The effect of multiple knowledge sources on learning and teaching

Current paradigms for machine-based learning and teaching tend to perform their task in isolation from a rich context of existing knowledge. In contrast, the research project presented here takes the view that bringing multiple sources of knowledge to bear is of central importance to learning in complex domains. As a consequence teaching must both take advantage of and beware of interactions between new and existing knowledge. The central process which connects learning to its context is reasoning by analogy, a primary concern of this research. In teaching, the connection is provided by the explicit use of a learning model to reason about the choice of teaching actions. In this learning paradigm, new concepts are incrementally refined and integrated into a body of expertise, rather than being evaluated against a static notion of correctness. The domain chosen for this experimentation is that of learning to solve "algebra story problems." A model of acquiring problem solving skills in this domain is described, including: representational structures for background knowledge, a problem solving architecture, learning mechanisms, and the role of analogies in applying existing problem solving abilities to novel problems. Examples of learning are given for representative instances of algebra story problems. After relating our views to the psychological literature, we outline the design of a teaching system. Finally, we insist on the interdependence of learning and teaching and on the synergistic effects of conducting both research efforts in parallel

NASA space station automation: AI-based technology review

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures

Semi-automatic geometric digital twinning for existing buildings based on images and CAD drawings

Despite the emerging new data capturing technologies and advanced modelling systems, the process of geometric digital twin modelling for existing buildings still lacks a systematic and completed framework to streamline. As-is Building Information Model (BIM) is one of the commonly used geometric digital twin modelling approaches. However, the process of as-is BIM construction is time-consuming and needed to improve. To address this challenge, in this paper, a semi-automatic approach is developed to establish a systematic, accurate and convenient digital twinning system based on images and CAD drawings. With this ultimate goal, this paper summarises the state-of-the-art geometric digital twinning methods and elaborates on the methodological framework of this semi-automatic geometric digital twinning approach. The framework consists of three modules. The Building Framework Construction and Geometry Information Extraction (Module 1) defines the locations of each structural component through recognising special symbols in a floor plan and then extracting data from CAD drawings using the Optical Character Recognition (OCR) technology. Meaningful text information is further filtered based on predefined rules. In order to integrate with completed building information, the Building Information Complementary (Module 2) is developed based on neuro-fuzzy system (NFS) and the image processing procedure to supplement additional building components. Finally, the Information Integration and IFC Creation (Module 3) integrates information from Module 1 and 2 and creates as-is Industry Foundation Classes (IFC) BIM based on IFC schema. A case study using part of an office building and the results of its analysis are provided and discussed from the perspectives of applicability and accuracy. Future works and limitations are also addressed

EU accession and Poland's external trade policy

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The Relevance-Based Model of Context in Processing Puns

While the essential role context plays in the understanding of expressions and utterances has never been questioned, the way it is perceived has evolved from a static factor established prior to the process of utterance interpretation, indeed a prerequisite for processing information, to a dynamic entity which emerges in this process. The latter view is espoused by relevance theorists, who define context as “the set of premises used in interpreting an utterance” (Sperber and Wilson 1986/95: 15) and treat it as a mental construct undergoing diverse modifications as the comprehender of an utterance processes and interprets incoming verbal information and other communicative signals supplied by the communicator. The aim of this paper is to consider the usefulness of this model of context for analyzing the derivation of meaning in puns, i.e. utterances in which, instead of its usual function of allowing the comprehender to resolve ambiguities ubiquitous in language and communication, the context plays a different role of leading him to entertain, and often to accept two diverse readings[…

Digital Image Access & Retrieval

The 33th Annual Clinic on Library Applications of Data Processing, held at the University of Illinois at Urbana-Champaign in March of 1996, addressed the theme of "Digital Image Access & Retrieval." The papers from this conference cover a wide range of topics concerning digital imaging technology for visual resource collections. Papers covered three general areas: (1) systems, planning, and implementation; (2) automatic and semi-automatic indexing; and (3) preservation with the bulk of the conference focusing on indexing and retrieval.published or submitted for publicatio