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Article
Publication date: 1 December 1999

Sarah B. Watstein, Pascal V. Calarco and James S. Ghaphery

This article identifies and defines some of the more commonly used terms and phrases which have been used to describe the evolving online/electronic/virtual/digital library…

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Abstract

This article identifies and defines some of the more commonly used terms and phrases which have been used to describe the evolving online/electronic/virtual/digital library phenomenon. Includes examination of findings from the authors’ examination of selected keywords increasingly found in the literature of both library and information science as well as in the literature of computer science, within the context of a (1970‐1997) bibliographic search for these terms in library literature, INSPEC, and EI COMPENDEX.

Details

Reference Services Review, vol. 27 no. 4
Type: Research Article
ISSN: 0090-7324

Keywords

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Article
Publication date: 1 March 2004

Lynne U. Turman, Phyllis C. Self and Pascal V. Calarco

Librarians at Virginia Commonwealth University teach a course in Health Informatics as part of a distance learning Doctoral program for allied health professionals. This paper…

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Abstract

Librarians at Virginia Commonwealth University teach a course in Health Informatics as part of a distance learning Doctoral program for allied health professionals. This paper discusses the experience of developing and delivering a Web‐based course for the curriculum. Lessons learned fall into the categories of communication, technology, and resources.

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Reference Services Review, vol. 32 no. 1
Type: Research Article
ISSN: 0090-7324

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Article
Publication date: 16 August 2023

Fanshu Zhao, Jin Cui, Mei Yuan and Juanru Zhao

The purpose of this paper is to present a weakly supervised learning method to perform health evaluation and predict the remaining useful life (RUL) of rolling bearings.

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Abstract

Purpose

The purpose of this paper is to present a weakly supervised learning method to perform health evaluation and predict the remaining useful life (RUL) of rolling bearings.

Design/methodology/approach

Based on the principle that bearing health degrades with the increase of service time, a weak label qualitative pairing comparison dataset for bearing health is extracted from the original time series monitoring data of bearing. A bearing health indicator (HI) quantitative evaluation model is obtained by training the delicately designed neural network structure with bearing qualitative comparison data between different health statuses. The remaining useful life is then predicted using the bearing health evaluation model and the degradation tolerance threshold. To validate the feasibility, efficiency and superiority of the proposed method, comparison experiments are designed and carried out on a widely used bearing dataset.

Findings

The method achieves the transformation of bearing health from qualitative comparison to quantitative evaluation via a learning algorithm, which is promising in industrial equipment health evaluation and prediction.

Originality/value

The method achieves the transformation of bearing health from qualitative comparison to quantitative evaluation via a learning algorithm, which is promising in industrial equipment health evaluation and prediction.

Details

Engineering Computations, vol. 40 no. 7/8
Type: Research Article
ISSN: 0264-4401

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