Abstract: In this paper we present an adaptive method for image
compression that is based on complexity level of the image. The
basic compressor/de-compressor structure of this method is a multilayer
perceptron artificial neural network. In adaptive approach
different Back-Propagation artificial neural networks are used as
compressor and de-compressor and this is done by dividing the
image into blocks, computing the complexity of each block and then
selecting one network for each block according to its complexity
value. Three complexity measure methods, called Entropy, Activity
and Pattern-based are used to determine the level of complexity in
image blocks and their ability in complexity estimation are evaluated
and compared. In training and evaluation, each image block is
assigned to a network based on its complexity value. Best-SNR is
another alternative in selecting compressor network for image blocks
in evolution phase which chooses one of the trained networks such
that results best SNR in compressing the input image block. In our
evaluations, best results are obtained when overlapping the blocks is
allowed and choosing the networks in compressor is based on the
Best-SNR. In this case, the results demonstrate superiority of this
method comparing with previous similar works and JPEG standard
coding.
Abstract: A new conceptual architecture for low-level neural
pattern recognition is presented. The key ideas are that the brain
implements support vector machines and that support vectors are
represented as memory patterns in competitive queuing memories. A
binary classifier is built from two competitive queuing memories
holding positive and negative valence training examples respectively.
The support vector machine classification function is calculated in
synchronized evaluation cycles. The kernel is computed by bisymmetric
feed-forward networks feed by sensory input and by
competitive queuing memories traversing the complete sequence of
support vectors. Temporary summation generates the output
classification. It is speculated that perception apparatus in the brain
reuses structures that have evolved for enabling fluent execution of
prepared action sequences so that pattern recognition is built on
internalized motor programmes.
Abstract: This work presents a new phonetic transcription system based on a tree of hierarchical pronunciation rules expressed as context-specific grapheme-phoneme correspondences. The tree is automatically inferred from a phonetic dictionary by incrementally analyzing deeper context levels, eventually representing a minimum set of exhaustive rules that pronounce without errors all the words in the training dictionary and that can be applied to out-of-vocabulary words. The proposed approach improves upon existing rule-tree-based techniques in that it makes use of graphemes, rather than letters, as elementary orthographic units. A new linear algorithm for the segmentation of a word in graphemes is introduced to enable outof- vocabulary grapheme-based phonetic transcription. Exhaustive rule trees provide a canonical representation of the pronunciation rules of a language that can be used not only to pronounce out-of-vocabulary words, but also to analyze and compare the pronunciation rules inferred from different dictionaries. The proposed approach has been implemented in C and tested on Oxford British English and Basic English. Experimental results show that grapheme-based rule trees represent phonetically sound rules and provide better performance than letter-based rule trees.
Abstract: TUSAT is a prospective Turkish
Communication Satellite designed for providing mainly data
communication and broadcasting services through Ku-Band
and C-Band channels. Thermal control is a vital issue in
satellite design process. Therefore, all satellite subsystems and
equipments should be maintained in the desired temperature
range from launch to end of maneuvering life. The main
function of the thermal control is to keep the equipments and
the satellite structures in a given temperature range for various
phases and operating modes of spacecraft during its lifetime.
This paper describes the thermal control design which uses
passive and active thermal control concepts. The active
thermal control is based on heaters regulated by software via
thermistors. Alternatively passive thermal control composes of
heat pipes, multilayer insulation (MLI) blankets, radiators,
paints and surface finishes maintaining temperature level of
the overall carrier components within an acceptable value.
Thermal control design is supported by thermal analysis using
thermal mathematical models (TMM).
Abstract: As wind, solar and other clean and green energy
sources gain popularity worldwide, engineers are seeking ways to
make renewable energy systems more affordable and to integrate
them with existing ac power grids. In the present paper an attempt
has been made for integrating the PV arrays to the smart nano grid
using an artificial intelligent (AI) based solar powered cascade multilevel
inverter. The AI based controller switching scheme has been
used for improving the power quality by reducing the Total Harmonic
Distortion (THD) of the multi-level inverter output voltage.
Abstract: A method and apparatus for noninvasive measurement
of blood glucose concentration based on transilluminated laser beam
via the Index Finger has been reported in this paper. This method
depends on atomic gas (He-Ne) laser operating at 632.8nm
wavelength. During measurement, the index finger is inserted into the
glucose sensing unit, the transilluminated optical signal is converted
into an electrical signal, compared with the reference electrical
signal, and the obtained difference signal is processed by signal
processing unit which presents the results in the form of blood
glucose concentration. This method would enable the monitoring
blood glucose level of the diabetic patient continuously, safely and
noninvasively.
Abstract: The knowledge base of welding defect recognition is
essentially incomplete. This characteristic determines that the recognition results do not reflect the actual situation. It also has a further influence on the classification of welding quality. This paper is
concerned with the study of a rough set based method to reduce the influence and improve the classification accuracy. At first, a rough set
model of welding quality intelligent classification has been built. Both condition and decision attributes have been specified. Later on, groups
of the representative multiple compound defects have been chosen
from the defect library and then classified correctly to form the
decision table. Finally, the redundant information of the decision table has been reducted and the optimal decision rules have been reached. By this method, we are able to reclassify the misclassified defects to
the right quality level. Compared with the ordinary ones, this method
has higher accuracy and better robustness.
Abstract: Wind farms (WFs) with high level of penetration are
being established in power systems worldwide more rapidly than
other renewable resources. The Independent System Operator (ISO),
as a policy maker, should propose appropriate places for WF
installation in order to maximize the benefits for the investors. There
is also a possibility of congestion relief using the new installation of
WFs which should be taken into account by the ISO when proposing
the locations for WF installation. In this context, efficient wind farm
(WF) placement method is proposed in order to reduce burdens on
congested lines. Since the wind speed is a random variable and load
forecasts also contain uncertainties, probabilistic approaches are used
for this type of study. AC probabilistic optimal power flow (P-OPF)
is formulated and solved using Monte Carlo Simulations (MCS). In
order to reduce computation time, point estimate methods (PEM) are
introduced as efficient alternative for time-demanding MCS.
Subsequently, WF optimal placement is determined using generation
shift distribution factors (GSDF) considering a new parameter
entitled, wind availability factor (WAF). In order to obtain more
realistic results, N-1 contingency analysis is employed to find the
optimal size of WF, by means of line outage distribution factors
(LODF). The IEEE 30-bus test system is used to show and compare
the accuracy of proposed methodology.
Abstract: The aim of every software product is to achieve an
appropriate level of software quality. Developers and designers are
trying to produce readable, reliable, maintainable, reusable and
testable code. To help achieve these goals, several approaches have
been utilized. In this paper, refactoring technique was used to
evaluate software quality with a quality index. It is composed of
different metric sets which describes various quality aspects.
Abstract: This paper proposes a new optimization techniques
for the optimization a gas processing plant uncertain feed and
product flows. The problem is first formulated using a continuous
linear deterministic approach. Subsequently, the single and joint
chance constraint models for steady state process with timedependent
uncertainties have been developed. The solution approach
is based on converting the probabilistic problems into their
equivalent deterministic form and solved at different confidence
levels Case study for a real plant operation has been used to
effectively implement the proposed model. The optimization results
indicate that prior decision has to be made for in-operating plant
under uncertain feed and product flows by satisfying all the
constraints at 95% confidence level for single chance constrained and
85% confidence level for joint chance constrained optimizations
cases.
Abstract: The present work is concerned with the effect of turning process parameters (cutting speed, feed rate, and depth of cut) and distance from the center of work piece as input variables on the chip micro-hardness as response or output. Three experiments were conducted; they were used to investigate the chip micro-hardness behavior at diameter of work piece for 30[mm], 40[mm], and 50[mm]. Response surface methodology (R.S.M) is used to determine and present the cause and effect of the relationship between true mean response and input control variables influencing the response as a two or three dimensional hyper surface. R.S.M has been used for designing a three factor with five level central composite rotatable factors design in order to construct statistical models capable of accurate prediction of responses. The results obtained showed that the application of R.S.M can predict the effect of machining parameters on chip micro-hardness. The five level factorial designs can be employed easily for developing statistical models to predict chip micro-hardness by controllable machining parameters. Results obtained showed that the combined effect of cutting speed at it?s lower level, feed rate and depth of cut at their higher values, and larger work piece diameter can result increasing chi micro-hardness.
Abstract: Chemical detection is still a continuous challenge when
it comes to designing single-walled carbon nanotube (SWCNT)
sensors with high selectivity, especially in complex chemical
environments. A perfect example of such an environment would be in
thermally oxidized soybean oil. At elevated temperatures, oil oxidizes
through a series of chemical reactions which results in the formation of
monoacylglycerols, diacylglycerols, oxidized triacylglycerols, dimers,
trimers, polymers, free fatty acids, ketones, aldehydes, alcohols,
esters, and other minor products. In order to detect the rancidity of
oxidized soybean oil, carbon nanotube chemiresistor sensors have
been coated with polyethylenimine (PEI) to enhance the sensitivity
and selectivity. PEI functionalized SWCNTs are known to have a high
selectivity towards strong electron withdrawing molecules. The
sensors were very responsive to different oil oxidation levels and
furthermore, displayed a rapid recovery in ambient air without the
need of heating or UV exposure.
Abstract: Nowadays, the earth is countered with serious problem
of air pollution. This problem has been started from the industrial
revolution and has been faster in recent years, so that leads the earth
to ecological and environmental disaster. One of its results is the
global warming problem and its related increase in global
temperature. The most important factors in air pollution especially in
urban environments are Automobiles and residential buildings that are
the biggest consumers of the fossil energies, so that if the residential
buildings as a big part of the consumers of such energies reduce their
consumption rate, the air pollution will be decreased. Since
Metropolises are the main centers of air pollution in the world,
assessment and analysis of efficient strategies in decreasing air
pollution in such cities, can lead to the desirable and suitable results
and can solve the problem at least in critical level. Tabriz city is one
of the most important metropolises in North west of Iran that about
two million people are living there. for its situation in cold dry
climate, has a high rate of fossil energies consumption that make air
pollution in its urban environment. These two factors, being both
metropolis and in cold dry climate, make this article try to analyze the
strategies of climatic design in old districts of the city and use them in
new districts of the future. These strategies can be used in this city
and other similar cities and pave the way to reduce energy
consumption and related air pollution to save whole world.
Abstract: Nowadays, access to sustainable development in cities is assumed as one of the most important goals of urban managers. In the meanwhile, neighborhood as the smallest unit of urban spatial organization has a substantial effect on urban sustainability. Hence, attention to and focus on this subject is highly important in urban development plans. The objective of this study is evaluation of the status of Jahanshahr Neighborhood in Karaj city based on sustainable neighborhood development indicators. This research has been applied based on documentary method and field surveys. Also, evaluating of Jahanshahr Neighborhood of Karaj shows that it has a high level in sustainability in physical and economical dimension while a low level in cultural and social dimension. For this purpose, this neighborhood as a semi-sustainable neighborhood must take measures for development of collective spaces and efficiency of utilizing the public neighborhood spaces via collaboration of citizens and officials.
Abstract: The Kowsar dam supply water for different usages
such as drinking, industrial, agricultural and aquaculture farms
usages and located next to the city of Dehdashat in Kohgiluye and
Boyerahmad province in southern Iran. There are some towns and
villages on the Kowsar dam watersheds, which Dehdasht and
Choram are the most important and populated cities in this area. The
study was undertaken to assess the status of water quality in the
urban areas of the Kowsar dam. A total of 28 water samples were
collected from 6 stations on surface water and 1 station from
groundwater on the watershed of the Kowsar dam. All the samples
were analyzed for Cd concentration using standard procedures. The
results were compared with other national and international
standards. Among the analyzed samples, as the maximum value of
cadmium (1.131 μg/L) was observed on the station 2 at the winter
2009, all the samples analyzed were within the maximum admissible
limits by the United States Environmental Protection Agency, EU,
WHO, New Zealand , Australian, Iranian, and the Indian standards.
In general results of the present study have shown that Cd mean
values of stations No. 4, 1 and 2 with 0.5135, 0.0.4733 and 0.4573
μg/L respectively are higher than the other stations . Although Cd
level of all samples and stations have had normal values but this is
an indication of pollution potential and hazards because of human
activity and waste water of towns in the areas, which can effect on
human health implications in future. This research, therefore,
recommends the government and other responsible authorities to take
suitable improving measures in the Kowsar dam watershed-s.
Abstract: The regional innovative competitiveness is an integrating characteristic of the innovative sphere of the region. It depends on a big variety of different parameters connected with all kinds of economic entities- activities. But management parameters shouldn't be irregular, so in order to avoid it, an institutional system should be formed. This system should carry out strategic management of factors having the greatest influence on the region's innovative development. This article is devoted to different aspects of organization of the region's development institutional mechanism, which is based on management of regional innovative competitiveness parameters. The base of the analysis is innovatively-active Russian regions which were compared according to the level of the innovative competitiveness. After that the most important parameters of successful innovative development of the region were revealed with the help of the correlation-regression analysis. The results of the research could be used for investigation of the region's innovative policy.
Abstract: This paper presents a new spread-spectrum
watermarking algorithm for digital images in discrete wavelet
transform (DWT) domain. The algorithm is applied for embedding
watermarks like patient identification /source identification or
doctors signature in binary image format into host digital
radiological image for potential telemedicine applications.
Performance of the algorithm is analysed by varying the gain factor,
subband decomposition levels, and size of watermark. Simulation
results show that the proposed method achieves higher watermarking
capacity.
Abstract: This paper is to explore the relationship and the level
of stock market integration of the Asian countries, primarily
concentrating on Malaysia, Thailand, Indonesia, and South Korea,
with the world from January 1997 to December 2009. The degree of
short-run and long-run stock market integration of those Asian
countries are analyzed in order to determine the significance of series
of regional and world financial crises, liberalization policies and
other financial reforms in influencing the level of stock market
integration. To test for cointegration, this paper applies coefficient
correlation, univariate regression analyses, cointegration tests, and
vector autoregressive models (VAR) by using the four Asian stock
markets main indices and the MSCI World index. The empirical
findings from this work reveal that there is no long-run stock market
integration for the four countries and the world market. However,
there is short run integration.
Abstract: Proteins levels produced by bacteria may be increased
in stressful surroundings, such as in the presence of antibiotics. It
appears that many antimicrobial agents or antibiotics, when used at
low concentrations, have in common the ability to activate or repress
gene transcription, which is distinct from their inhibitory effect.
There have been comparatively few studies on the potential of
antibiotics or natural compounds in nature as a specific chemical
signal that can trigger a variety of biological functions. Therefore,
this study was focusing on the effect of essential oils from
Cymbopogon flexuosus and C. nardus in regulating proteins
production by Bacillus subtilis ATCC 21332. The Minimum
Inhibition Concentrations (MICs) of both essential oils on B. subtilis
were determined by using microdilution assay, resulting 0.2% and
1.56% for each C. flexuosus and C. nardus subsequently. The
bacteria were further exposed to each essential oils at concentration
of 0.01XMIC for 2 days. The proteins were then isolated and
analyzed by sodium dodecyl sulfate polyacrylamide gel
electrophoresis (SDS-PAGE). Protein profile showed that a band
with approximate size of 250 kD was appeared for the treated
bacteria with essential oils. Thus, Bacillus subtilis ATCC 21332 in
stressful condition with the presence of essential oils at low
concentration could induce the protein production.
Abstract: In pattern recognition applications the low level
segmentation and the high level object recognition are generally
considered as two separate steps. The paper presents a method that
bridges the gap between the low and the high level object
recognition. It is based on a Bayesian network representation and
network propagation algorithm. At the low level it uses hierarchical
structure of quadratic spline wavelet image bases. The method is
demonstrated for a simple circuit diagram component identification
problem.