New Eliahou Semigroups and Verification of the Wilf Conjecture for Genus up to 65

We give a graphical reinterpretation of the seeds algorithm to explore the tree of numerical semigroups. We then exploit the seeds algorithm to find all the Eliahou semigroups of genus up to 65. Since all these semigroups satisfy the Wilf conjecture, this shows that the Wilf conjecture holds up to genus 65

Transits and starspots in the WASP-19 planetary system

We have developed a new model for analysing light curves of planetary transits when there are starspots on the stellar disc. Because the parameter space contains a profusion of local minima we developed a new optimisation algorithm which combines the global minimisation power of a genetic algorithm and the Bayesian statistical analysis of the Markov chain. With these tools we modelled three transit light curves of WASP-19. Two light curves were obtained on consecutive nights and contain anomalies which we confirm as being due to the same spot. Using these data we measure the star's rotation period and velocity to be $11.76 \pm 0.09$ d and $3.88 \pm 0.15$\kms, respectively, at a latitude of 65$^\circ$. We find that the sky-projected angle between the stellar spin axis and the planetary orbital axis is $\lambda = 1.0^{\circ} \pm 1.2^{\circ}$, indicating axial alignment. Our results are consistent with and more precise than published spectroscopic measurements of the Rossiter-McLaughlin effect.Comment: 9 pages, 6 figures, 5 table

REAL-TIME DROWSY FACE DETECTION FOR ONLINE LEARNING BASED ON RANDOM FOREST AND DECISION TREE ALGORITHMS

In the current era, technology regarding artificial intelligence has developed rapidly and has been used in various areas of life. Face detection is one of the applications of Artificial Intelligence. This research aims to detect students' faces during the online learning process and succeeded in getting positive feedback when tested on students. Student detection includes drowsy and alertness. The method is via webcam in real-time so that the screen will show whether the student is drowsy or alert. In the trial, the teacher can find out who is in a drowsy and alert condition. On the other hand, students can find out that they fall into the drowsy or alert category. So that both parties immediately respond to what should be done based on the classification results. The algorithms used are Decision Tree and Random Forest. The accuracy results of the Random Forest algorithm are better than the Decision Tree algorithm, namely 65 percent, while the Decision Tree algorithm is 58 percent. The division of training data and test data uses a Kfold of 5. When Kfold is equal to 2, both algorithms have the highest accuracy, where Random Forest has an accuracy of 85 percent, and Decision Tre has an accuracy of 65 percent

Adaptive MCMC methods for inference on affine stochastic volatility models with jumps

In this paper we propose an efficient Markov chain Monte Carlo (MCMC) algorithm to estimate stochastic volatility models with jumps and affine structure. Our idea relies on the use of adaptive methods that aim at reducing the asymptotic variance of the estimates. We focus on the Delayed Rejection algorithm in order to find accurate proposals and to efficiently simulate the volatility path. Furthermore, Bayesian model selection is addressed through the use of reduced runs of the MCMC together with an auxiliary particle filter necessary to evaluate the likelihood function. An empirical application based on the study of the Dow Jones Composite 65 and of the FTSE 100 financial indexes is presented to study some empirical properties of the algorithm implemented

Customer mobility and congestion in supermarkets

The analysis and characterization of human mobility using population-level mobility models is important for numerous applications, ranging from the estimation of commuter flows in cities to modeling trade flows between countries. However, almost all of these applications have focused on large spatial scales, which typically range between intra-city scales to inter-country scales. In this paper, we investigate population-level human mobility models on a much smaller spatial scale by using them to estimate customer mobility flow between supermarket zones. We use anonymized, ordered customer-basket data to infer empirical mobility flow in supermarkets, and we apply variants of the gravity and intervening-opportunities models to fit this mobility flow and estimate the flow on unseen data. We find that a doubly-constrained gravity model and an extended radiation model (which is a type of intervening-opportunities model) can successfully estimate 65--70\% of the flow inside supermarkets. Using a gravity model as a case study, we then investigate how to reduce congestion in supermarkets using mobility models. We model each supermarket zone as a queue, and we use a gravity model to identify store layouts with low congestion, which we measure either by the maximum number of visits to a zone or by the total mean queue size. We then use a simulated-annealing algorithm to find store layouts with lower congestion than a supermarket's original layout. In these optimized store layouts, we find that popular zones are often in the perimeter of a store. Our research gives insight both into how customers move in supermarkets and into how retailers can arrange stores to reduce congestion. It also provides a case study of human mobility on small spatial scales

Anisotropic AGN Outflows and Enrichment of the Intergalactic Medium

We investigate the cosmological-scale influence of outflows driven by AGNs on metal enrichment of the intergalactic medium. AGNs are located in dense cosmological structures which tend to be anisotropic. We designed a semi-analytical model for anisotropic AGN outflows which expand away along the direction of least resistance. This model was implemented into a cosmological numerical simulation algorithm for simulating the growth of large-scale structure in the universe. Using this modified algorithm, we perform a series of 9 simulations inside cosmological volumes of size $(128 h^{-1}{\rm Mpc})^3$, in a concordance $\Lambda$CDM universe, varying the opening angle of the outflows, the lifetimes of the AGNs, their kinetic fractions, and their level of clustering. For each simulation, we compute the volume fraction of the IGM enriched in metals by the outflows. The resulting enriched volume fractions are relatively small at $z \gtrsim 2.5$, and then grow rapidly afterward up to $z = 0$. We find that AGN outflows enrich from 65% to 100% of the entire universe at the present epoch, for different values of the model parameters. The enriched volume fraction depends weakly on the opening angle of the outflows. However, increasingly anisotropic outflows preferentially enrich underdense regions, a trend found more prominent at higher redshifts and decreasing at lower redshifts. The enriched volume fraction increases with increasing kinetic fraction and decreasing AGN lifetime and level of clustering.Comment: 19 pages, 16 figures, submitted. The version uploaded here does not contain Figs 5, 6 & 7, because of their large sizes. Those can be found along with the full paper at: http://www.astro.phy.ulaval.ca/staff/paramita/AllPages/Talks-Posters/Papers_Thesis/ms_AGNoutflow.pd

Building a Sample of Distant Clusters of Galaxies

Candidate clusters of galaxies drawn from the sample identified from the moderately deep I-band data of the ESO Imaging Survey (EIS), have been used for follow-up optical/infrared imaging and spectroscopic observations. The observations were conducted to assess the nature of these candidates over a large range of redshifts. Currently, 163 EIS candidates have (V-I) colors, 15 have (I-K) and 65 cluster fields have been observed spectroscopically. From a preliminary analysis of these data, we find that > 65% of the candidates studied show strong evidence of being real physical associations, over the redshift range 0.2<z<1.1. The evidence in some cases comes directly from spectroscopic measurements, in others indirectly from the detection of overdensities of objects with either the same color or the same photometric redshift, or from a combination of color and spectroscopic information. Preliminary results also suggest that the redshift derived from the matched-filter algorithm is a reasonable measure of the cluster's redshift, possibly overestimating it by Delta z ~0.1, at least for systems at z<0.7. Overdensities of red objects have been detected in over 100 candidates, 38 of which with estimated redshifts >0.6, and six candidates in the interval 0.45<z<0.81 have either been identified directly from measured redshifts or have been confirmed by the measurement of at least one redshift for galaxies located along a red-sequence typical of cluster early-type galaxies. Lastly, five candidates among those already observed in the infrared have (I-Ks) colors consistent with them being in the redshift interval 0.8<z<1.1. The sample of "confirmed" clusters, already the largest of its kind in the southern hemisphere, will be further enlarged by ongoing observations.Comment: To appear in "Large Scale Structure in the X-ray Universe", ed. M. Plionis and I. Georgantopoulos (Paris: Editions Frontieres), in pres