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A methodology based on Principal Component Analysis (PCA) and clustering is evaluated for process monitoring and process analysis of a pilot-scale SBR removing nitrogen and phosphorus. The first step of this method is to build a multi-way PCA (MPCA) model using the historical process data. In the second step, the principal scores and the Q-statistics(More)
A Sequencing Batch Reactor (SBR) is a wastewater process that occurs in a unique basin working with a predefined cycle. The reactor is monitored by the pH, Oxidation Reduction Potential, Dissolved Oxygen and Temperature sensors. This work proposes a qualitative representation of process variables based on episodes for ORP and pH signals to determine the(More)
OBJECTIVES The objective was the development of a method for the automatic recognition of different types of atypical lymphoid cells. METHODS In the method development, a training set (TS) of 1,500 lymphoid cell images from peripheral blood was used. To segment the images, we used clustering of color components and watershed transformation. In total, 113(More)
Some diversity and niche amplitude parameters were applied to rangeland pastures of the Central Iberian Peninsula and to their succession stages after the periodical ploughing typical of the traditional management of these areas. Four different slopes within a large area of undulating terrain were selected for the monitoring of succession as they contained(More)
The data set of batch biological and biotechnological processes can be organized in a three-way data matrix. In this paper the usefulness of different PCA approaches for monitoring is analyzed. Different ways of unfolding and scaling of data have been applied to a pilot-scale SBR data. PCA is used to reduce the dimensionality and to remove the non-linearity(More)
The paper focuses on the development of a classification strategy to identify critic situation in batch process control. Data acquired from a batch execution is reduced by means of multiway principal component analysis in order to be assessed according to the statistical model of the process. Multiple situations have been categorized by a classification(More)
The main idea of this paper is to develop a methodology for process monitoring, fault detection and predictive diagnosis of a WasteWater Treatment Plant (WWTP). To achieve this goal, a combination of Multiway Principal Component Analysis (MPCA) and Case-Based Reasoning (CBR) is proposed. First, MPCA is used to reduce the multi-dimensional nature of online(More)
Experiences in heterogeneous application domains treated with different data mining approaches are presented in this paper: Case based reasoning and self organising maps have used to diagnose beams and pipes after analysing their responses using wavelet decomposition. Also case based reasoning methodology has been used to improve electronic circuits(More)
Safety and reliability of hydrocarbon transportation lines (pipelines) around the world represents a critical aspect for industry, operators and population. Lines failures caused by external agents, corrosion, inadequate designs, among others, generate impacts on population, environment, infrastructure and economy, besides it may be catastrophically.(More)