Abstract: Since 1984 many schemes have been proposed for
digital signature protocol, among them those that based on discrete
log and factorizations. However a new identification scheme based
on iterated function (IFS) systems are proposed and proved to be
more efficient. In this study the proposed identification scheme is
transformed into a digital signature scheme by using a one way hash
function. It is a generalization of the GQ signature schemes. The
attractor of the IFS is used to obtain public key from a private one,
and in the encryption and decryption of a hash function. Our aim is
to provide techniques and tools which may be useful towards
developing cryptographic protocols. Comparisons between the
proposed scheme and fractal digital signature scheme based on RSA
setting, as well as, with the conventional Guillou-Quisquater
signature, and RSA signature schemes is performed to prove that, the
proposed scheme is efficient and with high performance.
Abstract: The entropy of intuitionistic fuzzy sets is used to indicate the degree of fuzziness of an interval-valued intuitionistic fuzzy set(IvIFS). In this paper, we deal with the entropies of IvIFS. Firstly, we propose a family of entropies on IvIFS with a parameter λ ∈ [0, 1], which generalize two entropy measures defined independently by Zhang and Wei, for IvIFS, and then we prove that the
new entropy is an increasing function with respect to the parameter λ. Furthermore, a new multiple attribute decision making (MADM) method using entropy-based attribute weights is proposed to deal with the decision making situations where the alternatives on attributes are expressed by IvIFS and the attribute weights information is unknown. Finally, a numerical example is given to illustrate the applications of the proposed method.
Abstract: The primary objective of the paper is to propose a new method for solving assignment problem under uncertain situation. In the classical assignment problem (AP), zpqdenotes the cost for assigning the qth job to the pth person which is deterministic in nature. Here in some uncertain situation, we have assigned a cost in the form of composite relative degree Fpq instead of and this replaced cost is in the maximization form. In this paper, it has been solved and validated by the two proposed algorithms, a new mathematical formulation of IVIF assignment problem has been presented where the cost has been considered to be an IVIFN and the membership of elements in the set can be explained by positive and negative evidences. To determine the composite relative degree of similarity of IVIFS the concept of similarity measure and the score function is used for validating the solution which is obtained by Composite relative similarity degree method. Further, hypothetical numeric illusion is conducted to clarify the method’s effectiveness and feasibility developed in the study. Finally, conclusion and suggestion for future work are also proposed.
Abstract: In conventional reliability assessment, the reliability data of system components are treated as crisp values. The collected data have some uncertainties due to errors by human beings/machines or any other sources. These uncertainty factors will limit the understanding of system component failure due to the reason of incomplete data. In these situations, we need to generalize classical methods to fuzzy environment for studying and analyzing the systems of interest. Fuzzy set theory has been proposed to handle such vagueness by generalizing the notion of membership in a set. Essentially, in a Fuzzy Set (FS) each element is associated with a point-value selected from the unit interval [0, 1], which is termed as the grade of membership in the set. A Vague Set (VS), as well as an Intuitionistic Fuzzy Set (IFS), is a further generalization of an FS. Instead of using point-based membership as in FS, interval-based membership is used in VS. The interval-based membership in VS is more expressive in capturing vagueness of data. In the present paper, vague set theory coupled with conventional Lambda-Tau method is presented for reliability analysis of repairable systems. The methodology uses Petri nets (PN) to model the system instead of fault tree because it allows efficient simultaneous generation of minimal cuts and path sets. The presented method is illustrated with the press unit of the paper mill.
Abstract: Medical imaging uses the advantage of digital
technology in imaging and teleradiology. In teleradiology systems
large amount of data is acquired, stored and transmitted. A major
technology that may help to solve the problems associated with the
massive data storage and data transfer capacity is data compression
and decompression. There are many methods of image compression
available. They are classified as lossless and lossy compression
methods. In lossy compression method the decompressed image
contains some distortion. Fractal image compression (FIC) is a lossy
compression method. In fractal image compression an image is
coded as a set of contractive transformations in a complete metric
space. The set of contractive transformations is guaranteed to
produce an approximation to the original image. In this paper FIC is
achieved by PIFS using quadtree partitioning. PIFS is applied on
different images like , Ultrasound, CT Scan, Angiogram, X-ray,
Mammograms. In each modality approximately twenty images are
considered and the average values of compression ratio and PSNR
values are arrived. In this method of fractal encoding, the
parameter, tolerance factor Tmax, is varied from 1 to 10, keeping the
other standard parameters constant. For all modalities of images the
compression ratio and Peak Signal to Noise Ratio (PSNR) are
computed and studied. The quality of the decompressed image is
arrived by PSNR values. From the results it is observed that the
compression ratio increases with the tolerance factor and
mammogram has the highest compression ratio. The quality of the
image is not degraded upto an optimum value of tolerance factor,
Tmax, equal to 8, because of the properties of fractal compression.
Abstract: The purpose of this paper is to solve the problem of protecting aerial lines from high impedance faults (HIFs) in distribution systems. This investigation successfully applies 3I0 zero sequence current to solve HIF problems. The feature extraction system based on discrete wavelet transform (DWT) and the feature identification technique found on statistical confidence are then applied to discriminate effectively between the HIFs and the switch operations. Based on continuous wavelet transform (CWT) pattern recognition of HIFs is proposed, also. Staged fault testing results demonstrate that the proposed wavelet based algorithm is feasible performance well.
Abstract: There have been different approaches to compute the
analytic instantaneous frequency with a variety of background reasoning
and applicability in practice, as well as restrictions. This paper presents an adaptive Fourier decomposition and (α-counting) based
instantaneous frequency computation approach. The adaptive Fourier
decomposition is a recently proposed new signal decomposition
approach. The instantaneous frequency can be computed through the so called mono-components decomposed by it. Due to the fast energy
convergency, the highest frequency of the signal will be discarded by the adaptive Fourier decomposition, which represents the noise of
the signal in most of the situation. A new instantaneous frequency
definition for a large class of so-called simple waves is also proposed
in this paper. Simple wave contains a wide range of signals for which
the concept instantaneous frequency has a perfect physical sense.
The α-counting instantaneous frequency can be used to compute the highest frequency for a signal. Combination of these two approaches one can obtain the IFs of the whole signal. An experiment is demonstrated the computation procedure with promising results.
Abstract: Intuitionistic fuzzy sets as proposed by Atanassov,
have gained much attention from past and latter researchers for
applications in various fields. Similarity measures between
intuitionistic fuzzy sets were developed afterwards. However, it does
not cater the conflicting behavior of each element evaluated. We
therefore made some modification to the similarity measure of IFS
by considering conflicting concept to the model. In this paper, we
concentrate on Zhang and Fu-s similarity measures for IFSs and
some examples are given to validate these similarity measures. A
simple modification to Zhang and Fu-s similarity measures of IFSs
was proposed to find the best result according to the use of degree of
indeterminacy. Finally, we mark up with the application to real
decision making problems.