INTRODUCTION Surgical treatment of Hirschsprung's disease may be performed in a single step, or in stages with a temporary stoma. The therapy depends on the clinical condition of the patient and the severity of symptoms. Planned multistage treatment is carried out in two or three steps. AIM To analyse our 15 years of experience with multistage surgery for the treatment of Hirschsprung's disea...

A multistage system refers to a system consisting of multiple components, stations or stages required to finish the final product or service. Multistage systems are very common in practice and include a variety of modern manufacturing and service systems. In most cases, the quality of the final product or service produced by a multistage system is determined by complex interactions among multip...

Multistage stochastic programs, which involve sequences of decisions over time, are usually hard to solve in realistically sized problems. In the two-stage case, several approaches based on different levels of available information has been adopted in literature such as the Expected Value Problem, EV , the Sum of Pairs Expected Values, SPEV , the Expectation of Pairs Expected Value, EPEV , solv...

The order of stages in a multistage game is often interpreted by looking at earlier stages as involving more long term decisions. For the purpose of making this interpretation precise, the notion of a delay supergame of a bounded multistage game is introduced. A multistage game is bounded if the length of play has an upper bound. A delay supergame is played over many periods. Decisions on all s...

In stochastic programming and decision analysis, an important issue consists in the approximate representation of the multidimensional stochastic underlying process in the form of scenario tree. This paper presents the approach to generate the multistage multidimensional scenario tree out of a set of scenario fans. For this purpose, the multistage K-means clustering algorithm is developed. The ...

In multistage manufacturing systems, modeling multiple quality indices based on the process sensing variables is important. However, classic technique predicts each variable one at a time, which fails to consider correlation within or between stages. We propose deep multi-task learning framework jointly predict all output in unified end-to-end according sequential system architecture MMS. Our n...

An understanding of the dynamic process of urban growth is a prerequisite to the prediction of land-cover change and the support of urban development planning and sustainable growth management. The spatial and temporal complexity inherent in urban growth requires the development of a new simulation approach, which should be process-oriented and have a strong interpretive element. In this paper ...