One important function of the discussion forums of Massive Open Online Courses (MOOCs) is for students to post problems they are unable to resolve and receive help from their peers and instructors. There are a large proportion of threads that are not resolved to the satisfaction of the students for various reasons. In this paper, we attack this problem by firstly constructing a conceptual model...

Predictions of the transport properties self-diffusion coefficient and shear viscosity are presented for a recently developed molecular ammonia model. These data show mean unsigned deviations to the experiment over a temperature range from 200 to 500 K of 8 % for the self-diffusion coefficient and 12% for the shear viscosity. Furthermore, the vapor-liquid equilibria of the ternary system carbon...

A new method for the spatial discretization of complex multi-scale systems described by partial differential equations is presented. This method allows to preserve the global power balance equation and the geometric structure of the system. The modelling of the adsorption column is based on a network approach. The key notions are the energy function and the description of the power transfers wi...

(Spatial) panel data are routinely modelled in discrete time (DT). However, there are compelling arguments for continuous time (CT) modelling of (spatial) panel data. Particularly, most social processes evolve in CT, so that statistical analysis in DT is an oversimplification, gives an incomplete representation of reality and may lead to misinterpretation of estimation results. The most compell...

This progress report is about equation-based modelling languages. In particular, the report discusses work [4] on formalising semantic aspects of Functional Hybrid Modelling (FHM) [12] – a hybrid, structurally dynamic, non-causal modelling language – in the dependently-typed programming language Agda [13]. Section 2 gives a preliminary outline of equation-based languages and FHM. Section 3 give...

Two complementary schools have come to the fore in the field of Structural Equation Modelling (SEM): covariance-based SEM and component-based SEM. The first approach has been developed around Karl Jöreskog and the second one around Herman Wold under the name "PLS" (Partial Least Squares). Hwang and Takane have proposed a new component-based SEM method named Generalized Structured Component Anal...

We present some preliminary results on the integration of integro-differential equations using Deep Learning techniques.

This article describes a machine learning based approach applied to acquiring empirical forecasting models. The approach makes use of the LAGRAMGE equation discovery tool to define a potentially very wide range of equations to be considered for the model. Importantly, the equations can vary in the number of terms and types of functors linking the variables. The parameters of each competing equa...