Abstract: For positive integer s and t, the Ramsey number R(s, t)
is the least positive integer n such that for every graph G of order n, either G contains Ks as a subgraph or G contains Kt as a subgraph.
We construct the circulant graphs and use them to obtain lower bounds of some small Ramsey numbers.
Abstract: Thousands of masters athletes participate
quadrennially in the World Masters Games (WMG), yet this cohort
of athletes remains proportionately under-investigated. Due to a
growing global obesity pandemic in context of benefits of physical
activity across the lifespan, the BMI trends for this unique population
was of particular interest. The nexus between health, physical
activity and aging is complex and has raised much interest in recent
times due to the realization that a multifaceted approach is necessary
in order to counteract the obesity pandemic. By investigating age
based trends within a population adhering to competitive sport at
older ages, further insight might be gleaned to assist in understanding
one of many factors influencing this relationship.BMI was derived
using data gathered on a total of 6,071 masters athletes (51.9% male,
48.1% female) aged 25 to 91 years ( =51.5, s =±9.7), competing at
the Sydney World Masters Games (2009). Using linear and loess
regression it was demonstrated that the usual tendency for prevalence
of higher BMI increasing with age was reversed in the sample. This
trend in reversal was repeated for both male and female only sub-sets
of the sample participants, indicating the possibility of improved
prevalence of BMI with increasing age for both the sample as a
whole and these individual sub-groups.This evidence of improved
classification in one index of health (reduced BMI) for masters
athletes (when compared to the general population) implies there are
either improved levels of this index of health with aging due to
adherence to sport or possibly the reduced BMI is advantageous and
contributes to this cohort adhering (or being attracted) to masters
sport at older ages.
Abstract: The paper shows the necessity to increase the security
level for paper management in the cadastral field by using specific
graphical watermarks. Using the graphical watermarking will
increase the security in the cadastral content management;
furthermore any altered document will be validated afterwards of its
originality by checking the graphic watermark. If, by any reasons the
document is changed for counterfeiting, it is invalidated and found
that is an illegal copy due to the graphic check of the watermarking,
check made at pixel level
Abstract: When acid is pumped into damaged reservoirs for
damage removal/stimulation, distorted inflow of acid into the
formation occurs caused by acid preferentially traveling into highly
permeable regions over low permeable regions, or (in general) into
the path of least resistance. This can lead to poor zonal coverage and
hence warrants diversion to carry out an effective placement of acid.
Diversion is desirably a reversible technique of temporarily reducing
the permeability of high perm zones, thereby forcing the acid into
lower perm zones.
The uniqueness of each reservoir can pose several challenges to
engineers attempting to devise optimum and effective diversion
strategies. Diversion techniques include mechanical placement and/or
chemical diversion of treatment fluids, further sub-classified into ball
sealers, bridge plugs, packers, particulate diverters, viscous gels,
crosslinked gels, relative permeability modifiers (RPMs), foams,
and/or the use of placement techniques, such as coiled tubing (CT)
and the maximum pressure difference and injection rate (MAPDIR)
methodology.
It is not always realized that the effectiveness of diverters greatly
depends on reservoir properties, such as formation type, temperature,
reservoir permeability, heterogeneity, and physical well
characteristics (e.g., completion type, well deviation, length of
treatment interval, multiple intervals, etc.). This paper reviews the
mechanisms by which each variety of diverter functions and
discusses the effect of various reservoir properties on the efficiency
of diversion techniques. Guidelines are recommended to help
enhance productivity from zones of interest by choosing the best
methods of diversion while pumping an optimized amount of
treatment fluid. The success of an overall acid treatment often
depends on the effectiveness of the diverting agents.
Abstract: There are two types of drought as conceptual drought
and operational drought. The three parameters as the beginning, the
end and the degree of severity of the drought can be identifying in
operational drought by average precipitation in the whole region. One
of the methods classified to measure drought is Reconnaissance
Drought Index (RDI). Evapotranspiration is calculated using
Penman-Monteith method by analyzing thirty nine years prolong
climatic data. The evapotranspiration is then utilized in RDI to
classify normalized and standardized RDI. These RDI classifications
led to what kind of drought faced in Bhavnagar region on 12 month
time scale basis. The comparison between actual drought conditions
and RDI method used to find out drought are also illustrated. It can
be concluded that the index results of drought in a particular year are
same in both methods but having different index values where as
severity remain same.
Abstract: The security of power systems against malicious cyberphysical
data attacks becomes an important issue. The adversary
always attempts to manipulate the information structure of the power
system and inject malicious data to deviate state variables while
evading the existing detection techniques based on residual test. The
solutions proposed in the literature are capable of immunizing the
power system against false data injection but they might be too costly
and physically not practical in the expansive distribution network.
To this end, we define an algebraic condition for trustworthy power
system to evade malicious data injection. The proposed protection
scheme secures the power system by deterministically reconfiguring
the information structure and corresponding residual test. More
importantly, it does not require any physical effort in either microgrid
or network level. The identification scheme of finding meters being
attacked is proposed as well. Eventually, a well-known IEEE 30-bus
system is adopted to demonstrate the effectiveness of the proposed
schemes.
Abstract: Knowledge is renowned as a significant component
for sustaining competitive advantage and gives leading edge in
business. This study emphasizes towards proper and effectuate
utilization of internal and external (both either explicit or tacit)
knowledge comes from stakeholders, highly supportive to combat
with the challenges and enhance organizational productivity.
Furthermore, it proposed a model under context of IRSA framework
which facilitates the organization including flow of knowledge and
experience sharing among employees. In discussion section an
innovative model which indulges all functionality as mentioned in
analysis section.
Abstract: Many single or multispan arch bridges are
strengthened with the addition of some kind of structural support
between adjacent arches of multispan or beside the arch barrel of a
single span to increase the strength of the overall structure. It was
traditionally formed by either placing loose rubble masonry blocks
between the arches and beside the arches or using mortar or concrete
to construct a more substantial structural bond between the spans. On
the other hand backing materials are present in some existing bridges.
Existing arch assessment procedures generally ignore the effects of
backing materials. In this paper an investigation of the effects of
backing on ratings for masonry arch bridges is carried out. It is
observed that increasing the overall lateral stability of the arch
system through the inclusion of structural backing results in an
enhanced failure load by reducing the likelihood of any tension
occurring at the top of the arch.
Abstract: Many studies have focused on the nonlinear analysis
of electroencephalography (EEG) mainly for the characterization of
epileptic brain states. It is assumed that at least two states of the
epileptic brain are possible: the interictal state characterized by a
normal apparently random, steady-state EEG ongoing activity; and
the ictal state that is characterized by paroxysmal occurrence of
synchronous oscillations and is generally called in neurology, a
seizure.
The spatial and temporal dynamics of the epileptogenic process is
still not clear completely especially the most challenging aspects of
epileptology which is the anticipation of the seizure. Despite all the
efforts we still don-t know how and when and why the seizure
occurs. However actual studies bring strong evidence that the
interictal-ictal state transition is not an abrupt phenomena. Findings
also indicate that it is possible to detect a preseizure phase.
Our approach is to use the neural network tool to detect interictal
states and to predict from those states the upcoming seizure ( ictal
state). Analysis of the EEG signal based on neural networks is used
for the classification of EEG as either seizure or non-seizure. By
applying prediction methods it will be possible to predict the
upcoming seizure from non-seizure EEG.
We will study the patients admitted to the epilepsy monitoring
unit for the purpose of recording their seizures. Preictal, ictal, and
post ictal EEG recordings are available on such patients for analysis
The system will be induced by taking a body of samples then
validate it using another. Distinct from the two first ones a third body
of samples is taken to test the network for the achievement of
optimum prediction. Several methods will be tried 'Backpropagation
ANN' and 'RBF'.
Abstract: Using spatial models as a shared common basis of
information about the environment for different kinds of contextaware
systems has been a heavily researched topic in the last years.
Thereby the research focused on how to create, to update, and to
merge spatial models so as to enable highly dynamic, consistent and
coherent spatial models at large scale. In this paper however, we
want to concentrate on how context-aware applications could use this
information so as to adapt their behavior according to the situation
they are in. The main idea is to provide the spatial model
infrastructure with a situation recognition component based on
generic situation templates. A situation template is – as part of a
much larger situation template library – an abstract, machinereadable
description of a certain basic situation type, which could be
used by different applications to evaluate their situation. In this
paper, different theoretical and practical issues – technical, ethical
and philosophical ones – are discussed important for understanding
and developing situation dependent systems based on situation
templates. A basic system design is presented which allows for the
reasoning with uncertain data using an improved version of a
learning algorithm for the automatic adaption of situation templates.
Finally, for supporting the development of adaptive applications, we
present a new situation-aware adaptation concept based on
workflows.
Abstract: Policies that support entrepreneurship are keys to the
generation of new business. In Brazil, seed capital, installation of
technology parks, programs and zero interest financing, economic
subsidy as Program First Innovative Company (PRIME) are
examples of incentive policies. For the implementation of PRIME, in
particular the Brazilian Innovation Agency (FINEP) decentralized
operationalization so that business incubators could select innovative
projects. This paper analyzes the program PRIME Business Incubator
Center of the State of Sergipe (CISE) after calculating the mean and
standard deviation of the grades obtained by companies in the factors
of innovation, market potential, financial return economic, market
strategy and staff and application of the Mann-Whitney test.
Abstract: The proximate composition, physical traits and
sensory properties of beef and chicken patties incorporated with
various level of dried cornsilk (Maydis stigma) were studied. The
beef and chicken patties were formulated with either 2%, 4% or 6%
of cornsilk. Both cooked beef and chicken patties incorporated with
6% cornsilk recorded the highest protein concentration at 23.3% and
28.42%, respectively. Both cooked beef and chicken patties
containing 6% cornsilk significantly recorded the lowest
concentration of fat at 11.4% and 14.60%, respectively. Beef and
chicken patties formulated with 6% cornsilk recorded the highest
cooking yield at 80.13% and 83.03% compared to other treatments.
The inclusion of cornsilk did not change the sensory properties and
consumer acceptability of cornsilk-based beef and chicken patties.
Cornsilk fibre has been effective in improving cooking yield,
moisture and fat retention of beef and chicken patties
Abstract: The design of a pattern classifier includes an attempt
to select, among a set of possible features, a minimum subset of
weakly correlated features that better discriminate the pattern classes.
This is usually a difficult task in practice, normally requiring the
application of heuristic knowledge about the specific problem
domain. The selection and quality of the features representing each
pattern have a considerable bearing on the success of subsequent
pattern classification. Feature extraction is the process of deriving
new features from the original features in order to reduce the cost of
feature measurement, increase classifier efficiency, and allow higher
classification accuracy. Many current feature extraction techniques
involve linear transformations of the original pattern vectors to new
vectors of lower dimensionality. While this is useful for data
visualization and increasing classification efficiency, it does not
necessarily reduce the number of features that must be measured
since each new feature may be a linear combination of all of the
features in the original pattern vector. In this paper a new approach is
presented to feature extraction in which feature selection, feature
extraction, and classifier training are performed simultaneously using
a genetic algorithm. In this approach each feature value is first
normalized by a linear equation, then scaled by the associated weight
prior to training, testing, and classification. A knn classifier is used to
evaluate each set of feature weights. The genetic algorithm optimizes
a vector of feature weights, which are used to scale the individual
features in the original pattern vectors in either a linear or a nonlinear
fashion. By this approach, the number of features used in classifying
can be finely reduced.
Abstract: The aim of the work presented here was to either use
existing forest dynamic simulation models or calibrate a new one
both within the SYMFOR framework with the purpose of examining
changes in stand level basal area and functional composition in
response to selective logging considering trees > 10 cm d.b.h for two
areas of undisturbed Amazonian non flooded tropical forest in Brazil
and one in Peru. Model biological realism was evaluated for forest in
the undisturbed and selectively logged state and it was concluded that
forest dynamics were realistically represented. Results of the logging
simulation experiments showed that in relation to undisturbed forest
simulation subject to no form of harvesting intervention there was a
significant amount of change over a 90 year simulation period that
was positively proportional to the intensity of logging. Areas which
had in the dynamic equilibrium of undisturbed forest a greater
proportion of a specific ecological guild of trees known as the light
hardwoods (LHW’s) seemed to respond more favorably in terms of
less deviation but only within a specific range of baseline forest
composition beyond which compositional diversity became more
important. These finds are in line partially with practical management
experience and partiality basic systematics theory respectively.
Abstract: From environmental aspect purification of ammonia
containing wastewater is expected. High efficiency ammonia
desorption can be done from the water by air on proper temperature.
After the desorption process, ammonia can be recovered and used in
another technology. The calculation method described below give
some methods to find either the minimum column height or ammonia
rich solution of the effluent.
Abstract: A model of (4, 4) single-walled boron-nitride nanotube as a representative of armchair boron-nitride nanotubes studied. At first the structure optimization performed and then Nuclear Magnetic Resonance parameters (NMR) by Density Functional Theory (DFT) method at 11B and 15N nuclei calculated. Resulted parameters evaluation presents electrostatic environment heterogeneity along the nanotube and especially at the ends but the nuclei in a layer feel the same electrostatic environment. All of calculations carried out using Gaussian 98 Software package.
Abstract: The main objective of this study was to demonstrate that differentiation of infected and vaccinated animals (DIVA) strategy using different ELISA tests is possible when a subunit vaccine (Haemagglutinin protein) is used to prevent Avian influenza. Special emphasis was placed on the differentiation in the serological response to different components of the AIV (Nucleoprotein, Neuraminidase, Haemagglutinin, Nucleocapsid) between chickens that were vaccinated with a whole virus kill vaccine and recombinant vaccine. Furthermore, the potential use of this DIVA strategy using ELISA assays to detect Neuraminidase 1 (N1) was analyzed as strategy in countries where the field virus is H5N1 and the vaccine used is formulated with H5N2. Detection of AIV-s antibodies to any component in serum was negative for all animals on the study days 0-13. At study day 14 the titers of antibodies against Nucleoprotein (NP) and Nucleocapsid (NC) rose in the experimental groups vaccinated with Volvac® AI KV and were negatives during all the trial in the experimental groups vaccinated with a subunit H5; significant statistically differences were observed between these groups (p < 0.05). The seroconversion either Haemagglutinin or Neuraminidase was evident after 21 days post-vaccination in the experimental groups vaccinated with the respective viral fraction. Regarding the main aim of this study and according with the results that were obtained, use a combination of different ELISA test as a DIVA strategy is feasible when the vaccination is carry out with a subunit H5 vaccine. Also is possible to use the ELISA kit to detect Neuraminidase (either N1 or N2) as a DIVA concept in countries where H5N1 is present and the vaccination programs are done with H5N2 vaccine.
Abstract: The quality of a machined surface is becoming more and more important to justify the increasing demands of sophisticated component performance, longevity, and reliability. Usually, any machining operation leaves its own characteristic evidence on the machined surface in the form of finely spaced micro irregularities (surface roughness) left by the associated indeterministic characteristics of the different elements of the system: tool-machineworkpart- cutting parameters. However, one of the most influential sources in machining affecting surface roughness is the instantaneous state of tool edge. The main objective of the current work is to relate the in-process immeasurable cutting edge deformation and surface roughness to a more reliable easy-to-measure force signals using a robust non-linear time-dependent modeling regression techniques. Time-dependent modeling is beneficial when modern machining systems, such as adaptive control techniques are considered, where the state of the machined surface and the health of the cutting edge are monitored, assessed and controlled online using realtime information provided by the variability encountered in the measured force signals. Correlation between wear propagation and roughness variation is developed throughout the different edge lifetimes. The surface roughness is further evaluated in the light of the variation in both the static and the dynamic force signals. Consistent correlation is found between surface roughness variation and tool wear progress within its initial and constant regions. At the first few seconds of cutting, expected and well known trend of the effect of the cutting parameters is observed. Surface roughness is positively influenced by the level of the feed rate and negatively by the cutting speed. As cutting continues, roughness is affected, to different extents, by the rather localized wear modes either on the tool nose or on its flank areas. Moreover, it seems that roughness varies as wear attitude transfers from one mode to another and, in general, it is shown that it is improved as wear increases but with possible corresponding workpart dimensional inaccuracy. The dynamic force signals are found reasonably sensitive to simulate either the progressive or the random modes of tool edge deformation. While the frictional force components, feeding and radial, are found informative regarding progressive wear modes, the vertical (power) components is found more representative carrier to system instability resulting from the edge-s random deformation.
Abstract: Today the social marketing was constituted as a tool
of significant value in what he refers to the promotion of changes of
behaviors, attitudes end practices. With the objective of analyzing the
benefits that the social marketing can bring for the organizations that
use it the research was of the exploratory and descriptive. In the
present study the comparative method was used, through a qualitative
approach, to analyze the activities developed by three institutions:
the Recovery Center Rosa de Saron, the House of Recovery for
addicts and Teen Challenge Institute Children's Cancer of the
Wasteland (ICIA), kindred of pointing out the benefits of the social
marketing in organizations that don-t seek the profit.
Abstract: Breast carcinoma is the most common form of cancer
in women. Multicolour fluorescent in-situ hybridisation (m-FISH) is
a common method for staging breast carcinoma. The interpretation
of m-FISH images is complicated due to two effects: (i) Spectral
overlap in the emission spectra of fluorochrome marked DNA probes
and (ii) tissue autofluorescence. In this paper hyper-spectral images of
m-FISH samples are used and spectral unmixing is applied to produce
false colour images with higher contrast and better information
content than standard RGB images. The spectral unmixing is realised
by combinations of: Orthogonal Projection Analysis (OPA), Alterating
Least Squares (ALS), Simple-to-use Interactive Self-Modeling
Mixture Analysis (SIMPLISMA) and VARIMAX. These are applied
on the data to reduce tissue autofluorescence and resolve the spectral
overlap in the emission spectra. The results show that spectral unmixing
methods reduce the intensity caused by tissue autofluorescence by
up to 78% and enhance image contrast by algorithmically reducing
the overlap of the emission spectra.