珐琅彩在现代中式家具设计中的应用

目前,我国家具的发展处于瓶颈阶段,市场需要多元化的产品来满足消费者日益增长的精神文化需求,当前的家具设计又缺乏创新,在国际市场上难以形成自我特色。中国古代工艺美术曾达到相当的高度,其中,珐琅彩盛名远播,工艺精湛,器形优美,值得我们进行深入研究和创新。本文通过对珐琅彩历史、工艺及图案装饰与色彩搭配方面的研究,提炼出珐琅彩适合现代家具设计的元素,以期为设计出能满足现代人们审美需要,又能实现具体功能,并适合现代市场的珐琅家具提供参考。     

减粘裂化分馏塔顶系统的腐蚀及防护

辽河石化分公司减粘裂化装置改炼辽河超稠油的减压渣油后 ,分馏塔顶系统由HCl -H2 S -HCN -有机酸 -H2 O引起的电化学腐蚀严重 ,其中油水分离器局部腐蚀速率达 3.1mm/a ,12AlMoV管束的空冷器运行不足两个月即发生泄漏。塔顶系统采用BZH - 1中和缓蚀剂、无机氨BZH - 913油溶性缓蚀剂综合注剂方案 ,使腐蚀得到控制     

New concept of surface modification to LiCoO2

As the continuance of our series study on LiCoO₂ surface modification, the complicated traditional surface coating method is replaced with simple addition of amorphous YPO₄ and Al₂O₃ in commercial LiCoO₂ or in commercial electrolyte based on our understanding to the improvement mechanism of surface modification. Comprehensive studies by X-ray photoelectron spectroscopy (XPS), gas chromatography and mass spectroscopy (GC–MS), inductively coupled plasma (ICP) and Fourier transformed infrared (FTIR) indicate that the products of spontaneous reaction between the additive and the LiPF₆ based electrolyte are responsible for the performance improvements.     

DH-2001综合地化录井仪的研制

地化录井仪是一种采用岩石热解法快速定量评价生油岩和储油岩的设备。文章介绍了DH - 2 0 0 1综合地化录井仪的组成和功能 ,阐述了仪器硬件和软件的设计思想。实际应用证明 ,该仪器的设计先进、实用     

涡流管类比逆流换热器方法的研究

结合Scheper，Lewins和Bejan的理论模型，对涡流管类比逆流换热器模型进行了深入地分析，得出了冷流分量对温度分离效应的函数关系式，为了解涡流管机理和实验中强化涡流管温度分离效应提供了理论依据。     

双极型静电感应晶体管开关时间的测量与分析

从理论和实验两方面对静电感应晶体管（ＢＳＩＴ）的开关时间进行了分析和测量，提出了简单的分析方法，将影响ＢＳＩＴ开关时间的各个因素归结为结构因子和材料因子，从而简化了分析影响ＢＳＩＴ开关时间的因素，对于ＢＳＩＴ的实际工艺，结构设计有指导意义。     

苯部分加氢催化剂失活原因的研究

探讨了环己醇装置苯部分加氢催化剂失活的原因，分析了失活机理，并结合实例——母液置换法解决催化剂的氮化物中毒。     

基于过程能力指数的刀具寿命研究

利用Glejser检验方法拟舍出刀具磨损过程残差模型，在此基础上，计算换刀时刻的过程能力指数，并且根据企业所要求的最低过程能力指数，计算刀具的质量寿命，提出将刀具的切削寿命和质量寿命结合起来进行换刀决策的方法。     

农发行应为贫困地区的新农村建设发挥作用

近两年来,中央通过多种政策支持广大农村的社会主义新农村建设,东部发达地区发展较快,中西部和革命老区发展较慢。促进农村发展,     

iMapReduce: A Distributed Computing Framework for Iterative Computation

Iterative computation is pervasive in many applications such as data mining, web ranking, graph analysis, online social network analysis, and so on. These iterative applications typically involve massive data sets containing millions or billions of data records. This poses demand of distributed computing frameworks for processing massive data sets on a cluster of machines. MapReduce is an example of such a framework. However, MapReduce lacks built-in support for iterative process that requires to parse data sets iteratively. Besides specifying MapReduce jobs, users have to write a driver program that submits a series of jobs and performs convergence testing at the client. This paper presents iMapReduce, a distributed framework that supports iterative processing. iMapReduce allows users to specify the iterative computation with the separated map and reduce functions, and provides the support of automatic iterative processing within a single job. More importantly, iMapReduce significantly improves the performance of iterative implementations by (1) reducing the overhead of creating new MapReduce jobs repeatedly, (2) eliminating the shuffling of static data, and (3) allowing asynchronous execution of map tasks. We implement an iMapReduce prototype based on Apache Hadoop, and show that iMapReduce can achieve up to 5 times speedup over Hadoop for implementing iterative algorithms.