The Role of Arts in the Process of Leadership Formation and Ecclesial Transformation

This dissertation investigates how the arts can be instrumental in the process of leadership formation and church transformation. By synthesizing results of an evaluation survey with a holistic-inductive design of inquiry, this dissertation demonstrates that the arts, as expressions of faith, can be transformative. By presenting the arts program at the Old West Church in Boston, which integrates arts as a medium for the expression of the Christian faith, this dissertation provides biblical, theological, and practical frameworks for reflecting on the transformative character of arts in the process of leadership formation and church transformation.

Practices of Ministerial Leadership of Korean-American United Methodist Clergywomen; Toward a Wesleyan Ecclesiology in a Global Context

This study documents, analyzes, and interprets Korean American United Methodist (KAUM) clergywomen‘s experiences in and understandings of the church. It examines contributions these (and potentially, other) clergywomen might make to Wesleyan ecclesiology generally, and particular ways United Methodists live out their faith in transitional, diverse, and global contexts. The project attempts to re-vision existing Wesleyan ecclesial discourse in the United Methodist Church (UMC) by recognizing and incorporating the contributions of racial-ethnic clergy as expressed through their leadership and practices of faith. A "practice-theory-practice" model of practical theology was used to pay systematic attention to the practical locus of the inquiries. Twenty Korean American United Methodist clergywomen were interviewed by telephone, using a voluntary sampling technique to ascertain how they both experienced the church and understood and lived out various practices of faith, including preaching, participation in and administration of the sacraments, preparation for ordained ministry, and other spiritual practices such as prayer, worship, retreats, and journaling. The dissertation summarizes those findings, provides contextual and historical interpretation, and then analyzes their responses in relation to Wesleyan theology, MinJung (mass of people) theology, and the theology of YeoSung (women who display dignity and honor as human beings). This study identifies the extraordinary call of the KAUM clergywomen interviewees to be bridge builders, strong nurturers, wounded healers, committed educators, breakers of old stereotypes, persistent seekers to fulfill God‘s call, and ecclesial leaders with ―tragic consciousness‖ who can disrupt marginality and facilitate the creative transformation of Han (a deep experience of suffering and oppression) into a constructive energy capable of shaping a new reality. According to this study, KAUM clergywomen‘s experiences and practices of faith as ecclesial leaders strengthen Wesleyan ecclesiology in terms of the UMC‘s efforts to be an inclusive church through connectionalism, and its commitment to social justice. MinJung theology and the theology of YeoSung, in their respective understandings of the church, broaden Wesleyan ecclesiology and enable the Church to be more relevant in a global context by embracing those who have not been normative theological subjects.

3D Hand Pose Estimation by Finding Appearance-Based Matches in a Large Database of Training Views

Ongoing work towards appearance-based 3D hand pose estimation from a single image is presented. A large database of synthetic hand views is generated using a 3D hand model and computer graphics. The views display different hand shapes as seen from arbitrary viewpoints. Each synthetic view is automatically labeled with parameters describing its hand shape and viewing parameters. Given an input image, the system retrieves the most similar database views, and uses the shape and viewing parameters of those views as candidate estimates for the parameters of the input image. Preliminary results are presented, in which appearance-based similarity is defined in terms of the chamfer distance between edge images.

Eliminating Redundant Training Data Using Unsupervised Clustering Techniques

Training data for supervised learning neural networks can be clustered such that the input/output pairs in each cluster are redundant. Redundant training data can adversely affect training time. In this paper we apply two clustering algorithms, ART2 -A and the Generalized Equality Classifier, to identify training data clusters and thus reduce the training data and training time. The approach is demonstrated for a high dimensional nonlinear continuous time mapping. The demonstration shows six-fold decrease in training time at little or no loss of accuracy in the handling of evaluation data.