Abstract: The paper provides an in-depth tutorial of mathematical
construction of maximal length sequences (m-sequences) via primitive
polynomials and how to map the same when implemented in
shift registers. It is equally important to check whether a polynomial
is primitive or not so as to get proper m-sequences. A fast method to
identify primitive polynomials over binary fields is proposed where
the complexity is considerably less in comparison with the standard
procedures for the same purpose.
Abstract: This paper deals with the problem of constructing
constraints in non safe Petri Nets and then reducing the number of the
constructed constraints. In a system, assigning some linear constraints
to forbidden states is possible. Enforcing these constraints on the
system prevents it from entering these states. But there is no a
systematic method for assigning constraints to forbidden states in non
safe Petri Nets. In this paper a useful method is proposed for
constructing constraints in non safe Petri Nets. But when the number of these constraints is large enforcing them on the system may complicate the Petri Net model. So, another method is proposed for reducing the number of constructed constraints.
Abstract: To learn about China-s future energy demand, this paper first proposed GM(1,1) model group based on recursive solutions of parameters estimation, setting up a general solving-algorithm of the model group. This method avoided the problems occurred on the past researches that remodeling, loss of information and large amount of calculation. This paper established respectively all-data-GM(1,1), metabolic GM(1,1) and new information GM (1,1)model according to the historical data of energy consumption in China in the year 2005-2010 and the added data of 2011, then modeling, simulating and comparison of accuracies we got the optimal models and to predict. Results showed that the total energy demand of China will be 37.2221 billion tons of equivalent coal in 2012 and 39.7973 billion tons of equivalent coal in 2013, which are as the same as the overall planning of energy demand in The 12th Five-Year Plan.
Abstract: Bonding has become a routine procedure in several
dental specialties – from prosthodontics to conservative dentistry and
even orthodontics. In many of these fields it is important to be able to
investigate the bonded interfaces to assess their quality. All currently
employed investigative methods are invasive, meaning that samples
are destroyed in the testing procedure and cannot be used again. We
have investigated the interface between human enamel and bonded
ceramic brackets non-invasively, introducing a combination of new
investigative methods – optical coherence tomography (OCT),
fluorescence OCT and confocal microscopy (CM). Brackets were
conventionally bonded on conditioned buccal surfaces of teeth. The
bonding was assessed using these methods. Three dimensional
reconstructions of the detected material defects were developed using
manual and semi-automatic segmentation. The results clearly prove
that OCT, fluorescence OCT and CM are useful in orthodontic
bonding investigations.
Abstract: Decomposition processes take place in landfill
generate leachates that can be categorized mainly of acetogenic and
methanogenic in nature. BOD:COD ratio computed in this study for a
landfill site over a 3 years duration revealed as a good indicator to
identify acetogenic leachate from methanogenic leachate. Correlation
relationships to predict pollutant level taking into consideration of
climatic condition are derived.
Abstract: This study is designed to investigate errors emerged in written texts produced by 30 Turkish EFL learners with an explanatory, and thus, qualitative perspective. Erroneous language elements were identified by the researcher first and then their grammaticality and intelligibility were checked by five native speakers of English. The analysis of the data showed that it is difficult to claim that an error stems from only one single factor since different features of an error are triggered by different factors. Our findings revealed two different types of errors: those which stem from the interference of L1 with L2 and those which are developmental ones. The former type contains more global errors whereas the errors in latter type are more intelligible.
Abstract: Power loss reduction is one of the main targets in power industry and so in this paper, the problem of finding the optimal configuration of a radial distribution system for loss reduction is considered. Optimal reconfiguration involves the selection of the best set of branches to be opened ,one each from each loop, for reducing resistive line losses , and reliving overloads on feeders by shifting the load to adjacent feeders. However ,since there are many candidate switching combinations in the system ,the feeder reconfiguration is a complicated problem. In this paper a new approach is proposed based on a simple optimum loss calculation by determining optimal trees of the given network. From graph theory a distribution network can be represented with a graph that consists a set of nodes and branches. In fact this problem can be viewed as a problem of determining an optimal tree of the graph which simultaneously ensure radial structure of each candidate topology .In this method the refined genetic algorithm is also set up and some improvements of algorithm are made on chromosome coding. In this paper an implementation of the algorithm presented by [7] is applied by modifying in load flow program and a comparison of this method with the proposed method is employed. In [7] an algorithm is proposed that the choice of the switches to be opened is based on simple heuristic rules. This algorithm reduce the number of load flow runs and also reduce the switching combinations to a fewer number and gives the optimum solution. To demonstrate the validity of these methods computer simulations with PSAT and MATLAB programs are carried out on 33-bus test system. The results show that the performance of the proposed method is better than [7] method and also other methods.
Abstract: In this paper, an improved edge detection algorithm
based on fuzzy combination of mathematical morphology and
wavelet transform is proposed. The combined method is proposed to
overcome the limitation of wavelet based edge detection and
mathematical morphology based edge detection in noisy images.
Experimental results show superiority of the proposed method, as
compared to the traditional Prewitt, wavelet based and morphology
based edge detection methods. The proposed method is an effective
edge detection method for noisy image and keeps clear and
continuous edges.
Abstract: In this paper, based on linear matrix inequality (LMI), by using Lyapunov functional theory, the exponential stability criterion is obtained for a class of uncertain Takagi-Sugeno fuzzy Hopfield neural networks (TSFHNNs) with time delays. Here we choose a generalized Lyapunov functional and introduce a parameterized model transformation with free weighting matrices to it, these techniques lead to generalized and less conservative stability condition that guarantee the wide stability region. Finally, an example is given to illustrate our results by using MATLAB LMI toolbox.
Abstract: The ITE Project is a project that has 1800 km length
and across the Turkey's land through east to west. The project of
pipeline enters geographically from Iran to Doğubayazit (Turkey) in
the east, exits to Greece from Ipsala province of Turkey in the west.
This project is the one of the international projects in such scale that
provides the natural gas of Iran and Caspian Sea through the
European continent. In this investigation, some information will be
given about the methods used to verify the direction of the pipeline
and the technical properties of the results obtained. The cost of
project itself entirely depends on the direction of the pipeline which
would be as short as possible and the specifications of the land cover.
Production standards of 1/2000 scaled digital orthophoto and vectoral
maps as a results of the use of map production materials and methods
(such as high resolution satellite images, and digital aerial images
captured from digital aerial cameras), will also be given in this report.
According to Turkish national map production standards, TM
((Transversal Mercator, 3 degree) projection is used for large scale
map and UTM (Universal Transversal Mercator, 6 degree) is used for
small scale map production standards. Some information is also given
about the projection used in the ITE natural gas pipeline project.
Abstract: Data mining uses a variety of techniques each of which is useful for some particular task. It is important to have a deep understanding of each technique and be able to perform sophisticated analysis. In this article we describe a tool built to simulate a variation of the Kohonen network to perform unsupervised clustering and support the entire data mining process up to results visualization. A graphical representation helps the user to find out a strategy to optmize classification by adding, moving or delete a neuron in order to change the number of classes. The tool is also able to automatically suggest a strategy for number of classes optimization.The tool is used to classify macroeconomic data that report the most developed countries? import and export. It is possible to classify the countries based on their economic behaviour and use an ad hoc tool to characterize the commercial behaviour of a country in a selected class from the analysis of positive and negative features that contribute to classes formation.
Abstract: Kepsut-Dursunbey volcanic field (KDVF) is located
in NW Turkey and contains various products of the post-collisional
Neogene magmatic activity. Two distinct volcanic suites have been
recognized; the Kepsut volcanic suite (KVS) and the Dursunbey
volcanic suite (DVS). The KVS includes basaltic trachyandesitebasaltic
andesite-andesite lavas and associated pyroclastic rocks. The
DVS consists of dacite-rhyodacite lavas and extensive pumice-ash
fall and flow deposits. Petrographical features (i.e. existence of
xenocrysts, glomerocrysts, and mixing-compatible textures) and
mineral chemistry of phenocryst assemblages of both suites provide
evidence for magma mixing/AFC. Calculated crystallization
pressures and temperatures give values of 5.7–7.0 kbar and 927–982
°C for the KVS and 3.7–5.3 kbar and 783-787°C for the DVS,
indicating separate magma reservoirs and crystallization in magma
chambers at deep and mid crustal levels, respectively. These
observations support the establishment and evolution of KDVF
magma system promoted by episodic basaltic inputs which may
generate and mix with crustal melts.
Abstract: Chaos and fractals are novel fields of physics and mathematics showing up a new way of universe viewpoint and creating many ideas to solve several present problems. In this paper, a novel algorithm based on the chaotic sequence generator with the highest ability to adapt and reach the global optima is proposed. The adaptive ability of proposal algorithm is flexible in 2 steps. The first one is a breadth-first search and the second one is a depth-first search. The proposal algorithm is examined by 2 functions, the Camel function and the Schaffer function. Furthermore, the proposal algorithm is applied to optimize training Multilayer Neural Networks.
Abstract: In the recent past Learning Classifier Systems have
been successfully used for data mining. Learning Classifier System
(LCS) is basically a machine learning technique which combines
evolutionary computing, reinforcement learning, supervised or
unsupervised learning and heuristics to produce adaptive systems. A
LCS learns by interacting with an environment from which it
receives feedback in the form of numerical reward. Learning is
achieved by trying to maximize the amount of reward received. All
LCSs models more or less, comprise four main components; a finite
population of condition–action rules, called classifiers; the
performance component, which governs the interaction with the
environment; the credit assignment component, which distributes the
reward received from the environment to the classifiers accountable
for the rewards obtained; the discovery component, which is
responsible for discovering better rules and improving existing ones
through a genetic algorithm. The concatenate of the production rules
in the LCS form the genotype, and therefore the GA should operate
on a population of classifier systems. This approach is known as the
'Pittsburgh' Classifier Systems. Other LCS that perform their GA at
the rule level within a population are known as 'Mitchigan' Classifier
Systems. The most predominant representation of the discovered
knowledge is the standard production rules (PRs) in the form of IF P
THEN D. The PRs, however, are unable to handle exceptions and do
not exhibit variable precision. The Censored Production Rules
(CPRs), an extension of PRs, were proposed by Michalski and
Winston that exhibit variable precision and supports an efficient
mechanism for handling exceptions. A CPR is an augmented
production rule of the form: IF P THEN D UNLESS C, where
Censor C is an exception to the rule. Such rules are employed in
situations, in which conditional statement IF P THEN D holds
frequently and the assertion C holds rarely. By using a rule of this
type we are free to ignore the exception conditions, when the
resources needed to establish its presence are tight or there is simply
no information available as to whether it holds or not. Thus, the IF P
THEN D part of CPR expresses important information, while the
UNLESS C part acts only as a switch and changes the polarity of D
to ~D. In this paper Pittsburgh style LCSs approach is used for
automated discovery of CPRs. An appropriate encoding scheme is
suggested to represent a chromosome consisting of fixed size set of
CPRs. Suitable genetic operators are designed for the set of CPRs
and individual CPRs and also appropriate fitness function is proposed
that incorporates basic constraints on CPR. Experimental results are
presented to demonstrate the performance of the proposed learning
classifier system.
Abstract: In this paper, the effect of atmospheric turbulence on
bit error probability in free-space optical CDMA scheme with
Sequence Inverse Keyed (SIK) optical correlator receiver is analyzed.
Here Intensity Modulation scheme is considered for transmission.
The turbulence induced fading is described by the newly introduced
gamma-gamma pdf[1] as a tractable mathematical model for
atmospheric turbulence. Results are evaluated with Gold and Kasami
code & it is shown that Gold sequence can be used for more
efficient transmission than Kasami sequence in an atmospheric
turbulence channel.
Abstract: In this paper, a new time-delay estimation
technique based on the cross IB-energy operator [5] is
introduced. This quadratic energy detector measures how
much a signal is present in another one. The location of the
peak of the energy operator, corresponding to the maximum of
interaction between the two signals, is the estimate of the
delay. The method is a fully data-driven approach. The
discrete version of the continuous-time form of the cross IBenergy
operator, for its implementation, is presented. The
effectiveness of the proposed method is demonstrated on real
underwater acoustic signals arriving from targets and the
results compared to the cross-correlation method.
Abstract: 17α-ethynylestradiol (EE2) is a synthetic estrogen
used as a key ingredient in an oral contraceptives pill. EE2 is an
endocrine disrupting compound, high in estrogenic potency.
Although EE2 exhibits low degree of biodegradability with common
microorganisms in wastewater treatment plants (WWTPs), this
compound can be biotransformed by ammonia-oxidizing bacteria
(AOB) via a co-metabolism mechanism in WWTPs. This study
aimed to investigate the effect of real wastewater on
biotransformation of EE2 by AOB. A preliminary experiment on the
effect of nitrite and pH levels on abiotic transformation of EE2
suggested that the abiotic transformation occurred at only pH
Abstract: We aimed to investigate how can target and optimize
pulmonary delivery distribution by changing physicochemical
characteristics of instilled liquid.Therefore, we created a new liquids
group:
a. eligible for desired distribution within lung because of
assorted physicochemical characteristics
b. capable of being augmented with a broad range of
chemicals inertly
c. no interference on respiratory function
d. compatible with airway surface liquid
We developed forty types of new liquid,were composed of
Carboxymethylcellulose sodium,Glycerin and different types of
Polysorbates.Viscosity was measured using a Programmable
Rheometer and surface tension by KRUSS Tensiometer.We
subsequently examined the liquids and delivery protocols by simple
and branched glass capillary tube models of airways.Eventually,we
explored pulmonary distribution of liquids being augmented with
technetium-99m in mechanically ventilated rabbits.We used a single
head large field of view gamma camera.Kinematic viscosity between
0.265Stokes and 0.289Stokes,density between 1g/cm3 and 1.5g/cm3
and surface tension between 25dyn/cm and 35dyn/cm were the most
acceptable.
Abstract: The temporal nature of negative selection is an under exploited area. In a negative selection system, newly generated antibodies go through a maturing phase, and the survivors of the phase then wait to be activated by the incoming antigens after certain number of matches. These without having enough matches will age and die, while these with enough matches (i.e., being activated) will become active detectors. A currently active detector may also age and die if it cannot find any match in a pre-defined (lengthy) period of time. Therefore, what matters in a negative selection system is the dynamics of the involved parties in the current time window, not the whole time duration, which may be up to eternity. This property has the potential to define the uniqueness of negative selection in comparison with the other approaches. On the other hand, a negative selection system is only trained with “normal" data samples. It has to learn and discover unknown “abnormal" data patterns on the fly by itself. Consequently, it is more appreciate to utilize negation selection as a system for pattern discovery and recognition rather than just pattern recognition. In this paper, we study the potential of using negative selection in discovering unknown temporal patterns.
Abstract: Dredged sediment (DS) was utilized as source of
silt-clay and organic matter in artificially prepared eelgrass substrates with mountain sand (MS) as the sand media. Addition of DS showed
improved growth of eelgrass in the mixed substrates. Increase in added
DS up to 15% silt-clay showed increased shoot growth but additional
DS in 20% silt-clay mixture didn-t result to further increase in eelgrass
growth. Improved root establishment were also found for plants in pots
with added DS as shown by the increased resistance to uprooting, increased number of rhizome nodes and longer roots. Results demonstrated that addition of DS may be beneficial to eelgrass up to a
certain extent only and too much of it might be harmful to eelgrass plants.