Ti3SiC2 is of interest due to its unique dual nature reminiscent of both brittle ceramics and ductile metals at ambient conditions. In this work, plate-impact experiments have been performed to study the dynamic behavior of Ti3SiC2 under shock compression up to 112 GPa by using laser velocity interferometer and electric pin techniques. Hugoniot elastic limits (HEL), spall strength, and Hugoniot equations of state have been obtained based on measured particle velocity profiles and shock wave velocities. The ratio of spall strength to HEL for Ti3SiC2 is larger than brittle ceramics but smaller than metals. This result indicates that the dual nature of Ti3SiC2 remains at least up to 10 GPa. On the other hand, the linearity of the Hugoniot equation of state, , suggests that the initial structure of Ti3SiC2 should be stable up to 112 GPa, in contrast to the result reported by Jordan et al. [J. Appl. Phys., 93 (2003) 9639]. 相似文献
Polyaniline emeraldine base/epoxy resin (EB/ER) coating was investigated for corrosion protection of mild steel coupled with copper in 3.5% NaCl solution. EB/ER coating with 5-10 wt% EB had long-term corrosion resistance on both uncoupled steel and copper due to the passivation effect of EB on the metal surfaces. During the 150 immersion days, the impedance at 0.1 Hz for the coating increased in the first 1-40 days and subsequently remained constant above 109 Ω cm2, whereas that for pure ER coating fell below 106 Ω cm2 after only 30 or 40 days. Immersion tests on coated steel-copper galvanic couple showed that EB/ER coating offered 100 times more protection than ER coating against steel dissolution and coating delamination on copper, which was mainly attributed to the passive metal oxide films formed by EB blocking both the anodic and cathodic reactions. Salt spray tests showed that 100 μm EB/ER coating protected steel-copper couple for at least 2000 h. 相似文献
This paper proposes a self-embedding watermarking scheme that reduces the watermark payload significantly while maintaining good recovery quality and security. The embedded watermark contributes to the tamper detection and content recovery and is composed of only the compression codes of the image content. The compression codes with variable length are generated according to the roughness of the image. To improve the security, a chaos-based pseudorandom sequence generator is adopted to generate block-mapping sequence and encrypt compression codes. The proposed method takes into account the invisibility, recovery quality, and security using the flexible watermark payload, which preserves sufficient information of the image block with as few bits as possible. Experimental results demonstrate that the proposed scheme not only outperforms conventional self-embedding fragile watermarking algorithms in tamper detection and recovery, but also improve the security against the various counterfeiting attacks. 相似文献
Logos are specially designed marks that identify goods, services, and organizations using distinguished characters, graphs, signals, and colors. Identifying logos can facilitate scene understanding, intelligent navigation, and object recognition. Although numerous logo recognition methods have been proposed for printed logos, a few methods have been specifically designed for logos in photos. Furthermore, most recognition methods use codebook-based approaches for the logos in photos. A codebook-based method is concerned with the generation of visual words for all the logo models. When new logos are added, the codebook reconstruction is required if effectiveness is a crucial factor. Moreover, logo detection in natural scenes is difficult because of perspective tilt and non-rigid deformation. Therefore, this study develops an extendable, but discriminating, model-based logo detection method. The proposed logo detection method is based on a support vector machine (SVM) using edge-based histograms of oriented gradient (HOGE) as features through multi-scale sliding window scanning. Thereafter, anti-distortion affine scale invariant feature transform (ASIFT) is used for logo verification with constraints on the ASIFT matching pairs and neighbors. The experimental results using the public Flickr-Logo database confirm that the proposed method has a higher retrieval and precision accuracy compared to existing model-based methods.
Multimedia Tools and Applications - Rate distortion optimization technique is adopted by H.264/AVC to select the best intra and inter prediction modes. It achieves remarkable improvement in... 相似文献
Space robots are in huge demand due to the rapid growth of their service targets, i.e., spacecraft. There are generally large flexible components on spacecraft, such as antenna reflectors and solar paddles. Due to the vibratility of their structure, it is challenging for a space robot with flexible appendages (the base is then called flexible-base) to capture and repair the large flexible spacecraft. After capturing, the two spacecraft with flexible appendages are connected by a space manipulator, and a compounded system is formed. In this paper, we developed a dynamic model and a closed-loop simulation system, to provide a means to verify path planning and control algorithms. Initially, the dynamic characteristics of different capturing stages (preimpact and post-impact) were analyzed. The topologies of a flexible-base space robot and the compounded system were described based on incidence and channel matrices. Secondly, the recursive dynamics was formulated and resolved by an effective numerical method. The modeling was verified by Adams’ model. Thirdly, we implemented a dynamics calculation block in Matlab/Simulink environment using the S-function package for the C program, and developed a closed-loop simulation system, which was composed of the Planning and Controller, the Multibody Dynamic, and the 3D Display modules. Finally, based on the simulation system, two typical missions—target berthing and on-orbital manipulation of the target along a circle, were simulated and evaluated. Dynamics analysis results presented some useful rules for the path planning and control to suppress the vibration of the flexible structure. 相似文献
Association Link Network (ALN) is a kind of Semantic Link Network built by mining the association relations among multimedia Web resources for effectively supporting Web intelligent application such as Web-based learning, and semantic search. This paper explores the Small-World properties of ALN to provide theoretical support for association learning (i.e., a simple idea of “learning from Web resources”). First, a filtering algorithm of ALN is proposed to generate the filtered status of ALN, aiming to observe the Small-World properties of ALN at given network size and filtering parameter. Comparison of the Small-World properties between ALN and random graph shows that ALN reveals prominent Small-World characteristic. Then, we investigate the evolution of Small-World properties over time at several incremental network sizes. The average path length of ALN scales with the network size, while clustering coefficient of ALN is independent of the network size. And we find that ALN has smaller average path length and higher clustering coefficient than WWW at the same network size and network average degree. After that, based on the Small-World characteristic of ALN, we present an Association Learning Model (ALM), which can efficiently provide association learning of Web resources in breadth or depth for learners. 相似文献
With the rapid development of online learning technology, a huge amount of e-learning materials have been generated which are highly heterogeneous and in various media formats. Besides, e-learning environments are highly dynamic with the ever increasing number of learning resources that are naturally distributed over the network. On the other hand, in the online learning scenario, it is very difficult for users without sufficient background knowledge to choose suitable resources for their learning. In this paper, a hybrid recommender system is proposed to recommend learning items in users’ learning processes. The proposed method consists of two steps: (1) discovering content-related item sets using item-based collaborative filtering (CF), and (2) applying the item sets to sequential pattern mining (SPM) algorithm to filter items according to common learning sequences. The two approaches are combined to recommend potentially useful learning items to guide users in their current learning processes. We also apply the proposed approach to a peer-to-peer learning environment for resource pre-fetching where a central directory of learning items is not available. Experiments are conducted in a centralized and a P2P online learning systems for the evaluation of the proposed method and the results show good performance of it. 相似文献