•The compressive strength relations of cubic and cylindrical specimens are proposed.•Empirical relations are obtained to correlate the strength of various size samples.•The crack patterns of cubic ...and various cylindrical specimens are analyzed.
Cylinder and cube are two common specimen shapes used in compressive tests to determine concrete strength. Many studies have proposed empirical relations to convert the static strengths of concrete obtained from specimens of these two shapes. There is, however, no study of the relations to convert the dynamic strengths of cylindrical and cubic concrete specimens obtained from impact tests. In this study, cubic and cylindrical concrete specimens of different sizes were prepared and tested under static and impact loads to investigate the shape and size effects on the concrete compressive strength under different loading rates. To investigate the influences of strength on these relations, concrete specimens of two characteristic strengths were made and tested. Cubes of dimension 50 mm and cylinders of diameter 50 mm with various length-to-diameter ratios were cast and tested. Empirical relations that correlate the static and dynamic compressive strengths of concrete obtained from specimens of different shapes and sizes were proposed. The crack patterns of different samples in both static and dynamic tests and their influences on the obtained compressive strengths were also analyzed. The results clearly demonstrate the influences of the specimen shape and size on the obtained compressive strength under static and dynamic tests.
Accurate characterization of morphological variation is crucial for generating reliable results and conclusions concerning changes and differences in form. Despite the prevalence of landmark-based ...geometric morphometric (GM) data in the scientific literature, a formal treatment of whether sampled landmarks adequately capture shape variation has remained elusive. Here, I introduce LaSEC (Landmark Sampling Evaluation Curve), a computational tool to assess the fidelity of morphological characterization by landmarks. This task is achieved by calculating how subsampled data converge to the pattern of shape variation in the full dataset as landmark sampling is increased incrementally. While the number of landmarks needed for adequate shape variation is dependent on individual datasets, LaSEC helps the user (1) identify under- and oversampling of landmarks; (2) assess robustness of morphological characterization; and (3) determine the number of landmarks that can be removed without compromising shape information. In practice, this knowledge could reduce time and cost associated with data collection, maintain statistical power in certain analyses, and enable the incorporation of incomplete, but important, specimens to the dataset. Results based on simulated shape data also reveal general properties of landmark data, including statistical consistency where sampling additional landmarks has the tendency to asymptotically improve the accuracy of morphological characterization. As landmark-based GM data become more widely adopted, LaSEC provides a systematic approach to evaluate and refine the collection of shape data--a goal paramount for accumulation and analysis of accurate morphological information.
Young children working with geometric figures Filipa Balinha; Ema Mamede
JETEN (Journal of the European Teacher Education Network),
09/2018, Letnik:
13, Številka:
2018
Journal Article
Recenzirano
Odprti dostop
This paper focuses on 20 young children spatial sense (3-4-years-old) from a public kindergarten, in Braga, Portugal. Three questions were addressed: 1) How do children understand some geometric ...figures? 2) How is children’s spatial sense characterized, concerning geometric figures? 3) What specific geometry vocabulary do children learn? Qualitative methods using a case study approach were used to describe children’s reactions when solving 10 tasks involving geometric figures and properties of these figures. Results suggests that children’s ideas of particular figures can be improved when specific tasks and materials are used. These aspects are explained in the paper.
Distance-based topological indices are numerical parameters that are derived from the distances between atoms in a molecular structure, and they provide a quantitative measure of the topology and ...geometry of a molecule. The distance-based topological indices uses to predict various properties of molecules, including their boiling points, melting points, and solubility. It also predicts the biological activity of molecules, including their pharmacological and toxicological properties. Pentagonal chain molecules are organic compounds that consist of a linear chain of five-membered (pentagons) connected by carbon and bonds. These molecules have unique structural and electronic properties that make them useful in a variety of applications. Motivated by the pentagonal chain molecules, we have considered a pentagonal chain graph and it is denoted by P.sub.n . We have computed some distance based topological indices for P.sub.n . The paper focuses on a pentagonal chain molecules denoted by G, and derives several distance-based topological indices. These indices compromise insights into physicochemical properties, aid in identifying structural characterizations, and enhance understanding of molecular properties.
A within-participants experiment was conducted in two countries (the UK and Colombia) in order to investigate the matching of shapes to taste words. Comparing the two countries allowed us to explore ...some of the cultural differences that have been reported thus far solely in terms of people's visual preferences. In particular, we addressed the question of whether properties other than angularity influence shape-valence and shape-taste matching (crossmodal correspondences). The participants in the present study repeatedly matched eight shapes, varying in terms of their angularity, symmetry, and number of elements to one of two words-pleasant or unpleasant and sweet or sour. Participants' choices, as well as the latency of their responses, and their hand movements, were evaluated. The participants were more likely to judge those shapes that were rounder, symmetrical, and those shapes that had fewer elements as both pleasant and sweet. Those shapes that were more angular, asymmetrical, and that had a greater number of elements, were more likely to be judged as both unpleasant and sour instead. The evidence presented here therefore suggests that aside from angularity and roundness, both symmetry/asymmetry and the number of elements present in a shape also influence valence and taste categorizations.
Shape is a defining feature of objects, and human observers can effortlessly compare shapes to determine how similar they are. Yet, to date, no image-computable model can predict how visually similar ...or different shapes appear. Such a model would be an invaluable tool for neuroscientists and could provide insights into computations underlying human shape perception. To address this need, we developed a model (‘ShapeComp’), based on over 100 shape features (e.g., area, compactness, Fourier descriptors). When trained to capture the variance in a database of >25,000 animal silhouettes, ShapeComp accurately predicts human shape similarity judgments between pairs of shapes without fitting any parameters to human data. To test the model, we created carefully selected arrays of complex novel shapes using a Generative Adversarial Network trained on the animal silhouettes, which we presented to observers in a wide range of tasks. Our findings show that incorporating multiple ShapeComp dimensions facilitates the prediction of human shape similarity across a small number of shapes, and also captures much of the variance in the multiple arrangements of many shapes. ShapeComp outperforms both conventional pixel-based metrics and state-of-the-art convolutional neural networks, and can also be used to generate perceptually uniform stimulus sets, making it a powerful tool for investigating shape and object representations in the human brain.
•Mental images in the geometry of art.•Spatial imagery skills and imagery control in fine art students favour the visualisation of geometric figures in artworks.•Spatial ability and image control are ...useful tools to achieve competences in the artistic field.
The study of artistic works requires an educated vision, a certain way of looking that unveils potential relations amongst objects. Fine art students develop skills that are resultant of their training in finding possible connections amongst elements in a painting. One of the abilities related to the observation and analysis of a work of art is the capacity to form mental images. The present study involved 188 fine art students (105 first-year students and 83 fourth-year students) and was meant to find out whether their education level, their spatial imagery ability and their imagery control had any influence on the location of geometric forms in a painting. We assessed hits minus errors. Results showed Results showed that fine arts students’ spatial ability and imagery control explained a significant percentage of score variation in the task of locating geometric figures in Velázquez's paintings. The significance of these results is consistent with those obtained in previous studies, spatial capacity, and imagery control influence on the achievement of skills in the artistic field.
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