Neutrosophic and Information Fusion

This work is concerned with the problem of estimating parameters of spatial quadratic models by the Bayesian technique (SQDM). This technique involves prior information on the first and second moments of the parameters, where its estimation model is called the Bayesian quadratic unbiased estimator. The results of the estimation are compared with the estimates of minimum-norm quadratic unbiased estimators.

In this paper, we study the problem of estimating variance components in the two-way classification with interaction in the random-effect linear model by non-linear maximization. We assume the model according to the assumptions and give the theory of derivation of the estimators of these components, then apply these estimators to real data and obtain the estimates. We estimate these components by two other methods: the solution of the expected equation of mean square in the analysis of the variance table, and the minimum-variance quadratic unbiased estimator.

The traditional methods of discovering objects no longer meet the requirements of the times as a result of their reliance on non-dynamic methods and their slow performance in light of the world’s dependence on a huge amount of multimedia and social media. The rapid development of deep learning provides more powerful tools capable of manipulating high-level and complex semantic features of objects. Several techniques have been developed to detect objects using deep learning algorithms. This research presents a comparative analysis of the most famous deep learning techniques for object detection, explaining their mechanisms and use cases and providing an experimental evaluation of their performance.

The objective of this paper is to study some of the elementary algebraic properties of 4-cyclic refined neutrosophic matrices with real entries, where we study the algebraic structure of the multiplication operation and its properties such as associativity, commutativity, and the existence of algebraic multiplication inverse. Also, we illustrate many examples that explain the validity of our work.

The objective of this paper is to study some of the elementary algebraic properties of 3-cyclic refined neutrosophic matrices with real entries, where we study the algebraic structure of the multiplication operation and its properties such as associativity, commutativity, and the existence of algebraic multiplication inverse. Also, we illustrate many examples that explain the validity of our work.