基于特征融合的中文简历解析方法研究

针对基于规则和统计的传统中文简历解析方法效率低、成本高、泛化能力差的缺点，提出一种基于特征融合的中文简历解析方法，即级联Word2Vec生成的词向量和用BLSTM（Bidirectional Long Short-Term Memory）建模字序列生成的词向量，然后再结合BLSTM和CRF（Conditional Random Fields）对中文简历进行解析（BLSTM-CRF）。为了提高中文简历解析的效率，级联包含字序列信息的词向量和用Word2Vec生成的词向量，融合成一个新的词向量表示；再由BLSTM强大的学习能力融合词的上下文信息，输出所有可能标签序列的分值给CRF层；再由CRF引入标签之间约束关系求解最优序列。利用梯度下降算法训练神经网络，使用预先训练的词向量和Dropout优化神经网络，最终完成对中文简历的解析工作。实验结果表明，所提的特征融合方法优于传统的简历解析方法。     

空气预热器实时监控系统堵塞可视化性能研究

针对电站锅炉回转式空气预热器运行时上下表面不可见的问题，本文提出了一种视频监控与故障分析系统，可直接监测转子表面情况。该系统通过视频监控获取图像，结合改进的Retinex算法对其进行处理，实现了以下2个功能:1）能分析积灰程度以判断转子堵塞 情况；2）与温度场融合实时显示转子表面热点分布以预防二次燃烧。该系统已应用于某600 MW机组，实现了在热态环境下对空气预热器转子积灰程度、热点分布、堵塞程度的估算与可视化，大大提高了空气预热器运行的可靠性。     

火电机组负荷分配中多源不确定性因素影响分析

不确定性因素存在于火电机组负荷分配中，影响机组负荷分配、节能环保目标。本文综合考虑负荷预测不确定性、机组煤耗率不确定性与其CO2排放系数不确定性，分别构建火电机组一次能源消耗成本与CO2排放量最小目标下的火电机组负荷优化分配模型；以此为基础，引入析因分析方差分解方法，量化多源不确定性因素单独与交互作用下对节能、环保目标的影响程度。结果表明:负荷预测不确定性对火电机组节能、环保目标影响最为显著，相对影响程度分别为51.13%、62.70%；机组煤耗特性及其CO2排放系数影响次之，相对影响程度分别为47.58%、34.95%。此研究结果对不确定性条件下电力系统负荷分配具有借鉴价值。     

A dense and compact laser cladding layer with solid metallurgical bonding significantly improved corrosion resistance of Mg alloy for engineering applications

Although Mg alloy attracts great attention for engineering applications because of high specific strength and low density, low corrosion resistance limits its extensive use. In this study, Mg–Al–Zn–Mn alloy was treated via a laser cladding process to generate a dense and compact laser cladding layer with solid metallurgical bonding on the substrate for improving corrosion resistance, effectively hindering the corrosion pervasion into Mg alloy. The corrosion current density declined from 103 μA/cm² for Mg alloy to 13 μA/cm² for the laser cladding layer in NaCl aqueous solution. Moreover, the laser cladding layer was slightly corroded in comparison with Mg alloy in NaCl aqueous solution. Besides, the microhardness of the cladding layer reached a mean value of 170.5 HV, 3.1 times of Mg alloy (56.8 HV) due to the in situ formation of hardening intermetallic phases. Wear resistance of laser cladding layer was also obviously improved. These results demonstrated that the laser cladding layer obviously enhanced anticorrosion property of Mg alloy for engineering applications.     

Formation of a protective layer against corrosion on Mg alloy via alkali pretreatment followed by vanillic acid treatment

Although Mg alloy possesses high specific strength, low density, and good biocompatibility, poor corrosion resistance hinders its further applications. In the present study, an innovative protective layer against corrosion was prepared on the AZ31 Mg alloy via alkali pretreatment followed by vanillic acid treatment. The alkali pretreatment supplied –OH for the AZ31 Mg alloy surface to react with vanillic acid. The vanillic acid treatment played a crucial role in enhancing the corrosion resistance due to the excellent ability to act as a barrier and retard aqueous solution penetration, which effectively isolated the underlying Mg alloy from the corrosive environment. The corrosion current density of alkali and vanillic acid-treated Mg alloy (AZ31V) almost showed two orders of magnitude lower values in comparison with that of the AZ31 Mg alloy, and the corrosion potential of AZ31V Mg alloy increased from −1.41 to −1.25 V. The immersion tests proved that there was no occurrence of severe corrosion. Hence, the alkali pretreatment and vanillic acid treatment may represent a promising method to improve the corrosion resistance of Mg alloy.     

Automatic breast tumor detection in ABVS images based on convolutional neural network and superpixel patterns

Breast cancer is one of the most common female malignancies, as well as the second leading cause of mortality for women. Early detection and treatment can dramatically decrease the mortality rate. Recently, automated breast volume scanner (ABVS) has become one of the most frequently used diagnose methods for breast tumor screening because of its operator-independent and reproducible advantages. However, it is a challenging job to obtain the tumors’ accurate locations and shapes by reviewing hundreds of ABVS slices. In this paper, a novel computer-aided detection (CADe) system is developed to reduce clinicians’ reading time and improve the efficiency. The CADe system mainly contains three parts: tumor candidate acquisition, false-positive reduction and tumor segmentation. Firstly, a local phase-based approach is built to obtain breast tumor candidates for further recognition. Subsequently, a convolutional neural network (CNN) is applied to reduce false positives (FPs). The introduction of CNN can help to avoid complicated feature extraction as well as elevate the accuracy and efficiency. Finally, superpixel-based segmentation is used to outline the breast tumor. Here, superpixel-based local binary pattern (SLBP) is proposed to assist the segmentation, which improves the performance. The methods were evaluated on a clinical ABVS dataset whose abnormal cases were manually labeled by an experienced radiologist. The experiment results were mainly composed of two parts. At the FP reduction stage, the proposed CNN achieved 100% and 78.12% sensitivity with FPs/case of 2.16 and 0. At the segmentation stage, our SLBP obtained 82.34% true positive, 15.79% false positive and 83.59% Dice similarity. In summary, the proposed CADe system demonstrated promising potential to detect and outline breast tumors in ABVS images.

     

高精度多环片自动装配控制技术

为了实现对微小环片零件的自动化装配,搭建了自动装配系统.通过4根直线导向轴与4个直线轴承来提高系统的导向精度和刚度.采用直线导轨进行各装配作业模块之间的切换,保证了微小环片零件的自动装配与取出.在环片的装配方向上,螺旋升降机和光栅尺实现环片的位置精度控制.在Lab VIEW编程环境中,采用分层软件架构和模块化控制思想,避免了不必要的数据循环检测与丢失,能够达到环片组件的装配精度要求.控制系统分为系统初始化模块、参数设置模块、装配模块和取出模块,自动装配系统通过各个模块间的相互交流配合完成装配任务.采用本文中自动装配系统装配环片的实验结果表明,环片零件装配的最大位置误差为26μm,垂直度误差为17μm,平均装配时间为75 s/片,可满足环片组件所需的精度要求.     

水文序列相依变异识别的RIC定阶准则——以自回归模型为例

水文过程相依性是水文变异的主要表现形式之一,应用自回归模型对其进行拟合时合理确定模型阶数是一个难点问题。本文在分析AIC和BIC准则的基础上,提出了一种以原序列与其相依成分的相关系数作为拟合度指标,同时借用信息熵形式的函数式,作为模型不确定性度量指标的自回归模型定阶准则(简称RIC准则)。以AR(1)、AR(2)、AR(3)和AR(4)模型为例进行统计试验,将不同序列长度下该准则的定阶准确率与其他定阶准则进行比较,试验结果表明,RIC准则对于上述模型均具有较好的适应性,且定阶准确率远高于AIC准则,其中对于前三阶模型RIC准则优于BIC准则,但四阶模型略低于BIC准则。RIC准则的优势是可以同时满足模型定阶、相依程度分级与模型检验的需求,将其应用于实测水文序列分析,结果显示,该准则能较准确地识别自回归模型的阶数,且符合提出的"相依有变异而残差无变异的最小阶数"的检验标准。     

马钢张庄矿高压辊磨机装配工艺研究

针对马钢张庄矿高压辊磨机辊套疲劳断裂严重、对辊精度不能满足生产要求等问题，马钢重机公司根据张庄矿实际生产要求对对辊进行国产化，国产化内容包括辊轴、辊套等零部件的新制以及装配工艺攻关，通过技术研发同时结合实际生产经验，成功对高压辊磨机辊套与辊轴以及辊轴与轴承进行装配，完成了张庄矿高压辊磨机整对对辊的国产化，为该型设备后续生产及优化提供了理论和实践参考依据。