Abstract: For the electrical metrics that describe photovoltaic
cell performance are inherently multivariate in nature, use of a
univariate, or one variable, statistical process control chart can have
important limitations. Development of a comprehensive process
control strategy is known to be significantly beneficial to reducing
process variability that ultimately drives up the manufacturing cost
photovoltaic cells. The multivariate moving average or MMA chart,
is applied to the electrical metrics of photovoltaic cells to illustrate
the improved sensitivity on process variability this method of control
charting offers. The result show the ability of the MMA chart to
expand to as any variables as needed, suggests an application
with multiple photovoltaic electrical metrics being used in
concert to determine the processes state of control.
Abstract: This paper focuses on cost and profit analysis of
single-server Markovian queuing system with two priority classes. In
this paper, functions of total expected cost, revenue and profit of the
system are constructed and subjected to optimization with respect to
its service rates of lower and higher priority classes. A computing
algorithm has been developed on the basis of fast converging
numerical method to solve the system of non linear equations formed
out of the mathematical analysis. A novel performance measure of
cost and profit analysis in view of its economic interpretation for the
system with priority classes is attempted to discuss in this paper. On
the basis of computed tables observations are also drawn to enlighten
the variational-effect of the model on the parameters involved
therein.
Abstract: In this paper, we generalize some propositions in [C.Z. Wang, D.G. Chen, A short note on some properties of rough groups, Comput. Math. Appl. 59(2010)431-436.] and we give some equivalent conditions for rough subgroups. The notion of minimal upper rough subgroups is introduced and a equivalent characterization is given, which implies the rough version of Lagranges Theorem.
Abstract: Many works have been carried out to compare the
efficiency of several goodness of fit procedures for identifying
whether or not a particular distribution could adequately explain a
data set. In this paper a study is conducted to investigate the power
of several goodness of fit tests such as Kolmogorov Smirnov (KS),
Anderson-Darling(AD), Cramer- von- Mises (CV) and a proposed
modification of Kolmogorov-Smirnov goodness of fit test which
incorporates a variance stabilizing transformation (FKS). The
performances of these selected tests are studied under simple
random sampling (SRS) and Ranked Set Sampling (RSS). This
study shows that, in general, the Anderson-Darling (AD) test
performs better than other GOF tests. However, there are some
cases where the proposed test can perform as equally good as the
AD test.
Abstract: In practice, wireless networks has the property that
the signal strength attenuates with respect to the distance from the
base station, it could be better if the nodes at two hop away are
considered for better quality of service. In this paper, we propose a
procedure to identify delay preserving substructures for a given
wireless ad-hoc network using a new graph operation G 2 – E (G) =
G* (Edge difference of square graph of a given graph and the
original graph). This operation helps to analyze some induced
substructures, which preserve delay in communication among them.
This operation G* on a given graph will induce a graph, in which 1-
hop neighbors of any node are at 2-hop distance in the original
network. In this paper, we also identify some delay preserving
substructures in G*, which are (i) set of all nodes, which are mutually
at 2-hop distance in G that will form a clique in G*, (ii) set of nodes
which forms an odd cycle C2k+1 in G, will form an odd cycle in G*
and the set of nodes which form a even cycle C2k in G that will form
two disjoint companion cycles ( of same parity odd/even) of length k
in G*, (iii) every path of length 2k+1 or 2k in G will induce two
disjoint paths of length k in G*, and (iv) set of nodes in G*, which
induces a maximal connected sub graph with radius 1 (which
identifies a substructure with radius equal 2 and diameter at most 4 in
G). The above delay preserving sub structures will behave as good
clusters in the original network.
Abstract: The detection of outliers is very essential because of
their responsibility for producing huge interpretative problem in
linear as well as in nonlinear regression analysis. Much work has
been accomplished on the identification of outlier in linear
regression, but not in nonlinear regression. In this article we propose
several outlier detection techniques for nonlinear regression. The
main idea is to use the linear approximation of a nonlinear model and
consider the gradient as the design matrix. Subsequently, the
detection techniques are formulated. Six detection measures are
developed that combined with three estimation techniques such as the
Least-Squares, M and MM-estimators. The study shows that among
the six measures, only the studentized residual and Cook Distance
which combined with the MM estimator, consistently capable of
identifying the correct outliers.
Abstract: Many systems in the natural world exhibit chaos or non-linear behavior, the complexity of which is so great that they appear to be random. Identification of chaos in experimental data is essential for characterizing the system and for analyzing the predictability of the data under analysis. The Lyapunov exponents provide a quantitative measure of the sensitivity to initial conditions and are the most useful dynamical diagnostic for chaotic systems. However, it is difficult to accurately estimate the Lyapunov exponents of chaotic signals which are corrupted by a random noise. In this work, a method for estimation of Lyapunov exponents from noisy time series using unscented transformation is proposed. The proposed methodology was validated using time series obtained from known chaotic maps. In this paper, the objective of the work, the proposed methodology and validation results are discussed in detail.
Abstract: Let F(x, y) = ax2 + bxy + cy2 be a positive definite
binary quadratic form with discriminant Δ whose base points lie on
the line x = -1/m for an integer m ≥ 2, let p be a prime number
and let Fp be a finite field. Let EF : y2 = ax3 + bx2 + cx be an
elliptic curve over Fp and let CF : ax3 + bx2 + cx ≡ 0(mod p) be
the cubic congruence corresponding to F. In this work we consider
some properties of positive definite quadratic forms, elliptic curves
and cubic congruences.
Abstract: ANNARIMA that combines both autoregressive integrated moving average (ARIMA) model and artificial neural network (ANN) model is a valuable tool for modeling and forecasting nonlinear time series, yet the over-fitting problem is more likely to occur in neural network models. This paper provides a hybrid methodology that combines both radial basis function (RBF) neural network and auto regression (AR) model based on binomial smoothing (BS) technique which is efficient in data processing, which is called BSRBFAR. This method is examined by using the data of Canadian Lynx data. Empirical results indicate that the over-fitting problem can be eased using RBF neural network based on binomial smoothing which is called BS-RBF, and the hybrid model–BS-RBFAR can be an effective way to improve forecasting accuracy achieved by BSRBF used separately.
Abstract: S-boxes (Substitution boxes) are keystones of modern
symmetric cryptosystems (block ciphers, as well as stream ciphers).
S-boxes bring nonlinearity to cryptosystems and strengthen their
cryptographic security. They are used for confusion in data security
An S-box satisfies the strict avalanche criterion (SAC), if and only if
for any single input bit of the S-box, the inversion of it changes each
output bit with probability one half. If a function (cryptographic
transformation) is complete, then each output bit depends on all of
the input bits. Thus, if it were possible to find the simplest Boolean
expression for each output bit in terms of the input bits, each of these
expressions would have to contain all of the input bits if the function
is complete. From some important properties of S-box, the most
interesting property SAC (Strict Avalanche Criterion) is presented
and to analyze this property three analysis methods are proposed.
Abstract: The purpose of the present paper is to study the concept
of fuzzy bi-ideals in ternary semirings. We give some characterizations of fuzzy bi-ideals. Characterizations of regular ternary semirings
are provided.
Abstract: In this paper we study the boundedness properties of
certain oscillatory integrals with polynomial phase. We obtain sharp
estimates for these oscillatory integrals. By the virtue of these
estimates and extrapolation we obtain Lp boundedness for these
oscillatory integrals under rather weak size conditions on the kernel
function.
Abstract: Implicit equations play a crucial role in Engineering.
Based on this importance, several techniques have been applied to
solve this particular class of equations. When it comes to practical
applications, in general, iterative procedures are taken into account.
On the other hand, with the improvement of computers, other
numerical methods have been developed to provide a more
straightforward methodology of solution. Analytical exact approaches
seem to have been continuously neglected due to the difficulty
inherent in their application; notwithstanding, they are indispensable
to validate numerical routines. Lagrange-s Inversion Theorem is a
simple mathematical tool which has proved to be widely applicable to
engineering problems. In short, it provides the solution to implicit
equations by means of an infinite series. To show the validity of this
method, the tree-parameter infiltration equation is, for the first time,
analytically and exactly solved. After manipulating these series,
closed-form solutions are presented as H-functions.
Abstract: In the present communication, the existing measures of
fuzzy entropy are reviewed. A generalized parametric exponential
fuzzy entropy is defined.Our study of the four essential and some
other properties of the proposed measure, clearly establishes the
validity of the measure as an entropy.
Abstract: In this paper we consider the approximate Jordan maps and boundedness of these maps. Also we investigate the stability of approximate Jordan maps and prove some stability properties for approximate Jordan maps.
Abstract: In this paper, a fuzzy algorithm and a fuzzy multicriteria
decision framework are developed and used for a practical
question of optimizing biofuels policy making. The methodological
framework shows how to incorporate fuzzy set theory in a decision
process of finding a sustainable biofuels policy among several policy
options. Fuzzy set theory is used here as a tool to deal with
uncertainties of decision environment, vagueness and ambiguities of
policy objectives, subjectivities of human assessments and imprecise
and incomplete information about the evaluated policy instruments.
Abstract: Biclustering aims at identifying several biclusters that
reveal potential local patterns from a microarray matrix. A bicluster is
a sub-matrix of the microarray consisting of only a subset of genes
co-regulates in a subset of conditions. In this study, we extend the
motif of subspace clustering to present a K-biclusters clustering (KBC)
algorithm for the microarray biclustering issue. Besides minimizing
the dissimilarities between genes and bicluster centers within all
biclusters, the objective function of the KBC algorithm additionally
takes into account how to minimize the residues within all biclusters
based on the mean square residue model. In addition, the objective
function also maximizes the entropy of conditions to stimulate more
conditions to contribute the identification of biclusters. The KBC
algorithm adopts the K-means type clustering process to efficiently
make the partition of K biclusters be optimized. A set of experiments
on a practical microarray dataset are demonstrated to show the
performance of the proposed KBC algorithm.
Abstract: Two constructions of unit-memory binary convolutional
codes from linear block codes over the finite semi-local ring F2r +vF2r , where v2 = v, are presented. In both cases, if the linear block code is systematic, then the resulting convolutional encoder
is systematic, minimal, basic and non-catastrophic. The Hamming
free distance of the convolutional code is bounded below by the
minimum Hamming distance of the block code. New examples of
binary convolutional codes that meet the Heller upper bound for
systematic codes are given.
Abstract: In this paper, a new time discontinuous expanded mixed finite element method is proposed and analyzed for two-order convection-dominated diffusion problem. The proofs of the stability of the proposed scheme and the uniqueness of the discrete solution are given. Moreover, the error estimates of the scalar unknown, its gradient and its flux in the L1( ¯ J,L2( )-norm are obtained.
Abstract: The purpose of this research is to study the concepts
of multiple Cartesian product, variety of multiple algebras and to
present some examples. In the theory of multiple algebras, like other
theories, deriving new things and concepts from the things and
concepts available in the context is important. For example, the first
were obtained from the quotient of a group modulo the equivalence
relation defined by a subgroup of it. Gratzer showed that every
multiple algebra can be obtained from the quotient of a universal
algebra modulo a given equivalence relation.
The purpose of this study is examination of multiple algebras and
basic relations defined on them as well as introduction to some
algebraic structures derived from multiple algebras. Among the
structures obtained from multiple algebras, this article studies submultiple
algebras, quotients of multiple algebras and the Cartesian
product of multiple algebras.