A Virtual Mouse Interface for Supporting Multi-user Interactions

2020 ◽  
pp. 497-508
Author(s):  
Matthew Peveler ◽  
Jeffery O. Kephart ◽  
Xiangyang Mou ◽  
Gordon Clement ◽  
Hui Su
Keyword(s):  
User Interactions ◽  
Virtual Mouse

Analysis of User Interactions in Online Social Networks

2011 ◽  
Author(s):  
Seokchan Yun ◽  
Heungseok Do ◽  
Jinuk Jung ◽  
Song Mina ◽  
Namgoong Hyun ◽  
...  
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
User Interactions

Unbiased Learning to Rank

2021 ◽  
Vol 39 (2) ◽  
pp. 1-29
Author(s):  
Qingyao Ai ◽  
Tao Yang ◽  
Huazheng Wang ◽  
Jiaxin Mao
Keyword(s):  
Online Learning ◽  
Theoretical Foundation ◽  
Learning To Rank ◽  
Research Question ◽  
Parameters Estimation ◽  
User Interactions ◽  
Empirical Performance ◽  
Search Data ◽  
Two Sides ◽  
Important Research Question

How to obtain an unbiased ranking model by learning to rank with biased user feedback is an important research question for IR. Existing work on unbiased learning to rank (ULTR) can be broadly categorized into two groups—the studies on unbiased learning algorithms with logged data, namely, the offline unbiased learning, and the studies on unbiased parameters estimation with real-time user interactions, namely, the online learning to rank. While their definitions of unbiasness are different, these two types of ULTR algorithms share the same goal—to find the best models that rank documents based on their intrinsic relevance or utility. However, most studies on offline and online unbiased learning to rank are carried in parallel without detailed comparisons on their background theories and empirical performance. In this article, we formalize the task of unbiased learning to rank and show that existing algorithms for offline unbiased learning and online learning to rank are just the two sides of the same coin. We evaluate eight state-of-the-art ULTR algorithms and find that many of them can be used in both offline settings and online environments with or without minor modifications. Further, we analyze how different offline and online learning paradigms would affect the theoretical foundation and empirical effectiveness of each algorithm on both synthetic and real search data. Our findings provide important insights and guidelines for choosing and deploying ULTR algorithms in practice.

scholarly journals A three-dimensional virtual mouse generates synthetic training data for behavioral analysis

2021 ◽  
Vol 18 (4) ◽  
pp. 378-381 ◽  
Author(s):  
Luis A. Bolaños ◽  
Dongsheng Xiao ◽  
Nancy L. Ford ◽  
Jeff M. LeDue ◽  
Pankaj K. Gupta ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Training Data ◽  
Behavioral Analysis ◽  
Virtual Mouse ◽  
Synthetic Training Data

scholarly journals Contrasting Perspectives on the Comfort and Safety of Pedestrians Interacting with Other Road Users

2021 ◽  
Vol 2675 (3) ◽  
pp. 33-43
Author(s):  
Alexander Bigazzi ◽  
Gurdiljot Gill ◽  
Meghan Winters
Keyword(s):  
Traffic Safety ◽  
Injury Risk ◽  
Road User ◽  
Motor Vehicles ◽  
Advisory Group ◽  
User Interactions ◽  
The Public ◽  
Road Users ◽  
Expert Assessments ◽  
Sample Representation

Assessments of interactions between road users are crucial to understanding comfort and safety. However, observers may vary in their perceptions and ratings of road user interactions. The objective of this paper is to examine how perceptions of yielding, comfort, and safety for pedestrian interactions vary among observers, ranging from members of the public to road safety experts. Video clips of pedestrian interactions with motor vehicles and bicycles were collected from 11 crosswalks and shown to three groups of participants (traffic safety experts, an engaged citizen advisory group, and members of the general public) along with questions about yielding, comfort, and risk of injury. Experts had similar views of yielding and comfort to the other two groups, but a consistently lower assessment of injury risk for pedestrians in the study. Respondent socio-demographics did not relate to perceptions of yielding, comfort, or risk, but self-reported travel habits did. Respondents who reported walking more frequently rated pedestrian comfort as lower, and respondents who reported cycling more frequently rated risk as lower for pedestrian interactions with both motor vehicles and bicycles. Findings suggest small groups of engaged citizens can provide useful information about public perspectives on safety that likely diverge from expert assessments of risk, and that sample representation should be assessed in relation to travel habits rather than socio-demographics.

scholarly journals Cartesian Mesh Generation with Local Refinement for Immersed Boundary Approaches

2021 ◽  
Vol 9 (6) ◽  
pp. 572
Author(s):  
Luca Di Di Angelo ◽  
Francesco Duronio ◽  
Angelo De De Vita ◽  
Andrea Di Di Mascio
Keyword(s):  
Mesh Generation ◽  
Cfd Simulation ◽  
Automatic Generation ◽  
Uniform Grid ◽  
Immersed Boundary ◽  
Adaptive Grids ◽  
Local Refinement ◽  
User Interactions ◽  
Cartesian Mesh ◽  
Time Required

In this paper, an efficient and robust Cartesian Mesh Generation with Local Refinement for an Immersed Boundary Approach is proposed, whose key feature is the capability of high Reynolds number simulations by the use of wall function models, bypassing the need for accurate boundary layer discretization. Starting from the discrete manifold model of the object to be analyzed, the proposed model generates Cartesian adaptive grids for a CFD simulation, with minimal user interactions; the most innovative aspect of this approach is that the automatic generation is based on the segmentation of the surfaces enveloping the object to be analyzed. The aim of this paper is to show that this automatic workflow is robust and enables to get quantitative results on geometrically complex configurations such as marine vehicles. To this purpose, the proposed methodology has been applied to the simulation of the flow past a BB2 submarine, discretized by non-uniform grid density. The obtained results are comparable with those obtained by classical body-fitted approaches but with a significant reduction of the time required for the mesh generation.

scholarly journals Leveraging Graphical User Interface Automation for Generic Robot Programming

Robotics ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 3
Author(s):  
Tudor B. Ionescu
Keyword(s):  
User Interface ◽  
Graphical User Interface ◽  
Programming Models ◽  
Shop Floor ◽  
Robot Programming ◽  
User Interactions ◽  
Programming Environments ◽  
Automated Generation ◽  
Novel Approach ◽  
Block Based

A novel approach to generic (or generalized) robot programming and a novel simplified, block-based programming environment, called “Assembly”, are introduced. The approach leverages the newest graphical user interface automation tools and techniques to generate programs in various proprietary robot programming environments by emulating user interactions in those environments. The “Assembly” tool is used to generate robot-independent intermediary program models, which are translated into robot-specific programs using a graphical user interface automation toolchain. The generalizability of the approach to list, tree, and block-based programming is assessed using three different robot programming environments, two of which are proprietary. The results of this evaluation suggest that the proposed approach is feasible for an entire range of programming models and thus enables the generation of programs in various proprietary robot programming environments. In educational settings, the automated generation of programs fosters learning different robot programming models by example. For experts, the proposed approach provides a means for generating program (or task) templates, which can be adjusted to the needs of the application at hand on the shop floor.

scholarly journals A Game Theory-Based Approach for Modeling Autonomous Vehicle Behavior in Congested, Urban Lane-Changing Scenarios

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1523
Author(s):  
Nikita Smirnov ◽  
Yuzhou Liu ◽  
Aso Validi ◽  
Walter Morales-Alvarez ◽  
Cristina Olaverri-Monreal
Keyword(s):  
Game Theory ◽  
Decision Making ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Urban Traffic ◽  
Road User ◽  
Lane Change ◽  
Traffic Light ◽  
User Interactions ◽  
Lane Changing

Autonomous vehicles are expected to display human-like behavior, at least to the extent that their decisions can be intuitively understood by other road users. If this is not the case, the coexistence of manual and autonomous vehicles in a mixed environment might affect road user interactions negatively and might jeopardize road safety. To this end, it is highly important to design algorithms that are capable of analyzing human decision-making processes and of reproducing them. In this context, lane-change maneuvers have been studied extensively. However, not all potential scenarios have been considered, since most works have focused on highway rather than urban scenarios. We contribute to the field of research by investigating a particular urban traffic scenario in which an autonomous vehicle needs to determine the level of cooperation of the vehicles in the adjacent lane in order to proceed with a lane change. To this end, we present a game theory-based decision-making model for lane changing in congested urban intersections. The model takes as input driving-related parameters related to vehicles in the intersection before they come to a complete stop. We validated the model by relying on the Co-AutoSim simulator. We compared the prediction model outcomes with actual participant decisions, i.e., whether they allowed the autonomous vehicle to drive in front of them. The results are promising, with the prediction accuracy being 100% in all of the cases in which the participants allowed the lane change and 83.3% in the other cases. The false predictions were due to delays in resuming driving after the traffic light turned green.

scholarly journals Web Augmentation as a Technique to Diminish User Interactions in Repetitive Tasks

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Inigo Aldalur ◽  
Alain Perez ◽  
Felix Larrinaga.
Keyword(s):  
User Interactions ◽  
Repetitive Tasks ◽  
Web Augmentation

Real-Time Web GIS Analysis Using WebGL

2012 ◽  
Vol 1 (3) ◽  
pp. 49-61 ◽  
Author(s):  
Michael Auer
Keyword(s):  
Parallel Processing ◽  
Real Time ◽  
Large Data ◽  
Web Gis ◽  
3D Graphics ◽  
Gis Analysis ◽  
User Interactions ◽  
Algorithm Performance ◽  
Gis Applications ◽  
Client Side

Parallel processing methods in Geographic Information Systems (GIS) are traditionally used to accelerate the calculation of large data volumes with sophisticated spatial algorithms. Such kinds of acceleration can also be applied to provide real-time GIS applications to improve the responsiveness of user interactions with the data. This paper presents a method to enable this approach for Web GIS applications. It uses the JavaScript 3D graphics API (WebGL) to perform client-side parallel real-time computations of 2D or 2.5D spatial raster algorithms on the graphics card. The potential of this approach is evaluated using an example implementation of a hillshade algorithm. Performance comparisons of parallel and sequential computations reveal acceleration factors between 25 and 100, mainly depending on mobile or desktop environments.

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