Damage and deterioration mechanism and curing technique of concrete structure in main coal cleaning plants

Concrete structures in main coal cleaning plants have been rebuilt and reinforced in the coal mines of the Shanghai Da-tun Energy Sources Co. Ltd., the first colliery of the Pingdingshan Coal Co. Ltd. and the Sanhejian mine of the Xuzhou Mining Group Co. Ltd. In these projects, the operating environment and reliability of concrete structures in the main plants of the three companies were investigated and the safety of the structures inspected. Qualitative and quantitative analyses were made on the spe-cial natural, technological and mechanical environments around the structures. On the basis of these analyses, we discuss the long-term, combined actions of the harsh natural (corrosive gases, liquids and solids) and mechanical environments on concrete structures and further investigated the damage and deteriorating mechanisms and curing techniques of concrete structures in the main coal cleaning plants. Our study can provide a theoretical basis for ensuring the reliability of concrete structures in main coal cleaning plants.     

电容器引线焊接机冲压切边凸轮的三维精确造型

根据电容器引线焊接机冲压切边模具中的凸轮设计要求,利用Pro/ENGINEER软件找出凸轮随动件滚子中心的轨迹,通过可变截面扫描间接得到凸轮的三维精确模型。为类似零件的建模提供一种行之有效的方法,并为后续的仿真分析和制造加工提供一种依据。     

高等院校开展学生职业生涯规划教育的思考

职业生涯规划对于人生发展具有极为重要的指导意义,对在校大学生进行职业生涯规划教育和指导,是高等学校人才培养的一项重要环节。文章针对高校学生对今后从业的认知现状和目前高校在开展就业教育工作中存在的不足,提出高等学校必须通过全程化和系统化的职业生涯规划教育指导,有效帮助学生发现和挖掘自身潜能,引导学生根据所学专业和个人志向及特长,设定毕业后的从业方向,确立大学不同阶段的努力目标,指导学生根据社会和个人发展的实际情况,实时修正从业方向和努力目标。在不断完善学生综合素质和专业技能的基础上,促进学生顺利完成学业、从容走向社会、尽早实现人生价值。     

配电网金属氧化物避雷器的选择

文章阐述了配电网金属氧化物避雷器选择的基本内容,给出了选择结果.     

资源生产供应链履行社会责任的内在动力研究

运用博弈论的基本思想,通过构造一个资源生产供应链,从资源保护这个角度出发,以资源生产供应链中的节点企业——资源开采商开采自然资源为例,对资源生产供应链履行社会责任的内在动力进行了研究。结果表明：对资源开采商合作开采带来的收益增量进行合理分配,既能使资源开采商进行合作,又能实现供应链系统与各资源开采商的帕累托最优。     

湖北黄麦岭沉积变质磷灰岩选矿技术研究

黄麦岭磷矿属较易选的低品位沉积变质磷灰岩矿,通过扩能改造、回水利用等措施,不仅提高了资源的综合利用率,也为公司每年降低生产成本4 000多万元,创造了可观的经济效益.     

基于模糊神经网络的大场景人群密度估计方法 *

提出了一种估计大场景下密集人群密度的方法。该方法根据人类视觉的模糊性原理,认为用模糊集来划分人群密度范围比用确定的方法更符合人眼视知觉的认知方式,利用统计的方法确定灰度共生矩阵各指标对于各个密度类别的隶属函数;设计基于误差反向传播训练算法（BP）的模糊神经网络,计算样本模式对于各个密度类别的隶属度,并根据人群密度变化的时域连续性原理对人群密度范围进行合理估计。实验表明该方法提高了估计精度。     

异构多核处理器的任务分配及能耗的研究*

异构多核处理器采用不同的任务分配与调度算法,会导致不同的时间消耗与能量消耗,采用合适的任务分配与调度算法能节省较多的能耗。目前普遍认为最有发展前途的任务分配与调度技术是先用启发式方法进行分组,然后再用遗传算法进行调度。在改进任务分组后,又首次提出了用遗传算法解决能耗问题。实验结果表明在实时要求不高的情况下,能以较小的时间代价来节省较多的能耗。     

Research on technology of desktop virtualization based on SPICE protocol and its improvement solutions

Increasingly mature cloud computing technology promotes virtual desktop technology, which can solve many problems existing in traditional computing models. However, virtual desktop solutions introduce the thorny problem of how to deliver a real desktop experience to users, as if they are using it locally, especially when playing video. The SPICE （simple protocol for independent computing environments） virtual desktop solution provides several image compression algorithms to address this problem with the purpose of making virtual desktops as real as possible. Although different compression algorithms can contribute their own abilities to different images to a large extent, switching between them is a big problem that consumes a large amount of resources to detect the different type of image and also causes jitter of the virtual desktop. This paper proposes a new solution, called SPICEx, using the JPEG2000 compression algorithm with dynamic compression ratios to solve the problem and finally validates that the performance is better than that of SPICE. With better quality of user experience and also reducing bandwidth consumption, SPICEx solution is meaningful in virtual desktop fields and can be widely used.     

Robust sparse principal component analysis

The model for improving the robustness of sparse principal component analysis（PCA） is proposed in this paper. Instead of the l2-norm variance utilized in the conventional sparse PCA model,the proposed model maximizes the l1-norm variance,which is less sensitive to noise and outlier. To ensure sparsity,lp-norm（0 p 1） constraint,which is more general and effective than l1-norm,is considered. A simple yet efficient algorithm is developed against the proposed model. The complexity of the algorithm approximately linearly increases with both of the size and the dimensionality of the given data,which is comparable to or better than the current sparse PCA methods. The proposed algorithm is also proved to converge to a reasonable local optimum of the model. The efficiency and robustness of the algorithm is verified by a series of experiments on both synthetic and digit number image data.