An A Priori Measure of Visual Difficulty of 2-D Sketches Depicting 3-D Objects

2019 ◽  
Vol 50 (5) ◽  
pp. 489-528
Author(s):  
Mirela Widder ◽  
Avi Berman ◽  
Boris Koichu
Keyword(s):  
High School ◽  
Spatial Ability ◽  
Time Allocation ◽  
A Priori ◽  
Study Time ◽  
Two Dimensional ◽  
Spatial Geometry ◽  
Geometrical Information ◽  
Visual Difficulty ◽  
Geometry Instruction

Aiming to enhance understanding of visual obstacles inherent in two-dimensional (2-D) sketches used in high school spatial geometry instruction, we propose a measure of visual difficulty based on two attributes of the sketches: potentially misleading geometrical information (PMI) and potentially helpful geometrical information (PHI). The difficulty of 12 normatively oriented cube-related sketches was theoretically ranked according to their ratios, #PHI/#PMI. The ranking was compared to the actual visual difficulty as measured by the percentage of correct or desired comprehension, individual spatial ability, and study-time allocation. This procedure was repeated for unnormatively oriented sketches, obtained by vertically flipping the original sketches. In both cases, the findings substantiate #PHI/#PMI as an a priori measure of visual difficulty. Practical, theoretical, and methodological implications are inspected and discussed.

Comparison principles for free-surface flows with gravity

1991 ◽  
Vol 230 ◽  
pp. 231-243 ◽  
Author(s):  
Walter Craig ◽  
Peter Sternberg
Keyword(s):  
Solitary Waves ◽  
Finite Depth ◽  
Free Surface Flows ◽  
Immiscible Fluids ◽  
Steady Flows ◽  
Two Dimensional ◽  
Surface Flows ◽  
Ship Hulls ◽  
Geometrical Information ◽  
Supercritical Flows

This article considers certain two-dimensional, irrotational, steady flows in fluid regions of finite depth and infinite horizontal extent. Geometrical information about these flows and their singularities is obtained, using a variant of a classical comparison principle. The results are applied to three types of problems: (i) supercritical solitary waves carrying planing surfaces or surfboards, (ii) supercritical flows past ship hulls and (iii) supercritical interfacial solitary waves in systems consisting of two immiscible fluids.

scholarly journals The effect of time pressure on metacognitive control: developmental changes in self-regulation and efficiency during learning

2021 ◽  
Author(s):  
Gökhan Gönül ◽  
Nike Tsalas ◽  
Markus Paulus
Keyword(s):  
Time Allocation ◽  
Time Pressure ◽  
Self Regulation ◽  
Age Groups ◽  
Study Time ◽  
Developmental Differences ◽  
Developmental Changes ◽  
Metacognitive Control ◽  
Metacognitive Cues ◽  
Study Time Allocation

AbstractThe effect of time pressure on metacognitive control is of theoretical and empirical relevance and is likely to allow us to tap into developmental differences in performances which do not become apparent otherwise, as previous studies suggest. In the present study, we investigated the effect of time pressure on metacognitive control in three age groups (10-year-olds, 14-year-olds, and adults, n = 183). Using an established study time allocation paradigm, participants had to study two different sets of picture pairs, in an untimed and a timed condition. The results showed that metacognitive self-regulation of study time (monitor-based study time allocation) differed between age groups when studying under time pressure. Even though metacognitive control is firmly coupled at 10 years of age, the overall level of self-regulation of adults was higher than that of children and adolescents across both study time conditions. This suggests that adults might have been more sensitive to experiential metacognitive cues such as JoL for the control of study time. Moreover, the timed condition was found to be more effective than the untimed, with regard to study time allocation. Also, there was an age effect, with adults being more efficient than 10- and 14-year-olds.

Machine vision-based sensing for helicopter flight control

Robotica ◽  
2000 ◽  
Vol 18 (3) ◽  
pp. 299-303 ◽  
Author(s):  
Carl-Henrik Oertel
Keyword(s):  
Machine Vision ◽  
Measurement System ◽  
Flight Control ◽  
A Priori ◽  
Image Data ◽  
Two Dimensional ◽  
Position Measurement ◽  
Additional Information ◽  
Helicopter Flight ◽  
Template Tracking

Machine vision-based sensing enables automatic hover stabilization of helicopters. The evaluation of image data, which is produced by a camera looking straight to the ground, results in a drift free autonomous on-board position measurement system. No additional information about the appearance of the scenery seen by the camera (e.g. landmarks) is needed. The technique being applied is a combination of the 4D-approach with two dimensional template tracking of a priori unknown features.

NUMERICAL SOLUTION OF TWO-DIMENSIONAL PROBLEMS OF THERMOVISCOELASTICITY

2021 ◽  
Vol 335 (1) ◽  
pp. 60-64
Author(s):  
M. Bukenov ◽  
Ye. Mukhametov
Keyword(s):  
A Priori ◽  
Elastic Collision ◽  
Qualitative Behavior ◽  
Stress Profile ◽  
Two Dimensional ◽  
A Priori Information ◽  
Deformable Solids ◽  
Methods Of Calculation ◽  
The Difference ◽  
Priori Information

This paper considers the numerical implementation of two-dimensional thermoviscoelastic waves. The elastic collision of an aluminum cylinder with a two-layer plate of aluminum and iron is considered. In work [1] the difference schemes and algorithm of their realization are given. The most complete reviews of the main methods of calculation of transients in deformable solids can be found in [2, 3, 4], which also indicates the need and importance of generalized studies on the comparative evaluation of different methods and identification of the areas of their most rational application. In the analysis and physical interpretation of numerical results in this work it is also useful to use a priori information about the qualitative behavior of the solution and all kinds of information about the physics of the phenomena under study. Here is the stage of evolution of contact resistance of collision – plate, stress profile.

Intermezzo

2014 ◽  
Author(s):  
Subrata Dasgupta
Keyword(s):  
High School ◽  
World War Ii ◽  
A Priori ◽  
World War ◽  
Structure Of Scientific Revolutions ◽  
Scientific Context ◽  
Computational Paradigm ◽  
Doctoral Work ◽  
Mature Science ◽  
Dominant Paradigm

By the end of World War II, independent of one another (and sometimes in mutual ignorance), a small assortment of highly creative minds—mathematicians, engineers, physicists, astronomers, and even an actuary, some working in solitary mode, some in twos or threes, others in small teams, some backed by corporations, others by governments, many driven by the imperative of war—had developed a shadowy shape of what the elusive Holy Grail of automatic computing might look like. They may not have been able to define a priori the nature of this entity, but they were beginning to grasp how they might recognize it when they saw it. Which brings us to the nature of a computational paradigm. Ever since the historian and philosopher of science Thomas Kuhn (1922–1996) published The Structure of Scientific Revolutions (1962), we have all become ultraconscious of the concept and significance of the paradigm, not just in the scientific context (with which Kuhn was concerned), but in all intellectual and cultural discourse. A paradigm is a complex network of theories, models, procedures and practices, exemplars, and philosophical assumptions and values that establishes a framework within which scientists in a given field identify and solve problems. A paradigm, in effect, defines a community of scientists; it determines their shared working culture as scientists in a branch of science and a shared mentality. A hallmark of a mature science, according to Kuhn, is the emergence of a dominant paradigm to which a majority of scientists in that field of science adhere and broadly, although not necessarily in detail, agree on. In particular, they agree on the fundamental philosophical assumptions and values that oversee the science in question; its methods of experimental and analytical inquiry; and its major theories, laws, and principles. A scientist “grows up” inside a paradigm, beginning from his earliest formal training in a science in high school, through undergraduate and graduate schools, through doctoral work into postdoctoral days. Scientists nurtured within and by a paradigm more or less speak the same language, understand the same terms, and read the same texts (which codify the paradigm).

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