Search results for "Adaptive"

An automatic quality system for injection molding

2007

This paper describes a fully automatic quality system for injection molding. The proposed system includes an on-line measurement platform with a digital camera, a methodology for adaptive design of experiments (DOE), statistical modeling, process monitoring, and a closed loop process control. The system has been tested in the manufacturing of plastic parts for mobile phones.

Robust Adaptive Modulation and Coding (AMC) selection in LTE systems using reinforcement learning

2014

Adaptive Modulation and Coding (AMC) in LTE networks is commonly employed to improve system throughput by ensuring more reliable transmissions. Most of existing AMC methods select the modulation and coding scheme (MCS) using pre-computed mappings between MCS indexes and channel quality indicator (CQI) feedbacks that are periodically sent by the receivers. However, the effectiveness of this approach heavily depends on the assumed channel model. In addition CQI feedback delays may cause throughput losses. In this paper we design a new AMC scheme that exploits a reinforcement learning algorithm to adjust at run-time the MCS selection rules based on the knowledge of the effect of previous AMC d…

Assessing the conservation values and tourism threats in Barrientos Island, Antarctic Peninsula

2019

Antarctica has been witnessing continued growth of tourism, both in the overall visitation and in the diversity of itineraries and visitor activities. Expanding tourism presents unique business and educational opportunities, but it is also putting immense pressure on Antarctica's natural, and for the most parts, pristine environment. Understanding the effectiveness of different tourism management strategies and instruments, like the Visitor Site Guidelines adopted by the Antarctic Treaty, is fundamental to the sustainable management of Antarctic tourism. The purpose of this study was to assess the effectiveness of Visitor Site Guidelines and other tourism management actions in reducing impa…

Estimation de la relation de salaires de Mincer : choix de specification et enjeux économétriques

2012

In the present doctoral thesis, we estimated Mincer’s (1974) semi logarithmic wage function for the French and Pakistani labour force data. This model is considered as a standard tool in order to estimate the relationship between earnings/wages and different contributory factors. Despite of its vide and extensive use, simple estimation of the Mincerian model is biased because of different econometric problems. The main sources of bias noted in the literature are endogeneity of schooling, measurement error, and sample selectivity. We have tackled the endogeneity and measurement error biases via instrumental variables two stage least squares approach for which we have proposed two new instrum…

Alcohol boosts pheromone production in male flies and makes them sexier

2020

The attraction of Drosophila melanogaster towards byproducts of alcoholic fermentation, especially ethanol, has been extensively studied 1–4. However, the adaptive value of this behavior has not been elucidated. Previous studies have suggested anthropomorphic interpretations of D. melanogaster behavior towards alcohols 5,6. Here, we instead assert that there exists a simple yet vital biological rationale for alcohol contact and consumption by these insects. We show that exposure to alcohols, especially methanol, results in an immediate amplification of fatty acid ester pheromone levels, which in turn elevates the probability that a male will successfully compete for a female during courtshi…

Evolutionary design optimization with Nash games and hybridized mesh/meshless methods in computational fluid dynamics

2012

Genre-adaptive Semantic Computing and Audio-based Modelling for Music Mood Annotation

2016

This study investigates whether taking genre into account is beneficial for automatic music mood annotation in terms of core affects valence, arousal, and tension, as well as several other mood scales. Novel techniques employing genre-adaptive semantic computing and audio-based modelling are proposed. A technique called the ACTwg employs genre-adaptive semantic computing of mood-related social tags, whereas ACTwg-SLPwg combines semantic computing and audio-based modelling, both in a genre-adaptive manner. The proposed techniques are experimentally evaluated at predicting listener ratings related to a set of 600 popular music tracks spanning multiple genres. The results show that ACTwg outpe…

On the use of approximate Bayesian computation Markov chain Monte Carlo with inflated tolerance and post-correction

2020

Approximate Bayesian computation allows for inference of complicated probabilistic models with intractable likelihoods using model simulations. The Markov chain Monte Carlo implementation of approximate Bayesian computation is often sensitive to the tolerance parameter: low tolerance leads to poor mixing and large tolerance entails excess bias. We consider an approach using a relatively large tolerance for the Markov chain Monte Carlo sampler to ensure its sufficient mixing, and post-processing the output leading to estimators for a range of finer tolerances. We introduce an approximate confidence interval for the related post-corrected estimators, and propose an adaptive approximate Bayesi…

Active and inactive quarantine in epidemic spreading on adaptive activity-driven networks

2020

We consider an epidemic process on adaptive activity-driven temporal networks, with adaptive behaviour modelled as a change in activity and attractiveness due to infection. By using a mean-field approach, we derive an analytical estimate of the epidemic threshold for SIS and SIR epidemic models for a general adaptive strategy, which strongly depends on the correlations between activity and attractiveness in the susceptible and infected states. We focus on strong social distancing, implementing two types of quarantine inspired by recent real case studies: an active quarantine, in which the population compensates the loss of links rewiring the ineffective connections towards non-quarantining …

Adaptive learning of compressible strings

2020

Suppose an oracle knows a string $S$ that is unknown to us and that we want to determine. The oracle can answer queries of the form "Is $s$ a substring of $S$?". In 1995, Skiena and Sundaram showed that, in the worst case, any algorithm needs to ask the oracle $\sigma n/4 -O(n)$ queries in order to be able to reconstruct the hidden string, where $\sigma$ is the size of the alphabet of $S$ and $n$ its length, and gave an algorithm that spends $(\sigma-1)n+O(\sigma \sqrt{n})$ queries to reconstruct $S$. The main contribution of our paper is to improve the above upper-bound in the context where the string is compressible. We first present a universal algorithm that, given a (computable) compre…