MRF-based image segmentation using Ant Colony System

In this paper, we propose a novel method for image segmentation that we call ACS-MRF method. ACS-MRF is a hybrid ant colony system coupled with a local search. We show how a colony of cooperating ants are able to estimate the labels field and minimize the MAP estimate. Cooperation between ants is performed by exchanging information through pheromone updating. The obtained results show the efficiency of the new algorithm, which is able to compete with other stochastic optimization methods like Simulated annealing and Genetic algorithm in terms of solution quality

Spatial Information based Image Clustering with A Swarm Approach

Fuzzy c-means algorithm (FCM) is one of the most used clustering methods for image segmentation. However, the conventional FCM algorithm presents some limits like its sensitivity to the noise because it does not take into consideration contextual information and its convergence to local minimum since it is based on a gradient descent method. In this paper, we present a new spatial fuzzy clustering algorithm optimized by the Artificial Bee Colony (ABC) algorithm. ABC-SFCM has two major characteristics. First it tackles better noisy image segmentation by making use of the spatial local information into the membership function. Secondly, it improves the global performance by taking advantages of the global search capability of ABC. Experiments with synthetic and real images show that ABC-SFCM is robust to noise compared to other methods.DOI: http://dx.doi.org/10.11591/ij-ai.v1i3.76

Hydrothermal complex of the Souk Ahras Basin: geological and hydrogeochemical approaches (north east of Algeria)

North- East of Algeria, in The Souk Ahras region, the Triassic evaporates are in the form of important intrusive masses. Thermal and cold water emerge from various training. These sources present are taking their pathways along the faulting system. A complex multilayered reservoir has significant potential water. The karstic aquifer consists mainly on fresh water. Thermal water characterized by high salinity is carbo-gaseous. Collection and chemical analysis of major water elements in addition to nonionic mineral compounds (SiO2) and trace elements (Sr2+, F-, Br-) have determined a deep saline fluid circulation. The tectonic effect would be responsible for the current water flow. Cartography of fracturing system has identified a NNW-SSE hot spring distribution. Similar alignment can match the faulting system direction affecting the concerned study area.Keywords: Triassic evaporate; thermal waters; tectonic; deep fluid circulatio

WALDATA : Wavelet transform based adversarial learning for the detection of anomalous trading activities

Detecting manipulative activities in stock market trading poses a significant challenge due to the complex temporal correlations inherent to the dynamically changing stock price data. This challenge is further exacerbated by the limited availability of labelled anomalous trading data instances. Stock price manipulations, which consist of infrequent anomalies in stock price trading data, are challenging to capture due to their sporadic occurrence and dynamically evolving nature. This scarcity and inherent complexity significantly complicate the creation of labelled datasets hence hinders the development of robust detection of different stock price manipulation schemes through supervised learning methods. Overcoming these challenges is crucial for enhancing our understanding of market dynamics and implementing robust market surveillance systems. To address these challenges, we introduce a novel stock price manipulation detection approach called WALDATA (Wavelet Transform based Adversarial Learning for the Detection of Anomalous Trading Activities). We leverage the Wavelet Transform (WT) to decompose non-stationary stock price time series into informative features and capture multi-scale dynamics within the data. We encode stock price data by transforming it into scalogram images through the Continuous Wavelet Transform, effectively converting stock price time series data into a 2D image representation. Subsequently, we employ a Generative Adversarial Network (GAN) architecture, originally applied to computer vision, to learn the underlying distribution of normal trading behaviour from the encoded images. We then train the discriminator as an anomaly detector for identifying manipulative trading activities in the stock market. The efficacy of WALDATA is rigorously evaluated on diverse real-world stock datasets using 1-level tick data from the LOBSTER project and the experimental results demonstrate the significant performance of our approach achieving an average AUC of 0.99 while maintaining low false alarm rates across various market conditions. These findings not only validate the effectiveness of the proposed WALDATA approach in accurately identifying stock price manipulations but also provide investors and regulators alike with valuable insights for the development of advanced market surveillance systems. This research demonstrates the promising potential of combining wavelet-based feature extraction and stock price time series to image representation with generative adversarial learning frameworks for anomaly detection in financial time series data. The successful implementation of WALDATA contributes to the development of advanced market surveillance systems and paves the way for further advancements in market surveillance, contributing towards a more efficient and robust financial system and a fair market environment

Parcours de vie, subjectivité et facteurs de la réussite chez les femmes professionnelles immigrantes d'origine maghrébine à Montréal

Au Québec, la population maghrébine est la communauté immigrante la plus importante d’un point de vue démographique. En raison de la sélection à l’immigration qui priorise les profils diplômés, compétents et francophones, les Maghrébines et Maghrébins qui s’installent au Québec sont très instruits. Cependant, la province ne tire pas le meilleur profit de cette immigration qualifiée puisque la population maghrébine se heurte à de nombreux obstacles en ce qui a trait à son insertion sur le marché du travail. En effet, plusieurs études démontrent l’existence de barrières à l’insertion socioprofessionnelle des personnes immigrantes à Montréal, particulièrement chez les femmes d’origine maghrébine. Cette recherche, pour sa part, s’intéresse aux femmes d’origine maghrébine à Montréal qui considèrent vivre une réussite. Dans cette perspective, serait-on en mesure de mieux comprendre et expliquer les situations d’échec des autres femmes immigrantes ? En quoi le parcours de celles qui considèrent vivre une réussite diffère-t-il de celui des autres ? Pour répondre à ces questions, l’analyse se concentre sur les facteurs qui entrent en jeu dans les parcours migratoires, précisément à ceux qui ont contribué à leur réussite, dont les réseaux sociaux et familiaux ainsi que l’agentivité, qui se révèlent en être au cœur. Également, cette étude considère exclusivement le point de vue de treize femmes d’origine maghrébine ainsi que leurs perceptions subjectives de la réussite en développant une étude de cas. Afin de documenter ces parcours migratoires, les récits de vie de ces participantes sont recueillis, depuis le pays de départ jusqu’à leur établissement à Montréal. Il en ressort que la réussite se conçoit dans la conciliation famille-travail-études, les aspirations professionnelles, l’entrepreneuriat, la tranquillité d’esprit ainsi qu’en l’honneur de leurs parents et des femmes racialisées et maghrébines qui les ont précédés.In Quebec, the Maghrebi population is the largest immigrant community. As a result of a selective immigration process that prioritizes qualified, competent, and French-speaking profiles, Maghrebi women and men who settle in Quebec are highly educated. However, the province does not make the most of this skilled immigration as the Maghrebi population faces significant social and professional challenges. Indeed, several studies expose the various obstacles Maghrebi immigrants, particularly women, face as they encounter Quebec’s labor market. This research focuses on Maghrebi women in Montreal who consider themselves successful. Could this perspective enable us to understand and explain the failure of other immigrant women? How do the experiences of those who consider themselves successful differ from the others? To answer these questions, this analysis focuses on the factors involved in women’s migratory paths and how they contributed to their success. Also, this research develops a case study around thirteen Maghrebi women’s subjective perceptions of success. Starting from their country of departure to their settlement in Montreal, the study documents these women’s migratory paths through their life stories. Helped by family and social networks, as well as personal agency and other factors, success arises from family-work balance, professional aspirations, entrepreneurship, peace of mind and flourishes in honor of the parents and the racialized women who preceded them