Multiplication and comultiplication of beliefs

Multiplication and comultiplication of beliefs represent a generalisation of multiplication and comultiplication of probabilities as well as of binary logic AND and OR. Our approach follows that of subjective logic, where belief functions are expressed as opinions that are interpreted as being equivalent to beta probability distributions. We compare different types of opinion product and coproduct, and show that they represent very good approximations of the analytical product and coproduct of beta probability distributions. We also define division and codivision of opinions, and compare our framework with other logic frameworks for combining uncertain propositions. (C) 2004 Elsevier Inc. All rights reserved.

Eco-efficiency and dairy processing

The dairy industry is a global industry that provides significant nutritional benefit to many cultures. in australia the industry is especially important economically, being a large export earner, as well as a vital domestic sector. in recent years the sector has come under increased competitive pressure and has restructured to cope with the changes. the industry recently undertook an eco-efficiency project to investigate where business and environmental improvements might be found. the project involved collecting and collating previous project data and surveying 38 companies in different dairy operations, from market milk to dried products. after the survey, 10 sites in two states were visited to discuss eco-efficiency issues in detail with key players. From the surveys, visits and data compilation, a comprehensive manual was prepared to help interested companies find relevant eco-efficiency data easily and assist them in the implementation process. ten fact sheets were also produced covering the topics of water management, water recycling and re-use, refrigeration optimisation, boiler optimisation, biogas, the use of treated wastewater, yield optimisation and product recovery, optimisation of ciP systems, chemical use and membranes the project highlighted the large amount of technical and engineering expertise within the sector that could result in eco-efficiency outcomes and also identified the opportunities that exist for changes to occur in some operations to save energy, input raw materials and water.

Face recognition robust to head pose from one sample image

Most face recognition systems only work well under quite constrained environments. In particular, the illumination conditions, facial expressions and head pose must be tightly controlled for good recognition performance. In 2004, we proposed a new face recognition algorithm, Adaptive Principal Component Analysis (APCA) [4], which performs well against both lighting variation and expression change. But like other eigenface-derived face recognition algorithms, APCA only performs well with frontal face images. The work presented in this paper is an extension of our previous work to also accommodate variations in head pose. Following the approach of Cootes et al, we develop a face model and a rotation model which can be used to interpret facial features and synthesize realistic frontal face images when given a single novel face image. We use a Viola-Jones based face detector to detect the face in real-time and thus solve the initialization problem for our Active Appearance Model search. Experiments show that our approach can achieve good recognition rates on face images across a wide range of head poses. Indeed recognition rates are improved by up to a factor of 5 compared to standard PCA.