The Brazilian federal government regulates the process for procurement of Information Technology (IT) solutions through specific legislation named Regulatory Instruction-RI N° 04/2010. This process consists of th...
详细信息
The substitution box,often known as an S-box,is a nonlinear component that is a part of several block *** purpose is to protect cryptographic algorithms from a variety of cryptanalytic assaults.A Multi-Criteria Decisi...
详细信息
The substitution box,often known as an S-box,is a nonlinear component that is a part of several block *** purpose is to protect cryptographic algorithms from a variety of cryptanalytic assaults.A Multi-Criteria Decision Making(MCDM)problem has a complex selection procedure because of having many options and criteria to choose *** of this,statistical methods are necessary to assess the performance score of each S-box and decide which option is the best one available based on this *** the Pythagorean Fuzzy-based Technique for Order of Preference by Similarity to Ideal Solution(TOPSIS)method,the major objective of this investigation is to select the optimal S-box to be implemented from a pool of twelve key *** the help of the Pythagorean fuzzy set(PFS),the purpose of this article is to evaluate whether this nonlinear component is suitable for use in a variety of encryption *** this article,we have considered various characteristics of S-boxes,including nonlinearity,algebraic degree,strict avalanche criterion(SAC),absolute indicator,bit independent criterion(BIC),sum of square indicator,algebraic immunity,transparency order,robustness to differential cryptanalysis,composite algebraic immunity,signal to noise ratio-differential power attack(SNR-DPA),and confusion coefficient variance on some standard S-boxes that are Advanced Encryption Following this,the findings of the investigation are changed into Pythagorean fuzzy numbers in the shape of a *** matrix is then subjected to an analysis using the TOPSIS method,which is dependent on the Pythagorean fuzzy set,to rank the most suitable S-box for use in encryption applications.
Tests for the goodness-of-fit problem based on sample spacings, i.e., observed distances between successive order statistics, have been used in the literature. We propose a new test based on the number of “small” a...
Tests for the goodness-of-fit problem based on sample spacings, i.e., observed distances between successive order statistics, have been used in the literature. We propose a new test based on the number of “small” and “large” spacings. The asymptotic theory under close alternative sequences is also given thus enabling one to calculate the asymptotic relative efficiencies of such tests. A comparison of the new test and other spacings tests is given.
In this study, we explore the potential of using Reinforcement Learning (RL) algorithms to develop a stock trading strategy that maximizes investment returns. We apply RL to monitor all 50 stocks listed in the SET 50,...
详细信息
Feature selection problems have been extensively studied in the setting of linear estimation (e.g. LASSO), but less emphasis has been placed on feature selection for non-linear functions. In this study, we propose a m...
详细信息
ISBN:
(纸本)9781713821120
Feature selection problems have been extensively studied in the setting of linear estimation (e.g. LASSO), but less emphasis has been placed on feature selection for non-linear functions. In this study, we propose a method for feature selection in neural network estimation problems. The new procedure is based on probabilistic relaxation of the `0 norm of features, or the count of the number of selected features. Our `0-based regularization relies on a continuous relaxation of the Bernoulli distribution;such relaxation allows our model to learn the parameters of the approximate Bernoulli distributions via gradient descent. The proposed framework simultaneously learns either a nonlinear regression or classification function while selecting a small subset of features. We provide an information-theoretic justification for incorporating Bernoulli distribution into feature selection. Furthermore, we evaluate our method using synthetic and real-life data to demonstrate that our approach outperforms other commonly used methods in both predictive performance and feature selection. Copyright 2020 by the author(s).
We propose a new similarity measure, Combined Connectivity and Spatial Adjacency (CCSA), to be used in hierarchical agglomerative clustering (HAC) for automated segmentation of Self-Organizing Maps (SOMs, Kohonen [1])...
详细信息
In applications, considerations on stochastic models often involve a Markov chain [formula omitted] with state space in R+, and a transition probability Q. For each x ε R+ the support of Q(x,) is [0, x]. This implies...
详细信息
A nonparametric formulation is set up for selecting the best one of k populations. “Best” is defined as the one with the smallest inter(a,e)-range, a measure of dispersion defined by the difference of the 6th quanti...
详细信息
暂无评论