Search results for "LMA"

JOINT TOPOLOGY LEARNING AND GRAPH SIGNAL RECOVERY VIA KALMAN FILTER IN CAUSAL DATA PROCESSES

2018

In this paper, a joint graph-signal recovery approach is investigated when we have a set of noisy graph signals generated based on a causal graph process. By leveraging the Kalman filter framework, a three steps iterative algorithm is utilized to predict and update signal estimation as well as graph topology learning, called Topological Kalman Filter or TKF. Similar to the regular Kalman filter, we first predict the a posterior signal state based on the prior available data and then this prediction is updated and corrected based on the recently arrived measurement. But contrary to the conventional Kalman filter algorithm, we have no information of the transition matrix and hence we relate t…

Wind component estimation for UAS flying in turbulent air

2019

One of the most important problem of autonomous flight for UAS is the wind identification, especially for small scale vehicles. This research focusses on an identification methodology based on the Extended Kalman Filter (EKF). In particular authors focus their attention on.the filter tuning problem. The proposed procedure requires low computational power, so it is very useful for UAS. Besides it allows a robust wind component identification even when, as it is usually, the measurement data set is affected by noticeable noises. (C) 2019 Elsevier Masson SAS. All rights reserved.

Opinion dynamics in social networks through mean field games

2016

Emulation, mimicry, and herding behaviors are phenomena that are observed when multiple social groups interact. To study such phenomena, we consider in this paper a large population of homogeneous social networks. Each such network is characterized by a vector state, a vector-valued controlled input, and a vector-valued exogenous disturbance. The controlled input of each network aims to align its state to the mean distribution of other networks' states in spite of the actions of the disturbance. One of the contributions of this paper is a detailed analysis of the resulting mean-field game for the cases of both polytopic and $mathcal L_2$ bounds on controls and disturbances. A second contrib…

Using Inverse Reinforcement Learning with Real Trajectories to Get More Trustworthy Pedestrian Simulations

2020

Reinforcement learning is one of the most promising machine learning techniques to get intelligent behaviors for embodied agents in simulations. The output of the classic Temporal Difference family of Reinforcement Learning algorithms adopts the form of a value function expressed as a numeric table or a function approximator. The learned behavior is then derived using a greedy policy with respect to this value function. Nevertheless, sometimes the learned policy does not meet expectations, and the task of authoring is difficult and unsafe because the modification of one value or parameter in the learned value function has unpredictable consequences in the space of the policies it represents…

Las almadrabas del Reino de Valencia entre finales del siglo XVI e inicios del XVII

2018

DESDEO : An Open Framework for Interactive Multiobjective Optimization

2018

We introduce a framework for interactive multiobjective optimization methods called DESDEO released under an open source license. With the framework, we want to make interactive methods easily accessible to be applied in solving real-world problems. The framework follows an object-oriented software design paradigm, where functionalities have been divided to modular, self-contained components. The framework contains implementations of some interactive methods, but also components which can be utilized to implement more interactive methods and, thus, increase the applicability of the framework. To demonstrate how the framework can be used, we consider an example problem where the pollution of…

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…

Consequences of single-locus and tightly linked genomic architectures for evolutionary responses to environmental change

2020

AbstractGenetic and genomic architectures of traits under selection are key factors influencing evolutionary responses. Yet, knowledge of their impacts has been limited by a widespread assumption that most traits are controlled by unlinked polygenic architectures. Recent advances in genome sequencing and eco-evolutionary modelling are unlocking the potential for integrating genomic information into predictions of population responses to environmental change. Using eco-evolutionary simulations, we demonstrate that hypothetical single-locus control of a life history trait produces highly variable and unpredictable harvesting-induced evolution relative to the classically applied multi-locus mo…

Red wine extract disrupts Th17 lymphocyte differentiation in a colorectal cancer context

2020

International audience; Scope: Scope: It is well established that immune response and inflammation promote tumoral progression. Immune cells communicate through direct contact or through cytokine secretion, and it is the pro-inflammatory status that will tip the balance toward tumor progression or anti-tumor immunity. It is demonstrated here that a red wine extract (RWE) can decrease inflammation through its action on the inflammasome complex. This study determines whether an RWE could impact other key actors of inflammation, including T helper 17 (Th17) immune cells in particular. Methods and results: Methods and results: Using an RWE containing 4.16 g of polyphenols/liter of wine, it is s…

Sema3a plays a role in the pathogenesis of CHARGE syndrome

2018

CHARGE syndrome is an autosomal dominant malformation disorder caused by heterozygous loss of function mutations in the chromatin remodeler CHD7. Chd7 regulates the expression of Sema3a, which also contributes to the pathogenesis of Kallmann syndrome, a heterogeneous condition with the typical features hypogonadotropic hypogonadism and an impaired sense of smell. Both features are common in CHARGE syndrome suggesting that SEMA3A may provide a genetic link between these syndromes. Indeed, we find evidence that SEMA3A plays a role in the pathogenesis of CHARGE syndrome. First, Chd7 is enriched at the Sema3a promotor in neural crest cells and loss of function of Chd7 inhibits Sema3a expression…