Comparison of SSM/I measurements to numerically-simulated cloud and precipitation during ERICA

These investigations focused essentially on the macroscale organization of cloud and precipitation which occurred during the 4th Intensive Observing Period (IOP-4) of the Experiment for Rapidly Intensifying Cyclones over the Atlantic (ERICA). This experiment, held off the East Coast of the United States and Canada during the winter of 1989, documented several episodes of rapid cyclonic storm development. Also playing a major role as validation and ground truth in these studies are Special Sensor Microwave Imager (SSM/I) retrievals of precipitable water, total liquid water and ice, generated by other Marshall Space Flight Center (MSFC) supported investigations. Model simulations produced to date suggest that, while the large-scale atmospheric dynamics was an essential driving mechanism, the role of condensation was crucial in facilitating the exceptionally rapid spinup of the cyclone and the low surface pressure. A model simulation of the precipitation rate at the time of most rapid storm intensification is shown in the accompanying figure. Heavier precipitation rates in the crescent shaped region are associated with deep convection along the leading edge of a dry intrusion behind the surface low. The majority of precipitation in the stratiform region to the northeast involved the production of ice with deposition from vapor to ice being the dominant process of growth. Some small amount of mixed phase cloudiness was present. Model condensate distributions matched well with SSM/I observations. The accompanying SSM/I imagery which delineates areas of large (greater than several hundred micron effective radius) precipitating ice over the ocean suggests that the model has done well in capturing the essential mechanisms responsible for the horizontal distribution of precipitation

Gesture-Controlled Interfaces for Self-Service Machines

Gesture-controlled interfaces are software- driven systems that facilitate device control by translating visual hand and body signals into commands. Such interfaces could be especially attractive for controlling self-service machines (SSMs) for example, public information kiosks, ticket dispensers, gasoline pumps, and automated teller machines (see figure). A gesture-controlled interface would include a vision subsystem comprising one or more charge-coupled-device video cameras (at least two would be needed to acquire three-dimensional images of gestures). The output of the vision system would be processed by a pure software gesture-recognition subsystem. Then a translator subsystem would convert a sequence of recognized gestures into commands for the SSM to be controlled; these could include, for example, a command to display requested information, change control settings, or actuate a ticket- or cash-dispensing mechanism. Depending on the design and operational requirements of the SSM to be controlled, the gesture-controlled interface could be designed to respond to specific static gestures, dynamic gestures, or both. Static and dynamic gestures can include stationary or moving hand signals, arm poses or motions, and/or whole-body postures or motions. Static gestures would be recognized on the basis of their shapes; dynamic gestures would be recognized on the basis of both their shapes and their motions. Because dynamic gestures include temporal as well as spatial content, this gesture- controlled interface can extract more information from dynamic than it can from static gestures

A Parameterization Invariant Approach to the Statistical Estimation of the CKM Phase α\alpha

In contrast to previous analyses, we demonstrate a Bayesian approach to the estimation of the CKM phase $\alpha$ that is invariant to parameterization. We also show that in addition to {\em computing} the marginal posterior in a Bayesian manner, the distribution must also be {\em interpreted} from a subjective Bayesian viewpoint. Doing so gives a very natural interpretation to the distribution. We also comment on the effect of removing information about $\mathcal{B}^{00}$.Comment: 14 pages, 3 figures, 1 table, minor revision; to appear in JHE

Dynamical system representation, generation, and recognition of basic oscillatory motion gestures

We present a system for generation and recognition of oscillatory gestures. Inspired by gestures used in two representative human-to-human control areas, we consider a set of oscillatory motions and refine from them a 24 gesture lexicon. Each gesture is modeled as a dynamical system with added geometric constraints to allow for real time gesture recognition using a small amount of processing time and memory. The gestures are used to control a pan-tilt camera neck. We propose extensions for use in areas such as mobile robot control and telerobotics

Gesture-controlled interfaces for self-service machines and other applications

A gesture recognition interface for use in controlling self-service machines and other devices is disclosed. A gesture is defined as motions and kinematic poses generated by humans, animals, or machines. Specific body features are tracked, and static and motion gestures are interpreted. Motion gestures are defined as a family of parametrically delimited oscillatory motions, modeled as a linear-in-parameters dynamic system with added geometric constraints to allow for real-time recognition using a small amount of memory and processing time. A linear least squares method is preferably used to determine the parameters which represent each gesture. Feature position measure is used in conjunction with a bank of predictor bins seeded with the gesture parameters, and the system determines which bin best fits the observed motion. Recognizing static pose gestures is preferably performed by localizing the body/object from the rest of the image, describing that object, and identifying that description. The disclosure details methods for gesture recognition, as well as the overall architecture for using gesture recognition to control of devices, including self-service machines

Dynamic System Representation of Basic and Non-Linear in Parameters Oscillatory Motion Gestures

We present a system for generation and recognition of oscillatory gestures. Inspired by gestures used in two representative human-to-human control areas, we consider a set of oscillatory (circular) motions and refine from them a 24 gestures lexicon. Each gesture is modeled as a dynamic system with added geometric constraints to allow for real time gesture recognition using a small amount of processing time and memory. The gestures are used to control a pan-tilt camera neck. The gesture lexicon is then enhanced to include non-linear in parameter ( come here ) gesture representations. An enhancement is suggested which would enable the system to be trained to recognized previously unidentified yet consistent human generated oscillatory motion gestures

Caltech Faint Field Galaxy Redshift Survey IX: Source detection and photometry in the Hubble Deep Field Region

Detection and photometry of sources in the U_n, G, R, and K_s bands in a 9x9 arcmin^2 region of the sky, centered on the Hubble Deep Field, are described. The data permit construction of complete photometric catalogs to roughly U_n=25, G=26, R=25.5 and K_s=20 mag, and significant photometric measurements somewhat fainter. The galaxy number density is 1.3x10^5 deg^{-2} to R=25.0 mag. Galaxy number counts have slopes dlog N/dm=0.42, 0.33, 0.27 and 0.31 in the U_n, G, R and K_s bands, consistent with previous studies and the trend that fainter galaxies are, on average, bluer. Galaxy catalogs selected in the R and K_s bands are presented, containing 3607 and 488 sources, in field areas of 74.8 and 59.4 arcmin^2, to R=25.5 and and K_s=20 mag.Comment: Accepted for publication in ApJS; some tables and slightly nicer figures available at http://www.sns.ias.edu/~hogg/deep

A Statement on the Appropriate Role for Research and Development in Climate Policy

This statement is issued by a group of economists and scientists which met at Stanford University on October 18, 2008 to discuss the role of research and development (R&D) in developing effective policies for addressing the adverse potential consequences of climate change. We believe that climate change is a serious issue that governments need to address. We also believe that research and development needs to be a central part of governments’ strategies for responding to this challenge. Solutions to manage long-term risks will require the development and global deployment of a range of technologies for energy supply and end-use, land-use, agriculture and adaptation that are not currently commercial. A key potential benefit of focused scientific and technological research and development investment is that it could dramatically reduce the cost of restricting greenhouse gas emissions by encouraging the development of more affordable, better performing technologies.

Use of single-component wind speed in Rankine-Hugoniot analysis of interplanetary shocks

We have extended and deployed a routine designed to run independently on the Web providing real-time analysis of interplanetary shock observations from L_1. The program accesses real-time magnetic field, solar wind speed, and proton density data from the Advanced Composition Explorer (ACE) spacecraft, searches for interplanetary shocks, analyzes shocks according to the Rankine-Hugoniot (R-H) jump conditions, and provides shock solutions on the Web for space weather applications. Because the ACE real-time data stream contains the wind speed but not the three-component wind velocity, we describe modifications to the R-H analysis that use the scalar wind speed and show successful results for analyses of strong interplanetary shocks at 1 AU. We compare the three-component and one-component solutions and find the greatest disagreement between the two rests in estimations of the shock speed rather than the shock propagation direction. Uncertainties in magnetic quantities such as magnetic compression and shock normal angle relative to the upstream magnetic field show large uncertainties in both analyses when performed using an automated routine whereas analyses of the shock normal alone do not. The automated data point selection scheme, together with the natural variability of the magnetic field, is inferred to be a problem in a few instances for this and other reasons. For a broad range of interplanetary shocks that arrive 30 to 60 min after passing L_1, this method will provide 15 to 45 min of advanced warning prior to the shock's collision with the Earth's magnetopause. The shock, in turn, provides advance warning of the approaching driver gas