10464813
Building Semantic Tools for Concept-based Learning Spaces: Knowledge Bases of Strongly-Structured Models for Scientific Concepts in Advanced Digital Libraries
Applying conventional principles of knowledge organization, representation, and other semantic tools, we have constructed a model for scientific concepts and employed knowledge bases and visualization tools to represent knowledge concerning scientific concepts. Strongly-structured models, such as the integration of a taxonomy (or thesaurus) with metadata (or attribute-value pairs) and domain-specific markup languages, as well as specialized models for learning scientific concepts, focus on such attributes as objective representations, operational semantics, use, and interrelationships of concepts. All of these play important roles in constructing representations of knowledge in most domains of science. Instructional activities for undergraduate teaching and learning are greatly facilitated with the use of such integrated semantic tools.
12375394
The Alexandria digital earth prototype
This note summarizes the system development activities of the Alexandr ia Digital Earth Prototype (ADEPT) Project.5 ADEPT and the Alexandria Digital Library (ADL) are, respectively, the research and operational components of the Alexandria Digital Library Project. The goal of ADEPT is to build a distributed digital library (DL) of personalized collections of geospatially referenced information. This DL is characterized by: (1) services for building, searching, and using personalized collections; (2) collections of georeferenced multimedia information, including dynamic simulation models of spatially distributed processes; and (3) user interfaces employing the concept of a “Digital Earth”. Important near-term objectives for ADEPT are to build prototype collections that support undergraduate learning in physical, human, and cultural geography and related disciplines, and then to evaluate whether using such resources helps students learn to reason scientifically. Collections and services developed by ADEPT researchers will migrate to ADL as they mature.
7260476
Visual Explorations for the Alexandria Digital Earth Prototype
The Alexandria Digital Earth Prototype project addresses issues of access, browsing, delivery and understanding of georeferenced library items. Two visualization approaches that address these issues in different ways are under development: interfaces between some existing digital earth systems and the digital library, and spatial but nongeoreferenced information spaces. Both the abstract spatial and georeferenced projects are being evaluated for their educational potential in classroom and lectures, in labs and as tools for students to use on their own.
9064289
Automatic Pattern Embedding in Protein Structure Models
This article describes an implementation of a set of rules for automatically embedding a minimal functional sequence pattern in a structural hidden Markov model. The final product is a library of wide ranging fold models with encoded information about the functional families.
1987929
Using speakeasy for ad hoc peer-to-peer collaboration
Peer-to-peer systems appear promising in terms of their ability to support ad hoc, spontaneous collaboration. However, current peer-to-peer systems suffer from several deficiencies that diminish their ability to support this domain, such as inflexibility in terms of discovery protocols, network usage, and data transports. We have developed the Speakeasy framework, which addresses these issues, and supports these types of applications. We show how Speakeasy addresses the shortcomings of current peer-to-peer systems, and describe a demonstration application, called Casca, that supports ad hoc peer-to-peer collaboration by taking advantages of the mechanisms provided by Speakeasy.
15703762
Armi: a High Level Communication Library for Stapl
ARMI is a communication library that provides a framework for expressing fine-grain parallelism and mapping it to a particular machine using shared-memory and message passing library calls. The library is an advanced implementation of the RMI protocol and handles low-level details such as scheduling incoming communication and aggregating outgoing communication to coarsen parallelism. These details can be tuned for different platforms to allow user codes to achieve the highest performance possible without manual modification. ARMI is used by STAPL, our generic parallel library, to provide a portable, user transparent communication layer. We present the basic design as well as the mechanisms used in the current Pthreads/OpenMP, MPI implementations and/or a combination thereof. Performance comparisons between ARMI and explicit use of Pthreads or MPI are given on a variety of machines, including an HP-V2200, Origin 3800, IBM Regatta and IBM RS/6000 SP cluster.
668272
First Results in the Coordination of Heterogeneous Robots for Large-Scale Assembly
While many multi-robot systems rely on fortuitous cooperation between agents, some tasks, such as the assembly of large structures, require tighter coordination. We present a general software architecture for coordinating heterogeneous robots that allows for both autonomy of the individual agents as well as explicit coordination. This paper presents recent results with three robots with very different configurations. Working as a team, these robots are able to perform a high-precision docking task that none could achieve individually.
6685885
Comprehensive statistical method for protein fold recognition
We present a protein fold recognition method that uses a comprehensive statistical interpretation of structural Hidden Markov Models (HMMs). The structure/fold recognition is done by summing the probabilities of all sequence-to-structure alignments Conventionally, Boltzmann statistics dictate that the optimal alignment can give an estimate of the lowest free energy of the sequence conformation imposed by the structural model. The alignment is optimized for a scoring function that is interpreted as a free energy of an amino acid in a structural environment. Near-optimal alignments are ignored, regardless of how likely they might be compared to the optimal alignment. Here we investigate an alternative view. A structure model can be seen as a statistical representation of an ensemble of similar structures. The optimal alignment is always the most probable, but sub-optimal alignments may have comparable probabilities. These sub-optimal alignments can be interpreted as optimal alignments to the “other” structures from the ensemble or optimal alignments under minor fluctuations in the scoring function. Summing probabilities for all alignments gives an estimate of sequence-model compatibility. We have built a set of structural HMMs for 188 protein structures, and have compared two methods for identifying the structure compatible with a sequence: by the optimal alignment probability and by the total probability. Fold recognition by total probability was 40% more accurate than fold recognition by the optimal alignment probability.