Tunnel vision optimization method for VR flood scenes based on Gaussian blur

Author(s):  
Lin Fu ◽  
Jun Zhu ◽  
Weilian Li ◽  
Qing Zhu ◽  
Bingli Xu ◽  
...  
2018 ◽  
Vol 23 (6) ◽  
pp. 14-15
Author(s):  
Lee H. Ensalada

Abstract Symptom validity testing (SVT), also known as forced-choice testing, is a means of assessing the validity of sensory and memory deficits, including tactile anesthesias, paresthesias, blindness, color blindness, tunnel vision, blurry vision, and deafness. The common feature among these symptoms is a claimed inability to perceive or remember a sensory signal. SVT comprises two elements: a specific ability is assessed by presenting a large number of items in a multiple-choice format, and then the examinee's performance is compared to the statistical likelihood of success based on chance alone. These tests usually present two alternatives; thus the probability of simply guessing the correct response (equivalent to having no ability at all) is 50%. Thus, scores significantly below chance performance indicate that the sensory cues must have been perceived, but the examinee chose not to report the correct answer—alternative explanations are not apparent. SVT also has the capacity to demonstrate that the examinee performed below the probabilities of chance. Scoring below a norm can be explained by fatigue, evaluation anxiety, inattention, or limited intelligence. Scoring below the probabilities of chance alone most likely indicates deliberate deceptions and is evidence of malingering because it provides strong evidence that the examinee received the sensory cues and denied the perception. Even so, malingering must be evaluated from the total clinical context.


1999 ◽  
Vol 4 (4) ◽  
pp. 4-4

Abstract Symptom validity testing, also known as forced-choice testing, is a way to assess the validity of sensory and memory deficits, including tactile anesthesias, paresthesias, blindness, color blindness, tunnel vision, blurry vision, and deafness—the common feature of which is a claimed inability to perceive or remember a sensory signal. Symptom validity testing comprises two elements: A specific ability is assessed by presenting a large number of items in a multiple-choice format, and then the examinee's performance is compared with the statistical likelihood of success based on chance alone. Scoring below a norm can be explained in many different ways (eg, fatigue, evaluation anxiety, limited intelligence, and so on), but scoring below the probabilities of chance alone most likely indicates deliberate deception. The positive predictive value of the symptom validity technique likely is quite high because there is no alternative explanation to deliberate distortion when performance is below the probability of chance. The sensitivity of this technique is not likely to be good because, as with a thermometer, positive findings indicate that a problem is present, but negative results do not rule out a problem. Although a compelling conclusion is that the examinee who scores below probabilities is deliberately motivated to perform poorly, malingering must be concluded from the total clinical context.


2020 ◽  
Vol 19 (2) ◽  
pp. 63-74
Author(s):  
Klaus Moser ◽  
Hans-Georg Wolff ◽  
Roman Soucek

Abstract. Escalation of commitment occurs when a course of action is continued despite repeated drawbacks (e.g., maintaining an employment relationship despite severe performance problems). We analyze process accountability (PA) as a de-escalation technique that helps to discontinue a failing course of action and show how time moderates both the behavioral and cognitive processes involved: (1) Because sound decisions should be based on (hopefully unbiased) information search, which requires time to gather, the effect of PA on de-escalation increases over time. (2) Because continuing information search creates behavioral commitment, the debiasing effect of PA on information search diminishes over time. (3) Consistent with the tunnel vision notion, the effects of less biased information search on de-escalation decrease over time.


CICTP 2019 ◽  
2019 ◽  
Author(s):  
Yuchen Wang ◽  
Tao Lu ◽  
Hongxing Zhao ◽  
Zhiying Bao
Keyword(s):  

Author(s):  
Fachrudin Hunaini ◽  
Imam Robandi ◽  
Nyoman Sutantra

Fuzzy Logic Control (FLC) is a reliable control system for controlling nonlinear systems, but to obtain optimal fuzzy logic control results, optimal Membership Function parameters are needed. Therefore in this paper Particle Swarm Optimization (PSO) is used as a fast and accurate optimization method to determine Membership Function parameters. The optimal control system simulation is carried out on the automatic steering system of the vehicle model and the results obtained are the vehicle's lateral motion error can be minimized so that the movement of the vehicle can always be maintained on the expected trajectory


TAPPI Journal ◽  
2015 ◽  
Vol 14 (2) ◽  
pp. 119-129 ◽  
Author(s):  
VILJAMI MAAKALA ◽  
PASI MIIKKULAINEN

Capacities of the largest new recovery boilers are steadily rising, and there is every reason to expect this trend to continue. However, the furnace designs for these large boilers have not been optimized and, in general, are based on semiheuristic rules and experience with smaller boilers. We present a multiobjective optimization code suitable for diverse optimization tasks and use it to dimension a high-capacity recovery boiler furnace. The objective was to find the furnace dimensions (width, depth, and height) that optimize eight performance criteria while satisfying additional inequality constraints. The optimization procedure was carried out in a fully automatic manner by means of the code, which is based on a genetic algorithm optimization method and a radial basis function network surrogate model. The code was coupled with a recovery boiler furnace computational fluid dynamics model that was used to obtain performance information on the individual furnace designs considered. The optimization code found numerous furnace geometries that deliver better performance than the base design, which was taken as a starting point. We propose one of these as a better design for the high-capacity recovery boiler. In particular, the proposed design reduces the number of liquor particles landing on the walls by 37%, the average carbon monoxide (CO) content at nose level by 81%, and the regions of high CO content at nose level by 78% from the values obtained with the base design. We show that optimizing the furnace design can significantly improve recovery boiler performance.


1943 ◽  
Vol 4 (3) ◽  
pp. 362-367 ◽  
Author(s):  
Albion Roy King
Keyword(s):  

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