Explore the vast range of titles available.

This book provides a solution to the ecological inference problem, which has plagued users of statistical methods for over seventy-five years: How can researchers reliably infer individual-level behavior from aggregate (ecological) data? In political science, this question arises when individual-level surveys are unavailable (for instance, local or comparative electoral politics), unreliable (racial politics), insufficient (political geography), or infeasible (political history). This ecological inference problem also confronts researchers in numerous areas of major significance in public policy, and other academic disciplines, ranging from epidemiology and marketing to sociology and quantitative history. Although many have attempted to make such cross-level inferences, scholars agree that all existing methods yield very inaccurate conclusions about the world. In this volume, Gary King lays out a unique--and reliable--solution to this venerable problem. King begins with a qualitative overview, readable even by those without a statistical background. He then unifies the apparently diverse findings in the methodological literature, so that only one aggregation problem remains to be solved. He then presents his solution, as well as empirical evaluations of the solution that include over 16,000 comparisons of his estimates from real aggregate data to the known individual-level answer. The method works in practice. King's solution to the ecological inference problem will enable empirical researchers to investigate substantive questions that have heretofore proved unanswerable, and move forward fields of inquiry in which progress has been stifled by this problem.

We give algorithms with running time \\[2^{\\mathcal {O}({\\sqrt{k}\\log {k}})} \\cdot n^{\\mathcal {O}(1)}\\] for the following problems. Given an n-vertex unit disk graph G and an integer k, decide whether G containsa path on exactly/at least k vertices,a cycle on exactly k vertices,a cycle on at least k vertices,a feedback vertex set of size at most k, anda set of k pairwise vertex-disjoint cycles. For the first three problems, no subexponential time parameterized algorithms were previously known. For the remaining two problems, our algorithms significantly outperform the previously best known parameterized algorithms that run in time \\[2^{\\mathcal {O}(k^{0.75}\\log {k})} \\cdot n^{\\mathcal {O}(1)}\\]. Our algorithms are based on a new kind of tree decompositions of unit disk graphs where the separators can have size up to \\[k^{\\mathcal {O}(1)}\\] and there exists a solution that crosses every separator at most \\[\\mathcal {O}(\\sqrt{k})\\] times. The running times of our algorithms are optimal up to the \\[\\log {k}\\] factor in the exponent, assuming the exponential time hypothesis.

This paper reports the auxetic behavior of modified conventional non-woven fabric. The auxetic behavior of fabric was achieved by forming rotating square unit geometry with a highly ordered pattern of slits by laser cutting. Two commercial needle-punched non-woven fabric used as lining and the reinforcement fabric for the footwear industry were investigated. The influence of two rotating square unit sizes was analyzed for each fabric. The original and modified fabric samples were subjected to quasi-static tensile load by using the Tinius Olsen testing machine to observe the in-plane mechanical properties and deformation behavior of tested samples. The tests were recorded with a full high-definition (HD) digital camera and the video recognition technique was applied to determine the Poisson’s ratio evolution during testing. The results show that the modified samples exhibit a much lower breaking force due to induced slits, which in turn limits the application of such modified fabric to low tensile loads. The samples with smaller rotating cell sizes exhibit the highest negative Poisson’s ratio during tensile loading through the entire longitudinal strain range until rupture. Non-woven fabric with equal distribution and orientation of fibers in both directions offer better auxetic response with a smaller out-of-plane rotation of rotating unit cells. The out-of-plane rotation of unit cells in non-homogenous samples is higher in machine direction.

Bayesian Reasoning is both a fundamental idea of probability and a key model in applied sciences for evaluating situations of uncertainty. Bayesian Reasoning may be defined as the dealing with, and understanding of, Bayesian situations. This includes various aspects such as calculating a conditional probability (performance), assessing the effects of changes to the parameters of a formula on the result (covariation) and adequately interpreting and explaining the results of a formula (communication). Bayesian Reasoning is crucial in several non-mathematical disciplines such as medicine and law. However, even experts from these domains struggle to reason in a Bayesian manner. Therefore, it is desirable to develop a training course for this specific audience regarding the different aspects of Bayesian Reasoning. In this paper, we present an evidence-based development of such training courses by considering relevant prior research on successful strategies for Bayesian Reasoning (e.g., natural frequencies and adequate visualizations) and on the 4C/ID model as a promising instructional approach. The results of a formative evaluation are described, which show that students from the target audience (i.e., medicine or law) increased their Bayesian Reasoning skills and found taking part in the training courses to be relevant and fruitful for their professional expertise.

Questions involving Bayesian Reasoning often arise in events of everyday life, such as assessing the results of a breathalyser test or a medical diagnostic test. Bayesian Reasoning is perceived to be difficult, but visualisations are known to support it. However, prior research on visualisations for Bayesian Reasoning has only rarely addressed the issue on how to design such visualisations in the most effective way according to research on multimedia learning. In this article, we present a concise overview on subject-didactical considerations, together with the most fundamental research of both Bayesian Reasoning and multimedia learning. Building on these aspects, we provide a step-by-step development of the design of visualisations which support Bayesian problems, particularly for so-called double-trees and unit squares.

In this paper we show that the simple closed curve cannot be obtained as the inverse limit of an upper semi-continuous multivalued function from [0,1] into [0,1].

Reversible logic has gained importance in the last few decades because of its low power dissipation. Quantum cost, garbage outputs, ancillary inputs and gate count are some of the performance parameters used to weigh reversible designs against one another. Optimization of these parameters is of great relevance to obtain an optimal design. This paper presents the design of a reversible squaring and sum-of-squares units explored for a trade-off between garbage outputs and quantum cost. The proposed work focuses on the design of dedicated unsigned and signed squaring units with a generalized methodology for n-bit squaring unit and novel sum-of-squares unit. For the optimization of the squaring circuit, the redundant product terms from the multiplier logic are eliminated. The ancillary inputs are regenerated due to which the extraneous garbage outputs are reduced. The obtained results are compared with existing state-of-art designs for performance. The garbage-cost optimized designs were found to have a 50% improvement of both ancillary inputs and garbage outputs over the direct implementation; 51% improvement of ancillary inputs and 27% improvement of quantum cost over the garbage free designs. Usage of optimized dedicated sum-of-squares unit enhances the functionality of the digital signal processor.

A dyadic tile of order nn is any rectangle obtained from the unit square by nn successive bisections by horizontal or vertical cuts. Let each dyadic tile of order nn be available with probability pp, independent of the others. We prove that for pp sufficiently close to 11, there exists a set of pairwise disjoint available tiles whose union is the unit square, with probability tending to 11 as n→∞n\\to \\infty, as conjectured by Joel Spencer in 1999. In particular, we prove that if p=7/8p=7/8, such a tiling exists with probability at least 1−(3/4)n1-(3/4)^n. The proof involves a surprisingly delicate counting argument for sets of unavailable tiles that prevent tiling.

The design of a sampling unit, whether a simple plot or a subplot within a clustered structure, including shape and size, has received little attention in inferential forestry research. The use of auxiliary variables from remote sensing impacts the precision of estimators from both model-assisted and model-based inference perspectives. In both cases, model parameters are estimated from a sample of field plots and information from pixels corresponding to these units. In studies assisted by remote sensing, the shape of the plot used to fit regression models (typically circular) often differs from the shape of the population elements for prediction, where the area of interest is divided into equal tessellated parts. This raises interest in understanding the effect of the sampling unit shape on the mean of variables in forest stands of interest. Therefore, the objective of this study was to evaluate the effect of circular and square subplots, concentrically overlapped and arranged in an inverted Y cluster structure, over tree density, basal area, and aboveground biomass in a managed temperate forest in central Mexico. We used a Multivariate Generalised Linear Mixed Model, which considers the Gamma distribution of the variables and accounts for spatial correlation between Secondary Sampling Units nested within the Primary Sampling Unit. The main findings of this study indicate that the type of secondary sampling unit of the same area and centroid, whether circular or square, does not significantly affect the mean tree density (trees), basal area (m2), and aerial biomass.

Design criteria of low-cost, dual-concentric metasurface possessing wideband phase gradient (PG) are introduced. The radar cross-section reduction (RCSR) is explained by anomalous reflection that characterizes the superficial planar. The geometry consists of two single band RCSR modulated surfaces (MSs) that are triggered in each other. Each MS is built-up of square patch (SP) unit cells configured as a modulation structure to realize PG that causes anomalous reflection and monostatic RCSR behavior. Applying sinusoidal modulation to the sequence of the SP unit cells leads to the formation of PG along the surface and hence the intensity of the reflected wave is reduced for the broadside direction (θr=0∘). The proposed structure fabricated on a 0.8 mm thin FR-4 substrate extends over 249 × 249 mm2. It achieves a wide RCSR bandwidth from 20.9 GHz to 45.7 GHz (i.e., relative bandwidth of 75%) as designed in Dassault Systèmes (CST) Microwave Studio as a full-wave simulator and confirmed by the measurement results.