With devastating natural disasters on the rise, technological improvements are needed in the field of search and rescue (SAR). Unmanned aerial vehicles (UAVs) would be ideal for the search function such that manned vehicles can be prioritized to distributing first-aid and ultimately saving lives. One of the major reasons that UAVs are under utilized in SAR is that they lack a long flight endurance which compromises their effectiveness. Dirigibles are well suited for SAR missions since they can hover and maintain lift without consuming energy and can be easily deflated for packaging and transportation. This research focuses on extending flight endurance of small-scale airship UAVs through improvements to the infrastructure design and flight trajectory planning. In the first area, airship design methodologies are reviewed leading to the development and experimental testing two hybrid fuel-electric power plants. The prevailing hybrid power plant design consists of a 4-stroke 14cc gasoline engine in-line with a brushless DC motor/generator and variable pitch propeller. The results show that this design can produce enough mechanical and electrical power to support 72 hours of flight compared to 1-4 hours typical of purely electric designs. A power plant configuration comparison method was also developed to compare its performance and endurance to other power plant configurations that could be used in dirigible UAVs. Overall, the proposed hybrid power plant has a 600% increase in energy density over that of a purely electric configuration. In the second area, a comprehensive multi-objective cost function is developed using spatially variable wind vector fields generated from computational fluid dynamic analysis on digital elevations maps. The cost function is optimized for time, energy and collision avoidance using a wavefront expansion approach to produce feasible trajectories that obey the differential constraints of the airship platform. The simulated trajectories including 1) variable vehicle velocity, 2) variable wind vector field (WVF) data, and 3) high grid resolutions were found to consume 50% less energy on average compared to planned trajectories not considering one of these three characteristics. In its entirety, this research addresses current UAV flight endurance limitations and provides a novel UAV solution to SAR surveillance.

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京都大学 / 新制・課程博士 / 博士(工学) / 甲第23505号 / 工博第4917号 / 新制||工||1768(附属図書館) / 京都大学大学院工学研究科機械理工学専攻 / (主査)教授 松野 文俊, 教授 泉田 啓, 教授 小森 雅晴 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DGAM

This thesis examines the extent to which Italy can instrumentalize international law to eschew protection responsibilities for migrants in distress at sea. In doing so, this study delimits itself by focusing on three legal cases: Aquarius, Hirsi Jamaa, and GLAN. These cases are analyzed against relevant international legal doctrine by means of Martti Koskenniemi’s deconstructive method, in order to explicate the political maneuvering embedded in the international legal framework. By adopting B.S. Chimni’s theory on the non-entrée regime, this thesis finds that Italy exploits the legal ambiguity in international law, in order to distance themselves from rescue and protection obligations. Conclusively, instead of creating a legal framework that is responsive to the protection needs of boat migrants, international law simultaneously enables Italy to barter off responsibility for refugees in distress at sea. Thus, this thesis contributes with a critical perspective to international law related to migrants in distress at sea.

Natural and manmade disasters have brought urban search and rescue (USAR) robots to the technology forefront as a means of providing additional support for search and rescue workers. The loss of life among victims and rescue workers necessitates the need for a wider acceptance of this assistive technology. Disasters, such as hurricane Harvey in 2017, hurricane Sandy in 2012, the 2012 United States tornadoes that devastated 17 states, the 2011 Australian floods, the 2011 Japan and 2010 Haiti earthquakes, the 2010 West Virginia coal mine explosions, the 2009 Typhoon caused mudslides in Taiwan, the 2001 Collapse of the World Trade Center, the 2005 Hurricane Katrina, the 1995 Oklahoma City bombing, and the 1995 Kobe Japan earthquake all benefited from the use of USAR. While there has been a push for use of USAR for disaster, user resistance to such technology is still significantly understudied. This study applied a mixed quantitative and qualitative approach to identify important system characteristics and critical value factors (CVFs) that contribute to team members’ resistance to use such technology. The populations for this study included 2,500 USAR team members from the Houston Professional Fire Fighters Association (HPFFA), and the expected sample size of approximately 250 respondents. The main goal of this quantitative study was to examine system characteristics and CVFs that contribute to USAR team members’ resistance to use such technology. System characteristics and CVFs are associated with USAR. Furthermore, the study utilized multivariate linear regression (MLR) and multivariate analysis of covariance (ANCOVA) to determine if, and to what extent, CVFs and computer self-efficacy (CSE) interact to influence USAR team members’ resistance to use such technology. This quantitative study will test for significant differences on CVF’s, CSE, and resistance to use such technology based on age, gender, prior experience with USAR events, years of USAR experience, and organizational role. The contribution of this study was to reduce USAR team members’ resistance to use such technology in an effort minimize risk to USAR team members while maintaining their lifesaving capability.

In the latest years, European governments have increasingly criminalized providing support to displaced people. Humanitarian non-governmental organizations (NGO) carrying out life-saving search and rescue (SAR) activities in the Mediterranean Sea have been facing wide obstacles in aiding newcomers, and in many instances have been subject to criminal proceedings. This research attempts to analyse the reasons why maritime sea rescue is equated with illegality. In doing so, it seeks to answer the question, “what are the challenges to reaching legal protection for humanitarian aid workers carrying out search and rescue operations in the Mediterranean when faced with criminalization?” The study argues that humanitarian aid workers (HAW) who have been criminalized as a result of their involvement in maritime sea rescue activities, have to endure many systemic deficiencies. Three layers of interrelated challenges are identified: legal, socio-political, and personal challenges. The study concludes that an independent, quality legal defence; a revisitation of the voluntary nature of the humanitarian exemption clause in the 2002 Facilitation Package; and a larger engagement of civil society actors in changing the narrative and improving the public’s practical knowledge of migration would ensure better protection for humanitarian practitioners involved in search and rescue activities. / <p>It was online.</p>

Aircraft-mounted cameras have potential to greatly increase the effectiveness of wilderness search and rescue efforts by collecting photographs or video of the search area. The more data that is collected, the more difficult it becomes to process it by visual inspection alone. This work presents a method for automatically detecting unusual objects in aerial video to assist people in locating signs of missing persons in wilderness areas. The detector presented here makes use of anomaly detection methods originally designed for hyperspectral imagery. Multiple anomaly detection methods are considered, implemented, and evaluated. These anomalies are then aggregated into spatiotemporal objects by using the video's inherent spatial and temporal redundancy. The results are therefore summarized into a list of unusual objects to enhance the search technician's video review interface. In the user study reported here, unusual objects found by the detector were overlaid on the video during review. This increased participants' ability to find relevant objects in a simulated search without significantly affecting the rate of false detection. Other effects and possible ways to improve the user interface are also discussed.

Every year there are numerous cases of individuals becoming lost in remote wilderness environments. Principles of search theory have become a foundation for developing more efficient and successful search and rescue methods. Measurements can be taken that describe how easily a search object is to detect. These estimates allow the calculation of the probability of detection—the probability that an object would have been detected if in the area. This value only provides information about the search area as a whole; it does not provide details about which portions were searched more thoroughly than others. Ground searchers often carry portable GPS devices and their resulting GPS track logs have recently been used to fill in part of this knowledge gap. We created a system that provides a detection likelihood map that estimates the probability that each point in a search area was seen well enough to detect the search object if it was there. This map will be used to aid ground searchers as they search an assigned area, providing real time feedback of what has been "seen." The maps will also assist incident commanders as they assess previous searches and plan future ones by providing more detail than is available by viewing GPS track logs.

In mid-2015 the European Union changed its response to the increase of migrants crossing the Mediterranean Sea from humanitarian to securitization and deterrence. In 2017 this became visible in the criminalization of search and rescue (SAR) organizations, which had an impact and both intended and unintended consequences. This study focuses on the impact of criminalization on the management of search and rescue NGOs in the Central Mediterranean Sea since 2017 by analysing changes in their recruitment, training and general management, their decision-making process when faced with (the risk of) criminalization and criminalization’s impact on their ability to fulfil their mission. This is done through analysing literature and conducting semi-structured interviews with four people who are active in SAR organizations affected by (the risk of) criminalization. This study finds that it is not generally known that authorities have changed strategies of criminalization. The previous more open form of criminalization partly strengthened one of the organizations as members became more resolute in their commitment to their mission and public support and donations increased by those who opposed the authorities’ strategy. The current strategy consists of mainly administrative hurdles, which are less visible but more difficult to manage for organizations.  Recruitment was impacted as there are fewer potential candidates and vetting increased. Trainings changed to give crew members additional information and enable them to obtain required licenses. In general management more sustainable structures were created for resilience to criminalization. In the decision-making process when faced with (the risk of) criminalization the organizations aim to be democratic, which makes the process more time-consuming and prone to internal conflict. The organizations’ ability to fulfil their missions was impacted by the negative influence of the media on their public image and needing to use resources for legal defence instead of SAR operations. There are currently less frequent SAR operations and it is increasingly difficult for small organizations to run their own ship.

There is a tremendous volume of data being generated in today’s world. As organizations around the globe realize the increased importance of their data as being a valuable asset in gaining a competitive edge in a fast-paced and a dynamic business world, more and more attention is being paid to the quality of the data. Advances in the fields of data mining, predictive modeling, text mining, web mining, business intelligence, health care analytics, etc. all depend on clean, accurate data. That one cannot effectively mine data, which is dirty, comes as no surprise. This research is an exploratory study of different domain data sets, addressing the data quality issues specific to each domain, identifying the challenges faced and arriving at techniques or methodologies for measuring and improving the data quality. The primary focus of the research is on the SAR or Search and Rescue dataset, identifying key issues related to data quality therein and developing an algorithm for improving the data quality. SAR missions which are routinely conducted all over the world show a trend of increasing mission costs. Retrospective studies of historic SAR data not only allow for a detailed analysis and understanding of SAR incidents and patterns, but also form the basis for generating probability maps, analytical data models, etc., which allow for an efficient use of valuable SAR resources and their distribution. One of the challenges with regards to the SAR dataset is that the collection process is not perfect. Often, the LKP or the Last Known Position is not known or cannot be arrived at. The goal is to fully or partially geocode the LKP for as many data points as possible, identify those data points where the LKP cannot be geocoded at all, and further highlight the underlying data quality issues. The SAR Algorithm has been developed, which makes use of partial or incomplete information, cleans and validates the data, and further extracts address information from relevant fields to successfully geocode the data. The algorithm improves the geocoding accuracy and has been validated by a set of approaches.