283 research outputs found
Gene-pool Optimal Mixing in Cartesian Genetic Programming
No full textGenetic Programming (GP) can make an important contribution to explainable artificial intelligence because it can create symbolic expressions as machine learning models. Nevertheless, to be explainable, the expressions must not become too large. This may, however, limit their potential to be accurate. The re-use of subexpressions has the unique potential to mitigate this issue. The Genetic Programming Gene-pool Optimal Mixing Evolutionary Algorithm (GP-GOMEA) is a recent model-based GP approach that has been found particularly capable of evolving small expressions. However, its tree representation offers no explicit mechanisms to re-use subexpressions. By contrast, the graph representation in Cartesian GP (CGP) is natively capable of re-use. For this reason, we introduce CGP-GOMEA, a variant of GP-GOMEA that uses graphs instead of trees. We experimentally compare various configurations of CGP-GOMEA with GP-GOMEA and find that CGP-GOMEA performs on par with GP-GOMEA on three common datasets. Moreover, CGP-GOMEA is found to produce models that re-use subexpressions more often than GP-GOMEA uses duplicate subexpressions. This indicates that CGP-GOMEA has unique added potential, allowing to find even smaller expressions than GP-GOMEA with similar accuracy
From Random Process to Chaotic Behavior in Swarms of UAVs
No full textpeer reviewedUnmanned Aerial Vehicles (UAVs) applications have seen an important increase in the last decade for both military and civilian applications ranging from fire and high seas rescue to military surveillance and target detection. While this technology is now mature for a single UAV, new methods are needed to operate UAVs in swarms, also referred to as fleets. This work focuses on the mobility management of one single autonomous swarm of UAVs which mission is to cover a given area in order to collect information. Several constraints are applied to the swarm to solve this problem due to the military context.
First, the UAVs mobility must be as unpredictable as possible to prevent any UAV tracking. However the Ground Control Station (GCS) operator(s) still needs to be able to forecast the UAVs paths. Finally, the UAVs are autonomous in order to guarantee the mission continuity in a hostile environment and the method must be distributed to ensure fault-tolerance of the system. To solve this problem, we introduce the Chaotic Ant Colony Optimization to Coverage (CACOC) algorithm that combines an Ant Colony Optimization approach (ACO) with a chaotic dynamical system. CACOC permits to obtain a deterministic but unpredictable system.
Its performance is compared to other state-of-the art models from the literature using several coverage-related metrics, i.e. coverage rate, recent coverage and fairness. Numerical results obtained by simulation underline the performance of our CACOC method: a deterministic method with unpredictable UAV trajectories that still ensures a high area coverage.R-AGR-0548 - ASIMUT (20150127-20170126) - BOUVRY Pasca
UAV Multilevel Swarms for Situation Management
No full textpeer reviewedThe development and usage of Unmanned Aerial Vehicles (UAVs) quickly increased in the last decades, mainly for military purposes. Nowadays, this type of technology is used in non-military contexts mainly for civil and environment protection: search & rescue teams, fire fighters, police officers, environmental scientific studies, etc. Although the technology for operating a single UAV is now mature, additional efforts are still necessary for using UAVs in fleets (or swarms).
This position paper presents the ASIMUT project (Aid to SItuation Management based on MUltimodal, MUltiUAVs, MUltilevel acquisition Techniques). The challenges of this project consist of handling several fleets of UAVs (swarms) including communication, networking and positioning aspects. This motivates the development of novel multilevel cooperation algorithms which is an area that has not been widely explored, especially when autonomy is an additional challenge. Moreover, we will provide techniques to optimize communications for multilevel swarms. Finally, we will develop distributed and localized mobility management algorithms that will cope with conflicting objectives such as connectivity maintenance and geographical area coverage.R-AGR-0548 - ASIMUT (20150127-20170126) - BOUVRY Pasca
Dense Gaussian Processes for Few-Shot Segmentation
No full textFew-shot segmentation is a challenging dense prediction task, which entails segmenting a novel query image given only a small annotated support set. The key problem is thus to design a method that aggregates detailed information from the support set, while being robust to large variations in appearance and context. To this end, we propose a few-shot segmentation method based on dense Gaussian process (GP) regression. Given the support set, our dense GP learns the mapping from local deep image features to mask values, capable of capturing complex appearance distributions. Furthermore, it provides a principled means of capturing uncertainty, which serves as another powerful cue for the final segmentation, obtained by a CNN decoder. Instead of a one-dimensional mask output, we further exploit the end-to-end learning capabilities of our approach to learn a high-dimensional output space for the GP. Our approach sets a new state-of-the-art on the PASCAL-5(i) and COCO-20(i) benchmarks, achieving an absolute gain of +8.4 mIoU in the COCO-20(i) 5-shot setting. Furthermore, the segmentation quality of our approach scales gracefully when increasing the support set size, while achieving robust cross-dataset transfer.</p
SOME REFLECTIONS ON CLIMATE CHANGE, GREEN GROWTH ILLUSIONS AND DEVELOPMENT SPACE
No full textMany economists and policy makers advocate a fundamental shift towards “green growth” as the new, qualitatively-different growth paradigm, based on enhanced material/resource/energy efficiency and drastic changes in the energy mix. “Green growth” may work well in creating new growth impulses with reduced environmental load and facilitating related technological and structural change. But can it also mitigate climate change at the required scale (i.e. significant, absolute and permanent decline of GHG emissions at global level) and pace? This paper argues that growth, technological, population-expansion and governance constraints as well as some key systemic issues cast a very long shadow on the “green growth” hopes. One should not deceive oneself into believing that such evolutionary (and often reductionist) approach will be sufficient to cope with the complexities of climate change. It may rather give much false hope and excuses to do nothing really fundamental that can bring about a U-turn of global GHG emissions. The proponents of a resource efficiency revolution and a drastic change in the energy mix need to scrutinize the historical evidence, in particular the arithmetic of economic and population growth. Furthermore, they need to realize that the required transformation goes beyond innovation and structural changes to include democratization of the economy and cultural change. Climate change calls into question the global equality of opportunity for prosperity (i.e. ecological justice and development space) and is thus a huge developmental challenge for the South and a question of life and death for some developing countries (who increasingly resist the framing of climate protection versus equity).
Voxel-based magnetic resonance image postprocessing in epilepsy
No full textOBJECTIVE: Although the general utility of voxel-based processing of structural magnetic resonance imaging (MRI) data for detecting occult lesions in focal epilepsy is established, many differences exist among studies, and it is unclear which processing method is preferable. The aim of this study was to compare the ability of commonly used methods to detect epileptogenic lesions in magnetic resonance MRI-positive and MRI-negative patients, and to estimate their diagnostic yield. METHODS: We identified 144 presurgical focal epilepsy patients, 15 of whom had a histopathologically proven and MRI-visible focal cortical dysplasia; 129 patients were MRI negative with a clinical hypothesis of seizure origin, 27 of whom had resections. We applied four types of voxel-based morphometry (VBM), three based on T1 images (gray matter volume, gray matter concentration, junction map [JM]) and one based on normalized fluid-attenuated inversion recovery (nFSI). Specificity was derived from analysis of 50 healthy controls. RESULTS: The four maps had different sensitivity and specificity profiles. All maps showed detection rates for focal cortical dysplasia patients (MRI positive and negative) of >30% at a strict threshold of p 60% with a liberal threshold of p < 0.0001 (uncorrected), except for gray matter volume (14% and 27% detection rate). All maps except nFSI showed poor specificity, with high rates of false-positive findings in controls. In the MRI-negative patients, absolute detection rates were lower. A concordant nFSI finding had a significant positive odds ratio of 7.33 for a favorable postsurgical outcome in the MRI-negative group. Spatial colocalization of JM and nFSI was rare, yet showed good specificity throughout the thresholds. SIGNIFICANCE: All VBM variants had specific diagnostic properties that need to be considered for an adequate interpretation of the results. Overall, structural postprocessing can be a useful tool in presurgical diagnostics, but the low specificity of some maps has to be taken into consideration
Can we prevent boom-bust cycles during euro area accession?
No full textEuro-area accession caused boom-bust cycles in several catching-up economies. Declining interest rates and easier financing conditions fuelled spending and worsened the current account balance. Over time inflation deteriorated external competitiveness and lowered domestic demand, turning the boom into a bust. We ask whether such a scenario can be avoided using macroeconomic tools that are available in the period of joining a monetary union: central parity revaluation, fiscal tightening or increased taxation. While all these policies can be used to cool down the output boom, exchange rate revaluation seems the most attractive option. It simultaneously trims the expansion of output and domestic demand, reduces the cost pressure and ranks first in terms of welfare. JEL Classification: E52, E58, E63Boom-bust cycles, dynamic general equilibrium models, euro area accession
The 7SK/P-TEFb snRNP controls ultraviolet radiation-induced transcriptional reprogramming
No full textConversion of promoter-proximally paused RNA polymerase II (RNAPII) into elongating polymerase by the positive transcription elongation factor b (P-TEFb) is a central regulatory step of mRNA synthesis. The activity of P-TEFb is controlled mainly by the 7SK small nuclear ribonucleoprotein (snRNP), which sequesters active P-TEFb into inactive 7SK/P-TEFb snRNP. Here we demonstrate that under normal culture conditions, the lack of 7SK snRNP has only minor impacts on global RNAPII transcription without detectable consequences on cell proliferation. However, upon ultraviolet (UV)-light-induced DNA damage, cells lacking 7SK have a defective transcriptional response and reduced viability. Both UV-induced release of "lesion-scanning" polymerases and activation of key early-responsive genes are compromised in the absence of 7SK. Proper induction of 7SK-dependent UV-responsive genes requires P-TEFb activity directly mobilized from the nucleoplasmic 7SK/P-TEFb snRNP. Our data demonstrate that the primary function of the 7SK/P-TEFb snRNP is to orchestrate the proper transcriptional response to stress
Predictors of a positive attitude of medical students towards general practice - a survey of three Bavarian medical faculties.
No full textGermany is witnessing an increasing shortage of general practitioners (GPs). The aim was to determine predictors of the job-related motivation of medical students of three medical faculties with different institutionalisation of general practice as an academic discipline.Medical students were surveyed with a standardised questionnaire about their attitudes towards general practice and their motivation to work as a GP in different working conditions. Predictors for positive attitudes and motivation were calculated using logistic regression models.940 (15.2%) out of 6182 medical students from three Bavarian medical faculties participated in an online survey. 585 (62.7%) were female, and the average age was 25.0 (standard deviation 3.7). The average grade of a university-entrance diploma was 1.6 (standard deviation 0.5). 718 (76.4%) could imagine working as a GP. However, they favoured being employed within another organisation and not having their own private practice (65.5% vs. 35.1%). "Presence of a professorship of general practice" was associated with a positive attitude towards general practice (OR 1.57; 95%CI 1.13-2.417). Motivation for working as a GP was associated with "being female" (OR 2.56; 95%CI 1.80-3.56) and "presence of a professorship of general practice" (OR 1.68; 95%CI 1.14-2.46). Having a lower grade for one's university-entrance diploma was associated with a higher preference to work in one's own practice (OR 1.39; 95%CI 1.02-1.90).A high amount of medical students were open-minded towards general practice. However, they favoured employment within an organization over working in their own practice. Institutionalisation of general practice as an academic discipline might be of importance to gain positive attitudes towards general practice and motivate medical students to work as a GP
Effects of Illicit Dexamethasone upon Hepatic Drug Metabolizing Enzymes and Related Transcription Factors mRNAs and Their Potential Use As Biomarkers in Cattle
No full textInternational audienceIn cattle fattening, the illicit use of growth promoters (GPs) represents a major problem. The synthetic corticosteroid dexamethasone (DEX) is the GP mostly used, alone or in combination with other steroids or β-agonists. Recently, GPs were shown to disrupt some cattle cytochromes P450 (CYPs) at the post-transcriptional level; therefore, the effects of two illicit protocols containing DEX (alone or together with 17β-estradiol, 17βE) upon main cattle liver drug metabolizing enzymes (DMEs) mRNAs and related transcription factors were investigated by quantitative real time RTPCR. Eleven genes, out of the 18 considered, were significantly modulated by GPs. Corticosteroidresponsive genes did not respond univocally, whereas retinoic X receptor alpha (RXRR) and estrogen receptor alpha (ERR) were upregulated depending on the illicit protocol used. Nowadays, an increasing interest has been noticed toward the detection of biomarkers of response (BMRs) to be used in the screening of GPs misuse in cattle farming. In the present study, CYP2B6-like, CYP2E1, glutathione S-transferase A1- and sulfotransferase A1-like (GSTA1- and SULT1A1-like) mRNAs were significantly modulated regardless of the GP, the illicit protocol, and the animal breed, representing promising BMRs. The usefulness of these BMRs needs to be characterized more in depth
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