3,351 research outputs found
Transcribing Content from Structural Images with Spotlight Mechanism
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
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
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
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-makersâ 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 designersâ capabilities
Hearing in Time: Bergsonian Concepts of Time in Maurice Ravelâs LâHeure espagnole
This dissertation examines Maurice Ravelâs first opera, LâHeure espagnole (1907â1911), as a turning point in the composerâs aesthetic approach, marking a moment at which he reacted strongly against Debussyâs 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 Ravelâs aesthetics and Bergsonism, but the musical underpinnings of Bergsonâs philosophy of time itself have remained vastly undertheorized. My project sets out to rectify this by locating both Ravelâs aesthetics and Bergsonâs 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©vitchâs writings, in turn, reveal important information about the practical application of Bergsonism to music and the intertwining of Debussyâs PellĂ©as et MĂ©lisande with Bergsonian philosophical ideals. The dissertation culminates in an analysis of LâHeure espagnole as a site of exchange between music and Bergsonâs 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 Ravelâs unique use of rhythm and meter in LâHeure 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 Ravelâs aesthetic direction around the time he was composing LâHeure espagnole: an archival approach (Chapters 1â3) and a hermeneutic approach (Chapter 4). The first half of my study (Chapters 1 and 2) surveys Ravelâs 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 Ravelâs music by exploring the practical implementation of Bergsonâs theories of duration and intuition in music through Bergsonâs disciples, Laloy and JankĂ©lĂ©vitch. My study concludes with a hermeneutic analysis of LâHeure espagnole that uses Bergsonâs 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.
Samuel Beckettâs 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. Beckettâs 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 Beckettâs 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 Beckettâs 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 Beckettâs Not I uniquely through the medium of music. This study will reveal how these musical works emphasize the sonic content of Beckettâs Not I in a significant manner
Tipping Point: The Diversity Threshold for White Student (Dis) Engagement in Traditional Student Organizations
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 studentsâ (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 studentsâ 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 ârhetoric of diversity,â I argue that the experiences and attitudes of White students can inform the policy debate on institutional mission and offerings
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