1275297
Bridging Physical and Virtual Worlds: Complex Event Processing for RFID Data Streams
Advances of sensor and RFID technology provide significant new power for humans to sense, understand and manage the world. RFID provides fast data collection with precise identification of objects with unique IDs without line of sight, thus it can be used for identifying, locating, tracking and monitoring physical objects. Despite these benefits, RFID poses many challenges for data processing and management: i) RFID observations contain duplicates, which have to be filtered; ii) RFID observations have implicit meanings, which have to be transformed and aggregated into semantic data represented in their data models; and iii) RFID data are temporal, streaming, and in high volume, and have to be processed on the fly. Thus, a general RFID data processing framework is needed to automate the transformation of physical RFID observations into the virtual counterparts in the virtual world linked to business applications. In this paper, we take an event-oriented approach to process RFID data, by devising RFID application logic into complex events. We then formalize the specification and semantics of RFID events and rules. We demonstrate that traditional ECA event engine cannot be used to support highly temporally constrained RFID events, and develop an RFID event detection engine that can effectively process complex RFID events. The declarative event-based approach greatly simplifies the work of RFID data processing, and significantly reduces the cost of RFID data integration.
14446563
Vague Content and Structure (VCAS) Retrieval for Document-centric XML Collections
document-centric XML collections with structure conditions improves retrieval precisions. The structures of such XML collections, however, are often too complex for users to fully grasp. Thus, for queries regarding such collections, it is more appropriate to retrieve answers that approximately match the structure and content conditions in these queries, a process also known as vague content and structure (VCAS) retrieval. Most existing XML engines, however, only support content-only (CO) retrieval and/or strict content and structure (SCAS) retrieval. To remedy these shortcomings, we propose an approach for VCAS retrieval using existing XML engines. Our approach first decomposes a VCAS query into a SCAS sub-query and a CO sub- query, then uses existing XML engines to retrieve SCAS results and CO results for the decomposed sub-queries, and finally combines results from both retrievals to produce approximate results for the original query. Further, to improve retrieval precision, we propose two similarity metrics to adjust the scores of CO retrieval results by their relevancies to the path condition for the original query target. We evaluate our VCAS retrieval approach through extensive experiments with the INEX 04 XML collection and VCAS query sets. The experimental results demonstrate the effectiveness of our VCAS retrieval approach.
6631927
Ctree: a compact tree for indexing XML data
In this paper, we propose a novel compact tree (Ctree) for XML indexing, which provides not only concise path summaries at the group level but also detailed child-parent links at the element level. Group level mapping allows efficient pruning of a large search space while element level mapping provides fast access to the parent of an element. Due to the tree nature of XML data and queries, such fast child-to-parent access is essential for efficient XML query processing. Using group-based element reference, Ctree enables the clustering of inverted lists according to groups, which provides efficient join between inverted lists and structural index group extents. Our experiments reveal that Ctree is efficient for processing both single-path and branching queries with various value predicates.
5842197
Configurable indexing and ranking for XML information retrieval
Indexing and ranking are two key factors for efficient and effective XML information retrieval. Inappropriate indexing may result in false negatives and false positives, and improper ranking may lead to low precisions. In this paper, we propose a configurable XML information retrieval system, in which users can configure appropriate index types for XML tags and text contents. Based on users' index configurations, the system transforms XML structures into a compact tree representation, Ctree, and indexes XML text contents. To support XML ranking, we propose the concepts of "weighted term frequency" and "inverted element frequency," where the weight of a term depends on its frequency and location within an XML element as well as its popularity among similar elements in an XML dataset. We evaluate the effectiveness of our system through extensive experiments on the INEX 03 dataset and 30 content and structure (CAS) topics. The experimental results reveal that our system has significantly high precision at low recall regions and achieves the highest average precision (0.3309) as compared with 38 official INEX 03 submissions using the strict evaluation metric.
7952210
Semi-automatic transformation from formal specifications to programs
As model-based formal methods (e.g. VDM, Z) are becoming popular for the development of safety-critical and complex systems in industry, automatic transformation from formal specifications to programs is an ideal and efficient approach to software production. However, it is impossible in general for this transformation to be fully automatic, because the language of first order logic used for specification is not decidable. This paper uses VDM (Vienna Development Method) as an example to investigate this difficulty, and proposes an approach to address the problem. Rules for automatically transforming abstract level VDM specifications are described and further transformation at a detailed level is discussed. Finally, further work towards the construction of a rule-based software system to support the transformation from VDM specifications to programs in general is addressed.
18135743
A clustering entropy-driven approach for exploring and exploiting noisy functions
Linear, Gaussian, fitness proportional, clustering, and Rosca entropies are succinct measures of diversity that have been applied to balance exploration and exploitation in evolutionary algorithms. In previous studies, an entropy-driven approach using linear entropy explicitly balances and/or searches optimal solutions for the selected unimodal and multimodal functions excluding noisy functions. This paper investigates the reasons for such an exception and introduces a clustering entropy-driven approach to solve the problem. Such an approach provides a coarse-grained diversity measure that filters the noise of functions, varies cluster size and categorizes individuals at the genotype level. The experimental results show that the clustering entropy-driven approach further improves the searching results of noisy functions by one more degree.
15677254
Inference Queues for Communicating and Monitoring Declarative Information between Web Services
We introduce the inference queue as a mechanism for communicating and transforming data in Web services choreography. The insert operation provides definite clauses to the inference queue, and the remove operation generates output that is sound, complete, fair, and irredundant. Both operations are thread safe and responsive. The inference queue can form part of a highly configurable data transformation system. Rules can also monitor for events of interest based on the occurrence of certain conditions. Our suggestion of system wide monitoring of communication is complementary to existing Web services proposals.
14954145
Interacting frameworks in Catalysis
In current OO design, most of the existing (semi-formal) methods use classes or objects as the basic unit of design. However it is increasingly recognised that classes are not the best focus for design. Typical design artefacts are about groups of objects and the way they interact In the Catalysis project, we use the term frameworks for descriptions of groups of objects, their relationships, division of responsibilities, and interactions. The power of frameworks lies in the fact that interactions can also occur at the level of frameworks. In a previous paper we defined a framework formally as a (first-order) many-sorted theory with a model theoretic semantics and showed how it can be represented using a pictorial notation for practical system development. However we considered only frameworks that do not interact with one another In this paper we discuss frameworks that interact with one another and show that such frameworks are very powerful tools for formal OO design.
9506912
Quantifying Input and Output Spike Statistics of a Winner-Take-All Network in a Vision System
Event-driven spike-based processing systems offer new possibilities for real-time vision. Signals are encoded asynchronously in time thus preserving the time information of the occurrence of an event. The paper examines this form of coding using experimental data from a multi-layered multi-chip system which consists of an artificial retina, a convolution filter bank and a winner-take-all network which detect the position of a moving object. The spike outputs of the convolution stage can be described by an inhomogeneous Poisson distribution of Gaussian profile, although the underlying building blocks are completely deterministic and exhibit only a small amount of variation. The authors discuss a method for measuring the accuracy of the asynchronous spiking representation in both time and value, thereby quantifying the performance of the winner-take-all network in determining the position of a ball rotating in front of the system.