This work proposes the use of machine learning methods applied to the construction of a gray level adaptive hitor-miss morphological operator. Because they are adaptive and translation invariant, it is expected that these operators can be better utilized for the process of pattern recognition. In a first approach, the investigated adaptive model is inspired on the Vector Quantization Unsupervis...

In this project, we consider minimizing multiple linear objective functions under a max-t-norm fuzzy relational equation constraint. Since the feasible domain of a max-Archimedean t-norm relational equation constraint is generally nonconvex, traditionally mathematical programming techiniques may have difficulty in yielding efficient solutions for such problems. In this paper, we apply the two-p...

In this series of lectures directed towards a mainly mathematically oriented audience I try to motivate the use of operator algebra methods in quantum field theory. Therefore a title as “why mathematicians are/should be interested in algebraic quantum field theory” would be equally fitting. Besides a presentation of the framework and the main results of local quantum physics these notes may ser...

Background: Heat stress in the steel industry is considered as a serious threat to the health and safety of workers. A wide spectrum of complications and diseases from mild disorders such as burning sensation to fatal conditions such as thermal shock may occur due to uncontrolled thermal stress. In this study, heat stress assessment was performed according to the wet-bulb globe temperature (WBG...

This paper focuses on presenting a technique to calculate energy retrofit horizons in process plants. In particular, it focuses on crude fractionation units. The methodology takes advantage of two facts: (a) Pinch-type calculations can be performed using operator type representations and (b) Processes like crude fractionation offer large flexibility in the operating/design parameters. This pape...

The article describes a new formal approach to model discrete stochastic processes, called observable operator models (OOMs). It is shown how hidden Markov models (HMMs) can be properly generalized to OOMs. These OOMs afford both mathematical simplicity and algorithmic efficiency, where HMMs exhibit neither. The observable operator idea also leads to an abstract, information-theoretic represent...

For an isolated macrosystem classical state parameters c(t) are introduced inside a quantum mechanical treatment. By a suitable mathematical representation of the actual preparation procedure in the time interval [T, to] a statistical operator is constructed as a solution of the Liouvilleevon Neumann equation. exhibiting at time t the state parameters [(t’), to 5 t’ < t, and preparation paramet...

We construct the symmetric functional model for an arbitrary closed operator with a non-empty resolvent set acting on a separable Hilbert space. The main techniques of the study are based on the explicit form of the Sz.-Nagy-Foiaş model for a closed dissipative operator, the Potapov-Ginzburg transform of characteristic functions, and certain resolvent identities. All considerations are carried ...