A century ago, Taylor published a landmark in the organisational sciences: his Principles of Scientific Management. Many researchers have elaborated on Taylor's principles, or have been influenced otherwise. The authors of the current paper evaluate a century of enterprise development, and conclude that a paradigm shift is needed for dealing adequately with the challenges that modern enterprises face. Three generic goals are identified. The first one, intellectual manageability, is the basis for mastering complexity; current approaches fall short in assisting professionals to master the complexity of enterprises and enterprise changes. The second goal, organisational concinnity, is conditional for making strategic initiatives operational; current approaches do not, or inadequately, address this objective. The third goal, social devotion, is the basis for achieving employee empowerment as well as knowledgeable management and governance; modern employees are highly educated knowledge workers; yet, the mindset of managers has not evolved accordingly. The emerging discipline of Enterprise Engineering, as conceived by the authors, is considered to be a suitable vehicle for achieving these goals. It does so by providing new, powerful theories and effective methodologies. A theoretical framework is presented for positioning the theories, goals, and fundamentals of enterprise engineering in four classes: philosophical, ontological, ideological and technological.
Several approaches for optical flow estimation use partial differential equations to model changes in image brightness throughout time. A commonly used equation is the so-called optical flow constraint (OFC), which assumes that the image brightness is stationary with respect to time. More recently, a different constraint referred to as the extended optical flow constraint (EOFC) has been introduced, which also contains the divergence of the flow field of image brightness. There is no agreement in the literature about which of these constraints provides the best estimation of the velocity field. Two new solutions for optical flow computation are proposed, which are based on an approximation of the constraint equations. The two techniques have been used with both EOFC and OFC constraint equations. Results achieved by using these solutions have been compared with several well-known computational methods for optical flow estimation in different motion conditions. Estimation errors have also been measured and compared for different types of motion.
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