared camera was next used to
evaluate the variation of paint coating thickness between 60 μm and
130 μm on two samples. Results show that the parameters extracted
for thermal images are correlated with the estimated thicknesses by
the Eddy current methods. The laser pulsed thermography is thus an
interesting alternative nondestructive method that can be moreover
used for nonconductive substrates.
Abstract: We report the microstructural and magnetic properties
of Ni50Mn39Sn11 and Ni50Mn36Sn14 ribbon Heusler alloys.
Experimental results were obtained by differential scanning
calorymetry, X-ray diffraction and vibrating sample magnetometry
techniques. The Ni-Mn-Sn system undergoes a martensitic structural
transformation in a wide temperature range. For example, for
Ni50Mn39Sn11 the start and finish temperatures of the martensitic and
austenite phase transformation for ribbon alloy were Ms=336K,
Mf=328K, As=335K and Af=343K whereas no structural
transformation is observed for Ni50Mn36Sn14 alloys. Magnetic
measurements show the typical ferromagnetic behavior with Curie
temperature 207 K at low applied field of 50 Oe. The complex
behavior exhibited by these Heusler alloys should be ascribed to the
strong coupling between magnetism and structure, being their
magnetic behavior determined by the distance between Mn atoms.
Abstract: An Australian manufacturer has fabricated an
innovative GFRP sandwich panel made from E-glass fiber skin and a
modified phenolic core for structural applications. Debonding, which
refers to separation of skin from the core material in composite
sandwiches, is one of the most common types of damage in
composites. The presence of debonding is of great concern because it
not only severely affects the stiffness but also modifies the dynamic
behaviour of the structure. Generally it is seen that the majority of
research carried out has been concerned about the delamination of
laminated structures whereas skin-core debonding has received
relatively minor attention. Furthermore it is observed that research
done on composite slabs having multiple skin-core debonding is very
limited. To address this gap, a comprehensive research investigating
dynamic behaviour of composite panels with single and multiple
debonding is presented. The study uses finite-element modelling and
analyses for investigating the influence of debonding on free
vibration behaviour of single and multilayer composite sandwich
panels. A broad parametric investigation has been carried out by
varying debonding locations, debonding sizes and support conditions
of the panels in view of both single and multiple debonding.
Numerical models were developed with Strand7 finite element
package by innovatively selecting the suitable elements to diligently
represent their actual behavior. Three-dimensional finite element
models were employed to simulate the physically real situation as
close as possible, with the use of an experimentally and numerically
validated finite element model. Comparative results and conclusions
based on the analyses are presented. For similar extents and locations
of debonding, the effect of debonding on natural frequencies appears
greatly dependent on the end conditions of the panel, giving greater
decrease in natural frequency when the panels are more restrained.
Some modes are more sensitive to debonding and this sensitivity
seems to be related to their vibration mode shapes. The fundamental
mode seems generally the least sensitive mode to debonding with
respect to the variation in free vibration characteristics. The results
indicate the effectiveness of the developed three dimensional finite
element models in assessing debonding damage in composite
sandwich panels.
Abstract: Image enhancement is a challenging issue in many applications. In the last two decades, there are various filters developed. This paper proposes a novel method which removes Gaussian noise from the gray scale images. The proposed technique is compared with Enhanced Fuzzy Peer Group Filter (EFPGF) for various noise levels. Experimental results proved that the proposed filter achieves better Peak-Signal-to-Noise-Ratio PSNR than the existing techniques. The proposed technique achieves 1.736dB gain in PSNR than the EFPGF technique.
Abstract: In this study, ultrasonic assisted machining (UAM) technique is applied in side-surface milling experiment for glass-ceramic workpiece material. The tungsten carbide cutting-tool with diamond coating is used in conjunction with two kinds of cooling/lubrication mediums such as water-soluble (WS) cutting fluid and minimum quantity lubricant (MQL). Full factorial process parameter combinations on the milling experiments are planned to investigate the effect of process parameters on cutting performance. From the experimental results, it tries to search for the better process parameter combination which the edge-indentation and the surface roughness are acceptable. In the machining experiments, ultrasonic oscillator was used to excite a cutting-tool along the radial direction producing a very small amplitude of vibration frequency of 20KHz to assist the machining process. After processing, toolmaker microscope was used to detect the side-surface morphology, edge-indentation and cutting tool wear under different combination of cutting parameters, and analysis and discussion were also conducted for experimental results. The results show that the main leading parameters to edge-indentation of glass ceramic are cutting depth and feed rate. In order to reduce edge-indentation, it needs to use lower cutting depth and feed rate. Water-soluble cutting fluid provides a better cooling effect in the primary cutting area; it may effectively reduce the edge-indentation and improve the surface morphology of the glass ceramic. The use of ultrasonic assisted technique can effectively enhance the surface finish cleanness and reduce cutting tool wear and edge-indentation.
Abstract: Association rule mining is one of the most important fields of data mining and knowledge discovery. In this paper, we propose an efficient multiple support frequent pattern growth algorithm which we called “MSFP-growth” that enhancing the FPgrowth algorithm by making infrequent child node pruning step with multiple minimum support using maximum constrains. The algorithm is implemented, and it is compared with other common algorithms: Apriori-multiple minimum supports using maximum constraints and FP-growth. The experimental results show that the rule mining from the proposed algorithm are interesting and our algorithm achieved better performance than other algorithms without scarifying the accuracy.
Abstract: This paper is focused on the CFD simulation of the radiaxial pump (i.e. mixed flow pump) with the aim to detect the reasons of Y-Q characteristic instability. The main reasons of pressure pulsations were detected by means of the analysis of velocity and pressure fields within the pump combined with the theoretical approach. Consequently, the modifications of spiral case and pump suction area were made based on the knowledge of flow conditions and the shape of dissipation function. The primary design of pump geometry was created as the base model serving for the comparison of individual modification influences. The basic experimental data are available for this geometry. This approach replaced the more complicated and with respect to convergence of all computational tasks more difficult calculation for the compressible liquid flow. The modification of primary pump consisted in inserting the three fins types. Subsequently, the evaluation of pressure pulsations, specific energy curves and visualization of velocity fields were chosen as the criterion for successful design.
Abstract: The present work attempts to investigate the
combustion, performance and emission characteristics of an existing
single-cylinder four-stroke compression-ignition engine operated in
dual-fuel mode with hydrogen as an alternative fuel. Environmental
concerns and limited amount of petroleum fuels have caused interests
in the development of alternative fuels like hydrogen for internal
combustion (IC) engines. In this experimental investigation, a diesel
engine is made to run using hydrogen in dual fuel mode with diesel,
where hydrogen is introduced into the intake manifold using an LPGCNG
injector and pilot diesel is injected using diesel injectors. A
Timed Manifold Injection (TMI) system has been developed to vary
the injection strategies. The optimized timing for the injection of
hydrogen was 10^0 CA after top dead center (ATDC). From the study
it was observed that with increasing hydrogen rate, enhancement in
brake thermal efficiency (BTHE) of the engine has been observed
with reduction in brake specific energy consumption (BSEC).
Furthermore, Soot contents decrease with an increase in indicated
specific NOx emissions with the enhancement of hydrogen flow rate.
Abstract: This work proposes a data-driven multiscale based
quantitative measures to reveal the underlying complexity of
electroencephalogram (EEG), applying to a rodent model of
hypoxic-ischemic brain injury and recovery. Motivated by that real
EEG recording is nonlinear and non-stationary over different
frequencies or scales, there is a need of more suitable approach over
the conventional single scale based tools for analyzing the EEG data.
Here, we present a new framework of complexity measures
considering changing dynamics over multiple oscillatory scales. The
proposed multiscale complexity is obtained by calculating entropies of
the probability distributions of the intrinsic mode functions extracted
by the empirical mode decomposition (EMD) of EEG. To quantify
EEG recording of a rat model of hypoxic-ischemic brain injury
following cardiac arrest, the multiscale version of Tsallis entropy is
examined. To validate the proposed complexity measure, actual EEG
recordings from rats (n=9) experiencing 7 min cardiac arrest followed
by resuscitation were analyzed. Experimental results demonstrate that
the use of the multiscale Tsallis entropy leads to better discrimination
of the injury levels and improved correlations with the neurological
deficit evaluation after 72 hours after cardiac arrest, thus suggesting an
effective metric as a prognostic tool.
Abstract: This paper presents effects of the mean operating
pressure on the optimal operating frequency based on temperature
differences across stack ends in a thermoacoustic refrigerator. In
addition to the length of the resonance tube, components of the
thermoacoustic refrigerator have an influence on the operating
frequency due to their acoustic properties, i.e., absorptivity,
reflectivity and transmissivity. The interference of waves incurs and
distorts the original frequency generated by the driver so that the
optimal operating frequency differs from the designs. These acoustic
properties are not parameters in the designs and be very complicated
to infer their responses. A prototype thermoacoustic refrigerator is
constructed and used to investigate its optimal operating frequency
compared to the design at various operating pressures. Helium and air
are used as working fluids during the experiments. The results
indicate that the optimal operating frequency of the prototype
thermoacoustic refrigerator using helium is at 6 bar and 490Hz or
approximately 20% away from the design frequency. The optimal
operating frequency at other mean pressures differs from the design
in an unpredictable manner, however, the optimal operating
frequency and pressure can be identified by testing.
Abstract: Scrubbing by a liquid spraying is one of the most
effective processes used for removal of fine particles and soluble
gas pollutants (such as SO2, HCl, HF) from the flue gas. There are
many configurations of scrubbers designed to provide contact
between the liquid and gas stream for effectively capturing
particles or soluble gas pollutants, such as spray plates, packed bed
towers, jet scrubbers, cyclones, vortex and venturi scrubbers. The
primary function of venturi scrubber is the capture of fine particles
as well as HCl, HF or SO2 removal with effect of the flue gas
temperature decrease before input to the absorption column. In this
paper, sulfur dioxide (SO2) from flue gas was captured using new
design replacing venturi scrubber (1st degree of wet scrubbing).
The flue gas was prepared by the combustion of the carbon
disulfide solution in toluene (1:1 vol.) in the flame in the reactor.
Such prepared flue gas with temperature around 150°C was
processed in designed laboratory O-element scrubber. Water was
used as absorbent liquid. The efficiency of SO2 removal, pressure
drop and temperature drop were measured on our experimental
device. The dependence of these variables on liquid-gas ratio was
observed. The average temperature drop was in the range from
150°C to 40°C. The pressure drop was increased with increasing of
a liquid-gas ratio, but no too much as for the common venturi
scrubber designs. The efficiency of SO2 removal was up to 70 %.
The pressure drop of our new designed wet scrubber is similar to
commonly used venturi scrubbers; nevertheless the influence of
amount of the liquid on pressure drop is not so significant.
Abstract: This paper is concerned with knowledge representation
and extraction of fuzzy if-then rules using Interval Type-2
Context-based Fuzzy C-Means clustering (IT2-CFCM) with the aid of
fuzzy granulation. This proposed clustering algorithm is based on
information granulation in the form of IT2 based Fuzzy C-Means
(IT2-FCM) clustering and estimates the cluster centers by preserving
the homogeneity between the clustered patterns from the IT2 contexts
produced in the output space. Furthermore, we can obtain the
automatic knowledge representation in the design of Radial Basis
Function Networks (RBFN), Linguistic Model (LM), and Adaptive
Neuro-Fuzzy Networks (ANFN) from the numerical input-output data
pairs. We shall focus on a design of ANFN in this paper. The
experimental results on an estimation problem of energy performance
reveal that the proposed method showed a good knowledge
representation and performance in comparison with the previous
works.
Abstract: This paper presents a model for a modified T-junction
device for microspheres generation. The numerical model is
developed using a commercial software package: COMSOL
Multiphysics. In order to test the accuracy of the numerical model,
multiple variables, such as the flow rate of cross-flow, fluid properties,
structure, and geometry of the microdevice are applied. The results
from the model are compared with the experimental results in the
diameter of the microsphere generated. The comparison shows a good
agreement. Therefore the model is useful in further optimization of the
device and feedback control of microsphere generation if any.
Abstract: The purposes of this study are 1) to study the effects
of participatory error correction process and 2) to find out the
students’ satisfaction of such error correction process. This study is a
Quasi Experimental Research with single group, in which data is
collected 5 times preceding and following 4 experimental studies of
participatory error correction process including providing coded
indirect corrective feedback in the students’ texts with error treatment
activities. Samples include 52 2nd year English Major students,
Faculty of Humanities and Social Sciences, Suan Sunandha Rajabhat
University. Tool for experimental study includes the lesson plan of
the course; Reading and Writing English for Academic Purposes II,
and tools for data collection include 5 writing tests of short texts and
a questionnaire. Based on formative evaluation of the students’
writing ability prior to and after each of the 4 experiments, the
research findings disclose the students’ higher scores with statistical
difference at 0.00. Moreover, in terms of the effect size of such
process, it is found that for mean of the students’ scores prior to and
after the 4 experiments; d equals 0.6801, 0.5093, 0.5071, and 0.5296
respectively. It can be concluded that participatory error correction
process enables all of the students to learn equally well and there is
improvement in their ability to write short texts. Finally the students’
overall satisfaction of the participatory error correction process is in
high level (Mean = 4.39, S.D. = 0.76).
Abstract: Microalgae Meyerella planktonica is a potential
biofuel source because it can grow in bulk in either autotrophic or
heterotrophic condition. However, the quantitative growth of this
algal type is still low as it tends to precipitates on the bottom.
Besides, the lipid concentration is still low when grown in
autotrophic condition. In contrast, heterotrophic condition can
enhance the lipid concentration. The combination of autotrophic
condition and agitation treatment was conducted to increase the
density of the culture. On the other hand, a heterotrophic condition
was set up to raise the lipid production. A two-stage experiment
was applied to increase the density at the first step and to increase
the lipid concentration in the next step. The autotrophic condition
resulted higher density but lower lipid concentration compared to
heterotrophic one. The agitation treatment produced higher density
in both autotrophic and heterotrophic conditions. The two-stage
experiment managed to enhance the density during the autotrophic
stage and the lipid concentration during the heterotrophic stage.
The highest yield was performed by using 0.4% v/v glycerol as a
carbon source (2.9±0.016 x 10^6 cells w/w) attained 7 days after the
heterotrophic stage began. The lipid concentration was stable
starting from day 7.