Timed Patterns: TCOZ to Timed Automata
The integrated logic-based modeling language, Timed Communicating Object Z (TCOZ), is well suited for presenting complete and coherent requirement models for complex real-time systems. However, the challenge is how to verify the TCOZ models with tool support, especially for analyzing timing properties. Specialized graph-based modeling technique, Timed Automata (TA), has powerful mechanisms for designing real-time models using multiple clocks and has well developed automatic tool support. One weakness of TA is the lack of high level composable graphical patterns to support systematic designs for complex systems. The investigation of possible links between TCOZ and TA may benefit both techniques. For TCOZ, TA’s tool support can be reused to check timing properties. For TA, a set of composable graphical patterns can be defined based on the semantics of the TCOZ constructs, so that those patterns can be re-used in a generic way. This paper firstly defines the composable TA graphical patterns, and then presents sound transformation rules and a tool for projecting TCOZ specifications into TA. A case study of a railroad crossing system is demonstrated.

title: A tools environment for developing and reasoning about ontologies
abstract: Started in the beginning of 2001, the semantic Web is regarded by many as the next generation of the Web. Ontology languages are the building blocks of semantic Web as they provide basic vocabularies for data markups: the ontologies. The correctness of shared ontologies is crucial to the proper functioning of agents. Hence ensuring the consistency of ontologies is a central issue in both the design and deployment phases of any semantic Web-aware application. Our experiences show that semantic Web is a novel and fruitful application domain for formal languages and their mature reasoning tool support. In order to ease the application of formal methods and tools to the semantic Web, we developed an integrated tools environment to support systematic development of OWL ontologies and then transformation, reasoning assistance and querying of them.

title: A Z Approach in Validating ORA-SS Data Models
abstract: The rapid growth of the World Wide Web has resulted in more data being accessed over the Internet. In turn there is an increase in the use of semistructured data, which plays a crucial role in many web applications particularly with the introduction of XML and its related technologies. This increase in use makes the design of good semistructured data structures essential. The Object Relationship Attribute model for Semistructured data (ORA-SS) is a graphical notation for designing and representing semistructured data. In this paper, we demonstrate an approach to formally validate the ORA-SS data models in order to enhance the correctness of semistructured data design. A mathematical semantics for the ORA-SS notation is defined using the Z formal language, and further validation processes are carried out to check the correctness of the semistructured data models at both the schema and instance levels.

title: Validating Semistructured Data Using OWL
abstract: Semistructured data has become prevalent in both web applications and database systems. This rapid growth in use makes the design of good semistructured data essential. Formal semantics and automated reasoning tools enable us to reveal the inconsistencies in a semistructured data model and its instances. The Object Relationship Attribute model for Semistructured data (ORA-SS) is a graphical notation for designing and representing semistructured data. This paper presents a methodology of encoding the semantics of ORA-SS in the Web Ontology Language (OWL) and automatically validating the semistructured data design using the OWL reasoning tool – RACER. Our methodology provides automated consistency checking of an ORA-SS data model at both the schema and instance levels.

title: Object-Z web environment and projections to UML
abstract: This paper presents the XML/XSL approach to the development of a web environment for the formal speci cation language Object-Z. The projection techniques and tools from Object-Z (in XML) to UML (in XMI) are developed using XSL Transformations (XSLT). Furthermore, Object-Z (itself) is used to specify and design the essential functionalities of the web environment and the projection tools to UML. In a sense, the paper also demonstrates a formal approach to modeling web applications.

title: XML-Based Static Type Checking and Dynamic Visualization for TCOZ
abstract: Timed Communicating Object Z(TCOZ) combines Object-Z's strengths in modelling complex data and state with TCSP's strengths in modeling real-time concurrency. Based on our previous work on the XML environment for TCOZ, this paper firstly demonstrates the development of a type checker for detecting static semantic errors of the TCOZ specification, then illustrates a transformation tool to automatically project TCOZ models into UML statechart diagrams for visualising the dynamic system behaviour.

title: Fault-tolerant grid architecture and practice
abstract: Grid computing emerges as effective technologies to couple geographically distributed resources and solve large-scale computational problems in wide area networks. The fault tolerance is a significant and complex issue in grid computing systems. Various techniques have been investigated to detect and correct faults in distributed computing systems. Unreliable fault detection is one of the most effective techniques. Globus as a grid middleware manages resources in a wide area network. The Globus fault detection service uses the well-known techniques based on unreliable fault detectors to detect and report component failures. However, more powerful techniques are required to detect and correct both system-level and application-level faults in a grid system, and a convenient toolkit is also needed to maintain the consistency in the grid. A fault-tolerant grid platform (FTGP) based on an unreliable fault detector and the Globus fault detection service is presented in this paper. The platform offers effective strategies in such three aspects as grid key components, user tasks, and high-level applications.

title: A Data Mining Based Intrusion Detection Model
abstract: Intrusion Detection Systems (IDSs) have become a critical part of security systems. The goal of an intrusion detection system is to block intrusion effectively and accurately. However, the performance of IDS is not satisfying. In this paper, we study the issue of building a data mining based intrusion detection model to raise the detection performance. The key ideas are to use data mining techniques to discover consistent and useful patterns for intrusion and use the set of patterns to recognize intrusion. By applying statistics inference theory to this model, the patterns mined from a set of test data are effective to detect the attacks in the same category, and therefore can detect most novel attacks that are variants of known attacks.

title: Terrain Synthesis from Digital Elevation Models
abstract: In this paper, we present an example-based system for terrain synthesis. In our approach, patches from a sample terrain (represented by a height field) are used to generate a new terrain. The synthesis is guided by a user-sketched feature map that specifies where terrain features occur in the resulting synthetic terrain. Our system emphasizes large-scale curvilinear features (ridges and valleys) because such features are the dominant visual elements in most terrains. Both the example height field and user's sketch map are analyzed using a technique from the field of geomorphology. The system finds patches from the example data that match the features found in the user's sketch. Patches are joined together using graph cuts and Poisson editing. The order in which patches are placed in the synthesized terrain is determined by breadth-first traversal of a feature tree and this generates improved results over standard raster-scan placement orders. Our technique supports user-controlled terrain synthesis in a wide variety of styles, based upon the visual richness of real-world terrain data.

title: Hiding in the Crowd: Privacy Preservation on Evolving Streams through Correlation Tracking
abstract: We address the problem of preserving privacy in streams, which has received surprisingly limited attention. For static data, a well-studied and widely used approach is based on random perturbation of the data values. However, streams pose additional challenges. First, analysis of the data has to be performed incrementally, using limited processing time and buffer space, making batch approaches unsuitable. Second, the characteristics of streams evolve over time. Consequently, approaches based on global analysis of the data are not adequate. We show that it is possible to efficiently and effectively track the correlation and autocorrelation structure of multivariate streams and leverage it to add noise which maximally preserves privacy, in the sense that it is very hard to remove. Our techniques achieve much better results than previous static, global approaches, while requiring limited processing time and memory. We provide both a mathematical analysis and experimental evaluation on real data to validate the correctness, efficiency, and effectiveness of our algorithms.

title: A semi-local paradigm for wavelet denoising
abstract: Wavelet denoising methods have been proven useful for many one- and two-dimensional problems. Most existing methods can in principle be carried over to three-dimensional problems, such as the denoising of volumetric positron emission tomography (PET) images, but they may not be sufficiently flexible in allowing some regions of an image to be denoised more aggressively than others. In this paper, we propose a semi-local paradigm for wavelet denoising. The semi-local paradigm involves the division of an image into suitable blocks, which are then individually denoised. To denoise the blocks, we use our modification of the generalized cross validation (GCV) technique of Jansen and Bultheel to choose thresholding parameters; we also present risk estimators to guide some of the other choices involved in the implementation. Experiments with phantom PET images show that the semi-local paradigm provides superior denoising compared to standard application of the GCV technique. An asymptotic analysis demonstrates that, under some regularity conditions, semi-local denoising is asymptotically consistent on the logarithmic scale. The paper concludes with a discussion on the nature of semi-local denoising and some topics for future research.