National University of Defense Technology

About: National University of Defense Technology is a education organization based out in Changsha, China. It is known for research contribution in the topics: Radar & Synthetic aperture radar. The organization has 39430 authors who have published 40181 publications receiving 358979 citations. The organization is also known as: Guófáng Kēxuéjìshù Dàxué & NUDT.

Review on techniques to improve the strength of adhesive joints with composite adherends

Abstract: The use of adhesive joints has increased rapidly in the past decades. Driven by the growing demand for lightweight structures, composite adherends have increased in popularity, benefiting from their high specific mechanical properties and design tailorability. However, composites are typically weak in the transverse direction, which can cause premature failure by delamination. Several techniques, aimed at reducing stress concentrations and increasing the transverse strength of the adherends, are discussed and compared in terms of material arrangement and geometry design. Lastly, a short summary on prominent features of the techniques is given. The paper is intended to provide guidelines for the design of adhesive joints with composite adherends.

Joint Resource Allocation for Latency-Sensitive Services Over Mobile Edge Computing Networks With Caching

Abstract: Mobile edge computing (MEC) has risen as a promising paradigm to provide high quality of experience via relocating the cloud server in close proximity to smart mobile devices (SMDs). In MEC networks, the MEC server with computation capability and storage resource can jointly execute the latency-sensitive offloading tasks and cache the contents requested by SMDs. In order to minimize the total latency consumption of the computation tasks, we jointly consider computation offloading, content caching, and resource allocation as an integrated model, which is formulated as a mixed integer nonlinear programming (MINLP) problem. We design an asymmetric search tree and improve the branch and bound method to obtain a set of accurate decisions and resource allocation strategies. Furthermore, we introduce the auxiliary variables to reformulate the proposed model and apply the modified generalized benders decomposition method to solve the MINLP problem in polynomial computation complexity time. Simulation results demonstrate the superiority of the proposed schemes.

Ship Classification in TerraSAR-X Images With Feature Space Based Sparse Representation

Abstract: Ship classification is the key step in maritime surveillance using synthetic aperture radar (SAR) imagery In this letter, we develop a new ship classification method in TerraSAR-X images based on sparse representation in feature space, in which the sparse representation classification (SRC) method is exploited In particular, to describe the ship more accurately and to reduce the dimension of the dictionary in SRC, we propose to employ a representative feature vector to construct the dictionary instead of utilizing the image pixels directly By testing on a ship data set collected from TerraSAR-X images, we show that the proposed method is superior to traditional methods such as the template matching (TM), K-nearest neighbor (K-NN), Bayes and Support Vector Machines (SVM)

Evaluating the Mechanical Behavior of Arterial Tissue using Digital Image Correlation

Abstract: In this study, digital image correlation (DIC) was adopted to examine the mechanical behavior of arterial tissue from bovine aorta. Rectangular sections comprised of the intimal and medial layers were excised from the descending aorta and loaded in displacement control uniaxial tension up to 40 percent elongation. Specimens of silicon rubber sheet were also prepared and served as a benchmark material in the application of DIC for the evaluation of large strains; the elastomer was loaded to 50 percent elongation. The arterial specimens exhibited a non-linear hyperelastic stress-strain response and the stiffness increased with percent elongation. Using a bilinear model to describe the uniaxial behavior, the average minor and major elastic modulii were 192±8 KPa and 912±40 KPa, respectively. Poisson's ratio of the arterial sections increased with the magnitude of axial strain; the average Poisson's ratio was 0.17±0.02. Although the correlation coefficient obtained from image correlation decreased with the percent elongation, a correlation coefficient greater than 0.8 was achieved for the tissue experiments and exceeded that obtained in the evaluation of the elastomer. Based on results from this study, DIC may serve as a valuable method for the determination of mechanical properties of arteries and other soft tissues.