in this study, vanadium recovery from the steelmaking converter slag was studied. salt roasting-basic leaching is the process which was applied to separate and extract vanadium from steel making slag. ground slag was roasted after mixing with determined quantities of sodium carbonate. the effect of time and temperature of roasting and sodium carbonate content were studied. the optimum temperatu...

We add conditionals with time-dependent conditions to the real time process algebra with parametric timing from the framework of process algebras with timing presented by Baeten and Middelburg [Handbook of Process Algebra, Elsevier, 2001, Chapter 10]. This extension facilitates flexible dependence of process behaviour on initialization time. We show that the conditions concerned generalize the ...

Process mining is a family of techniques to discover business process models and other knowledge of business processes from event logs. Existing process mining techniques are geared towards discovering models that capture the order of execution of tasks, but not the conditions under which tasks are executed – also called branching conditions. One existing process mining technique, namely ProM’s...

Methanol is one of the most important petrochemical products which is produced in large extents worldwide. Nowadays, it is mostly used as a feed in olefin units for production of synthetic fuels. In this work, methanol production process, under license of Davy Corporation, is simulated by using HYSYS software. The simulations are carried out for steady state condition. The simulation results we...

The Cox-Ingersoll-Ross (CIR) interest rate model is used to model interest rates and interest rate derivatives. We study the term structure equation for single-factor models that predict non-negative interest rates. It is shown using finite difference techniques that if the boundary is attainable, then this boundary behaviour serves as a boundary condition and guarantees a uniqueness of solutio...

We study the generation and visualization of residuals for detecting and identifying unseen faults using autoassociative models learned from process data. Least squares and kernel regression models are compared on the basis of their ability to describe the support of the data. Theoretical results show that kernel regression models are more appropriate in this sense. Moreover, experiments on vib...

Automated process discovery methods aim at extracting business process models from execution logs of information systems. Existing methods in this space are designed to discover synchronization conditions over a set of events that is fixed in number, such as for example discovering that a task should wait for two other tasks to complete. However, they fail to discover synchronization conditions...