General method of pattern classification using the two-domain theory

Human beings judge patterns (such as images) by complex mental processes, some of which may not be known, while computing machines extract features. By representing the human judgements with simple measurements and reducing them and the machine extracted features to a common metric space and fitting them by regression, the judgements of human experts rendered on a sample of patterns may be imposed on a pattern population to provide automatic classification

Introduction to Library Trends 38 (4) Spring 1990: Intellectual Access to Graphic Information

published or submitted for publicatio

A vector-product information retrieval system adapted to heterogeneous, distributed computing environments

Vector-product information retrieval (IR) systems produce retrieval results superior to all other searching methods but presently have no commercial implementations beyond the personal computer environment. The NASA Electronic Library Systems (NELS) provides a ranked list of the most likely relevant objects in collections in response to a natural language query. Additionally, the system is constructed using standards and tools (Unix, X-Windows, Notif, and TCP/IP) that permit its operation in organizations that possess many different hosts, workstations, and platforms. There are no known commercial equivalents to this product at this time. The product has applications in all corporate management environments, particularly those that are information intensive, such as finance, manufacturing, biotechnology, and research and development

Method and apparatus for filtering visual documents

A method and apparatus for producing an abstract or condensed version of a visual document is presented. The frames comprising the visual document are first sampled to reduce the number of frames required for processing. The frames are then subjected to a structural decomposition process that reduces all information in each frame to a set of values. These values are in turn normalized and further combined to produce only one information content value per frame. The information content values of these frames are then compared to a selected distribution cutoff point. This effectively selects those values at the tails of a normal distribution, thus filtering key frames from their surrounding frames. The value for each frame is then compared with the value from the previous frame, and the respective frame is finally stored only if the values are significantly different. The method filters or compresses a visual document with a reduction in digital storage on the ratio of up to 700 to 1 or more, depending on the content of the visual document being filtered

Major Field Change of College Students: Academic and Sociological Correlates

Purpose: The purpose of the study was to identify academic and sociological correlates which may determine speci f ic student populations showing tendencies to change major f ields. Procedure: The research sample (N = 59 7) consisted of University of North Dakota students who were f i rs t - t ime, full- time students in the 1982 fall semester and who continued enrollment through or graduated by the 198 6 spring semester. These students also had an ACT composite score on record. Selected information was obtained from the Student Profile Section of the American College Test (ACT) Assessment , the Student Information Form of the Cooperative Institutional Research Program, and the Student Record System of the University of North Dakota. Change of major was defined as a change between two academic majors characterized by changes in major codes on the Student Record System. For those students who were undecided upon initial enrollment, the change from undecided to the first academic major declared was not considered a change of major. Conclusions: 1. Students who were undecided upon initial enrollment changed majors significantly fewer times than students who were decided. 2. There were no significant rela tionships between change of major frequency and students\u27 sel f -professed indications of sureness of major and occupational choice s , need for a s s i s tanc e in deciding educational and vocat ional plans, and chance of changing major field and career choic e s . 3. Students from smaller graduating c la s s e s or with lower high school grade point averages made significantly more changes of majors than students from larger graduating c la s s e s or those with higher grade point averages. However, the size of the graduating c la s s e s and the grade point averages explained minimal variance in change of major frequency. 4 . No signif icant relationships were found between change of major frequency and parental levels of education, previous work experience, vocat ional coursework studied, high school academic rank, and ACT composite score. 5. Students with more frequent major changes had significantly lower cumulative grade point averages and earned le s s credit hours than students changing le s s frequently. However, change of major frequency explained minimal variance in cumulative grade point averages and credit hours earned

General method of pattern classification using the two-domain theory

Human beings judge patterns (such as images) by complex mental processes, some of which may not be known, while computing machines extract features. By representing the human judgements with simple measurements and reducing them and the machine extracted features to a common metric space and fitting them by regression, the judgements of human experts rendered on a sample of patterns may be imposed on a pattern population to provide automatic classification

Citizen participation in the design process of public plazas

Call number: LD2668 .T4 1986 R67Master of Landscape Architectur

Automatic Metadata Generation using Associative Networks

In spite of its tremendous value, metadata is generally sparse and incomplete, thereby hampering the effectiveness of digital information services. Many of the existing mechanisms for the automated creation of metadata rely primarily on content analysis which can be costly and inefficient. The automatic metadata generation system proposed in this article leverages resource relationships generated from existing metadata as a medium for propagation from metadata-rich to metadata-poor resources. Because of its independence from content analysis, it can be applied to a wide variety of resource media types and is shown to be computationally inexpensive. The proposed method operates through two distinct phases. Occurrence and co-occurrence algorithms first generate an associative network of repository resources leveraging existing repository metadata. Second, using the associative network as a substrate, metadata associated with metadata-rich resources is propagated to metadata-poor resources by means of a discrete-form spreading activation algorithm. This article discusses the general framework for building associative networks, an algorithm for disseminating metadata through such networks, and the results of an experiment and validation of the proposed method using a standard bibliographic dataset

The TREC2001 video track: information retrieval on digital video information

The development of techniques to support content-based access to archives of digital video information has recently started to receive much attention from the research community. During 2001, the annual TREC activity, which has been benchmarking the performance of information retrieval techniques on a range of media for 10 years, included a ”track“ or activity which allowed investigation into approaches to support searching through a video library. This paper is not intended to provide a comprehensive picture of the different approaches taken by the TREC2001 video track participants but instead we give an overview of the TREC video search task and a thumbnail sketch of the approaches taken by different groups. The reason for writing this paper is to highlight the message from the TREC video track that there are now a variety of approaches available for searching and browsing through digital video archives, that these approaches do work, are scalable to larger archives and can yield useful retrieval performance for users. This has important implications in making digital libraries of video information attainable

A new machine classification method applied to human peripheral blood leukocytes

Human beings judge images by complex mental processes, whereas computing machines extract features. By reducing scaled human judgments and machine extracted features to a common metric space and fitting them by regression, the judgments of human experts rendered on a sample of images may be imposed on an image population to provide automatic classification