条件概率关系数据库模型

现实世界中大量存在着的不确定性信息，关系数据库模型仅视它们为空值，有必要增强其处理这类信息的能力，文章在总结前人工作的基础上推广关系数据库模型，创建有效处理随机型不确定性信息的条件概念关系数据库模型，该模型通过在关系模式中增加一个条件概率测度属性，为每条记录指定适当的条件概率的途径，来表示不确定性信息。文中以对象码为基本工具，创建了条件概率关系结构；以特征函数为基本工具，定义了一套基于该结构的代数运算规则。条件概率的语意比概率的语意广泛，灵活，因而该模型能有效克服概率关系模型的许多不足。     

Probabilistic analysis of a static frame model

This paper describes our efforts during our participation in the Sandia Validation Workshop. The focus of the paper is the calibration of material models and simulation of random fields to characterize the variations of material properties across spatial field. Both parametric and non-parametric methods were used to represent uncertainty. Part of the challenge of this problem is the small amount of data that is available for the necessary probabilistic analyses in support of calibration, validation, accreditation and prediction activities. The analysis methods and corresponding results are described.     

国际放射防护委员会的剂量系数的可靠性

在评价公众成员摄入放射性核素的辐射危害时，需估算每单位摄入量所致的剂量。摄入放射性素后器官或民受到的剂量是受到的剂量是通过生物学模型和剂量学模型来确定的，因此剂量也必须根据模型来确定。文中初步探讨了国际放射防护委员会给出的剂量系数的可靠性问题。文中首先说明了估算剂量系数的概念和方法，然后分析了剂量系数估算中，采用胃肠道模型，呼吸道模型，系统生物动力学模型和剂量学模型所遇到的不确定度的各种主要来源。     

Hydrocarbon exploration risk evaluation through uncertainty and sensitivity analyses techniques

The evaluation of the exploration risk in the oil industry is a fundamental component of the decision process related to the exploratory phase. In this paper the two basic components of the exploratory risk: trap geometry and trapped hydrocarbon quantities (fluid), are compounded in a single coherent uncertainty and sensitivity approach. The results clarify that the model geometry influences each Petroleum System Modeling step and that the geometric uncertainty is correlated with the fluid uncertainty. The geometric uncertainty evaluation makes use of geostatistical techniques that produce a number of possible realizations of the trap geometry, all compatible with available data. The evaluation of the fluid uncertainty, through a Monte Carlo methodology, allows us to compute the possible quantities of oil and gas, generated in a basin and migrated from the hydrocarbon source location to each single trap. The final result is the probability distribution of oil and gas for each trap in the basin, together with other useful indicators like: the hydrocarbon filling probability map, the closure probability map, the drainage area probability map, the spilling paths probabilities, the trap-filling scenarios.     

Merging uncertain information with semantic heterogeneity in XML

Semistructured information can be merged in a logic-based framework [6, 7]. This framework has been extended to deal with uncertainty, in the form of probability values, degrees of beliefs, or necessity measures, associated with leaves (i.e. textentries) in the XML documents [3]. In this paper we further extend this approach to modelling and merging uncertain information that is defined at different levels of granularity of XML textentries, and to modelling and reasoning with XML documents that contain semantically heterogeneous uncertain information on more complex elements in XML subtrees. We present the formal definitions for modelling, propagating and merging semantically heterogeneous uncertain information and explain how they can be handled using logic-based fusion techniques. Anthony Hunter received a B.Sc. (1984) from the University of Bristol and an M.Sc. (1987) and Ph.D. (1992) from Imperial College, London. He is currently a reader in the Department of Computer Science at University College London. His main research interests are: Knowledge representation and reasoning, Analysing inconsistency, Argumentation, Default reasoning and Knowledge Fusion. Weiru Liu is a senior lecturer at the School of Computer Science, Queen's University Belfast. She received her B.Sc. and M.Sc. degrees in Computer Science from Jilin University, P.R China, and her Ph.D. degree in Artificial Intelligence from the University of Edinburgh. Her main research interests include reasoning under uncertainty, knowledge representation and reasoning, uncertain knowledge and information fusion, and knowledge discovery in databases. She has published over 50 journal and conference papers in these areas.     

用凯氏定氮仪测定蛋白质结果的不确定度评定

本文列出影响用凯氏定氮仪测定蛋白质结果的因子,依据测量不确定度评定规范,尝试对测定蛋白质结果不确定度的评价。     

Quantification of the layer dispersion degree in polymer layered silicate nanocomposites by transmission electron microscopy

As the performance of polymer layered silicate nanocomposites strongly depends on their interior layer dispersion, quantification of the layer dispersion degree is needed. In this work, a new methodology was developed to determine the dispersion parameter D_0.1, based on the measurement of the free-path spacing distance between the single clay sheets from the transmission electron microscopy (TEM) images. Several examples of exfoliated, intercalated, and immiscible composites were studied. It was found that the exfoliated composites had D_0.1 over 8%, while that of intercalated composites were between 4 and 8%. In the case of intercalation, a high frequency peak appeared at a short spacing distance in the histogram, which was a characteristic of the intercalation, distinct from the exfoliation. The main utility of this TEM methodology is for the quantification of exfoliated or intercalated samples with small number of layers with stacks. The dispersion parameter D_0.1 below 4% was suggested to classify as immiscible. A unique advantage of the TEM measurement is that the dispersion degree of different fillers can be counted individually.     

Optimizing investment levels for energy conservation: Individual versus social perspective and the role of uncertainty

The decision to invest in energy conservation must be made in the face of uncertainty: future energy prices and the magnitude of energy savings are uncertain. Since once does not know the optimal investment level in advance, one will incur cost penalties due to misoptimization. To analyse the cost penalties it is convenient to focus on the ratio of the life cycle costs that one pays and the life cycle costs one would have paid with an optimal investment level. Two models are used to evaluate this ratio: a model for conductive heat flow through a layer of insulation, and an exponential curve fit to a large number of residential energy conservation cost data. Plotting the life cycle cost ratio versus the ration of actual and guessed energy expenditures shows the effect both of price uncertainties and of uncertainties in the performance of conservation measures. The graph can also be used to evaluate the cost to society due to the mismatch between individual and social perspectives. The curve turns out to have a broad optimum, and penalties due to misoptimization are fairly small in most cases. With these models one can also calculate the long-term price elasticity of energy demand for rational consumers. It turns out to be -0.5 in the insulation model and -1.0 in the exponential model.     

Physics-guided logistic classification for tool life modeling and process parameter optimization in machining

This paper describes a physics-guided logistic classification method for tool life modeling and process parameter optimization in machining. Tool life is modeled using a classification method since the exact tool life cannot be measured in a typical production environment where tool wear can only be directly measured when the tool is replaced. In this study, laboratory tool wear experiments are used to simulate tool wear data normally collected during part production. Two states are defined: tool not worn (class 0) and tool worn (class 1). The non-linear reduction in tool life with cutting speed is modeled by applying a logarithmic transformation to the inputs for the logistic classification model. A method for interpretability of the logistic model coefficients is provided by comparison with the empirical Taylor tool life model. The method is validated using tool wear experiments for milling. Results show that the physics-guided logistic classification method can predict tool life using limited datasets. A method for pre-process optimization of machining parameters using a probabilistic machining cost model is presented. The proposed method offers a robust and practical approach to tool life modeling and process parameter optimization in a production environment.     

Effect of processing on sphingolipid content in soybean products

Soybeans are believed to be a rich source of sphingolipids, a class of polar lipids that has received attention for their possible cancer-inhibiting activities. The effect of processing on the sphingolipid content of various soybean products has not been determined. Glucosylceramide (GlcCer), the major sphingolipid type in soybeans, was measured in several processed soybean products to illustrate which product(s) GlcCer is partitioned into during processing and where it is lost. Whole soybeans were processed into full-fat flakes, from which crude oil was extracted. Crude oil was refined by conventional methods, and defatted soy flakes were further processed into alcohol-washed and acid-washed soy protein concentrates (SPC) and soy protein isolates (SPI) by laboratory-scale methods that simulated industrial practices. GlcCer was isolated from the samples by solvent extraction, solvent partition, and TLC and was quantified by HPLC. GlcCer remained mostly within the defatted soy flakes (91%) rather than in the oil (9%) after oil extraction. Only 52, 42, and 26% of GlcCer from defatted soy flakes was recovered in the acid-washed SPC, alcohol-washed SPC, and SPI products, respectively. All protein products had a similar GlcCer concentration of about 281 nmol/g (dry wt basis). The minor quantity of GlcCer in the crude oil was almost completely removed by water degumming.