This paper includes a 62-page book of original poems, 19 pages of which are visual poetry, and a 29-page preface which discusses visual poetry.

The subject of this paper is old--so old that to some it is new again. In simpler days young people learned everything except the formal mechanics of education from the people and places surrounding them. The prevailing type of "book learning" could best be accomplished indoors, where an errant butterfly might less successfully distract attention from the sad and solemn business of learning to read, spell, and cipher. Unfortunately, as education broadened its scope, it did not move out of its imprisoning walls and children continued to read textbooks about methods of seed distribution, while, unnoticed, milkweed parachutes set sail outside. / Typescript. / "August, 1948." / "Submitted to the Graduate Council of Florida State University in partial fulfillment of the requirements for the degree of Master of Arts." / Advisor: R. L. Eyman, Professor Directing Paper. / Includes bibliographical references (leaves 74-76).

Research into the nature and content of visual long-term memory has investigated what aspects of its representation may account for the remarkable ability we have to remember large amounts of detailed visual information. One theory proposed is that visual memories are supported by an underlying structure of conceptual knowledge around which visual information is organized. However, findings in memory for visual information learned in a visual search task were not explained by this theory of conceptual support, and a new theory is proposed that incorporates the importance of episodic, task-relevant visual information into the organizational structure of visual memory. The current study examined visual long-term memory organization as evidenced by retroactive interference effects in memory for objects learned in a visual search. Four experiments were conducted to examine the amount of retroactive interference induced based on aspects in which interfering objects were related to learned objects. Specifically, episodically task-relevant information about objects was manipulated between conditions based on search instructions. Aspects of conceptual category, perceptual information (color), and context (object role in search) were examined for their contribution to retroactive interference for learned objects. Findings indicated that when made episodically task-relevant, perceptual, as well as conceptual, information contributed to the organization of visual long-term memory. However, when made episodically non-relevant, perceptual information did not contribute to memory organization, and memory defaulted to conceptual category organization. This finding supports the theory of an episodically defined organizational structure in visual long-term memory that is overlaid upon an underlying conceptual structure.

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Indiana University-Purdue University Indianapolis (IUPUI) / You, Qian. Ph.D., Purdue University, December, 2010. Iterative Visual Analytics and its Applications in Bioinformatics. Major Professors: Shiaofen Fang and Luo Si. Visual Analytics is a new and developing field that addresses the challenges of knowledge discoveries from the massive amount of available data. It facilitates humans‘ reasoning capabilities with interactive visual interfaces for exploratory data analysis tasks, where automatic data mining methods fall short due to the lack of the pre-defined objective functions. Analyzing the large volume of data sets for biological discoveries raises similar challenges. The domain knowledge of biologists and bioinformaticians is critical in the hypothesis-driven discovery tasks. Yet developing visual analytics frameworks for bioinformatic applications is still in its infancy. In this dissertation, we propose a general visual analytics framework – Iterative Visual Analytics (IVA) – to address some of the challenges in the current research. The framework consists of three progressive steps to explore data sets with the increased complexity: Terrain Surface Multi-dimensional Data Visualization, a new multi-dimensional technique that highlights the global patterns from the profile of a large scale network. It can lead users‘ attention to characteristic regions for discovering otherwise hidden knowledge; Correlative Multi-level Terrain Surface Visualization, a new visual platform that provides the overview and boosts the major signals of the numeric correlations among nodes in interconnected networks of different contexts. It enables users to gain critical insights and perform data analytical tasks in the context of multiple correlated networks; and the Iterative Visual Refinement Model, an innovative process that treats users‘ perceptions as the objective functions, and guides the users to form the optimal hypothesis by improving the desired visual patterns. It is a formalized model for interactive explorations to converge to optimal solutions. We also showcase our approach with bio-molecular data sets and demonstrate its effectiveness in several biomarker discovery applications.

The purpose of this research was to study children's ability to recognize partially occluded images. Tasks were constructed which consisted of occluded images from video games, trademarks, and household objects. The tasks were administered to third and sixth grade students at two elementary schools in Arlington, Texas. The researcher discovered no significant differences between the scores of males and females except for the males' higher score on the video game task .

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