PERVASIVEhas one standard for communication between all agents: an agent communication language. ACLs incur overhead that makes them impractical or infeasible for the transfer of low-level data such as video, audio, sensory, or telemetry data. In response to these opposing needs for high-and low-level communication, we developed a two-tiered communication hierarchy, allowing additional, more efficient lines for low-level communication. Integrating the two-tiered communication architecture into the RETSINA MAS significantly improved the system's performance 6 on physical robots for USAR (see Figure 2). Simulation environmentThe scarcity and expense of USARcapable robots has severely restricted USAR robotics research. Field research shows that mobility is only one problem hindering effective use of robots for search and rescue. 3 Testing human perception, situational awareness, and teamwork depends on combining sensed data, human interaction, and automation in experiments. Expense, unreliability, and difficulties in running participants in parallel, especially in multirobot experiments, make physical robotics impractical for the large samples, repeated trials, and varied conditions needed for HRI research. To support HRI, a robotic simulation must accurately render the user interface (particularly, camera video), represent robot automation and behavior, and represent the remote environment that links the operator's awareness with the robot's behaviors. By anchoring the simulation to actual platforms and sensors, we hope to extend our experiments to novel, large, and hazardous environments with control of greater numbers of robots.To meet these requirements, we developed USARsim 7,8 a high-fidelity, extensible simulation of the NIST USAR arenas using the Unreal game engine (see Figure 3). The USAR arenas provide a controlled environment for comparing the effectiveness of different robotic designs, control and mapping algorithms, and team regimes. Each arena (yellow, orange, or red) can contain multiple "victims"-mannequins outfitted with thermal signatures, carbon dioxide emitters, and both noise (for example, screams for help) and motion (for example, waving of hands and fingers) as multimodal clues to the victims' vital signs. The quantitative challenge is discover as many victims as possible quickly and convey sufficient information for human rescuers to navigate the disaster and approach the victims. The arenas pose search tasks with varying difficulty on different dimensions. Challenges to mobility progress from the office-like environment of the yellow arena to the nearly impassable rubble of the red arena. Perceptual difficulties vary, from visually confusing patterns, glass panels, mirrors, and sonar-absorbing padding in the yellow arena to the few perceptual difficulties in the red arena.Our simulated environments include these three arenas and the larger, fixed USAR reference site in an abandoned Nike silo on the NIST Gaithersburg campus. Because the Unreal engine uses stan-

Purpose: Reduction of radiation dose in x-ray imaging has been recognized as a high priority in the medical community. Here the authors show that a regional adaptive exposure method can reduce dose-area product (DAP) in x-ray fluoroscopy. The authors' method is particularly geared toward providing dose savings for the pediatric population. Methods: The scanning beam digital x-ray system uses a large-area x-ray source with 8000 focal spots in combination with a small photon-counting detector. An imaging frame is obtained by acquiring and reconstructing up to 8000 detector images, each viewing only a small portion of the patient. Regional adaptive exposure was implemented by varying the exposure of the detector images depending on the local opacity of the object. A family of phantoms ranging in size from infant to obese adult was imaged in anteroposterior view with and without adaptive exposure. The DAP delivered to each phantom was measured in each case, and noise performance was compared by generating noise arrays to represent regional noise in the images. These noise arrays were generated by dividing the image into regions of about 6 mm 2 , calculating the relative noise in each region, and placing the relative noise value of each region in a one-dimensional array (noise array) sorted from highest to lowest. Dose-area product savings were calculated as the difference between the ratio of DAP with adaptive exposure to DAP without adaptive exposure. The authors modified this value by a correction factor that matches the noise arrays where relative noise is the highest to report a final dose-area product savings. Results:The average dose-area product saving across the phantom family was (42 ± 8)% with the highest dose-area product saving in the child-sized phantom (50%) and the lowest in the phantom mimicking an obese adult (23%). Conclusions: Phantom measurements indicate that a regional adaptive exposure method can produce large DAP savings without compromising the noise performance in the image regions with highest noise.

This paper presents a new approach for estimating physical properties of deformable models from experimental measurements. In contrast to most previous work, we introduce a new method based on particle filters which identifies the different stiffness properties for spring-based models. This approach addresses some important limitations encountered with gradient descent techniques which often converge towards ill solutions or remain fixed in local minima conditions.

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Iterative reconstruction methods have emerged as a promising avenue to reduce dose in CT imaging. Another, perhaps less well-known, advance has been the development of inverse geometry CT (IGCT) imaging systems, which can significantly reduce the radiation dose delivered to a patient during a CT scan compared to conventional CT systems. Here we show that IGCT data can be reconstructed using iterative methods, thereby combining two novel methods for CT dose reduction. A prototype IGCT scanner was developed using a scanning beam digital X-ray system -an inverse geometry fluoroscopy system with a 9,000 focal spot x-ray source and small photon counting detector. 90 fluoroscopic projections or "superviews" spanning an angle of 360 degrees were acquired of an anthropomorphic phantom mimicking a 1 year-old boy. The superviews were reconstructed with a custom iterative reconstruction algorithm, based on the maximum-likelihood algorithm for transmission tomography (ML-TR). The normalization term was calculated based on flat-field data acquired without a phantom. 15 subsets were used, and a total of 10 complete iterations were performed. Initial reconstructed images showed faithful reconstruction of anatomical details. Good edge resolution and good contrast-to-noise properties were observed. Overall, ML-TR reconstruction of IGCT data collected by a bench-top prototype was shown to be viable, which may be an important milestone in the further development of inverse geometry CT. IntroductionComputed tomography (CT) is an indispensable tool in medicine, and its importance is likely to increase in the coming years. Computed tomography (CT) has played an important role in significantly improving the outcome in many diseases, including cancer and heart disease. For example, for most types of cancer CT has become the dominant imaging method used for diagnoses, progress monitoring, and biopsy guidance among other applications throughout staging, treatment, and follow-up examinations; it is not uncommon for a cancer patient to receive ten CT scans during this time.According to the National Cancer Institute (NCI), CT is the largest contributor to medical radiation exposure received by the U.S. population [1]. Other recent publications predict that a significant number of cancers will be induced by the radiation from CT scans, especially in more radiation-sensitive subjects. While pediatric cancer is a small fraction in the overall cancer problem, children are particularly vulnerable to the effects of radiation exposure. Although the benefits of CT greatly outweigh the risk, it is important to work to reduce the radiation exposure from CT scanning. Simulations and preliminary experiments suggest that inverse geometry CT (IGCT) in conjunction with iterative reconstruction can accomplish this goal. In conventional geometry x-ray imaging systems, a pointsource X-ray tube is projected onto an extended detector. In contrast, inverse geometry imaging systems utilize an extended, multi-focal spot X-ray source, essentially a "spatially resol...