26,347 research outputs found
Dynamic Modeling and Statistical Analysis of Event Times
This review article provides an overview of recent work in the modeling and
analysis of recurrent events arising in engineering, reliability, public
health, biomedicine and other areas. Recurrent event modeling possesses unique
facets making it different and more difficult to handle than single event
settings. For instance, the impact of an increasing number of event occurrences
needs to be taken into account, the effects of covariates should be considered,
potential association among the interevent times within a unit cannot be
ignored, and the effects of performed interventions after each event occurrence
need to be factored in. A recent general class of models for recurrent events
which simultaneously accommodates these aspects is described. Statistical
inference methods for this class of models are presented and illustrated
through applications to real data sets. Some existing open research problems
are described.Comment: Published at http://dx.doi.org/10.1214/088342306000000349 in the
Statistical Science (http://www.imstat.org/sts/) by the Institute of
Mathematical Statistics (http://www.imstat.org
MODELING OF AGRICULTURAL SYSTEMS
The authors present an overview of agricultural systems models. Beginning with why systems are modeled and for what purposes, the paper examines types of agricultural systems and associated model types. The broad categories range from pictorial (iconic) models to descriptive analogue models to symbolic (usually mathematical) models. The uses of optimization versus non-optimizing mechanistic models are reviewed, as are the scale and aggregation challenges associated with scaling up from the plant cell to the landscape or from a farm enterprise to a world market supply-demand equilibrium Recent modeling developments include the integration of formerly stand-alone biophysical simulation models, increasingly with a unifying spatial database and often for the purpose of supporting management decisions. Current modeling innovations are estimating and incorporating environmental values and other system interactions. At the community and regional scale, sociological and economic models of rural community structure are being developed to evaluate long-term community viability. The information revolution is bringing new challenges in delivering agricultural systems models over the internet, as well as integrating decision support systems with the new precision agriculture technologies.Farm Management,
A new protocol for texture mapping process and 2d representation of rupestrian architecture
The development of the survey techniques for architecture and archaeology requires a general review in the methods used for the representation of numerical data. The possibilities offered by data processing allow to find new paths for studying issues connected to the drawing discipline. The research project aimed at experimenting different approaches for the representation of the rupestrian architecture and the texture mapping process. The nature of the rupestrian architecture does not allow a traditional representation of sections and projections of edges and outlines. The paper presents a method, the Equidistant Multiple Sections (EMS), inspired by cartography and based on the use of isohipses generated from different geometric plane. A specific paragraph is dedicated to the
texture mapping process for unstructured surface models. One of the main difficulty in the image projection consists in the recognition of homologous points between image and point cloud, above all in the areas with most deformations. With the aid of the “virtual scan” tool a different procedure was developed for improving the correspondences of the image. The result show a sensible improvement of the entire process above all for the architectural vaults. A detailed study concerned the unfolding of the straight line surfaces; the barrel vault of the analyzed chapel has been unfolded for observing the paintings in the real shapes out of the morphological context
Parsing Occluded People by Flexible Compositions
This paper presents an approach to parsing humans when there is significant
occlusion. We model humans using a graphical model which has a tree structure
building on recent work [32, 6] and exploit the connectivity prior that, even
in presence of occlusion, the visible nodes form a connected subtree of the
graphical model. We call each connected subtree a flexible composition of
object parts. This involves a novel method for learning occlusion cues. During
inference we need to search over a mixture of different flexible models. By
exploiting part sharing, we show that this inference can be done extremely
efficiently requiring only twice as many computations as searching for the
entire object (i.e., not modeling occlusion). We evaluate our model on the
standard benchmarked "We Are Family" Stickmen dataset and obtain significant
performance improvements over the best alternative algorithms.Comment: CVPR 15 Camera Read
Articulated Clinician Detection Using 3D Pictorial Structures on RGB-D Data
Reliable human pose estimation (HPE) is essential to many clinical
applications, such as surgical workflow analysis, radiation safety monitoring
and human-robot cooperation. Proposed methods for the operating room (OR) rely
either on foreground estimation using a multi-camera system, which is a
challenge in real ORs due to color similarities and frequent illumination
changes, or on wearable sensors or markers, which are invasive and therefore
difficult to introduce in the room. Instead, we propose a novel approach based
on Pictorial Structures (PS) and on RGB-D data, which can be easily deployed in
real ORs. We extend the PS framework in two ways. First, we build robust and
discriminative part detectors using both color and depth images. We also
present a novel descriptor for depth images, called histogram of depth
differences (HDD). Second, we extend PS to 3D by proposing 3D pairwise
constraints and a new method that makes exact inference tractable. Our approach
is evaluated for pose estimation and clinician detection on a challenging RGB-D
dataset recorded in a busy operating room during live surgeries. We conduct
series of experiments to study the different part detectors in conjunction with
the various 2D or 3D pairwise constraints. Our comparisons demonstrate that 3D
PS with RGB-D part detectors significantly improves the results in a visually
challenging operating environment.Comment: The supplementary video is available at https://youtu.be/iabbGSqRSg
Animated virtual agents to cue user attention: comparison of static and dynamic deictic cues on gaze and touch responses
This paper describes an experiment developed to study the performance of virtual agent animated cues within digital interfaces. Increasingly, agents are used in virtual environments as part of the branding process and to guide user interaction. However, the level of agent detail required to establish and enhance efficient allocation of attention remains unclear. Although complex agent motion is now possible, it is costly to implement and so should only be routinely implemented if a clear benefit can be shown. Pevious methods of assessing the effect of gaze-cueing as a solution to scene complexity have relied principally on two-dimensional static scenes and manual peripheral inputs. Two experiments were run to address the question of agent cues on human-computer interfaces. Both experiments measured the efficiency of agent cues analyzing participant responses either by gaze or by touch respectively. In the first experiment, an eye-movement recorder was used to directly assess the immediate overt allocation of attention by capturing the participant’s eyefixations following presentation of a cueing stimulus. We found that a fully animated agent could speed up user interaction with the interface. When user attention was directed using a fully animated agent cue, users responded 35% faster when compared with stepped 2-image agent cues, and 42% faster when compared with a static 1-image cue. The second experiment recorded participant responses on a touch screen using same agent cues. Analysis of touch inputs confirmed the results of gaze-experiment, where fully animated agent made shortest time response with a slight decrease on the time difference comparisons. Responses to fully animated agent were 17% and 20% faster when compared with 2-image and 1-image cue severally. These results inform techniques aimed at engaging users’ attention in complex scenes such as computer games and digital transactions within public or social interaction contexts by demonstrating the benefits of dynamic gaze and head cueing directly on the users’ eye movements and touch responses
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