36 resultados para Mining Equipment


Relevância:

20.00% 20.00%

Publicador:

Resumo:

This paper focuses on document data, one of the most significant sources for technology intelligence. To help organisations use their knowledge in documents effectively, this research aims to identify what organizations really want from documents and what might be possible to obtain from them. The research involves a literature review, a series of in-depth/on-site interviews and a descriptive analysis of document mining applications. The output of the research includes: a document mining framework; an analysis of the current condition of document mining in technology-based organisations together with their future requirements; and guidelines for introducing document mining into an organisation along with a discussion on the practical issues that are faced by users. Copyright © 2011 Inderscience Enterprises Ltd.

Relevância:

20.00% 20.00%

Publicador:

Resumo:

Vision-based object detection has been introduced in construction for recognizing and locating construction entities in on-site camera views. It can provide spatial locations of a large number of entities, which is beneficial in large-scale, congested construction sites. However, even a few false detections prevent its practical applications. In resolving this issue, this paper presents a novel hybrid method for locating construction equipment that fuses the function of detection and tracking algorithms. This method detects construction equipment in the video view by taking advantage of entities' motion, shape, and color distribution. Background subtraction, Haar-like features, and eigen-images are used for motion, shape, and color information, respectively. A tracking algorithm steps in the process to make up for the false detections. False detections are identified by catching drastic changes in object size and appearance. The identified false detections are replaced with tracking results. Preliminary experiments show that the combination with tracking has the potential to enhance the detection performance.

Relevância:

20.00% 20.00%

Publicador:

Resumo:

This research proposes a method for extracting technology intelligence (TI) systematically from a large set of document data. To do this, the internal and external sources in the form of documents, which might be valuable for TI, are first identified. Then the existing techniques and software systems applicable to document analysis are examined. Finally, based on the reviews, a document-mining framework designed for TI is suggested and guidelines for software selection are proposed. The research output is expected to support intelligence operatives in finding suitable techniques and software systems for getting value from document-mining and thus facilitate effective knowledge management. Copyright © 2012 Inderscience Enterprises Ltd.

Relevância:

20.00% 20.00%

Publicador:

Resumo:

Most research on technology roadmapping has focused on its practical applications and the development of methods to enhance its operational process. Thus, despite a demand for well-supported, systematic information, little attention has been paid to how/which information can be utilised in technology roadmapping. Therefore, this paper aims at proposing a methodology to structure technological information in order to facilitate the process. To this end, eight methods are suggested to provide useful information for technology roadmapping: summary, information extraction, clustering, mapping, navigation, linking, indicators and comparison. This research identifies the characteristics of significant data that can potentially be used in roadmapping, and presents an approach to extracting important information from such raw data through various data mining techniques including text mining, multi-dimensional scaling and K-means clustering. In addition, this paper explains how this approach can be applied in each step of roadmapping. The proposed approach is applied to develop a roadmap of radio-frequency identification (RFID) technology to illustrate the process practically. © 2013 © 2013 Taylor & Francis.