1221956
Knowledge-based integration of neuroscience data sources
The need for information integration is paramount in many biological disciplines, because of the large heterogeneity in both the types of data involved and in the diversity of approaches (physiological, anatomical, biochemical, etc.) taken by biologists to study the same or correlated phenomena. However, the very heterogeneity makes the task of information integration very difficult since two approaches studying different aspects of the same phenomena may not even share common attributes in their schema description. The paper develops a wrapper-mediator architecture which extends the conventional data- and view-oriented information mediation approach by incorporating additional knowledge modules that bridge the gap between the heterogeneous data sources. The semantic integration of the disparate local data sources employs F-logic as a data and knowledge representation and reasoning formalism. We show that the rich object oriented modeling features of F-logic together with its declarative rule language and the uniform treatment of data and metadata (schema information) make it an ideal candidate for complex integration tasks. We substantiate this claim by elaborating on our integration architecture and illustrating the approach using real world examples from the neuroscience domain. The complete integration framework is currently under development; a first prototype establishing the viability of the approach is operational.
28954888
Modeling shape and topology of 3D images of biological specimens
This paper presents an efficient way of representing the geometry and topology of 3D images of biological specimens derived from electron microscopy. A vector quantization algorithm is used in order to select a reduced set of interior points that best approximates the probability density function of the original volumetric data. Object's geometry and topology are obtained from the point set by the use of the alpha shapes theory.
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.
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.
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.
14666453
An Interpolated Volume Data Model
Publisher Summary This chapter explores the basic functionality of the volume data model. It considers examples from biology and volumes of measurement from quantum physics. The data model is similar in the two cases, but the operations that are commonly used are quite different. In the second case, for instance, one is often interested in conditions on the behavior of local differential operators, such as zero-flow surfaces, while in the biological case one has a mix of value conditions and geometric condition. With these two application fields, this chapter highlights the generality and flexibility of the model. The system is based on a commercial database, augmented with specialized functions to manipulate the volume data model. The chapter demonstrates various operations specifying queries both using a graphical user interface and entering them directly in structured query language (SQL) augmented with the volume algebra operations.
38885821
Embeddings of k-Connected Graphs of Pathwidth k
We present O(n3) embedding algorithms (generalizing subgraph isomorphism) for classes of graphs of bounded pathwidth, where n is the number of vertices in the graph. These include the first polynomialtime algorithm for minor containment and the first O(nc) algorithm (c a constant independent of k) for topological embedding of graphs from subclasses of partial k-trees. Of independent interest are structural properties of k-connected graphs of bounded pathwidth on which our algorithms are based. We also describe special cases which reduce to various generalizations of string matching, permitting more efficient solutions.
11586348
Cost-Sharing Mechanisms for Network Design
We consider a single source network design problem from a game-theoretic perspective. Gupta, Kumar and Roughgarden (Proc. 35th Annual ACM STOC, pages 365-372, 2003) developed a simple method for single source rent-or-buy problem that also yields the best-known approximation ratio for the problem. We show how to use a variant of this method to develop an approximately budget-balanced and group strategyproof cost-sharing method for the problem. The novelty of our approach stems from our obtaining the cost-sharing methods for the rent-or-buy problem by carefully combining cost-shares for the simpler problem Steiner tree problem; we feel that this idea may have wider implications. Our algorithm is conceptually simpler than the previous such cost-sharing method due to Pal and Tardos (Proc. 44th Annual FOCS, pages 584-593, 2003), and has a much improved approximation factor of 4.6 (over the previously known factor of 15).
5297326
Parametric Circuit Representation Using Inductive Boolean Functions
We have developed a methodology based on symbolic manipulation of inductive Boolean functions (IBFs) for formal verification of inductively-defined hardware. This methodology combines the techniques of reasoning by induction and symbolic tautologychecking in an automated and potentially efficient way. In this paper, we describe a component of this methodology that regards various mechanisms used to represent inductivelydefined circuits in the form of IBFs. The focus is on general parameterization issues, such as multiple parameter functions, multiple output functions, interaction of different parameters for supporting compositions etc. These mechanisms, which may be useful in other applications involving parametric circuit descriptions, are illustrated through practical circuit examples along with preliminary results. We also describe an application of our formal verification methodology, where a proof by induction is performed by automatic symbolic manipulation of parametric circuit representations.
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.
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