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The fractal geometries are applied extensively in many applications like pattern recognition, texture analysis and segmentation. The application of fractal geometry requires estimation of the fractal features. The fractal dimension and fractal length are found effective to analyze and measure image features, such as texture, resolution, etc. This paper proposes a new wavelet–fractal technique for image resolution enhancement. The resolution of the wavelet sub-bands are improved using scaling operator and then it is transformed into texture vector. The proposed method then computes fractal dimension and fractal length in gradient domain which is used for resolution enhancement. It is observed that by using scaling operator in the gradient domain, the fractal dimension and fractal length becomes scale invariant. The major advantage of the proposed wavelet–fractal technique is that the feature vector retains fractal dimension and fractal length both. Thus, the resolution enhanced image restores the texture information well. The texture information has also been observed in terms of fractal dimension with varied sample size. We present qualitative and quantitative analysis of the proposed method with existing state of art methods. [ABSTRACT FROM AUTHOR]

The aim of this work is to establish a new methodology to tackle the multi-objective transportation problems [MOTP] in a Fermatean fuzzy environment that can deal with all the parameters that possess a conflicting nature. In our research work, we developed a new score function in the context of a fermatean nature for converting fuzzy data into crisp data with the help of the Fermatean fuzzy technique. Then, we introduced an algorithm-based methodology, i.e., the Fermatean Fuzzy Programming approach to tackle transportation problems with multi-objectives. The main purpose of this research work is to give an alternate fuzzy programming approach to handle the MOTP. To justify the potential and validity of our work, numerical computations have been carried out using our proposed methodology. [ABSTRACT FROM AUTHOR]

In realistic scenarios, multipath scattering environments usually require an approach which can easily model signal behavior. We have considered a Rayleigh multipath scattering channel. The multipath scattering environment captures degradation of signals in fading channels. In this paper, performance of the channel is investigated through the distribution of mutual information in the multipath scattering channel using matrix method. The probability density function for multipath scattering channels is still a developing area of research. The need of the hour is performance evaluation of these communication links in an efficient manner. By using techniques of probability theory, the variance of mutual information is derived for multiple cases based on fading environment. In this paper, we have considered a matrix based multipath scattering model for communication link. We have derived closed-form expression for mutual information in a multipath scattering channel. The matrix method is used to substitute this effect in terms of the Gaussian distribution. This substitution will prove to be very accurate for different cases as analyzed in this paper. [ABSTRACT FROM AUTHOR]

As the ever-shrinking transistor approaches atomic proportions, Moore's law must confront the small-scale granularity of the world: We cannot build wires thinner than atoms. Worse still, at atomic dimensions, we must contend with the laws of quantum mechanics. This pressure of fundamental limits on classical computation and the promise of exponential speedups from quantum effects have recently brought quantum circuits to the attention of the electronic design automation community. However, the near-term limits are not truly fundamental, and may be avoided by making radical changes to the physical and logical architecture of computers. In particular, certain assumed limits to the energy efficiency of computers have never been rigorously proven, and may be circumvented using physical mechanisms that recover and reuse signal energies with efficiency approaching 100%. However, this concept, called reversible computing, imposes tight constraints on the design of the machine at all levels from physics to algorithms. This research work comprehends the advantages of proposed reversible gate in terms of various device parameters like device utilization, delay and power consumption as compared to existing reversible logic. The proposed design as compared to conventional approach shows 80% reduced unit delay and 27% reduction in delay and 40% reduced complexity in respect to available reversible logic. Also, the quantum simulation is successfully performed for the reversible gates, which proves that reversible gates can be used for quantum computation and are suitable for the next generation designs with all advantages of power and reduced device size. The proposed gate is proved to exhibit the fault detection property also. In this research work fourier tansform simulation using reversible gates as quantum gates(5-bits) is performed and compared with the existing fourier transform algorithm, which comprehends its speed up feature. [ABSTRACT FROM AUTHOR]

The reversible architecture scheme yields significantly reduced complexity, low power and high speed features. It is a key issue in the interface between computation and physics, and of growing importance as miniaturization progresses towards its physical limits. With the advent of nanotechnology the fault detection and testability is of high interest for accuracy concerns. This research work describes the reversible testable design of various multipliers. There is 82% reduction in number of garbage outputs and constant inputs using proposed logic which is a key parameter for reversible logic. The proposed CSD multiplier circuit shows better performance than others and can be used in the systems requiring very high performance. The proposed approach shows 14% reduced logical complexity. The proposed add and shift multipliers incorporate 40% increased speed and 42% reduced power consumption than existing multiplier designs. [ABSTRACT FROM AUTHOR]

In this research work, a soft computing optimization operating approach is developed for a multi-objective aspirational level fractional transportation problem. In the proposed technique, a mathematical model is formulated for the multi-objective aspirational level fractional transportation problem (MOFTP) based on the highest value of one and all objectives of the model. We also used the symmetry concept over our model to identify the best optimum solution based on symmetrical data. We constructed the membership grades for the set of fetched parameters having symmetry. In this work, we also used the concept of ranking function in our mathematical model to obtain the optimum solution of the fuzzy multi-objective fractional transportation. In this proposed algorithm, the aspiration levels are also associated with the objective function of MOFTP. We are also proposing a new approach for the optimization of fractional problems in which the objectives are being optimized by using the numerator function and denominator function simultaneously. Further, a methodology is also developed to find the average cost for each fractional objective of the model. After that, we will find the ranking function for each parameter by using the defuzzification method. By this methodology, we will be able to convert the MOFTP into a bi-objective transportation problem. The provided technique is elaborated with the help of numerical computations to prove the beauty and power of the proposed technique. [ABSTRACT FROM AUTHOR]