Abstract. In this paper, a Cascaded Lattice Boltzmann Method with second order slip boundary conditions is developed to study gas flows in a microchannel in the slip and transition flow regimes with a wide range of Knudsen numbers. For the first time the effect of wall confinement is considered on the effective mean free path of the gas molecules using a function with nonconstant Bosanquet para...

Dynamic data driven simulation dynamically assimilates observation data at runtime to improve the simulation results. Typically, the observations are “hard data” that are data collected from sensors. In this paper we consider dynamic data driven simulation with soft data, which are data coming from human reports. Compared with the quantified hard data, soft data are qualitative, fuzzy and subje...

This paper concerns the design of a workflow which permits to feed and query a data warehouse opened on the Web, driven by a domain ontology. This data warehouse has been built to enrich local data sources and is composed of data tables extracted from Web documents. We recall the main steps of our semi-automatic method to annotate Web data tables driven by a domain ontology. The output of this ...

A novel data-driven soft sensor is designed for online product quality prediction and control performance modification in industrial units. A combined approach of time variable parameter (TVP) model, dynamic auto regressive exogenous variable (DARX) algorithm, nonlinear correlation analysis and criterion-based elimination method is introduced in this work. The soft sensor performance validation...

Sequential pattern mining is the method that has received much attention in sequence data mining research and applications, however, a drawback is that it does not profit from prior knowledge of domains. In our previous work, we proposed a belief-driven method with fuzzy set theory for discovering the unexpected sequences that contradict existing knowledge of data, including occurrence constrai...

TThe uncertainty estimation and compensation are challenging problems for the robust control of robot manipulators which are complex systems. This paper presents a novel decentralized model-free robust controller for electrically driven robot manipulators. As a novelty, the proposed controller employs a simple Gaussian Radial-Basis-Function Network as an uncertainty estimator. The proposed netw...