Rabbit Anti-BPI monoclonal antibody, clone TO17-74

This paper proposes boundary parallel-like index (BPI) to describe shape features for high-resolution remote sensing image classification. Parallel-like boundary is found to be a discriminating clue which can reveal the shape regularity of segmented objects. Therefore, multi-orientation distance projections were constructed to measure and quantify parallel-like information. The discriminating ability was tested using original and segmented ground objects, respectively. The proposed BPI showed better discrimination for both original and segmented data than for other shape features, especially for buildings. This was also confirmed by the considerably higher accuracy of BPI in building classification experiments of high-resolution remote sensing imagery. It suggests the proposed BPI is useful for building related applications.

Today's business environment is filled of complex business systems that comprise of nature, technology, and human resources. As there is such a dynamic environment, business systems are highly changeable, and, therefore, cannot be fully understood just by their observation. The understanding needs proper filtering and keeping the strong elements and structuring the information about business systems and their processes in form of different models. The field of Business Process Management (BPM) is in direct relation to a series of industry standards that deal with improving the business processes. The present paper discusses some of the main issues regarding BPM and BPI (Business Process Improvement) implementation and it also contains a research conducted with the aim of providing more information on the current status of Romanian organizations in regard to adopting and implementing BPM and BPI techniques and principles in their businesses.