Abductively Robust Inference

Inference to the Best Explanation (IBE) is widely criticized for being an unreliable form of ampliative inference – partly because the explanatory hypotheses we have considered at a given time may all be false, and partly because there is an asymmetry between the comparative judgment on which an IBE is based and the absolute verdict that IBE is meant to license. In this paper, I present a further reason to doubt the epistemic merits of IBE and argue that it motivates moving to an inferential pattern in which IBE emerges as a degenerate limiting case. Since this inferential pattern is structurally similar to an argumentative strategy known as Inferential Robustness Analysis (IRA), it effectively combines the most attractive features of IBE and IRA into a unified approach to non-deductive inference

Variation in English subject extraction : the case of hyperactive subjects

International audienceStarting from the well known observation that for some speakers of English, wh-subjects extracted across a transitive predicate can bear accusative case, we investigate the syntax of the pattern in which a subject is wh-moved across a passive predicate. For a minority of speakers, in this second pattern the moved wh-subject can trigger agreement with the predicate in the matrix clause, yielding an apparent case of finite raising which we will call wh-raising. In attempt to offer a unified account of these two structures, we suggest that both are possible in a grammar that allows for DPs to be 'hyperactive' (Carstens 2011) and to take part in A-operations (i.e. syntactic phenomena related to Case and agreement) in more than one clause. The analysis that we propose is couched in the cartographic framework, and adopts the approach to subject extraction from Rizzi (2006) and Rizzi & Shlonsky (2006, 2007)

From patterned response dependency to structured covariate dependency: categorical-pattern-matching

Data generated from a system of interest typically consists of measurements from an ensemble of subjects across multiple response and covariate features, and is naturally represented by one response-matrix against one covariate-matrix. Likely each of these two matrices simultaneously embraces heterogeneous data types: continuous, discrete and categorical. Here a matrix is used as a practical platform to ideally keep hidden dependency among/between subjects and features intact on its lattice. Response and covariate dependency is individually computed and expressed through mutliscale blocks via a newly developed computing paradigm named Data Mechanics. We propose a categorical pattern matching approach to establish causal linkages in a form of information flows from patterned response dependency to structured covariate dependency. The strength of an information flow is evaluated by applying the combinatorial information theory. This unified platform for system knowledge discovery is illustrated through five data sets. In each illustrative case, an information flow is demonstrated as an organization of discovered knowledge loci via emergent visible and readable heterogeneity. This unified approach fundamentally resolves many long standing issues, including statistical modeling, multiple response, renormalization and feature selections, in data analysis, but without involving man-made structures and distribution assumptions. The results reported here enhance the idea that linking patterns of response dependency to structures of covariate dependency is the true philosophical foundation underlying data-driven computing and learning in sciences.Comment: 32 pages, 10 figures, 3 box picture

X-ray Phase-Contrast Imaging and Metrology through Unified Modulated Pattern Analysis

We present a method for x-ray phase-contrast imaging and metrology applications based on the sample-induced modulation and subsequent computational demodulation of a random or periodic reference interference pattern. The proposed unified modulated pattern analysis (UMPA) technique is a versatile approach and allows tuning of signal sensitivity, spatial resolution, and scan time. We characterize the method and demonstrate its potential for high-sensitivity, quantitative phase imaging, and metrology to overcome the limitations of existing methods

A Frequency Analysis of Monte-Carlo and other Numerical Integration Schemes

The numerical calculation of integrals is central to many computer graphics algorithms such as Monte-Carlo Ray Tracing. We show that such methods can be studied using Fourier analysis. Numerical error is shown to correspond to aliasing and the link between properties of the sampling pattern and the integrand is studied. The approach also permits the unified study of image aliasing and numerical integration, by considering a multidimensional domain where some dimensions are integrated while others are sampled

Aplikasi Rekomendasi Pola Makan Berbasis IOS

The goal for implementing this system is to help users manage and track history about their eat pattern, choose proper food for body\u27s need, and pick restaurants. Methodology used for this research contains three parts, which is analysis, design, and literature study. In requirement analysis, we do some interview with nutritionist and food provider, analysis iOS user, compare with same kind of application, and identify components that we need. In design method, we use Unified Modelling Language approach, ERD design, and user interface design. The result is a food planning mobile application with iOS platform. This application can help user manage and track their eat pattern, help user choose balanced food that suitable for their body, and inform user where they can get food they plan to eat