Abstract: One of the most challenges for hard surface cleaning product is to get rid of soap scum, a filmy sticky layer in the bathroom. The deposits of soap scum can be removed by using a proper surfactant solution with chelating agent. Unfortunately, the conventional chelating agent, ethylenediamine tetraacetic acid (EDTA), has low biodegradability, which can be tolerance in water resources and harmful to aquatic animal and microorganism. In this study, two biodegradable chelating agents, ethylenediamine disuccinic acid (EDDS) and glutamic acid diacetic acid (GLDA) were introduced as a replacement of EDTA. The result shows that using GLDA with amphoteric surfactant gave the highest equilibrium solubility of soap scum.
Abstract: Face recognition in the infrared spectrum has attracted a lot of interest in recent years. Many of the techniques used in infrared are based on their visible counterpart, especially linear techniques like PCA and LDA. In this work, we introduce a probabilistic Bayesian framework for face recognition in the infrared spectrum. In the infrared spectrum, variations can occur between face images of the same individual due to pose, metabolic, time changes, etc. Bayesian approaches permit to reduce intrapersonal variation, thus making them very interesting for infrared face recognition. This framework is compared with classical linear techniques. Non linear techniques we developed recently for infrared face recognition are also presented and compared to the Bayesian face recognition framework. A new approach for infrared face extraction based on SVM is introduced. Experimental results show that the Bayesian technique is promising and lead to interesting results in the infrared spectrum when a sufficient number of face images is used in an intrapersonal learning process.
Abstract: novel and simple method is introduced for rapid and
highly efficient water treatment by reverse osmosis (RO) method using
multi-walled carbon nanotubes (MWCNTs) / polyacrylonitrile (PAN)
polymer as a flexible, highly efficient, reusable and semi-permeable
mixed matrix membrane (MMM). For this purpose, MWCNTs were
directly synthesized and on-line purified by chemical vapor deposition
(CVD) process, followed by directing the MWCNT bundles towards an
ultrasonic bath, in which PAN polymer was simultaneously suspended
inside a solid porous silica support in water at temperature to ~70 οC.
Fabrication process of MMM was finally completed by hot isostatic
pressing (HIP) process. In accordance with the analytical figures of
merit, the efficiency of fabricated MMM was ~97%. The rate of water
treatment process was also evaluated to 6.35 L min-1. The results reveal
that, the CNT-based MMM is suitable for rapid treatment of different
forms of industrial, sea, drinking and well water samples.
Abstract: Gilaburu (Viburnum opulus L.) grown naturally in
Anatolia. In this study, some physico-chemical (sugar, acid, protein,
crude fat, crude fiber, ash etc.) characteristics and mineral
composition of Gilaburu fruit have been investigated. The length,
width, thickness, weight, total soluble solid, protein, crude ash, crude
fiber and crude oil of fruit were found to be 1.12 cm, 1.58 cm, 1.87
cm, 0.87 g, 14.73 %, 0.2 %, 0.11 %, 6.56 % and 0.4 %, respectively.
The seed of fruit mean weight, length, width and thickness were
determinated as 0.08 g, 7.76 cm, 7.67 cm and 1.66, respectively. In
addition 27 mineral elements (Al, Mg, Na, Ba, Ca, Ni, Cd, P, Cr, Pb,
S, Cu, Se, Fe, K, Sr, Li, Z, V, Ag, Bi, Co, Mn, B, Ga, In, Ti) were
analyzed. Gilaburu (Viburnum opulus L.) fruit was richest in
potassium (10764.764 ppm), Mg (1289.088 ppm) and P (1304.169
ppm).
Abstract: We have applied new accelerated algorithm for linear
discriminate analysis (LDA) in face recognition with support vector
machine. The new algorithm has the advantage of optimal selection
of the step size. The gradient descent method and new algorithm has
been implemented in software and evaluated on the Yale face
database B. The eigenfaces of these approaches have been used to
training a KNN. Recognition rate with new algorithm is compared
with gradient.
Abstract: This paper explores oil prices changes impact on energy policy of Kazakhstan in 2001-2009. It involves the role of oil income to the economic development, process of diversification of internal and external energy policy of Kazakhstan, and the changes in oil law towards subsoil users.
Abstract: The purpose of this study is to determine in what
ways elementary education prospective teachers are being informed
about innovations and to explain the role of social influence in the
usage process of a technological innovation in terms of genders. The
study group consisted of 300 prospective teachers, including 234
females and 66 males. Data have been collected by a questionnaire
developed by the researchers. The result of the study showed that,
while prospective teachers are being informed about innovations
most frequently by mass media, they rarely seek to take expert
advice. In addition, analysis of results showed that the social
influence on females were significantly higher than males in usage
process of a technological innovation.
Abstract: In this paper, a Dynamic Economic Dispatch (DED) model is developed for the system consisting of both thermal generators and wind turbines. The inclusion of a significant amount of wind energy into power systems has resulted in additional constraints on DED to accommodate the intermittent nature of the output. The probability of stochastic wind power based on the Weibull probability density function is included in the model as a constraint; A Here-and-Now Approach. The Environmental Protection Agency-s hourly emission target, which gives the maximum emission during the day, is used as a constraint to reduce the atmospheric pollution. A 69-bus test system with non-smooth cost function is used to illustrate the effectiveness of the proposed model compared with static economic dispatch model with including the wind power.
Abstract: In this paper we propose a novel approach for ascertaining human identity based on fusion of profile face and gait biometric cues The identification approach based on feature learning in PCA-LDA subspace, and classification using multivariate Bayesian classifiers allows significant improvement in recognition accuracy for low resolution surveillance video scenarios. The experimental evaluation of the proposed identification scheme on a publicly available database [2] showed that the fusion of face and gait cues in joint PCA-LDA space turns out to be a powerful method for capturing the inherent multimodality in walking gait patterns, and at the same time discriminating the person identity..
Abstract: The main aim of this study was to examine whether
people understand indicative conditionals on the basis of syntactic
factors or on the basis of subjective conditional probability. The
second aim was to investigate whether the conditional probability of
q given p depends on the antecedent and consequent sizes or derives
from inductive processes leading to establish a link of plausible cooccurrence
between events semantically or experientially associated.
These competing hypotheses have been tested through a 3 x 2 x 2 x 2
mixed design involving the manipulation of four variables: type of
instructions (“Consider the following statement to be true", “Read the
following statement" and condition with no conditional statement);
antecedent size (high/low); consequent size (high/low); statement
probability (high/low). The first variable was between-subjects, the
others were within-subjects. The inferences investigated were Modus
Ponens and Modus Tollens. Ninety undergraduates of the Second
University of Naples, without any prior knowledge of logic or
conditional reasoning, participated in this study.
Results suggest that people understand conditionals in a syntactic
way rather than in a probabilistic way, even though the perception of
the conditional probability of q given p is at least partially involved in
the conditionals- comprehension. They also showed that, in presence
of a conditional syllogism, inferences are not affected by the
antecedent or consequent sizes. From a theoretical point of view these
findings suggest that it would be inappropriate to abandon the idea
that conditionals are naturally understood in a syntactic way for the
idea that they are understood in a probabilistic way.
Abstract: The degradation of selected pharmaceuticals in some
water matrices was studied by using several chemical treatments. The
pharmaceuticals selected were the beta-blocker metoprolol, the
nonsteroidal anti-inflammatory naproxen, the antibiotic amoxicillin,
and the analgesic phenacetin; and their degradations were conducted
by using UV radiation alone, ozone, Fenton-s reagent, Fenton-like
system, photo-Fenton system, and combinations of UV radiation and
ozone with H2O2, TiO2, Fe(II), and Fe(III). The water matrices, in
addition to ultra-pure water, were a reservoir water, a groundwater,
and two secondary effluents from two municipal WWTP. The results
reveal that the presence of any second oxidant enhanced the
oxidation rates, with the systems UV/TiO2 and O3/TiO2 providing the
highest degradation rates. It is also observed in most of the
investigated oxidation systems that the degradation rate followed the
sequence: amoxicillin > naproxen > metoprolol > phenacetin. Lower
rates were obtained with the pharmaceuticals dissolved in natural
waters and secondary effluents due to the organic matter present
which consume some amounts of the oxidant agents.
Abstract: Linear Discrimination Analysis (LDA) is a linear
solution for classification of two classes. In this paper, we propose a
variant LDA method for multi-class problem which redefines the
between class and within class scatter matrices by incorporating a
weight function into each of them. The aim is to separate classes as
much as possible in a situation that one class is well separated from
other classes, incidentally, that class must have a little influence on
classification. It has been suggested to alleviate influence of classes
that are well separated by adding a weight into between class scatter
matrix and within class scatter matrix. To obtain a simple and
effective weight function, ordinary LDA between every two classes
has been used in order to find Fisher discrimination value and passed
it as an input into two weight functions and redefined between class
and within class scatter matrices. Experimental results showed that
our new LDA method improved classification rate, on glass, iris and
wine datasets, in comparison to different versions of LDA.
Abstract: Supersonic open and closed cavity flows are investigated experimentally and computationally. Free stream Mach number of two is set. Schlieren imaging is used to visualise the flow behaviour showing stark differences between open and closed. Computational Fluid Dynamics (CFD) is used to simulate open cavity of flow with aspect ratio of 4. A rear wall treatment is implemented in order to pursue a simple passive control approach. Good qualitative agreement is achieved between the experimental flow visualisation and the CFD in terms of the expansion-shock waves system. The cavity oscillations are shown to be dominated by the first and third Rossister modes combining to high fluctuations of non-linear nature above the cavity rear edge. A simple rear wall treatment in terms of a hole shows mixed effect on the flow oscillations, RMS contours, and time history density fluctuations are given and analysed.
Abstract: Power System Security is a major concern in real time
operation. Conventional method of security evaluation consists of
performing continuous load flow and transient stability studies by
simulation program. This is highly time consuming and infeasible
for on-line application. Pattern Recognition (PR) is a promising
tool for on-line security evaluation. This paper proposes a Support
Vector Machine (SVM) based binary classification for static and
transient security evaluation. The proposed SVM based PR approach
is implemented on New England 39 Bus and IEEE 57 Bus systems.
The simulation results of SVM classifier is compared with the other
classifier algorithms like Method of Least Squares (MLS), Multi-
Layer Perceptron (MLP) and Linear Discriminant Analysis (LDA)
classifiers.
Abstract: Wavelet transforms are multiresolution
decompositions that can be used to analyze signals and images.
Image compression is one of major applications of wavelet
transforms in image processing. It is considered as one of the most
powerful methods that provides a high compression ratio. However,
its implementation is very time-consuming. At the other hand,
parallel computing technologies are an efficient method for image
compression using wavelets. In this paper, we propose a parallel
wavelet compression algorithm based on quadtrees. We implement
the algorithm using MatlabMPI (a parallel, message passing version
of Matlab), and compute its isoefficiency function, and show that it is
scalable. Our experimental results confirm the efficiency of the
algorithm also.
Abstract: The latest Geographic Information System (GIS)
technology makes it possible to administer the spatial components of
daily “business object," in the corporate database, and apply suitable
geographic analysis efficiently in a desktop-focused application. We
can use wireless internet technology for transfer process in spatial
data from server to client or vice versa. However, the problem in
wireless Internet is system bottlenecks that can make the process of
transferring data not efficient. The reason is large amount of spatial
data. Optimization in the process of transferring and retrieving data,
however, is an essential issue that must be considered. Appropriate
decision to choose between R-tree and Quadtree spatial data indexing
method can optimize the process. With the rapid proliferation of
these databases in the past decade, extensive research has been
conducted on the design of efficient data structures to enable fast
spatial searching. Commercial database vendors like Oracle have also
started implementing these spatial indexing to cater to the large and
diverse GIS. This paper focuses on the decisions to choose R-tree
and quadtree spatial indexing using Oracle spatial database in mobile
GIS application. From our research condition, the result of using
Quadtree and R-tree spatial data indexing method in one single
spatial database can save the time until 42.5%.
Abstract: Presently and in line with the United Nations (EPA),
human thinking system has shifted towards clean fuels so as to
maintain a cleaner environment and to save our planet earth.
One of the most successful studies in order to achieve new
energies includes the use of animal wastes and their organic residues,
and the result of these researches has been represented in the form of
very simple and cheap methods called biogas technology. Biogas
technology has developed a lot in the recent decades; its reason is the
high cost of fossil fuels and the greater attention of countries to the
environmental pollutions due to the consumption of this kind of
fuels.
IRAN is ready for the optimized application of renewable
energies, having much enriched resources of this kind of energies; so
a special place could be considered for it when making programs.
The purpose of biogas technology is the recovery of energy and
finally the protection of the environment, which is much appropriate
for the third world farmers with respect to their technical abilities and
economic potentials. Studies show that the production and
consumption of biogas is appropriate and economic in IRAN,
because of the high amount of waste in the agriculture sector, the
significant amount of animal and human excrement production, the
great volume of garbage produced and the most important the
specific social, climatic and agricultural conditions in IRAN, in order
to proceed towards the reduction of pollution due to the use of fossil
fuels.
Abstract: Texture information plays increasingly an important
role in remotely sensed imagery classification and many pattern
recognition applications. However, the selection of relevant textural
features to improve this classification accuracy is not a straightforward
task. This work investigates the effectiveness of two Mutual
Information Feature Selector (MIFS) algorithms to select salient
textural features that contain highly discriminatory information for
multispectral imagery classification. The input candidate features are
extracted from a SPOT High Resolution Visible(HRV) image using
Wavelet Transform (WT) at levels (l = 1,2).
The experimental results show that the selected textural features
according to MIFS algorithms make the largest contribution to
improve the classification accuracy than classical approaches such
as Principal Components Analysis (PCA) and Linear Discriminant
Analysis (LDA).
Abstract: The purpose of this study is to investigate the effects
of modality principles in instructional software among first grade
pupils- achievements in the learning of Arabic Language. Two modes
of instructional software were systematically designed and
developed, audio with images (AI), and text with images (TI). The
quasi-experimental design was used in the study. The sample
consisted of 123 male and female pupils from IRBED Education
Directorate, Jordan. The pupils were randomly assigned to any one of
the two modes. The independent variable comprised the two modes
of the instructional software, the students- achievement levels in the
Arabic Language class and gender. The dependent variable was the
achievements of the pupils in the Arabic Language test. The
theoretical framework of this study was based on Mayer-s Cognitive
Theory of Multimedia Learning. Four hypotheses were postulated
and tested. Analyses of Variance (ANOVA) showed that pupils using
the (AI) mode performed significantly better than those using (TI)
mode. This study concluded that the audio with images mode was an
important aid to learning as compared to text with images mode.
Abstract: The paper depicts air velocity values, reproduced by laser Doppler anemometer (LDA) and ultrasonic anemometer (UA), relations with calculated ones from flow rate measurements using the gas meter which calibration uncertainty is ± (0.15 – 0.30) %. Investigation had been performed in channel installed in aerodynamical facility used as a part of national standard of air velocity. Relations defined in a research let us confirm the LDA and UA for air velocity reproduction to be the most advantageous measures. The results affirm ultrasonic anemometer to be reliable and favourable instrument for measurement of mean velocity or control of velocity stability in the velocity range of 0.05 m/s – 10 (15) m/s when the LDA used. The main aim of this research is to investigate low velocity regularities, starting from 0.05 m/s, including region of turbulent, laminar and transitional air flows. Theoretical and experimental results and brief analysis of it are given in the paper. Maximum and mean velocity relations for transitional air flow having unique distribution are represented. Transitional flow having distinctive and different from laminar and turbulent flow characteristics experimentally have not yet been analysed.