Deterministic context-free languageIn formal language theory, deterministic context-free languages (DCFL) are a proper subset of context-free languages. They are the context-free languages that can be accepted by a deterministic pushdown automaton. DCFLs are always unambiguous, meaning that they admit an unambiguous grammar. There are non-deterministic unambiguous CFLs, so DCFLs form a proper subset of unambiguous CFLs. DCFLs are of great practical interest, as they can be parsed in linear time, and various restricted forms of DCFGs admit simple practical parsers.
Food marketingFood marketing brings together the food producer and the consumer through a chain of marketing activities. Pomeranz & Adler, 2015, defines food marketing as a chain of marketing activities that takes place within the food system between a food organisation and the consumer. This has the potential to be a complicated procedure, as there are many processes that are used prior to the sale the food product. These include food processing, wholesaling, retailing, food service and transport.
Data profilingData profiling is the process of examining the data available from an existing information source (e.g. a database or a ) and collecting statistics or informative summaries about that data.
Deterministic pushdown automatonIn automata theory, a deterministic pushdown automaton (DPDA or DPA) is a variation of the pushdown automaton. The class of deterministic pushdown automata accepts the deterministic context-free languages, a proper subset of context-free languages. Machine transitions are based on the current state and input symbol, and also the current topmost symbol of the stack. Symbols lower in the stack are not visible and have no immediate effect. Machine actions include pushing, popping, or replacing the stack top.
FuturistFuturists (also known as futurologists, prospectivists, foresight practitioners and horizon scanners) are people whose specialty or interest is futurology or the attempt to systematically explore predictions and possibilities about the future and how they can emerge from the present, whether that of human society in particular or of life on Earth in general.
Cook's distanceIn statistics, Cook's distance or Cook's D is a commonly used estimate of the influence of a data point when performing a least-squares regression analysis. In a practical ordinary least squares analysis, Cook's distance can be used in several ways: to indicate influential data points that are particularly worth checking for validity; or to indicate regions of the design space where it would be good to be able to obtain more data points. It is named after the American statistician R.