ALGORITMOS EVOLUTIVOS MULTIOBJETIVO APLICADOS EM SELEÇÃO DE CARACTERÍSTICAS

A seleção de características (ou redução da dimensionalidade) é um dos principais emais utilizados métodos na mineração de dados. O objetivo da seleção de característicasé selecionar o subconjunto de características mais apropriado do conjunto de dadosoriginal, eliminando as características irrelevantes (Liu e Motoda 2002).Técnicas de seleção de características não alteram a representação original dasvariáveis, mas apenas selecionam um subconjunto delas. Assim, elas preservam asemântica original das variáveis, oferecendo, portanto, a vantagem de interpretabilidadepor um especialista sobre o domínio (Saeys et al ., 2007). Apesar dos benefícios que aseleção de características provê, existe o problema do equilíbrio entre redução eprecisão, onde se tenta manter a qualidade na classificação, minimizando a quantidadede dados.Na busca do melhor equilíbrio entre redução dos dados e precisão, diversasmetodologias vêm sendo propostas para selecionar características. No entanto, após oestudo dos trabalhos relacionados, notou-se que muitos utilizaram algoritmos evolutivospara seleção de características, mas nenhum deles é um Algoritmo EvolutivoMultiobjetivo (AEMO), apesar de tais métodos buscarem otimizar dois objetivosconsiderados conflitantes entre si, precisão e redução do custo computacional.Diante do exposto, este trabalho se propõe a avaliar a aplicação de três AEMOamplamente conhecidos pela comunidade científica, sendo eles, o Non-dominatedSorting Genetic Algorithm (NSGA-II) (Deb et al . , 2002), o NSGA-III (Deb & Jain,2014) e o Non-Dominated Sorting Genetic Algorithm Distance Oriented (NSGA-DO)(Pimenta & Camargo, 2015) na seleção de características em bases de dados, além devalidar a efetividade do método por meio de testes estatísticos

trans-1,2-Bis(3,5-dimethoxy­phen­yl)ethene

The title compound, C18H20O4, was prepared in high yield from 3,5-dimethoxy­styrene via a Ru-catalysed homo-olefin metathesis. Exclusive formation of the E-configurated isomer was observed. Inter­estingly, one symmetric unit contains two mol­ecules adopting an s-syn-anti and and an all-s-anti conformation

trans-Ethyl­enedi-p-phenyl­ene diacetate

The centrosymmetric title compound, C18H26O4, was prepared in high yield from 4-acetoxy­styrene via Ru-catalysed homo-olefin metathesis. Exclusive formation of the E-configurated isomer was observed. In the crystal, a strong C—H⋯π inter­molecular inter­action links the mol­ecules together

Alias calculus, change calculus and frame inference

Abstract Alias analysis, which determines whether two expressions in a program may reference to the same object, has many potential applications in program construction and verification. We have developed a theory for alias analysis, the "alias calculus", implemented its application to an object-oriented language, and integrated the result into a modern IDE. The calculus has a higher level of precision than many existing alias analysis techniques. One of the principal applications is to allow automatic change analysis, which leads to inferring "modifies clauses", providing a significant advance towards addressing the Frame Problem. Experiments were able to infer the "modifies" clauses of an existing formally specified library. Other applications, in particular to concurrent programming, also appear possible. The article presents the calculus, the application to frame inference including experimental results, and other projected applications. The ongoing work includes building more efficient model capturing aliasing properties and soundness proof for its essential elements

Protocol for Outcome Evaluation of Ayahuasca-Assisted Addiction Treatment : The Case of Takiwasi Center

The present study describes the protocol for the Ayahuasca Treatment Outcome Project (ATOP) with a special focus on the evaluation of addiction treatment services provided through Takiwasi Center, the first ATOP study site. The goal of the project is to assess treatment outcomes and understand the therapeutic mechanisms of an Ayahuasca-assisted, integrative treatment model for addiction rehabilitation in the Peruvian Amazon. The proposed intervention protocol highlights the significance of treatment setting in the design, delivery, and efficacy of an addiction rehabilitation program that involves the potent psychedelic tea known as Ayahuasca. After describing the context of the study, we put forth details about our mixed-methods approach to data collection and analysis, with which we seek to gain an understanding of why, how, and for whom this specific ayahuasca-assisted treatment program is effective across a range of outcomes. The ATOP protocol employs qualitative research methods as a means to determine which aspects of the setting are meaningful to clients and practitioners, and how this may correlate with outcome measures. This paper delineates the core principles, methods, and measures of the overall ATOP umbrella, then discusses the role of ATOP in the context of the literature on long-term residential programs. To conclude, we discuss the strengths and limitations of the protocol and the intended future of the project

Bis[5-chloro-2-(phenyl­diazenyl-κN 2)pyridine-κN]bis­(thio­cyanato-κN)iron(II)

In the title complex, [Fe(NCS)2(C11H8ClN3)2], the FeII atom is coordinated by two N atoms from the thio­cyanate ligands and four N atoms from two chelating 5-chloro-2-(phenyl­diazen­yl)pyridine ligands, generating a fairly regular FeN6 octa­hedral coordination geometry. The thio­cyanate ions are in a cis disposition and the pyridine N atoms are in a trans orientation. In the crystal, a short inter­molecular Cl⋯S contact [3.366 (3) Å] is observed

Method to predict the minimum measurement and experiment durations needed to achieve converged and significant results in a wind energy field experiment

Experiments offer incredible value to science, but results must always come with an uncertainty quantification to be meaningful. This requires grappling with sources of uncertainty and how to reduce them. In wind energy, field experiments are sometimes conducted with a control and treatment. In this scenario uncertainty due to bias errors can often be neglected as they impact both control and treatment approximately equally. However, uncertainty due to random errors propagates such that the uncertainty in the difference between the control and treatment is always larger than the random uncertainty in the individual measurements if the sources are uncorrelated. As random uncertainties are usually reduced with additional measurements, there is a need to know the minimum duration of an experiment required to reach acceptable levels of uncertainty. We present a general method to simulate a proposed experiment, calculate uncertainties, and determine both the measurement duration and the experiment duration required to produce statistically significant and converged results. The method is then demonstrated as a case study with a virtual experiment that uses real-world wind resource data and several simulated tip extensions to parameterize results by the expected difference in power. With the method demonstrated herein, experiments can be better planned by accounting for specific details such as controller switching schedules, wind statistics, and postprocess binning procedures such that their impacts on uncertainty can be predicted and the measurement duration needed to achieve statistically significant and converged results can be determined before the experiment.</p