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.
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.
10145188
Towards a formalization of disease-specific ontologies for neuroinformatics
We present issues arising when trying to formalize disease maps, i.e. ontologies to represent the terminological relationships among concepts necessary to construct a knowledge-base of neurological disorders. These disease maps are being created in the context of a large-scale data mediation system being created for the Biomedical Informatics Research Network (BIRN). The BIRN is a multi-university consortium collaborating to establish a large-scale data and computational grid around neuroimaging data, collected across multiple scales. Test bed projects within BIRN involve both animal and human studies of Alzheimer's disease, Parkinson's disease and schizophrenia. Incorporating both the static 'terminological' relationships and dynamic processes, disease maps are being created to encapsulate a comprehensive theory of a disease. Terms within the disease map can also be connected to the relevant terms within other ontologies (e.g. the Unified Medical Language System), in order to allow the disease map management system to derive relationships between a larger set of terms than what is contained within the disease map itself. In this paper, we use the basic structure of a disease map we are developing for Parkinson's disease to illustrate our initial formalization for disease maps.
29770608
Ontology services for curriculum development in NSDL
We describe our effort to develop an ontology service on top of an educational digital library. The ontology is developed by relating library holdings to the educational concepts they refer to. The ontology system supports basic services like ontology-based search and complex services such as comparison of multiple curricula.
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.
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.
5331854
On the Scalable Computation of Large Sets of Integrals
We consider efficient strategies for the parallel and distributed computation of large sets of multivariate integrals. These arise in many applications such as computational chemistry, high energy physics and finite element problems. We use a hierarchical architecture which is highly scalable and allows parallelization not only at the domain level but also at the integral level. We present experimental results on a family of parametrized integrals and show that our approach leads to an efficient scalable load balanced algorithm. The methods are easily applicable to other areas where a large number of problems need to be solved efficiently on a parallel and distributed system.
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
10298588
Using Statically Computed Invariants Inside the Predicate Abstraction and Refinement Loop
Predicate abstraction is a powerful technique for extracting finite-state models from often complex source code. This paper reports on the usage of statically computed invariants inside the predicate abstraction and refinement loop. The main idea is to selectively strengthen (conjoin) the concrete transition relation at a given program location by efficiently computed invariants that hold at that program location. We experimentally demonstrate the usefulness of transition relation strengthening in the predicate abstraction and refinement loop. We use invariants of the form ±x ±y ≤c where c is a constant and x,y are program variables. These invariants can be discovered efficiently at each program location using the octagon abstract domain. We observe that the abstract models produced by predicate abstraction of strengthened transition relation are more precise leading to fewer spurious counterexamples, thus, decreasing the total number of abstraction refinement iterations. Furthermore, the length of relevant fragments of spurious traces needing refinement shortens. This leads to an addition of fewer predicates for refinement. We found a consistent reduction in the total number of predicates, maximum number of predicates tracked at a given program location, and the overall verification time.
37922436
Improved Bandwidth Approximation for Trees and Chordal Graphs
A linear arrangement of an n-vertex graph G=(V,E) is a one?one mapping f of the vertex set V onto the set n]={0,1,?,n?1}. The bandwidth of this linear arrangement is the maximum difference between the images of the endpoints of any edge in E(G). When the input graph G is a tree, the best known approximation algorithms for the minimum bandwidth linear arrangement (which are based on the principle of volume respecting embeddings) output a linear arrangement which has bandwidth within O(log3n) of the optimal bandwidth. In this paper, we present a simple randomized O(log2.5n)-approximation algorithm for bandwidth minimization on trees. We also show that a close variant of this algorithm gives a similar performance guarantee for chordal graphs.
10440176
Task assignment with imprecise information for real-time operation in a supply chain
Abstract Real-time operation is often required in a supply chain, where it is desirable to re-optimize the schedules each time a new order is submitted. An organization in a supply chain may not be able to perform all the tasks it has received completely due to lack of resources. It has to delegate those subtasks which it cannot perform to its suppliers in the supply chain. In a practical situation, the suppliers may be parts of more than one supply chain. Hence the organization does not have a complete control over the schedules of its suppliers. There should be coordination within and across organizations for producing the schedules. Usually, multiple objectives (or criteria) like quality, cost, and duration are associated with a task. Preference ratings, assigned by the end-user or the organization itself, may be associated with these criteria. The preference ratings may be specified in an imprecise manner by using ordinal values or linguistic terms. The assignment of the tasks to the suppliers, which is a multiobjective decision making problem, has to be done quickly for real-time operation. In this paper, a supply chain is first modeled using a multiagent framework and an architecture for the agents located at every organization in the chain is presented. We then propose a real-time scheduler that can schedule new orders with soft real-time deadlines. An algorithm for the task assignment using the fuzzy set approach for the real-time operation in a supply chain is then proposed. Comparison of the algorithm versus other commonly used heuristic methods for task assignment is done in a simulated environment. The experimental results show significant performance gains for a large range of task arrival rates. However, the performance deteriorates for very high arrival rates. In order to overcome this limitation, we present a hybrid algorithm that augments the fuzzy technique and does not suffer from performance degradation even for high arrival rates.