Classification of airborne laser scanning point clouds based on binomial logistic regression analysis

This article presents a newly developed procedure for the classification of airborne laser scanning (ALS) point clouds, based on binomial logistic regression analysis. By using a feature space containing a large number of adaptable geometrical parameters, this new procedure can be applied to point clouds covering different types of topography and variable point densities. Besides, the procedure can be adapted to different user requirements. A binomial logistic model is estimated for all a priori defined classes, using a training set of manually classified points. For each point, a value is calculated defining the probability that this point belongs to a certain class. The class with the highest probability will be used for the final point classification. Besides, the use of statistical methods enables a thorough model evaluation by the implementation of well-founded inference criteria. If necessary, the interpretation of these inference analyses also enables the possible definition of more sub-classes. The use of a large number of geometrical parameters is an important advantage of this procedure in comparison with current classification algorithms. It allows more user modifications for the large variety of types of ALS point clouds, while still achieving comparable classification results. It is indeed possible to evaluate parameters as degrees of freedom and remove or add parameters as a function of the type of study area. The performance of this procedure is successfully demonstrated by classifying two different ALS point sets from an urban and a rural area. Moreover, the potential of the proposed classification procedure is explored for terrestrial data

Top-down Modulations in the Visual Form Pathway Revealed with Dynamic Causal Modeling

Perception entails interactions between activated brain visual areas and the records of previous sensations, allowing for processes like figure–ground segregation and object recognition. The aim of this study was to characterize top-down effects that originate in the visual cortex and that are involved in the generation and perception of form. We performed a functional magnetic resonance imaging experiment, where subjects viewed 3 groups of stimuli comprising oriented lines with different levels of recognizable high-order structure (none, collinearity, and meaning). Our results showed that recognizable stimuli cause larger activations in anterior visual and frontal areas. In contrast, when stimuli are random or unrecognizable, activations are greater in posterior visual areas, following a hierarchical organization where areas V1/V2 were less active with “collinearity” and the middle occipital cortex was less active with “meaning.” An effective connectivity analysis using dynamic causal modeling showed that high-order visual form engages higher visual areas that generate top-down signals, from multiple levels of the visual hierarchy. These results are consistent with a model in which if a stimulus has recognizable attributes, such as collinearity and meaning, the areas specialized for processing these attributes send top-down messages to the lower levels to facilitate more efficient encoding of visual form

Mapping bilateral information interests using the activity of Wikipedia editors

We live in a global village where electronic communication has eliminated the geographical barriers of information exchange. The road is now open to worldwide convergence of information interests, shared values, and understanding. Nevertheless, interests still vary between countries around the world. This raises important questions about what today's world map of in- formation interests actually looks like and what factors cause the barriers of information exchange between countries. To quantitatively construct a world map of information interests, we devise a scalable statistical model that identifies countries with similar information interests and measures the countries' bilateral similarities. From the similarities we connect countries in a global network and find that countries can be mapped into 18 clusters with similar information interests. Through regression we find that language and religion best explain the strength of the bilateral ties and formation of clusters. Our findings provide a quantitative basis for further studies to better understand the complex interplay between shared interests and conflict on a global scale. The methodology can also be extended to track changes over time and capture important trends in global information exchange.Comment: 11 pages, 3 figures in Palgrave Communications 1 (2015

LINEAR FEATURES IN PHOTOGRAMMETRY

Traditional photogrammetric activities such as orientation, triangulation, and object space reconstruction have been relying on distinct points in their underlying operations. With the evolution of digital photogrammetry, there has been a tremendous interest in utilizing linear features in various photogrammetric activities. This interest has been motivated by the fact that the extraction of linear features from the image space is easier to automate than distinct points. On the other hand, object space linear features can be directly derived form terrestrial Mobile Mapping Systems (MMS), GIS databases, and/or existing maps. Moreover, automatic matching of linear features, either within overlapping images or between image and object space, is easier than that of distinct points. Finally, linear features possess more semantic information than distinct points since they most probably correspond to object boundaries. Such semantics can be automatically identified in imagery to facilitate higher-level tasks (e.g., surface reconstruction and object recognition). This paper summarizes the use of linear features, which might be represented by analytical functions (e.g., straight-line segments) or irregular (freeform) shapes, in photogrammetric activities such as automatic space resection, photogrammetric triangulation, camera calibration, image matching, surface reconstruction, image-to-image registration, and absolute orientation. Current progress, future expectations, and possible research directions are discussed as well

What residualizing predictors in regression analyses does (and what it does not do)

Psycholinguists are making increasing use of regression analyses and mixed-effects modeling. In an attempt to deal with concerns about collinearity, a number of researchers orthogonalize predictor variables by residualizing (i.e., by regressing one predictor onto another, and using the residuals as a stand-in for the original predictor). In the current study, the effects of residualizing predictor variables are demonstrated and discussed using ordinary least-squares regression and mixed-effects models. Some of these effects are almost certainly not what the researcher intended and are probably highly undesirable. Most importantly, what residualizing does not do is change the result for the residualized variable, which many researchers probably will find surprising. Further, some analyses with residualized variables cannot be meaningfully interpreted. Hence, residualizing is not a useful remedy for collinearity

Analyzing gender inequality through large-scale Facebook advertising data

Online social media are information resources that can have a transformative power in society. While the Web was envisioned as an equalizing force that allows everyone to access information, the digital divide prevents large amounts of people from being present online. Online social media in particular are prone to gender inequality, an important issue given the link between social media use and employment. Understanding gender inequality in social media is a challenging task due to the necessity of data sources that can provide large-scale measurements across multiple countries. Here we show how the Facebook Gender Divide (FGD), a metric based on aggregated statistics of more than 1.4 Billion users in 217 countries, explains various aspects of worldwide gender inequality. Our analysis shows that the FGD encodes gender equality indices in education, health, and economic opportunity. We find gender differences in network externalities that suggest that using social media has an added value for women. Furthermore, we find that low values of the FGD are associated with increases in economic gender equality. Our results suggest that online social networks, while suffering evident gender imbalance, may lower the barriers that women have to access informational resources and help to narrow the economic gender gap

The source ambiguity problem: Distinguishing the effects of grammar and processing on acceptability judgments

Judgments of linguistic unacceptability may theoretically arise from either grammatical deviance or significant processing difficulty. Acceptability data are thus naturally ambiguous in theories that explicitly distinguish formal and functional constraints. Here, we consider this source ambiguity problem in the context of Superiority effects: the dispreference for ordering a wh-phrase in front of a syntactically “superior” wh-phrase in multiple wh-questions, e.g., What did who buy? More specifically, we consider the acceptability contrast between such examples and so-called D-linked examples, e.g., Which toys did which parents buy? Evidence from acceptability and self-paced reading experiments demonstrates that (i) judgments and processing times for Superiority violations vary in parallel, as determined by the kind of wh-phrases they contain, (ii) judgments increase with exposure, while processing times decrease, (iii) reading times are highly predictive of acceptability judgments for the same items, and (iv) the effects of the complexity of the wh-phrases combine in both acceptability judgments and reading times. This evidence supports the conclusion that D-linking effects are likely reducible to independently motivated cognitive mechanisms whose effects emerge in a wide range of sentence contexts. This in turn suggests that Superiority effects, in general, may owe their character to differential processing difficulty