生物氧化预处理中进气量实时预测数学模型研究

精准预测生物氧化预处理中的进气量对提高黄金提取率和节能降耗具有重要意义。以气体管流连续性方程和运动方程为控制方程，采用Preissmann隐格式法作为差分方法。同时，根据集合卡尔曼滤波(Ensemble Kalman filter，EnKF)算法原理，构造进气量、压强的状态空间模型。结果表明，基于气体管流控制方程建立的进气量模型预测结果与实际进气量观测值具有较好的一致性；与传统静态预测方法相比，EnKF同化方法引入实时观测值和模型参数的更新，有效提高了进气量的预测精度，其平均绝对误差、平均相对误差和均方根误差有明显的降低。可见，基于气体管流控制方程建立的预测模型结合EnKF同化方法是提高生物氧化槽进气量预测精度的有效手段。     

基于哈希链的软件定义网络路径安全

针对软件定义网络中，控制器无法保证下发的网络策略能够在转发设备上得到正确执行的安全问题，提出一种新的转发路径监控安全方案。首先以控制器的全局视图能力为基础，设计了基于OpenFlow协议的路径凭据交互处理机制；然后采用哈希链和消息验证码作为生成和处理转发路径凭据信息的关键技术；最后在此基础上，对Ryu控制器和Open vSwitch开源交换机进行深度优化，添加相应处理流程，建立轻量级的路径安全机制。测试结果表明，该机制能够有效保证数据转发路径安全，吞吐量消耗比SDN数据层可信转发方案（SDNsec）降低20%以上，更适用于路径复杂的网络环境，但时延和CPU使用率的浮动超过15%，有待进一步优化。     

Engineering egress data considering pedestrians with reduced mobility

To quantify the evacuation process, evacuation practitioners use engineering egress data describing the occupant movement characteristics. These data are typically based to young and fit populations. However, the movement abilities of occupants who might be involved in evacuations are becoming more variable—with the building populations of today typically including increasing numbers of individuals: with impairments or who are otherwise elderly or generally less mobile. Thus, there will be an increasing proportion of building occupants with reduced ability to egress. For safe evacuation, there is therefore a need to provide valid engineering egress data considering pedestrians with disabilities. Gwynne and Boyce recently compiled a series of data sets related to the evacuation process to support practitioner activities in the chapter Engineering Data in the SFPE Handbook of Fire Protection Engineering. This paper supplements these data sets by providing information on and presenting data obtained from additional research related to the premovement and horizontal movement of participants with physical‐, cognitive‐, or age‐related disabilities. The aim is to provide an overview of currently available data sets related to, and key factors affecting the egress performance of, mixed ability populations which could be used to guide fire safety engineering decisions in the context of building design.     

陈四楼煤矿“123456双重预防体系”的建设与应用

针对煤矿“双重预防体系”如何落地生根问题，结合陈四楼煤矿在风险分级管控和隐患排查治理方面的实用方法和“双重预防体系”的建设经验，深入研究了“双重预防体系”的相关标准、风险隐患事故之间的关系及其各自的产生和发展机理、安全风险的有关辨识评估方法、事故隐患的排查和治理方法，分析了传统安全管理模式与“双重预防体系”的新型安全管理模式的差别，总结出了“123456双重预防体系”这个囊括了事前安全风险辨识、事中隐患排查治理、事后安全现状评估的创新成果，实现了“事前、事中、事后”的全过程控制，对夯实煤矿安全管理根基、促进矿井平稳有序发展发挥着越来越重要的作用，为煤炭行业“双重预防体系”的落地生根提供了借鉴和参考。     

无失效数据机载多余度EWIS可靠性研究

针对高可靠度机载多余度EWIS各组成部分寿命服从指数分布但参数未知的情况，提出采用无失效数据可靠度分析方法评估EWIS的可靠度水平。通过Monte-Carlo仿真方法对连接形式为“先并联、后串联”EWIS各组成部分寿命进行抽样，利用“最小最大值”方法获得系统寿命的抽样值，用概率纸检验法初步判断EWIS寿命是否服从威布尔分布，再用Pearson拟合优度检验法判断EWIS寿命是否服从威布尔分布。结合无故障飞行时间的样本值与EWIS寿命服从威布尔分布的假设，采用无失效数据分析方法评估EWIS的可靠度水平。研究方法对机载多余度EWIS无失效数据可靠度分析有一定的贡献。     

基于张量分解融合RGB-D图像的物体识别

为了充分利用RGB-D图像的深度图像信息，提出了基于张量分解的物体识别方法。首先将RGB-D图像构造成一个四阶张量，然后将该四阶张量分解为一个核心张量和四个因子矩阵，再利用相应的因子矩阵将原张量进行投影，获得融合后的RGB-D数据，最后输入到卷积神经网络中进行识别。RGB-D数据集中三组相似物体的识别结果表明，利用张量分解融合RGB-D图像的物体识别准确率高于未采用张量分解的物体识别准确率，并且单一错分实例的准确率最高可提升99%。     

Stream-Based Data Sampling Mechanism for Process Object

Process object is the instance of process. Vertexes and edges are in the graph of process object. There are different types of the object itself and the associations between object. For the large-scale data, there are many changes reflected. Recently, how to find appropriate real-time data for process object becomes a hot research topic. Data sampling is a kind of finding c hanges o f p rocess o bjects. There i s r equirements f or s ampling to be adaptive to underlying distribution of data stream. In this paper, we have proposed a adaptive data sampling mechanism to find a ppropriate d ata t o m odeling. F irst o f all, we use concept drift to make the partition of the life cycle of process object. Then, entity community detection is proposed to find changes. Finally, we propose stream-based real-time optimization of data sampling. Contributions of this paper are concept drift, community detection, and stream-based real-time computing. Experiments show the effectiveness and feasibility of our proposed adaptive data sampling mechanism for process object.