Motivation. Diagnostic systems play an important role in industry since they help to maximise equipment’s up-time and minimise its maintenance and operating costs [16]. In the energy sector companies like Siemens often rely on rule-based diagnostics to analyse power generating equipment by, e.g., testing newly deployed electricity generating gas turbines [11], or checking vibration instrumentat...

Clinical trial designs often incorporate a sequential stopping rule to serve as a guide in the early termination of a study. When choosing a particular stopping rule, it is most common to examine frequentist operating characteristics such as type I error, statistical power, and precision of confidence intervals (Statist. Med. 2005, in revision). Increasingly, however, clinical trials are design...

The D/H variations in chondritic meteorites are reviewed and compared with astronomical observations in the interstellar medium. The observed D enrichment in organic molecules — and to a lesser extent in water — is a general rule in the universe. The D is preferentially transferred from the universal reservoir (H2) by low-temperature reactions (10–100 K) from neutral molecules (H2 or H) to hot ...

Classiier systems have traditionally used explicit measures of utility (strength, predicted payoo, accuracy, etc.) to quantify the performance and tness of classiier rules. Much of the eeort in designing and implementing these systems has focused on getting these utilities \right". One alternative worth exploring is the idea of using endogenous t-ness; that is, reinforcing successful performanc...

Abstract We consider a lattice gas interacting by the exclusion rule in the presence of a random field given by i.i.d. bounded random variables in a bounded domain in contact with particles reservoir at different densities. We show, in dimensions d ≥ 3, that the rescaled empirical density field almost surely, with respect to the random field, converges to the unique weak solution of a non linea...

The optimization of an oil and gas separation plant operating revenue has been performed for different characteristic reservoir fluid types (gas condensate, volatile oil, black oil) using ev...

We propose a multi-timescale learning rule for spiking neuron networks, in the line of the recently emerging field of reservoir computing. The reservoir is a network model of spiking neurons, with random topology and driven by STDP (Spike-TimeDependent Plasticity), a temporal Hebbian unsupervised learning mode, biologically observed. The model is further driven by a supervised learning algorith...

A scale-up study has been performed with three different size reactors to establish the optimum operating conditions for the hydrogen production from synthesis gas by biological water-gas shift reaction using the photosynthetic bacterium Rhodosprilliunt rubrum. Optimum medium composition and operating conditions previously determined in a bench scale 1.25 L continuous stirred tank reactor (CSTR...

r a 200 .021 : +886 2 ail.tku.e Summary Real-time flood control of a multi-purpose reservoir should consider decreasing the flood peak stage downstream and storing floodwaters for future usage during typhoon seasons. This study proposes a reservoir flood control optimization model with linguistic description of requirements and existing regulations for rational operating decisions. The approach...