Query processing of spatial objects: Complexity versus Redundancy

The management of complex spatial objects in applications, such as geography and cartography, imposes stringent new requirements on spatial database systems, in particular on efficient query processing. As shown before, the performance of spatial query processing can be improved by decomposing complex spatial objects into simple components. Up to now, only decomposition techniques generating a linear number of very simple components, e.g. triangles or trapezoids, have been considered. In this paper, we will investigate the natural trade-off between the complexity of the components and the redundancy, i.e. the number of components, with respect to its effect on efficient query processing. In particular, we present two new decomposition methods generating a better balance between the complexity and the number of components than previously known techniques. We compare these new decomposition methods to the traditional undecomposed representation as well as to the well-known decomposition into convex polygons with respect to their performance in spatial query processing. This comparison points out that for a wide range of query selectivity the new decomposition techniques clearly outperform both the undecomposed representation and the convex decomposition method. More important than the absolute gain in performance by a factor of up to an order of magnitude is the robust performance of our new decomposition techniques over the whole range of query selectivity

Faster k-Medoids Clustering: Improving the PAM, CLARA, and CLARANS Algorithms

Clustering non-Euclidean data is difficult, and one of the most used algorithms besides hierarchical clustering is the popular algorithm Partitioning Around Medoids (PAM), also simply referred to as k-medoids. In Euclidean geometry the mean-as used in k-means-is a good estimator for the cluster center, but this does not hold for arbitrary dissimilarities. PAM uses the medoid instead, the object with the smallest dissimilarity to all others in the cluster. This notion of centrality can be used with any (dis-)similarity, and thus is of high relevance to many domains such as biology that require the use of Jaccard, Gower, or more complex distances. A key issue with PAM is its high run time cost. We propose modifications to the PAM algorithm to achieve an O(k)-fold speedup in the second SWAP phase of the algorithm, but will still find the same results as the original PAM algorithm. If we slightly relax the choice of swaps performed (at comparable quality), we can further accelerate the algorithm by performing up to k swaps in each iteration. With the substantially faster SWAP, we can now also explore alternative strategies for choosing the initial medoids. We also show how the CLARA and CLARANS algorithms benefit from these modifications. It can easily be combined with earlier approaches to use PAM and CLARA on big data (some of which use PAM as a subroutine, hence can immediately benefit from these improvements), where the performance with high k becomes increasingly important. In experiments on real data with k=100, we observed a 200-fold speedup compared to the original PAM SWAP algorithm, making PAM applicable to larger data sets as long as we can afford to compute a distance matrix, and in particular to higher k (at k=2, the new SWAP was only 1.5 times faster, as the speedup is expected to increase with k)

Predicting the Next Best View for 3D Mesh Refinement

3D reconstruction is a core task in many applications such as robot navigation or sites inspections. Finding the best poses to capture part of the scene is one of the most challenging topic that goes under the name of Next Best View. Recently, many volumetric methods have been proposed; they choose the Next Best View by reasoning over a 3D voxelized space and by finding which pose minimizes the uncertainty decoded into the voxels. Such methods are effective, but they do not scale well since the underlaying representation requires a huge amount of memory. In this paper we propose a novel mesh-based approach which focuses on the worst reconstructed region of the environment mesh. We define a photo-consistent index to evaluate the 3D mesh accuracy, and an energy function over the worst regions of the mesh which takes into account the mutual parallax with respect to the previous cameras, the angle of incidence of the viewing ray to the surface and the visibility of the region. We test our approach over a well known dataset and achieve state-of-the-art results.Comment: 13 pages, 5 figures, to be published in IAS-1

The Epistemology of Intentionality: Notional Constituents vs. Direct Grasp

Franz Brentano is well known for highlighting the importance of intentionality, but he said curiously little about the nature of intentionality. According to Mark Textor, there is a deep reason for this: Brentano took intentionality to be a conceptual primitive the nature of which is revealed only in direct grasp. Although there is certainly textual support for this interpretation, it appears in tension with Brentano’s repeated attempts to analyze intentionality in terms of ‘notional constituents’ – aspects of intentionality which cannot come apart in reality but which can be conceptually distinguished. After bringing out this tension, I explore some options for resolving it, ultimately offering my own favored interpretation

Personhood, consciousness, and god : how to be a proper pantheist

© Springer Nature B.V. 2018In this paper I develop a theory of personhood which leaves open the possibility of construing the universe as a person. If successful, it removes one bar to endorsing pantheism. I do this by examining a rising school of thought on personhood, on which persons, or selves, are understood as identical to episodes of consciousness. Through a critique of this experiential approach to personhood, I develop a theory of self as constituted of qualitative mental contents, but where these contents are also capable of unconscious existence. On this theory, though we can be conscious of our selves, consciousness turns out to be inessential to personhood. This move, I then argue, provides resources for responding to the pantheist’s problem of God’s person.Peer reviewedFinal Accepted Versio

Transrectal Prostate Biopsy and Fiducial Marker Placement in a Standart 1.5T Magnetic Resonance Imaging Scanner

Cataloged from PDF version of article.Purpose: We investigated the accuracy and feasibility of a system that provides transrectal needle access to the prostate concurrent with 1.5 Tesla MRI which previously has not been possible. Materials and Methods: In 5 patients with previously diagnosed prostate cancer, MRI guided intraprostatic placement of gold fiducial markers (4 procedures) and/or prostate biopsy (3 procedures) was performed using local anesthesia. Results: Mean procedure duration was 76 minutes and all patients tolerated the intervention well. Procedure related adverse events included self-limited hematuria and hematochezia following 3 of 8 procedures (all resolved in less than 1 week). Mean needle placement accuracy was 1.9 mm for the fiducial marker placement studies and 1.8 mm for the biopsy procedures. Mean fiducial marker placement accuracy was 4.8 mm and the mean fiducial marker placement accuracy transverse to the needle direction was 2.6 mm. All patients who underwent the procedure were able to complete their course of radiotherapy without delay or complication. Conclusions: While studies of clinical usefulness are warranted, transrectal 1.5 T MRI guided prostate biopsy and fiducial marker placement is feasible using this system, providing new opportunities for image guided diagnostic and therapeutic prostate interventions

Morally Respectful Listening and its Epistemic Consequences

What does it mean to listen to someone respectfully, that is, insofar as they are due recognition respect? This paper addresses that question and gives the following answer: it is to listen in such a way that you are open to being surprised. A specific interpretation of this openness to surprise is then defended