Search results for " Computer Science"
showing 10 items of 3983 documents
Automatic Integration of Spatial Data into the Semantic Web
2017
International audience
Performance Estimation using the Fitness-Fatigue Model with Kalman Filter Feedback
2016
Abstract Tracking and predicting the performance of athletes is of great interest, not only in training science but also, increasingly, for serious hobbyists. The increasing availability and use of smart watches and fitness trackers means that abundant data is becoming available, and the interest to optimally use this data for performance tracking and training optimization is great. One competitive model in this domain is the 3-time-constant fitness-fatigue model by Busso based on the model by Banister and colleagues. In the following, we will show that this model can be written equivalently as a linear, time-variant state-space model. With this understanding, it becomes clear that all meth…
Formation-based modelling and simulation of success in soccer
2018
Abstract The players’ positions of tactical groups in soccer can be mapped to formation-patterns by means of artificial neural networks (Kohonen, 1995). This way, the hundreds of positional situations of one half of a match can be reduced to about 20 to 30 types of formations (Grunz, Perl & Memmert, 2012; Perl, 2015), the coincidences of which can be used for describing and simulating tactical processes of the teams (Memmert, Lemmink & Sampaio, 2017): Developing and changing formations in the interaction with the opponent activities can be understood as a tactical game in the success context of ball control, space control and finally generating dangerous situations. As such it can b…
Including the Past: Performance Modeling Using a Preload Concept by Means of the Fitness-Fatigue Model
2019
Abstract In mathematical modeling by means of performance models, the Fitness-Fatigue Model (FF-Model) is a common approach in sport and exercise science to study the training performance relationship. The FF-Model uses an initial basic level of performance and two antagonistic terms (for fitness and fatigue). By model calibration, parameters are adapted to the subject’s individual physical response to training load. Although the simulation of the recorded training data in most cases shows useful results when the model is calibrated and all parameters are adjusted, this method has two major difficulties. First, a fitted value as basic performance will usually be too high. Second, without mo…
Constructing Antidictionaries of Long Texts in Output-Sensitive Space
2021
AbstractA wordxthat is absent from a wordyis calledminimalif all its proper factors occur iny. Given a collection ofkwordsy1, … ,ykover an alphabetΣ, we are asked to compute the set$\mathrm {M}^{\ell }_{\{y_1,\ldots ,y_k\}}$M{y1,…,yk}ℓof minimal absent words of length at mostℓof the collection {y1, … ,yk}. The set$\mathrm {M}^{\ell }_{\{y_1,\ldots ,y_k\}}$M{y1,…,yk}ℓcontains all the wordsxsuch thatxis absent from all the words of the collection while there existi,j, such that the maximal proper suffix ofxis a factor ofyiand the maximal proper prefix ofxis a factor ofyj. In data compression, this corresponds to computing the antidictionary ofkdocuments. In bioinformatics, it corresponds to c…
Potential Health Benefits of Olive Oil and Plant Polyphenols
2018
Beneficial effects of natural plant polyphenols on the human body have been evaluated in a number of scientific research projects. Bioactive polyphenols are natural compounds of various chemical structures. Their sources are mostly fruits, vegetables, nuts and seeds, roots, bark, leaves of different plants, herbs, whole grain products, processed foods (dark chocolate), as well as tea, coffee, and red wine. Polyphenols are believed to reduce morbidity and/or slow down the development of cardiovascular and neurodegenerative diseases as well as cancer. Biological activity of polyphenols is strongly related to their antioxidant properties. They tend to reduce the pool of reactive oxygen species…
Efficient Algorithms for Sequence Analysis with Entropic Profiles
2017
Entropy, being closely related to repetitiveness and compressibility, is a widely used information-related measure to assess the degree of predictability of a sequence. Entropic profiles are based on information theory principles, and can be used to study the under-/over-representation of subwords, by also providing information about the scale of conserved DNA regions. Here, we focus on the algorithmic aspects related to entropic profiles. In particular, we propose linear time algorithms for their computation that rely on suffix-based data structures, more specifically on the truncated suffix tree (TST) and on the enhanced suffix array (ESA). We performed an extensive experimental campaign …
Quantitatively characterizing drug-induced arrhythmic contractile motions of human stem cell-derived cardiomyocytes.
2018
Quantification of abnormal contractile motions of cardiac tissue has been a noteworthy challenge and significant limitation in assessing and classifying the drug-induced arrhythmias (i.e. Torsades de pointes). To overcome these challenges, researchers have taken advantage of computational image processing tools to measure contractile motion from cardiomyocytes derived from human induced pluripotent stem cells (hiPSC-CMs). However, the amplitude and frequency analysis of contractile motion waveforms doesn't produce sufficient information to objectively classify the degree of variations between two or more sets of cardiac contractile motions. In this paper, we generated contractile motion dat…
SpCLUST: Towards a fast and reliable clustering for potentially divergent biological sequences
2019
International audience; This paper presents SpCLUST, a new C++ package that takes a list of sequences as input, aligns them with MUSCLE, computes their similarity matrix in parallel and then performs the clustering. SpCLUST extends a previously released software by integrating additional scoring matrices which enables it to cover the clustering of amino-acid sequences. The similarity matrix is now computed in parallel according to the master/slave distributed architecture, using MPI. Performance analysis, realized on two real datasets of 100 nucleotide sequences and 1049 amino-acids ones, show that the resulting library substantially outperforms the original Python package. The proposed pac…
The Active Inference Approach to Ecological Perception: General Information Dynamics for Natural and Artificial Embodied Cognition
2018
The emerging neurocomputational vision of humans as embodied, ecologically embedded, social agents – who shape and are shaped by their environment – offers a golden opportunity to revisit and revise ideas about the physical and information-theoretic underpinnings of life, mind, and consciousness itself. In particular, the active inference framework (AIF) makes it possible to bridge connections from computational neuroscience and robotics/AI to ecological psychology and phenomenology, revealing common underpinnings and overcoming key limitations. AIF opposes the mechanistic to the reductive, while staying fully grounded in a naturalistic and information theoretic foundation, using the princi…