Search results for " Modeling"

Semiautomatic Behavioral Change-Point Detection: A Case Study Analyzing Children Interactions With a Social Agent

2021

The study of human behaviors in cognitive sciences provides clues to understand and describe people’s personal and interpersonal functioning. In particular, the temporal analysis of behavioral dynamics can be a powerful tool to reveal events, correlations and causalities but also to discover abnormal behaviors. However, the annotation of these dynamics can be expensive in terms of temporal and human resources. To tackle this challenge, this paper proposes a methodology to semi-automatically annotate behavioral data. Behavioral dynamics can be expressed as sequences of simple dynamical processes: transitions between such processes are generally known as change-points. This paper describes th…

Testing for goodness rather than lack of fit of continuous probability distributions.

2021

The vast majority of testing procedures presented in the literature as goodness-of-fit tests fail to accomplish what the term is promising. Actually, a significant result of such a test indicates that the true distribution underlying the data differs substantially from the assumed model, whereas the true objective is usually to establish that the model fits the data sufficiently well. Meeting that objective requires to carry out a testing procedure for a problem in which the statement that the deviations between model and true distribution are small, plays the role of the alternative hypothesis. Testing procedures of this kind, for which the term tests for equivalence has been coined in sta…

Predicting perceived visual complexity of abstract patterns using computational measures: The influence of mirror symmetry on complexity perception

2017

Visual complexity is relevant for many areas ranging from improving usability of technical displays or websites up to understanding aesthetic experiences. Therefore, many attempts have been made to relate objective properties of images to perceived complexity in artworks and other images. It has been argued that visual complexity is a multidimensional construct mainly consisting of two dimensions: A quantitative dimension that increases complexity through number of elements, and a structural dimension representing order negatively related to complexity. The objective of this work is to study human perception of visual complexity utilizing two large independent sets of abstract patterns. A w…

From fractal urban pattern analysis to fractal urban planning concepts

2014

International audience; Fractal geometry can be used to develop a multiscale approach toinvestigate the spatial organization of urban fabrics. First, the concepts behindfractal reference models are introduced so as to provide a better understandingof the results obtained from empirical analyses of urban patterns. Then, differentmethods for conducting fractal analyses are presented and the results obtained forurban patterns are discussed. It turns out that, despite their irregular appearance,urban patterns are often organized by an inherent fractal order principle, at leastacross a certain range of scales. More detailed analysis of the findings reveals linksbetween these fractal properties a…

Multimodal 2D Image to 3D Model Registration via a Mutual Alignment of Sparse and Dense Visual Features

2018

International audience; Many fields of application could benefit from an accurate registration of measurements of different modalities over a known 3D model. However, aligning a 2D image to a 3D model is a challenging task and is even more complex when the two have a different modality. Most of the 2D/3D registration methods are based on either geometric or dense visual features. Both have their own advantages and their own drawbacks. We propose, in this paper, to mutually exploit the advantages of one feature type to reduce the drawbacks of the other one. For this, an hybrid registration framework has been designed to mutually align geometrical and dense visual features in order to obtain …

Zur Identifikation von Strukturanalogien in Datenmodellen

2005

On the one hand, data models decrease the complexity of information system development. On the other hand, data models causes additional complexity. Recently structural analogies are discussed as instruments reducing the complexity of data models. This piece of research presents a procedure to identify structural analogies in data models and demonstrates its performance by analyzing Scheer’s reference model for industrial enterprises (Y-CIM-model). The proposed procedure is based on formalizing data models within set theory and uses a quantitative similarity measure. The obtained results show both identical and very similar information structures within the Y-CIM-model. Furthermore, ways of…

Towards a Business Process Model-based Testing of Information Systems Functionality

2020

Real-time characterization of aspect flaws on warped surface by artificial vision

1997

Artificial vision is an efficient means of assuring the quality of a certain class of products. The vision system must respect the industrial constraints, in particular, the production rate. The geometrical features of flaws are pertinent information used for the acceptance of the controlled product. This article presents a real-time algorithm for the geometrical characterization of defects located on warped objects. The algorithms described enable the characterization of defects by their size and their 2-D shape. Both parameters are calculated in real time by simple reference to a look-up table. The 2-D shape is obtained by a geometrical transform and an interpolation. The efficiency of th…

Context-Awareness in Ensemble Recommender System Framework

2021

Recommender systems that provide recommendations based uniquely on information over users and items may not be very accurate in some situations. Therefore, adding contextual information to recommendations may be a good choice resulting in a system with increased precision. In an early work, we proposed an Ensemble Variational Autoencoders (EnsVAE) framework for recommendation. EnsVAE is adjusted to output interest probabilities by learning the distribution of each item's ratings and attempts to provide diverse novel items that are pertinent to users. In this paper, we propose and investigate a context awareness framework based on the Ensemblist Variational Autoencoders model with integratin…

Predictive models for energy saving in Wireless Sensor Networks

2011

ICT devices nowadays cannot disregard optimizations toward energy sustainability. Wireless Sensor Networks, in particular, are a representative class of a technology where special care must be given to energy saving, due to the typical scarcity and non-renewability of their energy sources, in order to enhance network lifetime. In our work we propose a novel approach that aims to adaptively control the sampling rate of wireless sensor nodes using prediction models, so that environmental phenomena can be consistently modeled while reducing the required amount of transmissions; the approach is tested on data available from a public dataset.