Reasoning Under Uncertainty: Towards Collaborative Interactive Machine Learning

In this paper, we present the current state-of-the-art of decision making (DM) and machine learning (ML) and bridge the two research domains to create an integrated approach of complex problem solving based on human and computational agents. We present a novel classification of ML, emphasizing the human-in-the-loop in interactive ML (iML) and more specific on collaborative interactive ML (ciML), which we understand as a deep integrated version of iML, where humans and algorithms work hand in hand to solve complex problems. Both humans and computers have specific strengths and weaknesses and integrating humans into machine learning processes might be a very efficient way for tackling problems. This approach bears immense research potential for various domains, e.g., in health informatics or in industrial applications. We outline open questions and name future challenges that have to be addressed by the research community to enable the use of collaborative interactive machine learning for problem solving in a large scale

Discovery and Creation: Alternative Theories of Entrepreneurial Action

As oportunidades empreendedoras existem, independentemente, das percepções dos empreendedores, esperando apenas para serem descobertas? Ou, estas oportunidades são criadas pelas ações dos empreendedores? Duas teorias, internamente, consistentes com as oportunidades empreendedoras são: teoria da criação e teoria da descoberta- as quais serão descritas. Enquanto, será sempre possível, descrever a formação de uma oportunidade particular, como exemplo, de um processo da descoberta ou da criação de oportunidade, estas duas teorias têm implicações importantes para a eficácia de uma variedade ampla de ações empreendedoras em contextos diferentes. As implicações destas teorias para sete destas ações serão descritas, acompanhadas de uma discussão sobre algumas das implicações teóricas mais amplas destas duas teorias para os campos do empreendimento e do gerenciamento estratégico

Population fluctuation of Spodoptera frugiperda eggs and natural parasitism by Trichogramma in maize.

This study aimed to evaluate the fluctuation of S. frugiperda eggs and natural parasitism by Trichogramma and identify and quantify parasitoid species in maize fields in the state of Rio Grande do Sul, Brazil. Surveys were carried out in two growing seasons: in 2006/2007 we assessed one growing season (late sowing) in Santa Maria, and in 2007/2008 we assessed two growing seasons (early and late sowing) in Santa Bárbara do Sul. Daily air temperature and rainfall were recorded at both locations. In each evaluation, entire plants were examined for the presence or absence of S. frugiperda egg masses, which were analyzed for larvae hatching or parasitoid emergence. The number of S. frugiperda eggs is higher between 8 and 30 days after plant emergence, decreasing in the later stages of maize growth; the occurrence of parasitoids begins about two days after pest egg occurrence; S. frugiperda egg parasitism is low; and eggs are parasitized by Trichogramma pretiosum and Trichogramma atopovirilia, with marked predominance of the first and possible occurrence of both parasitoid species in the same egg mass