Abstract: Purpose: To explore the use of Curvelet transform to
extract texture features of pulmonary nodules in CT image and support
vector machine to establish prediction model of small solitary
pulmonary nodules in order to promote the ratio of detection and
diagnosis of early-stage lung cancer. Methods: 2461 benign or
malignant small solitary pulmonary nodules in CT image from 129
patients were collected. Fourteen Curvelet transform textural features
were as parameters to establish support vector machine prediction
model. Results: Compared with other methods, using 252 texture
features as parameters to establish prediction model is more proper.
And the classification consistency, sensitivity and specificity for the
model are 81.5%, 93.8% and 38.0% respectively. Conclusion: Based
on texture features extracted from Curvelet transform, support vector
machine prediction model is sensitive to lung cancer, which can
promote the rate of diagnosis for early-stage lung cancer to some
extent.
Abstract: Coal tar is a liquid by-product of the process of coal
gasification and carbonation. This liquid oil mixture contains various
kinds of useful compounds such as phenol, o-cresol, and p-cresol.
These compounds are widely used as raw material for insecticides,
dyes, medicines, perfumes, coloring matters, and many others.
This research needed to be done that given the optimum conditions
for the separation of phenol, o-cresol, and p-cresol from the coal tar
by solvent extraction process. The aim of the present work was to
study the effect of two kinds of aqueous were used as solvents:
methanol and acetone solutions, the effect of temperature (298, 306,
and 313K) and mixing (30, 35, and 40rpm) for the separation of
phenol, o-cresol, and p-cresol from coal tar by solvent extraction.
Results indicated that phenol, o-cresol, and p-cresol in coal tar
were selectivity extracted into the solvent phase and these
components could be separated by solvent extraction. The aqueous
solution of methanol, mass ratio of solvent to feed, Eo/Ro=1,
extraction temperature 306K and mixing 35 rpm were the most
efficient for extraction of phenol, o-cresol, and p-cresol from coal tar.
Abstract: Frequency domain independent component analysis has
a scaling indeterminacy and a permutation problem. The scaling
indeterminacy can be solved by use of a decomposed spectrum. For
the permutation problem, we have proposed the rules in terms of gain
ratio and phase difference derived from the decomposed spectra and
the source-s coarse directions.
The present paper experimentally clarifies that the gain ratio and
the phase difference work effectively in a real environment but their
performance depends on frequency bands, a microphone-space and
a source-microphone distance. From these facts it is seen that it is
difficult to attain a perfect solution for the permutation problem in a
real environment only by either the gain ratio or the phase difference.
For the perfect solution, this paper gives a solution to the problems
in a real environment. The proposed method is simple, the amount of
calculation is small. And the method has high correction performance
without depending on the frequency bands and distances from source
signals to microphones. Furthermore, it can be applied under the real
environment. From several experiments in a real room, it clarifies
that the proposed method has been verified.
Abstract: In this paper we present an off line system for the
recognition of the handwritten numeric chains. Our work is divided
in two big parts. The first part is the realization of a recognition
system of the isolated handwritten digits. In this case the study is
based mainly on the evaluation of neural network performances,
trained with the gradient back propagation algorithm. The used
parameters to form the input vector of the neural network are
extracted on the binary images of the digits by several methods: the
distribution sequence, the Barr features and the centred moments of
the different projections and profiles. The second part is the
extension of our system for the reading of the handwritten numeric
chains constituted of a variable number of digits. The vertical
projection is used to segment the numeric chain at isolated digits and
every digit (or segment) will be presented separately to the entry of
the system achieved in the first part (recognition system of the
isolated handwritten digits). The result of the recognition of the
numeric chain will be displayed at the exit of the global system.
Abstract: The morphology, mineralogical and chemical
composition of a low-grade nickel ore from Mpumalanga, South
Africa, were studied by scanning electron microscope (SEM), X-ray
diffraction (XRD) and X-ray fluorescence (XRF), respectively. The
ore was subjected to atmospheric agitation leaching using sulphuric
acid to investigate the effects of acid concentration, leaching
temperature, leaching time and particle size on extraction of nickel
and cobalt. Analyses results indicated the ore to be a saprolitic nickel
laterite belonging to the serpentine group of minerals. Sulphuric acid
was found to be able to extract nickel from the ore. Increased acid
concentration and temperature only produced low amounts of nickel
but improved cobalt extraction. As high as 77.44% Ni was achieved
when leaching a -106+75μm fraction with 4.0M acid concentration at
25oC. The kinetics of nickel leaching from the saprolitic ore were
studied and the activation energy was determined to be 18.16kJ/mol.
This indicated that nickel leaching reaction was diffusion controlled.
Abstract: Independent component analysis can estimate unknown
source signals from their mixtures under the assumption that the
source signals are statistically independent. However, in a real environment,
the separation performance is often deteriorated because
the number of the source signals is different from that of the sensors.
In this paper, we propose an estimation method for the number of
the sources based on the joint distribution of the observed signals
under two-sensor configuration. From several simulation results, it
is found that the number of the sources is coincident to that of
peaks in the histogram of the distribution. The proposed method can
estimate the number of the sources even if it is larger than that of
the observed signals. The proposed methods have been verified by
several experiments.
Abstract: As a result of the daily workflow in the design
development departments of companies, databases containing huge
numbers of 3D geometric models are generated. According to the
given problem engineers create CAD drawings based on their design
ideas and evaluate the performance of the resulting design, e.g. by
computational simulations. Usually, new geometries are built either
by utilizing and modifying sets of existing components or by adding
single newly designed parts to a more complex design.
The present paper addresses the two facets of acquiring
components from large design databases automatically and providing
a reasonable overview of the parts to the engineer. A unified
framework based on the topographic non-negative matrix
factorization (TNMF) is proposed which solves both aspects
simultaneously. First, on a given database meaningful components
are extracted into a parts-based representation in an unsupervised
manner. Second, the extracted components are organized and
visualized on square-lattice 2D maps. It is shown on the example of
turbine-like geometries that these maps efficiently provide a wellstructured
overview on the database content and, at the same time,
define a measure for spatial similarity allowing an easy access and
reuse of components in the process of design development.
Abstract: This paper presents the new results of energy plant –
rye and triticale at yellow ripeness and ripe, pre-treatment in high
pressure steam reactor and monosaccharide extraction. There were
investigated the influence of steam pressure (20 to 22 bar), retention
duration (180 to 240 s) and catalytic sulphuric acid concentration
strength (0 to 0.5 %) on the pre-treatment process, contents of
monosaccharides (glucose, arabinose, xylose, mannose) and
undesirable by-compounds (furfural and HMF) in the reactor. The
study has determined that the largest amount of monosaccharides
(37.2 % of glucose, 2.7 % of arabinose, 8.4 % of xylose, and 1.3 %
of mannose) was received in the rye at ripe, the samples of which
were mixed with 0.5 % concentration of catalytic sulphuric acid, and
hydrolysed in the reactor, where the pressure was 20 bar, whereas the
reaction time – 240 s.
Abstract: This research studied the hypoglycemic effect of
water soluble polysaccharide (WSP) extracted from yam (Dioscorea
hispida) tuber by three different methods: aqueous extraction, papain
assisted extraction, and tempeh inoculums assisted extraction. The
two later extraction methods were aimed to remove WSP binding
protein to have more pure WSP. The hypoglycemic activities were
evaluated by means in vivo test on alloxan induced hyperglycemic
rats, glucose response test (GRT), in situ glucose absorption test
using everted sac, and short chain fatty acids (SCFAs) analysis. All
yam WSP extracts exhibited ability to decrease blood glucose level in
hyperglycemia condition as well as inhibited glucose absorption and
SCFA formation. The order of hypoglycemic activity was tempeh
inoculums assisted- >papain assisted- >aqueous WSP extracts. GRT
and in situ glucose absorption test showed that order of inhibition
was papain assisted- >tempeh inoculums assisted- >aqueous WSP
extracts. Digesta of caecum of yam WSP extracts oral fed rats had
more SCFA than control. Tempeh inoculums assisted WSP extract
exhibited the most significant hypoglycemic activity.
Abstract: In this paper a new approach to face recognition is presented that achieves double dimension reduction making the system computationally efficient with better recognition results. In pattern recognition techniques, discriminative information of image increases with increase in resolution to a certain extent, consequently face recognition results improve with increase in face image resolution and levels off when arriving at a certain resolution level. In the proposed model of face recognition, first image decimation algorithm is applied on face image for dimension reduction to a certain resolution level which provides best recognition results. Due to better computational speed and feature extraction potential of Discrete Cosine Transform (DCT) it is applied on face image. A subset of coefficients of DCT from low to mid frequencies that represent the face adequately and provides best recognition results is retained. A trade of between decimation factor, number of DCT coefficients retained and recognition rate with minimum computation is obtained. Preprocessing of the image is carried out to increase its robustness against variations in poses and illumination level. This new model has been tested on different databases which include ORL database, Yale database and a color database. The proposed technique has performed much better compared to other techniques. The significance of the model is two fold: (1) dimension reduction up to an effective and suitable face image resolution (2) appropriate DCT coefficients are retained to achieve best recognition results with varying image poses, intensity and illumination level.
Abstract: The principal objective of this study is to be able to
extract niobium oxide from columbite-tantalite concentrate of Thayet
Kon Area in Nay Phi Taw. It is recovered from columbite-tantalite
concentrate which contains 19.29 % Nb2O5.The recovery of niobium
oxide from columbite-tantalite concentrate can be divided into three
main sections, namely, digestion of the concentrate, recovery from
the leached solution and precipitation and calcinations. The
concentrate was digested with hydrofluoric acid and sulfuric acid. Of
the various parameters that effect acidity and time were studied. In
the recovery section solvent extraction process using methyl isobutyl
ketone was investigated. Ammonium hydroxide was used as a
precipitating agent and the precipitate was later calcined. The
percentage of niobium oxide is 74%.
Abstract: The experimental and theoretical results of a ZVS
(Zero Voltage Switching) isolated flyback DC-DC converter using
multilayered coreless PCB step down 2:1 transformer are presented.
The performance characteristics of the transformer are shown which
are useful for the parameters extraction. The measured energy
efficiency of the transformer is found to be more than 94% with the
sinusoidal input voltage excitation. The designed flyback converter
has been tested successfully upto the output power level of 10W,
with a switching frequency in the range of 2.7MHz-4.3MHz. The
input voltage of the converter is varied from 25V-40V DC.
Frequency modulation technique is employed by maintaining
constant off time to regulate the output voltage of the converter. The
energy efficiency of the isolated flyback converter circuit under ZVS
condition in the MHz frequency region is found to be approximately
in the range of 72-84%. This paper gives the comparative results in
terms of the energy efficiency of the hard switched and soft switched
flyback converter in the MHz frequency region.
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 rapid expansion of the web is causing the
constant growth of information, leading to several problems such as
increased difficulty of extracting potentially useful knowledge. Web
content mining confronts this problem gathering explicit information
from different web sites for its access and knowledge discovery.
Query interfaces of web databases share common building blocks.
After extracting information with parsing approach, we use a new
data mining algorithm to match a large number of schemas in
databases at a time. Using this algorithm increases the speed of
information matching. In addition, instead of simple 1:1 matching,
they do complex (m:n) matching between query interfaces. In this
paper we present a novel correlation mining algorithm that matches
correlated attributes with smaller cost. This algorithm uses Jaccard
measure to distinguish positive and negative correlated attributes.
After that, system matches the user query with different query
interfaces in special domain and finally chooses the nearest query
interface with user query to answer to it.
Abstract: In this paper an extensive verification of the extraction
method (published earlier) that consistently accounts for self-heating
and Early effect to accurately extract both base and thermal resistance
of bipolar junction transistors is presented. The method verification is
demonstrated on advanced RF SiGe HBTs were the extracted results
for the thermal resistance are compared with those from another
published method that ignores the effect of Early effect on internal
base-emitter voltage and the extracted results of the base resistance
are compared with those determined from noise measurements. A
self-consistency of our method in the extracted base resistance and
thermal resistance using compact model simulation results is also
carried out in order to study the level of accuracy of the method.
Abstract: Hidden Markov Model (HMM) is a stochastic method
which has been used in various signal processing and character
recognition. This study proposes to use HMM to recognize Javanese
characters from a number of different handwritings, whereby HMM
is used to optimize the number of state and feature extraction. An
85.7 % accuracy is obtained as the best result in 16-stated vertical
model using pure HMM. This initial result is satisfactory for
prompting further research.
Abstract: The polyfunctional and highly reactive bio-polymer,
the chitosan was first regioselectively converted into dialkylated
chitosan using dimsyl anionic solution(NaH in DMSO) and
bromodecane after protecting amino groups by phthalic anhydride.
The dibenzo-18-crown-6-ether, on the other hand, was converted into
its carbonyl derivatives via Duff reaction prior to incorporate into
chitosan by Schiff base formation. Thus formed diformylated
dibenzo-18-crown-6-ether was condensed with lipophilic chitosan to
prepare the novel solvent extraction reagent. The products were
characterized mainly by IR and 1H-NMR. Hence, the multidentate
crown ether-embedded polyfunctional bio-material was tested for
extraction of Pd(II) and Pt(IV) in aqueous solution.
Abstract: Keystroke authentication is a new access control system
to identify legitimate users via their typing behavior. In this paper,
machine learning techniques are adapted for keystroke authentication.
Seven learning methods are used to build models to differentiate user
keystroke patterns. The selected classification methods are Decision
Tree, Naive Bayesian, Instance Based Learning, Decision Table, One
Rule, Random Tree and K-star. Among these methods, three of them
are studied in more details. The results show that machine learning
is a feasible alternative for keystroke authentication. Compared to
the conventional Nearest Neighbour method in the recent research,
learning methods especially Decision Tree can be more accurate. In
addition, the experiment results reveal that 3-Grams is more accurate
than 2-Grams and 4-Grams for feature extraction. Also, combination
of attributes tend to result higher accuracy.
Abstract: Raisin Concentrate (RC) are the most important
products obtained in the raisin processing industries. These RC
products are now used to make the syrups, drinks and confectionery
productions and introduced as natural substitute for sugar in food
applications. Iran is a one of the biggest raisin exporter in the world
but unfortunately despite a good raw material, no serious effort to
extract the RC has been taken in Iran. Therefore, in this paper, we
determined and analyzed affected parameters on extracting RC
process and then optimizing these parameters for design the
extracting RC process in two types of raisin (round and long)
produced in Khorasan region. Two levels of solvent (1:1 and 2:1),
three levels of extraction temperature (60°C, 70°C and 80°C), and
three levels of concentration temperature (50°C, 60°C and 70°C)
were the treatments. Finally physicochemical characteristics of the
obtained concentrate such as color, viscosity, percentage of reduction
sugar, acidity and the microbial tests (mould and yeast) were
counted. The analysis was performed on the basis of factorial in the
form of completely randomized design (CRD) and Duncan's multiple
range test (DMRT) was used for the comparison of the means.
Statistical analysis of results showed that optimal conditions for
production of concentrate is round raisins when the solvent ratio was
2:1 with extraction temperature of 60°C and then concentration
temperature of 50°C. Round raisin is cheaper than the long one, and
it is more economical to concentrate production. Furthermore, round
raisin has more aromas and the less color degree with increasing the
temperature of concentration and extraction. Finally, according to
mentioned factors the concentrate of round raisin is recommended.
Abstract: Prospective readers can quickly determine whether a document is relevant to their information need if the significant phrases (or keyphrases) in this document are provided. Although keyphrases are useful, not many documents have keyphrases assigned to them, and manually assigning keyphrases to existing documents is costly. Therefore, there is a need for automatic keyphrase extraction. This paper introduces a new domain independent keyphrase extraction algorithm. The algorithm approaches the problem of keyphrase extraction as a classification task, and uses a combination of statistical and computational linguistics techniques, a new set of attributes, and a new machine learning method to distinguish keyphrases from non-keyphrases. The experiments indicate that this algorithm performs better than other keyphrase extraction tools and that it significantly outperforms Microsoft Word 2000-s AutoSummarize feature. The domain independence of this algorithm has also been confirmed in our experiments.