3,351 research outputs found

    Transcribing Content from Structural Images with Spotlight Mechanism

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    Transcribing content from structural images, e.g., writing notes from music scores, is a challenging task as not only the content objects should be recognized, but the internal structure should also be preserved. Existing image recognition methods mainly work on images with simple content (e.g., text lines with characters), but are not capable to identify ones with more complex content (e.g., structured symbols), which often follow a fine-grained grammar. To this end, in this paper, we propose a hierarchical Spotlight Transcribing Network (STN) framework followed by a two-stage "where-to-what" solution. Specifically, we first decide "where-to-look" through a novel spotlight mechanism to focus on different areas of the original image following its structure. Then, we decide "what-to-write" by developing a GRU based network with the spotlight areas for transcribing the content accordingly. Moreover, we propose two implementations on the basis of STN, i.e., STNM and STNR, where the spotlight movement follows the Markov property and Recurrent modeling, respectively. We also design a reinforcement method to refine the framework by self-improving the spotlight mechanism. We conduct extensive experiments on many structural image datasets, where the results clearly demonstrate the effectiveness of STN framework.Comment: Accepted by KDD2018 Research Track. In proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'18

    Neural Cognitive Diagnosis for Intelligent Education Systems

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    Cognitive diagnosis is a fundamental issue in intelligent education, which aims to discover the proficiency level of students on specific knowledge concepts. Existing approaches usually mine linear interactions of student exercising process by manual-designed function (e.g., logistic function), which is not sufficient for capturing complex relations between students and exercises. In this paper, we propose a general Neural Cognitive Diagnosis (NeuralCD) framework, which incorporates neural networks to learn the complex exercising interactions, for getting both accurate and interpretable diagnosis results. Specifically, we project students and exercises to factor vectors and leverage multi neural layers for modeling their interactions, where the monotonicity assumption is applied to ensure the interpretability of both factors. Furthermore, we propose two implementations of NeuralCD by specializing the required concepts of each exercise, i.e., the NeuralCDM with traditional Q-matrix and the improved NeuralCDM+ exploring the rich text content. Extensive experimental results on real-world datasets show the effectiveness of NeuralCD framework with both accuracy and interpretability

    Exploiting Cognitive Structure for Adaptive Learning

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    Adaptive learning, also known as adaptive teaching, relies on learning path recommendation, which sequentially recommends personalized learning items (e.g., lectures, exercises) to satisfy the unique needs of each learner. Although it is well known that modeling the cognitive structure including knowledge level of learners and knowledge structure (e.g., the prerequisite relations) of learning items is important for learning path recommendation, existing methods for adaptive learning often separately focus on either knowledge levels of learners or knowledge structure of learning items. To fully exploit the multifaceted cognitive structure for learning path recommendation, we propose a Cognitive Structure Enhanced framework for Adaptive Learning, named CSEAL. By viewing path recommendation as a Markov Decision Process and applying an actor-critic algorithm, CSEAL can sequentially identify the right learning items to different learners. Specifically, we first utilize a recurrent neural network to trace the evolving knowledge levels of learners at each learning step. Then, we design a navigation algorithm on the knowledge structure to ensure the logicality of learning paths, which reduces the search space in the decision process. Finally, the actor-critic algorithm is used to determine what to learn next and whose parameters are dynamically updated along the learning path. Extensive experiments on real-world data demonstrate the effectiveness and robustness of CSEAL.Comment: Accepted by KDD 2019 Research Track. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD'19

    An aesthetics of touch: investigating the language of design relating to form

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    How well can designers communicate qualities of touch? This paper presents evidence that they have some capability to do so, much of which appears to have been learned, but at present make limited use of such language. Interviews with graduate designer-makers suggest that they are aware of and value the importance of touch and materiality in their work, but lack a vocabulary to fully relate to their detailed explanations of other aspects such as their intent or selection of materials. We believe that more attention should be paid to the verbal dialogue that happens in the design process, particularly as other researchers show that even making-based learning also has a strong verbal element to it. However, verbal language alone does not appear to be adequate for a comprehensive language of touch. Graduate designers-makers’ descriptive practices combined non-verbal manipulation within verbal accounts. We thus argue that haptic vocabularies do not simply describe material qualities, but rather are situated competences that physically demonstrate the presence of haptic qualities. Such competencies are more important than groups of verbal vocabularies in isolation. Design support for developing and extending haptic competences must take this wide range of considerations into account to comprehensively improve designers’ capabilities

    Hearing in Time: Bergsonian Concepts of Time in Maurice Ravel’s L’Heure espagnole

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    This dissertation examines Maurice Ravel’s first opera, L’Heure espagnole (1907–1911), as a turning point in the composer’s aesthetic approach, marking a moment at which he reacted strongly against Debussy’s influence and seems to have increasingly oriented his compositional perspective toward comedy, mechanism, and manipulations of musical time. In recent years, Ravel scholars have identified promising connections between Ravel’s aesthetics and Bergsonism, but the musical underpinnings of Bergson’s philosophy of time itself have remained vastly undertheorized. My project sets out to rectify this by locating both Ravel’s aesthetics and Bergson’s philosophy of time within the music-historical context of debussysme, and identifying a Bergsonian strain of music criticism in the writings of Louis Laloy and Vladimir JankĂ©lĂ©vitch, both of whom studied under Bergson. Laloy and JankĂ©lĂ©vitch’s writings, in turn, reveal important information about the practical application of Bergsonism to music and the intertwining of Debussy’s PellĂ©as et MĂ©lisande with Bergsonian philosophical ideals. The dissertation culminates in an analysis of L’Heure espagnole as a site of exchange between music and Bergson’s philosophy of time, analyzing it as a testing ground for the Bergsonian concept of duration, a theory of time that reflects our lived experience as it unfolds in the present. Ultimately, I theorize that Ravel’s unique use of rhythm and meter in L’Heure espagnole encourages a practice of real-time analysis through the act of hearing, which in turn allows the listener to provisionally enact durational time through a constant re-evaluation of the metric and rhythmic frame based on material that was just heard. My dissertation employs a twofold methodological approach to investigate the shift in Ravel’s aesthetic direction around the time he was composing L’Heure espagnole: an archival approach (Chapters 1–3) and a hermeneutic approach (Chapter 4). The first half of my study (Chapters 1 and 2) surveys Ravel’s personal correspondence with the Godebski family and the press reception of his works between roughly 1905 and 1910 as evidence for the creation of a new aesthetic posture that would distance him from Debussy and catalyze his novel use of time and meter as a distinctive aspect of his style. Chapter 3 presents archival research on Bergson and his interlocutors, linking his philosophy of time to contemporaneous research on music, sensation, and consciousness by Gustav Fechner, ThĂ©odule Ribot, and Paul and Pierre Janet. Here, I develop the grounds for a Bergsonian approach to Ravel’s music by exploring the practical implementation of Bergson’s theories of duration and intuition in music through Bergson’s disciples, Laloy and JankĂ©lĂ©vitch. My study concludes with a hermeneutic analysis of L’Heure espagnole that uses Bergson’s theory of duration as an interpretive lens to make sense of the complex interaction between comedy, mechanism, and time in the opera

    The sounds behind language : three musical settings of Beckett\u27s not I by Heinz Holliger, Paul Rhys, and Agata Zubel.

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    Samuel Beckett’s literary and dramatic works have served as sources of inspiration in the last five decades for multiple composers such as Morton Feldman and György KurtĂĄg. Beckett’s late minimalist monologue Not I (1972) is the basis for recent compositions by Heinz Holliger, Paul Rhys, and Agata Zubel. While scholars have discussed similarities between Beckett’s style and individual musical works, a comprehensive study of multiple compositions based on the same work by Samuel Beckett has not yet been completed. Each of these compositions reflects various aspects of Beckett’s late dramatic style such as his use of rhythm, depiction of internal voices, and exploration of speech production. These musical works highlight aural features of Beckett’s Not I uniquely through the medium of music. This study will reveal how these musical works emphasize the sonic content of Beckett’s Not I in a significant manner

    Tipping Point: The Diversity Threshold for White Student (Dis) Engagement in Traditional Student Organizations

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    During a time when most institutions of higher education are in search of underrepresented student participation, Georgia State University (GSU), a majority White institution, has observed a lack of involvement of White students in co-curricular activities. The purpose of the research study was to critically examine White students’ (dis) engagement in traditional student organizations at this university that has a significant student of color population. I used case study methodology that allowed for a breadth of conceptual frameworks and research options. The methods of collecting data included interviews (formal, informal, and oral history) of current and former students, as well as campus administrators. In addition, the use of archived texts and photographs, yearbooks, organization rosters, and university enrollment statistics allowed for crystallization of data, layered interpretations, and document analyses. I used the data sources to interpret GSU White students’ perceptions of campus climate, racial interactions, leadership among students of color, and racial identity that influence their (dis) engagement in traditional student organizations and campus life. In exploring the “rhetoric of diversity,” I argue that the experiences and attitudes of White students can inform the policy debate on institutional mission and offerings
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