Explanation in Science

Scientific explanation is an important goal of scientific practise. Philosophers have proposed a striking diversity of seemingly incompatible accounts of explanation, from deductive-nomological to statistical relevance, unification, pragmatic, causal-mechanical, mechanistic, causal intervention, asymptotic, and model-based accounts. In this dissertation I apply two novel methods to reexamine our evidence about scientific explanation in practise and thereby address the fragmentation of philosophical accounts. I start by collecting a data set of 781 articles from one year of the journal Science. Using automated text mining techniques I measure the frequency and distribution of several groups of philosophically interesting words, such as explain , cause , evidence , theory , law , mechanism , and model . I show that explain words are much more common in scientific writing than in other genres, occurring in roughly half of all articles, and that their use is very often qualified or negated. These results about the use of words complement traditional conceptual analysis. Next I use random samples from the data set to develop a large number of small case studies across a wide range of scientific disciplines. I use a sample of explain sentences to develop and defend a new general philosophical account of scientific explanation, and then test my account against a larger set of randomly sampled sentences and abstracts. Five coarse categories can classify the explanans and explananda of my cases: data, entities, kinds, models, and theories. The pair of the categories of the explanans and explanandum indicates the form of an explanation. The explain-relation supports counterfactual reasoning about the dependence of qualities of the explanandum on qualities of the explanans. But for each form there is a different core relation between explanans and explanandum that supports the explain-relation. Causation, modelling, and argument are the core relations for different forms of scientific explanation between different categories of explanans and explananda. This flexibility allows me to resolve some of the fragmentation in the philosophical literature. I provide empirical evidence to show that my general philosophical account successfully describes a wide range of scientific practise across a large number of scientific disciplines

A multicriteria optimization framework for the definition of the spatial granularity of urban social media analytics

The spatial analysis of social media data has recently emerged as a significant source of knowledge for urban studies. Most of these analyses are based on an areal unit that is chosen without the support of clear criteria to ensure representativeness with regard to an observed phenomenon. Nonetheless, the results and conclusions that can be drawn from a social media analysis to a great extent depend on the areal unit chosen, since they are faced with the well-known Modifiable Areal Unit Problem. To address this problem, this article adopts a data-driven approach to determine the most suitable areal unit for the analysis of social media data. Our multicriteria optimization framework relies on the Pareto optimality to assess candidate areal units based on a set of user-defined criteria. We examine a case study that is used to investigate rainfall-related tweets and to determine the areal units that optimize spatial autocorrelation patterns through the combined use of indicators of global spatial autocorrelation and the variance of local spatial autocorrelation. The results show that the optimal areal units (30 km2 and 50 km2) provide more consistent spatial patterns than the other areal units and are thus likely to produce more reliable analytical results

Advances and Applications of Dezert-Smarandache Theory (DSmT) for Information Fusion (Collected Works), Vol. 4

The fourth volume on Advances and Applications of Dezert-Smarandache Theory (DSmT) for information fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics. The contributions (see List of Articles published in this book, at the end of the volume) have been published or presented after disseminating the third volume (2009, http://fs.unm.edu/DSmT-book3.pdf) in international conferences, seminars, workshops and journals. First Part of this book presents the theoretical advancement of DSmT, dealing with Belief functions, conditioning and deconditioning, Analytic Hierarchy Process, Decision Making, Multi-Criteria, evidence theory, combination rule, evidence distance, conflicting belief, sources of evidences with different importance and reliabilities, importance of sources, pignistic probability transformation, Qualitative reasoning under uncertainty, Imprecise belief structures, 2-Tuple linguistic label, Electre Tri Method, hierarchical proportional redistribution, basic belief assignment, subjective probability measure, Smarandache codification, neutrosophic logic, Evidence theory, outranking methods, Dempster-Shafer Theory, Bayes fusion rule, frequentist probability, mean square error, controlling factor, optimal assignment solution, data association, Transferable Belief Model, and others. More applications of DSmT have emerged in the past years since the apparition of the third book of DSmT 2009. Subsequently, the second part of this volume is about applications of DSmT in correlation with Electronic Support Measures, belief function, sensor networks, Ground Moving Target and Multiple target tracking, Vehicle-Born Improvised Explosive Device, Belief Interacting Multiple Model filter, seismic and acoustic sensor, Support Vector Machines, Alarm classification, ability of human visual system, Uncertainty Representation and Reasoning Evaluation Framework, Threat Assessment, Handwritten Signature Verification, Automatic Aircraft Recognition, Dynamic Data-Driven Application System, adjustment of secure communication trust analysis, and so on. Finally, the third part presents a List of References related with DSmT published or presented along the years since its inception in 2004, chronologically ordered

Application of GIS and Spatial Data Modeling to Archaeology: A Case Study in the American Southwest

One of the most important methodological advances in the archaeology of the past quarter century is the use of Geographic Information System (GIS) in archaeological research. Within this time frame, GIS has evolved from an emergent geospatial technology with limited mapmaking capabilities to a technology of choice for cultural resource managers, planners, and academic archaeologists alike. This dissertation examines the evolutionary trajectory and impact of GIS in the discipline since its introduction, and its potential to support new applications of GIS-driven innovation in archaeological research. As part of this project, two separate studies were conducted. The first study assessed adoption and diffusion trends for the technology based on the published literature from 1987-2010 using bibliometric and content analysis. These results suggest that despite adoption reaching a critical mass point in 2003-2006, GIS use is still maturing, and emphasis continues to be on methodological refinements rather than theoretical advances. Many of the technical developments coincide with larger changes within computing and in the convergence of technologies and platforms within the GIS industry. Recent publications, however, indicate the emergence of a possibly new direction for archaeological research which relies more on computationally intensive rather than empirical methods of investigation, in effect blurring traditional distinctions between method and theory. The second study conducted as part of this project explores the implications of this phenomenon by developing and implementing an application within a GIS environment for knowledge discovery in databases. The objective was to explore the feasibility and efficacy of geographic data mining using current technologies and archaeological data standards, identify barriers to its implementation, and demonstrate a new course for GIS-driven innovation in the field. Various archaeological and environmental datasets from the Fort Wingate Depot Activity in western New Mexico, USA were selected, compiled, prepared, and analyzed as part of the case study. Logistic regression was combined with Weights-of-Evidence modeling to discover previously unknown but statistically significant relationships and patterns within the prehistoric and historic data. This study offers suggestions on both how to adapt old data to new technologies and how to adapt new technologies to new ways of thinking

Evidentiality, egophoricity and engagement

The expression of knowledge in language (i.e. epistemicity) consists of a number of distinct notions and proposed categories that are only partly related to a well explored forms like epistemic modals. The aim of the volume is therefore to contribute to the ongoing exploration of epistemic marking systems in lesser-documented languages from the Americas, Papua New Guinea, and Central Asia from the perspective of language description and cross-linguistic comparison. As the title of the volume suggests, part of this exploration consists of situating already established notions (such as evidentiality) with the diversity of systems found in individual languages. Epistemic forms that feature in the present volume include ones that signal how speakers claim knowledge based on perceptual-cognitive access (evidentials); the speaker’s involvement as a basis for claiming epistemic authority (egophorics); the distribution of knowledge between the speech-participants where the speaker signals assumptions about the addressee’s knowledge of an event as either shared, or non-shared with the speaker (engagement marking)

Traffic Scene Perception for Automated Driving with Top-View Grid Maps

Ein automatisiertes Fahrzeug muss sichere, sinnvolle und schnelle Entscheidungen auf Basis seiner Umgebung treffen. Dies benötigt ein genaues und recheneffizientes Modell der Verkehrsumgebung. Mit diesem Umfeldmodell sollen Messungen verschiedener Sensoren fusioniert, gefiltert und nachfolgenden Teilsysteme als kompakte, aber aussagekräftige Information bereitgestellt werden. Diese Arbeit befasst sich mit der Modellierung der Verkehrsszene auf Basis von Top-View Grid Maps. Im Vergleich zu anderen Umfeldmodellen ermöglichen sie eine frühe Fusion von Distanzmessungen aus verschiedenen Quellen mit geringem Rechenaufwand sowie eine explizite Modellierung von Freiraum. Nach der Vorstellung eines Verfahrens zur Bodenoberflächenschätzung, das die Grundlage der Top-View Modellierung darstellt, werden Methoden zur Belegungs- und Elevationskartierung für Grid Maps auf Basis von mehreren, verrauschten, teilweise widersprüchlichen oder fehlenden Distanzmessungen behandelt. Auf der resultierenden, sensorunabhängigen Repräsentation werden anschließend Modelle zur Detektion von Verkehrsteilnehmern sowie zur Schätzung von Szenenfluss, Odometrie und Tracking-Merkmalen untersucht. Untersuchungen auf öffentlich verfügbaren Datensätzen und einem Realfahrzeug zeigen, dass Top-View Grid Maps durch on-board LiDAR Sensorik geschätzt und verlässlich sicherheitskritische Umgebungsinformationen wie Beobachtbarkeit und Befahrbarkeit abgeleitet werden können. Schließlich werden Verkehrsteilnehmer als orientierte Bounding Boxen mit semantischen Klassen, Geschwindigkeiten und Tracking-Merkmalen aus einem gemeinsamen Modell zur Objektdetektion und Flussschätzung auf Basis der Top-View Grid Maps bestimmt

Evidentiality, egophoricity and engagement

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