Computing the set of Epsilon-efficient solutions in multiobjective space mission design

In this work, we consider multiobjective space mission design problems. We will start from the need, from a practical point of view, to consider in addition to the (Pareto) optimal solutions also nearly optimal ones. In fact, extending the set of solutions for a given mission to those nearly optimal significantly increases the number of options for the decision maker and gives a measure of the size of the launch windows corresponding to each optimal solution, i.e., a measure of its robustness. Whereas the possible loss of such approximate solutions compared to optimal—and possibly even ‘better’—ones is dispensable. For this, we will examine several typical problems in space trajectory design—a biimpulsive transfer from the Earth to the asteroid Apophis and two low-thrust multigravity assist transfers—and demonstrate the possible benefit of the novel approach. Further, we will present a multiobjective evolutionary algorithm which is designed for this purpose

The Gradient Free Directed Search Method as Local Search within Multi-objective Evolutionary Algorithms

Recently, the Directed Search Method has been proposed as a point-wise iterative search procedure that allows to steer the search, in any direction given in objective space, of a multi-objective optimization problem. While the original version requires the objectives’ gradients, we consider here a possible modification that allows to realize the method without gradient information. This makes the novel algorithm in particular interesting for hybridization with set oriented search procedures, such as multi-objective evolutionary algorithms. In this paper, we propose the DDS, a gradient free Directed Search method, and make a first attempt to demonstrate its benefit, as a local search procedure within a memetic strategy, by integrating the DDS into the well-known algorithmMOEA/D. Numerical results on some benchmark models indicate the advantage of the resulting hybrid

A study on using genetic niching for query optimisation in document retrieval

International audienceThis paper presents a new genetic approach for query optimisation in document retrieval. The main contribution of the paper is to show the effectiveness of the genetic niching technique to reach multiple relevant regions of the document space. Moreover, suitable merging procedures have been proposed in order to improve the retrieval evaluation. Experimental results obtained using a TREC sub-collection indicate that the proposed approach is promising for applications

Household Contamination with Salmonella enterica1

Household contamination with Salmonella enterica increases when occupational exposure exists (cattle farms with known salmonellosis in cattle, a salmonella research laboratory, or a veterinary clinic experiencing an outbreak of salmonellosis). Fifteen of 55 (27.2%) vacuum cleaner bags from households with occupational exposure to S. enterica were positive versus 1 of 24 (4.2% without known exposure. Use of a carpet cleaner and several cleaners/disinfectants reduced, but failed to eliminate, S. enterica from artificially contaminated carpet

Suscetibilidade de Anastrepha fraterculus (Diptera: Tephritidae) a iscas tóxicas formuladas com espinosinas.

A mosca-das-frutas Anastrepha fraterculus é a principal praga da fruticultura de clima temperado. Para o manejo da praga, uma alternativa é o emprego de iscas tóxicas que consiste na associação de um atrativo alimentar com um agente letal. No Brasil, as formulações de iscas tóxicas utilizam principalmente inseticidas fosforados como agente letal sendo as espinosinas uma alternativa. Nesse trabalho, foi avaliada a suscetibilidade de adultos de A. fraterculus a iscas tóxicas formuladas com inseticidas espinosade (Tracer? 480 SC) e espinetoram (Delegate? 250 WG) em mistura com os atrativos alimentares a base de proteína hidrolisada de milho (Biofruit? 3%) e melaço de cana-de-açúcar (7%).(Embrapa Uva e Vinho. Documentos, 99

Efeito de iscas tóxicas sobre o parasitoide Diachasmimorpha longicaudata (Hymenoptera: Braconidae) em laboratório.

As moscas-das-frutas causam prejuízos significativos aos fruticultores. A liberação de parasitoides da família Braconidae (Hymenoptera) é uma estratégia de Manejo Integrado da Praga que pode ser associada ao controle químico. Diachasmimorpha longicaudata é a espécie de parasitoide mais utilizada pela facilidade de multiplicação em laboratório e por ser efetivo sobre várias espécies de tefritídeos de importância econômica. Neste trabalho, foi avaliado em laboratório (temperatura: 24±2°C, UR: 70±10%) o efeito de iscas tóxicas sobre D. longicaudata.(Embrapa Uva e Vinho. Documentos, 99

Kinetics of the urea–urease clock reaction with urease immobilized in hydrogel beads

Feedback driven by enzyme catalyzed reactions occurs widely in biology and has been well characterized in single celled organisms such as yeast. There are still few examples of robust enzyme oscillators in vitro that might be used to study nonlinear dynamical behavior. One of the simplest is the urea–urease reaction that displays autocatalysis driven by the increase in pH accompanying the production of ammonia. A clock reaction was obtained from low to high pH in batch reactor and bistability and oscillations were reported in a continuous flow rector. However, the oscillations were found to be irreproducible and one contributing factor may be the lack of stability of the enzyme in solution at room temperature. Here, we investigated the effect of immobilizing urease in thiol-poly(ethylene glycol) acrylate (PEGDA) hydrogel beads, prepared using emulsion polymerization, on the urea–urease reaction. The resultant mm-sized beads were found to reproduce the pH clock and, under the conditions employed here, the stability of the enzyme was increased from hours to days

Machine Learning in Automated Text Categorization

The automated categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last ten years, due to the increased availability of documents in digital form and the ensuing need to organize them. In the research community the dominant approach to this problem is based on machine learning techniques: a general inductive process automatically builds a classifier by learning, from a set of preclassified documents, the characteristics of the categories. The advantages of this approach over the knowledge engineering approach (consisting in the manual definition of a classifier by domain experts) are a very good effectiveness, considerable savings in terms of expert manpower, and straightforward portability to different domains. This survey discusses the main approaches to text categorization that fall within the machine learning paradigm. We will discuss in detail issues pertaining to three different problems, namely document representation, classifier construction, and classifier evaluation.Comment: Accepted for publication on ACM Computing Survey