Indiana University-Purdue University Indianapolis (IUPUI) / Research on military families has increased since the beginning of the wars in Afghanistan and Iraq; however, the research focuses on military families is general with little specific information on Black families within the military. Given the known general impact of race, this is a critical gap in the research into military families. This qualitative descriptive study explores the life of Black daughters in military families by examining the challenges and benefits of growing up as a Black daughter in a military family. There were three primary research questions asked of the participants about their experiences: 1) What challenges did you experience growing up in a military family; 2) What benefits did you experience growing up in a military family; and, 3) Do you believe that being Black affected the challenges and benefits you experienced? If so, in what way(s)? The participants also answered two additional questions of importance to social workers and health practitioners who work with military families: 1) What advice would you give to social workers who work with military families?; and, 2) What advice would you have for the military to help families address the challenges you have mentioned? The answers to the primary research questions are reviewed through the Multidimensional Model of Racial Identity (MMRI), models of systems theory, mettle, adaptability, and transformability. Consideration of the “Strong Black Woman” perspective is also examined. A look at the roles that women play as well as roles imposed on women by others is explored. Implications for social workers, health practitioners, and schools of social work are discussed, inclusive of military family culture and the importance of cultural competence in considering the intersections of a person’s life: racial identity in addition to military implications. / 2021-10-02

京都大学 / 0048 / 新制・課程博士 / 博士(理学) / 甲第17771号 / 理博第3894号 / 新制||理||1562(附属図書館) / 30578 / 京都大学大学院理学研究科化学専攻 / (主査)教授 谷村 吉隆, 准教授 安藤 耕司, 教授 寺嶋 正秀 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DGAM

We focus on multi-dimensional classification (MDC) problems with conditional dependence, which we call multiple output dependence (MOD) problems. MDC is the task of predicting a vector of categorical outputs for each input. Conditional dependence in MDC means that the choice for one output value affects the choice for others, so it is not desirable to predict outputs independently. We show that conditional dependence in MDC implies that a single input can map to multiple correct output vectors. This means it is desirable to find multiple correct output vectors per input. Current solutions for MOD problems are not sufficient because they predict only one of the correct output vectors per input, ignoring all others.We modify four existing MDC solutions, including chain classifiers, to predict multiple output vectors. We further create a novel ensemble technique named weighted output vector ensemble (WOVE) which combines these multiple predictions from multiple chain classifiers in a way that preserves the integrity of output vectors and thus preserves conditional dependence among outputs. We verify the effectiveness of WOVE by comparing it against 7 other solutions on a variety of data sets and find that it shows significant gains over existing methods.

The three major optical character recognition (OCR) engines (ExperVision, Scansoft OCR, and Abby OCR) in use today are all capable of recognizing text at near perfect percentages. The remaining errors however have proven very difficult to identify within a single engine. Recent research has shown that a comparison between the errors of the three engines proved to have very little correlation, and thus, when used in conjunction, may be useful to increase accuracy of the final result. This document discusses the implementation and results of a simple voting system designed to prove the hypothesis and show a statistical improvement in overall accuracy. Additional aspects of implementing an improved OCR scheme such as dealing with multiple engine data output alignment and recognizing application specific solutions are also addressed in this research. Although voting systems are currently in use by many major OCR engine developers, this research focuses on the addition of a collaborative system which is able to utilize the various positive aspects of multiple engines while also addressing the immediate need for practical industry applications such as litigation and forms processing. Doculex TM, a major developer and leader in the document imaging industry, has provided the funding for this research.

This dissertation introduces new heuristic methods for the 0-1 multi-dimensional knapsack problem (0-1 MKP). 0-1 MKP can be informally stated as the problem of packing items into a knapsack while staying within the limits of different constraints (dimensions). Each item has a profit level assigned to it. They can be, for instance, the maximum weight that can be carried, the maximum available volume, or the maximum amount that can be afforded for the items. One main assumption is that we have only one item of each type, hence the problem is binary (0-1). The single dimensional version of the 0-1 MKP is the uni-dimensional single knapsack problem which can be solved in pseudo-polynomial time. However the 0-1 MKP is a strongly NP-Hard problem. Reduced cost values are rarely used resources in 0-1 MKP heuristics; using reduced cost information we introduce several new heuristics and also some improvements to past heuristics. We introduce two new ordering strategies, decision variable importance (DVI) and reduced cost based ordering (RCBO). We also introduce a new greedy heuristic concept which we call the "sliding concept" and a sub-branch of the "sliding concept" which we call "sliding enumeration". We again use the reduced cost values within the sliding enumeration heuristic. RCBO is a brand new ordering strategy which proved useful in several methods such as improving Pirkul's MKHEUR, a triangular distribution based probabilistic approach, and our own sliding enumeration. We show how Pirkul's shadow price based ordering strategy fails to order the partial variables. We present a possible fix to this problem since there tends to be a high number of partial variables in hard problems. Therefore, this insight will help future researchers solve hard problems with more success. Even though sliding enumeration is a trivial method it found optima in less than a few seconds for most of our problems. We present different levels of sliding enumeration and discuss potential improvements to the method. Finally, we also show that in meta-heuristic approaches such as Drexl's simulated annealing where random numbers are abundantly used, it would be better to use better designed probability distributions instead of random numbers.

This qualitative research aims to understand better how the multi-dimensional autonomy facilitated by social media activism influenced the dynamics of the Arab Spring, with a particular focus on the Egyptian Revolution of 2011. Based on semi-structured interviews with earlier Egyptian activists, social media significantly provided individuals with platforms to express their opinions more freely, engage in dialogue, and foster a sense of solidarity and empowerment, which enhanced their feeling of autonomy. Moreover, social media provided safe spaces and fostered a sense of unity and collective strength among activists. On the other side, activists faced challenges related to misinformation and censorship, which has affected interviewees’ individual autonomy negatively. This research also highlights the concept of liberty as non-domination and the need for individuals to be free from arbitrary control or interference by others, allowing them to act autonomously. Based on the interviews, the activists faced various forms of domination and control, such as government surveillance and harassment, which limited the extent to which social media could provide a platform for liberty as non-domination. However, the activists demonstrated resilience and adaptability in these challenges.

京都大学 / 新制・課程博士 / 博士(理学) / 甲第24436号 / 理博第4935号 / 新制||理||1705(附属図書館) / 京都大学大学院理学研究科化学専攻 / (主査)教授 北川 宏, 教授 有賀 哲也, 教授 吉村 一良 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DGAM

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