Modelica - A Language for Physical System Modeling, Visualization and Interaction

Modelica is an object-oriented language for modeling of large, complex and heterogeneous physical systems. It is suited for multi-domain modeling, for example for modeling of mechatronics including cars, aircrafts and industrial robots which typically consist of mechanical, electrical and hydraulic subsystems as well as control systems. General equations are used for modeling of the physical phenomena, No particular variable needs to be solved for manually. A Modelica tool will have enough information to do that automatically. The language has been designed to allow tools to generate efficient code automatically. The modeling effort is thus reduced considerably since model components can be reused and tedious and error-prone manual manipulations are not needed. The principles of object-oriented modeling and the details of the Modelica language as well as several examples are presented

Direct mail selection by joint modeling of the probability and quantity of response

Operations such as integration or modularization of databases can be considered as operations on database universes. This paper describes some operations on database universes. Formally, a database universe is a special kind of table. It turns out that various operations on tables constitute interesting operations on database universes as well.

Tungsten resonance integrals and Doppler coefficients First quarterly progress report, Jul. - Sep. 1965

Resonance integrals and Doppler coefficients of samples of natural tungsten, tungsten isotopes, and uranium oxide tungsten fue

Sparse Nerves in Practice

Topological data analysis combines machine learning with methods from algebraic topology. Persistent homology, a method to characterize topological features occurring in data at multiple scales is of particular interest. A major obstacle to the wide-spread use of persistent homology is its computational complexity. In order to be able to calculate persistent homology of large datasets, a number of approximations can be applied in order to reduce its complexity. We propose algorithms for calculation of approximate sparse nerves for classes of Dowker dissimilarities including all finite Dowker dissimilarities and Dowker dissimilarities whose homology is Cech persistent homology. All other sparsification methods and software packages that we are aware of calculate persistent homology with either an additive or a multiplicative interleaving. In dowker_homology, we allow for any non-decreasing interleaving function $\alpha$. We analyze the computational complexity of the algorithms and present some benchmarks. For Euclidean data in dimensions larger than three, the sizes of simplicial complexes we create are in general smaller than the ones created by SimBa. Especially when calculating persistent homology in higher homology dimensions, the differences can become substantial

Tungsten resonance integrals and Doppler coefficients Third quarterly report, Jan. - Mar. 1966

Reactivities, Doppler coefficients, and resonance integrals for tungsten isotope

Topological Phases: An Expedition off Lattice

Motivated by the goal to give the simplest possible microscopic foundation for a broad class of topological phases, we study quantum mechanical lattice models where the topology of the lattice is one of the dynamical variables. However, a fluctuating geometry can remove the separation between the system size and the range of local interactions, which is important for topological protection and ultimately the stability of a topological phase. In particular, it can open the door to a pathology, which has been studied in the context of quantum gravity and goes by the name of `baby universe', Here we discuss three distinct approaches to suppressing these pathological fluctuations. We complement this discussion by applying Cheeger's theory relating the geometry of manifolds to their vibrational modes to study the spectra of Hamiltonians. In particular, we present a detailed study of the statistical properties of loop gas and string net models on fluctuating lattices, both analytically and numerically.Comment: 38 pages, 22 figure

A criterion for the number of factors

This note proposes a new criterion for the determination of the number of factors in an approximate static factor model. The criterion is strongly associated with the scree test and compares the differences between consecutive eigenvalues to a threshold. The size of the threshold is derived from a hyperbola and depends only on the sample size and the number of factors k. Monte Carlo simulations compare its properties with well-established estimators from the literature. Our criterion shows similar results as the standard implementations of these estimators, but is not prone to a lack of robustness against a too large a priori determined maximum number of factors kmax