Behavioural hybrid process calculus

Process algebra is a theoretical framework for the modelling and analysis of the behaviour of concurrent discrete event systems that has been developed within computer science in past quarter century. It has generated a deeper nderstanding of the nature of concepts such as observable behaviour in the presence of nondeterminism, system composition by interconnection of concurrent component systems, and notions of behavioural equivalence of such systems. It has contributed fundamental concepts such as bisimulation, and has been successfully used in a wide range of problems and practical applications in concurrent systems. We believe that the basic tenets of process algebra are highly compatible with the behavioural approach to dynamical systems. In our contribution we present an extension of classical process algebra that is suitable for the modelling and analysis of continuous and hybrid dynamical systems. It provides a natural framework for the concurrent composition of such systems, and can deal with nondeterministic behaviour that may arise from the occurrence of internal switching events. Standard process algebraic techniques lead to the characterisation of the observable behaviour of such systems as equivalence classes under some suitably adapted notion of bisimulation

Timed Chi: Modeling, Simulation and Verification of Hardware Systems

Timed Chi (chi) is a timed process algebra, designed for Modeling, simulation, verification and real-time control. Its application domain consists of large and complex manufacturing systems. The straightforward syntax and semantics are also highly suited to architects, engineers and researchers from the hardware design community. There are many different tools for timed Chi that support the analysis and manipulation of timed Chi specifications; and such tools are the results of software engineering research with a very strong foundation in formal theories/methods. Since timed Chi is a well-developed algebraic theory from the field of process algebras with timing, we have the idea that timed Chi is also well-suited for addressing various aspects of hardware systems (discrete-time systems by nature). To show that timed Chi is useful for the formal specification and analysis of hardware systems, we illustrate the use of timed Chi with several benchmark examples of hardware systems

Multi modal multi-semantic image retrieval

PhDThe rapid growth in the volume of visual information, e.g. image, and video can overwhelm users’ ability to find and access the specific visual information of interest to them. In recent years, ontology knowledge-based (KB) image information retrieval techniques have been adopted into in order to attempt to extract knowledge from these images, enhancing the retrieval performance. A KB framework is presented to promote semi-automatic annotation and semantic image retrieval using multimodal cues (visual features and text captions). In addition, a hierarchical structure for the KB allows metadata to be shared that supports multi-semantics (polysemy) for concepts. The framework builds up an effective knowledge base pertaining to a domain specific image collection, e.g. sports, and is able to disambiguate and assign high level semantics to ‘unannotated’ images. Local feature analysis of visual content, namely using Scale Invariant Feature Transform (SIFT) descriptors, have been deployed in the ‘Bag of Visual Words’ model (BVW) as an effective method to represent visual content information and to enhance its classification and retrieval. Local features are more useful than global features, e.g. colour, shape or texture, as they are invariant to image scale, orientation and camera angle. An innovative approach is proposed for the representation, annotation and retrieval of visual content using a hybrid technique based upon the use of an unstructured visual word and upon a (structured) hierarchical ontology KB model. The structural model facilitates the disambiguation of unstructured visual words and a more effective classification of visual content, compared to a vector space model, through exploiting local conceptual structures and their relationships. The key contributions of this framework in using local features for image representation include: first, a method to generate visual words using the semantic local adaptive clustering (SLAC) algorithm which takes term weight and spatial locations of keypoints into account. Consequently, the semantic information is preserved. Second a technique is used to detect the domain specific ‘non-informative visual words’ which are ineffective at representing the content of visual data and degrade its categorisation ability. Third, a method to combine an ontology model with xi a visual word model to resolve synonym (visual heterogeneity) and polysemy problems, is proposed. The experimental results show that this approach can discover semantically meaningful visual content descriptions and recognise specific events, e.g., sports events, depicted in images efficiently. Since discovering the semantics of an image is an extremely challenging problem, one promising approach to enhance visual content interpretation is to use any associated textual information that accompanies an image, as a cue to predict the meaning of an image, by transforming this textual information into a structured annotation for an image e.g. using XML, RDF, OWL or MPEG-7. Although, text and image are distinct types of information representation and modality, there are some strong, invariant, implicit, connections between images and any accompanying text information. Semantic analysis of image captions can be used by image retrieval systems to retrieve selected images more precisely. To do this, a Natural Language Processing (NLP) is exploited firstly in order to extract concepts from image captions. Next, an ontology-based knowledge model is deployed in order to resolve natural language ambiguities. To deal with the accompanying text information, two methods to extract knowledge from textual information have been proposed. First, metadata can be extracted automatically from text captions and restructured with respect to a semantic model. Second, the use of LSI in relation to a domain-specific ontology-based knowledge model enables the combined framework to tolerate ambiguities and variations (incompleteness) of metadata. The use of the ontology-based knowledge model allows the system to find indirectly relevant concepts in image captions and thus leverage these to represent the semantics of images at a higher level. Experimental results show that the proposed framework significantly enhances image retrieval and leads to narrowing of the semantic gap between lower level machinederived and higher level human-understandable conceptualisation

Bridging formal models : an engineering perspective

The thesis presents different techniques that can be used to build formal behavioral models. If modal properties are formulated, the models can be subjected to verification techniques to determine whether a model possesses the desired properties. However many native environments do not facilitate tools or techniques to verify them. Hence, these models need to be transformed into other models that provide suitable techniques for a formal analysis. The transformations are classified into two engineering approaches, namely syntactically engineered models and semantically engineered models. Syntactically engineered models are constructed from input specifications without explicitly considering the semantics. Semantically engineered models are constructed from input specifications by explicitly considering the semantics. The syntactic engineering approach presents four dedicated modeling techniques that construct or disseminate verification results for formal models. The first modeling technique describes a way to create models from system descriptions that specify concurrent behavior. Here, we model three variations of a 2×2 switch, for which the models are subsequently compared to models created in the specification languages: TLA+, Bluespec, Statecharts, and ACP. The comparison validates that mCRL2 is a suitable specification language to model descriptions or specify the behavior for prototype systems. The second syntactic technique constructs an mCRL2 model from a software implementation that operates a printer for printing Printed Circuit Boards. The model is used to advise (other) software engineers on dangerous language constructs in the control software. Hence, the model is model checked for various safety properties. The implementation is modeled through an over-approximation on the behavior by abstracting from program variables, such that only interface calls between processes and non-deterministic choices in procedures remain. The third modeling technique describes a language transformation from the language Chi 2.0 language to the mCRL2 language. The purpose of the transformation is to facilitate model checking techniques to the discrete part of the Chi 2.0 language