Fast Back-Projection for Non-Line of Sight Reconstruction

Recent works have demonstrated non-line of sight (NLOS) reconstruction by using the time-resolved signal frommultiply scattered light. These works combine ultrafast imaging systems with computation, which back-projects the recorded space-time signal to build a probabilistic map of the hidden geometry. Unfortunately, this computation is slow, becoming a bottleneck as the imaging technology improves. In this work, we propose a new back-projection technique for NLOS reconstruction, which is up to a thousand times faster than previous work, with almost no quality loss. We base on the observation that the hidden geometry probability map can be built as the intersection of the three-bounce space-time manifolds defined by the light illuminating the hidden geometry and the visible point receiving the scattered light from such hidden geometry. This allows us to pose the reconstruction of the hidden geometry as the voxelization of these space-time manifolds, which has lower theoretic complexity and is easily implementable in the GPU. We demonstrate the efficiency and quality of our technique compared against previous methods in both captured and synthetic dat

Planeacion Financiera: Aplicación de las herramientas de la planeacion financiera en la Empresa Químicas Veterinarias S,A. en el periodo 2015-2016

Con esta investigación abordamos problemas de liquidez y rentabilidad que se estaban presentando en la empresa Químicas Veterinarias, S.A. con el objetivo de aplicar las principales herramientas de planeación financiera y explicar la importancia y utilidad de las mismas en toda empresa. Para llevar a cabo esta investigación, se utilizó la técnica de investigación documental y bibliográfica, además se revisó los principales Documentos de Gestión e información financiera de la empresa Químicas Veterinarias, S.A que se abordó en el caso práctico. Se logró así comprender en más detalle la problemática presentada por la Empresa. También se determinó las causas que generaron el problema y las posibles soluciones. Como solución, se implementaron las principales herramientas de planeación financiera como son: Presupuesto Maestro, Flujo de Caja Presupuestado y Estados Financieros Proforma, logrando así dar solución a los problemas de Liquidez con la Planeación del Efectivo y mejorar la Rentabilidad con la Planeación de las Utilidades a través del control y planificación de los gastos al analizar el efecto e importancia que los mismos presentaban en los Estados Financieros Proforma. Se puede concluir que las herramientas de planeación financiera son un instrumento de vital importancia en toda empresa si se quiere prolongar la existencia de la misma y si se quiere mantener un crecimiento y desarrollo sostenibles, puesto que con la planeación financiera adecuada se pueden alcanzar los objetivos estratégicos y mantener la “salud” financiera de empresa

Description logics of context

We introduce Description Logics of Context (DLCs)—an extension of Description Logics (DLs) for context-based reasoning. Our approach descends from J. McCarthy's tradition of treating contexts as formal objects over which one can quantify and express first-order properties. DLCs are founded in two-dimensional possible world semantics, where one dimension represents a usual object domain and the other a domain of contexts, and accommodate two interacting DL languages—the object and the context language—interpreted over their respective domains. Effectively, DLCs comprise a family of two-sorted , two-dimensional combinations of pairs of DLs. We argue that this setup ensures a well-grounded, generic framework for capturing and studying mechanisms of contextualization in the DL paradigm. As the main technical contribution, we prove 2ExpTime-completeness of the satisfiability problem in the maximally expressive DLC, based on the DL forumla . As an interesting corollary, we show that under certain conditions this result holds also for a range of two-dimensional DLs, including the prominent forumla

Combining DL-LiteNbool with branching time: a gentle marriage

We study combinations of the description logic DL-Lite_{bool}^N with the branching temporal logics CTL* and CTL. We analyse two types of combinations, both with rigid roles: (i) temporal operators are applied to concepts and to ABox assertions, and (ii) temporal operators are applied to concepts and Boolean combinations of concept inclusions and ABox assertions. For the resulting logics, we present algorithms for the satisfiability problem and (mostly tight) complexity bounds ranging from ExpTime to 3ExpTime

How do your rivals' releasing dates affect your box office?

In this paper, we study to what extent a movie's box office receipts are affected by the temporal distribution of rival films. We propose a theoretical model that analyses the effects of past, present and future releases on a film's results. Using this model we can analyse how rivals' release dates impact on others' box office revenues. This theoretical model also allows us to carry out some comparative statics by changing some relevant parameters such as time depreciation, film quality or the timeline of exhibition. We have tested the empirical implications of this model using information on the films released in five countries: the USA, the United Kingdom, Germany, France and Spain. In order to maintain a degree of homogeneity, we have constructed an unbalanced panel consisting of films that were released in at least three of these countries. The geographical dimension of our data set allows us to use panel data techniques to control for unobserved heterogeneity among the films released. This allows us to control for one of the most relevant features of the movie market, namely the presence of highly differentiated products.temporal competition, movie exhibition, film industry, panel data, unobserved heterogeneity, differentiated product

Beyond the grounding bottleneck: Datalog techniques for inference in probabilistic logic programs

State-of-the-art inference approaches in probabilistic logic programming typically start by computing the relevant ground program with respect to the queries of interest, and then use this program for probabilistic inference using knowledge compilation and weighted model counting. We propose an alternative approach that uses efficient Datalog techniques to integrate knowledge compilation with forward reasoning with a non-ground program. This effectively eliminates the grounding bottleneck that so far has prohibited the application of probabilistic logic programming in query answering scenarios over knowledge graphs, while also providing fast approximations on classical benchmarks in the field