Effects of search intent on eye-movement patterns in a change detection task

The goal of the present study was to examine whether intention type affects eye movement patterns in a change detection task In addition, we assessed whether the eye movement index could be used to identify human implicit intent. We attempted to generate three types of intent amongst the study participants, dividing them into one of three conditions; each condition received different information regarding an impending change to the visual stimuli. In the “navigational intent” condition, participants were asked to look for any interesting objects, and were not given any more information about the impending change. In the “low-specific intent” condition, participants were informed that a change would occur. In the “high-specific intent” condition, participants were told that a change would occur, and that an object would disappear. In addition to this main change detection task, participants also had to perform a primary task, in which they were required to name aloud the colors of objects in the pre-change scene. This allowed us to control for the visual searching process during the pre-change scene. The main results were as follows: firstly, the primary task successfully controlled for the visual search process during the pre-change scene, establishing that there were no differences in the patterns of eye movements across all three conditions despite differing intents. Secondly, we observed significantly different patterns of eye movement between the conditions in the post-change scene, suggesting that generating a specific intent for change detection yields a distinctive pattern of eye-movements. Finally, discriminant function analysis showed a reasonable classification rate for identifying a specific intent. Taken together, it was found that both participant intent and the specificity of information provided to the participants affect eye movements in a change detection task

Estimates of Discharge Coefficient in Levee Breach Under Two Different Approach Flow Types

The amount of released water (discharge) in a levee breach is a primary input variable to establish an emergency action plan for the area next to the levee. However, although several studies have been conducted, there is still no widely applicable discharge coefficient formula; this needs to be known to estimate discharge amount through an opening caused by a levee breach. Sometimes, the discharge coefficient developed for a sharp crested side weir is used to rate the discharge, but, in case of a levee breach, the resulting geometry and flow types are similar to that over a broad crested weir. Thus, in this study, two different openings—rectangular and trapezoidal shape—are constructed in the center of a levee at a height of 0.6m to replicate levee breach scenarios, and the effect of two different approach flow types—the river type approach and reservoir type approach—are explored to suggest a discharge coefficient formula applicable for discharge rating for a levee breach. The results show that the ratio of head above the bottom of an opening and the opening width is a key variable for calculating the discharge coefficient of a reservoir type, but the approach Froude number should also be considered for a river type approach. The measured data are used to improve rating equations and will be useful in the future to validate computational fluid dynamics simulations of wave propagation during levee failure into the inundation area

Elastic seismic design of steel high-rise buildings in regions of strong wind and moderate seismicity

Lateral loading due to wind or earthquake is a major factor that affects the design of high-rise buildings. This paper highlights the problems associated with the seismic design of high-rise buildings in regions of strong wind and moderate seismicity. Seismic response analysis and performance evaluation were conducted for wind-designed concentrically braced steel high-rise buildings in order to check the feasibility of designing them per elastic seismic design criterion (or strength and stiffness solution) in such regions. Review of wind design and pushover analysis results indicated that wind-designed high-rise buildings possess significantly increased elastic seismic capacity due to the overstrength resulting from the wind serviceability criterion. The strength demand-to-capacity study showed that, due to the wind design overstrength, high-rise buildings with a slenderness ratio of larger than four or five can elastically withstand even the maximum considered earthquake (MCE) with the seismic performance level of immediate occupancy under the limited conditions of this study. A step-by-step seismic design procedure per the elastic criterion that is directly usable for practicing design engineers is also recommended.Financial support to this study provided by the Ministry of Construction and Trnasportation of Korea (03 R&D C04-01) is gratefully acknowledged

Indium as an efficient ohmic contact to N-face n-GaN of GaN-based vertical light-emitting diodes

We propose indium (In), a low work function and nitride-forming element, as an efficient ohmic contact layer to N-face n-GaN. While conventional Al-based ohmic contacts show severe degradation after annealing at 300 C, In-based ohmic contacts display considerable improvement in contact resistivity. The annealing-induced enhancement of ohmic behavior in In-based contacts is attributed to the formation of an InN interfacial layer, which is supported by x-ray photoemission spectroscopy measurements. These results suggest that In is of particular importance for application as reliable ohmic contacts to n-GaN of GaN-based vertical light-emitting diodes.open3

PG-RCNN: Semantic Surface Point Generation for 3D Object Detection

One of the main challenges in LiDAR-based 3D object detection is that the sensors often fail to capture the complete spatial information about the objects due to long distance and occlusion. Two-stage detectors with point cloud completion approaches tackle this problem by adding more points to the regions of interest (RoIs) with a pre-trained network. However, these methods generate dense point clouds of objects for all region proposals, assuming that objects always exist in the RoIs. This leads to the indiscriminate point generation for incorrect proposals as well. Motivated by this, we propose Point Generation R-CNN (PG-RCNN), a novel end-to-end detector that generates semantic surface points of foreground objects for accurate detection. Our method uses a jointly trained RoI point generation module to process the contextual information of RoIs and estimate the complete shape and displacement of foreground objects. For every generated point, PG-RCNN assigns a semantic feature that indicates the estimated foreground probability. Extensive experiments show that the point clouds generated by our method provide geometrically and semantically rich information for refining false positive and misaligned proposals. PG-RCNN achieves competitive performance on the KITTI benchmark, with significantly fewer parameters than state-of-the-art models. The code is available at https://github.com/quotation2520/PG-RCNN.Comment: Accepted by ICCV 202