High-Performance Interactive Scientific Visualization With Datoviz via the Vulkan Low-Level GPU API

We reported initial work towards a new fast and scalable scientific visualization technology that leverages the Vulkan API to achieve unprecedented performance through GPUs. This technology is implemented in a C/C++ library called Datoviz that offers an intermediate-level API for scientific visualization libraries and software. Datoviz provides a unified graphics stack for 2-D, 3-D, graphical user interfaces, and natively supports efficient interactions between rendering and general-purpose GPU computing. A major direction of development is to investigate the integration of Datoviz as a low-level backend of a future version of VisPy, a popular Python scientific plotting librar

Study of one class boundary method classifiers for application in a video-based fall detection system

In this paper, we introduce a video-based robust fall detection system for monitoring an elderly person in a smart room environment. Video features, namely the centroid and orientation of a voxel person, are extracted. The boundary method, which is an example one class classification technique, is then used to determine whether the incoming features lie in the ‘fall region’ of the feature space, and thereby effectively distinguishing a fall from other activities, such as walking, sitting, standing, crouching or lying. Four different types of boundary methods, k-center, k-th nearest neighbor, one class support vector machine and single class minimax probability machine are assessed on representative test datasets. The comparison is made on the following three aspects: 1). True positive rate, false positive rate and geometric means in detection 2). Robustness to noise in the training dataset 3). The computational time for the test phase. From the comparison results, we show that the single class minimax probability machine achieves the best overall performance. By applying one class classification techniques with 3-d features, we can obtain a more efficient fall detection system with acceptable performance, as shown in the experimental part; besides, it can avoid the drawbacks of other traditional fall detection methods

An enigmatic large-sized partial skeleton of an eucynodont from the Antlers Formation, Trinity Group, Early Cretaceous of Texas

The first remains of Early Cretaceous mammals in the Antlers Formation, Trinity Group, Texas, were described as a new genus and species of triconodont, Astroconodon denisoni. Mammals from the Antlers Formation, both in Texas and Oklahoma, include, in addition to Astroconodon, basal multituberculates, a spalcotheroid, a variety of small tribosphenic mammals basal to Theria, and arguably primitive members of both Metatheria and Eutheria. A small semi-articulated skeleton was also found at Mart Frye?s Farm, about 4.5 miles from the center of Decatur, TX, in the sandstones of the Antler Formation, Trinity Group. Mart Frye?s farm is about 2 miles from Greenwood Canyon, the type locality of Astroconodon. The skeleton includes ten dorsal vertebrae (some of them articulated to ribs), partial right pelvis, epipubic bone and partial right leg including femur and proximal fragments of tibia and fibula. No dental elements were found. All of the bones are deficiently preserved and the articular surfaces appear not to be completely ossified suggesting a sub-adult individual. The ilium, pubis and ischium are relatively gracile, while the femur, which has suffered much compression, is short and stout, with poorly differentiated laminar trocanters and neck. The incomplete femoral head would be oval and only slightly medially inflected. In these features, the femur resembles those of recently described triconodonts from the Jurassic and Cretaceous of China and tritylodonts. The pelvis (ilium plus ischium) is approximately 40mm long and the femur slightly longer. This is a large specimen for a Mesozoic mammal and does not agree in size with any of the dentally known mammals from the Antlers Fm. The similarly aged Cloverly Fm. from central USA, has yielded a tricondont similar to Astroconodon and, among other forms, the larger gobiconodontid Gobiconodon ostromi. The femur and tibia of the skeleton presented here are unlike that of Gobiconodon. We regard this partial skeleton as representing either a yet unknown mammal, probably a triconodont, or more likely a tritylodont.Fil: Rougier, Guillermo Walter. University of Louisville; Estados UnidosFil: Gaetano, Leandro Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Estudios Andinos "Don Pablo Groeber". Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Estudios Andinos "Don Pablo Groeber"; ArgentinaFil: Macovicky, Peter J.. Field Museum of National History; Estados Unidos71th Meeting Society of Vertebrate PaleontologyLas VegasEstados UnidosSociety of Vertebrate Paleontolog

Bayesian modeling and inference for one-shot experiments

In one-shot experiments, units are subjected to varying levels of stimulus and their binary response (go/no-go) is recorded. Experimental data is used to estimate the “sensitivity function”, which characterizes the probability of a “go” for a given level of stimulus. We review the current GLM approaches to modeling and inference, and identify some deficiencies. To address these, we propose a novel Bayesian approach using an adjustable number of cubic splines, with physically-plausible smoothness, monotonicity, and tail constraints introduced through the prior distribution on the coefficients. Our approach runs “out of the box,” and in roughly the same time as the GLM approaches. We illustrate with two contrasting datasets, and show that our more flexible Bayesian approach gives different inferences to the GLM approaches for both the sensitivity function and its inverse

Design for a Darwinian Brain: Part 1. Philosophy and Neuroscience

Physical symbol systems are needed for open-ended cognition. A good way to understand physical symbol systems is by comparison of thought to chemistry. Both have systematicity, productivity and compositionality. The state of the art in cognitive architectures for open-ended cognition is critically assessed. I conclude that a cognitive architecture that evolves symbol structures in the brain is a promising candidate to explain open-ended cognition. Part 2 of the paper presents such a cognitive architecture.Comment: Darwinian Neurodynamics. Submitted as a two part paper to Living Machines 2013 Natural History Museum, Londo