Environmental Fatigue and Static Behavior of RC Beams Strengthened with Carbon-Fiber-Reinforced Polymer

Many countries around the world have tremendous needs to repair and strengthen their transportation infrastructure. Almost everywhere, traffic loads have reached levels largely exceeding design expectations. Northern countries also experience severe winter conditions that are combined with an extensive use of deicing salts and accelerate structural deterioration. In Canada, the extent of deterioration has prompted many authorities, including the federal and provincial governments, to investigate the potential use of fiber-reinforced polymer products to extend the life of their existing structures. However, it is widely recognized that the large-scale implementation of these products is often impaired by the lack of data on their durability. This paper presents an experimental project undertaken in order to assess the durability of reinforced concrete beams externally strengthened with two types of carbon-fiber-reinforced polymer (CFRP). The beams were first exposed to either wet-dry cycles or continuous immersion in water and then were loaded in fatigue. Finally, they were tested quasi-statically under four-point bending up to failure. The test results presented here provide some insights on the potential long-term performance of CFRP-strengthened beams exposed to severe environmental conditions.     

Stenting of "unprotected" left main coronary artery stenoses: early and late results

The effect of bone plug length and Kurosaka screw (DePuy, Warsaw, IN) diameter on graft holding strength of the bone-tendon-bone construct was determined. Random length porcine bone plugs were assigned to fixation with 7 or 9 mm Kurosaka screws. Peak load to failure was determined. There was a significant decrease in peak load to failure of the 5-mm long bone plugs compared with longer bone plugs. No difference was found between longer lengths of bone plug in either the 7- or 9-mm screw diameter groups. The 9-mm diameter screws significantly increased peak load to failure for both 1- and 2-cm bone plug lengths.     

Short‐Wave Infrared Sensor by the Photothermal Effect of Colloidal Gold Nanorods

Photodetection in the short‐wave infrared (SWIR) spectrum is a challenging task achieved often by costly low bandgap compound semiconductors involving highly toxic elements. In this work, an alternative low‐cost approach is reported for SWIR sensors that rely on the plasmonic‐induced photothermal effect of solution‐processed colloidal gold nanorods (Au NRs). A series of uniform solution‐processed Au NRs of various aspect ratios are prepared exhibiting a strong and well‐defined longitudinal localized surface plasmon resonance (L‐LSPR) maximum from 900 nm to 1.3 µm. A hybrid device structure is fabricated by applying Au NRs on the surface of a thermistor. Under a monochromatic illumination, hybrid Au‐NR/thermistor devices exhibit a clear photoresponse in the form of photoinduced resistance drop in the wavelength window from 1.0 to 1.8 µm. The photoresponsivity of such hybrid devices reaches a maximum value of 4.44 × 10⁷ Ω W^?1 at λ = 1.4 µm (intensity = 0.28 mW cm^?2), a wavelength in agreement with the L‐LSPR of the Au NRs applied. Colloidal Au NRs, capable to perform fast conversion between photon absorption and thermal energy, thus open an interesting avenue for alternative low‐cost SWIR photodetection.     

Rain or Snow Detection in Image Sequences Through Use of a Histogram of Orientation of Streaks

The detection of bad weather conditions is crucial for meteorological centers, specially with demand for air, sea and ground traffic management. In this article, a system based on computer vision is presented which detects the presence of rain or snow. To separate the foreground from the background in image sequences, a classical Gaussian Mixture Model is used. The foreground model serves to detect rain and snow, since these are dynamic weather phenomena. Selection rules based on photometry and size are proposed in order to select the potential rain streaks. Then a Histogram of Orientations of rain or snow Streaks (HOS), estimated with the method of geometric moments, is computed, which is assumed to follow a model of Gaussian-uniform mixture. The Gaussian distribution represents the orientation of the rain or the snow whereas the uniform distribution represents the orientation of the noise. An algorithm of expectation maximization is used to separate these two distributions. Following a goodness-of-fit test, the Gaussian distribution is temporally smoothed and its amplitude allows deciding the presence of rain or snow. When the presence of rain or of snow is detected, the HOS makes it possible to detect the pixels of rain or of snow in the foreground images, and to estimate the intensity of the precipitation of rain or of snow. The applications of the method are numerous and include the detection of critical weather conditions, the observation of weather, the reliability improvement of video-surveillance systems and rain rendering.     

计算机电话查询系统的设计和实现技术

本文讨论了利用电话来构造计算机系统语音界面的技术。     

Back and forth between continuous and discrete for the working computer scientist

This paper gives a perfect, ideal, discretization of continuous notions. This is a very convenient frame to treat continuous problems or theories with the help of a computer. This is illustrated by the conversion of algorithms using real numbers into algorithms using integers only and the founding of discrete geometry.     

Sparse Adaptive Parameterization of Variability in Image Ensembles

This paper introduces a new parameterization of diffeomorphic deformations for the characterization of the variability in image ensembles. Dense diffeomorphic deformations are built by interpolating the motion of a finite set of control points that forms a Hamiltonian flow of self-interacting particles. The proposed approach estimates a template image representative of a given image set, an optimal set of control points that focuses on the most variable parts of the image, and template-to-image registrations that quantify the variability within the image set. The method automatically selects the most relevant control points for the characterization of the image variability and estimates their optimal positions in the template domain. The optimization in position is done during the estimation of the deformations without adding any computational cost at each step of the gradient descent. The selection of the control points is done by adding a L ¹ prior to the objective function, which is optimized using the FISTA algorithm.     

Efficient Geodesic Attribute Thinnings Based on the Barycentric Diameter

An attribute opening is an idempotent, anti-extensive and increasing operator, which removes from an image connected components which do not fulfil a given criterion. When the increasingness property is dropped, we obtain a—more general—attribute thinning. In this paper, we propose efficient grey scale thinnings based on geodesic attributes. Given that the geodesic diameter is time consuming, we propose a new geodesic attribute, the barycentric diameter to speed up the computation time. Then, we give the theoretical error bound between these two attributes, and we note that in practice, the barycentric diameter gives very similar results in comparison with the geodesic diameter. Finally, we present the algorithm with further optimisations, to obtain a 60× speed up. We illustrate the use of these thinnings in automated non-destructive material inspection: the detection of cracks. We discuss the advantages of these operators over other methods such as path openings or the supremum of openings with segments.