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In this paper we present an approach for the query refinement called librarian agent query refinement process, which simulates the role a human librarian plays in the searching for information resources in a library. The process consists of two phases: problem discovery, in which the potential problems (ambiguities) of the initial query are discovered and estimated and query refinement, which analyses these ambiguities in order to provide suitable modification of that query that increases the precision and recall of the searching process. The agent performs comprehensive analyses of a query, based on the structure of the used vocabulary in an information portal and the content of its information repository. Moreover, the information about the previous users' behaviour and the activities of the current user are used for making the query refinement process more efficient (i.e. usage-driven and personalized). From the user's point of view, the main advantage of such an approach is that it enables a user to satisfy his information need in a more intuitive and efficient way.

We present a framework for query refinement that is driven by users' information needs. Since a query just approximates a user's need, we analyze the ambiguities of that query with respect to the vocabulary used for querying and the information repository. The goal is to determine the refinements that can help the user to express his original need more clearly. Particularly, a user is provided with the queries that are "nearby" the given query and a "compass" for determining the ways of changing the ambiguities of the query. The neighborhood of a query is defined regarding the result of that query. The formal concept analysis is used for its efficient calculation. We present an evaluation study that shows the benefits of our approach.

The success of the Semantic Web crucially depends on the easy creation, integration and use of semantic data. For this purpose, we consider an integration scenario that defies core assumptions of current metadata construction methods. We describe a framework of metadata creation where web pages are generated from a database and the database owner is cooperatively participating in the Semantic Web. This leads us to the deep annotation of the database directly by annotation of the logical database schema or indirectly by annotation of the Web presentation generated from the database contents. From this annotation, one may execute data mapping and/or migration steps and, thus, prepare the data for use in the Semantic Web. We consider deep annotation as particularly valid because, (i), dynamic web pages generated from databases outnumber static web pages, (ii), deep annotation may be a very intuitive way to create semantic data from a database and, (iii), data from databases should remain where it can be handled most efficiently in its databases. Interested users can then query this data directly or choose to materialize the data as RDF files.

The working Group investigated the relations between KM and BPM to increase the efficiency of enterprise collaborations in the virtual environment.

The Semantic Web is intended to enable machine understandable web content and seems to be a solution for many drawbacks of the current Web. It is based on metadata that formally describe the semantics of Web contents. In this paper we present an integrated and semi-automatic approach for generating shared-understandable metadata for data-intensive Web applications. This approach is based on mapping a given relational schema into an already existing ontology structure using a reverse engineering process. As a case study we present this style of a schema- and data-migration for our Institute web portal. The presented approach can be applied to a broad range of today’s data-intensive Web sites.

A nanofabricated electrothermal test structure is reported for directly measuring the thermal conductivity of aluminum nanowires near room temperature. Interdigitated nanowires perturb an otherwise symmetric heater-sensor structure analogous to an electrical bridge circuit. Nanowires studied are 100 nm thick with 75, 100, and 150 nm widths. Finite element simulation accounts for complex device geometry. Thermal conductivity and electrical resistivity vary significantly with nanowire dimensions. Electron transport equation models which adequately describe the resistivity data consistently underestimate the thermal conductivity. Incorporating a phonon contribution of ∼21 W/m K to the total thermal conductivity is found to accurately describe the measured values.

InGaN quantum well (QW) microrings were grown using selective area epitaxy on patterned (0001) AlN/sapphire. The well defined shapes are comprised of {112¯2} and {213¯3} facets on inner sidewalls, and {11¯01} facets on outer sidewalls, as well as (0001) top surfaces. The sidewall facets exhibit distinct emission spectra when investigated using cathodoluminescence. Differences in emission spectra are attributed to variations in growth rate and indium incorporation on the facets, with peak emission wavelength as long as 500 nm. The observed weak blueshift with increasing cathodoluminescence excitation current verifies that the internal piezoelectric fields of the semipolar sidewall facets are lower than reference (0001) InGaN QWs.

Metal-organic chemical vapor deposition has been used for selective epitaxy of GaN pyramids ranging in size from over 1μm to 500 nm in length at the base. Pyramids are terminated by {11¯01} crystal facets. The optical properties of the pyramids are investigated by cathodoluminescence (CL) in a scanning electron microscope. CL spectrum imaging reveals the pyramid apices to emit light at ∼363.4 nm corresponding to the emission wavelength of relaxed GaN. As the CL excitation is moved away from the apex a systematic redshift is observed. The redshift is ∼4 nm for pyramids with 3 μm base dimension and ∼2 nm for the 500 nm pyramids. The shift is attributed to diffusion of silicon and oxygen into the GaN pyramids due to SiO2 mask decomposition with negligible contribution from stress. The observations are backed by finite element simulations of diffusion and stress.

The authors report the effects of nanoscale texturing on the optical properties of GaN. The texture consists of circular holes etched in a hexagonal array with 1μm spacing. Hole diameters range from 120to700nm and depths range up to 1μm. The optical properties are studied using cathodoluminescence (CL) measurements in a scanning electron microscope. Intensity is found to increase with pore diameter, an effect they attribute to changes in the optical extraction efficiencies. A systematic redshift observed in the CL peak is attributed to local relaxation of the compressive stress present in the starting GaN epilayer.

The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University's Department of Computer Science, was pleased to present the 2009 Spring Symposium Series, held Monday through Wednesday, March 23–25, 2009 at Stanford University. The titles of the nine symposia were Agents that Learn from Human Teachers, Benchmarking of Qualitative Spatial and Temporal Reasoning Systems, Experimental Design for Real-World Systems, Human Behavior Modeling, Intelligent Event Processing, Intelligent Narrative Technologies II, Learning by Reading and Learning to Read, Social Semantic Web: Where Web 2.0 Meets Web 3.0, and Technosocial Predictive Analytics. The goal of the Agents that Learn from Human Teachers was to investigate how we can enable software and robotics agents to learn from real-time interaction with an everyday human partner. The aim of the Benchmarking of Qualitative Spatial and Temporal Reasoning Systems symposium was to initiate the development of a problem repository in the field of qualitative spatial and temporal reasoning and identify a graded set of challenges for future midterm and long-term research. The Experimental Design symposium discussed the challenges of evaluating AI systems. The Human Behavior Modeling symposium explored reasoning methods for understanding various aspects of human behavior, especially in the context of designing intelligent systems that interact with humans. The Intelligent Event Processing symposium discussed the need for more AI-based approaches in event processing and defined a kind of research agenda for the field, coined as intelligent complex event processing (iCEP). The Intelligent Narrative Technologies II AAAI symposium discussed innovations, progress, and novel techniques in the research domain. The Learning by Reading and Learning to Read symposium explored two aspects of making natural language texts semantically accessible to, and processable by, machines. The Social Semantic Web symposium focused on the real-world grand challenges in this area. Finally, the Technosocial Predictive Analytics symposium explored new methods for anticipatory analytical thinking that provide decision advantage through the integration of human and physical models.

A least-squares parameter estimation algorithm is designed to extract the thermal conductivity of metallic nanowires using a nanofabricated microelectrothermal test structure. The device is a thermal analog of a bridge circuit, such as is commonly used to measure electrical impedance. A resistive heater is positioned symmetrically between two temperature sensors. A nanowire array extends from the heater to one sensor, unbalancing the bridge temperatures. The least-squares cost function exploits the underlying symmetry of the thermal bridge circuit, reducing sensitivity to parasitic thermal conductances and other uncertain parameters. The algorithm is demonstrated on a series of aluminum nanowire arrays with varying nanowire widths. The results are shown to be consistent with predictions made using the electron thermal transport analogy.