Optimization of K-NN algorithm by clustering and reliability coefficients: application to breast-cancer diagnosis

Abstract There is a growing trend towards data mining applications in medicine. Different algorithms have been explored by medical practitioners in an attempt to assist their work; the diagnosis of breast cancer is one of those applications. Machine learning algorithms are of vital importance to many medical problems, they can help to diagnose a disease, to detect its causes, to predict the outcome of a treatment, etc. K-Nearest Neighbors algorithm (KNN) is one of the simplest algorithms; it is widely used in predictive analysis. To optimize its performance and to accelerate its process, this paper proposes a new solution to speed up KNN algorithm based on clustering and attributes filtering. It also includes another improvement based on reliability coefficients which insures a more accurate classification. Thus, the contributions of this paper are three-fold: (i) the clustering of class instances, (ii) the selection of most significant attributes, and (iii) the ponderation of similarities by reliability coefficients. Results of the proposed approach exceeded most known classification techniques with an average f-measure exceeding 94% on the considered breast-cancer Dataset

Écoulements et rupture en milieu poreux déformable. Application au stockage géologique de CO2

Underground carbon dioxyde (CO2) storage operation in deep geological formation like saline aquifers or gas reservoirs is considered to be a prospective solution to reduce the emission of greenhouse gases into the atmosphere. However CO2 sealing injection has to be assured for centuries. Once setting, the cement is a few centimeters thickness interface between the rock and the casing. This cementeous interface appears as the most critical point for the sealing and containment of CO2. A continuous stream of CO2 being injected into reservoir rock formation will cause in a region around the injection water desaturation and drying shrinkage of the reservoir and the cement paste and potentially hydraulic fracture. Therefore, the moisture balance with the CO2 reservoir induces water desaturation and drying shrinkage. Some local stresses are then expected because of the strain incompatibility between the cement and the steel casing and the high pressures levels. These stresses may result in a cracking process along the interface and in a secondary cracks network. In this context, we investigate how the poromechanical theory should be extended using a energy approach framework to describe the fracture mechanic induced by the fluid injection in a porous medium. The original idea of this approach consists in deriving the poro-mechanical equations introducing explicitly the multiphase flow. This model, aims at describing coupled flows in a damageable elastic porous medium, due to the combined influence of hydraulic and pressure gradients simultaneously imposed. The numerical implementation is based on a standard finite element discretization and adaptation of a eigenerosion model to simulate cracking.Une des solutions visant à atténuer le changement climatique est le stockage géologique de CO2 dans des aquifères salins ou des réservoirs de pétrole - ou de gaz - en fin de vie. L'étanchéité des puits d'injection de CO2 doit cependant être garantie pour des durées séculaires. En théorie, le ciment coulé après le forage du puits entre le cuvelage en acier et la formation rocheuse a pour vocation de rétablir l'étanchéité naturelle entre les différentes couches géologiques traversées par le puits. Une fois pris, le ciment constitue une interface de quelques centimètres d'épaisseur entre la roche et le cuvelage. Cette interface cimentaire apparaît comme le point le plus critique vis-à-vis de l’étanchéité et du confinement CO2. En effet, le CO2 injecté étant sec et sous pression, la zone « proche puits » au niveau du point d'injection va s'assécher progressivement et s'étendre vers le toit du réservoir au fur et à mesure que le CO2 est injecté. L’interface se retrouve alors soumise à de fortes sollicitations hydriques induisant un séchage et de fortes contraintes mécaniques (réservoir de CO2). On s'attend donc à ce que ces contraintes engendrées par les incompatibilités de déformation entre les différents matériaux et les pressions d'injection soient par conséquent à l'origine d'une fissuration le long de l'interface et dans la zone proche puits. Dans ce contexte, nous nous intéressons à la manière dont le formalisme de la poromécanique doit être étendu en utilisant une approche énergétique de la mécanique de la rupture pour décrire ces phénomènes induit par l'injection de fluide sous pression dans un milieu poreux confiné. L’idée originale de cette démarche est de pouvoir décrire des écoulements couplés dans un milieu poreux élastique déformable et endommageable induits par une action combinée des gradients hydrauliques et de pressions imposés simultanément. Ce modèle devrait permettre une bonne compréhension, ainsi qu'une analyse théorique, de la physique mise en jeu dans ces processus complexes de transport pouvant provoquer la dégradation d’une structure. L’implémentation numérique s'appuie sur une discrétisation éléments finis standard et sur l’adaptation d’un modèle d'eigenerosion pour simuler l’apparition de fissures

improving parking availability prediction in smart cities with iot and ensemble based model

Abstract Smart cities are part of the ongoing advances in technology to provide a better life quality to its inhabitants. Urban mobility is one of the most important components of smart cities. Due to the growing number of vehicles in these cities, urban traffic congestion is becoming more common. In addition, finding places to park even in car parks is not easy for drivers who run in circles. Studies have shown that drivers looking for parking spaces contribute up to 30% to traffic congestion. In this context, it is necessary to predict the spaces available to drivers in parking lots where they want to park. We propose in this paper a new system that integrates the IoT and a predictive model based on ensemble methods to optimize the prediction of the availability of parking spaces in smart parking. The tests that we carried out on the Birmingham parking data set allowed to reach a Mean Absolute Error (MAE) of 0.06% on average with the algorithm of Bagging Regression (BR). This results have thus improved the best existing performance by over 6.6% while dramatically reducing system complexity

A simplified vertical and horizontal geomechanical model for compaction in sedimentary basins

In the context of mechanical compaction in sedimentary basins, we introduce a simple model including lateral deformations with the goal to improve the results obtained under oedometric conditions (i.e., neglecting horizontal strains) without losing much computational time. The model is based on a modified vertical porosity-stress law where horizontal strains are inserted and on an elastic stress-strain law with stress-dependent Young modulus. Though it is not three-dimensional and does not involve plasticity, we manage to validate the model on a geometrically and lithologically complex test case by comparing our results with those obtained on the same case using a full-dimensional finite-element simulator. We conclude that our model offers a significant improvement in accuracy against an oedometric model, with little loss in computational time, and so provides a useful tool to users who want a quick insight into results before running longer and more accurate simulations

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Fracture and multiphase flow in porous media within the context of geological storage of CO2

Une des solutions visant à atténuer le changement climatique est le stockage géologique de CO2 dans des aquifères salins ou des réservoirs de pétrole - ou de gaz - en fin de vie. L'étanchéité des puits d'injection de CO2 doit cependant être garantie pour des durées séculaires. En théorie, le ciment coulé après le forage du puits entre le cuvelage en acier et la formation rocheuse a pour vocation de rétablir l'étanchéité naturelle entre les différentes couches géologiques traversées par le puits. Une fois pris, le ciment constitue une interface de quelques centimètres d'épaisseur entre la roche et le cuvelage. Cette interface cimentaire apparaît comme le point le plus critique vis-à-vis de l’étanchéité et du confinement CO2. En effet, le CO2 injecté étant sec et sous pression, la zone « proche puits » au niveau du point d'injection va s'assécher progressivement et s'étendre vers le toit du réservoir au fur et à mesure que le CO2 est injecté. L’interface se retrouve alors soumise à de fortes sollicitations hydriques induisant un séchage et de fortes contraintes mécaniques (réservoir de CO2). On s'attend donc à ce que ces contraintes engendrées par les incompatibilités de déformation entre les différents matériaux et les pressions d'injection soient par conséquent à l'origine d'une fissuration le long de l'interface et dans la zone proche puits. Dans ce contexte, nous nous intéressons à la manière dont le formalisme de la poromécanique doit être étendu en utilisant une approche énergétique de la mécanique de la rupture pour décrire ces phénomènes induit par l'injection de fluide sous pression dans un milieu poreux confiné. L’idée originale de cette démarche est de pouvoir décrire des écoulements couplés dans un milieu poreux élastique déformable et endommageable induits par une action combinée des gradients hydrauliques et de pressions imposés simultanément. Ce modèle devrait permettre une bonne compréhension, ainsi qu'une analyse théorique, de la physique mise en jeu dans ces processus complexes de transport pouvant provoquer la dégradation d’une structure. L’implémentation numérique s'appuie sur une discrétisation éléments finis standard et sur l’adaptation d’un modèle d'eigenerosion pour simuler l’apparition de fissures.Underground carbon dioxyde (CO2) storage operation in deep geological formation like saline aquifers or gas reservoirs is considered to be a prospective solution to reduce the emission of greenhouse gases into the atmosphere. However CO2 sealing injection has to be assured for centuries. Once setting, the cement is a few centimeters thickness interface between the rock and the casing. This cementeous interface appears as the most critical point for the sealing and containment of CO2. A continuous stream of CO2 being injected into reservoir rock formation will cause in a region around the injection water desaturation and drying shrinkage of the reservoir and the cement paste and potentially hydraulic fracture. Therefore, the moisture balance with the CO2 reservoir induces water desaturation and drying shrinkage. Some local stresses are then expected because of the strain incompatibility between the cement and the steel casing and the high pressures levels. These stresses may result in a cracking process along the interface and in a secondary cracks network. In this context, we investigate how the poromechanical theory should be extended using a energy approach framework to describe the fracture mechanic induced by the fluid injection in a porous medium. The original idea of this approach consists in deriving the poro-mechanical equations introducing explicitly the multiphase flow. This model, aims at describing coupled flows in a damageable elastic porous medium, due to the combined influence of hydraulic and pressure gradients simultaneously imposed. The numerical implementation is based on a standard finite element discretization and adaptation of a eigenerosion model to simulate cracking

Increasing Verilog’s Generative Power

To cope with more complex circuits, well-understood higher-level abstraction mechanisms are needed. Verilog is already equipped with promising generative constructs making it possible to concisely describe a family of circuits as a parameterized module; however these constructs suffer from limited expressivity even in the latest IEEE standard. In this paper, we address generative constructs expressivity limitations, identifying the key extensions needed to overcome these limitations, and showing how to incorporate them in Verilog in a disciplined, backward-compatible way.This work was supported by the National Science Foundation (NSF) CPS award 1136099 and the Semiconductor Research Consortium (SRC) Task ID: 1403.001 (Intel custom project).</p

Incorporation of Preferences into Supply Chains DEA Efficiency: A Geometric Attribution Approach

Among many applications, several studies using Data Envelopment Analysis (DEA) have examined and studied the efficiency of supply chains. However, the majority of existing approaches dealing with this research area have ignored the important factor of decision makers’ preferences. The main objective of this article is to provide consistent DEA models that allow for efficiency analysis in order to determine the optimal allocation of resources according to these preferences. We propose three cases that are inspired from the geometric decomposition of preference attributions: (1) horizontal attribution, which is when decision makers treat each supply chain as a single non-detachable entity; (2) vertical attribution, which is when decision makers consider supply chains detachable and (3) combined attribution, which is when decision makers concurrently assign weights to the supply chain and to its members. Based on this suggested decomposition, new DEA models are developed, and an illustrative example is applied. The obtained results are relevant and show that DEA is capable of easily incorporating the preferences of decision-makers without resorting to weight restrictions on inputs or outputs

A branch-and-bound method for the single-machine scheduling problem under a non-availability constraint for maximum delivery time minimization

International audienceWe consider the single machine scheduling problem with release dates and tails, provided that the machine is unavailable during a fixed interval. We aim to minimize the maximum delivery time under the nonresumable senario. This problem is strongly NP- hard. The proposed algorithm is based on a branch- and- bound method. We use Jackson's preemptive algorithm with precedence constraints to compute the lower bound and Schrage's sequence as an upper bound. Numerical experiments show that the algorithm can solve large- size instances with up to 1000 jobs. (C) 2014 Elsevier Inc. All rights reserved