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Level of detail in writing, sometimes known as level of abstraction, refers to three concepts: the precision in using the right words to form phrases, clauses and sentences; [1] the generality of statements; and the organisational strategy in which authors arrange ideas according to a common topic in the hierarchy of detail.
High-level and low-level, as technical terms, are used to classify, describe and point to specific goals of a systematic operation; and are applied in a wide range of contexts, such as, for instance, in domains as widely varied as computer science and business administration.
Level of detail may refer to: Level of detail (writing), the level of abstraction in written works; Level of detail (computer graphics) ...
Three levels are the minimum recommended, with additional levels for and only for items of high cost or high risk, [25] and two levels of detail at cases such as systems engineering or program management, [26] with the standard showing examples of WBS with varying depth such as software development at points going to 5 levels [27] or fire ...
Bottom-up parsing is parsing strategy that recognizes the text's lowest-level small details first, before its mid-level structures, and leaves the highest-level overall structure to last. [4] In top-down parsing , on the other hand, one first looks at the highest level of the parse tree and works down the parse tree by using the rewriting rules ...
Image resolution is the level of detail of an image. The term applies to digital images, film images, and other types of images. "Higher resolution" means more image detail. Image resolution can be measured in various ways. Resolution quantifies how close lines can be to each other and still be visibly resolved. Resolution units can be tied to ...
What reviewers say 💬. More than 1,700 five-star fans are already feeling snug as a bug under this shawl. Pro 👍 "I am 5'7" and 240 — used to weigh half this — and I swear this makes me ...
The level of detail required to ensure data quality is extremely high and is often underestimated. This is also true for the vast majority of mHealth apps, EHRs and other health related software solutions. However, some open source tools exist that examine data quality. [21]