Can a connectionist model explain the processing of regularly and irregularly inflected words in German as L1 and L2?

The connectionist model is a prevailing model of the structure and functioning of the cognitive system of the processing of morphology. According to this model, the morphology of regularly and irregularly inflected words (e.g., verb participles and noun plurals) is processed in the same cognitive network. A validation of the connectionist model of the processing of morphology in German as L2 has yet to be achieved. To investigate L2-specific aspects, we compared a group of L1 speakers of German with speakers of German as L2. L2 and L1 speakers of German were assigned to their respective group by their reaction times in picture naming prior to the central task. The reaction times in the lexical decision task of verb participles and noun plurals were largely consistent with the assumption of the connectionist model. Interestingly, speakers of German as L2 showed a specific advantage for irregular compared with regular verb participles

A hybrid method for inversion of 3D DC resistivity logging measurements

This paper focuses on the application of hp hierarchic genetic strategy (hp-HGS) for solution of a challenging problem, the inversion of 3D direct current (DC) resistivity logging measurements. The problem under consideration has been formulated as the global optimization one, for which the objective function (misfit between computed and reference data) exhibits multiple minima. In this paper, we consider the extension of the hp-HGS strategy, namely we couple the hp-HGS algorithm with a gradient based optimization method for a local search. Forward simulations are performed with a self-adaptive hp finite element method, hp-FEM. The computational cost of misfit evaluation by hp-FEM depends strongly on the assumed accuracy. This accuracy is adapted to the tree of populations generated by the hp-HGS algorithm, which makes the global phase significantly cheaper. Moreover, tree structure of demes as well as branch reduction and conditional sprouting mechanism reduces the number of expensive local searches up to the number of minima to be recognized. The common (direct and inverse) accuracy control, crucial for the hp-HGS efficiency, has been motivated by precise mathematical considerations. Numerical results demonstrate the suitability of the proposed method for the inversion of 3D DC resistivity logging measurements

A multi-objective memetic inverse solver reinforced by local optimization methods

We propose a new memetic strategy that can solve the multi-physics, complex inverse problems, formulated as the multi-objective optimization ones, in which objectives are misfits between the measured and simulated states of various governing processes. The multi-deme structure of the strategy allows for both, intensive, relatively cheap exploration with a moderate accuracy and more accurate search many regions of Pareto set in parallel. The special type of selection operator prefers the coherent alternative solutions, eliminating artifacts appearing in the particular processes. The additional accuracy increment is obtained by the parallel convex searches applied to the local scalarizations of the misfit vector. The strategy is dedicated for solving ill-conditioned problems, for which inverting the single physical process can lead to the ambiguous results. The skill of the selection in artifact elimination is shown on the benchmark problem, while the whole strategy was applied for identification of oil deposits, where the misfits are related to various frequencies of the magnetic and electric waves of the magnetotelluric measurement

Multi-objective hierarchic memetic solver for inverse parametric problems

We propose a multi-objective approach for solving challenging inverse parametric problems. The objectives are misfits for several physical descriptions of a phenomenon under consideration, whereas their domain is a common set of admissible parameters. The resulting Pareto set, or parameters close to it, constitute various alternatives of minimizing individual misfits. A special type of selection applied to the memetic solution of the multi-objective problem narrows the set of alternatives to the ones that are sufficiently coherent. The proposed strategy is exemplified by solving a real-world engineering problem consisting of the magnetotelluric measurement inversion that leads to identification of oil deposits located about 3 km under the Earth's surface, where two misfit functions are related to distinct frequencies of the electric and magnetic waves

Flight Demonstration Of Low Overpressure N-Wave Sonic Booms And Evanescent Waves

The recent flight demonstration of shaped sonic booms shows the potential for quiet overland supersonic flight, which could revolutionize air transport. To successfully design quiet supersonic aircraft, the upper limit of an acceptable noise level must be determined through quantitative recording and subjective human response measurements. Past efforts have concentrated on the use of sonic boom simulators to assess human response, but simulators often cannot reproduce a realistic sonic boom sound. Until now, molecular relaxation effects on low overpressure rise time had never been compared with flight data. Supersonic flight slower than the cutoff Mach number, which generates evanescent waves, also prevents loud sonic booms from impacting the ground. The loudness of these evanescent waves can be computed, but flight measurement validation is needed. A novel flight demonstration technique that generates low overpressure N-waves using conventional military aircraft is outlined, in addition to initial quantitative flight data. As part of this demonstration, evanescent waves also will be recorded

Explicit wave overtopping formula for mound breakwaters with crown walls using CLASH neural network-derived data

Based on the Crest Level Assessment of Coastal Structures (CLASH) Neural Network Overtopping prediction method, a new 16-parameter overtopping estimator (Q6) was developed for conventional mound breakwaters with crown walls, both with and without toe berms. Q6 was built up using the overtopping estimations given by the CLASH Neural Network and checked using the CLASH database. Q6 was compared to other conventional overtopping formulas, and the Q6 obtained the lowest prediction errors. Q6 provides overtopping predictions similar to the CLASH Neural Network for conventional mound breakwaters but using only six explanatory dimensionless variables (Rc=Hm0; Ir; Rc=h;Gc=Hm0; Ac=Rc, and a toe berm variable based on Rc=h) and two reduction factors (g f and g b ). Q6 describes explicit relationships between input variables and overtopping discharge, and hence it facilitates use in engineering design to identify costeffective solutions and to quantify the influence of variations in wave and structural parameters.The authors are grateful for financial support from the Spanish Ministerio de Economia y Competitividad (Grant BIA2012-33967). The first author was funded through the FPU program (Formacion del Profesorado Universitario, Grant AP2010-4366) by the Spanish Ministerio de Educacion, Cultura y Deporte. The authors also thank Debra Westall for revising the manuscript.Molines, J.; Medina, JR. (2016). Explicit wave overtopping formula for mound breakwaters with crown walls using CLASH neural network-derived data. Journal of Waterway Port Coastal and Ocean Engineering. 142(3). https://doi.org/10.1061/(ASCE)WW.1943-5460.0000322S142

Analytic Tableaux for Simple Type Theory and its First-Order Fragment

We study simple type theory with primitive equality (STT) and its first-order fragment EFO, which restricts equality and quantification to base types but retains lambda abstraction and higher-order variables. As deductive system we employ a cut-free tableau calculus. We consider completeness, compactness, and existence of countable models. We prove these properties for STT with respect to Henkin models and for EFO with respect to standard models. We also show that the tableau system yields a decision procedure for three EFO fragments

Trakhtenbrot's Theorem in Coq, A Constructive Approach to Finite Model Theory

We study finite first-order satisfiability (FSAT) in the constructive setting of dependent type theory. Employing synthetic accounts of enumerability and decidability, we give a full classification of FSAT depending on the first-order signature of non-logical symbols. On the one hand, our development focuses on Trakhtenbrot's theorem, stating that FSAT is undecidable as soon as the signature contains an at least binary relation symbol. Our proof proceeds by a many-one reduction chain starting from the Post correspondence problem. On the other hand, we establish the decidability of FSAT for monadic first-order logic, i.e. where the signature only contains at most unary function and relation symbols, as well as the enumerability of FSAT for arbitrary enumerable signatures. All our results are mechanised in the framework of a growing Coq library of synthetic undecidability proofs