ELIMINATION PROPERTIES FOR A PROBABILISTIC SCHEDULING PROBLEM

Elimination Properties for a Probabilistic Scheduling Problem

In many areas of the economy, we deal with random processes, e.g., transport, agriculture, trade, construction, etc.Effective management of such processes often leads to optimization models with random parameters.Solving these problems is already very difficult in deterministic cases, because they usually belong to the NP-hard class.In addition the

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COVID-19 anomaly detection and classification method based on supervised machine learning of chest X-ray images

The term COVID-19 is an abbreviation of Coronavirus 2019, which is considered Corner Chair a global pandemic that threatens the lives of millions of people.Early detection of the disease offers ample opportunity of recovery and prevention of spreading.This paper proposes a method for classification and early detection of COVID-19 through image proc

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A Distributed Spatial Method for Modeling Maritime Routes

In this work we propose a novel spatial knowledge discovery pipeline capable of automatically unravelling the “roads of the sea” and maritime traffic patterns by analysing voluminous vessel tracking data, as collected through the Automatic Identification System Right Side Sticker (AIS).We present a computationally efficient and highly

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