Observations of the Vertical Structure of Tidal Currents in Two Inlets

Observations of the vertical structure of broad band tidal currents were obtained at two energetic inlets. Each experiment took place over a 4 week period, the first at Hampton Inlet in southeastern New Hampshire, USA, in the Fall of 2011, and the second at New River Inlet in southern North Carolina, USA, in the spring of 2012. The temporal variation and vertical structure of the currents were observed at each site with 600 kHz and 1200 kHz RDI Acoustic Doppler Current Profilers (ADCP) deployed on low-profile bottom tripods in 7.5 and 12.5 m water depths near the entrance to Hampton Inlet, and in 8 and 9 m water depth within and outside New River Inlet, respectively. In addition, a Nortek Aquapro ADCP was mounted on a jetted pipe in about 2.5 m water depth on the flank of the each inlet channel. Flows within the Hampton/Seabrook Inlet were dominated by semi-diurnal tides ranging 2.5 - 4 m in elevation, with velocities exceeding 2.5 m/s. Flows within New River inlet were also semi-diurnal with tides ranging about 1 – 1.5 m in elevation and with velocities exceeding 1.5 m/s. Vertical variation in the flow structure at the dominant tidal frequency are examined as a function of location within and near the inlet. Outside the inlet, velocities vary strongly over the vertical, with a nearly linear decay from the surface to near the bottom. The coherence between the upper most velocity bin and the successively vertically separated bins drops off quickly with depth, with as much as 50% coherence decay over the water column. The phase relative to the uppermost velocity bin shifts over depth, with as much as 40 deg phase lag over the vertical, with bottom velocities leading the surface. Offshore, rotary coefficients indicate a stable ellipse orientation with rotational directions consistent over the vertical. At Hampton, the shallower ADCP, but still outside the inlet, shows a rotational structure that changes sign in the vertical indicating a sense of rotation at the bottom that is opposite to that at the surface. Within the inlet, the flow is more aligned with the channel, the decay in amplitude over the vertical is diminished, the coherence and phase structure is nearly uniform, and the rotary coefficients indicate no sense of rotation in the flow. The observations are qualitatively consistent with behavior described by Prandle (1982) for shallow water tidal flows

Machine Learning and Irresponsible Inference: Morally Assessing the Training Data for Image Recognition Systems

Just as humans can draw conclusions responsibly or irresponsibly, so too can computers. Machine learning systems that have been trained on data sets that include irresponsible judgments are likely to yield irresponsible predictions as outputs. In this paper I focus on a particular kind of inference a computer system might make: identification of the intentions with which a person acted on the basis of photographic evidence. Such inferences are liable to be morally objectionable, because of a way in which they are presumptuous. After elaborating this moral concern, I explore the possibility that carefully procuring the training data for image recognition systems could ensure that the systems avoid the problem. The lesson of this paper extends beyond just the particular case of image recognition systems and the challenge of responsibly identifying a person’s intentions. Reflection on this particular case demonstrates the importance (as well as the difficulty) of evaluating machine learning systems and their training data from the standpoint of moral considerations that are not encompassed by ordinary assessments of predictive accuracy

Ray-optical refraction with confocal lenslet arrays

Two parallel lenslet arrays with focal lengths f1 and f2 that share a common focal plane (that is, which are separated by a distance f1+f2) can refract transmitted light rays according to Snell's law, but with the 'sin's replaced with 'tan's. This is the case for a limited range of input angles and other conditions. Such confocal lenslet arrays can therefore simulate the interface between optical media with different refractive indices, n1 and n2, whereby the ratio η=-f2/f1 plays the role of the refractive-index ratio n2/n1. Suitable choices of focal lengths enable positive and negative refraction. In contrast to Snell's law, which leads to nontrivial geometric imaging by a planar refractive-index interface only for the special case of n1=±n2, the modified refraction law leads to geometric imaging by planar confocal lenslet arrays for any value of η. We illustrate some of the properties of confocal lenslet arrays with images rendered using ray-tracing software

Wavelength-scale stationary-wave integrated Fourier-transform spectrometry

Spectrometry is a general physical-analysis approach for investigating light-matter interactions. However, the complex designs of existing spectrometers render them resistant to simplification and miniaturization, both of which are vital for applications in micro- and nanotechnology and which are now undergoing intensive research. Stationary-wave integrated Fourier-transform spectrometry (SWIFTS)-an approach based on direct intensity detection of a standing wave resulting from either reflection (as in the principle of colour photography by Gabriel Lippmann) or counterpropagative interference phenomenon-is expected to be able to overcome this drawback. Here, we present a SWIFTS-based spectrometer relying on an original optical near-field detection method in which optical nanoprobes are used to sample directly the evanescent standing wave in the waveguide. Combined with integrated optics, we report a way of reducing the volume of the spectrometer to a few hundreds of cubic wavelengths. This is the first attempt, using SWIFTS, to produce a very small integrated one-dimensional spectrometer suitable for applications where microspectrometers are essential

The roles of motivation and ability in controlling the consequences of stereotype suppression

Two experiments investigated the conditions under which previously suppressed stereotypes are applied in impression formation. In Experiment 1, the extent to which a previously suppressed racial stereotype influenced subsequent impressions depended on the race of the target who was subsequently encountered. Whereas impressions of race-unspecified targets were assimilated to the stereotype following its suppression, no such effects were observed when the target belonged to the racial group whose stereotype had been initially suppressed. These results demonstrate that when perceivers are motivated to avoid stereo-typing individuals, the influence of a stereotype that has been previously activated through suppression is minimized. Experiment 2 demonstrated that these processing goals effectively reduce the impact of suppression-activated stereotypes only when perceivers have sufficient capacity to enact the goals. These results suggest that both sufficient motivation and capacity are necessary to prevent heightened stereotyping following stereotype suppression

Evolving high-speed, easy-to-understand network intrusion detection rules with genetic programming

Proceeding of: EvoWorkshops 2009: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG, Tübingen, Germany, April 15-17, 2009An ever-present problem in intrusion detection technology is how to construct the patterns of (good, bad or anomalous) behaviour upon which an engine have to make decisions regarding the nature of the activity observed in a system. This has traditionally been one of the central areas of research in the field, and most of the solutions proposed so far have relied in one way or another upon some form of data mining–with the exception, of course, of human-constructed patterns. In this paper, we explore the use of Genetic Programming (GP) for such a purpose. Our approach is not new in some aspects, as GP has already been partially explored in the past. Here we show that GP can offer at least two advantages over other classical mechanisms: it can produce very lightweight detection rules (something of extreme importance for high-speed networks or resource-constrained applications) and the simplicity of the patterns generated allows to easily understand the semantics of the underlying attack.Publicad