Comparative Study of Fatigue Provisions for the AASHTO Fatigue Guide Specifications and LRFR Manual for Evaluation

The recently developed Manual for condition evaluation and load and resistance factor rating (LRFR) of highway bridges in 2003 provides an alternative procedure for practicing engineers to evaluate the fatigue life of steel bridge structures. Although the evaluation manual maintains several aspects used in the AASHTO fatigue guide specification in 1990, it also utilizes formulas and values specified in the AASHTO LRFD bridge design specifications in 1998. A comparative study of the fatigue lives provided by the procedures in the Evaluation manual and the Guide specifications was performed using a life prediction of 14 steel bridges with different structural configurations and various fatigue details. It has been shown that longer predicted fatigue lives are typically obtained when using the Evaluation manual. The ratio of the finite evaluation fatigue lives for the two procedures was found to be in a range of 0.99–2.14.     

Statistical Modeling to Forecast Odor Levels of Biosolids Applied to Reuse Sites

Proper use or disposal of wastewater solids is an important responsibility of wastewater treatment plants. At present, there are several options for wastewater solids, including agriculture, forestry, and mine reclamation reuse; production of marketable products such as compost and dried pellets; and disposal in landfills and incinerators. Land application of biosolids products is beneficial as part of recycling efforts on local farms, forests, tree farms, and mines and has gained greater acceptance of late. Coupled with these beneficial aspects are odors, which must be managed relative to the receiving populations. In this paper we present several statistical models that predict biosolids odor levels based on processing and management variables as well as ambient conditions. Such models are useful to managers at advanced wastewater treatment plants in helping them to better forecast the biosolids odors and minimize the “odor footprint,” thus making these biosolids products better received.     

Reduced autobiographical memory specificity and rumination in predicting the course of depression.

Reduced autobiographical memory (AM) specificity is a known vulnerability factor for depression. AM specificity was investigated as a predictor of depression with the Autobiographical Memory Test (J. M. G. Williams & K. Broadbent, 1986). When baseline depression scores were partialed, reduced AM specificity to negative cue words predicted higher levels of depression at 7-month follow-up. Once rumination was taken into account by means of the Rumination on Sadness Scale (M. Conway, P. A. R. Csank, S. L. Holm, & C. K. Blake, 2000), AM specificity no longer predicted depression, suggesting that the predictive value of AM specificity observed in previous studies might be--at least partly--explained as an effect of rumination. Further mediation analyses indeed revealed support for rumination as a mediator of the relation between reduced AM specificity and poor outcome of depression. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A formal relationship between program slicing and partial evaluation

A formal relationship between program slicing and partial evaluation is established. It is proved that for terminating programs, a residual program produced by partial evaluation is semantically equivalent to a conditioned slice. Received May 2002 Revised Octber 2004 and July 2005 Accepted August 2005 by D. J. Cooke     

Using duration models to reduce fragmentation in audio segmentation

We investigate explicit segment duration models in addressing the problem of fragmentation in musical audio segmentation. The resulting probabilistic models are optimised using Markov Chain Monte Carlo methods; in particular, we introduce a modification to Wolff’s algorithm to make it applicable to a segment classification model with an arbitrary duration prior. We apply this to a collection of pop songs, and show experimentally that the generated segmentations suffer much less from fragmentation than those produced by segmentation algorithms based on clustering, and are closer to an expert listener’s annotations, as evaluated by two different performance measures. Editor: Gerhard Widmer     

A suffix tree approach to anti-spam email filtering

We present an approach to email filtering based on the suffix tree data structure. A method for the scoring of emails using the suffix tree is developed and a number of scoring and score normalisation functions are tested. Our results show that the character level representation of emails and classes facilitated by the suffix tree can significantly improve classification accuracy when compared with the currently popular methods, such as naive Bayes. We believe the method can be extended to the classification of documents in other domains. Editor: Tom Fawcett     

The conformal alpha shape filtration

Conformal alpha shapes are a new filtration of the Delaunay triangulation of a finite set of points in ℝ^d. In contrast to (ordinary) alpha shapes the new filtration is parameterized by a local scale parameter instead of the global scale parameter in alpha shapes. The local scale parameter conforms to the local geometry and is motivated from applications and previous algorithms in surface reconstruction. We show how conformal alpha shapes can be used for surface reconstruction of non-uniformly sampled surfaces, which is not possible with alpha shapes.     

Hunting for metamorphic engines

In this paper, we analyze several metamorphic virus generators. We define a similarity index and use it to precisely quantify the degree of metamorphism that each generator produces. Then we present a detector based on hidden Markov models and we consider a simpler detection method based on our similarity index. Both of these techniques detect all of the metamorphic viruses in our test set with extremely high accuracy. In addition, we show that popular commercial virus scanners do not detect the highly metamorphic virus variants in our test set.A talk based on the results in this paper was presented by the authors at Defcon 14, August 5, 2006, Las Vegas, Nevada.     

Towards embedded model predictive control for System-on-a-Chip applications

We propose a framework for embedding model predictive control for Systems-on-a-Chip applications. In order to allow the implementation of such a computationally expensive controller on chip, we propose reducing the precision of the microprocessor to the minimum while maintaining near optimal control performance. Taking advantage of the low precision, a logarithmic number system based microprocessor architecture is used, that allows the design of a reduced size processor, providing further energy and computational cost savings. The design parameters for this high-performance embedded controller are chosen using a combination of finite element method simulations and bit-accurate hardware emulations in a number of parametric tests. We provide the methodology for choosing the design parameters for two particular control problems; the temperature regulation in a wafer cross-section geometry, and the control of temperature in a non-isothermal fluid flow problem in a microdevice. Finally, we provide the microprocessor architecture details and estimates for the performance of the resulting embedded model predictive controller.