No abstract

The differential phase contrast CT detects the projection of refractive coefficient's derivative and uses the Hilbert filter for image reconstruction, which leads to the radical difference in its NPS and the advantage in noise in comparison to that of the conventional CT.

No abstract

Abstract. Runtime (dynamic) model checking is a promising verification methodology for real-world threaded software because of its many features, the prominent ones being: (i) it avoids the need to extract a model and instead runs the actual code, and (ii) the precision of information available at run-time allows techniques such as dynamic partial order reduction (DPOR) [1] to dramatically cut down the number of interleavings examined. Unfortunately, DPOR does not have many implementations for real thread libraries such as POSIX Pthreads, and suffers from high computational overheads due to a stateless search that requires re-executions. In our previous work [2], we designed a runtime model checker, inspect, that overcomes the first of these drawbacks. Inspect has been shown capable of detecting data races, deadlocks and other incorrect API usages in real-world PThreads C programs. In this paper, we describe a distributed version of inspect, which implements an extended DPOR algorithm. Our two key contributions are: (i) a practical algorithm for distributed dynamic partial order reduction; (ii) the innovations that helped distributed inspect attain nearly linear (with respect to the number of CPUs) speedup on realistic examples.

No abstract

Purpose: Differential phase contrast CT (DPC-CT) is emerging as a new technology to improve the contrast sensitivity of conventional attenuation-based CT. The noise equivalent quanta as a function over spatial frequency, i.e., the spectrum of noise equivalent quanta NEQ(k), is a decisive indicator of the signal and noise transfer properties of an imaging system. In this work, we derive the functional form of NEQ(k) in DPC-CT. Via system modeling, analysis, and computer simulation, we evaluate and verify the derived NEQ(k) and compare it with that of the conventional attenuation-based CT. Methods: The DPC-CT is implemented with x-ray tube and gratings. The x-ray propagation and data acquisition are modeled and simulated through Fresnel and Fourier analysis. A monochromatic x-ray source (30 keV) is assumed to exclude any system imperfection and interference caused by scatter and beam hardening, while a 360• full scan is carried out in data acquisition to avoid any weighting scheme that may disrupt noise randomness. Adequate upsampling is implemented to simulate the x-ray beam's propagation through the gratings G 1 and G 2 with periods 8 and 4 μm, respectively, while the intergrating distance is 193.6 mm (1/16 of the Talbot distance). The dimensions of the detector cell for data acquisition are 32 × 32, 64 × 64, 96 × 96, and 128 × 128 μm 2 , respectively, corresponding to a 40.96 × 40.96 mm 2 field of view in data acquisition. An air phantom is employed to obtain the noise power spectrum NPS(k), spectrum of noise equivalent quanta NEQ(k), and detective quantum efficiency DQE(k). A cylindrical water phantom at 5.1 mm diameter and complex refraction coefficient n = 1 − δ + iβ = 1 −2.5604 × 10 −7 + i1.2353 × 10 −10 is placed in air to measure the edge transfer function, line spread function and then modulation transfer function MTF(k), of both DPC-CT and the conventional attenuation-based CT. The x-ray flux is set at 5 × 10 6 photon/cm 2 per projection and observes the Poisson distribution, which is consistent with that of a micro-CT for preclinical applications. Approximately 360 regions, each at 128 × 128 matrix, are used to calculate the NPS(k) via 2D Fourier transform, in which adequate zero padding is carried out to avoid aliasing in noise. Results:The preliminary data show that the DPC-CT possesses a signal transfer property [MTF(k)] comparable to that of the conventional attenuation-based CT. Meanwhile, though there exists a radical difference in their noise power spectrum NPS(k) (trait 1/|k| in DPC-CT but |k| in the conventional attenuation-based CT) the NEQ(k) and DQE(k) of DPC-CT and the conventional attenuation-based CT are in principle identical. Conclusions: Under the framework of ideal observer study, the joint signal and noise transfer property NEQ(k) and detective quantum efficiency DQE(k) of DPC-CT are essentially the same as those of the conventional attenuation-based CT. The findings reported in this paper may provide insightful guidelines on the research, development, and performance optimization o...

Abstract. We present new techniques for fast, accurate and scalable static data race detection in concurrent programs. Focusing our analysis on Linux device drivers allowed us to identify the unique challenges posed by debugging largescale real-life code and also pinpointed drawbacks in existing race warning generation methods. This motivated the development of new techniques that helped us in improving both the scalability as well as the accuracy of each of the three main steps in a race warning generation system. The first and most crucial step is the automatic discovery of shared variables. Towards that end, we present a new, efficient dataflow algorithm for shared variable detection which is more effective than existing correlation-based techniques that failed to detect the shared variables responsible for data races in majority of the drivers in our benchmark suite. Secondly, accuracy of race warning generation strongly hinges on the precision of the pointer analysis used to compute aliases for lock pointers. We formulate a new scalable context sensitive alias analysis that effectively combines a divide and conquer strategy with function summarization and is demonstrably more efficient than existing BDD-based techniques. Finally, we provide a new warning reduction technique that leverages lock acquisition patterns to yield provably better warning reduction than existing lockset based methods.

Abstract. In applying stateless model checking methods to realistic multithreaded programs, we find that stateless search methods are ineffective in practice, even with dynamic partial order reduction (DPOR) enabled. To solve the inefficiency of stateless runtime model checking, this paper makes two related contributions. The first contribution is a novel and conservative light-weight method for storing abstract states at runtime to help avoid redundant searches. The second contribution is a stateful dynamic partial order reduction algorithm (SDPOR) that avoids a potential unsoundness when DPOR is naively applied in the context of stateful search. Our stateful runtime model checking approach combines light-weight state recording with SDPOR, and strikes a good balance between state recording overheads, on one hand, and the elimination of redundant searches, on the other hand. Our experiments confirm the effectiveness of our approach on several multithreaded benchmarks in C, including some practical programs.