Standardized testA standardized test is a test that is administered and scored in a consistent, or "standard", manner. Standardized tests are designed in such a way that the questions and interpretations are consistent and are administered and scored in a predetermined, standard manner. Any test in which the same test is given in the same manner to all test takers, and graded in the same manner for everyone, is a standardized test. Standardized tests do not need to be high-stakes tests, time-limited tests, or multiple-choice tests.
Invariant subspace problemIn the field of mathematics known as functional analysis, the invariant subspace problem is a partially unresolved problem asking whether every bounded operator on a complex Banach space sends some non-trivial closed subspace to itself. Many variants of the problem have been solved, by restricting the class of bounded operators considered or by specifying a particular class of Banach spaces.
Minimally conscious stateA minimally conscious state or MCS is a disorder of consciousness distinct from persistent vegetative state and locked-in syndrome. Unlike persistent vegetative state, patients with MCS have partial preservation of conscious awareness. MCS is a relatively new category of disorders of consciousness. The natural history and longer term outcome of MCS have not yet been thoroughly studied. The prevalence of MCS was estimated to be 9 times of PVS cases (adult and pediatric), or between 112,000 and 280,000 in the US by year 2000.
Database normalizationDatabase normalization or database normalisation (see spelling differences) is the process of structuring a relational database in accordance with a series of so-called normal forms in order to reduce data redundancy and improve data integrity. It was first proposed by British computer scientist Edgar F. Codd as part of his relational model. Normalization entails organizing the columns (attributes) and tables (relations) of a database to ensure that their dependencies are properly enforced by database integrity constraints.
Hilbert spaceIn mathematics, Hilbert spaces (named after David Hilbert) allow the methods of linear algebra and calculus to be generalized from (finite-dimensional) Euclidean vector spaces to spaces that may be infinite-dimensional. Hilbert spaces arise naturally and frequently in mathematics and physics, typically as function spaces. Formally, a Hilbert space is a vector space equipped with an inner product that induces a distance function for which the space is a complete metric space.
Mutual intelligibilityIn linguistics, mutual intelligibility is a relationship between languages or dialects in which speakers of different but related varieties can readily understand each other without prior familiarity or special effort. It is sometimes used as an important criterion for distinguishing languages from dialects, although sociolinguistic factors are often also used. Intelligibility between languages can be asymmetric, with speakers of one understanding more of the other than speakers of the other understanding the first.
Database administratorDatabase administrators (DBAs) use specialized software to store and organize data. The role may include capacity planning, installation, configuration, database design, migration, performance monitoring, security, troubleshooting, as well as backup and data recovery. Some common and useful skills for database administrators are: Knowledge of database queries Knowledge of database theory Knowledge of database design Knowledge about the RDBMS itself, e.g. Microsoft SQL Server or MySQL Knowledge of SQL, e.g.
Speech perceptionSpeech perception is the process by which the sounds of language are heard, interpreted, and understood. The study of speech perception is closely linked to the fields of phonology and phonetics in linguistics and cognitive psychology and perception in psychology. Research in speech perception seeks to understand how human listeners recognize speech sounds and use this information to understand spoken language.
Spectral density estimationIn statistical signal processing, the goal of spectral density estimation (SDE) or simply spectral estimation is to estimate the spectral density (also known as the power spectral density) of a signal from a sequence of time samples of the signal. Intuitively speaking, the spectral density characterizes the frequency content of the signal. One purpose of estimating the spectral density is to detect any periodicities in the data, by observing peaks at the frequencies corresponding to these periodicities.
Numerical linear algebraNumerical linear algebra, sometimes called applied linear algebra, is the study of how matrix operations can be used to create computer algorithms which efficiently and accurately provide approximate answers to questions in continuous mathematics. It is a subfield of numerical analysis, and a type of linear algebra. Computers use floating-point arithmetic and cannot exactly represent irrational data, so when a computer algorithm is applied to a matrix of data, it can sometimes increase the difference between a number stored in the computer and the true number that it is an approximation of.