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: Extraction of laccase produced by L. polychrous in an
aqueous two-phase system, composed of polyethylene glycol and
phosphate salt at pH 7.0 and 250C was investigated. The effect of
PEG molecular weight, PEG concentration and phosphate
concentration was determined. Laccase preferentially partitioned to
the top phase. Good extraction of laccase to the top phase was
observed with PEG 4000. The optimum system was found in the
system containing 12% w/w PEG 4000 and 16% w/w phosphate salt
with KE of 88.3, purification factor of 3.0-fold and 99.1% yield.
Some properties of the enzyme such as thermal stability, effect of
heavy metal ions and kinetic constants were also presented in this
work. The thermal stability decreased sharply with high temperature
above 60 0C. The enzyme was inhibited by Cd2+, Pb2+, Zn2+ and
Cu2+. The Vmax and Km values of the enzyme were 74.70
μmol/min/ml and 9.066 mM respectively.
Abstract: We present a new numerical method for the computation of the steady-state solution of Markov chains. Theoretical analyses show that the proposed method, with a contraction factor α, converges to the one-dimensional null space of singular linear systems of the form Ax = 0. Numerical experiments are used to illustrate the effectiveness of the proposed method, with applications to a class of interesting models in the domain of tandem queueing networks.
Abstract: This paper is concerned with propagation of thermoelastic longitudinal vibrations of an infinite circular cylinder, in the context of the linear theory of generalized thermoelasticity with two relaxation time parameters (Green and Lindsay theory). Three displacement potential functions are introduced to uncouple the equations of motion. The frequency equation, by using the traction free boundary conditions, is given in the form of a determinant involving Bessel functions. The roots of the frequency equation give the value of the characteristic circular frequency as function of the wave number. These roots, which correspond to various modes, are numerically computed and presented graphically for different values of the thermal relaxation times. It is found that the influences of the thermal relaxation times on the amplitudes of the elastic and thermal waves are remarkable. Also, it is shown in this study that the propagation of thermoelastic longitudinal vibrations based on the generalized thermoelasticity can differ significantly compared with the results under the classical formulation. A comparison of the results for the case with no thermal effects shows well agreement with some of the corresponding earlier results.
Abstract: In face recognition, feature extraction techniques
attempts to search for appropriate representation of the data. However,
when the feature dimension is larger than the samples size, it brings
performance degradation. Hence, we propose a method called
Normalization Discriminant Independent Component Analysis
(NDICA). The input data will be regularized to obtain the most
reliable features from the data and processed using Independent
Component Analysis (ICA). The proposed method is evaluated on
three face databases, Olivetti Research Ltd (ORL), Face Recognition
Technology (FERET) and Face Recognition Grand Challenge
(FRGC). NDICA showed it effectiveness compared with other
unsupervised and supervised techniques.
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: The Requirements Abstraction Model (RAM) helps in managing abstraction in requirements by organizing them at four levels (product, feature, function and component). The RAM is adaptable and can be tailored to meet the needs of the various organizations. Because software requirements are an important source of information for developing high-level tests, organizations willing to adopt the RAM model need to know the suitability of the RAM requirements for developing high-level tests. To investigate this suitability, test cases from twenty randomly selected requirements were developed, analyzed and graded. Requirements were selected from the requirements document of a Course Management System, a web based software system that supports teachers and students in performing course related tasks. This paper describes the results of the requirements document analysis. The results show that requirements at lower levels in the RAM are suitable for developing executable tests whereas it is hard to develop from requirements at higher levels.
Abstract: A spatial classification technique incorporating a State of Art Feature Extraction algorithm is proposed in this paper for classifying a heterogeneous classes present in hyper spectral images. The classification accuracy can be improved if and only if both the feature extraction and classifier selection are proper. As the classes in the hyper spectral images are assumed to have different textures, textural classification is entertained. Run Length feature extraction is entailed along with the Principal Components and Independent Components. A Hyperspectral Image of Indiana Site taken by AVIRIS is inducted for the experiment. Among the original 220 bands, a subset of 120 bands is selected. Gray Level Run Length Matrix (GLRLM) is calculated for the selected forty bands. From GLRLMs the Run Length features for individual pixels are calculated. The Principle Components are calculated for other forty bands. Independent Components are calculated for next forty bands. As Principal & Independent Components have the ability to represent the textural content of pixels, they are treated as features. The summation of Run Length features, Principal Components, and Independent Components forms the Combined Features which are used for classification. SVM with Binary Hierarchical Tree is used to classify the hyper spectral image. Results are validated with ground truth and accuracies are calculated.
Abstract: Natural outdoor scene classification is active and
promising research area around the globe. In this study, the
classification is carried out in two phases. In the first phase, the
features are extracted from the images by wavelet decomposition
method and stored in a database as feature vectors. In the second
phase, the neural classifiers such as back-propagation neural network
(BPNN) and resilient back-propagation neural network (RPNN) are
employed for the classification of scenes. Four hundred color images
are considered from MIT database of two classes as forest and street.
A comparative study has been carried out on the performance of the
two neural classifiers BPNN and RPNN on the increasing number of
test samples. RPNN showed better classification results compared to
BPNN on the large test samples.
Abstract: Emotion recognition is an important research field that finds lots of applications nowadays. This work emphasizes on recognizing different emotions from speech signal. The extracted features are related to statistics of pitch, formants, and energy contours, as well as spectral, perceptual and temporal features, jitter, and shimmer. The Artificial Neural Networks (ANN) was chosen as the classifier. Working on finding a robust and fast ANN classifier suitable for different real life application is our concern. Several experiments were carried out on different ANN to investigate the different factors that impact the classification success rate. Using a database containing 7 different emotions, it will be shown that with a proper and careful adjustment of features format, training data sorting, number of features selected and even the ANN type and architecture used, a success rate of 85% or even more can be achieved without increasing the system complicity and the computation time
Abstract: The electrochemical coagulation of a kaolin
suspension was investigated at the currents of 0.06, 0.12, 0.22, 0.44,
0.85 A (corresponding to 0.68, 1.36, 2.50, 5.00, 9.66 mA·cm-2,
respectively) for the contact time of 5, 10, 20, 30, and 50 min. The
TSS removal efficiency at currents of 0.06 A, 0.12 A and 0.22 A
increased with the amount of iron generated by the sacrificial anode,
while the removal efficiencies did not increase proportionally with
the amount of iron generated at the currents of 0.44 and 0.85 A,
where electroflotation was clearly observed. Zeta potential
measurement illustrated the presence of the highly positive charged
particles created by sorption of highly charged polymeric metal
hydroxyl species onto the negative surface charged kaolin particles at
both low and high applied currents. The disappearance of the
individual peaks after certain contact times indicated the attraction
between these positive and negative charged particles causing
agglomeration. It was concluded that charge neutralization of the
individual species was not the only mechanism operating in the
electrocoagulation process at any current level, but electrostatic
attraction was likely to co-operate or mainly operate.
Abstract: This paper presents an ESN-based Arabic phoneme
recognition system trained with supervised, forced and combined
supervised/forced supervised learning algorithms. Mel-Frequency
Cepstrum Coefficients (MFCCs) and Linear Predictive Code (LPC)
techniques are used and compared as the input feature extraction
technique. The system is evaluated using 6 speakers from the King
Abdulaziz Arabic Phonetics Database (KAPD) for Saudi Arabia
dialectic and 34 speakers from the Center for Spoken Language
Understanding (CSLU2002) database of speakers with different
dialectics from 12 Arabic countries. Results for the KAPD and
CSLU2002 Arabic databases show phoneme recognition
performances of 72.31% and 38.20% respectively.
Abstract: In this paper we present the deep study about the Bio-
Medical Images and tag it with some basic extracting features (e.g.
color, pixel value etc). The classification is done by using a nearest
neighbor classifier with various distance measures as well as the
automatic combination of classifier results. This process selects a
subset of relevant features from a group of features of the image. It
also helps to acquire better understanding about the image by
describing which the important features are. The accuracy can be
improved by increasing the number of features selected. Various
types of classifications were evolved for the medical images like
Support Vector Machine (SVM) which is used for classifying the
Bacterial types. Ant Colony Optimization method is used for optimal
results. It has high approximation capability and much faster
convergence, Texture feature extraction method based on Gabor
wavelets etc..
Abstract: Studying literature theme in the fields of tourism and
sustainable development and its importance in today world and their
criteria in architecture, here in this article we will also study the area
where the selected site is located; beside the Aab-Ask Village located
in Larijan region in Mazandaran province on the way to Haraz – one
of the tourism routes of Iran. After these studies by analyzing the
site, its strong potentials – such as mineral water springs (hot
springs), geothermal, landscapes and ideal climate - as a tourist
attraction spot in the region, and considering sustainable
development criteria – with regard to limits and available facilities –
a plan was offered that could change the region to provide the needs
of local people and in addition change it to a place where tourism
services is offered to the visitors and make it an acceptable sample of
stable building in Iran. Finally the reason to make design for this
complex is recovery of natural and historical values of Aab-Ask area
regarding development and sustainable architecture criteria in the
form of a functional sample which can be a suitable place to fulfill
this goal for having lots of strong points in attracting cultural and
sustainable tourist.
Abstract: Clusters of microcalcifications in mammograms are an
important sign of breast cancer. This paper presents a complete
Computer Aided Detection (CAD) scheme for automatic detection of
clustered microcalcifications in digital mammograms. The proposed
system, MammoScan μCaD, consists of three main steps. Firstly
all potential microcalcifications are detected using a a method for
feature extraction, VarMet, and adaptive thresholding. This will also
give a number of false detections. The goal of the second step,
Classifier level 1, is to remove everything but microcalcifications.
The last step, Classifier level 2, uses learned dictionaries and sparse
representations as a texture classification technique to distinguish
single, benign microcalcifications from clustered microcalcifications,
in addition to remove some remaining false detections. The system
is trained and tested on true digital data from Stavanger University
Hospital, and the results are evaluated by radiologists. The overall
results are promising, with a sensitivity > 90 % and a low false
detection rate (approx 1 unwanted pr. image, or 0.3 false pr. image).
Abstract: The use of human hand as a natural interface for humancomputer interaction (HCI) serves as the motivation for research in hand gesture recognition. Vision-based hand gesture recognition involves visual analysis of hand shape, position and/or movement. In this paper, we use the concept of object-based video abstraction for segmenting the frames into video object planes (VOPs), as used in MPEG-4, with each VOP corresponding to one semantically meaningful hand position. Next, the key VOPs are selected on the basis of the amount of change in hand shape – for a given key frame in the sequence the next key frame is the one in which the hand changes its shape significantly. Thus, an entire video clip is transformed into a small number of representative frames that are sufficient to represent a gesture sequence. Subsequently, we model a particular gesture as a sequence of key frames each bearing information about its duration. These constitute a finite state machine. For recognition, the states of the incoming gesture sequence are matched with the states of all different FSMs contained in the database of gesture vocabulary. The core idea of our proposed representation is that redundant frames of the gesture video sequence bear only the temporal information of a gesture and hence discarded for computational efficiency. Experimental results obtained demonstrate the effectiveness of our proposed scheme for key frame extraction, subsequent gesture summarization and finally gesture recognition.
Abstract: Nanofluids are novel fluids that are going to have an
important role in future industrial thermal device designs. Studies are
being predominantly conducted on the mechanism of these heat
transfers. The key to this attraction is in the increase in thermal
conductivity brought about by the Nanofluids compared with the
base fluid. Different models have been proposed for calculation of
effective thermal conduction that has been gradually modified. In this
investigation effect of nanolayer structure and Brownian motion of
particles are studied and a new modified thermal conductivity model
is proposed. Temperature, concentration, nanolayer thickness and
particle size are taken as variables and their effect are studied
simultaneously on the thermal conductivity of the fluids, showing the
concentration of the nanoparticles to affect the nanolayer thickness
which also affects the Brownian motion.
Abstract: Modes of occurrence of Pb, As, Cr, Co, Cu, and Ni in bituminous coal and lignite were determined by means of sequential extraction using NH4OAc, HCl, HF and HNO3 extraction solutions. Elemental affinities obtained were then evaluated in relation to volatility of these elements during the combustion of these coals in two circulating fluidised-bed power stations. It was found out that higher percentage of the elements bound in silicates brought about lower volatility, while higher elemental proportion with monosulphides association (or bound as exchangeable ion) resulted in higher volatility. The only exception was the behavior of arsenic, whose volatility depended on amount of limestone added during the combustion process (as desulphurisation additive) rather than to its association in coal.
Abstract: Sugarcane bagasses are one of the most extensively used agricultural residues. Using acid hydrolysis and fermentation, conversion of sugarcane bagasses to lactic acid was technically and economically feasible. This research was concerned with the solubility of lignin in ammonium hydroxide, acid hydrolysis and lactic acid fermentation by Lactococcus lactis, Lactobacillus delbrueckii, Lactobacillus plantarum, and Lactobacillus casei. The lignin extraction results for different ammonium hydroxide concentrations showed that 10 % (v/v) NH4OH was favorable to lignin dissolution. Acid hydrolysis can be enhanced with increasing acid concentration and reaction temperature. The optimum glucose and xylose concentrations occurred at 121 ○C for 1 hour hydrolysis time in 10% sulphuric acid solution were 32 and 11 g/l, respectively. In order to investigate the significance of medium composition on lactic acid production, experiments were undertaken whereby a culture of Lactococcus lactis was grown under various glucose, peptone, yeast extract and xylose concentrations. The optimum medium was composed of 5 g/l glucose, 2.5 g/l xylose, 10 g/l peptone and 5 g/l yeast extract. Lactococcus lactis represents the most efficient for lactic acid production amongst those considered. The lactic acid fermentation by Lactococcus lactis after 72 hours gave the highest yield of 1.4 (g lactic acid per g reducing sugar).
Abstract: A sensitive and specific method for quantitative
determination of aflatoxins(B1, B2, G1,G2), deoxynivalenol,
fumonisin(B1,B2), ochratoxin A, zearalenone, T-2 and HT-2 in
roasted and ground grains using liquid chromatography combined
with tandem mass spectrometry. A double extraction using a
phosphate buffer solution followed by methanol was applied to
achieve effective co extraction of 11 mycotoxins. A multitoxin
immunoaffinity column for all these mycotoxins was used to clean up
the extract. The LODs of mycotoxins were 0.1~6.1 μg/kg, LOQs were
0.3~18.4 μg/kg. Forty seven samples collected from Seoul (Korea) for
mycotoxin contamination monitoring. The results showed that the
occurrence of zearalenone and deoxynivalenol were frequent.
Zearalenone was detected in all samples and deoxynivalenol was
detected in 80.9 % samples in the range 0.626 ~ 29.264 μg/kg and N.D
~ 48.332 μg/kg respectively. Fumonisins and ochratoxin A were
detected in 46.8% samples and 17 % samples respectively, aflatoxins
and T-2/HT-2 toxins were not detected all samples.