Abstract: The paper presents a one-dimensional transient
mathematical model of compressible non-isothermal multicomponent
fluid mixture flow in a pipe. The set of the mass,
momentum and enthalpy conservation equations for gas phase is
solved in the model. Thermo-physical properties of multi-component
gas mixture are calculated by solving the Equation of State (EOS)
model. The Soave-Redlich-Kwong (SRK-EOS) model is chosen. Gas
mixture viscosity is calculated on the basis of the Lee-Gonzales-
Eakin (LGE) correlation. Numerical analysis of rapid gas
decompression process in rich and base natural gases is made on the
basis of the proposed mathematical model. The model is successfully
validated on the experimental data [1]. The proposed mathematical
model shows a very good agreement with the experimental data [1] in
a wide range of pressure values and predicts the decompression in
rich and base gas mixtures much better than analytical and
mathematical models, which are available from the open source
literature.
Abstract: This paper presents a Neural Network (NN) identification of icing parameters in an A340 aircraft and a reconfiguration technique to keep the A/C performance close to the performance prior to icing. Five aircraft parameters are assumed to be considerably affected by icing. The off-line training for identifying the clear and iced dynamics is based on the Levenberg-Marquard Backpropagation algorithm. The icing parameters are located in the system matrix. The physical locations of the icing are assumed at the right and left wings. The reconfiguration is based on the technique known as the control mixer approach or pseudo inverse technique. This technique generates the new control input vector such that the A/C dynamics is not much affected by icing. In the simulations, the longitudinal and lateral dynamics of an Airbus A340 aircraft model are considered, and the stability derivatives affected by icing are identified. The simulation results show the successful NN identification of the icing parameters and the reconfigured flight dynamics having the similar performance before the icing. In other words, the destabilizing icing affect is compensated.
Abstract: In the recent past, there has been an increasing interest
in applying evolutionary methods to Knowledge Discovery in
Databases (KDD) and a number of successful applications of Genetic
Algorithms (GA) and Genetic Programming (GP) to KDD have been
demonstrated. The most predominant representation of the
discovered knowledge is the standard Production Rules (PRs) in the
form 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 & 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 C (Censor) is an exception to the rule.
Such rules are employed in situations, in which the 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 the CPR expresses
important information, while the Unless C part acts only as a switch
and changes the polarity of D to ~D.
This paper presents a classification algorithm based on evolutionary
approach that discovers comprehensible rules with exceptions in the
form of CPRs.
The proposed approach has flexible chromosome encoding, where
each chromosome corresponds to a CPR. Appropriate genetic
operators are suggested and a fitness function is proposed that
incorporates the basic constraints on CPRs. Experimental results are
presented to demonstrate the performance of the proposed algorithm.
Abstract: Open Agent System platform based on High Level
Architecture is firstly proposed to support the application involving
heterogeneous agents. The basic idea is to develop different wrappers
for different agent systems, which are wrapped as federates to join a
federation. The platform is based on High Level Architecture and the
advantages for this open standard are naturally inherited, such as
system interoperability and reuse. Especially, the federal architecture
allows different federates to be heterogeneous so as to support the
integration of different agent systems. Furthermore, both implicit
communication and explicit communication between agents can be
supported. Then, as the wrapper RTI_JADE an example, the
components are discussed. Finally, the performance of RTI_JADE is
analyzed. The results show that RTI_JADE works very efficiently.
Abstract: A pot experiment was carried out under controlled
conditions to evaluate the residual effects of different doses of
atrazine+alachlor and foramsulfuron used in corn fields on the
growth and physiology of rapeseed (Brassica napus L.). A split-plot
experiment in CRD with 4 replications was used. The main plots
consisted of herbicide type (atrazine+alachlor mixture and
foramsulfuron) and the sub-plots were different residual doses of the
herbicides (0, 1%, 5%, 10%, 20%, 40%, 50% and 100%). 7 cm
diameter pots were filled with a virgin soil and seeds of rapeseed cv.
Hayola were planted in them. The pots were kept under controlled
conditions for 8 weeks after germination. At harvest, the growth
parameters and the chlorophyll contents of the leaves were
determined. The results showed that the growth of rapeseed plants
was completely prevented at the highest residual doses of the
herbicides (50 and 100 %). The growth parameters of rapeseed plants
were affected by all doses of both types of the herbicide as compared
to the controls. The residual effects of atrazine+alachlor mixture in
reducing the growth parameters of rapeseed were more pronounced
as compared to the residual effects of foramsulfuron alone.
Abstract: Radio propagation from point-to-point is affected by
the physical channel in many ways. A signal arriving at a destination
travels through a number of different paths which are referred to as
multi-paths. Research in this area of wireless communications has
progressed well over the years with the research taking different
angles of focus. By this is meant that some researchers focus on
ways of reducing or eluding Multipath effects whilst others focus on
ways of mitigating the effects of Multipath through compensation
schemes. Baseband processing is seen as one field of signal
processing that is cardinal to the advancement of software defined
radio technology. This has led to wide research into the carrying out
certain algorithms at baseband. This paper considers compensating
for Multipath for Frequency Modulated signals. The compensation
process is carried out at Radio frequency (RF) and at Quadrature
baseband (QBB) and the results are compared. Simulations are
carried out using MatLab so as to show the benefits of working at
lower QBB frequencies than at RF.
Abstract: Wireless Sensor Network (WSN) comprises of sensor
nodes which are designed to sense the environment, transmit sensed
data back to the base station via multi-hop routing to reconstruct
physical phenomena. Since physical phenomena exists significant
overlaps between temporal redundancy and spatial redundancy, it is
necessary to use Redundancy Suppression Algorithms (RSA) for sensor
node to lower energy consumption by reducing the transmission
of redundancy. A conventional algorithm of RSAs is threshold-based
RSA, which sets threshold to suppress redundant data. Although
many temporal and spatial RSAs are proposed, temporal-spatial RSA
are seldom to be proposed because it is difficult to determine when
to utilize temporal or spatial RSAs. In this paper, we proposed a
novel temporal-spatial redundancy suppression algorithm, Codebookbase
Redundancy Suppression Mechanism (CRSM). CRSM adopts
vector quantization to generate a codebook, which is easily used to
implement temporal-spatial RSA. CRSM not only achieves power
saving and reliability for WSN, but also provides the predictability
of network lifetime. Simulation result shows that the network lifetime
of CRSM outperforms at least 23% of that of other RSAs.
Abstract: Einstein vacuum equations, that is a system of nonlinear
partial differential equations (PDEs) are derived from Weyl metric
by using relation between Einstein tensor and metric tensor. The
symmetries of Einstein vacuum equations for static axisymmetric
gravitational fields are obtained using the Lie classical method. We
have examined the optimal system of vector fields which is further
used to reduce nonlinear PDE to nonlinear ordinary differential
equation (ODE). Some exact solutions of Einstein vacuum equations
in general relativity are also obtained.
Abstract: This paper presents a comparative analysis of a new
unsupervised PCA-based technique for steel plates texture segmentation
towards defect detection. The proposed scheme called Variance
Based Component Analysis or VBCA employs PCA for feature
extraction, applies a feature reduction algorithm based on variance of
eigenpictures and classifies the pixels as defective and normal. While
the classic PCA uses a clusterer like Kmeans for pixel clustering,
VBCA employs thresholding and some post processing operations to
label pixels as defective and normal. The experimental results show
that proposed algorithm called VBCA is 12.46% more accurate and
78.85% faster than the classic PCA.
Abstract: Mostly the systems are dealing with time varying
signals. The Power efficiency can be achieved by adapting the system
activity according to the input signal variations. In this context
an adaptive rate filtering technique, based on the level crossing sampling
is devised. It adapts the sampling frequency and the filter order
by following the input signal local variations. Thus, it correlates the
processing activity with the signal variations. Interpolation is required
in the proposed technique. A drastic reduction in the interpolation
error is achieved by employing the symmetry during the interpolation
process. Processing error of the proposed technique is
calculated. The computational complexity of the proposed filtering
technique is deduced and compared to the classical one. Results
promise a significant gain of the computational efficiency and hence
of the power consumption.
Abstract: Soft topological spaces are considered as mathematical tools for dealing with uncertainties, and a fuzzy topological space is a special case of the soft topological space. The purpose of this paper is to study soft topological spaces. We introduce some new concepts in soft topological spaces such as soft first-countable spaces, soft second-countable spaces and soft separable spaces, and some basic properties of these concepts are explored.
Abstract: A clustering is process to identify a homogeneous
groups of object called as cluster. Clustering is one interesting topic
on data mining. A group or class behaves similarly characteristics.
This paper discusses a robust clustering process for data images with
two reduction dimension approaches; i.e. the two dimensional
principal component analysis (2DPCA) and principal component
analysis (PCA). A standard approach to overcome this problem is
dimension reduction, which transforms a high-dimensional data into
a lower-dimensional space with limited loss of information. One of
the most common forms of dimensionality reduction is the principal
components analysis (PCA). The 2DPCA is often called a variant of
principal component (PCA), the image matrices were directly treated
as 2D matrices; they do not need to be transformed into a vector so
that the covariance matrix of image can be constructed directly using
the original image matrices. The decomposed classical covariance
matrix is very sensitive to outlying observations. The objective of
paper is to compare the performance of robust minimizing vector
variance (MVV) in the two dimensional projection PCA (2DPCA)
and the PCA for clustering on an arbitrary data image when outliers
are hiden in the data set. The simulation aspects of robustness and
the illustration of clustering images are discussed in the end of
paper
Abstract: Writer identification is one of the areas in pattern
recognition that attract many researchers to work in, particularly in
forensic and biometric application, where the writing style can be
used as biometric features for authenticating an identity. The
challenging task in writer identification is the extraction of unique
features, in which the individualistic of such handwriting styles
can be adopted into bio-inspired generalized global shape for
writer identification. In this paper, the feasibility of generalized
global shape concept of complimentary binding in Artificial
Immune System (AIS) for writer identification is explored. An
experiment based on the proposed framework has been conducted
to proof the validity and feasibility of the proposed approach for
off-line writer identification.
Abstract: This paper represents an investigation on how exploiting multiple transmit antennas by OFDM based wireless LAN subscribers can mitigate physical layer error rate. Then by comparing the Wireless LANs that utilize spatial diversity techniques with the conventional ones it will reveal how PHY and TCP throughputs behaviors are ameliorated. In the next step it will assess the same issues based on a cellular context operation which is mainly introduced as an innovated solution that beside a multi cell operation scenario benefits spatio-temporal signaling schemes as well. Presented simulations will shed light on the improved performance of the wide range and high quality wireless LAN services provided by the proposed approach.
Abstract: Place is a where dimension formed by people-s
relationship with physical settings, individual and group activities,
and meanings. 'Place Attachment', 'Place Identity'and 'Sense of
Place' are some concepts that could describe the quality of people-s
relationships with a place. The concept of Sense of place is used in
studying human-place bonding, attachment and place meaning. Sense
of Place usually is defined as an overarching impression
encompassing the general ways in which people feel about places,
senses it, and assign concepts and values to it. Sense of place is
highlighted in this article as one of the prevailing concepts among
place-based researches. Considering dimensions of sense of place has
always been beneficial for investigating public place attachment and
pro-environmental attitudes towards these places. The creation or
preservation of Sense of place is important in maintaining the quality
of the environment as well as the integrity of human life within it.
While many scholars argued that sense of place is a vague concept,
this paper will summarize and analyze the existing seminal literature.
Therefore, in this paper first the concept of Sense of place and its
characteristics will be examined afterward the scales of Sense of
place will be reviewed and the factors that contribute to form Sense
of place will be evaluated and finally Place Attachment as an
objective dimension for measuring the sense of place will be
described.
Abstract: The seemingly ambiguous title of this paper – use of the terms maturity and innovation in concord – signifies the imperative of every organisation within the competitive domain. Where organisational maturity and innovativeness were traditionally considered antonymous, the assimilation of these two seemingly contradictory notions is fundamental to the assurance of long-term organisational prosperity. Organisations are required, now more than ever, to grow and mature their innovation capability – rending consistent innovative outputs. This paper describes research conducted to consolidate the principles of innovation and identify the fundamental components that constitute organisational innovation capability. The process of developing an Innovation Capability Maturity Model is presented. A brief description is provided of the basic components of the model, followed by a description of the case studies that were conducted to evaluate the model. The paper concludes with a summary of the findings and potential future research.
Abstract: Emerging Adulthood, the period during ages 18 to 25,
is a new conceptualitation proposed by Arnett which is especially
prevalent in the industrialized countries. Turkey is basically a
developing country having a young population structure.
Investigating the presence of such a life period in such a culture
might be helpful in understanding educational and psychological
needs of people who are in their twenties. With the aim of
investigating Emerging Adulthood in Turkey, a well-known
instrument (IDEA, 2003) was adapted to Turkish language and
Turkish culture. The scale was administered to 296 participants
between 15 and 34 ages and validity and reliability were conducted.
Exploratory factor analysis revealed three subscales. Reliability
coefficients of the scale (Cronbach a) was found as .69. Test-retest
reliability coefficients was found for the scale as .81. Finally, “The
IDEA" with 20 items was obtained to be used in the Turkish
population. The instrument is ready to be administered among
Turkish young people for the investigation of transition to adulthood,
and whether such a emerging adulthood period really existed.
Abstract: The automatic classification of non stationary signals is an important practical goal in several domains. An essential classification task is to allocate the incoming signal to a group associated with the kind of physical phenomena producing it. In this paper, we present a modular system composed by three blocs: 1) Representation, 2) Dimensionality reduction and 3) Classification. The originality of our work consists in the use of a new wavelet called "Ben wavelet" in the representation stage. For the dimensionality reduction, we propose a new algorithm based on the random projection and the principal component analysis.
Abstract: Starting from the basic pillars of the supportability
analysis this paper queries its characteristics in LCI (Life Cycle
Integration) environment. The research methodology contents a
review of modern logistics engineering literature with the objective to
collect and synthesize the knowledge relating to standards of
supportability design in e-logistics environment. The results show
that LCI framework has properties which are in fully compatibility
with the requirement of simultaneous logistics support and productservice
bundle design. The proposed approach is a contribution to the
more comprehensive and efficient supportability design process.
Also, contributions are reflected through a greater consistency of
collected data, automated creation of reports suitable for different
analysis, as well as the possibility of their customization according
with customer needs. In addition to this, convenience of this approach
is its practical use in real time. In a broader sense, LCI allows
integration of enterprises on a worldwide basis facilitating electronic
business.
Abstract: The previous researches focused on the influence of
anthropogenic greenhouse gases exerting global warming, but not
consider whether desert sand may warm the planet, this could be
improved by accounting for sand's physical and geometric properties.
Here we show, sand particles (because of their geometry) at the desert
surface form an extended surface of up to 1 + π/4 times the planar area
of the desert that can contact sunlight, and at shallow depths of the
desert form another extended surface of at least 1 + π times the planar
area that can contact air. Based on this feature, an enhanced heat
exchange system between sunlight, desert sand, and air in the spaces
between sand particles could be built up automatically, which can
increase capture of solar energy, leading to rapid heating of the sand
particles, and then the heating of sand particles will dramatically heat
the air between sand particles. The thermodynamics of deserts may
thus have contributed to global warming, especially significant to
future global warming if the current desertification continues to
expand.