Computational methods for the detection of facial palsy

We are developing a telemedicine application which offers automated diagnosis of facial (Bell's) palsy through a Web service. We used a test data set of 43 images of facial palsy patients and 44 normal people to develop the automatic recognition algorithm. Three different image pre-processing methods were used. Machine learning techniques (support vector machine, SVM) were used to examine the difference between the two halves of the face. If there was a sufficient difference, then the SVM recognized facial palsy. Otherwise, if the halves were roughly symmetrical, the SVM classified the image as normal. It was found that the facial palsy images had a greater Hamming Distance than the normal images, indicating greater asymmetry. The median distance in the normal group was 331 (interquartile range 277-435) and the median distance in the facial palsy group was 509 (interquartile range 334-703). This difference was significant (P

Termination of real-time programs: Definitely, definitely not, or maybe

Real-time control programs are often used in contexts where (conceptually) they run forever. Repetitions within such programs (or their specifications) may either (i) be guaranteed to terminate, (ii) be guaranteed to never terminate (loop forever), or (iii) may possibly terminate. In dealing with real-time programs and their specifications, we need to be able to represent these possibilities, and define suitable refinement orderings. A refinement ordering based on Dijkstra's weakest precondition only copes with the first alternative. Weakest liberal preconditions allow one to constrain behaviour provided the program terminates, which copes with the third alternative to some extent. However, neither of these handles the case when a program does not terminate. To handle this case a refinement ordering based on relational semantics can be used. In this paper we explore these issues and the definition of loops for real-time programs as well as corresponding refinement laws.

Scaleup of wet granulation processes: science not art

Significant advances have been made in the last decade to quantify the process of wet granulation. The attributes of product granules from the granulation process are controlled by a combination of three groups of processes occurring in the granulator: (1) wetting and nucleation, (2) growth and consolidation and (3) breakage and attrition. For the first two of these processes, the key controlling dimensionless groups are defined and regime maps are presented and validated with data from tumbling and mixer granulators. Granulation is an example of particle design. For quantitative analysis, both careful characterisation of the feed formulation and knowledge of operating parameters are required. A key thesis of this paper is that the design, scaleup and operation of granulation processes can now be considered as quantitative engineering rather than a black art. Résumé