Augmented Online Sequential Quaternion Extreme Learning Machine

Neural Processing Letters - Online sequential extreme learning machine (OS-ELM) is one of the most popular real-time learning strategy for feedforward neural networks with single hidden layer due...     

Electrochemical investigation of La0.4Sr0.6TiO3 synthesized in air for SOFC application

Journal of Applied Electrochemistry - La-doped titanate materials have been widely investigated as alternative Ni-free anodes for solid oxide fuel cells (SOFCs). In this study, La0.4Sr0.6TiO3 (LST)...     

Degradability and biocompatibility of bioglass/poly(amino acid) composites with different surface bioactivity as bone repair materials

Bioglass (BG) possesses excellent bioactivity and has been widely used in the manufacture of biomaterials. In this study, a composite with different surface bioactivity was fabricated via in situ melting polymerization by incorporating BG and poly(amino acid) (PAA) at a suitable ratio. The structure of the composite was characterized by Fourier transform infrared spectroscopy and XRD. The compressive strength of the BG/PAA composites was 139 MPa (BG:PAA = 30:70). The BG/PAA composites were degradable, and higher BG in composite showed higher weight loss after 4 weeks of incubation in simulated body fluid. In addition, the BG/PAA composite maintained adequate residual compressive strength during the degradation period. The SEM results showed the differences in surface bioactivities of the composites directly, and 30BG/PAA composite showed thicker apatite layer and higher Ca/p than 15BG/PAA. in vitro MG-63 cell culture experiments showed that the composite was noncytotoxic and thus allows cells to adhere, proliferate, and differentiate. This indicates that the composite has good biocompatibility. The implantations in the bone defects of rabbits for 4 and 12 weeks were studied. The composites had good biocompatibility and were capable of guiding new bone formation without causing any inflammation. The composite may be successfully used in the development of bone implants.     

Engineering all-aromatic polyamide surface from hydrophilic to superhydrophobic and the accelerated strategy

Being a new kind of nanomaterials, aromatic polyamide nanofibers (ANF) have been much highlighted in recent studies. We here demonstrate an isopropyl alcohol (IPA) accelerated chemical cleavage on poly (p-phenylene terephthalamide) chopped fibers, which provides an efficient preparation method of ANF. The comprehensive study on the processes accelerated by different alcohols revealed that the preparation time of ANF in the mixed medium of dimethyl sulfoxide (DMSO)-alcohol (20:1 in volume) was shorten to 45 min and 75 min for methanol (ethanol) and isopropanol, respectively. However, the nanofibers prepared in DMSO-IPA exhibited the minimum in axial and radial dimensions, providing the finest and most uniform diameter of 16 nm. The corresponding ANF films through vacuum assisted filtration also showed the highest tensile strength of 150 MPa, in comparison with those of the ANF films prepared using other alcohols, which were about 110 MPa. Furthermore, ANF/silicon hybrid films were prepared by the ionic ring-opening reaction followed by the alkoxysilane condensation and nanoparticle fabrication. By changing the organo functional groups in the alkoxysilane, the surface of the films were adjustable in a wide contact angle range from 56° (hydrophilic) to 150° (superhydrophobic), suggesting the amendable interfacial properties potential applicable to composite fabrication with most of the resin matrix.     

Video summarization via minimum sparse reconstruction

The rapid growth of video data demands both effective and efficient video summarization methods so that users are empowered to quickly browse and comprehend a large amount of video content. In this paper, we formulate the video summarization task with a novel minimum sparse reconstruction (MSR) problem. That is, the original video sequence can be best reconstructed with as few selected keyframes as possible. Different from the recently proposed convex relaxation based sparse dictionary selection method, our proposed method utilizes the true sparse constraint L₀ norm, instead of the relaxed constraint _L2,1$L_{2,1}$ norm, such that keyframes are directly selected as a sparse dictionary that can well reconstruct all the video frames. An on-line version is further developed owing to the real-time efficiency of the proposed MSR principle. In addition, a percentage of reconstruction (POR) criterion is proposed to intuitively guide users in obtaining a summary with an appropriate length. Experimental results on two benchmark datasets with various types of videos demonstrate that the proposed methods outperform the state of the art.     

Accelerating a Recurrent Neural Network to Finite-Time Convergence for Solving Time-Varying Sylvester Equation by Using a Sign-Bi-power Activation Function

Bartels–Stewart algorithm is an effective and widely used method with an O(n ³) time complexity for solving a static Sylvester equation. When applied to time-varying Sylvester equation, the computation burden increases intensively with the decrease of sampling period and cannot satisfy continuous realtime calculation requirements. Gradient-based recurrent neural network are able to solve the time-varying Sylvester equation in real time but there always exists an estimation error. In contrast, the recently proposed Zhang neural network has been proven to converge to the solution of the Sylvester equation ideally when time goes to infinity. However, this neural network with the suggested activation functions never converges to the desired value in finite time, which may limit its applications in realtime processing. To tackle this problem, a sign-bi-power activation function is proposed in this paper to accelerate Zhang neural network to finite-time convergence. The global convergence and finite-time convergence property are proven in theory. The upper bound of the convergence time is derived analytically. Simulations are performed to evaluate the performance of the neural network with the proposed activation function. In addition, the proposed strategy is applied to online calculating the pseudo-inverse of a matrix and nonlinear control of an inverted pendulum system. Both theoretical analysis and numerical simulations validate the effectiveness of proposed activation function.     

Word2000文档恢复技术

通过对Word2000文档文件删除后的磁盘结构及文档文件结构的分析研究．给出恢夏Word2000文档文件的技术过程。     

基于图像检测的发动机缸体探伤系统设计及应用

为了实现某型号航空发动机缸体的自动化检测,设计了一套全自动荧光磁粉探伤系统。介绍了系统的结构和实现方式、重点介绍了图像采集和图像处理部分,系统采用Laplacian算子对原始图像进行锐化处理,然后采用Prewitt算子进行边缘提取,最后采用面积和周长两个物理量作为判断产品合格与否的特征值;实际测量显示,系统的测量精度可达0.01 mm,满足发动机缸体检测的要求。     

合成孔径雷达1553B通信接口设计与实现

介绍某型号合成孔径雷达系统的1553B总线通信接口设计方案与工程实现;方案采用国内自主研发的4M/s速率1553B总线接口芯片,PC/104工控机与FPGA结合,通过硬件系统设计和软件编程,实现对1553B总线数据收发和雷达部分辅助数据的提供,实现项目总体对1553B总线通信接口的要求。实际应用情况表明,该通信接口运行稳定、可靠,具有一定的实用性和良好的应用前景。