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The dynamometer card is a main method to analyze downhole working conditions of the beam pumping unit in actual operation. For computer based diagnosis mode, a method based on 16-directions chain codes and K-means clustering is proposed in this paper. First, the 16-directions chain codes are used to recreate boundary contour curve of the dynamometer card; then seven feature vectors which can accurately...
With the completion of the Human Genome Project, proteomics research has become one of the most important topics in the fields of life science and natural science. The project determined that proteins participate in life activities mainly in the form of complexes. At present, research on protein-protein interaction networks (PPINs) have mainly focused on detecting protein complexes or function modules...
Treatment based on the syndrome differentiation is the key of traditional Chinese medicine (TCM) treating acquired immune deficiency syndrome (AIDS). Syndrome differentiation, where the patients suffering from a western medicine disease are divided into several classes based on their symptoms and signs, is an important diagnostic method and affects the effective use of TCM treatments. Some researches...
Dynamometer cards are commonly used to analyze down-hole conditions of beam pumping units in practical oil production. In the literature, supervised learning based methods heavily rely on training samples. In order to realize unsupervised learning of fault diagnosis for down-hole conditions, a method based on an improved fuzzy Iterative Self-Organizing Data Analysis Technique (ISODATA) with “merging”...
At present, the region growing algorithm has been used as a segmentation technique of digital images. Most region growing algorithms are using fixed or determinate criterions to distinguish disease spots from leaf image with gray level differences between leaf and disease spot. But in practice, the objects in the disease leaf image have fuzziness and uncertainty, and edges of the objects are unclear...
Outlier detection is the process of detecting the data objects which are grossly different from or inconsistent with the remaining set of data. Some of the important applications in the field of data mining are fraud detection, customer behavior analysis, and intrusion detection. There are number of good research algorithms for detecting outliers if the entire data is available and algorithms can...
Anomaly detection is currently an important and active research problem in many fields and involved in numerous applications. Most of the existing methods are based on distance measure. But in case of data stream these methods are not very efficient as computational point of view. Most of the exiting work on outlier detection in data stream declare a point as an outlier/inlier as soon as it arrive...
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