A Trustworthy Proof Checker

Proof-carrying code (PCC) and other applications in computer security require machine-checkable proofs of properties of machine-language programs. The main advantage of the PCC approach is that the amount of code that must be explicitly trusted is very small: it consists of the logic in which predicates and proofs are expressed, the safety predicate, and the proof checker. We have built a minimal proof checker, and we explain its design principles and the representation issues of the logic, safety predicate, and safety proofs. We show that the trusted computing base (TCB) in such a system can indeed be very small. In our current system the TCB is less than 2,700 lines of code (an order of magnitude smaller even than other PCC systems), which adds to our confidence of its correctness.     

Robust Algorithms for Object Localization

Model-based localization, the task of estimating an object's pose from sensed and corresponding model features, is a fundamental task in machine vision. Exact constant time localization algorithms have been developed for the case where the sensed features and the model features are the same type. Still, it is not uncommon for the sensed features and the model features to be of different types, i.e., sensed data points may correspond to model faces or edges. Previous localization approaches have handled different model and sensed features of different types via sampling and synthesizing virtual features to reduce the problem of matching features of dissimilar types to the problem of matching features of similar types. Unfortunately, these approaches may be suboptimal because they introduce artificial errors. Other localization approaches have reformulated object localization as a nonlinear least squares problem where the error is between the sensed data and model features in image coordinates (the Euclidean image error metric). Unfortunately, all of the previous approaches which minimized the Euclidean image error metric relied on gradient descent methods to find the global minima, and gradient descent methods may suffer from problems of local minima. In this paper, we describe an exact, efficient solution to the nonlinear least squares minimization problem based upon resultants, linear algebra, and numerical techniques. On a SPARC 20, our localization algorithm runs in a few microseconds for rectilinear polygonal models, a few milliseconds for generic polygonal models, and one second for generalized polygonal models (models composed of linear edges and circular arcs).     

Effectiveness of Cognitive-Behavioral Treatment for Panic Disorder Versus Treatment as Usual in a Managed Care Setting.

Eighty clients enrolled in a managed care health plan who identified panic disorder as their primary presenting problem were randomly assigned to treatment by a therapist recently trained in a manual-based empirically supported psychotherapy (M. G. Craske, E. Meadows, & D. H. Barlow, 1994) or a therapist conducting treatment as usual (TAU). Participants in both conditions showed significant change from pre- to posttreatment on a number of measures. Those receiving panic control therapy (PCT) showed greater levels of change than those receiving TAU. Among treatment completers, an average of 42.9% of those in PCT and 18.8% in TAU achieved clinically significant change across measures. The results are discussed with reference to the dissemination of PCT and other evidence-based psychotherapies to clinical practice settings. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Temporal Coding in Conditioned Inhibition: Analysis of Associative Structure of Inhibition.

Two experiments with rats as subjects were conducted to investigate the associative structure of temporal control of conditioned inhibition through posttraining manipulation of the training excitor-unconditioned stimulus (US) temporal relationship. Experiment 1 found that following simultaneous Pavlovian inhibition training (i.e., A → US/XA-no US) in which a conditioned stimulus (CS A) was established as a delay excitor, maximal inhibition was observed on a summation test when CS X was compounded with a delay transfer CS. Furthermore, posttraining shifts in the A-US temporal relationship from delay to trace resulted in maximal inhibition of a trace transfer CS. Experiment 2 found complementary results to Experiment 1 with an A-US posttraining shift from serial to simultaneous. These results suggest that temporal control of inhibition is mediated by the training excitor-US temporal relationship. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Remote sensing of vegetation and land-cover change in Arctic Tundra Ecosystems

The objective of this paper is to review research conducted over the past decade on the application of multi-temporal remote sensing for monitoring changes of Arctic tundra lands. Emphasis is placed on results from the National Science Foundation Land-Air-Ice Interactions (LAII) program and on optical remote sensing techniques. Case studies demonstrate that ground-level sensors on stationary or moving track platforms and wide-swath imaging sensors on polar orbiting satellites are particularly useful for capturing optical remote sensing data at sufficient frequency to study tundra vegetation dynamics and changes for the cloud prone Arctic. Less frequent imaging with high spatial resolution instruments on aircraft and lower orbiting satellites enable more detailed analyses of land cover change and calibration/validation of coarser resolution observations.The strongest signals of ecosystem change detected thus far appear to correspond to expansion of tundra shrubs and changes in the amount and extent of thaw lakes and ponds. Changes in shrub cover and extent have been documented by modern repeat imaging that matches archived historical aerial photography. NOAA Advanced Very High Resolution Radiometer (AVHRR) time series provide a 20-year record for determining changes in greenness that relates to photosynthetic activity, net primary production, and growing season length. The strong contrast between land materials and surface waters enables changes in lake and pond extent to be readily measured and monitored.     

An Empirical Study Evaluating Social Networking Continuance and Success

Social networking site (SNS) use decisions have led to major economic and social transformations worldwide. While many organizations seek to use SNSs from a strategic perspective to reach their customer, it is important to understand what makes SNSs successful in order to use them for competitive purposes. The current research evaluates the influence of the social capital theory on SNS success measures. A model was developed and empirically tested using two data samples to ensure valid and reliable results for success of SNSs. The results display the importance of social capital in SNS success followed by practitioner and academic implications.