Can Stroboscopic Training Improve Judgments of Time-to-Collision?

2019 ◽  
Vol 62 (1) ◽  
pp. 152-165 ◽  
Author(s):  
Adam M. Braly ◽  
Patricia R. DeLucia
Keyword(s):  
Optical Flow ◽  
Real World ◽  
Moving Objects ◽  
Constant Error ◽  
Performance Degradation ◽  
Driver Training ◽  
Time To Collision ◽  
Repeated Practice ◽  
Improved Performance ◽  
Over Time

Objective: The aim of this study was to determine whether training with stroboscopic viewing could improve time-to-collision (TTC) judgments, which have importance in real-world tasks such as driving. Background: Prior research demonstrated that training with stroboscopic vision can improve motion coherence thresholds, improve anticipatory timing performance for laterally moving objects, and can protect against performance degradation over time. Method: Participants viewed computer simulations of an object that moved and then disappeared. In two separate experiments, the object approached the observer or moved laterally toward a target, representing different optical flow patterns. Participants judged TTC by pressing a button when they thought the object would hit them (approach), or the target (lateral). Performance was measured during four sessions—pretest, intervention, immediately after intervention, and 10 min after intervention. Results: Both stroboscopic training and repeated practice improved performance over time for approach motion (decrease in constant error) and stroboscopic training protected against performance degradation for lateral motion (no decrement in variable error), but only when TTC was 3.0 s. There was no difference between training and repeated practice. Conclusion: Under certain conditions, stroboscopic training may improve TTC judgments. However, effects of stroboscopic training depend on the nature of the optical flow pattern. Application: It is important to determine the conditions under which training can improve TTC judgments which have importance in real-world tasks such as driving. If individuals can be trained to judge TTC more accurately, they may benefit from driver training programs.

Can Stroboscopic Training Improve Time-to-Collision Judgments of Laterally Moving Objects?

2018 ◽  
Vol 62 (1) ◽  
pp. 1975-1976
Author(s):  
Adam M. Braly ◽  
Patricia R. DeLucia
Keyword(s):  
Optical Flow ◽  
Flow Pattern ◽  
Visual Information ◽  
Constant Error ◽  
Performance Degradation ◽  
Lateral Motion ◽  
Time To Collision ◽  
Variable Error ◽  
Vision Condition ◽  
Over Time

We investigated whether effects of stroboscopic training on time-to-collision (TTC) judgments depend on the optical flow pattern. Prior research showed that TTC judgments of lateral motion reflected benefits of stroboscopic viewing (Ballester, Huertas, Uji, & Bennett, 2017; Smith & Mitroff, 2012), but TTC judgments of approach motion did not reflect such benefits (Braly & DeLucia, 2017). This discrepancy may be due to differences in the optical flow patterns between lateral and approach motion. In lateral motion, the optical flow pattern is linear; the change in the object’s optical position is the same throughout its trajectory. In approach motion, the optical flow pattern is non-linear; the change in the object’s optical size increases as it gets closer to the eye. It has been proposed that this difference in the optical flow pattern underlies the greater accuracy of TTC judgments that occur with lateral motion compared to approach motion (Schiff & Oldak, 1990). In the current study, we measured effects of stroboscopic viewing on TTC judgments of lateral motion using identical methods in our prior study of approach motion. Although prior research demonstrated potential benefits of stroboscopic viewing for judgments of lateral motion, the stimulus was visible when the response was made. Prior demonstrations that the object’s trajectory (and thus nature of the optic flow) affects TTC judgments were demonstrated with prediction-motion (PM) tasks in which the object disappeared before a response was made. The two types of tasks are putatively based on different visual information and cognitive processes (Tresilian, 1995). Thus, we used a PM task in the current study. Participants viewed computer simulations of an object that moved laterally toward a target and then disappeared. They pressed a mouse button at the exact time that they thought the object would hit the target. Mean constant error and variable error of TTC judgments were compared among intervention conditions of stroboscopic training (5 minutes in duration), continuous viewing (practice without feedback), and a control filler task. Performance was measured during four sessions—pre-test, intervention, immediately after intervention, and 10 minutes after intervention. When distance was far, participants in the stroboscopic intervention condition were, on average, less variable at the 10-minute posttest compared to the pretest. Although the difference was not statistically significant, it is noteworthy that performance did not significantly degrade over time as it did in the filler condition, and in our prior study of approach motion (Braly & DeLucia, 2017). Such results suggest that stroboscopic training can protect against performance degradation over time (due to fatigue, monotony, etc). A protective effect also was observed in the continuous vision condition (performance did not degrade over time); however, observations of the means suggest that performance would have degraded over time if longer training was completed. When TTC was 3.0 s, performance in the stroboscopic intervention was not more variable in the immediate posttest compared to the pretest and, more importantly, was less variable at the ten-minute posttest (although p = 0.0515). Our results show that under specific conditions (when TTC was 3.0 s; when distance was far) stroboscopic training can protect against performance degradation over time; that is, variable error did not increase. Such protective effects of stroboscopic training were not observed in our earlier study of approach motion (Braly & DeLucia, 2017). Neither study showed a significant effect of stroboscopic training on constant error. The implication is that the effects of stroboscopic training depend on the nature of the optical flow pattern. In future studies, it is important to systematically determine the conditions under which stroboscopic training can improve performance. Results will have important implications for traffic safety and for driver training programs.

An Efficient Perpetual Learning Algorithm

2019 ◽  
Vol 28 (07) ◽  
pp. 1950022 ◽  
Author(s):  
Haiou Qin ◽  
Du Zhang ◽  
Xibin Sun ◽  
Jiahua Tang ◽  
Jun Peng
Keyword(s):  
Machine Learning ◽  
Real World ◽  
Efficient Algorithm ◽  
Learning Algorithm ◽  
Small Data ◽  
Computing Systems ◽  
Agent Systems ◽  
Multiple Tasks ◽  
Improved Performance ◽  
Over Time

One of the emerging research opportunities in machine learning is to develop computing systems that learn many tasks continuously and improve the performance of learned tasks incrementally over time. In real world, learners have to adapt to labeled and unlabeled samples from various tasks which arrive randomly. In this paper, we propose an efficient algorithm called Efficient Perpetual Learning Algorithm (EPLA) which is suitable for learning multiple tasks in both offline and online settings. The algorithm, which is an extension of ELLA,4 is part of what we call perpetual learning that can learn new tasks or refine knowledge of learned tasks for improved performance with newly arrived labeled samples in an incremental fashion. Several salient features exist for EPLA. The learning episodes are triggered via either extrinsic or intrinsic stimuli. Agent systems based on the proposed algorithm can be engaged in an open-ended and alternating sequence of learning episodes and working episodes. Unlabeled samples can be used to self-train the learner in small data setting. Compared with ELLA, EPLA shows almost equivalent performance without memorizing any labeled samples learned previously.

Can Stroboscopic Training Improve Time-to-Collision Judgments of Approaching Objects?

2017 ◽  
Vol 61 (1) ◽  
pp. 1497-1498 ◽  
Author(s):  
Adam M. Braly ◽  
Patricia R. DeLucia
Keyword(s):  
Training Programs ◽  
Lateral Motion ◽  
Driver Training ◽  
Subsequent Performance ◽  
Time To Collision ◽  
Optical Pattern ◽  
Visual Tasks ◽  
Prior Literature ◽  
Improved Performance ◽  
And Performance

Prior studies have shown that training with stroboscopic viewing improved performance on visual tasks, such as motion coherence thresholds, and performance on coincident anticipation tasks (Appelbaum, Schroeder, Cain, & Mitroff, 2011; Smith & Mitroff, 2012). In stroboscopic viewing, individuals wear occlusion goggles which present an intermittent view of the environment. It is assumed that training during “degraded” viewing will enhance subsequent performance during unimpaired viewing. We examined whether training with stroboscopic viewing can improve time-to-collision (TTC) judgments, which have importance in real-world tasks such as driving, using a prediction motion (PM) task (Schiff & Detwiler, 1979). The PM task is particularly well- suited for stroboscopic training because the task involves extrapolation of the object’s motion after it disappears (DeLucia & Liddell, 1998; Schiff & Oldak, 1990). In stroboscopic viewing, the object appears and then disappears, but does so repeatedly throughout the object’s approach. During periods of occlusion, observers putatively extrapolate the object’s motion. When the object reappears, observers get feedback on their extrapolation. Thus, they get feedback on their extrapolation throughout the object’s entire approach. Participants viewed computer simulations of an object that approached them and then disappeared. They judged TTC by pressing a button when they thought the object would hit them. Mean constant error of TTC judgments were compared among intervention conditions of stroboscopic training (5 minutes), continuous viewing (practice without feedback), and a control filler task. Performance was measured during four sessions—pre-test, intervention, immediately after intervention, and 10 minutes after intervention. Differences among the interventions were not significant, and judgment accuracy decreased across sessions. In contrast to Smith and Mitroff’s (2012) study of anticipatory timing of lateral motion, five minutes of stroboscopic training was not sufficient to improve TTC judgments of approaching objects. We considered several reasons why stroboscopic training did not improve TTC judgments. First, participants may not have mentally extrapolated the object’s motion when its view was occluded and thus did not benefit from its reappearance throughout the stroboscopic viewing. This seems unlikely, because research has shown that PM tasks involve motion extrapolation (DeLucia & Liddell, 1998). Second, the occlusion period may have been too short to allow observers to get feedback on their extrapolation of the object’s motion. We employed a strobe frequency of 4 Hz based on prior literature, but longer occlusion periods may be needed to see performance benefits and should be examined in future studies. Third, training that is more than 5 minutes may be required to show benefits for TTC judgments of approach motion (current study) than for lateral motion (Smith & Mitroff’s study). This may occur because the optical pattern is linear in lateral motion (the object’s change in position is the same throughout its trajectory) and non-linear in approach motion (the object’s change in optical size increases as it gets closer to the eye) and may result in the less accurate TTC judgments of approach compared to lateral motion (Schiff & Oldak, 1990). In conclusion, it is important to determine the conditions under which training can improve TTC judgments of approaching objects. If individuals can be trained to make more accurate TTC judgements, there are important implications for driver training programs. Drivers must anticipate the future position of vehicles that are around them when changing lanes, turning left, or overtaking vehicles, in traffic. Importantly, research has shown that observers have difficulty making these judgments and may misperceive the distance and speed of other vehicles (e.g., Caird & Hancock, 1994; Gray & Regan, 2005; Levulis, DeLucia, & Jupe, 2015). Driver training programs designed to improve observers’ abilities to judge TTC may help to reduce accidents.

scholarly journals Real World Performance Evaluation of Transcatheter Aortic Valve Implantation

2021 ◽  
Vol 10 (9) ◽  
pp. 1890
Author(s):  
Gabriele Pesarini ◽  
Gabriele Venturi ◽  
Domenico Tavella ◽  
Leonardo Gottin ◽  
Mattia Lunardi ◽  
...  
Keyword(s):  
Aortic Valve ◽  
Real World ◽  
Baseline Risk ◽  
Risk Scores ◽  
World Population ◽  
Control Analysis ◽  
Transcatheter Aortic Valve ◽  
Procedural Control ◽  
Risk Patients ◽  
Over Time

Background: The aim of this research is to describe the performance over time of transcatheter aortic valve implantations (TAVIs) in a high-volume center with a contemporary, real-world population. Methods: Patients referred for TAVIs at the University Hospital of Verona were prospectively enrolled. By cumulative sum failures analysis (CUSUM), procedural-control curves for standardized combined endpoints—as defined by the Valve Academic Research Consortium-2 (VARC-2)—were calculated and analyzed over time. Acceptable and unacceptable limits were derived from recent studies on TAVI in intermediate and low-risk patients to fit the higher required standards for current indications. Results: A total of 910 patients were included. Baseline risk scores significantly reduced over time. Complete procedural control was obtained after approximately 125 and 190 cases for device success and early safety standardized combined endpoints, respectively. High risk patients (STS ≥ 8) had poorer outcomes, especially in terms of VARC-2 clinical efficacy, and required a higher case load to maintain in-control and proficient procedures. Clinically relevant single endpoints were all influenced by operator’s experience as well. Conclusions: Quality-control analysis for contemporary TAVI interventions based on standardized endpoints suggests the need for relevant operator’s experience to achieve and maintain optimal clinical results, especially in higher-risk subjects.

scholarly journals POS0619 MODELLING OF DISEASE ACTIVITY IN PATIENTS WITH INFLAMMATORY ARTHROPATHIES TREATED WITH ETANERCEPT ORIGINATOR OR BIOSIMILAR AS FIRST-LINE BIOLOGIC IN AN AUSTRALIAN REAL-WORLD DATASET

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 547.1-547
Author(s):  
C. Deakin ◽  
G. Littlejohn ◽  
H. Griffiths ◽  
T. Smith ◽  
C. Osullivan ◽  
...  
Keyword(s):  
Disease Activity ◽  
Clinical Data ◽  
Real World ◽  
Rank Test ◽  
P Value ◽  
Continuous Variables ◽  
Linear Quadratic ◽  
First Line ◽  
Modest Improvement ◽  
Over Time

Background:The availability of biosimilars as non-proprietary versions of established biologic disease-modifying anti-rheumatic drugs (bDMARDs) is enabling greater access for patients with rheumatic diseases to effective medications at a lower cost. Since April 2017 both the originator and a biosimilar for etanercept (trade names Enbrel and Brenzys, respectively) have been available for use in Australia.Objectives:[1]To model effectiveness of etanercept originator or biosimilar in reducing Disease Activity Score 28-joint count C reactive protein (DAS28CRP) in patients with rheumatoid arthritis (RA), psoriatic arthritis (PsA) or ankylosing spondylitis (AS) treated with either drug as first-line bDMARD[2]To describe persistence on etanercept originator or biosimilar as first-line bDMARD in patients with RA, PsA or ASMethods:Clinical data were obtained from the Optimising Patient outcomes in Australian rheumatoLogy (OPAL) dataset, derived from electronic medical records. Eligible patients with RA, PsA or AS who initiated etanercept originator (n=856) or biosimilar (n=477) as first-line bDMARD between 1 April 2017 and 31 December 2020 were identified. Propensity score matching was performed to select patients on originator (n=230) or biosimilar (n=136) with similar characteristics in terms of diagnosis, disease duration, joint count, age, sex and concomitant medications. Data on clinical outcomes were recorded at 3 months after baseline, and then at 6-monthly intervals. Outcomes data that were missing at a recorded visit were imputed.Effectiveness of the originator, relative to the biosimilar, for reducing DAS28CRP over time was modelled in the matched population using linear mixed models with both random intercepts and slopes to allow for individual heterogeneity, and weighting of individuals by inverse probability of treatment weights to ensure comparability between treatment groups. Time was modelled as a combination of linear, quadratic and cubic continuous variables.Persistence on the originator or biosimilar was analysed using survival analysis (log-rank test).Results:Reduction in DAS28CRP was associated with both time and etanercept originator treatment (Table 1). The conditional R-squared for the model was 0.31. The average predicted DAS28CRP at baseline, 3 months, 6 months, 9 months and 12 months were 4.0 and 4.4, 3.1 and 3.4, 2.6 and 2.8, 2.3 and 2.6, and 2.2 and 2.4 for the originator and biosimilar, respectively, indicating a clinically meaningful effect of time for patients on either drug and an additional modest improvement for patients on the originator.Median time to 50% of patients stopping treatment was 25.5 months for the originator and 24.1 months for the biosimilar (p=0.53). An adverse event was the reason for discontinuing treatment in 33 patients (14.5%) on the originator and 18 patients (12.9%) on the biosimilar.Conclusion:Analysis using a large national real-world dataset showed treatment with either the etanercept originator or the biosimilar was associated with a reduction in DAS28CRP over time, with the originator being associated with a further modest reduction in DAS28CRP that was not clinically significant. Persistence on treatment was not different between the two drugs.Table 1.Respondent characteristics.Fixed EffectEstimate95% Confidence Intervalp-valueTime (linear)0.900.89, 0.911.5e-63Time (quadratic)1.011.00, 1.011.3e-33Time (cubic)1.001.00, 1.007.1e-23Originator0.910.86, 0.960.0013Acknowledgements:The authors acknowledge the members of OPAL Rheumatology Ltd and their patients for providing clinical data for this study, and Software4Specialists Pty Ltd for providing the Audit4 platform.Supported in part by a research grant from Investigator-Initiated Studies Program of Merck & Co Inc, Kenilworth, NJ, USA. The opinions expressed in this paper are those of the authors and do not necessarily represent those of Merck & Co Inc, Kenilworth, NJ, USA.Disclosure of Interests:Claire Deakin: None declared, Geoff Littlejohn Consultant of: Over the last 5 years Geoffrey Littlejohn has received educational grants and consulting fees from AbbVie, Bristol Myers Squibb, Eli Lilly, Gilead, Novartis, Pfizer, Janssen, Sandoz, Sanofi and Seqirus., Hedley Griffiths Consultant of: AbbVie, Gilead, Novartis and Lilly., Tegan Smith: None declared, Catherine OSullivan: None declared, Paul Bird Speakers bureau: Eli Lilly, abbvie, pfizer, BMS, UCB, Gilead, Novartis

Multi Object Detection and Tracking from Video File

2014 ◽  
Vol 533 ◽  
pp. 218-225 ◽  
Author(s):  
Rapee Krerngkamjornkit ◽  
Milan Simic
Keyword(s):  
Computer Vision ◽  
Background Subtraction ◽  
Moving Objects ◽  
Gaussian Mixture Models ◽  
Gaussian Mixture ◽  
Video Tracking ◽  
Partial Occlusion ◽  
Video File ◽  
Detection And Tracking ◽  
Over Time

This paper describes computer vision algorithms for detection, identification, and tracking of moving objects in a video file. The problem of multiple object tracking can be divided into two parts; detecting moving objects in each frame and associating the detections corresponding to the same object over time. The detection of moving objects uses a background subtraction algorithm based on Gaussian mixture models. The motion of each track is estimated by a Kalman filter. The video tracking algorithm was successfully tested using the BIWI walking pedestrians datasets [. The experimental results show that system can operate in real time and successfully detect, track and identify multiple targets in the presence of partial occlusion.

scholarly journals Comparing Optical Flow Algorithms Using 6-DOF Motion of Real-World Rigid Objects

2012 ◽  
Vol 42 (6) ◽  
pp. 1752-1762 ◽  
Author(s):  
Marco Mammarella ◽  
Giampiero Campa ◽  
Mario L. Fravolini ◽  
Marcello R. Napolitano
Keyword(s):  
Optical Flow ◽  
Real World ◽  
Rigid Objects

scholarly journals Friendship paradox in growth networks: analytical and empirical analysis

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Sergei P. Sidorov ◽  
Sergei V. Mironov ◽  
Alexey A. Grigoriev
Keyword(s):  
Real World ◽  
Preferential Attachment ◽  
Empirical Studies ◽  
Mean Field ◽  
Network Models ◽  
Average Degree ◽  
Closure Model ◽  
Triadic Closure ◽  
Attachment Mechanism ◽  
Over Time

AbstractMany empirical studies have shown that in social, citation, collaboration, and other types of networks in real world, the degree of almost every node is less than the average degree of its neighbors. This imbalance is well known in sociology as the friendship paradox and states that your friends are more popular than you on average. If we introduce a value equal to the ratio of the average degree of the neighbors for a certain node to the degree of this node (which is called the ‘friendship index’, FI), then the FI value of more than 1 for most nodes indicates the presence of the friendship paradox in the network. In this paper, we study the behavior of the FI over time for networks generated by growth network models. We will focus our analysis on two models based on the use of the preferential attachment mechanism: the Barabási–Albert model and the triadic closure model. Using the mean-field approach, we obtain differential equations describing the dynamics of changes in the FI over time, and accordingly, after obtaining their solutions, we find the expected values of this index over iterations. The results show that the values of FI are decreasing over time for all nodes in both models. However, for networks constructed in accordance with the triadic closure model, this decrease occurs at a much slower rate than for the Barabási–Albert graphs. In addition, we analyze several real-world networks and show that their FI distributions follow a power law. We show that both the Barabási–Albert and the triadic closure networks exhibit the same behavior. However, for networks based on the triadic closure model, the distributions of FI are more heavy-tailed and, in this sense, are closer to the distributions for real networks.

Robust Autonomous Car-Like Robot Tracking Based on Tracking-Learning-Detection

2014 ◽  
Vol 687-691 ◽  
pp. 564-571 ◽  
Author(s):  
Lin Bao Xu ◽  
Shu Ming Tang ◽  
Jin Feng Yang ◽  
Yan Min Dong
Keyword(s):  
Optical Flow ◽  
Fast Moving ◽  
Moving Objects ◽  
Tracking Algorithm ◽  
Robust Tracking ◽  
Symmetry Detection ◽  
Tracking Method ◽  
Robot Tracking ◽  
Improve Accuracy ◽  
First Time

This paper proposes a robust tracking algorithm for an autonomous car-like robot, and this algorithm is based on the Tracking-Learning-Detection (TLD). In this paper, the TLD method is extended to track the autonomous car-like robot for the first time. In order to improve accuracy and robustness of the proposed algorithm, a method of symmetry detection of autonomous car-like robot rear is integrated into the TLD. Moreover, the Median-Flow tracker in TLD is improved with a pyramid-based optical flow tracking method to capture fast moving objects. Extensive experiments and comparisons show the robustness of the proposed method.

scholarly journals Camp stability predicts patterns of hunter–gatherer cooperation

2016 ◽  
Vol 3 (7) ◽  
pp. 160131 ◽  
Author(s):  
Daniel Smith ◽  
Mark Dyble ◽  
James Thompson ◽  
Katie Major ◽  
Abigail E. Page ◽  
...  
Keyword(s):  
Real World ◽  
Ecological Context ◽  
Hunter Gatherers ◽  
Ecological Conditions ◽  
Resource Transfers ◽  
Experimental Games ◽  
Using Data ◽  
Over Time ◽  
Do So

Humans regularly cooperate with non-kin, which has been theorized to require reciprocity between repeatedly interacting and trusting individuals. However, the role of repeated interactions has not previously been demonstrated in explaining real-world patterns of hunter–gatherer cooperation. Here we explore cooperation among the Agta, a population of Filipino hunter–gatherers, using data from both actual resource transfers and two experimental games across multiple camps. Patterns of cooperation vary greatly between camps and depend on socio-ecological context. Stable camps (with fewer changes in membership over time) were associated with greater reciprocal sharing, indicating that an increased likelihood of future interactions facilitates reciprocity. This is the first study reporting an association between reciprocal cooperation and hunter–gatherer band stability. Under conditions of low camp stability individuals still acquire resources from others, but do so via demand sharing (taking from others), rather than based on reciprocal considerations. Hunter–gatherer cooperation may either be characterized as reciprocity or demand sharing depending on socio-ecological conditions.

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