Effect of Cu-Rich Phase Precipitation on the Microstructure and Mechanical Properties of CoCrNiCux Medium-Entropy Alloys Prepared via Laser Directed Energy Deposition

CoCrNiCux (x=0.16,0.33,0.75,and 1) without macro-segregation medium-entropy alloys (MEAs) was prepared using laser directed energy deposition (LDED).The microstructure and mechanical properties of CoCrNiCux alloys with increas-ing Cu content were investigated.The results indicate that a single matrix phase changes into a dual-phase structure and the tensile fracture behaviors convert from brittle to plastic pattern with increasing Cu content in CoCrNiCux alloys.In addi-tion,the tensile strength of CoCrNiCux alloys increased from 148 to 820 MPa,and the ductility increased from 1 to 11％with increasing Cu content.The nano-precipitated particles had a mean size of approximately 20 nm in the Cu-rich phase area,and a large number of neatly arranged misfit dislocations were observed at the interface between the two phases due to Cu-rich phase precipitation in the CoCrNiCu alloy.These misfit dislocations hinder the movement of dislocations during tensile deformation,as observed through transmission electron microscopy.This allows the CoCrNiCu alloy to reach the largest tensile strength and plasticity,and a new strengthening mechanism was achieved for the CoCrNiCu alloy.Moreover,twins were observed in the matrix phase after tensile fracture.Simultaneously,the dual-phase structure with different elastic moduli coordinated with each other during the deformation process,significantly improving the plasticity and strength of the CoCrNiCu alloy.     

基于k-shell的复杂网络最短路径近似算法

复杂网络最短路径经典算法的处理效率较低，不适用于大规模复杂网络，而现有近似算法通用性有限，且计算准确率不理想，不能满足规模日益扩大的复杂网络中的最短路径计算需求。针对于此，提出基于[k]-shell的复杂网络最短路径近似算法。算法利用节点的[k]-shell值进行网络划分并引导搜索路径，利用超点聚合处理[k]-shell子网来降低路径搜索中节点和连边的规模，通过在路径搜索过程使用双向搜索树方法提高算法的计算效率和准确率。实验结果表明，算法通用性较好，在现实与仿真大规模复杂网络中均具有较高的计算效率和准确率。     

面向二进制程序的导向性模糊测试方法

为了解决当前模糊测试技术中变异存在一定的盲目性以及变异生成的样本大多经过相同的高频路径的问题，提出并实现了一种基于轻量级程序分析技术的二进制程序模糊测试方法。首先对目标二进制程序进行静态分析来筛选在模糊测试过程中阻碍样本文件深入程序内部的比较指令；随后对目标文件进行插桩来获取比较指令中操作数的具体值，并根据该具体值为比较指令建立实时的比较进度信息，通过比较进度衡量样本的重要程度；然后基于模糊测试过程中实时的路径覆盖信息为经过稀有路径的样本增加其被挑选进行变异的概率；最后根据比较进度信息并结合启发式策略有针对性地对样本文件进行变异，通过变异引导提高模糊测试中生成能够绕过程序规约检查的有效样本的效率。实验结果表明，所提方法发现crash及发现新路径的能力均优于模糊测试工具AFL-Dyninst。     

A gradient boosting decision tree approach for insider trading identification: An empirical model evaluation of China stock market

Insider trading is a kind of criminal behavior in stock market by using nonpublic information. In recent years, it has become the major illegal activity in China’s stock market. In this study, a combination approach of GBDT (Gradient Boosting Decision Tree) and DE (Differential Evolution) is proposed to identify insider trading activities by using data of relevant indicators. First, insider trading samples occurred from year 2007 to 2017 and corresponding non-insider trading samples are collected. Next, the proposed method is trained by the GBDT, and initial parameters of the GBDT are optimized by the DE. Finally, out-of-samples are classified by the trained GBDT–DE model and its performances are evaluated. The experiment results show that our proposed method performed the best for insider trading identification under time window length of ninety days, indicating the relevant indicators under 90-days time window length are relatively more useful. Additionally, under all three time window lengths, relative importance result shows that several indicators are consistently crucial for insider trading identification. Furthermore, the proposed approach significantly outperforms other benchmark methods, demonstrating that it could be applied as an intelligent system to improve identification accuracy and efficiency for insider trading regulation in China stock market.     

2.5 GHz城市环境电磁态势的计算与补偿

复杂城市空间的电磁态势分布可以通过电磁场数值计算的方法进行预测。文章使用矩量法(MOM)结合一致性几何绕射理论(UTD)的方法对2.5 GHz频率下某小区环境中的电磁态势进行了仿真计算以及实际测量。场景中的树木结构在此频率下显示出比较强烈的波动性,对电磁仿真计算结果产生了不可忽略的影响,文中将其对仿真计算结果的影响进行了单独建模仿真,给出其产生影响的经验值,对仿真结果进行修正。修正结果与测量结果对比证明该经验值在该频率下可以有效补偿计算结果的缺失。     

Design structure matrix (DSM) method application to issue of modeling and analyzing the fault tree of a wind energy asset

The perpetual energy production of a wind farm could be accomplished (under proper weather conditions) if no failures occurred. But even the best possible design, manufacturing, and maintenance of a system cannot eliminate the failure possibility. In order to understand and minimize the system failures, the most crucial components of the wind turbines, which are prone to failures, should be identified. Moreover, it is essential to determine and classify the criticality of the system failures according to the impact of these failure events on wind turbine safety. The present study is processing the failure data from a wind farm and uses the Fault Tree Analysis as a baseline for applying the Design Structure Matrix technique to reveal the failure and risk interactions between wind turbine subsystems. Based on the analysis performed and by introducing new importance measures, the “readiness to fail” of a subsystem in conjunction with the “failure riskiness” can determine the “failure criticality.” The value of the failure criticality can define the frame within which interventions could be done. The arising interventions could be applied either to the whole system or could be focused in specified pairs of wind turbine subsystems. In conclusion, the method analyzed in the present research can be effectively applied by the wind turbine manufacturers and the wind farm operators as an operation framework, which can lead to a limited (as possible) design‐out maintenance cost, failures' minimization, and safety maximization for the whole wind turbine system.     

太阳能及空气源热泵复合供热系统故障诊断研究与应用

为确保复杂太阳能热水系统的稳定运行,有必要采集实时运行数据从中获取故障特征信号,通过专家系统进行自动故障诊断。采用故障树分析方法,以太阳能热利用系统典型故障为例构建故障树,求解最小割集,并以此为基础建立诊断知识库;运用正向推理结合人工辅助决策机制进行故障诊断和定位,建立故障诊断专家系统。开发故障诊断软件,并在工程中进行测试,验证故障辨识的准确性。     

Predicting Prostephanus truncatus (Horn) (Coleoptera: Bostrichidae) populations and associated grain damage in smallholder farmers’ maize stores: A machine learning approach

Prostephanus truncatus is a notorious pest of stored-maize grain and its spread throughout sub-Saharan Africa has led to increased levels of grain storage losses. The current study developed models to predict the level of P. truncatus infestation and associated damage of maize grain in smallholder farmer stores. Data were gathered from grain storage trials conducted in Hwedza and Mbire districts of Zimbabwe and correlated with weather data for each site. Insect counts of P. truncatus and other common stored grain insect pests had a strong correlation with time of year with highest recorded numbers from January to May. Correlation analysis showed insect-generated grain dust from boring and feeding activity to be the best indicator of P. truncatus presence in stores (r = 0.70), while a moderate correlation (r = 0.48) was found between P. truncatus numbers and storage insect parasitic wasps, and grain damage levels significantly correlated with the presence of Tribolium castaneum (r = 0.60). Models were developed for predicting P. truncatus infestation and grain damage using parameter selection algorithms and decision-tree machine learning algorithms with 10-fold cross-validation. The P. truncatus population size prediction model performance was weak (r = 0.43) due to the complicated sampling and detection of the pest and eight-week long period between sampling events. The grain damage prediction model had a stronger correlation coefficient (r = 0.93) and is a good estimator for in situ stored grain insect damage. The models were developed for use under southern African climatic conditions and can be improved with more input data to create more precise models for building decision-support tools for smallholder maize-based production systems.     

直投式纳豆菌发酵剂制备工艺优化

为探索出一种工艺简便、成本低且活菌数高的直投式纳豆菌（Bacillus natto）发酵剂的制备方法，该研究以大米粉为基质替代传统的种子液培养基培养纳豆菌后直接将其烘干制成直投式纳豆菌发酵剂，通过单因素及正交试验优化直投式纳豆菌发酵剂的制备工艺。结果表明，用含1.5%蛋白胨的大米粉作为培养基，在接种量4.0%、加水量40%、培养温度43 ℃条件下培养纳豆菌28 h，菌体生长良好，将培养物烘干后制成的直投式纳豆菌发酵剂中的活菌数含量达4.71×109 CFU/g。此技术操作简便，可推广至工业生产中，简化生产过程。