This article investigates the detection and identification problems for changing of regimes about non-linear time series process. We apply the concept of genetic algorithm and AIC criterion to test the changing of regimes. This way is different from traditional detection methods According to our statistical decision procedure, the mean of moving average and the genetic detection for the underlying time series will be considered to decide change points. Finally, an empirical application about the detection and identification of change points for the Taiwan Business Cycle is illustrated.

The zebrafish is rapidly becoming a vital tool in studies of genetic disease. Use of the zebrafish embryo as an experimental model combines the efficiency of techniques specific to invertebrates with the human applicability of vertebrate studies, along with a number of other advantages such as optical transparency and high spawn number. Sequencing maps and mutant screen data are available, and gene ontology annotation is progressing. Furthermore, a number of highly important projects are underway to expand the utility of the zebrafish still further (eg. Mutant screens and TILLING projects; see (Lieschke and Currie, 2007) for review). As such the zebrafish has become a vital model organism for study of a variety of genetic defects, toxicology and pharmacological screens etc. These papers trace the development of zebrafish embryos as a model organism for both genetic disease and, as part of this, the development of a relatively high throughput approach to analysing relative levels of apoptosis. The first paper describes the fmr1 gene family in zebrafish (fmr1, and its orthologs fxr1 and fxr2). This paper includes a phylogenetic analysis of the gene family that demonstrates the high conservation between human and zebrafish, in the context of Drosophila. We then describe expression of the genes in the embryo (using in situ hybridisation) and adult (using real time pcr). The conclusions are that the zebrafish is an appropriate model in which to study Fragile X Mental Retardation genetic disease. The second paper builds upon this conclusion and further establishes the appropriateness of the model by recapitulating elements of the disease that had already been modelled in other model organisms. The research is validated using a number of controls. We describe a number of original findings that extended the body of knowledge regarding pharmacological rescue of the FMRP loss phenotypes. A craniofacial phenotype is identified, the first such discovery in a model of Fragile X syndrome. These findings are a vital step toward understanding the pathway from gene, to molecular phenotype, to cellular morphology, to gross morphology. As part of these studies, we found it necessary to analyse apoptosis. The technique developed to facilitate this analysis is described in our third paper. Given the highly stochastic nature of the apoptotic patterns we developed a method to take full advantage of the characteristics of zebrafish embryos, primarily their transparency and availability in large numbers. As the zebrafish becomes more widely accepted as a model for a diverse range of scientific questions, the development of such a technique is doubly important given the necessity of a cheap, reliable and simple generalizable method of analysing processes affecting cell viability in fish. This has clear importance for pharmacological studies, but is also a long overdue addition to the battery of controls available for highly invasive techniques such as microinjection, in which apoptosis is regularly found among its non specific effects. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1311173 / Thesis (Ph.D.) -- University of Adelaide, School of Molecular and Biomedical Science, 2008

This research applies the biologically inspired, artificial evolutionary processes of Genetic Algorithms and Genetic Programming to digital hardware circuit synthesis and minimization. In this new application, three approaches are taken to genetic hardware development. First, as a method for logic synthesis, Genetic Programming is applied to the building of logic functions. Experimental results have shown the logic equations from this technique produce better than 88% coverage of the given truth-tables, but the method cannot guarantee complete (100%) coverage. Secondly, to better achieve complete function coverage, an XOR Correction Circuit Algorithm used in conjunction with the Genetic Logic Synthesis was developed. With this algorithm, the genetic logic synthesis can reiteratively attempt coverage by formulating its own selective "correction" functions, for input combinations where complete truth table coverage has not previously been achieved. With this technique, complete function coverage was synthesized in all experiments conducted. The third application of the paradigm is to the minimization of Reed-Muller Equations. In this application, a Genetic Algorithm is implemented only in the search space of all "correct", functionally equivalent equations, with only the task of finding reductions. With this limited search space the solutions have absolute guaranteed function coverage, as well as a better defined focus for the genetic evolutionary process. In both the logic synthesis and minimization processes the genetic operators determine efficient circuit implementations and reductions. The results are often different from those of human designers. Because the genetic techniques incorporate logical testing into the design and build process, one can be assured that the circuit will function as derived on completion. For all three applications, the effects of a number of evolutionary parameters on the genetic operators' problem solving capability are examined. The resulting logic and logic minimizations are also compared with both arbitrarily defined functions and well known logic synthesis benchmarks. It has been shown that genetic operators applied to digital logic can effectively find good solutions for both logic synthesis and logic minimization. / Graduation date: 1997

Graduation date: 1997

Thesis (Th. M.)--Dallas Theological Seminary, 2005. / Includes bibliographical references (leaves [61-65]).

Thesis (Ph. D.)--Rutgers University, 2009. / "Graduate Program in Plant Biology." Includes bibliographical references.

Thesis (Ph.D.)--Virginia Commonwealth University, 2009. / Prepared for: Dept. of Pharmacology and Toxicology. Title from title-page of electronic thesis. Bibliography: leaves 266-287.

Thesis (Ph. D.)--University of Chicago, Dept. of Ecology and Evolution, August 2001. / Includes bibliographical references. Also available on the Internet.

Thesis (doctoral). / At head ot title: Pontificia Universitas Santae Crucis, Facultas philosophiae." Includes bibliographical references (p. 477-510).

Research Project (M.B.A.) - Simon Fraser University, 2007. / Theses (Faculty of Business Administration) / Simon Fraser University. Senior supervisor: Dr. Aidan Vining -- Faculty of Business Administration. MBA-MOT Program. Also issued in digital format and available on the World Wide Web.