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DATA blocks can be used to read and manipulate input data, and create data sets. PROC blocks are used to perform analyses and operations on these data sets, sort data, and output results in the form of descriptive statistics, tables, results, charts and plots. [15] [16] PROC SQL can be used to work with SQL syntax within SAS. [17]
Synthetic-aperture sonar (SAS) is a form of sonar in which sophisticated post-processing of sonar data is used in ways closely analogous to synthetic-aperture radar. Synthetic-aperture sonars combine a number of acoustic pings to form an image with much higher along-track resolution than conventional sonars.
[7] [16] JMP began integrating with SAS in version 7.0 in 2007 and has strengthened this integration ever since. Users can write SAS code in JMP, connect to SAS servers, and retrieve and use data from SAS. Support for bubble plots was added in version 7. [6] [17] JMP 7 also improved data visualization and diagnostics. [18]
SAS macros are pieces of code or variables that are coded once and referenced to perform repetitive tasks. [8] SAS data can be published in HTML, PDF, Excel, RTF and other formats using the Output Delivery System, which was first introduced in 2007. [9] SAS Enterprise Guide is SAS's point-and-click interface.
SAS, [30] a system of software products for statistics. It includes SAS/IML, [31] a matrix programming language. VisSim is a visual block-diagram language for simulation of nonlinear dynamic systems and model-based embedded development. Its fast ODE engine supports real-time simulation of complex large-scale models.
RAWPED is a dataset for detection of pedestrians in the context of railways. The dataset is labeled box-wise. 26000 Images Object recognition and classification 2020 [90] [91] Tugce Toprak, Burak Belenlioglu, Burak Aydın, Cuneyt Guzelis, M. Alper Selver OSDaR23 OSDaR23 is a multi-sensory dataset for detection of objects in the context of railways.
The higher voltage offers (among other features) the ability to use SAS in server backplanes. [12] Because of its higher signaling voltages, SAS can use cables up to 10 m (33 ft) long, whereas SATA has a cable-length limit of 1 m (3.3 ft) or 2 m (6.6 ft) for eSATA. [12] SAS is full duplex, whereas SATA is half duplex. The SAS transport layer ...
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]