41630036
Virage image search engine: an open framework for image management
Until recently, the management of large image databases has relied exclusively on manually entered alphanumeric annotations. Systems are beginning to emerge in both the research and commercial sectors based on 'content-based' image retrieval, a technique which explicitly manages image assets by directly representing their visual attributes. The Virage image search engine provides an open framework for building such systems. The Virage engine expresses visual features as image 'primitives.' Primitives can be very general (such as color, shape, or texture) or quite domain specific (face recognition, cancer cell detection, etc.). The basic philosophy underlying this architecture is a transformation from the data-rich representation of explicit image pixels to a compact, semantic-rich representation of visually salient characteristics. In practice, the design of such primitives is non-trivial, and is driven by a number of conflicting real-world constraints (e.g. computation time vs. accuracy). The virage engine provides an open framework for developers to 'plug-in' primitives to solve specific image management problems. The architecture has been designed to support both static images and video in a unified paradigm. The infrastructure provided by the Virage engine can be utilized to address high-level problems as well, such as automatic, unsupervised keyword assignment, or image classification.
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.
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.
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.
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.
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.
11289392
Efficient Routing for Peer-to-Peer Overlays
Most current peer-to-peer lookup schemes keep a small amount of routing state per node, typically logarithmic in the number of overlay nodes. This design assumes that routing information at each member node must be kept small, so that the bookkeeping required to respond to system membership changes is also small, given that aggressive membership dynamics are expected. As a consequence, lookups have high latency as each lookup requires contacting several nodes in sequence. 
 
In this paper, we question these assumptions by presenting two peer-to-peer routing algorithms with small lookup paths. First, we present a one-hop routing scheme. We show how to disseminate information about membership changes quickly enough so that nodes maintain accurate routing tables with complete membership information. We also deduce analytic bandwidth requirements for our scheme that demonstrate its feasibility. 
 
We also propose a two-hop routing scheme for large scale systems of more than a few million nodes, where the bandwidth requirements of one-hop routing can become too large. This scheme keeps a fixed fraction of the total routing state on each node, chosen such that the first hop has low latency, and thus the additional delay is small. 
 
We validate our analytic model using simulation results that show that our algorithms can maintain routing information sufficiently up-to-date such that a large fraction (e.g., 99%) of the queries will succeed without being re-routed.
17058061
Sequential and Parallel Algorithms for Embedding Problems on Classes of Partial k-Trees
We present sequential and parallel algorithms for various embedding problems on bounded degree partial k-trees and k-connected partial k-trees; these include subgraph isomorphism and topological embedding, known to be NP-complete for general partial k-trees. As well as contributing to our understanding of the types of graphs for which these problems are tractable, this paper introduces methods for solving problems on graphs. In particular, we make use of the tree-decomposition of the graph to apply techniques used to solve problems on trees to solve problems on partial k-trees.
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.
18052775
Pricing of risk for loss guaranteed intra-domain internet service contracts
The Internet today offers primarily a best-effort service. Research and technology development efforts are currently underway to allow provisioning of better than best-effort Quality of Service (QoS) assurances. The residual uncertainty in QoS can be managed using pricing strategies. In this article, we develop a spot pricing framework for intra-domain expected bandwidth contracts with loss-based QoS guarantees. The framework builds on a nonlinear pricing scheme for cost recovery from earlier work and extends it to price risk. A utility-based options pricing approach is developed to account for the uncertainties in delivering loss guarantees. Application of options pricing techniques in Internet services provides a mechanism for fair risk sharing between the provider and the customer, and may be extended to price other uncertainties in QoS guarantees.
6254649
Disjunctive Image Computation for Embedded Software Verification
Finite state models generated from software programs have unique characteristics that are not exploited by existing model checking algorithms. In this paper, we propose a novel disjunctive image computation algorithm and other simplifications based on these characteristics. Our algorithm divides an image computation into a disjunctive set of easier ones that can be performed in isolation. Hypergraph partitioning is used to minimize the number of live variables in each disjunctive component. We use the live variables to simplify transition relations and reachable state subsets. Our experiments on a set of real-world C programs show that the new algorithm achieves orders-of-magnitude performance improvement over the best known conjunctive image computation algorithm