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Multivariate calibration models using NIR spectroscopy on pulp and paper industrial applications
A goal for the pulp and paper industry is to get a fast and reliable characterization of raw materials as wood and pulp compositions. One possibility for this is near infrared reflectance (NIR)Expand
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Detection of kappa number distributions in kraft pulps using nir spectroscopy and multivariate calibration
Chemical pulp is characterized by its average lignin content, commonly expressed as the pulp-kappa number. However, this average kappa number provides no information about the distribution of kappaExpand
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Automatic grading of Scots pine (Pinus sylvestris L.) sawlogs using an industrial X-ray log scanner
Abstract The successful running of a sawmill is dependent on its ability to achieve the highest possible value recovery from the sawlogs, i.e. to optimize the use of the raw material. SuchExpand
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2D wavelet analysis and compression of on‐line industrial process data
In recent years the wavelet transform (WT) has interested a large number of scientists from many different fields. Pattern recognition, signal processing, signal compression, process monitoring andExpand
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Strategies for implementation and validation of on‐line models for multivariate monitoring and control of wood chip properties
Here we present an approach for on‐line control and monitoring of pulpwood chip properties based on near infrared (NIR) spectroscopy and multivariate data analysis. In addition, this paper suggestsExpand
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Multivariate data analysis of multivariate populations
For data that can be arranged in populations, multivariate data analysis of digitalized distributions is suggested as an alternative method to detect variations. This approach includes aExpand