80 research outputs found
Using neural networks in software repositories
The first topic is an exploration of the use of neural network techniques to improve the effectiveness of retrieval in software repositories. The second topic relates to a series of experiments conducted to evaluate the feasibility of using adaptive neural networks as a means of deriving (or more specifically, learning) measures on software. Taken together, these two efforts illuminate a very promising mechanism supporting software infrastructures - one based upon a flexible and responsive technology
A neural net-based approach to software metrics
Software metrics provide an effective method for characterizing software. Metrics have traditionally been composed through the definition of an equation. This approach is limited by the fact that all the interrelationships among all the parameters be fully understood. This paper explores an alternative, neural network approach to modeling metrics. Experiments performed on two widely accepted metrics, McCabe and Halstead, indicate that the approach is sound, thus serving as the groundwork for further exploration into the analysis and design of software metrics
Low-density hydrodynamic optical-field-ionized plasma channels generated with an axicon lens
We demonstrate optical guiding of high-intensity laser pulses in long, low
density hydrodynamic optical-field-ionized (HOFI) plasma channels. An axicon
lens is used to generate HOFI plasma channels with on-axis electron densities
as low as and matched spot
sizes in the range . Control of these channel parameters via adjustment of the initial
cell pressure and the delay after the arrival of the channel-forming pulse is
demonstrated. For laser pulses with a peak axial intensity of , highly reproducible, high-quality guiding over
more than 14 Rayleigh ranges is achieved at a pulse repetition rate of 5 Hz,
limited by the available channel-forming laser and vacuum pumping system.
Plasma channels of this type would seem to be well suited to multi-GeV laser
wakefield accelerators operating in the quasi-linear regime
Für Aeltern, Erzieher und Jünglinge
von J. G. BoetticherVorlageform des Erscheinungsvermerks: Königsberg, 1786. Bey Gottlieb Lebrecht Hartung
[Stammbuch G. W. Boetticher]
[STAMMBUCH G. W. BOETTICHER]
[Stammbuch G. W. Boetticher] ( - )
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Besitzvermerk (1r)
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Statistische Uebersichts-Tabellen aller europäischen Staaten : nebst deren Münzen, Maaßen und Gewichten
[Jakob Gottlieb Isaack Bötticher]Autopsie nach Ex. der ULB Sachsen-AnhaltVorlageform des Erscheinungsvermerks: Königsberg und Leipzig, im Verlag der Hartungschen Hofbuchdruckerey und Buchhandlung. 1789
A Neural Net-Based Approach to Software Metrics
Software metrics provide effective methods for characterizing software. Metrics have traditionally been composed through the definition of an equation, but this approach is limited by the fact that all the interrelationships among all the parameters be fully understood. Derivation of a polynomial providing the desired characteristics is a substantial challenge. This paper explores an alternative, neural network approach to generating metrics. Experiments performed on two widely known metrics, McCabe and Halstead, indicate that the approach is sound, thus serving as the groundwork for further exploration into the analysis and design of software metrics
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