Automating Integration of Heterogeneous COTS Components

Abstract. Mismatches make COTS components difficult to be incorporated. In this paper, an approach is presented to eliminate mismatches among COTS components, which can truly consider COTS components as black boxes. In the approach, only the assembly description of components is required, based on which adaptors for resolving mismatches can be generated automatically. This paper also described an agent-based GUI implementation of the approach.

Context-Aware Tuples for the Ambient

In tuple space approaches to context-aware mobile systems, the notion of context is defined by the presence or absence of certain tuples in the tuple space. Existing approaches define such presence either by collocation of devices holding the tuples or by replication of those tuples across all devices. We show that both approaches can lead to an erroneous perception of context. The former ties the perception of context to network connectivity which does not always yield the expected result. The latter causes context to be perceived even if a device has left that context a long time ago. We propose a tuple space approach in which tuples themselves carry a predicate that determines whether they are in the right context or not. We present a practical API for our approach and show its use by means of the implementation of a mobile game

The use of artificial intelligence for safeguarding fuel reprocessing plants

Recorded process data from the ''Minirun'' campaigns conducted at the Barnwell Nuclear Fuel Plant (BNFP) in Barnwell, South Carolina during 1980 to 1981 have been utilized to study the suitability of computer-based Artificial Intelligence (AI) methods for process monitoring for safeguards purposes. The techniques of knowledge engineering were used to formulate the decision-making software which operates on the process data customarily used for process operations. The OPS5 AI language was used to construct an Expert System for this purpose. Such systems are able to form reasoned conclusions from incomplete, inaccurate or otherwise ''fuzzy'' data, and to explain the reasoning that led to them. The programs were tested using minirun data taken during simulated diversions ranging in size from 1 to 20 L of solution that had been monitored previously using conventional procedural techniques. 13 refs., 3 figs

SPARQL Update for Complex Event Processing

Peer reviewe

Argus: Rete + dbms = efficient persistent profile matching on large-volume data streams

Abstract. Efficient processing of complex streaming data presents multiple challenges, especially when combined with intelligent detection of hidden anomalies in real time. We label such systems Stream Anomaly Monitoring Systems (SAMS), and describe the CMU/Dynamix ARGUS system as a new kind of SAMS to detect rare but high value patterns combining streaming and historical data. Such patterns may correspond to hidden precursors of terrorist activity, or early indicators of the onset of a dangerous disease, such as a SARS outbreak. Our method starts from an extension of the RETE algorithm for matching streaming data against multiple complex persistent queries, and proceeds beyond to transitivity inferences, conditional intermediate result materialization, and other such techniques to obtain both accuracy and efficiency, as demonstrated by the evaluation results outperforming classical techniques such as a modern DMBS.

Dynamic Generation of Context Rules

Abstract. This paper presents a scheme for the dynamic generation of context rules which are useful for modifying the behaviour of mobile devices according to the social and physical settings of their users. Existing context-aware systems employ a pool of predefined rules which will be executed whenever a context of interest is sensed and captured. Defining rules at design time, however, has the following limitations: (1) The system designer should identify the set of context primitives which describe a context of interest as accurately as possible; (2) the various states of each context primitive should be predetermined and mapped to sensory data, which often requires experience or expertise; (3) the availability of mechanisms for capturing the context primitives is presupposed; if instead of the specified context primitives other context primitives are discovered, which may equally describe a similar situation, the system does not react to them, unless of course, all possible alternatives are foreseen; and (4) the desired behaviour itself may not be a priori known, as it is specific to the user. To facilitate a flexible use of context rules, they should be generated dynamically. The scheme proposed in this paper associates decision events – signifying the activities of a user – with a set of context primitives which are acquired at the time the decision events are produced. From the decision-context associations, context rules are generated. The Context-Aware E-Pad will be introduced to illustrate the scheme proposed. 1