A foundation for machine learning in design

This paper presents a formalism for considering the issues of learning in design. A foundation for machine learning in design (MLinD) is defined so as to provide answers to basic questions on learning in design, such as, "What types of knowledge can be learnt?", "How does learning occur?", and "When does learning occur?". Five main elements of MLinD are presented as the input knowledge, knowledge transformers, output knowledge, goals/reasons for learning, and learning triggers. Using this foundation, published systems in MLinD were reviewed. The systematic review presents a basis for validating the presented foundation. The paper concludes that there is considerable work to be carried out in order to fully formalize the foundation of MLinD

Uncovering latent structure in valued graphs: A variational approach

As more and more network-structured data sets are available, the statistical analysis of valued graphs has become common place. Looking for a latent structure is one of the many strategies used to better understand the behavior of a network. Several methods already exist for the binary case. We present a model-based strategy to uncover groups of nodes in valued graphs. This framework can be used for a wide span of parametric random graphs models and allows to include covariates. Variational tools allow us to achieve approximate maximum likelihood estimation of the parameters of these models. We provide a simulation study showing that our estimation method performs well over a broad range of situations. We apply this method to analyze host--parasite interaction networks in forest ecosystems.Comment: Published in at http://dx.doi.org/10.1214/10-AOAS361 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Natural Kinds in Evolution and Systematics: Metaphysical and Epistemological Considerations

Despite the traditional focus on metaphysical issues in discussions of natural kinds in biology, epistemological considerations are at least as important. By revisiting the debate as to whether taxa are kinds or individuals, I argue that both accounts are metaphysically compatible but one or the other approach can be pragmatically preferable depending on the epistemic context. Recent objections against construing species as homeostatic property cluster kinds are also addressed. The second part of the paper broadens the perspective by considering homologues as another example of natural kinds, comparing them with analogues as functionally defined kinds. Given that there are various types of natural kinds, I discuss the different theoretical purposes served by diverse kind concepts, suggesting that there is no clear-cut distinction between natural kinds and other kinds, such as functional kinds. Rather than attempting to offer a unique metaphysical account of ‘natural’ kind, a more fruitful approach consists in the epistemological study of how different natural kind concepts are employed in scientific reasoning

Steps Towards a Method for the Formal Modeling of Dynamic Objects

Fragments of a method to formally specify object-oriented models of a universe of discourse are presented. The task of finding such models is divided into three subtasks, object classification, event specification, and the specification of the life cycle of an object. Each of these subtasks is further subdivided, and for each of the subtasks heuristics are given that can aid the analyst in deciding how to represent a particular aspect of the real world. The main sources of inspiration are Jackson System Development, algebraic specification of data- and object types, and algebraic specification of processes

Main Belt Asteroids with WISE/NEOWISE: Near-Infrared Albedos

We present revised near-infrared albedo fits of 2835 Main Belt asteroids observed by WISE/NEOWISE over the course of its fully cryogenic survey in 2010. These fits are derived from reflected-light near-infrared images taken simultaneously with thermal emission measurements, allowing for more accurate measurements of the near-infrared albedos than is possible for visible albedo measurements. As our sample requires reflected light measurements, it undersamples small, low albedo asteroids, as well as those with blue spectral slopes across the wavelengths investigated. We find that the Main Belt separates into three distinct groups of 6%, 16%, and 40% reflectance at 3.4 um. Conversely, the 4.6 um albedo distribution spans the full range of possible values with no clear grouping. Asteroid families show a narrow distribution of 3.4 um albedos within each family that map to one of the three observed groupings, with the (221) Eos family being the sole family associated with the 16% reflectance 3.4 um albedo group. We show that near-infrared albedos derived from simultaneous thermal emission and reflected light measurements are an important indicator of asteroid taxonomy and can identify interesting targets for spectroscopic followup.Comment: Accepted for publication in ApJ; full version of Table1 to be published electronically in the journa

The taxonomic distribution of asteroids from multi-filter all-sky photometric surveys

The distribution of asteroids across the Main Belt has been studied for decades to understand the compositional distribution and what that tells us about the formation and evolution of our solar system. All-sky surveys now provide orders of magnitude more data than targeted surveys. We present a method to bias-correct the asteroid population observed in the Sloan Digital Sky Survey (SDSS) according to size, distance, and albedo. We taxonomically classify this dataset consistent with the Bus and Bus-DeMeo systems and present the resulting taxonomic distribution. The dataset includes asteroids as small as 5 km, a factor of three in diameter smaller than in previous works. Because of the wide range of sizes in our sample, we present the distribution by number, surface area, volume, and mass whereas previous work was exclusively by number. While the distribution by number is a useful quantity and has been used for decades, these additional quantities provide new insights into the distribution of total material. We find evidence for D-types in the inner main belt where they are unexpected according to dynamical models of implantation of bodies from the outer solar system into the inner solar system during planetary migration (Levison et al. 2009). We find no evidence of S-types or other unexpected classes among Trojans and Hildas, albeit a bias favoring such a detection. Finally, we estimate for the first time the total amount of material of each class in the inner solar system. The main belt's most massive classes are C, B, P, V and S in decreasing order. Excluding the four most massive asteroids, Ceres, Pallas, Vesta and Hygiea that heavily skew the values, primitive material (C-, P-types) account for more than half main-belt and Trojan asteroids by mass, most of the remaining mass being in the S-types. All the other classes are minor contributors to the material between Mars and Jupiter.Comment: Accepted for publication in Icarus -- 43 pages, 15 figures, 7 table

Do functional traits improve prediction of predation rates for a disparate group of aphid predators?

Aphid predators are a systematically disparate group of arthropods united on the basis that they consume aphids as part of their diet. In Europe, this group includes Araneae, Opiliones, Heteroptera, chrysopids, Forficulina, syrphid larvae, carabids, staphylinids, cantharids and coccinellids. This functional group has no phylogenetic meaning but was created by ecologists as a way of understanding predation, particularly for conservation biological control. We investigated whether trait-based approaches could bring some cohesion and structure to this predator group. A taxonomic hierarchy-based null model was created from taxonomic distances in which a simple multiplicative relationship described the Linnaean hierarchies (species, genera, etc.) of fifty common aphid predators. Using the same fifty species, a functional groups model was developed using ten behavioural traits (e.g. polyphagy, dispersal, activity, etc.) to describe the way in which aphids were predated in the field. The interrelationships between species were then expressed as dissimilarities within each model and separately analysed using PROXSCAL, a multidimensional scaling (MDS) program. When ordinated using PROXSCAL and then statistically compared using Procrustes analysis, we found that only 17% of information was shared between the two configurations. Polyphagy across kingdoms (i.e. predatory behaviour across animal, plant and fungi kingdoms) and the ability to withstand starvation over days, weeks and months were particularly divisive within the functional groups model. Confirmatory MDS indicated poor prediction of aphid predation rates by the configurations derived from either model. The counterintuitive conclusion was that the inclusion of functional traits, pertinent to the way in which predators fed on aphids, did not lead to a large improvement in the prediction of predation rate when compared to the standard taxonomic approach

How to Identify Scientifc Revolutions?

Conceptualizing scientific revolutions by means of explicating their causes, their underlying structure and implications has been an important part of Kuhn's philosophy of science and belongs to its legacy. In this paper we show that such “explanatory concepts” of revolutions should be distinguished from a concept based on the identification criteria of scientific revolutions. The aim of this paper is to offer such a concept, and to show that it can be fruitfully used for a further elaboration of the explanatory conceptions of revolutions. On the one hand, our concept can be used to test the preciseness and accuracy of these conceptions, by examining to what extent their criteria fit revolutions as they are defined by our concept. On the other hand, our concept can serve as the basis on which these conceptions can be further specified. We will present four different explanatory concepts of revolutions – Kuhn's, Thagard's, Chen's and Barker's, and Laudan's – and point to the ways in which each of them can be further specified in view of our concept