Behind, Between, and Beyond Anthropomorphic Models

The plurality of models of ultimate reality is a central problem for religious philosophy. This essay sketches what is involved in mounting comparative inquiries across the plurality of models. In order to illustrate what advance would look like in such a comparative inquiry, an argument is presented to show that highly anthropomorphic models of ultimate reality are inferior to a number of competitors. This paper was delivered as a keynote address during the APA Pacific 2007 Mini-Conference on Models of God

Recent developments towards optimality in multiple hypothesis testing

There are many different notions of optimality even in testing a single hypothesis. In the multiple testing area, the number of possibilities is very much greater. The paper first will describe multiplicity issues that arise in tests involving a single parameter, and will describe a new optimality result in that context. Although the example given is of minimal practical importance, it illustrates the crucial dependence of optimality on the precise specification of the testing problem. The paper then will discuss the types of expanded optimality criteria that are being considered when hypotheses involve multiple parameters, will note a few new optimality results, and will give selected theoretical references relevant to optimality considerations under these expanded criteria.Comment: Published at http://dx.doi.org/10.1214/074921706000000374 in the IMS Lecture Notes--Monograph Series (http://www.imstat.org/publications/lecnotes.htm) by the Institute of Mathematical Statistics (http://www.imstat.org

Testing of mixed-signal systems using dynamic stimuli

The impulse response of a linear circuit element contains enough information to functionally characterise that element. A technique for comparison of observed and expected (reference) transient responses, which results in an absolute measure of device functionality, is presented. Comparisons of transient response test results with the results from existing test programs are also presented

Increasing discrimination in multi-criteria analysis

Multi criteria methods for supporting decision-making procedures are widely used in sustainability assessment. One of the most important steps in decision-making procedures is the evaluation of policy options or alternatives in order to find a hierarchy of option choices. Utility function value distributions are often constructed for the range of indicators for the options to be assessed. This distribution can be presented as an impact matrix stacked with indicator weights to reflect the relative importance of different indicators for the decision-maker. Solving rules are then introduced to integrate all individual indicator evaluations into a single integral utility estimation. These are often based on the averaging procedures, one of the simplest being arithmetic averaging. Whilst averaging rules are very attractive to decision makers due to their simplicity and logical transparency, using averaging as the first step of the decision-making procedures can significantly reduce the discrimination of the options, especially if there are counteractive individual indicator estimations.This paper proposes a method to evaluate and overcome this loss of discrimination. The paper explains the basis of a discriminatory analysis approach to sustainability assessment demonstrates its application through the use of illustrative data and describes its application to an existing case study where researchers had applied a number of multi criteria analysis tools. It was concluded that the discriminatory analysis provided a useful addition to the decision-makers toolbox as it provided a means of assessment of the validity of the application of the simple arithmetic averaging technique

Finding the way forward for forensic science in the US:a commentary on the PCAST report

A recent report by the US President’s Council of Advisors on Science and Technology (PCAST) [1] has made a number of recommendations for the future development of forensic science. Whereas we all agree that there is much need for change, we find that the PCAST report recommendations are founded on serious misunderstandings. We explain the traditional forensic paradigms of match and identification and the more recent foundation of the logical approach to evidence evaluation. This forms the groundwork for exposing many sources of confusion in the PCAST report. We explain how the notion of treating the scientist as a black box and the assignment of evidential weight through error rates is overly restrictive and misconceived. Our own view sees inferential logic, the development of calibrated knowledge and understanding of scientists as the core of the advance of the profession