Search results
Results from the WOW.Com Content Network
This vector builds on each of the ones which comes before it. It involves becoming comfortable with oneself. This includes physical appearance, gender and sexual identity, ethnicity, and social roles. It also includes becoming stable and gaining self-esteem. A person who has a well-developed identity can handle feedback and criticism from others.
Flow is an individual experience and the idea behind flow originated from the sports-psychology theory about an Individual Zone of Optimal Functioning. The individuality of the concept of flow suggests that each person has their subjective area of flow, where they would function best given the situation.
A cognitive model is a representation of one or more cognitive processes in humans or other animals for the purposes of comprehension and prediction. There are many types of cognitive models, and they can range from box-and-arrow diagrams to a set of equations to software programs that interact with the same tools that humans use to complete tasks (e.g., computer mouse and keyboard).
The vector model of emotion appeared in 1992. [16] This two-dimensional model consists of vectors that point in two directions, representing a "boomerang" shape. The model assumes that there is always an underlying arousal dimension, and that valence determines the direction in which a particular emotion lies.
Stock and flow diagrams - a way to quantify the structure of a dynamic system; These methods allow showing a mental model of a dynamic system, as an explicit, written model about a certain system based on internal beliefs. Analyzing these graphical representations has been an increasing area of research across many social science fields. [9]
System properties are defined in terms of the behavior. The system = (,,) is said to be "linear" if is a vector space and is a linear subspace of , "time-invariant" if the time set consists of the real or natural numbers and
Get AOL Mail for FREE! Manage your email like never before with travel, photo & document views. Personalize your inbox with themes & tabs. You've Got Mail!
A flow-based generative model is a generative model used in machine learning that explicitly models a probability distribution by leveraging normalizing flow, [1] [2] [3] which is a statistical method using the change-of-variable law of probabilities to transform a simple distribution into a complex one.