Metric information and bound Bousso

Metric information and surface

Cognitive maps in the wild: revealing the use of metric information in black howler monkey route navigation

ABSTRACT When navigating, wild animals rely on internal representations of the external world – called ‘cognitive maps’ – to take movement decisions. Generally, flexible navigation is hypothesized to be supported by sophisticated spatial skills (i.e. Euclidean cognitive maps); however, constrained movements along habitual routes are the most commonly reported navigation strategy. Even though incorporating metric information (i.e. distances and angles between locations) in route-based cognitive maps would likely enhance an animal's navigation efficiency, there has been no evidence of this strategy reported for non-human animals to date. Here, we examined the properties of the cognitive map used by a wild population of primates by testing a series of cognitive hypotheses against spatially explicit movement simulations. We collected 3104 h of ranging and behavioural data on five groups of black howler monkeys (Alouatta pigra) at Palenque National Park, Mexico, from September 2016 through August 2017. We simulated correlated random walks mimicking the ranging behaviour of the study subjects and tested for differences between observed and simulated movement patterns. Our results indicated that black howler monkeys engaged in constrained movement patterns characterized by a high path recursion tendency, which limited their capacity to travel in straight lines and approach feeding trees from multiple directions. In addition, we found that the structure of observed route networks was more complex and efficient than simulated route networks, suggesting that black howler monkeys incorporate metric information into their cognitive map. Our findings not only expand the use of metric information during route navigation to non-human animals, but also highlight the importance of considering efficient route-based navigation as a cognitively demanding mechanism.

Optimizing the Maximal Perturbation in Point Sets while Preserving the Order Type

Recently a new kind of fiducial marker based on order type (OT) has been proposed. Using OT one can unequivocally identify a set of points through its triples of point orientation, and therefore, there is no need to use metric information. These proposed order type tags (OTTs) are invariant under a projective transformation which allows identification of them directly from a photograph. The magnitude of noise in the point positions that a set of points can support without changing its OT, is named the maximal perturbation (MP) value. This value represents the maximal displacement that any point in the set can have in any direction without changing the triplet’s orientation in the set. A higher value of the MP makes an OTT instance more robust to perturbations in the points positions. In this paper, we address the problem of how to improve the MP value for sets of points. We optimize “by hand” the MP for all the 16 subsets of points in the set of OTs composed of six points, and we also propose a general algorithm to optimize all the sets of OTs composed of six, seven, and eight points. Finally, we show several OTTs with improved MP values, and their use in an augmented reality application.

Heisenberg Modules over Quantum 2-tori are Metrized Quantum Vector Bundles

The modular Gromov–Hausdorff propinquity is a distance on classes of modules endowed with quantum metric information, in the form of a metric form of a connection and a left Hilbert module structure. This paper proves that the family of Heisenberg modules over quantum two tori, when endowed with their canonical connections, form a family of metrized quantum vector bundles, as a first step in proving that Heisenberg modules form a continuous family for the modular Gromov–Hausdorff propinquity.

AUTOMATING THE VERIFICATION OF HERITAGE BUILDING INFORMATION MODELS CREATED FROM POINT CLOUD DATA

<p><strong>Abstract.</strong> The use of remote sensors to acquire metric information for building information modelling (BIM) of heritage buildings is now common. Problematically, the creation of models from that information is still largely a manual and non-quantifiable process. As a result, a key aspect of the scan-to-BIM process is verification of the accuracy of the model in relation to the metric information. The most common method to check a model element constructed from a point cloud seems to be the analysis of deviations between this element and the corresponding point cloud (Anil et al., 2013; Tang et al., 2011). It is comprised of three main steps: the computation, the visualisation and the analysis of deviations. The verification process is particularly onerous for large-scale buildings where it is necessary to ensure that all elements of a model are consistent with metric data that may come from diverse sources (Chow and Fai, 2017). In this paper, we discuss the development of a plug-in for Autodesk Revit that automates this verification process.</p>

INFORMATION TECHNOLOGY OF SEARCHING COMPARATIVE COMPANIES FOR BUSINESS VALUATION USING INTELLIGENT AGENTS

The paper deals with developing information technology of data processing for solving business valuation problems based on the selection of comparative companies. An emerging IT company or a startup are taken as the object of study, for which traditional valuation methods are not apt. In terms of the research task there has been introduced the concept of a precedent - a company for which the search of analogues is being realized. The basic concepts of multi-agent systems are used. Four types of intelligent agents are presented that provide the implementation of the elements of the end-to-end technology: information search of objects with specified properties, intelligent processing of user requests, monitoring of objects, data mining. Stage sequence of the distributed decision-making technology has been considered. There are given metric and non-metric information processing mechanisms about analogues using metrics and proximity measures. The problem of non-metric information processing has been formulated. The tasks of data mining analysis have been defined, which are vital for monitoring the IT-companies in order to evaluate the business. The presented conclusions are summarized in the form of a complex information technology of data processing.

Permutation Entropy: New Ideas and Challenges

During the last years some new variants of Permutation entropy have been introduced and applied to EEG analysis, among them a conditional variant and variants using some additional metric information or being based on entropies different from the Shannon entropy. In some situations it is not completely clear what kind of information the new measures and their algorithmic implementations provide. We discuss the new developments and illustrate them for EEG data.