44,678 research outputs found

    Handwriting Performance of Typical Second-Grade Students as Measured by the Evaluation Tool of Children\u27s Handwriting - Manuscript and Teacher Perceptions of Legibility

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    Background: The purpose of the study was to describe scores achieved by typical second-grade students on the Evaluation Tool of Children’s Handwriting – Manuscript and to compare scores with teacher perceptions. Method: As part of a larger study, the ETCH-M was administered to 74 second-grade students. Teachers scored classroom samples of handwriting assignments using a researcher-developed scale and scores were compared to ETCH-M scores to determine cutoff values for good versus poor handwriting. Results: Mean scores for total word legibility, total letter legibility, and total numeral legibility were 88.82%, 84.30%, and 89.26%, respectively. Cutoff scores below 82% for word legibility and 77% for letter legibility for second-grade students based on teacher perceptions of below average handwriting are cautiously suggested. Research with a larger dataset is needed. Boys scored significantly lower on the ETCH-M and this finding warrants further research. Conclusion: The findings add to the limited body of information about the psychometric properties of the ETCH-M and the normative performance of typical second-grade students

    Legibility of electroluminescent instrument panels investigated

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    Legibility studies of several EL /electroluminescent/ displays correlate reading time and accuracy with number size, stroke/width ratio, indicia size, pointer width, contrast, ambient illumination, and color background and and contrast. Human factor criteria established on non-EL displays may not apply to EL displays

    Students Exploration on Campus Legibility

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    AbstractUniversity Campuses are significant functional areas of cities. Successfully designed campuses help to balance university's academic, research and service missions with its educational services and raise learning performances. Campuses’ high level of design and planning service has close relation with its legibility. Kevin Lynch, one of the leading theorists who had research on place legibility used cognitive mapping as a tool and defined five fundamental elements, have great influence on place legibility. In this study, Black Sea Technical University is selected as the research area and its legibility level has determined. Aim of this study is to define the legibility level of the campus by students perceptions. In this context, Lynch's five fundamental legibility elements directed students to generate cognitive maps of the campus, and each student's perception level on campus area is determined. Respondent group include students from Architecture, and Urban and Regional Planning departments have contributed this study. End product is the analysis of the cognitive maps, produced by each student, based on legibility elements. The result of the analysis legibility map of the campus has created, and the legibility level of the campus area is determined. Following, the results are classified as the areas with high, medium and low cognition. Finally, possibility of raising university's educational and research activities through design are discussed

    Learning the Legibility of Visual Text Perturbations

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    Many adversarial attacks in NLP perturb inputs to produce visually similar strings ('ergo' →\rightarrow 'ϵ\epsilonrgo') which are legible to humans but degrade model performance. Although preserving legibility is a necessary condition for text perturbation, little work has been done to systematically characterize it; instead, legibility is typically loosely enforced via intuitions around the nature and extent of perturbations. Particularly, it is unclear to what extent can inputs be perturbed while preserving legibility, or how to quantify the legibility of a perturbed string. In this work, we address this gap by learning models that predict the legibility of a perturbed string, and rank candidate perturbations based on their legibility. To do so, we collect and release LEGIT, a human-annotated dataset comprising the legibility of visually perturbed text. Using this dataset, we build both text- and vision-based models which achieve up to 0.910.91 F1 score in predicting whether an input is legible, and an accuracy of 0.860.86 in predicting which of two given perturbations is more legible. Additionally, we discover that legible perturbations from the LEGIT dataset are more effective at lowering the performance of NLP models than best-known attack strategies, suggesting that current models may be vulnerable to a broad range of perturbations beyond what is captured by existing visual attacks. Data, code, and models are available at https://github.com/dvsth/learning-legibility-2023.Comment: 14 pages, 7 figures. Accepted at EACL 2023 (main, long

    How form and structure of Chinese characters affect eye movement control

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    This study investigated the correlations between the form features and legibility of Chinese characters by employing the eye tracking method in two experiments: Experiment 1 examined factors affecting Chinese character legibility with character modules and identified the correlations between character form and legibility of crossing strokes; and Experiment 2 examined the effect of crossing strokes on subjective complicacy perception in both Chinese characters and English letters. This study determined that enclosed Chinese characters affect subjective complicacy perception and reduce saccadic amplitude. In addition, greater number of stroke crossings produced higher subjective complicacy perceived for both Chinese characters and English letters. The results of this study serve as a reference for predicting Chinese character legibility and assessing type design superiority
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