Combinación varias Características para evaluar el contenido del resumen de texto

In this paper, we propose a method that evaluates the content of a text summary using a machine learning approach. This method operates by combining multiple features to build models that predict the PYRAMID scores for new summaries. We have tested several single and "Ensemble Learning" classifiers to build the best model. The evaluation of summarization system is made using the average of the scores of summaries that are built from each system. The results show that our method has achieved good performance in predicting the content score for a summary as well as for a summarization system.En este artículo proponemos un método que evalúa el contenido de un resumen de texto utilizando un enfoque de aprendizaje automático. Este método funciona combinando múltiples Características para construir modelos que predicen las puntuaciones PYRAMID para nuevos resúmenes. Hemos probado varios clasificadores individuales y "Ensemble Learning" para construir el mejor modelo. La evaluación del sistema de resumen se realiza utilizando el promedio de las puntuaciones de los resúmenes que se construyen a partir de cada sistema. Los resultados muestran que nuestro método ha logrado un buen rendimiento en la predicción de la puntuación de contenido para un resumen, así como para un sistema de resumen

Mathematical Model for CO₂ Emissions Reduction to Slow and Reverse Global Warming

This chapter aims to provide climate policy makers with smooth patterns of global carbon dioxide (CO2) emissions consistent with the UN climate targets. An accessible mathematical approach is used to design such models. First, the global warming is quantified with time to determine when the climate targets will be hit in case of no climate mitigation. Then, the remaining budget for CO2 emissions is derived based on recent data. Considering this for future emissions, first proposed is an exponential model for their rapid reduction and long-term stabilization slightly above zero. Then, suitable interpolations are performed to ensure a smooth and flexible transition to the exponential decline. Compared to UN climate simulation models, the designed smooth pathways would, in the short term, overcome a global lack of no-carbon energy and, in the long term, tolerate low emissions that will almost disappear as soon as desired from the 2040s with no need for direct removal of CO2

Mix Multiple Features to Evaluate the Content and the Linguistic Quality of Text Summaries

In this article, we propose a method of text summary\u27s content and linguistic quality evaluation that is based on a machine learning approach. This method operates by combining multiple features to build predictive models that evaluate the content and the linguistic quality of new summaries (unseen) constructed from the same source documents as the summaries used in the training and the validation of models. To obtain the best model, many single and ensemble learning classifiers are tested. Using the constructed models, we have achieved a good performance in predicting the content and the linguistic quality scores. In order to evaluate the summarization systems, we calculated the system score as the average of the score of summaries that are built from the same system. Then, we evaluated the correlation of the system score with the manual system score. The obtained correlation indicates that the system score outperforms the baseline scores

Application of statistical experimental design for optimisation of bioinsecticides production by sporeless Bacillus thuringiensis strain on cheap medium

In order to overproduce bioinsecticides production by a sporeless Bacillus thuringiensis strain, an optimal composition of a cheap medium was defined using a response surface methodology. In a first step, a Plackett-Burman design used to evaluate the effects of eight medium components on delta-endotoxin production showed that starch, soya bean and sodium chloride exhibited significant effects on bioinsecticides production. In a second step, these parameters were selected for further optimisation by central composite design. The obtained results revealed that the optimum culture medium for delta-endotoxin production consists of 30 g L(-1) starch, 30 g L(-1) soya bean and 9 g L(-1) sodium chloride. When compared to the basal production medium, an improvement in delta-endotoxin production up to 50% was noted. Moreover, relative toxin yield of sporeless Bacillus thuringiensis S22 was improved markedly by using optimised cheap medium (148.5 mg delta-endotoxins per g starch) when compared to the yield obtained in the basal medium (94.46 mg delta-endotoxins per g starch). Therefore, the use of optimised culture cheap medium appeared to be a good alternative for a low cost production of sporeless Bacillus thuringiensis bioinsecticides at industrial scale which is of great importance in practical point of view.Tunisian Ministry of Higher Education and Scientific Research

Data Preparation in Machine Learning for Condition-based Maintenance

ABSTRACT: Using Machine Learning (ML) prediction to achieve a successful, cost-effective, Condition-Based Maintenance (CBM) strategy has become very attractive in the context of Industry 4.0. In other fields, it is well known that in order to benefit from the prediction capability of ML algorithms, the data preparation phase must be well conducted. Thus, the objective of this paper is to investigate the effect of data preparation on the ML prediction accuracy of Gas Turbines (GTs) performance decay. First a data cleaning technique for robust Linear Regression imputation is proposed based on the Mixed Integer Linear Programming. Then, experiments are conducted to compare the effect of commonly used data cleaning, normalization and reduction techniques on the ML prediction accuracy. Results revealed that the best prediction accuracy of GTs decay, found with the k-Nearest Neighbors ML algorithm, considerately deteriorate when changing the data preparation steps and/or techniques. This study has shown that, for effective CBM application in industry, there is a need to develop a systematic methodology for design and selection of adequate data preparation steps and techniques with the proposed ML algorithms

Overcome of carbon catabolite repression of bioinsecticides production by sporeless Bacillus thuringiensis through adequate fermentation technology

The overcoming of catabolite repression, in bioinsecticides production by sporeless Bacillus thuringiensisstrain S22 was investigated into fully controlled 3 L fermenter, using glucose based medium. When applying adequate oxygen profile throughout the fermentation period (75% oxygen saturation), it was possible to partially overcome the catabolite repression, normally occurring at high initial glucose concentrations (30 and 40 g/L glucose). Moreover, toxin production yield by sporeless strain S22 was markedly improved by the adoption of the fed-batch intermittent cultures technology. With 22.5 g/L glucose used into culture medium, toxin production was improved by about 36% when applying fed-batch culture compared to one batch. Consequently, the proposed fedbatch strategy was efficient for the overcome of the carbon catabolite repression. So, it was possible to overproduce insecticidal crystal proteins into highly concentrated mediumTunisian Ministry of Higher Education and Scientific Research

Algorithme de recherche tabou pour la planification optimale d'une campagne marketing sur les moteurs de recherche

RÉSUMÉ : Avec l’essor de l’Internet et des moteurs de recherche, le Web marketing est devenu un métier à part entière qui s’est développé de manière totalement disruptive par rapport au marketing classique. Plusieurs paramètres forment la clé de voûte de la réussite d’une campagne de Web marketing dont : le choix des mots clés, le budget à allouer pour chaque mot clé, une bonne appréciation des attributs des cibles (langue, localisation, …) etc. Ce paramétrage est une tâche complexe à cause des quantités gigantesques de données à traiter d’où le recours grandissant à des firmes spécialisées dans la gestion des campagnes publicitaires sur Internet. Pour faire face à la très forte concurrence dans ce secteur de pointe, la société Aquisio, un leader mondial dans ce domaine, a lancé ce projet en collaboration avec l’École Polytechnique de Montréal. L’objectif étant de développer un module d’optimisation robuste permettant la gestion des campagnes publicitaires dans les moteurs de recherches d’Internet. Le présent projet de maîtrise porte sur le développement et l’implantation d’un module d’optimisation, à base de la recherche Tabou, dont le but est de maximiser le rendement de toute une campagne publicitaire sur Internet. L’efficacité de notre approche de résolution a été prouvée par des tests réalisés sur des échantillons de six bases de données fournies par notre partenaire industriel. En effet, l’utilisation du Tabou nous a permis de nous affranchir des limitations des méthodes d’optimisation généralement implantées dans les outils commerciaux. De plus la solution finale générée par notre module atteint aisément les 95% de la solution optimale et ceci est vrai pour les trois solutions initiales testées. Outre la bonne qualité des solutions, nous nous sommes également intéressés au temps d’exécution. Ainsi, en réduisant la taille du voisinage, nous avons réussi à générer des solutions de bonne qualité en un temps de calcul raisonnable, de l’ordre de quelques minutes. Mots clés : Web marketing, Optimisation, Recherche Tabou.----------ABSTRACT : With the rise of the Internet and search engines, Web marketing has become a profession in its own that has disrupted the evolution of traditional marketing. Several parameters are key to a successful Web marketing campaign including the selection of keywords, the budget allocated for each keyword, a good understanding of the attributes of the target (language, location, etc.). This configuration is an increasingly complex task due to the gigantic quantity of data to be processed. Thus, the use of specialized firms’ services for managing advertising campaigns on the Internet is continuously growing. To cope with the strong competition in this leading sector, the company Aquisio, a world leader in this field, launched this project in collaboration with the Polytechnic School of Montreal. The objective is to develop a robust optimization module for managing advertising campaigns in Internet search engines. This Master project focuses on the development and implementation of an optimization module, based on the Tabu Search, whose goal is to maximize the performance of any advertising campaign on the Internet. The effectiveness of our approach resolution was proved by tests conducted on samples of six databases provided by our industrial partner. Indeed, the use of Tabu has allowed us to overcome the limitations of optimization methods generally provided in commercial tools. In addition, the final solution generated by our module reaches easily 95% of the optimal solution and this is true for the initial three solutions tested. Besides the high quality of solutions, we are also interested to execution time. Thus, by reducing the size of the neighborhood, we were able to generate good solution quality in a reasonable computation time, on the order of a few minutes. Key words: Web marketing, Optimization, Tabu Searc

Tradition and Transformation: Frost’s “Home Burial” and the Poetics of Mild Transformation

In negotiation with the modernist literary agenda, Frost wrote his North of Boston and strived to publish it in London at a time when American publishers mostly aligned with the then-new trend of modernism. When the book won Frost both national and international acclaim – as it was favorably reviewed by Ezra Pound, one of the pillars of modernist poetry – Henry Holt hastened to win the prerogative of becoming Frost’s first American publisher. Endeavoring to understand the book’s special character, the present article sheds light on “Home Burial,” one of the narrative pieces in North of Boston which shows Robert Frost at his best as both traditionalist and innovator. A study of the poem’s poetic structure, narrative design, and language will seek to explain how the New England poet, thanks to the special strategy he adopts – what this article calls ‘poetics of mild transformation’– managed to reconcile the old with the new without wholly surrendering to the dictations of modernist poetics

A proteomic investigation of Aspergillus carbonarius exposed to yeast volatilome or to its major component 2-phenylethanol reveals major shifts in fungal metabolism

The use of yeast-derived volatile organic compounds (VOCs) represents a promising strategy for the biological control of various plant pathogens, including mycotoxin-producing fungi. Previous studies demonstrated the efficacy of the low-fermenting yeast Candida intermedia isolate 253 in reducing growth, sporulation, and ochratoxin A biosynthesis by Aspergillus carbonarius MPVA566. This study aimed to investigate whether the inhibitory effect of the yeast volatilome is solely attributable to 2-phenylethanol, its major component, or if a synergistic effect of all volatilome components is required to achieve an effective control of the fungal growth and metabolism. Microbiological methods, HPLC measurements and a UPLC-MS/MS approach were used to investigate the metabolic profile of A. carbonarius MPVA566 at different growing conditions: standard incubation (control), exposed to C. intermedia 253 volatilome, and incubation in the presence of 2-phenylethanol. Both yeast volatilome and 2-phenylethanol succeeded in the macroscopic inhibition of the radial mycelial growth, along with a significant reduction of ochratoxin A production. Functional classification of the fungal proteome identified in the diverse growing conditions revealed a different impact of both yeast VOCs and 2-phenylethanol exposure on the fungal proteome. Yeast VOCs target an array of metabolic routes of fungal system biology, including a marked reduction in protein biosynthesis, proliferative activity, mitochondrial metabolism, and particularly in detoxification of toxic substances. Exposure to 2-phenylethanol only partially mimicked the metabolic effects observed by the whole yeast volatilome, with protein biosynthesis and proliferative activity being reduced when compared with the control samples, but still far from the VOCs-exposed condition. This study represents the first investigation on the effects of yeast-derived volatilome and 2-phenylethanol on the metabolism of a mycotoxigenic fungus by means of proteomics analysis. Chemical compounds studied or used in this article: 2-Phenylethanol (PubChem CID: 6054); ochratoxin-A (PubChem CID: 442530); sodium dodecyl sulfate (PubChem CID: 3423265); dithiothreitol (PubChem CID: 446094); phenylmethylsulfonyl fluoride (PubChem CID: 4784); iodoacetamide (PubChem CID: 3727); ammonium bicarbonate (PubChem CID: 14013); acetic acid (PubChem CID: 176); and acetonitrile (PubChem CID: 6342). - 2019 The AuthorsThis publication was made possible by NPRP grant # 8-392-4-003 from the Qatar National Research Fund (a member of Qatar Foundation). The findings achieved herein are solely the responsibility of the authors.Scopu