Szu-Feng Chen, Assistant Professor, Department of Theatre and Dance, travels to Singapore

Professor Szu-Feng Chen was invited by The Theatre Practice (TTP) in Singapore to create set and costume design for Lao Jiu: The Musical, its feature musical production for the Singapore Kuo Pao Kun Festival.I was invited by The Theatre Practice (TTP) in Singapore to create set and costume design for its feature musical production for Singapore Kuo Pao Kun Festival. Lao Jiu: The Musical, is a musical version of Kuo’s signature play. It was opened in July 2012 in memory of ten years of Kuo Pao Kun’s passing. Kuo Pao Kun was the pioneer and art educator of Singaporean theatre—awarded the National Culture Medallion in 1989, the Culture Award in 1992, Asean Cultural Award in 1993and the Excellence for Singapore Award in 2002. The festival is hosted by The Theatre Practice and supported by Singapore National Arts Council in honor of Kuo’s contribution to the Singapore performing arts

Beardsley on literature, fiction, and nonfiction

This paper attempts to revive interest in the speech act theory of literature by looking into Monroe C. Beardsley's account in particular. Beardsley's view in this respect has received, surprisingly, less attention than deserved. I first offer a reconstruction of Beardsley's account and then use it to correct some notable misconceptions. Next, I show that the reformulation reveals a hitherto unnoticed discrepancy in Beardsley's position and that this can be explained away by a weak version of intentionalism that Beardsley himself actually tolerates. Finally, I assess the real difficulty of Beardsley's theory and its relevance today

Optimal Curvature Decays on Asymptotically Locally Euclidean Manifolds

We present a method in nonlinear elliptic systems to study curvature decays on asymptotically locally Euclidean (ALE) manifolds. In particular, we show that scalar flat Kahler and harmonic ALE metrics of real dimension n are of order n-2.Comment: 28 page

Adaptive pattern recognition by mini-max neural networks as a part of an intelligent processor

In this decade and progressing into 21st Century, NASA will have missions including Space Station and the Earth related Planet Sciences. To support these missions, a high degree of sophistication in machine automation and an increasing amount of data processing throughput rate are necessary. Meeting these challenges requires intelligent machines, designed to support the necessary automations in a remote space and hazardous environment. There are two approaches to designing these intelligent machines. One of these is the knowledge-based expert system approach, namely AI. The other is a non-rule approach based on parallel and distributed computing for adaptive fault-tolerances, namely Neural or Natural Intelligence (NI). The union of AI and NI is the solution to the problem stated above. The NI segment of this unit extracts features automatically by applying Cauchy simulated annealing to a mini-max cost energy function. The feature discovered by NI can then be passed to the AI system for future processing, and vice versa. This passing increases reliability, for AI can follow the NI formulated algorithm exactly, and can provide the context knowledge base as the constraints of neurocomputing. The mini-max cost function that solves the unknown feature can furthermore give us a top-down architectural design of neural networks by means of Taylor series expansion of the cost function. A typical mini-max cost function consists of the sample variance of each class in the numerator, and separation of the center of each class in the denominator. Thus, when the total cost energy is minimized, the conflicting goals of intraclass clustering and interclass segregation are achieved simultaneously