7,324 research outputs found
Neural network-based retrieval from software reuse repositories
A significant hurdle confronts the software reuser attempting to select candidate components from a software repository - discriminating between those components without resorting to inspection of the implementation(s). We outline an approach to this problem based upon neural networks which avoids requiring the repository administrators to define a conceptual closeness graph for the classification vocabulary
Engineering Quantum Jump Superoperators for Single Photon Detectors
We study the back-action of a single photon detector on the electromagnetic
field upon a photodetection by considering a microscopic model in which the
detector is constituted of a sensor and an amplification mechanism. Using the
quantum trajectories approach we determine the Quantum Jump Superoperator (QJS)
that describes the action of the detector on the field state immediately after
the photocount. The resulting QJS consists of two parts: the bright counts
term, representing the real photoabsorptions, and the dark counts term,
representing the amplification of intrinsic excitations inside the detector.
First we compare our results for the counting rates to experimental data,
showing a good agreement. Then we point out that by modifying the field
frequency one can engineer the form of QJS, obtaining the QJS's proposed
previously in an ad hoc manner
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
Optical Coherence Tomography Angiography of the Optic Disc; an Overview.
Different diseases of the optic disc may be caused by or lead to abnormal vasculature at the optic nerve head. Optical coherence tomography angiography (OCTA) is a novel technology that provides high resolution mapping of the retinal and optic disc vessels. Recent studies have shown the ability of OCTA to visualize vascular abnormalities in different optic neuropathies. In addition, quantified OCTA measurements were found promising for differentiating optic neuropathies from healthy eyes
Implementation of projective measurements with linear optics and continuous photon counting
We investigate the possibility of implementing a given projection measurement
using linear optics and arbitrarily fast feedforward based on the continuous
detection of photons. In particular, we systematically derive the so-called
Dolinar scheme that achieves the minimum error discrimination of binary
coherent states. Moreover, we show that the Dolinar-type approach can also be
applied to projection measurements in the regime of photonic-qubit signals. Our
results demonstrate that for implementing a projection measurement with linear
optics, in principle, unit success probability may be approached even without
the use of expensive entangled auxiliary states, as they are needed in all
known (near-)deterministic linear-optics proposals.Comment: 11 pages, 2 figures, updated to the published versio
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