367 research outputs found

    Distinguishing Posed and Spontaneous Smiles by Facial Dynamics

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    Smile is one of the key elements in identifying emotions and present state of mind of an individual. In this work, we propose a cluster of approaches to classify posed and spontaneous smiles using deep convolutional neural network (CNN) face features, local phase quantization (LPQ), dense optical flow and histogram of gradient (HOG). Eulerian Video Magnification (EVM) is used for micro-expression smile amplification along with three normalization procedures for distinguishing posed and spontaneous smiles. Although the deep CNN face model is trained with large number of face images, HOG features outperforms this model for overall face smile classification task. Using EVM to amplify micro-expressions did not have a significant impact on classification accuracy, while the normalizing facial features improved classification accuracy. Unlike many manual or semi-automatic methodologies, our approach aims to automatically classify all smiles into either `spontaneous' or `posed' categories, by using support vector machines (SVM). Experimental results on large UvA-NEMO smile database show promising results as compared to other relevant methods.Comment: 16 pages, 8 figures, ACCV 2016, Second Workshop on Spontaneous Facial Behavior Analysi

    Individual differences in search and monitoring for color targets in dynamic visual displays

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    Many jobs now involve the monitoring visual representations of data that change over time. Monitoring dynamically changing displays for the onset of targets can be done in two ways: detecting targets directly post their onset or predicting their onset from the prior state of distractors. In the present study, participants? eye movements were measured as they monitored arrays of 108 colored squares whose colors changed systematically over time. Across three experiments, the data show that participants detected the onset of targets both directly and predictively. Experiments 1 and 2 showed that predictive detection was only possible when supported by sequential color changes that followed a scale ordered in color space. Experiment 3 included measures of individual differences in working memory capacity (WMC) and anxious affect and a manipulation of target prevalence in the search task. It found that predictive monitoring for targets, and decisions about target onsets, were influenced by interactions between individual differences in verbal and spatial WMC and intolerance of uncertainty, a characteristic that reflects worry about uncertain future events. The results have implications for the selection of individuals tasked with monitoring dynamic visual displays for target onsets

    Meeting the Needs of Middle Grades Social Studies Students with Language Based Learning Disabilities: An Analysis of Students’ and Teachers’ Perspectives

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    The purpose of this study was to investigate the consistency with which middle level social studies and special education teachers and administrators assist, educate, and guide middle level social studies students with language-based learning disabilities. The study was an inquiry into the students’, teachers’, and administrator’s literacy beliefs and practices and it examined the coherence and congruence among these beliefs and practices. Conducted as an action research study, it examined the extent of the alignment using data collected from five teachers, six students and one administrator by means of interviews, focus groups, photographs, journal entries, and inventories. The data from teachers included interviews, observations, focus groups, a literacy journal and inventories. The primary aim of the study was to evaluate the extent to which schools provide well-aligned and congruent structural and organizational systems to support a coherent approach to literacy-based learning in middle level social studies classes. The findings suggest that there is coherence and congruence between the literacy beliefs of the students, teachers and administrator. They further suggest that for the most part, there exists congruence and coherence between the participants’ practices. However, there are some incongruences about students’ and teachers’ literacy based beliefs and practices in a middle level social studies setting. These are largely misconceptions and may be the source of some disconnect between these participants. Implications for the field include the need to improve teacher and administrator opportunities for professional development and reflection as well as the need to define best practices, including metacognitive skills for students with language-based learning disabilities in a middle level social studies setting

    Leibniz Seminorms and Best Approximation from C*-subalgebras

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    We show that if B is a C*-subalgebra of a C*-algebra A such that B contains a bounded approximate identity for A, and if L is the pull-back to A of the quotient norm on A/B, then L is strongly Leibniz. In connection with this situation we study certain aspects of best approximation of elements of a unital C*-algebra by elements of a unital C*-subalgebra.Comment: 24 pages. Intended for the proceedings of the conference "Operator Algebras and Related Topics". v2: added a corollary to the main theorem, plus several minor improvements v3: much simplified proof of a key lemma, corollary to main theorem added v4: Many minor improvements. Section numbers increased by

    Strategies for getting produce into corner stores

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    Thesis (M.C.P.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 68-71).Availability of fresh, healthy produce for low-income people is a growing concern for advocates and public officials concerned with health disparities and diet-related disease. Healthy corner store conversions are a promising strategy to address issues of food access. To be successful, conversion programs must address the challenges of sourcing and selling produce. As a perishable product, produce requires store owner to possess significant skills and infrastructure for proper management. Additionally, corner stores face a supply chain increasingly structured for large supermarkets and must balance the often-competing factors of small scale, affordability, and quality. Finally, programs must consider how to appropriately serve and engage communities to ensure financial viability and maximize health impacts. This thesis explores strategies to improve the provision of produce through corner stores through a review of reports, literature, and practice. Central to these approaches are the goals of increased efficiency and affordability and long-term sustainability. Several corner store programs have demonstrated the possibility for making money through produce sales using a holistic approach that engages community members and provides training and assistance to store owners. Supply strategies range from cooperative purchasing, shared docking with larger stores or institutions, convincing wholesalers to accommodate smaller orders, and developing new distribution infrastructure that integrates small stores into the local food system. This work concludes with key lessons for corner store programs seeking to improve produce supply practices and infrastructure. The discussion also includes opportunities for actors in produce supply and distribution to capture this emerging market and support food access efforts.by Angela J. Hadwin.M.C.P
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