A great deal of academic research, particularly in the social sciences, makes an implicit assumption that the processes being investigated are largely decomposable, meaning that the effects of individual variables identified in one context are likely to be observed in other contexts as well. Many of the statistical tools employed in analyzing social science data, such as regression and structur...

Up to now there is neither data available on how many errors can be expected in process model collections, nor is it understood why errors are introduced. In this article, we provide empirical evidence for these questions based on the SAP reference model. This model collection contains about 600 process models expressed as Eventdriven Process Chains (EPCs). We translated these EPCs into YAWL mo...

Forest fires are one of the most dangerous natural hazards, especially when they are recurrent. In areas such as Galicia (Spain), forest fires are frequent and devastating. The development of fire risk models becomes a very important prevention task for these regions. Vegetation and moisture indices can be used to monitor vegetation status; however, the different indices may perform differently...

caesarean section (c-section) rates have been increasing dramatically in the past decades around the world. this increase has been attributed to multiple factors such as maternal, socio-demographic and institutional fac-tors. therefore, this study examines the impact of maternal, socio-demographic and relevant characteristics on caesar-ean delivery in the northern region of bangladesh.this stud...

چکیده شناسایی رقومی خاک ها بهعنوان ابزاری برای ایجاد اطلاعات مکانی خاک، راه حل هایی برای نیاز رو به افزایش نقشه های خاک با تفکیک مکانی بالا را تأمین می کند. بنابراین، باید روش های جدید بهمنظور بهدست آوردن اطلاعات مکانی خاک با تفکیک مکانی بالا توسعه پیدا کند. به همین منظور مطالعه ای جهت پیش بینی کلاس های خاک با استفاده از مدل های رگرسیونی در منطقه زرند کرمان طراحی گردید. در این مطالعه، مدل های ر...

The purpose of the paper was to extract important features of children’s mathematical gift by using neural networks and logistic regression, in order to create a model that will assist teachers in elementary schools to recognize mathematically gifted children in an early stage, therefore enabling further development and realization of that gift. The initial model was created on the basis of a t...

This study applied logistic regression to model urban growth in the Atlanta Metropolitan Area of Georgia in a GIS environment and to discover the relationship between urban growth and the driving forces. Historical land use/cover data of Atlanta were extracted from the 1987 and 1997 Landsat TM images. Multi-resolution calibration of a series of logistic regression models was conducted from 50 m...

Although researchers have long studied using statistical modeling techniques to detect anomaly intrusion and profile user behavior, the feasibility of applying multinomial logistic regression modeling to predict multi-attack types has not been addressed, and the risk factors associated with individual major attacks remain unclear. To address the gaps, this study used the KDD-cup 1999 data and b...

The author proposes a new method for flexible regression modeling of multi-dimensional data, where the regression function is approximated by a linear combination of logistic basis functions. The method is adaptive, selecting simple or more complex models as appropriate. The number, location, and (to some extent) shape of the basis functions are automatically determined from the data. The metho...