2635468
A System for Managing Alternate Models in Model-Based Mediation
In [1,3], we have described the problem of model-based mediation (MBM) as an extension of the global-as-view paradigm of information integration. The need for this extension arises in many application domains where the information sources to be integrated not only differ in their export formats, data models, and query capabilities, but have widely different schema with very little overlap in attributes. In scientific applications, the information sources come from different subdisciplines, and despite their poorly overlapping schema, can be integrated because they capture different aspects of the same scientific objects or phenomena, and can be conceptually integrated due to scientific reasons. In the MBM paradigm, a “mediation engineer” consults with domain experts to explicitly model the “glue knowledge” using a set of facts and rules at the mediator. Integrated views are defined in MBM on top of the exported schemas from the information sources together with the glue knowledge source that ties them together. We have successfully applied the MBM technique to develop the KIND mediator or Neuroscience information sources [1]-[4]. To accomplish this, sources in the MBM framework export their conceptual models (CMs), consisting of the logical schema, domain constraints, and object contexts, i.e., formulas that relate their conceptual schema with the global domain knowledge maintained at the mediator. Thus model-based mediation has a hybrid approach to information integration - on the one hand at the mediator integrated views are defined over source CMs and the Knowledge Map using a global-as-view approach; on the other hand, object-contexts of the source are defined as local-as-view.
28715235
Virage video engine
The temporal and multi-modal nature of video increases the dimensionality of content based retrieval problem. This places new demands on the indexing and retrieval tools required. The Virage Video Engine (VVE) with the default set of primitives provide the necessary frame work and basic tools for video content based retrieval. The video engine is a flexible platform independent architecture which provides support for processing multiple synchronized data streams like image sequences, audio and closed captions. The architecture allows for multi-modal indexing and retrieval of video through the use of media specific primitives. This paper presents the use of the VVE framework for content based video retrieval.
9743987
Complex Visual Activity Recognition Using a Temporally Ordered Database
We propose using a temporally ordered database for complex visual activity recognition. We use a temporal precedence relation together with the assumption of fixed bounded temporal uncertainty of occurrence time of an atomic activity and comparatively large temporal extent of the complex activity. Under these conditions we identify the temporal structure of complex activities as a semiorder and design a database that has semiorder as its data model. A query algebra is then defined for this data model.
11105634
Model-based mediation with domain maps
Proposes an extension to current view-based mediator systems called "model-based mediation", in which views are defined and executed at the level of conceptual models (CMs) rather than at the structural level. Structural integration and lifting of data to the conceptual level is "pushed down" from the mediator to wrappers which, in our system, export the classes, associations, constraints and query capabilities of a source. Another novel feature of our architecture is the use of domain maps - semantic nets of concepts and relationships that are used to mediate across sources from multiple worlds (i.e. whose data are related in indirect and often complex ways). As part of registering a source's CM with the mediator, the wrapper creates a "semantic index" of its data into the domain map. We show that these indexes not only semantically correlate the multiple-worlds data, and thereby support the definition of the integrated CM, but they are also useful during query processing, for example, to select relevant sources. A first prototype of the system has been implemented for a complex neuroscience mediation problem.
17115672
Emergent Semantics through Interaction in Image Databases
In this paper, we briefly discuss some aspects of image semantics and the role that it plays for the design of image databases. We argue that images don't have an intrinsic meaning, but that they are endowed with a meaning by placing them in the context of other images and by the user interaction. From this observation, we conclude that, in an image, database users should be allowed to manipulate not only the individual images, but also the relation between them. We present an interface model based on the manipulation of configurations of images.
8323337
Modeling Functional Data Sources as Relations
In this paper we present a model of functional access to data that, we argue, is suitable for modeling a class of data repositories characterized by functional access, such as web sites. We discuss the problem of modeling such data sources as a set of relations, of determining whether a given query expressed on these relations can be translated into a combination of functions defined by the data sources, and of finding an optimal plan to do so.
11198288
Why the Information Explosion Can Be Bad for Data Mining, and How Data Fusion Provides a Way Out
One may claim that the exponential growth in the amount of data provides great opportunities for data mining. Reality can be different though. In many real world applications, the number of sources over which this information is fragmented grows at an even faster rate, resulting in barriers to widespread application of data mining and missed business opportunities. Let us illustrate this paradox with a motivating example from database marketing. In marketing, direct forms of communication are becoming increasingly popular. Instead of broadcasting a single message to all customers through traditional mass media such as television and print, the most promising potential customers receive personalized offers through the most appropriate channels. So it becomes more important to gather information about media consumption, attitudes, product propensity etc. at an individual level. Basic, company specific customer information resides in customer databases, but market survey data depicting a richer view of the customer are only available for a small sample or a disjoint set of reference customers. Collecting all this information for the whole customer database in a single source survey would certainly be valuable but is usually a very expensive proposition. The common alternative within business to
25366029
Formal hardware verification methods: A survey
Growing advances in VLSI technology have led to an increased level of complexity in current hardware systems. Late detection of design errors typically results in higher costs due to the associated time delay as well as loss of production. Thus it is important that hardware designs be free of errors. Formal verification has become an increasingly important technique towards establishing the correctness of hardware designs. In this article we survey the research that has been done in this area, with an emphasis on more recent trends. We present a classification framework for the various methods, based on the forms of the specification, the implementation, and the proff method. This framework enables us to better highlight the relationships and interactions between seemingly different approaches.
13925350
Embedding k-outerplanar graphs into ℓ1
We show that the shortest-path metric of any k-outerplanar graph, for any fixed k, can be approximated by a probability distribution over tree metrics with constant distortion, and hence also embedded into l1 with constant distortion. These graphs play a central role in polynomial time approximation schemes for many NP-hard optimization problems on general planar graphs, and include the family of weighted k × n planar grids.This result implies a constant upper bound on the ratio between the sparsest cut and the maximum concurrent flow in multicommodity networks for k-outerplanar graphs, thus extending a classical theorem of Okamura and Seymour [26] for outerplanar graphs, and of Gupta et al. [17] for treewidth-2 graphs. In addition, we obtain improved approximation ratios for k-outerplanar graphs on various problems for which approximation algorithms are based on probabilistic tree embeddings. We also conjecture that our random tree embeddings for k-outerplanar graphs can serve as a building block for more powerful l1 embeddings in future.
639197
An integrated and collaborative framework for business design: A knowledge engineering approach
Many large-scale endeavors, especially the ones that need to be performed on an occasional basis, are performed on a de novo basis. Whether one is designing a spacecraft or a dam, or launching a sales campaign, each endeavor tends to have a life of its own. Very little knowledge, if any, is transferred from one business or engineering design endeavor to a successive one. This paper describes an approach that involves the acquisition of raw information from the keystrokes entered by the user while performing the primary activity. Such information is distilled to produce knowledge for future use, without imposing additional burden on human users involved in the first endeavor or the succeeding endeavors. The paper also describes a complementary approach that significantly reduces the time and effort spent by human beings in articulating their requirements, and specifically, in terms of delineating the indifference points among a set of feasible alternatives. Both these approaches have been validated in a complex multi-organizational situation related to spacecrafts. The approaches can be applied, either singly or jointly, to a broad class of business and engineering scenarios. They incorporate the notion of automated knowledge acquisition, discovery, management, and dissemination. The proposed approach is discussed in the context of supporting workteams that are distributed both on geographic and temporal basis, thereby creating a "24-Hour Knowledge Factory" environment.
9811083
Performance enhancement of a contract net protocol based system through instance-based learning
The contract net protocol (CNP) is a widely used coordination mechanism in multiagent systems. It has a lot of communication overhead due to the broadcast of the task announcements. The performance of the CNP degrades drastically when the number of communicating agents and the number of tasks announced increases. Hence, it has problems of scalability. In order to overcome this limitation, an instance-based learning (IBL) mechanism is designed that uses previously stored instances in order to select a target agent. This avoids the expensive bidding process. The scheme is implemented in a simulated distributed hospital system where the CNP is used for resource sharing across hospitals. Experimental results demonstrate that with the incorporation of the IBL, the system performance improves significantly. The system is better scalable with respect to the number of tasks.