3072771
A practical approach for microscopy imaging data management (MIDM) in neuroscience
Current data management approaches can easily handle the relatively simple requirements for molecular biology research but not the more varied and sophisticated microscopy imaging data in neuroscience research. We developed a project-oriented experimental imaging data management system through integration of the object-relational Oracle DBMS (database management system) and a distributed file management system, the storage resource broker (SRB). The data model we developed on Oracle9i supports semantic and analytical queries and image content mining. The MIDM provides comprehensive descriptive, structural, spatial and administrative information on microscopy image datasets. The current MIDM is web accessible at http://ncmir.ucsd.edu/CCDB. This paper describes the MIDM architecture and data mode in MIDM.
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.
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.
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.
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.
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
22674996
Estimating Link Characteristics of Internet Paths With FPathchar
RESEARCH PROJECTS Understanding the design tradeoffs of cooperative streaming multicast: Cooperative end-system multicast (CEM) is emerging as a promi sing paradigm for video distribution since the bandwidth overhead of dissemi nating content is shared among the participants themselves. Prior research in CEMs h as focused either on the design of new protocols or on comparisons of complete sys tems. However, the inherent tradeoffs between different CEM designs, particu larly under a wide range of operating conditions, are not well understood. In this wo rk [1], we empirically and systematically evaluate CEM design choices. We synthes ize our results into a model that captures the inherent tradeoffs in CEMs, which i n particular, conjectures that no CEM design can simultaneously achieve low over head, low lag, and high streaming quality.
6555974
Lazy constraints and SAT heuristics for proof-based abstraction
SAT proof analysis techniques have been used recently with BMC in order to generate proof-based abstractions that preserve the correctness of the property up to a certain depth. In this paper, we propose various techniques for handling BMC constraints that are targeted at reducing the size of the abstract model while preserving bounded correctness. We propose lazy constraints, where the idea is to delay propagation of certain implied values without modifying a standard SAT solver. We propose different methods for automatic use of lazy constraints in SAT-based BMC. Their use can be regarded as a heuristic, which typically leads to significant reduction in the size of the abstract model, frequently accompanied by an overall performance improvement. We also use SAT proof analysis to loosen the user-specified environmental constraints, in order to generate smaller abstract models for conservative verification. We briefly describe other SAT-based heuristics for reducing the size of the abstract model. We have implemented our techniques in a prototype verification platform, and demonstrate their effectiveness on several large industry designs.
18557537
Localization and Register Sharing for Predicate Abstraction
In the domain of software verification, predicate abstraction has emerged to be a powerful and popular technique for extracting finite-state models from often complex source code. In this paper, we report on the application of three techniques for improving the performance of the predicate abstraction refinement loop. The first technique allows faster computation of the abstraction. Instead of maintaining a global set of predicates, we find predicates relevant to various basic blocks of the program by weakest pre-condition propagation along spurious program traces. The second technique enables faster model checking of the abstraction by reducing the number of state variables in the abstraction. This is done by re-using Boolean variables to represent different predicates in the ion. However, some predicates are useful at many program locations and discovering them lazily in various parts of the program leads to a large number of abstraction refinement iterations. The third technique attempts to identify such predicates early in the abstraction refinement loop and handles them separately by introducing dedicated state variables for such predicates. We have incorporated these techniques into NEC's software verification tool F-SOFT, and present promising experimental results for various case studies using these techniques.
24549782
Adaptive Fault Tolerant Hospital Resource Scheduling
In a distributed hospital system, different hospitals should collaborate among themselves for sharing their resources to provide better and faster service to the patients. We address the distributed hospital resource scheduling problem and apply the Generalized Partial Global Planning (GPGP) approach used for multiagent systems for the same. An adaptive coordination mechanism based on the contract net protocol is proposed to support inter-hospital collaboration. We have performed simulation studies and the experimental results show that our coordination mechanism performs better than commonly used schemes. Fault handling mechanisms are presented so that the system continues to provide service even in the presence of faults. The proposed approach is applicable in contexts other than the distributed hospital system as well.