Satellite SAR Remote Sensing of Great Lakes Ice Cover,Part 2. Ice Classification and Mapping

During the 1997 winter season, shipborne polarimetric backscatter measurements of Great Lakes (freshwater) ice types using the Jet Propulsion Laboratory C-band scatterometer, together with surface-based ice physical characterization measurements and environmental parameters, were acquired concurrently with Earth Resource Satellite 2 (ERS-2) and RADARSAT Synthetic Aperture Radar (SAR) data. This polarimetric data set, composed of over 20 variations of different ice types measured at incident angles from 0° to 60° for all polarizations, was processed to radar cross-section to establish a library of signatures (look-up table) for different ice types. The library is used in the computer classification of calibrated satellite SAR data. Computer analysis of ERS-2 and RADARSAT ScanSAR images of Great Lakes ice cover using a supervised classification technique indicates that different ice types in the ice cover can be identified and mapped, and that wind speed and direction can have an influence on the classification of water as ice based on single frequency, single polarization data. Once satellite SAR data are classified into ice types, the ice map provides important and necessary input for environmental protection and management, ice control and ice breaking operations, and ice forecasting and modeling efforts.     

Microprocessor testability

As the level of microprocessor complexity increases to several hundred thousand transistors for a single-chip machine, it is becoming very difficult to test commercially available designs to the level of fault coverage desired by some customers. In order to achieve near 100-percent coverage of single stuck-at faults, future microprocessors must be designed with special testing features (designed for testability). The authors describe the testing problem for microprocessors, including the various methods of generating test sets and their application by the user. A survey of the testability features of some of today's commercially available microprocessors is presented. Suggestions for testability features for future-generation microprocessors are also discussed     

Probability of error for selection diversity as a function of dwelltime

An expression is derived for the probability of error of an N th-order selection diversity system for the case where the receiver is forced to swell on one channel for several symbols before being allowed to make a decision regarding the best channel. It is found that the time-varying nature of a fading channel causes significant degradation of the probability of error when the dwell time becomes longer than about 10% of the inverse of the fading bandwidth of the channel. The onset of degradation is a function of the signal-to-noise ratio and of the order of diversity. Specific probabilities of error are calculated for differential phase-shift keyed modulation (DPSK). However, the calculations can be done for any other modulation technique     

StoryGrid [educational computing]

The StoryGrid project undertook studying the role new interface technologies might play in education, particularly at the high school level. Unfortunately, technology often seizes center stage in high school classrooms; i.e., it becomes the topic of instruction. We believe that learning about technology would be most successful when technology is not the topic, but simply a tool used during instruction. StoryGrid, therefore, was designed to support and to enhance existing narrative activity in classrooms by adhering to the following goals: trigger reflection and interpretation, accommodate individual expression and encourage student discourse.