Generate may refer to: * Create
Generate outputs. In the case of programs this includes the program LOAD module/s, DBRM and source. A GENERATE is generally executed immediately following an ADD or UPDATE.
Generate also has a management arm that represents entertainers including Patton Oswalt, Brian Posehn, Al Madrigal, Adam Rifkin, Arj Barker, Nat Coombs and Jon Reep.
Generate is a Los Angeles-based entertainment studio that produces content for distribution across media, including the Internet, television, web television, film, video games, mobile devices and books. The company completed a $6 million Series A round of funding backed by Velocity Interactive Group and MK Capital in March 2008, in addition to naming co-founding partner Jordan Levin CEO. Levin was formerly CEO of The WB. Generate opened an office in New York City in June 2008.
On August 19, 2008, Generate debuted "Republicrats" in partnership with MSN. The Web series "follows the comedic presidential aspirations of Sean Masterson. Masterson’s political platform is his lack of one. His character doesn’t harbor any of those pesky strong opinions on topics of the day. There will be 24 episodes of Republicrats with new episodes launching twice a week" until Election Day 2008. Generate produced "Republicrats," which is hosted on MSN.
In June 2012, Brian Keating, one of Calgary’s best known naturalists and an official spokesperson for Generate Choice, became the 100th Calgary homeowner to join in the program. "Through a lease program, the panels generate a portion of a home’s energy needs. A set of six panels is a 1.3 kilowatt-hour [sic] photovoltaic system that will produce between 1,000 and 1,400 kWh per year. The average home in Calgary uses 625 kWh per month," says Colin Dumais, technology specialist with ENMAX".
In 2011, ENMAX Energy launched its Generate Choice, a program which offers Albertans home-based renewable energy choices such as solar power and wind generation (ENMAX 2011:7). Response to the program has been poor: by August 2011, only 3,100 people even expressed interest in having a solar photo-voltaic (PV) system installed, and of those, only 172 agreed to have one installed.
Using fix templates is an alternative way to generate candidate patches. Fix templates are typically predefined program mutation rules for fixing specific classes of bugs. Examples of fix templates include inserting a conditional statement to check whether the value of a variable is null to fix null pointer exception, and changing an integer constant by one to fix off-by-one errors. Fix templates are therefore often adopted by targeted techniques. It is also possible to automatically mine fix templates for generate-and-validate approches.
* Gateway Generate (EP) (2013)
One way to generate candidate patches is to apply mutation operators on the original program. Mutation operators manipulate the original program, potentially via its abstract syntax tree representation, or a more coarse-grained representation such as operating at the statement-level or block-level. Earlier genetic improvement approaches operate at the statement level and carry out simple delete/replace operations such as deleting an existing statement or replacing an existing statement with another statement in the same source file. Recent approaches use more fine-grained operators at the abstract syntax tree level to generate more diverse set of candidate patches.
An obvious way to generate permutations of n is to generate values for the Lehmer code (possibly using the factorial number system representation of integers up to n!), and convert those into the corresponding permutations. However, the latter step, while straightforward, is hard to implement efficiently, because it requires n operations each of selection from a sequence and deletion from it, at an arbitrary position; of the obvious representations of the sequence as an array or a linked list, both require (for different reasons) about n 2 /4 operations to perform the conversion. With n likely to be rather small (especially if generation of all permutations is needed) that is not too much of a problem, but it turns out that both for random and for systematic generation there are simple alternatives that do considerably better. For this reason it does not seem useful, although certainly possible, to employ a special data structure that would allow performing the conversion from Lehmer code to permutation in O(n log n) time.
In computing it may be required to generate permutations of a given sequence of values. The methods best adapted to do this depend on whether one wants some randomly chosen permutations, or all permutations, and in the latter case if a specific ordering is required. Another question is whether possible equality among entries in the given sequence is to be taken into account; if so, one should only generate distinct multiset permutations of the sequence.
William L. Cleveland of Simon Fraser University states that the revolt failed to generate significant support from within the Ottoman Empire's Arab provinces, and remained largely limited to tribal levies from the Arabian Peninsula loyal to Sharif Hussein. Efraim Karsh of Bar-Ilan University considers the term Arab Revolt as a misnomer as it implies that the majority of the Ottoman Arabs rebelled, when in fact the majority stayed loyal.
Having received applications to register copyrights for computer programs that generated typefaces using "typeface in digitized form", the Copyright Office revisited the 1988 Policy Decision in 1992. The Office was concerned that the claims indicated a significant technological advance since the previous policy decision. One advance was scalable font representations (Bézier curves). This format can output a font at any resolution, and stores its data as control points rather than pixels. The Office acknowledged that these fonts might involve original computer instructions to generate typefaces, and thus be protectable as computer programs, but ended saying that "The scope of the copyright will be, as in the past, a matter for the courts to determine."
Higher order methods not only use the velocity in the current timestep, but velocities from the previous timestep to generate a more accurate result. For instance, Huen’s Method (second order) averages the velocity from the current and previous timestep to determine the next position of a vehicle:
For a given string or chunk of data, Pearson's original algorithm produces only an 8-bit byte or integer, 0-255. However, the algorithm makes it extremely easy to generate a hash of whatever length is desired. As Pearson noted, a change to any bit in the string causes his algorithm to create a completely different hash (0-255). In the code above, following every completion of the inner loop, the first byte of the string is effectively incremented by one (without modifying the string itself).
The scheme used above is a very straightforward implementation of the algorithm, with a simple extension to generate a hash longer than 8 bits. That extension comprises the outer loop (i.e. all statement lines that include the variable j) and the array hh.
This shows that Pearson's algorithm can be made to generate hashes of any desired length by concatenating a sequence of 8-bit hash values, each of which is computed simply by slightly modifying the string each time the hash function is computed. Thus the same core logic can be made to generate 32-bit or 128-bit hashes.
Starting with scale free graphs with low degree correlation and clustering coefficient, one can generate new graphs with much higher degree correlations and clustering coefficients by applying edge-dual transformation.