高功率LDA紧密侧面抽运Nd:YLF两级双程离轴放大系统实验研究

 介绍了一台10mm口径两级双程离轴放大系统，实现了对5mm×5mm口径光束的激光放大，耦合系统采用高功率LDA紧密侧面直接抽运棒状Nd:YLF方式。分析并实验研究了在不同抽运电流、放大脉冲与放大器LDA抽运时刻的不同延时及不同注入能量条件下，放大系统及光束每次放大时放大特性的规律。实验得到：在放大系统5mm×5mm软光阑处注入1.58mJ能量时，放大系统可输出129.2mJ能量，能量提取效率达到19.5%，满足该系统的设计指标。     

Interplay of Electronic Structure and Bulk Properties in 2D and 3D Ternary Carbonitrides from First Principles

The changes in electronic structure and hardness as inferred from the bulk modulus are investigated for model structures of ternary compounds XC₃N₃ (X = B, Al, P, As, Ga) within the framework of density functional theory (DFT). The optimisations of the proposed two‐ (2D) and three‐dimensional (3D) structures and the calculations of the bulk moduli are performed by a pseudo potential method. The electronic structures are calculated with the augmented sphere wave method (ASW). The obtained hardness for 2D BC₃N₃ system (B₀ ～ 220 GPa) points to a magnitude close to that of graphitic C₃N₄. For heavier X atoms it decreases rapidly. This is equally observed for the 3D systems examined in the β‐C₃N₄ structure for which B₀(β‐BC₃N₃) amounts to ～330 GPa. Within the magnitude of the well known hard material cubic BN, the BC₃N₃ phases can be predicted as candidates for ultra hard materials. The electronic effect induced by the chemical nature of the X substitutional was examined according to its position in the periodic table i.e. X_III or X_V. Both, band structures and the electron localisation function (ELF) were used for this analysis. The ELF plots show a decreasing covalency with heavier X‐atoms. Potential applications of the devised systems are proposed such as dopings with atoms (Li, rare gas) and molecules (N₂).     

Multivariate analysis of non-homogeneous peaks in liquid chromatography

Summary The effects of concentration, separation and spectral similarity as factors influencing the accuracy of iterative target testing factor analysis (ITT-FA) are investigated for three component systems by the application of analysis of variance (ANOVAR). ANOVAR is applied over a range of peak separations to map the changing effects of the three factors with increasing overlap. Two error responses were measured and analysed, (a) Relative cluster error (RCE) a measure of the error over all peaks in a cluster and (b) Relative peak error (RPE) the error of an individual peak. Multicomponent analysis (MCA) a method requiringa priori spectral information, is used as a referee method for ITT-FA.     

Applying Text Analytics for Studying Research Trends in Dependability

The dependability of systems and networks has been the target of research for many years now. In the 1970s, what is now known as the top conference on dependability—The IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)—emerged gathering international researchers and sparking the interest of the scientific community. Although it started in niche systems, nowadays dependability is viewed as highly important in most computer systems. The goal of this work is to analyze the research published in the proceedings of well-established dependability conferences (i.e., DSN, International Symposium on Software Reliability Engineering (ISSRE), International Symposium on Reliable Distributed Systems (SRDS), European Dependable Computing Conference (EDCC), Latin-American Symposium on Dependable Computing (LADC), Pacific Rim International Symposium on Dependable Computing (PRDC)), while using Natural Language Processing (NLP) and namely the Latent Dirichlet Allocation (LDA) algorithm to identify active, collapsing, ephemeral, and new lines of research in the dependability field. Results show a strong emphasis on terms, like ‘security’, despite the general focus of the conferences in dependability and new trends that are related with ’machine learning’ and ‘blockchain’. We used the PRDC conference as a use case, which showed similarity with the overall set of conferences, although we also found specific terms, like ‘cyber-physical’, being popular at PRDC and not in the overall dataset.     

Coal analysis by diffuse reflectance near-infrared spectroscopy: Hierarchical cluster and linear discriminant analysis

An extensive study was carried out in coal samples coming from several origins trying to establish a relationship between nine coal properties (moisture (%), ash (%), volatile matter (%), fixed carbon (%), heating value (kcal/kg), carbon (%), hydrogen (%), nitrogen (%) and sulphur (%)) and the corresponding near-infrared spectral data. This research was developed by applying both quantitative (partial least squares regression, PLS) and qualitative multivariate analysis techniques (hierarchical cluster analysis, HCA; linear discriminant analysis, LDA), to determine a methodology able to estimate property values for a new coal sample. For that, it was necessary to define homogeneous clusters, whose calibration equations could be obtained with accuracy and precision levels comparable to those provided by commercial online analysers and, study the discrimination level between these groups of samples attending only to the instrumental variables. These two steps were performed in three different situations depending on the variables used for the pattern recognition: property values, spectral data (principal component analysis, PCA) or a combination of both. The results indicated that it was the last situation what offered the best results in both two steps previously described, with the added benefit of outlier detection and removal.     

Acoustic detection and classification of river boats

We present a robust algorithm to detect the arrival of a boat of a certain type when other background noises are present. It is done via the analysis of its acoustic signature against an existing database of recorded and processed acoustic signals. We characterize the signals by the distribution of their energies among blocks of wavelet packet coefficients. To derive the acoustic signature of the boat of interest, we use the Best Discriminant Basis method. The decision is made by combining the answers from the Linear Discriminant Analysis (LDA) classifier and from the Classification and Regression Trees (CART) that is also accompanied with an additional unit, called Aisles, that reduces false alarms rate. The proposed algorithm is a generic solution for process control that is based on a learning phase (training) followed by an automatic real time detection while minimizing the false alarms rate.     

添加聚合物对混合层流场特性影响的实验研究

叙述了适用于粘弹性流体混合层流场的实验装置的设计和研制．采用二维激光多普勒系统对混合层流场进行了测量，得到了平均速度剖面、动量厚度、湍流脉动强度、雷诺应力等一些流场的基本特征量．结果表明，混合层中加入聚合物后流场将有较大的变化，同时也说明本文所研制的实验装置满足实验的要求．