耐火材料混练设备现状与发展

针对我国耐火材料行业的主要生产设备之一──混练设备的当前技术状况、市场供应情况、使用现状进行了论述，就混练设备更新改造的发展趋势，提出了看法。

硅砖泥料混练过程研究

通过对Φ1 600×450湿碾机混练硅砖泥料过程中泥料主要成分的混合均匀度、泥料成型性能的变化规律研究,发现在各种物料加入湿碾机时,同时存在着扩散混合作用,延长干混、湿混阶段的时间,对于提高混合均匀度实际上没有意义;随捏练时间延长,泥料成型性能改善,砖坯气孔率呈下降趋势,但捏练14 min以后继续延长捏练时间,采用正常压制制度时,砖坯气孔率降低值已经很小。根据试验结果,将混练过程的各个时间段进行调整,在保证泥料成型性能的同时,大大缩短了混练时间,提高了设备利用率。

成型用配料混练状态的传感器系统

本文叙述了成型用配料混练状态的K传感器系统。并以MgO-C质耐火材料为例详尽地说明了该系统的卓越功能。日本黑崎窑业公司为清水工厂已实现了数台自动成型机的无人操作。

一种表征连续混炼机分散混合能力的方法

通过对混炼过程中附聚体解聚过程的分析,提出了两个描述混炼流场解聚能力的参数——解聚能量密度和描述混炼解聚效果的参数——平均解聚功。并运用该参数对混炼过程和混炼特性进行了表征,结果表明,解聚能量密度较好的表征了混炼流场熔体解聚能力的大小,而平均解聚功则可以直接表征混炼流场对共混物中颗粒的解聚效果。

机械处理畜禽粪便条件控制研究

G.P畜禽粪便处理机运行的特点是利用“混练”过程,以提高发酵物料的初始温度,缩短有机物的腐熟时间,因此对水分指标要求十分严格,应控制在含水51％～54％之间,调理剂的使用对调节水分、C/N、改善物理性状等都十分必要,而调理剂本身参与降解并成为肥料的组成部分。

蜂窝陶瓷的制备、性能及其应用

本文对蜂窝陶瓷的制备、性能、应用等方面作了详细的论述，指出蜂窝陶瓷在环保领域前景广阔。

首钢京唐300t钢包用上水口的试验研究

以棕刚玉、板状刚玉、锆莫来石、单质硅、氧化铝微粉以及石墨等为主要原料,热固性酚醛树脂为结合剂,制备了钢包用上水口试样,研究了混练工艺及原料组成对泥料性能的影响。结果表明:(1)新的混练工艺使泥料的自然堆积密度提高,并且物料分散均匀,尤其树脂对颗粒料的包裹较好,石墨分散均匀。(2)新的材料体系加入了锆莫来石等原料,使材料的抗热震性有所提高,材料更加致密。(3)试验水口满足了钢厂的需求,尤其抗热震性比之前大大提高。

Recognition of Speech Based on HMM/MLP Hybrid Network

This paper presents a new HMM/MLP hybrid network for speech recognition. By taking advantage of the discriminative training of MLP, the unreasonable model correctness assumption on the model correctness of the ML training in basic HMM can be overcome, and its discriminative ability and recognition performance can be improved. Experimental results demonstrate that the discriminative ability and recognition performance of HMM/MLP is apparently better than normal HMM.

清河县连铸耐火材料有限公司

我公司采用国内最先进的10000吨冷等静压成型和高效混练设备,技术力量雄厚,生产工艺独特,主要生产二大系列(铝碳和锆质系列)几十个品种的产品。 主要产品有:铝碳质整体塞捧,铝碳质浸入式水口,铝碳质长水口、镁碳质出钢口,锆质定经水口,铝锆质复合式中间仓上水口等耐火制品。 产品营销全国20多个钢厂,主要用户有通化钢厂、宣化钢厂、承德钢厂、天津二炼钢、小平钢厂。

钢包用富铝尖晶石炭不烧砖的研制

以高铝矾熟料、电熔镁铝尖晶石为主要原料，加入5-10％鳞片状石墨，外加6％磷酸铝溶液为结合剂，可制得气孔率低、体积密度高、强度大、抗热震、耐侵蚀的富铝尖晶石炭不烧钢包内衬砖。

Hybrid force control of astronaut rehabilitative training robot under active loading mode

In order to mitigate the effects of space adaptation syndrome(SAS) and improve the training efficiency of the astronauts, a novel astronaut rehabilitative training robot(ART) was proposed. ART can help the astronauts to carry out the bench press training in the microgravity environment. Firstly, a dynamic model of cable driven unit(CDU) was established whose accuracy was verified through the model identification. Secondly, to improve the accuracy and the speed of the active loading, an active loading hybrid force controller was proposed on the basis of the dynamic model of the CDU. Finally, the actual effect of the hybrid force controller was tested by simulations and experiments. The results suggest that the hybrid force controller can significantly improve the precision and the dynamic performance of the active loading with the maximum phase lag of the active loading being 9° and the maximum amplitude error being 2% at the frequency range of 10 Hz. The controller can meet the design requirements.

Researchers＇ Attitudes towards Varietal Development of Hybrid Rice： A Case Study in Myanmar

The purpose of this study was to identify the existing rice breeding programs in Myanmar and to determine researchers＇ attitudes on hybrid rice research mid its determinmlts. A sample consists of 56 researchers who are working in Department of Agricultural Research, Department of Agriculture and Yezin Agricultural University, and involving varietal development of hybrid rice. The research instruments were a questionnaire used by 4 points Likert scale of strongly agree, agree, less agree and not agree to measure on researchers＇ attitudes towards 14 determinants of varietal development of hybrid rice production. The study revealed that the average age of the researchers was 46.5 years ranged from 25 to 60 years. The majority of researchers were 51-60 years old （41.1%）. The working experience of researchers ranged from 5 to 36 years and the metal of their experience was 20 years. The educational level was Ph.D. （35.7%）, M.Agr.Sc. （26.8%）, and B.Agr.Sc. （37.5%）. Majority of researchers were female （76.8%） and 58.9% were rice breeders. Moreover, 48.2% of researchers obtained the hybrid rice technology from breeding training and the researchers who believed in their current breeding works were 51.8%. Among 33 rice breeders, 72.7% of the rice breeders applied only convention breeding method. In addition, researchers＇ opinions on farmer＇s perception of hybrid rice technology, 60.7% of the researchers agreed on inferior grain quality and 73.2% of researchers strongly agreed on not stable market. This study found out more thin1 half of the researchers strongly agreed on 10 out of 14 determinmlts such as poor infrastructure, low human resource development, parental problem, insufficient experience, limit germplasm resource, limit research facilities, no incentive for breeders, weak public-private partnership, fewer quality breeders and not enough research fund. Moreover, half of the researchers agreed on 3 determinants likely need special technical training, need international assistance and climate change challenges. Finally, development of hybrid rice research in Mymlmar, there will be needed international assistmlce, and upgraded to hybrid rice research center from currently hybrid rice research section and need integrated hybrid rice policy supported by government.

Sub-pixel mapping method based on BP neural network

A new sub-pixel mapping method based on BP neural network is proposed in order to determine the spatial distribution of class components in each mixed pixel.The network was used to train a model that describes the relationship between spatial distribution of target components in mixed pixel and its neighboring information.Then the sub-pixel scaled target could be predicted by the trained model.In order to improve the performance of BP network,BP learning algorithm with momentum was employed.The experiments were conducted both on synthetic images and on hyperspectral imagery(HSI).The results prove that this method is capable of estimating land covers fairly accurately and has a great superiority over some other sub-pixel mapping methods in terms of computational complexity.

Online split-and-merge expec tation-maximization training of Gaussian mixture model and its optimization

This paper presents a new online incremental training algorithm of Gaussian mixture model （GMM）, which aims to perform the expectation-maximization（EM） training incrementally to update GMM model parameters online sample by sample, instead of waiting for a block of data with the sufficient size to start training as in the traditional EM procedure. The proposed method is extended from the split-and-merge EM procedure, so inherently it is also capable escaping from local maxima and reducing the chances of singularities. In the application domain, the algorithm is optimized in the context of speech processing applications. Experiments on the synthetic data show the advantage and efficiency of the new method and the results in a speech processing task also confirm the improvement of system performance.

A new constrained maximum margin approach to discriminative learning of Bayesian classifiers

We propose a novel discriminative learning approach for Bayesian pattern classification, called ＇constrained maximum margin （CMM）＇. We define the margin between two classes as the difference between the minimum decision value for positive samples and the maximum decision value for negative samples. The learning problem is to maximize the margin under the con- straint that each training pattern is classified correctly. This nonlinear programming problem is solved using the sequential un- constrained minimization technique. We applied the proposed CMM approach to learn Bayesian classifiers based on Gaussian mixture models, and conducted the experiments on 10 UCI datasets. The performance of our approach was compared with those of the expectation-maximization algorithm, the support vector machine, and other state-of-the-art approaches. The experimental results demonstrated the effectiveness of our approach.