Computing explanations for interactive constraint-based systems

Constraint programming has emerged as a successful paradigm for modelling combinatorial problems arising from practical situations. In many of those situations, we are not provided with an immutable set of constraints. Instead, a user will modify his requirements, in an interactive fashion, until he is satisfied with a solution. Examples of such applications include, amongst others, model-based diagnosis, expert systems, product configurators. The system he interacts with must be able to assist him by showing the consequences of his requirements. Explanations are the ideal tool for providing this assistance. However, existing notions of explanations fail to provide sufficient information. We define new forms of explanations that aim to be more informative. Even if explanation generation is a very hard task, in the applications we consider, we must manage to provide a satisfactory level of interactivity and, therefore, we cannot afford long computational times. We introduce the concept of representative sets of relaxations, a compact set of relaxations that shows the user at least one way to satisfy each of his requirements and at least one way to relax them, and present an algorithm that efficiently computes such sets. We introduce the concept of most soluble relaxations, maximising the number of products they allow. We present algorithms to compute such relaxations in times compatible with interactivity, achieving this by indifferently making use of different types of compiled representations. We propose to generalise the concept of prime implicates to constraint problems with the concept of domain consequences, and suggest to generate them as a compilation strategy. This sets a new approach in compilation, and allows to address explanation-related queries in an efficient way. We define ordered automata to compactly represent large sets of domain consequences, in an orthogonal way from existing compilation techniques that represent large sets of solutions.

Pervasive handheld computing systems

The technological role of handheld devices is fundamentally changing. Portable computers were traditionally application specific. They were designed and optimised to deliver a specific task. However, it is now commonly acknowledged that future handheld devices need to be multi-functional and need to be capable of executing a range of high-performance applications. This thesis has coined the term pervasive handheld computing systems to refer to this type of mobile device. Portable computers are faced with a number of constraints in trying to meet these objectives. They are physically constrained by their size, their computational power, their memory resources, their power usage, and their networking ability. These constraints challenge pervasive handheld computing systems in achieving their multi-functional and high-performance requirements. This thesis proposes a two-pronged methodology to enable pervasive handheld computing systems meet their future objectives. The methodology is a fusion of two independent and yet complementary concepts. The first step utilises reconfigurable technology to enhance the physical hardware resources within the environment of a handheld device. This approach recognises that reconfigurable computing has the potential to dynamically increase the system functionality and versatility of a handheld device without major loss in performance. The second step of the methodology incorporates agent-based middleware protocols to support handheld devices to effectively manage and utilise these reconfigurable hardware resources within their environment. The thesis asserts the combined characteristics of reconfigurable computing and agent technology can meet the objectives of pervasive handheld computing systems.

“Green preservatives” – combating fungi in the food industry by applying antifungal lactic acid bacteria

Fungal spoilage is the most common type of microbial spoilage in food leading to significant economical and health problems throughout the world. Fermentation by lactic acid bacteria (LAB) is one of the oldest and most economical methods of producing and preserving food. Thus, LAB can be seen as an interesting tool in the development of novel bio-preservatives for food industry. The overall objective of this study was to demonstrate, that LAB can be used as a natural way to improve the shelf-life and safety of a wide range of food products. In the first part of the thesis, 116 LAB isolates were screened for their antifungal activity against four Aspergillus and Penicillium spp. commonly found in food. Approximately 83% of them showed antifungal activity, but only 1% showed a broad range antifungal activity against all tested fungi. The second approach was to apply LAB antifungal strains in production of food products with extended shelf-life. L. reuteri R29 strain was identified as having strong antifungal activity in vitro, as well as in sourdough bread against Aspergillus niger, Fusarium culmorum and Penicillium expansum. The ability of the strain to produce bread of good quality was also determined using standard baking tests. Another strain, L. amylovorus DSM19280, was also identified as having strong antifungal activity in vitro and in vivo. The strain was used as an adjunct culture in a Cheddar cheese model system and demonstrated the inhibition of P. expansum. Significantly, its presence had no detectable negative impact on cheese quality as determined by analysis of moisture, salt, pH, and primary and secondary proteolysis. L. brevis PS1 a further strain identified during the screening as very antifungal, showed activity in vitro against common Fusarium spp. and was used in the production of a novel functional wortbased alcohol-free beverage. Challenge tests performed with F. culmorum confirmed the effectiveness of the antifungal strain in vivo. The shelf-life of the beverage was extended significantly when compared to not inoculated wort sample. A range of antifungal compounds were identified for the 4 LAB strains, namely L. reuteri ee1p, L. reuteri R29, L. brevis PS1 and L. amylovorous DSM20531. The identification of the compounds was based on liquid chromatography interfaced to the mass spectrometer and PDA detector