Optimization of efficiency-loss figure of merit in carrier-depletion silicon Mach-Zehnder optical modulator.

In this paper we study the optimization of interleaved Mach-Zehnder silicon carrier depletion electro-optic modulator. Following the simulation results we demonstrate a phase shifter with the lowest figure of merit (modulation efficiency multiplied by the loss per unit length) 6.7 V-dB. This result was achieved by reducing the junction width to 200 nm along the phase-shifter and optimizing the doping levels of the PN junction for operation in nearly fully depleted mode. The demonstrated low FOM is the result of both low V(π)L of ~0.78 Vcm (at reverse bias of 1V), and low free carrier loss (~6.6 dB/cm for zero bias). Our simulation results indicate that additional improvement in performance may be achieved by further reducing the junction width followed by increasing the doping levels.

Numerical analysis of gain saturation, noise figure, and carrier distribution for quantum-dot semiconductor-optical amplifiers

The gain saturation behaviors and noise figure are numerically analyzed for quantum-dot semiconductor optical amplifiers (QD-SOAs). The carrier and photon distributions in the longitudinal direction as well as the photon energy dependent facet reflectivity are accounted in the rate equations, which are solved with output amplified spontaneous emission spectrum as iterative variables. The longitudinal distributions of the occupation probabilities and spectral-hole burning are presented for electrons in the excited and ground states of quantum dots. The saturation output power 19.7 dBm and device gain 20.6 dB are obtained for a QD-SOA with the cavity length of 6 rum at the bias current of 500 mA. The influences of them electron intradot relaxation time and the QD capture time on the gain spectrum are simulated with the relaxation time of 1, 30, and 60 ps and capture time of 1, 5, and 10 ps. The noise figure as low as 3.5 dB is expected due to the strong polarization sensitive spontaneous emission. The characteristics of gain saturation and noise figure versus input signal power for QD-SOAs are similar to that of semiconductor. linear optical amplifiers with gain clamping by vertical laser fields.

Polarity dependence of hexagonal inclusions and cubic twins in GaN/GaAs(001) epilayers measured by conventional X-ray pole figure and grazing incident diffraction pole figure

The distribution of mixed phases and its dependence on the polarity of cubic GaN epilayers are investigated by conventional X-ray pole figure and grazing incident diffraction (GID) pole figure. The hexagonal inclusions and cubic twins can be classified into two portions: one is formed with strict crystalline orientations, the other with crystalline misorientations. The former can be measured by conventional pole figures which reveal that the density of lamellate hexagonal grains and cubic twins located on (1 1 1)(Ga) and ((1) over bar (1) over bar1)(Ga) along [1 (1) over bar 0] direction are higher than those on ((1) over bar 1 1), and (1 (1) over bar 1)(N) along [110] direction. However, the low signals from tiny mixed phases with crystalline misorientations, detected by GID pole figures, distribute in a larger phi region near the [1 1 0] and [(1) over bar (1) over bar 0] directions with much weaker intensity, and in a smaller phi region near the [1 (1) over bar 0] and [(1) over bar 1 0] directions with slightly stronger intensity. (C) 2001 Elsevier Science B.V. All rights reserved.

Environmentally stable ytterbium figure-of-eight fiber laser producing 177-fs pulses

Pulses of 177 fs and 1035 nm, with average power of 1.2 mW, have been generated directly from a passively mode-locked Yb-doped figure-of-eight fiber laser, with a nonlinear optical loop mirror for mode-locking and pairs of diffraction gratings for intracavity dispersion compensation. To our knowledge, these are the shortest pulses ever to come from a passively mode-locked Yb-doped figure-of-eight fiber laser. This represents a 5-fold reduction in pulse duration compared with that of previously reported passively mode-locked Yb-doped figure-of-eight fiber lasers. Stable pulse trains are produced at the fundamental repetition rate of the resonator, 24.0 MHz. (c) 2007 Elsevier B.V. All rights reserved.

Generation of 207-femtosecond pulses from a ytterbium figure-of-eight fibre laser

We report the generation of 207-fs pulses with 1.2mW average power at 1036 nm directly from a passively mode-locked Yb-doped fibre laser with a nonlinear optical loop mirror for mode-locking and pairs of diffraction gratings for intracavity dispersion compensation. These results imply a 4-fold reduction in pulse duration over previously reported figure-of-eight cavity passively mode-locked Yb-doped fibre lasers. Stable pulse trains are produced at the fundamental repetition rate of the resonator, 24.0MHz. On the other hand, this laser offers a cleaner spectrum and greater stability and is completely self-starting.

Perceptual Organization, Figure-Ground, Attention and Saliency

Notions of figure-ground, inside-outside are difficult to define in a computational sense, yet seem intuitively meaningful. We propose that "figure" is an attention-directed region of visual information processing, and has a non-discrete boundary. Associated with "figure" is a coordinate frame and a "frame curve" which helps initiate the shape recognition process by selecting and grouping convex image chunks for later matching- to-model. We show that human perception is biased to see chunks outside the frame as more salient than those inside. Specific tasks, however, can reverse this bias. Near/far, top/bottom and expansion/contraction also behave similarly.

CONFIGR: A Vision-Based Model for Long-Range Figure Completion

CONFIGR (CONtour FIgure GRound) is a computational model based on principles of biological vision that completes sparse and noisy image figures. Within an integrated vision/recognition system, CONFIGR posits an initial recognition stage which identifies figure pixels from spatially local input information. The resulting, and typically incomplete, figure is fed back to the “early vision” stage for long-range completion via filling-in. The reconstructed image is then re-presented to the recognition system for global functions such as object recognition. In the CONFIGR algorithm, the smallest independent image unit is the visible pixel, whose size defines a computational spatial scale. Once pixel size is fixed, the entire algorithm is fully determined, with no additional parameter choices. Multi-scale simulations illustrate the vision/recognition system. Open-source CONFIGR code is available online, but all examples can be derived analytically, and the design principles applied at each step are transparent. The model balances filling-in as figure against complementary filling-in as ground, which blocks spurious figure completions. Lobe computations occur on a subpixel spatial scale. Originally designed to fill-in missing contours in an incomplete image such as a dashed line, the same CONFIGR system connects and segments sparse dots, and unifies occluded objects from pieces locally identified as figure in the initial recognition stage. The model self-scales its completion distances, filling-in across gaps of any length, where unimpeded, while limiting connections among dense image-figure pixel groups that already have intrinsic form. Long-range image completion promises to play an important role in adaptive processors that reconstruct images from highly compressed video and still camera images.

Figure-Ground Separation

Air Force Office of Scientific Research (F49620-92-J-0499); Advanced Research Projects Agency (ONR N00014-92-J-4015); Office of Naval Research (N00014-91-J-4100)

A Neural Network Architecture for Figure-ground Separation of Connected Scenic Figures

A neural network model, called an FBF network, is proposed for automatic parallel separation of multiple image figures from each other and their backgrounds in noisy grayscale or multi-colored images. The figures can then be processed in parallel by an array of self-organizing Adaptive Resonance Theory (ART) neural networks for automatic target recognition. An FBF network can automatically separate the disconnected but interleaved spirals that Minsky and Papert introduced in their book Perceptrons. The network's design also clarifies why humans cannot rapidly separate interleaved spirals, yet can rapidly detect conjunctions of disparity and color, or of disparity and motion, that distinguish target figures from surrounding distractors. Figure-ground separation is accomplished by iterating operations of a Feature Contour System (FCS) and a Boundary Contour System (BCS) in the order FCS-BCS-FCS, hence the term FBF, that have been derived from an analysis of biological vision. The FCS operations include the use of nonlinear shunting networks to compensate for variable illumination and nonlinear diffusion networks to control filling-in. A key new feature of an FBF network is the use of filling-in for figure-ground separation. The BCS operations include oriented filters joined to competitive and cooperative interactions designed to detect, regularize, and complete boundaries in up to 50 percent noise, while suppressing the noise. A modified CORT-X filter is described which uses both on-cells and off-cells to generate a boundary segmentation from a noisy image.

3-D Vision and Figure-Ground Separation by Visual Cortex

A neural network theory of :3-D vision, called FACADE Theory, is described. The theory proposes a solution of the classical figure-ground problem for biological vision. It does so by suggesting how boundary representations and surface representations are formed within a Boundary Contour System (BCS) and a Feature Contour System (FCS). The BCS and FCS interact reciprocally to form 3-D boundary and surface representations that arc mutually consistent. Their interactions generate 3-D percepts wherein occluding and occluded object completed, and grouped. The theory clarifies how preattentive processes of 3-D perception and figure-ground separation interact reciprocally with attentive processes of spatial localization, object recognition, and visual search. A new theory of stereopsis is proposed that predicts how cells sensitive to multiple spatial frequencies, disparities, and orientations are combined by context-sensitive filtering, competition, and cooperation to form coherent BCS boundary segmentations. Several factors contribute to figure-ground pop-out, including: boundary contrast between spatially contiguous boundaries, whether due to scenic differences in luminance, color, spatial frequency, or disparity; partially ordered interactions from larger spatial scales and disparities to smaller scales and disparities; and surface filling-in restricted to regions surrounded by a connected boundary. Phenomena such as 3-D pop-out from a 2-D picture, DaVinci stereopsis, a 3-D neon color spreading, completion of partially occluded objects, and figure-ground reversals are analysed. The BCS and FCS sub-systems model aspects of how the two parvocellular cortical processing streams that join the Lateral Geniculate Nucleus to prestriate cortical area V4 interact to generate a multiplexed representation of Form-And-Color-And-Depth, or FACADE, within area V4. Area V4 is suggested to support figure-ground separation and to interact. with cortical mechanisms of spatial attention, attentive objcect learning, and visual search. Adaptive Resonance Theory (ART) mechanisms model aspects of how prestriate visual cortex interacts reciprocally with a visual object recognition system in inferotemporal cortex (IT) for purposes of attentive object learning and categorization. Object attention mechanisms of the What cortical processing stream through IT cortex are distinguished from spatial attention mechanisms of the Where cortical processing stream through parietal cortex. Parvocellular BCS and FCS signals interact with the model What stream. Parvocellular FCS and magnocellular Motion BCS signals interact with the model Where stream. Reciprocal interactions between these visual, What, and Where mechanisms arc used to discuss data about visual search and saccadic eye movements, including fast search of conjunctive targets, search of 3-D surfaces, selective search of like-colored targets, attentive tracking of multi-element groupings, and recursive search of simultaneously presented targets.

A Solution of the Figure-ground Problem for Biological Vision

A neural network model of 3-D visual perception and figure-ground separation by visual cortex is introduced. The theory provides a unified explanation of how a 2-D image may generate a 3-D percept; how figures pop-out from cluttered backgrounds; how spatially sparse disparity cues can generate continuous surface representations at different perceived depths; how representations of occluded regions can be completed and recognized without usually being seen; how occluded regions can sometimes be seen during percepts of transparency; how high spatial frequency parts of an image may appear closer than low spatial frequency parts; how sharp targets are detected better against a figure and blurred targets are detector better against a background; how low spatial frequency parts of an image may be fused while high spatial frequency parts are rivalrous; how sparse blue cones can generate vivid blue surface percepts; how 3-D neon color spreading, visual phantoms, and tissue contrast percepts are generated; how conjunctions of color-and-depth may rapidly pop-out during visual search. These explanations arise derived from an ecological analysis of how monocularly viewed parts of an image inherit the appropriate depth from contiguous binocularly viewed parts, as during DaVinci stereopsis. The model predicts the functional role and ordering of multiple interactions within and between the two parvocellular processing streams that join LGN to prestriate area V4. Interactions from cells representing larger scales and disparities to cells representing smaller scales and disparities are of particular importance.

Cortical Dynamics of 3-D Vision and Figure-Ground Pop-Out

Air Force Office of Scientific Research (90-0175); Defense Advanced Research Projects Agency (90-0083); Office of Naval Research (N00014-91-J-4100)

Azione destabilizzante e impegno politico. Le figure femminili tra il giallo e il nero Italiani dal 1980 a oggi

My thesis analyses female figures in Italian crime fiction since 1980, from narratological, sociological and gender-studies perspectives. It considers the narrative structure of the giallo and the noir, taking into account the difficulties, particularly in Italy, of establishing what noir fiction is and if/how it is possible to frame it in a specific narrative scheme. This discourse connects to the extraordinary success of Italian giallo and noir fiction over the past fifteen-twenty years. In this scenario, I examine the place of female writers in relation to this phenomenon, especially since the 1980s: in terms of the level of visibility/acceptance of their work, in a narrative space traditionally considered as a male territory, and with regard to their writings, which introduce different narrative perspectives. Specifically, I consider selected texts by leading female Italian writers, in which female elements (writers/characters) become destabilizing factor both on the narrative level, by undermining the schemes of ‘formulaic’ fiction, and on the political one, through their implicit potential (as women) for disrupting the rigid models inherited from processes of social conditioning and from political structures. In terms of gender identities, such texts offer scope to question conventional social constructions of the subject: by empowering the female narrative voice and by embodying it in characters (investigators/killers) traditionally personified by male figures. These texts offer themselves as a critical space where, potentially, readers can rethink static gendered relationships and stereotypical symbolical categories.