Maturity model of Knowledge Management in the interpretativist perspective

Many authors have proposed categorizations for approaches to Knowledge Management; outstanding prospects including functionalist and interpretativist. In the first approach, knowledge is considered as a “static object” that exists in a number of ways and locations; in the second one, knowledge does not exist independently of human experience, social practice, of knowledge itself and its use, where it is shared by the social practices of communities, because it is “dynamic and active”. These articles constitute an extensive review on the subject, focused in reviewing, analyzing and presenting a study of the interpretativist perspective, and describe a maturity model for KM operational from it.     

Toward a theory of collection development: an activities and attributes approach

This paper presents results of a study of corporate library selection activity performed to support four global corporations. The firms examined are involved in providing communication, knowledge in its different forms, and computing. Using these results, this paper synthesizes literature on selection and collection development to present an approach to developing an eventual theory of collection development. Using this approach, such a theory would predict the performance of selection activity; the operation of its attributes, such as its cost, centralization, and formalization; and the operation of other collection development activities. Concurrently, it would explain these predictions using dynamics such as the need to include specified ideas within selected content, the need to cope with selector's abilities to choose vast amounts of content, the need to contain selection cost, and the need to gather material together so as to support browsing and its resulting impromptu development of ideas.     

Real-time output trajectory tracking neural sliding mode controller for induction motors

This paper deals with real-time discrete adaptive output trajectory tracking for induction motors in the presence of bounded disturbances. A recurrent high order neural network structure is used to design a nonlinear observer and based on this model, a discrete-time control law is derived, which combines discrete-time block control and sliding modes techniques. Applicability of the scheme is illustrated via experimental results in real-time for a three phase induction motor.