Prediction of Final Product Properties After Cocurrent Spray Drying

The effect of drying and atomization conditions on the physical properties of powders for agglomerate-like materials and skin-forming material are studied in this article. A neural model is used for powder bulk and tapped density predictions.     

Optimal size,hydraulic retention time and volatile solids loading rate of biogas unit using water hyacinth

With a view to evaluate the effects of hydraulic retention time and volatile solids loading rate on methane production using water hyacinth, experiments were conducted in a 160 dm³ capacity, well-mixed continuous digestion unit at ambient temperature. The optimal design of biogas plant using water hyacinth was elucidated, to provide a unit giving a maximum methane yield of 0.16 nm³ kg^?1 volatile solids added, which was 60% greater than the conventional plant using cowdung. The calculations of optimal design factors were based on reactor size, hydraulic retention time and volatile solids loading rate; considerations were made of capital cost, running costs and operational revenue.     

Use of ultrafiltration for preparing improved tomato pulp

The characteristics of high-quality tomato pulp (commercial def.: crushed or diced tomatoes with about 30% tomato juice as packing medium) canned with tomato juice pulp enriched by ultrafiltration as packing medium were compared with those covered with conventional vacuum-concentrated juice.
Both hot- and cold-break products were prepared and those containing 20% serum-reduced packing juice proved to be the best, showing no signs of syneresis on storage and with improvements in sensory properties, colour and non-enzymatic browning; some volatile components were reduced.     

Emulsifying Properties of the Total Fraction and the Hydrophobic Fraction of Bovine Milk Proteose-peptones

Since proteose-peptone is a mixture of heterogeneous proteins and peptides, its functional properties have not yet been fully understood. The present study was undertaken to elucidate the emulsifying properties of proteose-peptones and a parallel evaluation was performed of the emulsifying activity of the total fraction prepared from bulk skimmed milk by precipitation with ammonium sulphate and of the most hydrophobic fraction purified by hydrophobic interaction fast protein liquid chromatography. A turbidimetric technique was used and the absorbance value at 500 nm was then directly used as the emulsifying activity index. The results obtained confirmed the good emulsifying activity of this protein fraction of the whey and demonstrated the considerable influence of the concentration on the capacity of the proteose-peptones to stabilize a model oil-in-water emulsion. Moreover, at all the concentrations examined, the purified component 3 showed a higher emulsifying activity than the total unpurified fraction.     

基于PCA-Logistic模型的围岩稳定性分类研究

为了建立易于理解和应用的围岩稳定性分类模型,采用主成分分析法对围岩样本数据进行降维处理,以Logistic模型来描述围岩稳定性影响因素与围岩稳定性之间的经验关系。选取影响围岩分类的5个主要因素,根据分类标准,采用在每级标准中随机内插的方法,得到100个标准样本,用于建立PCA-Logistic模型。分析结果显示,PCA-Logistic模型拟合效果良好,对工程实例的预测结果同投影寻踪模型和分形-插值模型完全一致,表明该模型在围岩稳定性评价中具有可行性和有效性。     

Mining partial periodic correlations in time series

Recently, periodic pattern mining from time series data has been studied extensively. However, an interesting type of periodic pattern, called partial periodic (PP) correlation in this paper, has not been investigated. An example of PP correlation is that power consumption is high either on Monday or Tuesday but not on both days. In general, a PP correlation is a set of offsets within a particular period such that the data at these offsets are correlated with a certain user-desired strength. In the above example, the period is a week (7 days), and each day of the week is an offset of the period. PP correlations can provide insightful knowledge about the time series and can be used for predicting future values. This paper introduces an algorithm to mine time series for PP correlations based on the principal component analysis (PCA) method. Specifically, given a period, the algorithm maps the time series data to data points in a multidimensional space, where the dimensions correspond to the offsets within the period. A PP correlation is then equivalent to correlation of data when projected to a subset of the dimensions. The algorithm discovers, with one sequential scan of data, all those PP correlations (called minimum PP correlations) that are not unions of some other PP correlations. Experiments using both real and synthetic data sets show that the PCA-based algorithm is highly efficient and effective in finding the minimum PP correlations. Zhen He is a lecturer in the Department of Computer Science at La Trobe University. His main research areas are database systems optimization, time series mining, wireless sensor networks, and XML information retrieval. Prior to joining La Trobe University, he worked as a postdoctoral research associate in the University of Vermont. He holds Bachelors, Honors and Ph.D degrees in Computer Science from the Australian National University. X. Sean Wang received his Ph.D degree in Computer Science from the University of Southern California in 1992. He is currently the Dorothean Chair Professor in Computer Science at the University of Vermont. He has published widely in the general area of databases and information security, and was a recipient of the US National Science Foundation Research Initiation and CAREER awards. His research interests include database systems, information security, data mining, and sensor data processing. Byung Suk Lee is associate professor of Computer Science at the University of Vermont. His main research areas are database systems, data modeling, and information retrieval. He held positions in industry and academia: Gold Star Electric, Bell Communications Research, Datacom Global Communications, University of St. Thomas, and currently University of Vermont. He was also a visiting professor at Dartmouth College and a participating guest at Lawrence Livermore National Laboratory. He served on international conferences as a program committee member, a publicity chair, and a special session organizer, and also on US federal funding proposal review panel. He holds a BS degree from Seoul National University, MS from Korea Advanced Institute of Science and Technology, and Ph.D from Stanford University. Alan C. H. Ling is an assistant professor at Department of Computer Science in University of Vermont. His research interests include combinatorial design theory, coding theory, sequence designs, and applications of design theory.     

An improved SVD-based watermarking technique for copyright protection

The drawbacks of SVD-based image watermarking are false positive, robust and transparency. The former can be overcome by embedding the principal components of the watermark into the host image, the latter is dependent on how much the quantity (i.e., scaling factor) of the principal components is embedded. For the existing methods, the scaling factor is a fixed value; actually, it is image-dependent. Different watermarks need the different scaling factors, although they are embedded in the same host image. In this paper, two methods are proposed to improve the reliability and robustness. To improve the reliability, for the first method, the principal components of the watermark are embedded into the host image in discrete cosine transform (DCT); and for the second method, those are embedded into the host image in discrete wavelets transform (DWT). To improve the robustness, the particle swarm optimization (PSO) is used for finding the suitable scaling factors. The experimental results demonstrate that the performance of the proposed methods outperforms than those of the existing methods.     

锻造零件缺陷分析

介绍了四种典型锻造缺陷案例并进行了详尽的追述，主要从锻造过程中金属流动和冶金缺陷的重新分布的角度对锻造缺陷产生原因作了比较全面的解析，提出了解决这些问题比较成熟的经验和方法。     

CAPP系统中图形控件的设计与实现

提出一种采用控件方式设计CAPP(computeraidedprocessplanning)系统的方法,该控件底层引用Auto CAD的自动化对象,直接调用AutoCAD的DWG数据,用该方法构造的控件容易与CAPP中的属性数据进行连接,实现双向查询与操作.