WORKS BY FRANCO-BELGIAN COMPOSERS AND THE VIOLINISTS WHO INSPIRED THEM

In the late nineteenth century, French composers such as Camille Saint- Saens, Cesar Franck, and Claude Debussy worked to elevate instrumental music in late-Romantic period France, creating symphonies, concertos, and chamber ensembles, including duo sonatas. These composers and followers like, Ernest Chausson and Guillaume Lekeu were all influenced by a particular violinist to whom they dedicated their compositions. The primary violinist who inspired these composers was Eugene Ysaye (1858-1931), a brilliant performer and composer. His freedom of expression motivated many prominent French composers to dedicate major works to him. For example, Debussy dedicated his string quartet to Ysaye, who established the Ysaye Quartet and premiered Debussy's composition. In 1886, Franck completed his sonata for violin and piano which he also dedicated to Ysaye. Fritz Kreisler (1875-1962), one of the most talented violinists of his era, had a relationship withYsaye that was quite special. They respected, supported, and befriended each other. To Ysaye, Kreisler dedicated his Recitativo and Scherzo. To Kreisler, Ysaye dedicated one ofhis celebrated Sonatas for Solo Violin. Pablo de Sarasate (1844-1908) was a magnificent Spanish violinist of the late nineteenth century, and his music and performances influenced many composers, especially Saint-Saens, who included Spanish gypsy fragments in his works. These motifs may found in his Havanaise, Introduction and Rondo Capriccioso and Violin Concerto No.3 which were dedicated to Sarasate. My goal for this dissertation project has been to find and present, in three recitals, works by French composers and also works by the violinists who inspired them. As a violinist, I have endeavored to understand the influence of the various violinists on these French composers and how that knowledge can inform my approach to performing these works. In my first recital, with pianist Soo Young Jung, I performed works by Saint-Saens, Ysaye and Sarasate. With pianist Sun Ha Yoon, I performed works by Ysaye, Debussy, Kreisler and Franck in my second recital. My third recital, again with pianist Sun Ha Yoon, featured works by Ysaye, Chausson, and Lekeu. All recitals were recorded and performed at the University ofMaryland, College Park.

Context Models for Understanding Images and Videos

A computer vision system that has to interact in natural language needs to understand the visual appearance of interactions between objects along with the appearance of objects themselves. Relationships between objects are frequently mentioned in queries of tasks like semantic image retrieval, image captioning, visual question answering and natural language object detection. Hence, it is essential to model context between objects for solving these tasks. In the first part of this thesis, we present a technique for detecting an object mentioned in a natural language query. Specifically, we work with referring expressions which are sentences that identify a particular object instance in an image. In many referring expressions, an object is described in relation to another object using prepositions, comparative adjectives, action verbs etc. Our proposed technique can identify both the referred object and the context object mentioned in such expressions. Context is also useful for incrementally understanding scenes and videos. In the second part of this thesis, we propose techniques for searching for objects in an image and events in a video. Our proposed incremental algorithms use the context from previously explored regions to prioritize the regions to explore next. The advantage of incremental understanding is restricting the amount of computation time and/or resources spent for various detection tasks. Our first proposed technique shows how to learn context in indoor scenes in an implicit manner and use it for searching for objects. The second technique shows how explicitly written context rules of one-on-one basketball can be used to sequentially detect events in a game.

Flooded with Information from Social Media: Effects of Disaster Information Source and Visuals on Viewers' Cognitive, Affective, and Behavioral Responses

While a variety of crisis types loom as real risks for organizations and communities, and the media landscape continues to evolve, research is needed to help explain and predict how people respond to various kinds of crisis and disaster information. For example, despite the rising prevalence of digital and mobile media centered on still and moving visuals, and stark increases in Americans’ use of visual-based platforms for seeking and sharing disaster information, relatively little is known about how the presence or absence of disaster visuals online might prompt or deter resilience-related feelings, thoughts, and/or behaviors. Yet, with such insights, governmental and other organizational entities as well as communities themselves may best help individuals and communities prepare for, cope with, and recover from adverse events. Thus, this work uses the theoretical lens of the social-mediated crisis communication model (SMCC) coupled with the limited capacity model of motivated mediated message processing (LC4MP) to explore effects of disaster information source and visuals on viewers’ resilience-related responses to an extreme flooding scenario. Results from two experiments are reported. First a preliminary 2 (disaster information source: organization/US National Weather Service vs. news media/USA Today) x 2 (disaster visuals: no visual podcast vs. moving visual video) factorial between-subjects online experiment with a convenience sample of university students probes effects of crisis source and visuals on a variety of cognitive, affective, and behavioral outcomes. A second between-subjects online experiment manipulating still and moving visual pace in online videos (no visual vs. still, slow-pace visual vs. still, medium-pace visual vs. still, fast-pace visual vs. moving, slow-pace visual vs. moving, medium-pace visual vs. moving, fast-pace visual) with a convenience sample recruited from Amazon’s Mechanical Turk (mTurk) similarly probes a variety of potentially resilience-related cognitive, affective, and behavioral outcomes. The role of biological sex as a quasi-experimental variable is also investigated in both studies. Various implications for community resilience and recommendations for risk and disaster communicators are explored. Implications for theory building and future research are also examined. Resulting modifications of the SMCC model (i.e., removing “message strategy” and adding the new category of “message content elements” under organizational considerations) are proposed.