7447998
Semiorder database for complex activity recognition in multi-sensory environments
A prototype semiorder database used for activity recognition in multi-sensory monitoring environments is described. Activities are spatio-temporal compositions of events, which are a type of atomic semantic units for such compositions. The focus is on the temporal composition of activities from events in the presence of bounded duration of temporal uncertainty in an event occurrence. Such temporal uncertainty forces the concurrency between event occurrences to be intransitive. Under certain assumptions, a subclass of partial orders, known as semiorders, models such intransitive concurrency appropriately. The semiorder database stores events and their semiorder temporal order of occurrences. A semiorder data model and the corresponding query language that embeds a semiorder pattern language are the main constituents of the semiorder database. We demonstrate this database and queries for activity recognition in a real time environment. The demonstration also includes a transducer subsystem for detection of events.
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.
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.
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.
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.
2840997
A survey of recent advances in SAT-based formal verification
Dramatic improvements in SAT solver technology over the last decade and the growing need for more efficient and scalable verification solutions have fueled research in verification methods based on SAT solvers. This paper presents a survey of the latest developments in SAT-based formal verification, including incomplete methods such as bounded model checking and complete methods for model checking. We focus on how the surveyed techniques formulate the verification problem as a SAT problem and how they exploit crucial aspects of a SAT solver, such as application-specific heuristics and conflict-driven learning. Finally, we summarize the noteworthy achievements in this area so far and note the major challenges in making this technology more pervasive in industrial design verification flows.
685138
Tradeoffs in canonical sequential function representations
State space exploration is of prime importance in the study of finite state sequential systems, with several efforts aimed at compact representation of the state space in order to tackle the state explosion problem. In the work presented on formal verification of inductively-defined hardware, we have identified a useful class of Boolean functions called linearly inductive functions (LIFs). We explore the relationship between our LIF representation and the classic DFA (deterministic finite state automaton) representation of a sequential function, and examine the associated tradeoffs. We show that our LIF representation corresponds to a minimal reverse DFA, i.e. a minimal DFA which accepts the language consisting of the reverse input strings, where our implicit method for obtaining an LIF representation does not require explicit construction of a forward DFA. Its practical usefulness arises from our demonstration that reverse DFAs for several datapath circuits are exponentially more compact than the classic forward DFAs. Furthermore, in comparison to the traditional representation of DFAs as state transition diagrams, our LIF representations allow for state-sharing while maintaining decomposition, resulting in memory savings in practice.<<ETX>>
6738229
A comparison of point-based approaches to qualitative temporal reasoning
We address the problem of implementing general, qualitative, point-based temporal reasoning. Given a database of assertions concerning relative occurrences of points in time, we are interested in various operations on this database, including compiling the assertions into a representation that supports efficient reasoning, determining whether a database is consistent, and computing the strongest entailed relation between two points. We begin by specifying a set of operations and their corresponding algorithms, applicable to general point-based temporal domains. We next consider a special-purpose reasoner, based on series-parallel graphs, which performs very well in a temporal domain with a particular restricted structure. We discuss the notion of a metagraph, which encapsulates local structure inside metaedges and uses special purpose algorithms within such local structures, to obtain a fast general point-based reasoner. That is, specifically, we use a very fast, series-parallel graph reasoner to speed up general point-based reasoning. We also analyse the TimeGraph reasoner of Gerevini and Schubert. For purposes of comparison, we have implemented four approaches: a generic point-based reasoner, the generic point-based reasoner with a ranking heuristic, a reasoner based on series-parallel graphs, and a version of Gerevini and Schubert's TimeGraph reasoner. We compare these different approaches, as well as the original TimeGraph-II reasoner of Gerevini and Schubert, on different data sets. We conclude that the series-parallel graph reasoner provides the best overall performance: our results show that it dominated on domains exhibiting structure, and it degraded gracefully when conditions were less than ideal, in that it did worse than the generic approach by only a constant factor in this case.
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.