Sr2+–Mg2+-Doped SiAlON Ceramics

In the present work, multi-cation-doped (Sr²⁺–Mg²⁺) SiAlON ceramics were investigated. MgO and SrO were used in 100:0 and 50:50 molar ratios. The mixture was sintered at 1800° and 1830°C for 1 h in a gas pressure-sintering furnace. The results showed that sintered samples were composed of mainly α- and β-SiAlON phases and small amounts of some Sr-containing phases and SiAlON polytypes. According to Rietveld analysis of X-ray diffraction patterns, Mg is incorporated into the α-SiAlON structure. However, the incorporation of Sr is limited.     

XRF法在聚乙烯微量金属分析中的应用

探讨了用Ｘ射线荧光光谱分析法（ＸＲＦ法）测定聚乙烯中所含的微量金属Ｆｅ、Ｔｉ、Ａｌ的方法，简 分析条件及实验方法。     

An ERP software selection process with using artificial neural network based on analytic network process approach

An enterprise resource planning (ERP) software selection is known to be multi attribute decision making (MADM) problem. This problem has been modeled according with analytic network process (ANP) method due to fact that it considers criteria and sub criteria relations and interrelations in selecting the software.Opinions of many experts are obtained while building ANP model for the selection ERP then opinions are reduced to one single value by methods like geometric means so as to get desired results. To use ANP model for the selection of ERP for a new organization, a new group of expert’s opinions are needed. In this case the same problem will be in counter. In the proposed model, when ANP and ANN models are setup, an ERP software selection can be made easily by the opinions of one single expert. In that case calculation of geometric mean of answers that obtained from many experts will be unnecessary. Additionally the effect of subjective opinion of one single decision maker will be avoided. In terms of difficulty, ANP has some difficulties due to eigenvalue and their limit value calculation.An ANN model has been designed and trained with using ANP results in order to calculate ERP software priority. The artificial neural network (ANN) model is trained by results obtained from ANP. It seems that there is no any major difficulty in order to predict software priorities with trained ANN model. By this results ANN model has been come suitable for using in the selection of ERP for another new decision.     

Effects of Adhesive Composition on Green Joining of CePO_4-ZrO_2 Ceramics

1　Introduction Among structural advanced ceramics, zirconia isconsidered as an important ceramic material for its excel lent high temperature strength, resistance to wear and oxi dation.In order to widen its applications,it is essential todevelop re…     

Accelerate the alkaline hydrogen evolution reaction of the heterostructural Ni2P@Ni(OH)2/NF by dispersing a trifle of Ru on the surface

Electrocatalytic water splitting for hydrogen production plays a vital role in the development of new energy field, but there is still a lack of low-content precious metal or cost-effective non-noble metal catalysts for the hydrogen evolution reaction (HER). Therefore, how to develop the catalysts with a smaller amount of precious metal to achieve higher performance is still a major challenge. Herein, we have fabricated Ru–Ni₂P@Ni(OH)₂/NF-2 heterostructure by phosphating Ni(OH)₂/NF and then anchoring Ru on the surface through wet chemical strategy. Benefiting from its optimal ΔG_H1 and synergistic effect, this Ru–Ni₂P@Ni(OH)₂/NF-2 catalyst shows superior electrocatalytic HER kinetics in alkaline electrolyte. A small overpotential of 31 mV is needed for this electrocatalyst to obtain the current densities of 10 mA cm^?2 with remarkable durability over 24 h. This work provides a new strategy for the preparation of effective HER electrocatalyst with a low precious metal content.     

论非线性媒质中电磁孤波的存在性

本文讨论了非线性媒质中电磁孤波的存在性。作者在文中指出:F.Bloom~([1—3])的假设(λ3)是不恒成立的,从而可得在非线性媒质中有可能存在稳定的电磁孤波。     

多重网格法及其在微带电路计算中的应用

本文简要介绍了多重网格法的基本原理,并以盒内微带的位场及特性阻抗计算为例说明了多重网格法的收敛性.本文将完全多重网格法用于盒内 L型耦合微带的奇偶模位场及特性阻抗的计算。结果表明:多重网格法是电磁计算的一种高精度快速算法。     

Automatic segmentation of corpus collasum using Gaussian mixture modeling and Fuzzy C means methods

This paper presents a comparative study of the success and performance of the Gaussian mixture modeling and Fuzzy C means methods to determine the volume and cross-sectionals areas of the corpus callosum (CC) using simulated and real MR brain images. The Gaussian mixture model (GMM) utilizes weighted sum of Gaussian distributions by applying statistical decision procedures to define image classes. In the Fuzzy C means (FCM), the image classes are represented by certain membership function according to fuzziness information expressing the distance from the cluster centers. In this study, automatic segmentation for midsagittal section of the CC was achieved from simulated and real brain images. The volume of CC was obtained using sagittal sections areas. To compare the success of the methods, segmentation accuracy, Jaccard similarity and time consuming for segmentation were calculated. The results show that the GMM method resulted by a small margin in more accurate segmentation (midsagittal section segmentation accuracy 98.3% and 97.01% for GMM and FCM); however the FCM method resulted in faster segmentation than GMM. With this study, an accurate and automatic segmentation system that allows opportunity for quantitative comparison to doctors in the planning of treatment and the diagnosis of diseases affecting the size of the CC was developed. This study can be adapted to perform segmentation on other regions of the brain, thus, it can be operated as practical use in the clinic.     

Two approaches for solving the buffer allocation problem in unreliable production lines

This paper presents an integrated approach to solve the buffer allocation problem in unreliable production lines so as to maximize the throughput rate of the line with minimum total buffer size. The proposed integrated approach has two control loops; the inner loop and the outer loop. While the inner loop control includes an adaptive tabu search algorithm proposed by Demir et al. [8], binary search and tabu search are proposed for the outer loop. These nested loops aim at minimizing the total buffer size to achieve the desired throughput level. To improve the efficiency of the proposed tabu search, alternative neighborhood generation mechanisms are developed. The performances of the proposed algorithms are evaluated by extensive computational experimentation, and the results are reported.