Search results
Results from the WOW.Com Content Network
This framework spans every class of knowledge work that is being or is likely to be undertaken. There are seven levels or scales of knowledge work, with references for each are cited. Knowledge work (e.g., writing, analyzing, advising) is performed by subject-matter specialists in all areas of an organization.
The anticipate, recognize, evaluate, control, and confirm (ARECC) decision-making framework began as recognize, evaluate, and control.In 1994 then-president of the American Industrial Hygiene Association (AIHA) Harry Ettinger added the anticipate step to formally convey the duty and opportunity of the worker protection community to proactively apply its growing body of knowledge and experience ...
One early commercial application of information theory was in the field of seismic oil exploration. Work in this field made it possible to strip off and separate the unwanted noise from the desired seismic signal. Information theory and digital signal processing offer a major improvement of resolution and image clarity over previous analog methods.
Knowledge retention is part of knowledge management. It helps convert tacit form of knowledge into an explicit form. It is a complex process which aims to reduce the knowledge loss in the organization. [67] Knowledge retention is needed when expert knowledge workers leave the organization after a long career. [68]
Decision Making processes are strongly correlated to the level of available knowledge regarding the environment, the decision is based on. [21] Successfully using knowledge management supporting tools improves overall project performance and is an essential method for organizations with project-related work styles. [22]
Bayesian probability (/ ˈ b eɪ z i ə n / BAY-zee-ən or / ˈ b eɪ ʒ ən / BAY-zhən) [1] is an interpretation of the concept of probability, in which, instead of frequency or propensity of some phenomenon, probability is interpreted as reasonable expectation [2] representing a state of knowledge [3] or as quantification of a personal belief.
For example, based on analysis of the history of science, Kuhn concludes that "large amounts of qualitative work have usually been prerequisite to fruitful quantification in the physical sciences". [8] Qualitative research is often used to gain a general sense of phenomena and to form theories that can be tested using further quantitative research.
Uncertainty quantification (UQ) is the science of quantitative characterization and estimation of uncertainties in both computational and real world applications. It tries to determine how likely certain outcomes are if some aspects of the system are not exactly known.