Thesis (M.A.) -- University of Texas at Arlington, 2008.

Thesis (M.S. in Operations Research)--Naval Postgraduate School, September 2003. / Thesis advisor(s): Susan M. Sanchez, Niki Goerger, Lloyd Brown. Includes bibliographical references (p. 141-143). Also available online.

Thesis (Ph. D.)--University of North Texas, Dec., 2009. / Title from title page display. Includes bibliographical references.

Thesis (M.S. in Information Technology Management)--Naval Postgraduate School, 2005. / Title from title screen (viewed Nov. 8, 2005). "September 2005." Includes bibliographical references (p. 63-66). Also issued in paper format.

Thesis (M.M.A.S.) -- U.S. Army Command and General Staff College, 2009. / "AD-A512 377." Includes bibliographical references.

Thesis (M.A. in Security Studies (Homeland Security and Defense))--Naval Postgraduate School, March 2007. / Thesis Advisor(s): David Tucker. "March 2007." Includes bibliographical references (p. 115-125). Also available in print.

<p> </p> <p>A search and rescue (SAR) operation requires a rapid, accurate, and effective response to provide the missing person the best chance of being rescued. Personnel from the local area are likely to be closest to the location of the missing person, be familiar with the area, but they may not be adequately trained, experienced, or equipped with the best tools to effectively locate, identify, and retrieve the missing person. Thus, most SAR operations rely on a mix of trained personnel and volunteers. Among the trained personnel, there is a wide variance in proficiency, experience, and access to technology, leading to some emergency response agencies being better prepared than others. Volunteers, on the other hand, could be very helpful, but are largely untrained and inexperienced, reducing their inherent likelihood of success. The primary challenge to successful SAR operations is the lack of consistently trained, adequately equipped, and diversely experienced personnel. Despite the lack of desired resources, SAR operations must be completed rapidly and emergency responders often turn to volunteers. In response to this challenge, the use of unmanned aerial systems, UAS, in small volunteer teams was proposed. Available, off-the-shelf UAS technology can be used to simplify training with the help of affordable advanced technology, and thereby enable rapid, accurate, and effective SAR operations.  </p> <p>The following research was executed in the form of three independent, but related, studies. The first study focused on the efficiency of a UAS-equipped SAR operation; the second study focused on the accuracy of a UAS and image analysis software-enabled SAR operation; and the third study tested the ability of novice volunteers to learn and apply the new technologies (UAS plus image analysis) efficiently and effectively. The goal of these studies was to determine whether affordable commercial, off-the-shelf technologies could be used to enhance the efficiency and effectivity of SAR operations. The experimental methodology used specifically designed simulations of SAR operational scenarios. Two operational tactics were tested: (a) Equip the SAR team with UAS and (b) equip the SAR team with UAS and image analysis software. The specific scenarios selected were similar in complexity, but different enough to minimize the transfer of learning from the first study to the second study.  Finally, the reference times for manual SAR operations were compared against UAS and computerized image analysis software-assisted methods. The results of the proposed studies determined whether off-the-shelf UAS and image analysis technologies could be used to enable rapid, accurate, and effective SAR operations. </p>

Thesis (M.P.H.)--University of Texas Health Science Center at Houston, School of Public Health, 2008. / Source: Masters Abstracts International, Volume: 46-05, page: 2641. Advisers: Arnold J. Schecter; Bahman S. Roudsari. Includes bibliographical references.

Thesis (MMAS)--Command and General Staff College (CGSC), 2006. / AD-A452 186.

To a large extent, natural phenomenon like earthquakes, floods, lanslides and etc may seem &ldquo / natural events&rdquo / which are out of human control. In fact, the sociopolitical structure is the main cause of earth tremors which turn into disasters. What is notable and striking is that, because of institutional and social vulnerabilities and little or misguided efforts for disaster loss mitigation, natural events may turn into disasters resulting negative and devastating consequences. Institutional vulnerabilities connote a lack of local administrations&rsquo / capacity for disaster mitigation planning, furthermore awareness for accreting local stakeholders for disaster loss reduction. Social vulnerabilities, refers to miss-knowledge and lack of awareness for disasters in the society. In Turkey, it is hard to say that there has never been efforts for disaster loss reduction, whereas / the main focus of the state agencies has been on post-disaster emergency relief, literally wound healing for decades. Generally speaking, localities which experience a disaster may encounter significant losses in development, hence a significant decrease in local capacities which takes enormous resources to restore. The housing stock and urban fabric, which inherit an historical background weaved by missguided disaster policy that only focus on post-disaster emergency relief phase, pictures the extent of the problem in Turkey. In addition, both &ldquo / institutional errors which lead to underachievement in disaster policy and practice&rdquo / and &ldquo / opportunities for building robust and resilient forms of institutions&rdquo / come into local agenda. Errors, which might have been altered by long term and comprehensive modes of local planning for disasters, may lead to underachievement by local agents. To achieve such a model, we are in need to carry out qualitative and quantitative data collecting and analyzing techniques in different phases. The two analysis techniques are in-depth interviews (IDI) and drawing Concept Maps that will be conducted in the analyses process with local respondents selected by snowball technique.