Informatica

The Industry 4.0 and smart city solutions are impossible to be implemented without using IoT devices. There can be several problems in acquiring data from these IoT devices, problems that can lead to missing values. Without a complete set of data, the automation of processes is not possible or is not satisfying enough. The aim of this paper is to introduce a new algorithm that can be used to fill in the missing values of signals sent by IoT devices. In order to do that, we introduce Shepard local approximation operators in Riesz MV-algebras for one variable function and we structure the set of possible values of the IoT devices signals as Riesz MV-algebra. Based on these local approximation operators we define a new algorithm and we test it to prove that it can be used to fill in the missing values of signals sent by IoT devices.

In this paper we establish some properties of fuzzy quasi-pseudo-metric spaces. An important result is that any partial ordering can be defined by a fuzzy quasi-metric, which can be applied both in theoretical computer science and in information theory, where it is usual to work with sequences of objects of increasing information. We also obtain decomposition theorems of a fuzzy quasi-pseudo metric into a right continuous and ascending family of quasi-pseudo metrics. We develop a topological foundation for complexity analysis of algorithms and programs, and based on our results a fuzzy complexity space can be considered. Also, we built a fertile ground to study some types of fuzzy quasi-pseudo-metrics on the domain of words, which play an important role on denotational semantics, and on the poset $\mathit{B}\mathit{X}$ of all closed formal balls on a metric space.