Sentence examples for features in the database from inspiring English sources

We have made several test on these services executed over the Grid infrastructure [Grid Middleware gLite (2002)], with a varying number of features in the database (amount of data) and a varying request complexity (number of performed service requests).

It is not possible to derive such a set from a pre-existing statistic of common user queries, which favors popular queries viable for recently conducted research, or from identified features in the database, which favors queries based on the feature identification method and produces a bias towards database content.

Table 3 Correlation among the other URL features in the database   URL_Size NH ND NNC IP URL_Size 100 42 75 63 −3 NH 42 100342626 −3 ND 75 34 100 60 20 NNC 63 26 60 100 44 IP −3 −3 20 44 100 Italic values indicate an important correlation between the URL_Size, ND, NNC.

where t in and t ^ i are, respectively, the query human motion feature and music features in the database M ^ i ( i = 1, 2, …, M t ) transformed into the same feature space shown as follows: t ^ i = B ′ ϕ M ( vec [ M ^ i ] ) - ϕ ̄ M = E M ′ κ M ^ i - 1 N K M 1, (41) t i n = Λ A ′ ϕ V ( vec [ V i n ] ) - ϕ ̄ V = Λ E V ′ κ V i n - 1 N K V 1, (42).

We intend to include more features in the database including conversion of SNPs into putative CAPS markers and designing primers for SNPs.

All 24 725 protein-coding genes in Tetrahymena are represented as features in the database, each with its own dedicated Gene Page.

For LC MS data, the putative identities of each ion were first given within XCMS by matching features in the databases with the following parameters: ppm = 20, adducts = [M+H]+, [M+NH4]+, [M+Na]+, and [M+K]+ in the positive ion mode.

If an adversary having a large database of biometric features of various users steals the biohash of a system user and knows his secret key, the adversary can compute biohashes of each biometric feature in the database using the random projection matrix of the user and create a table of biohashes and their corresponding feature vectors.

Sarepta Therapeutics, which is not featured in the database, has taken measures to support its patient base.

If the corresponding feature in the database has been changed by another user, Artemis will warn that this has occurred and ask whether to continue with the commit process, thus allowing a forced overwrite of previous changes, where necessary.

Matching and Decision Subsystem The matching and decision subsystem matches the inputted and processed biometric features with the registered biometric features stored in the database.