62571539
Integrating brain data spatially: spatial data infrastructure and atlas environment for online federation and analysis of brain images
Numerous digital atlases of the brain have been developed for different species through the efforts of researchers around the world. For a comprehensive picture of brain morphology and function, it is important to discover and bring together various images, segmentations and markup, generated within different projects, and juxtapose them within a single federated atlas interface. This paper describes strategies and tools for integrating distributed sources of brain data spatially. We focus on the organization of Web-enabled spatial data sources, which include ArcIMS feature and image services and distributed grid sources, and on the Smart Atlas, a GIS-based atlas environment enabling users to discover, access, visualize and query heterogeneous images and image markup. We demonstrate construction of spatial databases from unorganized vector and raster brain data based on ontological relationships between anatomical features from the unified medical language system, spatial registration mechanisms, and tools and user interfaces for federated brain data visualization and analysis.
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.
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.
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.
195611449
Scheduling tasks in multiprocessor systems using evolutionary strategies
Scheduling tasks in multiprocessor systems is a difficult problem. The paper describes a method based upon evolutionary strategies (using genetic algorithms) to aid in finding good task assignments. The technique is illustrated by scheduling a digital signal processing algorithm on a two processor distributed system.<<ETX>>
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
14365594
Symbolic Model Checking of Concurrent Programs Using Partial Orders and On-the-Fly Transactions
The state explosion problem is one of the core bottlenecks in the model checking of concurrent software. We show how to ameliorate the problem by combining the ability of partial order techniques to reduce the state space of the concurrent program with the power of symbolic model checking to explore large state spaces. Our new verification methodology involves translating the given concurrent program into a circuit-based model which gives us the flexibility to then employ any model checking technique of choice - either SAT or BDD-based - for verifying a broad range of linear time properties, not just safety. The reduction in the explored state-space is obtained by statically augmenting the symbolic encoding of the program by additional constraints. These constraints restrict the scheduler to choose from a minimal conditional stubborn set of transitions at each state. Another key contribution of the paper, is a new method for detecting transactions on-the-fly which takes into account patterns of lock acquisition and yields better reductions than existing methods which rely on a lockset based analysis. Moreover unlike existing techniques, identifying on-the-fly transactions does not require the program to follow a lock discipline in accessing shared variables. We have applied our techniques to the Daisy test bench and shown the existence of several bugs.
5025109
Embedding Complete Binary Trees into Butterfly Networks
The authors present embeddings of complete binary trees into butterfly networks with or without wrap-around connections. Let m be an even integer and q=m+(log m)-1. The authors show how to embed a 2/sup q+1/-1-node complete binary tree T(q) into a (m+1)2/sup m+1/-node wrap-around butterfly B/sub w/(m+1) with a dilation of 4, and how to embed T(q) into a (m+2)2/sup m+2/-node wrap-around butterfly B/sub w/(m+2) with an optimal dilation of 2. They also present an embedding of a wrap-around butterfly B/sub w/(m) into a (m+1)2/sup m/-node no-wrap-around butterfly B(m) with a dilation of 3. Using this embedding it is shown that T(q) can be embedded into a no-wrap butterfly B(m+1) (resp. B(m+2)) with a dilation of 8 (resp. 5). >
6027825
Generalized compressed tree machines
Parallel machines interconnecting up to thousands of processors have been proposed and recently built. One of the earliest and the most prominent one is a complete binary tree machine. The authors propose a family of tree machines called generalized compressed tree machines. Generalized compressed tree machines may, in general, be viewed as a derivative of the complete binary tree networks.<<ETX>>