Tuning a two-round group key agreement

In 2007, Bohli et al. (Int J Inf Secur 6:243–254, 2007) proposed a two-round group key agreement protocol in the random oracle model, which in addition to semantic security offers strong entity authentication and a security guarantee against malicious insiders. We suggest a modification of this protocol that preserves the security guarantees and the round complexity, but reduces the amount of data that has to be sent and also reduces the number of signature computations and verifications by 50 %. Moreover, we propose a variant of Bohli et al.’s protocol whose security analysis does not require a random oracle or other idealizing assumptions.     

Exploiting probability density function of deep convolutional autoencoders’ latent space for reliable COVID-19 detection on CT scans

The Journal of Supercomputing - We present a probabilistic method for classifying chest computed tomography (CT) scans into COVID-19 and non-COVID-19. To this end, we design and train, in an...     

Serum from diabetic BB/W rats enhances calcium currents in primary sensory neurons

We examined the hypothesis that exposure of nondiabetic rat dorsal root ganglion (DRG) neurons to sera from diabetic BB/W rats would produce an increase in calcium currents associated with impaired regulation of the inhibitory G protein-calcium channel complex. Acutely dissociated rat DRGs were incubated for 18-24 h in medium supplemented with sera (10% vol/vol) from either diabetic rats with neuropathy or age-matched, nondiabetic controls. Exposure of DRG neurons to sera from diabetic BB/W rats resulted in a surface membrane immunofluorescence pattern when treated with an anti-rat light-chain antibody that was not observed in neurons exposed to control sera. Calcium current density (IDCa) was assessed with the use of the whole cell variation of the patch-clamp technique. IDCa in neurons exposed to diabetic sera was significantly increased compared with neurons exposed to control sera. Guanine nucleotide-binding (G) protein regulation of calcium channel function was examined with the use of a two-pulse "facilitation" or IDCa enhancement protocol in the presence of activators [guanosine 5'-O-(3-thiotriphosphate) (GTP gamma S)] or antagonists [guanosine 5'-O-(2-thiodiphosphate) (GDP beta S) and pertussis toxin (PTX)] of G protein function. Facilitation was significantly decreased in neurons exposed to diabetic sera. Intracellular diffusion of neurons with GDP beta s blocked facilitation, whereas dialysis with GTP gamma s increased facilitation to a similar magnitude in neurons exposed to either diabetic or control sera. Treatment with PTX resulted in a significant increase in IDCa and approximately 50% decrease in facilitation in neurons treated with control sera but no significant changes in neurons exposed to diabetic sera. We conclude that serum from diabetic BB/W rats with neuropathy contains an autoimmune immunoglobulin that impairs regulation of the inhibitory G protein-calcium channel complex, resulting in enhanced calcium influx. Regulation of the inhibitory G protein-calcium channel complex involves PTX-sensitive and -insensitive G proteins.     

Inter-image outliers and their application to image classification

Image variability that is impossible or difficult to restore by intra-image processing, such as the variability caused by occlusions, significantly reduces the performance of image-recognition methods. To address this issue, we propose that the pixels associated with large distances obtained by inter-image pixel-by-pixels comparisons should be considered as inter-image outliers and should be removed from the similarity calculation used for the image classification. When this method is combined with the template-matching method for image recognition, it leads to state-of-the-art recognition performance: 91% with AR database that includes occluded face images, 90% with PUT database that includes pose variations of face images and 100% with EYale B database that includes images with large illumination variation.     

A two-dimensional warranty servicing strategy based on reduction in product failure intensity

The cost of servicing a warranty depends, amongst other factors, on the type of repair performed under warranty. Although “all minimal repair” and “all replacement” policies are easy to implement and analyze, they are not always feasible and/or practical. Having a combination of different types of repair often leads to lower warranty servicing costs. In this article, to reduce the warranty servicing cost, we study a servicing strategy that involves performing imperfect repairs in place of some of the minimal repairs of an “all minimal repair” strategy; the effect of an imperfect repair is characterized by a drop in the conditional intensity function of the failure process. We consider both fixed and random degrees of repair. For a given type of product, we partition the warranty region so that the expected total warranty servicing cost is minimized. We provide a numerical illustration and a comparison with previously-studied repair-replacement strategies.     

A blur-robust descriptor with applications to face recognition

Understanding the effect of blur is an important problem in unconstrained visual analysis. We address this problem in the context of image-based recognition by a fusion of image-formation models and differential geometric tools. First, we discuss the space spanned by blurred versions of an image and then, under certain assumptions, provide a differential geometric analysis of that space. More specifically, we create a subspace resulting from convolution of an image with a complete set of orthonormal basis functions of a prespecified maximum size (that can represent an arbitrary blur kernel within that size), and show that the corresponding subspaces created from a clean image and its blurred versions are equal under the ideal case of zero noise and some assumptions on the properties of blur kernels. We then study the practical utility of this subspace representation for the problem of direct recognition of blurred faces by viewing the subspaces as points on the Grassmann manifold and present methods to perform recognition for cases where the blur is both homogenous and spatially varying. We empirically analyze the effect of noise, as well as the presence of other facial variations between the gallery and probe images, and provide comparisons with existing approaches on standard data sets.     

刚性屋面渗漏的原因及预防措施

本文针对刚性防水屋面渗漏的原因进行了分析,并提出了处理措施,旨在控制刚性防水屋面渗漏的产 生,保证屋面质量,满足使用要求。     

Microwave tomography for breast cancer detection on Cell broadband engine processors

Microwave tomography (MT) is a safe screening modality that can be used for breast cancer detection. The technique uses the dielectric property contrasts between different breast tissues at microwave frequencies to determine the existence of abnormalities. Our proposed MT approach is an iterative process that involves two algorithms: Finite-Difference Time-Domain (FDTD) and Genetic Algorithm (GA). It is a compute intensive problem: (i) the number of iterations can be quite large to detect small tumors; (ii) many fine-grained computations and discretizations of the object under screening are required for accuracy. In our earlier work, we developed a parallel algorithm for microwave tomography on CPU-based homogeneous, multi-core, distributed memory machines. The performance improvement was limited due to communication and synchronization latencies inherent in the algorithm. In this paper, we exploit the parallelism of microwave tomography on the Cell BE processor. Since FDTD is a numerical technique with regular memory accesses, intensive floating point operations and SIMD type operations, the algorithm can be efficiently mapped on the Cell processor achieving significant performance. The initial implementation of FDTD on Cell BE with 8 SPEs is 2.9 times faster than an eight node shared memory machine and 1.45 times faster than an eight node distributed memory machine. In this work, we modify the FDTD algorithm by overlapping computations with communications during asynchronous DMA transfers. The modified algorithm also orchestrates the computations to fully use data between DMA transfers to increase the computation-to-communication ratio. We see 54% improvement on 8 SPEs (27.9% on 1 SPE) for the modified FDTD in comparison to our original FDTD algorithm on Cell BE. We further reduce the synchronization latency between GA and FDTD by using mechanisms such as double buffering. We also propose a performance prediction model based on DMA transfers, number of instructions and operations, the processor frequency and DMA bandwidth. We show that the execution time from our prediction model is comparable (within 0.5 s difference) with the execution time of the experimental results on one SPE.