"Army of One" to "Army Strong" : visual media and U.S. Army recruitment during Bush"s "War on Terror"

From Bush’s September 20, 2001 “War on Terror” speech to Congress to President-Elect Barack Obama’s acceptance speech on November 4, 2008, the U.S. Army produced visual recruitment material that addressed the concerns of falling enlistment numbers—due to the prolonged and difficult war in Iraq—with quickly-evolving and compelling rhetorical appeals: from the introduction of an “Army of One” (2001) to “Army Strong” (2006); from messages focused on education and individual identity to high-energy adventure and simulated combat scenarios, distributed through everything from printed posters and music videos to first-person tactical-shooter video games. These highly polished, professional visual appeals introduced to the American public during a time of an unpopular war fought by volunteers provide rich subject matter for research and analysis. This dissertation takes a multidisciplinary approach to the visual media utilized as part of the Army’s recruitment efforts during the War on Terror, focusing on American myths—as defined by Barthes—and how these myths are both revealed and reinforced through design across media platforms. Placing each selection in its historical context, this dissertation analyzes how printed materials changed as the War on Terror continued. It examines the television ad that introduced “Army Strong” to the American public, considering how the combination of moving image, text, and music structure the message and the way we receive it. This dissertation also analyzes the video game America’s Army, focusing on how the interaction of the human player and the computer-generated player combine to enhance the persuasive qualities of the recruitment message. Each chapter discusses how the design of the particular medium facilitates engagement/interactivity of the viewer. The conclusion considers what recruitment material produced during this time period suggests about the persuasive strategies of different media and how they create distinct relationships with their spectators. It also addresses how theoretical frameworks and critical concepts used by a variety of disciplines can be combined to analyze recruitment media utilizing a Selber inspired three literacy framework (functional, critical, rhetorical) and how this framework can contribute to the multimodal classroom by allowing instructors and students to do a comparative analysis of multiple forms of visual media with similar content.

THE EFFECTS OF WEB-BASED TECHNOLOGICAL RESOURCES IN A RURAL SCIENCE CLASSROOM

Today’s technology is evolving at an exponential rate. Everyday technology is finding more inroads into our education system. This study seeks to determine if having access to technology, including iPad tablets and a teacher's physical science webpage resources (videos, PowerPoint® presentations, and audio podcasts), assists ninth grade high school students in attaining greater comprehension and improved scientific literacy. Comprehension of the science concepts was measured by comparing current student pretest and post test scores on a teacher-written assessment. The current student post test scores were compared with prior classes’ (2010-2011 and 2009-2010) to determine if there was a difference in outcomes between the technology interventions and traditional instruction. Students entered responses to a technology survey that measured intervention usage and their perception of helpfulness of each intervention. The current year class’ mean composite scores, between the pretest and post test increased by 6.9 points (32.5%). Student composite scores also demonstrated that the interventions were successful in helping a majority of students (64.7%) attain the curriculum goals. The interventions were also successful in increasing student scientific literacy by meeting all of Bloom's cognitive levels that were assessed. When compared with prior 2010-2011 and 2009-2010 classes, the current class received a higher mean post test score indicating a positive effect of the use of technological interventions. The survey showed a majority of students utilized at least some of the technology interventions and perceived them as helpful, especially the videos and PowerPoint® presentations.

Automatic Food Intake Assessment Using Camera Phones

Obesity is becoming an epidemic phenomenon in most developed countries. The fundamental cause of obesity and overweight is an energy imbalance between calories consumed and calories expended. It is essential to monitor everyday food intake for obesity prevention and management. Existing dietary assessment methods usually require manually recording and recall of food types and portions. Accuracy of the results largely relies on many uncertain factors such as user's memory, food knowledge, and portion estimations. As a result, the accuracy is often compromised. Accurate and convenient dietary assessment methods are still blank and needed in both population and research societies. In this thesis, an automatic food intake assessment method using cameras, inertial measurement units (IMUs) on smart phones was developed to help people foster a healthy life style. With this method, users use their smart phones before and after a meal to capture images or videos around the meal. The smart phone will recognize food items and calculate the volume of the food consumed and provide the results to users. The technical objective is to explore the feasibility of image based food recognition and image based volume estimation. This thesis comprises five publications that address four specific goals of this work: (1) to develop a prototype system with existing methods to review the literature methods, find their drawbacks and explore the feasibility to develop novel methods; (2) based on the prototype system, to investigate new food classification methods to improve the recognition accuracy to a field application level; (3) to design indexing methods for large-scale image database to facilitate the development of new food image recognition and retrieval algorithms; (4) to develop novel convenient and accurate food volume estimation methods using only smart phones with cameras and IMUs. A prototype system was implemented to review existing methods. Image feature detector and descriptor were developed and a nearest neighbor classifier were implemented to classify food items. A reedit card marker method was introduced for metric scale 3D reconstruction and volume calculation. To increase recognition accuracy, novel multi-view food recognition algorithms were developed to recognize regular shape food items. To further increase the accuracy and make the algorithm applicable to arbitrary food items, new food features, new classifiers were designed. The efficiency of the algorithm was increased by means of developing novel image indexing method in large-scale image database. Finally, the volume calculation was enhanced through reducing the marker and introducing IMUs. Sensor fusion technique to combine measurements from cameras and IMUs were explored to infer the metric scale of the 3D model as well as reduce noises from these sensors.