Reduction and Conversion Strategies for the Calculus of (co)Inductive Constructions: Part I

We compare several reduction and conversion strategies for the Calculus of (co)Inductive Constructions by running benchmarks from the library of the Coq proof assistant. All the strategies have been implemented in an independent verifier for the proof objects of Coq that is part of the Matita proof assistant.     

Linear and non-linear behaviour of steel plates with circular and rectangular holes under shear loading

In this work, linear buckling and the non-linear behaviour of steel plates with one perforation subjected to shear loading was studied. The influence of the dimension, position with respect to the two main axes, shape (circular or rectangular) and orientation of a hole with respect to the panel slenderness and aspect ratio were all investigated.In both circular and rectangular holes, the strong influence of hole dimensions on the shear buckling coefficient was observed, and the values of the shear buckling coefficient fell with the plate aspect ratio. Small differences in buckling coefficients were noted in rectangular plates with various hole diameters, and buckling coefficients were practically not influenced by the orientation of the rectangular hole. In both rectangular and circular holes, the coefficient remained constant, regardless of hole position for a given distance from the edge.Linear buckling and non-linear behaviour were compared by observing different shear failure modes for slender and thick perforated plates. Elastic and plastic regions were found, on the basis of critical slenderness, for some common geometries.     

Geographical information systems for map based navigation in urban environments

In order to solve most of the existing mobile robotics applications, the robot needs some information about its spatial environment encoded in what it has been commonly called a map. The knowledge contained in such a map, whatever approach is used to obtain it, will mainly be used by the robot to gain the ability to navigate in a given environment. We are describing in this paper, a method that allows a robot or team of robots to navigate in large urban areas for which an existing map in a standard human understandable fashion is available. As detailed maps of most urban areas already exist, it will be assumed that a map of the zone where the robot is supposed to work is given, which has not been constructed using the robot’s own sensors. We propose in this paper, the use of an existing Geographical Information System based map of an urban zone so that a robot or a team of robots can connect to this map and use it for navigation purposes. Details of the implemented system architecture as well as a position tracking experiment in a real outdoor environment, a University Campus, are provided.     

Personalities of politicians and voters: Unique and synergistic relationships.

A rare collection of personality assessments from 103 Italian politicians revealed predictable patterns of contrasts and similarities with personality dimensions from a large normative sample (N = 4,578). Three modal personality characteristics distinguished politicians, with their significantly higher levels of Energy, Agreeableness, and Social Desirability, from the general public. Comparability between politicians and the public existed on dimensions of Emotional Stability, Conscientiousness, and Openness (Big Five Questionnaire assessment). Politicians from rival coalitions differed on several dimensions; center-right was higher than center-left in Energy and Conscientiousness. Congruencies emerged between politicians and voters for their coalition on all personality dimensions, except that center-left politicians were higher in Energy than center-left voters, and center-right politicians were higher than voters in both Energy and Agreeableness. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Fast adaptive digital equalization by recurrent neural networks

Neural networks (NNs) have been extensively applied to many signal processing problems. In particular, due to their capacity to form complex decision regions, NNs have been successfully used in adaptive equalization of digital communication channels. The mean square error (MSE) criterion, which is usually adopted in neural learning, is not directly related to the minimization of the classification error, i.e., bit error rate (BER), which is of interest in channel equalization. Moreover, common gradient-based learning techniques are often characterized by slow speed of convergence and numerical ill conditioning. In this paper, we introduce a novel approach to learning in recurrent neural networks (RNNs) that exploits the principle of discriminative learning, minimizing an error functional that is a direct measure of the classification error. The proposed method extends to RNNs a technique applied with success to fast learning of feedforward NNs and is based on the descent of the error functional in the space of the linear combinations of the neurons (the neuron space); its main features are higher speed of convergence and better numerical conditioning w.r.t. gradient-based approaches, whereas numerical stability is assured by the use of robust least squares solvers. Experiments regarding the equalization of PAM signals in different transmission channels are described, which demonstrate the effectiveness of the proposed approach     

Structural oscillation modes identification by applying controlled loads and using microwave interferometry

Radar interferometry, capable of remote detection of displacements and deformations of a structure, has been successfully experimented in a number of case studies. Radar interferometry offers high-speed range imaging and range displacement measurement capability, but it lacks in the identification of the different kinds of modes usually excited in a dynamic test. In this paper an approach to the measurement capable of identifying bending and torsional oscillation modes is described. The basic idea rely on the application of suitable loads to the structure under test in order to cause controlled changes of its frequency response. The results of such a dynamic test, performed on a canopy, are reported.     

Growth characteristics and fermentation products of Streptococcus salivarius subsp. thermophilus, Lactobacillus casei and L?. fermentum in soymilk

 Growth and substrate consumption of Lactobacillus fermentum, L. casei, and Streptococcus salivarius subsp. thermophilus were studied in soy milk. All cultures tested metabolized sucrose in the range of 60–75% with various rates of sugar consumption, but only L. fermentum was able to hydrolyse stachyose (85%). Lactic acid was the major end-product while acetic acid was only produced by L. casei and L. fermentum. Received: 12 June 1997