Doing Good in American Communities: Congregations and Service Organizations Working Together

A Research Report from the "Organizing Religious Work Project," Hartford Institute for Religion Research Hartford Seminary

A day of good tidings / C.B. Keenleyside, with introduction by A. Carman.

http://www.archive.org/details/adayofgoodtiding00keenuoft

"Not Without My Ancestors": A Christological Case Study of the Shona Ancestor Cult of Zimbabwe

The issue of ancestors has been controversial since the first encounters of Christianity with Shona religion. It remains a major theological problem that needs to be addressed within the mainline churches of Zimbabwe today. Instead of ignoring or dismissing the ancestor cult, which deeply influences the socio-political, religious, and economic lives of the Shona, churches in Zimbabwe should initiate a Christology that is based on it. Such a Christology would engage the critical day-to-day issues that make the Shona turn to their ancestors. Among these concerns are daily protection from misfortune, maintaining good health and increasing longevity, successful rainy seasons and food security, and responsible governance characterized by economic and political stability. Since the mid-16th century arrival of Jesuit missionaries in the Mutapa Kingdom, the Church has realized that many African Christians resorted to their ancestors in times of crisis. Although both Catholic and Protestant missionaries from the 1700s through the early 1900s fiercely attacked Shona traditional beliefs as superstitious and equated ancestors with evil spirits, the cult did not die. Social institutions, such as schools and hospitals provided by missionaries, failed to eliminate ancestral beliefs. Even in the 21st century, many Zimbabweans consult their ancestors. The Shona message to the church remains "Not without My Ancestors." This dissertation examines the significance of the ancestors to the Shona, and how selected denominations and new religious movements have interpreted and accommodated ancestral practices. Taking the missiological goal of "self-theologizing" as the framework, this dissertation proposes a "tripartite Christology" of "Jesus the Family Ancestor", "Jesus the Tribal Ancestor," and "Jesus the National Ancestor," which is based on the Shona "tripartite ancestrology." Familiar ecclesiological and liturgical language, idioms, and symbols are used to contribute to the wider Shona understanding of Jesus as the ancestor par excellence, in whom physical and spiritual needs-including those the ordinary ancestors fail to meet-are fulfilled.

How Good are Genetic Algorithms at Finding Large Cliques: An Experimental Study

This paper investigates the power of genetic algorithms at solving the MAX-CLIQUE problem. We measure the performance of a standard genetic algorithm on an elementary set of problem instances consisting of embedded cliques in random graphs. We indicate the need for improvement, and introduce a new genetic algorithm, the multi-phase annealed GA, which exhibits superior performance on the same problem set. As we scale up the problem size and test on \hard" benchmark instances, we notice a degraded performance in the algorithm caused by premature convergence to local minima. To alleviate this problem, a sequence of modi cations are implemented ranging from changes in input representation to systematic local search. The most recent version, called union GA, incorporates the features of union cross-over, greedy replacement, and diversity enhancement. It shows a marked speed-up in the number of iterations required to find a given solution, as well as some improvement in the clique size found. We discuss issues related to the SIMD implementation of the genetic algorithms on a Thinking Machines CM-5, which was necessitated by the intrinsically high time complexity (O(n3)) of the serial algorithm for computing one iteration. Our preliminary conclusions are: (1) a genetic algorithm needs to be heavily customized to work "well" for the clique problem; (2) a GA is computationally very expensive, and its use is only recommended if it is known to find larger cliques than other algorithms; (3) although our customization e ort is bringing forth continued improvements, there is no clear evidence, at this time, that a GA will have better success in circumventing local minima.

Generating Good Degree Distributions for Sparse Parity Check Codes using Oracles

Fast forward error correction codes are becoming an important component in bulk content delivery. They fit in naturally with multicast scenarios as a way to deal with losses and are now seeing use in peer to peer networks as a basis for distributing load. In particular, new irregular sparse parity check codes have been developed with provable average linear time performance, a significant improvement over previous codes. In this paper, we present a new heuristic for generating codes with similar performance based on observing a server with an oracle for client state. This heuristic is easy to implement and provides further intuition into the need for an irregular heavy tailed distribution.

Is a Detector Only Good for Detection?

A common design of an object recognition system has two steps, a detection step followed by a foreground within-class classification step. For example, consider face detection by a boosted cascade of detectors followed by face ID recognition via one-vs-all (OVA) classifiers. Another example is human detection followed by pose recognition. Although the detection step can be quite fast, the foreground within-class classification process can be slow and becomes a bottleneck. In this work, we formulate a filter-and-refine scheme, where the binary outputs of the weak classifiers in a boosted detector are used to identify a small number of candidate foreground state hypotheses quickly via Hamming distance or weighted Hamming distance. The approach is evaluated in three applications: face recognition on the FRGC V2 data set, hand shape detection and parameter estimation on a hand data set and vehicle detection and view angle estimation on a multi-view vehicle data set. On all data sets, our approach has comparable accuracy and is at least five times faster than the brute force approach.