Received: 25 February 2005 Revised: 29 November 2005 Accepted: 3 January 2006; Online publication date: 10 April 2006 Abstract Business operations involve many factors and relationships and are modeled as complex business process workflows. The execution of these business processes generates vast volumes of complex data. The operational data are instances of the process flow, taking different p...

Hyperspectral anomaly detection is one of the main challenging topics in both military and civilian fields. The spectral information contained in a hyperspectral cube provides a high ability for anomaly detection. In addition, the costly spatial information of adjacent pixels such as texture can also improve the discrimination between anomalous targets and background. Most studies miss the wort...

In this paper, we develop a process control approach to detect linear trends in the process mean. A statistic based on the deviation between the target mean and the expected mean of the process is used in the development of the new approach. The statistic is shown to have a Chi-square distribution. The approach is described and its performance is compared with Cumulative Sum (CUSUM), Exponentia...

Classical outlier detection approaches may hardly fit process mining applications, since in these settings anomalies emerge not only as deviations from the sequence of events most often registered in the log, but also as deviations from the behavior prescribed by some (possibly unknown) process model. These issues have been faced in the paper via an approach for singling out anomalous evolution...

Certain microstructural features of materials, such as grain size in metals, porosity in ceramics, and structural phase compositions, are important for determining mechanical properties. Many of these microstructural features have been characterized by ultrasonic wave propagation measurements, such as wave velocity and attenuation. Real-time monitoring of ultrasonic wave propagation during the ...

most of the contour detection methods suffers from some drawbacks such as noise, occlusion of objects, shifting, scaling and rotation of objects in image which they suppress the recognition accuracy. to solve the problem, this paper utilizes zernike moment (zm) and pseudo zernike moment (pzm) to extract object contour features in all situations such as rotation, scaling and shifting of object i...

in this research, the framework is presented for unsupervised change detection using multitemporal sar images based on integration clustering and level set methods. spatial correlation between pixels were considered by using contextual information. also as proposed method was used integration of gustafson-kessel clustering techniques (gkc) and level set methods for change detection. using clust...

automatic road extraction from aerial images can be very helpful in traffic control and vehicle guidance systems. most of the road detection approaches are based on image segmentation algorithms. color-based segmentation is very sensitive to light changes and consequently the change of weather condition affects the recognition rate of road detection systems. in order to reduce the light change ...