EFFECT OF PORE DIFFUSION ON DEACTIVATING RATES OF SECOND ORDER REACTION

The research and development of catalysts, the design and operation of catalytic reactors are complicated by the phenomenon of catalyst deactivation which is affected by various factors. In this paper, the effect of internal mass transfer resistance in the second order catalytic reaction system of uniform independent deactivation on both reaction and deactivation rates of straight cylindrical pore model has been discussed. In addition, the quantitative relations between effectiveness factor and Thiele modulus in second order reaction and first order deactivation system have been correlated     

3D fingerprint reconstruction system using feature correspondences and prior estimated finger model

The paper studies a 3D fingerprint reconstruction technique based on multi-view touchless fingerprint images. This technique offers a solution for 3D fingerprint image generation and application when only multi-view 2D images are available. However, the difficulties and stresses of 3D fingerprint reconstruction are the establishment of feature correspondences based on 2D touchless fingerprint images and the estimation of the finger shape model. In this paper, several popular used features, such as scale invariant feature transformation (SIFT) feature, ridge feature and minutiae, are employed for correspondences establishment. To extract these fingerprint features accurately, an improved fingerprint enhancement method has been proposed by polishing orientation and ridge frequency maps according to the characteristics of 2D touchless fingerprint images. Therefore, correspondences can be established by adopting hierarchical fingerprint matching approaches. Through an analysis of 440 3D point cloud finger data (220 fingers, 2 pictures each) collected by a 3D scanning technique, i.e., the structured light illumination (SLI) method, the finger shape model is estimated. It is found that the binary quadratic function is more suitable for the finger shape model than the other mixed model tested in this paper. In our experiments, the reconstruction accuracy is illustrated by constructing a cylinder. Furthermore, results obtained from different fingerprint feature correspondences are analyzed and compared to show which features are more suitable for 3D fingerprint images generation.     

A global energy optimization framework for 2.1D sketch extraction from monocular images

The 2.1D sketch is a layered image representation, which assigns a partial depth ordering of over-segmented regions in a monocular image. This paper presents a global optimization framework for inferring the 2.1D sketch from a monocular image. Our method only uses over-segmented image regions (i.e., superpixels) as input, without any information of objects in the image, since (1) segmenting objects in images is a difficult problem on its own and (2) the objective of our proposed method is to be generic as an initial module useful for downstream high-level vision tasks. This paper formulates the inference of the 2.1D sketch using a global energy optimization framework. The proposed energy function consists of two components: (1) one is defined based on the local partial ordering relations (i.e., figure-ground) between two adjacent over-segmented regions, which captures the marginal information of the global partial depth ordering and (2) the other is defined based on the same depth layer relations among all the over-segmented regions, which groups regions of the same object to account for the over-segmentation issues. A hybrid evolution algorithm is utilized to minimize the global energy function efficiently. In experiments, we evaluated our method on a test data set containing 100 diverse real images from Berkeley segmentation data set (BSDS500) with the annotated ground truth. Experimental results show that our method can infer the 2.1D sketch with high accuracy.     

GLCM based extraction of flame image texture features and KPCA-GLVQ recognition method for rotary kiln combustion working conditions

According to the pulverized coal combustion flame image texture features of the rotary-kiln oxide pellets sintering process,a combustion working condition recognition method based on the generalized learning vector(GLVQ) neural network is proposed.Firstly,the numerical flame image is analyzed to extract texture features,such as energy,entropy and inertia,based on grey-level co-occurrence matrix(GLCM) to provide qualitative information on the changes in the visual appearance of the flame.Then the kernel principal component analysis(KPCA) method is adopted to deduct the input vector with high dimensionality so as to reduce the GLVQ target dimension and network scale greatly.Finally,the GLVQ neural network is trained by using the normalized texture feature data.The test results show that the proposed KPCA-GLVQ classifer has an excellent performance on training speed and correct recognition rate,and it meets the requirement for real-time combustion working condition recognition for the rotary kiln process.     

试谈高可用性计算机实训室的配置与管理

基于计算机实训教学的需求,重点探讨高可用性计算机实训室的搭建要求、配置特点与管理策略。     

中国古代陶瓷雕塑的美学特征

中华民族是个古老的、有着悠久历史和灿烂文明的伟大民族,远在八千年前,中国的文明在世界就已初露曙光。漫步在漫长的历史长河边,流连于丰富的博物馆展厅里,对我国悠久的历史和灿烂的文明作一次美的巡礼该是使人感到无比的欣慰和自豪的了。美学特征乃艺术的属性,总结它不是为了停留于前人的成果上,而是为了新的创造和新的开拓。     

An intelligent stock trading system using comprehensive features

The aim of this study is to predict automatic trading decisions in stock markets. Comprehensive features (CF) for predicting future trend are very difficult to generate in a complex environment, especially in stock markets. According to related work, the relevant stock information can help investors formulate objects that may result in better profits. With this in mind, we present a framework of an intelligent stock trading system using comprehensive features (ISTSCF) to predict future stock trading decisions. The ISTSCF consists of stock information extraction, prediction model learning and stock trading decision. We apply three different methods to generate comprehensive features, including sentiment analysis (SA) that provides sensitive market events from stock news articles for sentiment indices (SI), technical analysis (TA) that yields effective trading rules based on trading information on the stock exchange for technical indices (TI), as well as the trend-based segmentation method (TBSM) that raises trading decisions from stock price for trading signals (TS). Experiments on the Taiwan stock market show that the results of employing comprehensive features are significantly better than traditional methods using numeric features alone (without textual sentiment features).     

异辛酸合成液的气相色谱分析

建立了异辛酸合成过程中异辛醇、异辛酸和酯的气相色谱分析方法。以 10 %改性聚乙二醇 2 0M为固定液 ,苯乙酮为内标物 ,氢火焰离子化检测器 ,内标法定量分析异辛酸。实验结果表明 ,该方法准确可靠 ,测得异辛酸的相对重量校正因子 1.30 5 ,相对误差小于 2 .0 %。同时通过与化学法对照结果显示 ,合成液用内标法测定较好 ,而精产品用带校正因子的归一化法测定较好。     

合成氨双甲精制工艺副产双甲燃料应用实践

总结了合成氨双甲精制新工艺的实际应用情况，着重阐述其工艺流程，设备，工艺指标，安全，特点，效益。旨在从实践的角度察看其理论的成熟性与合理性，促进双甲工艺在八成氨生产中的广泛应用，创造更好的社会效益和与经济效益。     

RPG游戏角色设定的艺术特征和方法分析

RPG游戏作为现今最受欢迎的游戏类型,具有高度的艺术性、故事性与交互性。优秀的角色设计能够调动玩家参与游戏的积极性,文章在RGP游戏类别下,提出“三维”的细节化角色造型设定的方法,结合经典RPG游戏对角色设定的艺术特征进行了描述性的分析与归纳,并且引发迎合女性玩家角色缺失的关注,为拓展RPG游戏角色设定空间提供参考。