泰氟隆烧蚀产物对电子密度的影响

采用WNND格式,对有泰氟隆烧蚀产物引射的化学非平衡NS方程进行了数值模拟。采用7组元纯空气化学反应和19组元、28种反应的空气—泰氟隆化学反应系统,对照计算了壁面有泰氟隆烧蚀产物引射和纯空气绕流两种流场,研究了泰氟隆烧蚀产物对电子密度的影响。     

Production scheduling with history‐dependent setup times

We consider a parallel‐machine scheduling problem with jobs that require setups. The duration of a setup does not depend only on the job just completed but on a number of preceding jobs. These setup times are referred to as history‐dependent. Such a scheduling problem is often encountered in the food processing industry as well as in other process industries. In our model, we consider two types of setup times—a regular setup time and a major setup time that becomes necessary after several “hard‐to‐clean” jobs have been processed on the same machine. We consider multiple objectives, including facility utilization, flexibility, number of major setups, and tardiness. We solve several special cases assuming predetermined job sequences and propose strongly polynomial time algorithms to determine the optimal timing of the major setups for given job sequences. We also extend our analysis to develop pseudopolynomial time algorithms for cases with additional objectives, including the total weighted completion time, the total weighted tardiness, and the weighted number of tardy jobs. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

从吉化双苯厂爆炸事故处置解读化工火灾扑救对策

吉化双苯厂“11.13”爆炸火灾事故是一起典型的化工类火灾事故,造成了严重的财产损失和人员伤亡。这起火灾爆炸事故具有爆炸、燃烧速度快、立体式燃烧、过火面积大、危害性大等特点,总结了这起事故处置经验,给出了准确判断,科学决策;快攻近战;统一指挥,协同作战;多种措施相结合;冷却防爆,堵截蔓延;隐蔽抵近,适时出击等处置化工类火灾的对策。     

防化科研工作的6S管理浅析

介绍了6S管理的基本内容和具体实施标准,论述了推行6S管理对防化科研工作的重要意义,探讨了实施过程中应把握的问题。     

铁酸镍和铁酸锰的制备及磁性对比

用化学共沉淀法在90℃的反应温度制备了NiFe2O4和MnFe2O4铁酸盐多晶微粉,发现经沉淀洗涤后直接得到MnFe2O4纳米微粉,不需热处理过程;而要获得NiFe2O4需要对沉淀洗涤后的前驱体进行热处理。利用振动样品磁强计测量了样品在室温下的磁性能,对两种磁粉的磁性进行了对比。     

A misclassification cost‐minimizing evolutionary–neural classification approach

Machine learning algorithms that incorporate misclassification costs have recently received considerable attention. In this paper, we use the principles of evolution to develop and test an evolutionary/genetic algorithm (GA)‐based neural approach that incorporates asymmetric Type I and Type II error costs. Using simulated, real‐world medical and financial data sets, we compare the results of the proposed approach with other statistical, mathematical, and machine learning approaches, which include statistical linear discriminant analysis, back‐propagation artificial neural network, integrated cost preference‐based linear mathematical programming‐based minimize squared deviations, linear integrated cost preference‐based GA, decision trees (C 5.0, and CART), and inexpensive classification with expensive tests algorithm. Our results indicate that the proposed approach incorporating asymmetric error costs results in equal or lower holdout sample misclassification cost when compared with the other statistical, mathematical, and machine learning misclassification cost‐minimizing approaches. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006.     

非晶碳类金刚石薄膜摩擦学特性及其应用

综合地介绍了类金刚石膜研究现状,着重说明了非晶碳类金刚石薄膜的摩擦学特性,分析了沉积方法、掺杂元素、摩擦环境、基体及对偶材料对其摩擦学特性的影响。最后,简要说明了非晶碳类金刚石膜应用情况。     

Predicting intensive care unit bed occupancy for integrated operating room scheduling via neural networks

In a master surgery scheduling (MSS) problem, a hospital's operating room (OR) capacity is assigned to different medical specialties. This task is critical since the risk of assigning too much or too little OR time to a specialty is associated with overtime or deficit hours of the staff, deferral or delay of surgeries, and unsatisfied—or even endangered—patients. Most MSS approaches in the literature focus only on the OR while neglecting the impact on downstream units or reflect a simplified version of the real‐world situation. We present the first prediction model for the integrated OR scheduling problem based on machine learning. Our three‐step approach focuses on the intensive care unit (ICU) and reflects elective and urgent patients, inpatients and outpatients, and all possible paths through the hospital. We provide an empirical evaluation of our method with surgery data for Universitätsklinikum Augsburg, a German tertiary care hospital with 1700 beds. We show that our model outperforms a state‐of‐the‐art model by 43% in number of predicted beds. Our model can be used as supporting tool for hospital managers or incorporated in an optimization model. Eventually, we provide guidance to support hospital managers in scheduling surgeries more efficiently.     

基于改进核极限学习机和集成学习理论的目标机动轨迹预测

为了提高目标轨迹预测的精度以及预测模型的泛化能力,提出基于改进蝙蝠算法优化的核极限学习机(Kernel Extreme Learning Machine,KELM)和集成学习理论目标机动轨迹预测模型。构建KELM模型,并采用改进的蝙蝠算法对KELM的参数进行优化;以优化后的KELM神经网络为弱预测器,结合集成学习算法生成强预测器,通过训练不断优化强预测的结构和参数,得到一种基于集成学习理论的目标机动轨迹预测模型;基于不同规模的样本,将所得预测模型与逆传播神经网络、支持向量机和极限学习机等模型进行对比分析。仿真结果表明:所提目标机动轨迹预测模型具有较好的预测精度和泛化能力。     

等离子体销毁日本遗弃化学武器排放气体采集方法选择探讨

等离子体销毁日本化学武器是目前正在探索的新课题,销毁过程排放尾气采集方法是该课题中需研究的内容之一。在认真分析、综合比较的基础上,提出了适应等离子体销毁日本遗弃化学武器的排放尾气采集方法的看法及其须关注的问题。