GPU accelerated regional lung air volume measurements from phase contrast X-ray images

Phase contrast X-ray imaging can provide significantly enhanced visibility of soft tissues over absorption contrast imaging with spatial resolution on the micron scale. These characteristics have enabled the visualisation of lungs aerating at birth in real time. We have developed techniques to measure regional lung air volume from these images to help develop methods for safely ventilating the lungs of preterm infants. However, analyzing a large sequence of image data requires considerable computation time on traditional desktop computers. Real-time feedback of the regional ventilation would greatly benefit researches to optimize ventilation strategies. The present paper describes methods for improving the execution time of the lung volume measurements using graphics processing units (GPUs). We tested the performance of the GPU-accelerated lung volume computations using two different GPUs and compared the results with two CPUs. An overall speedup of 1.75–14.12× was achieved if an absorption contrast-based computation was used for volumetric computation, while a 2.43–15.78× speedup was attained in the case of a more compute bound phase retrieval technique. This speedup enabled us to perform lung air volume reconstruction on a local computer with the analysis taking only a few minutes, which is very helpful to guide our experiments in the laboratory. We also show that the accuracy of the GPU-based lung volume measurements was in excellent agreement with the CPU-based counterpart.     

A Software Agent Architecture for Network Management: Case Studies and Experience Gained

Current Network Management paradigms are rigid and lack flexibility. This makes the task of managing a highly evolving and dynamic network difficult to cope with. This paper presents the results of our work on Agent technology as a new paradigm for developing Network Management applications. First, we present our agent architecture that is built in a way that allows the agent to acquire new capabilities at runtime. Second, we present two case studies implemented with a prototype of this agent architecture. The first case study consists of an agent system in which faulty agents are automatically detected, their tasks then being reallocated to other agents, thus providing a fault-tolerant management system. The second case study deals with the configuration of heterogeneous ATM networks to establish end-to-end permanent virtual channels. Finally, we evaluate our agent architecture and the agent paradigm in general when applied to Network Management.     

Fast and precise points-to analysis

Many software engineering applications require points-to analysis. These client applications range from optimizing compilers to integrated program development environments (IDEs) and from testing environments to reverse-engineering tools. Moreover, software engineering applications used in an edit-compile cycle need points-to analysis to be fast and precise.In this article, we present a new context- and flow-sensitive approach to points-to analysis where calling contexts are distinguished by the points-to sets analyzed for their call target expressions. Compared to other well-known context-sensitive techniques it is faster in practice, on average, twice as fast as the call string approach and by an order of magnitude faster than the object-sensitive technique. In fact, it shows to be only marginally slower than a context-insensitive baseline analysis. At the same time, it provides higher precision than the call string technique and is similar in precision to the object-sensitive technique. We confirm these statements with experiments using a number of abstract precision metrics and a concrete client application: escape analysis.     

Optimum design of a banked memory with power management for wireless sensor networks

Wireless Networks - The ever-increasing complexity of applications covered by wireless sensor networks (WSNs) demands for increasing memory size, which in turn increases the power drain. It is well...     

Moderate intensity exercise as an adjunct to standard smoking cessation treatment for women: A pilot study.

Previous randomized controlled trials have not supported moderate intensity exercise as an efficacious adjunct to smoking cessation treatments for women; however, compliance with exercise programs in these studies has been poor. The purpose of this pilot study was to estimate the effects of moderate intensity exercise on smoking cessation outcomes under optimal conditions for exercise program compliance. Sixty previously sedentary, healthy, female smokers were randomized to an 8-week program consisting of brief baseline smoking cessation counseling and the nicotine patch plus either 150 min/week of moderate intensity exercise or contact control. Participants attended a median of 86.4% and 95.5% of prescribed exercise/control sessions, respectively. There was a moderate, though statistically nonsignificant, effect of exercise at post-treatment for objectively verified 7-day point prevalence abstinence (48.3% vs. 23.3%; OR = 3.07, 95% CI: 0.89–11.07) and prolonged abstinence (34.5% vs. 20.0%; OR = 2.11, 95% CI: 0.56–8.32). Effects were attenuated when controlling for potential confounders, and after a 1-month, no-treatment period. The findings provide a preliminary indication that, given adequate compliance, moderate intensity exercise may enhance short-term smoking cessation outcomes for women; however, a larger trial is warranted. (PsycINFO Database Record (c) 2010 APA, all rights reserved)