Error rate estimation on the basis of posterior probabilities

The so-called posterior probability estimator, e, formed by averaging the minimum of the posterior probabilities over a set of initial or additional observations (which need not be classified) is considered in the context of estimating the overall actual error rate for the linear discriminant function appropriate for two multivariate normal populations with a common covariance matrix. The bias of e is examined by deriving asymptotic approximations under three different models, the normal, logistic, and mixture models. The properties of e are investigated further by a series of simulation experiments for the logistic and mixture models for which there are few other available estimators.     

Response-time simulation of multivariate point process models for multiprogrammed jobstreams

We consider simulation methods for particular marked multivariate point processes, calledR-processes, which have recently been proposed as models for multiprogrammed jobstreams. Using workload marks on events, such models facilitate the incorporation of realistic workload characteristics into computer system performance predictions. We consider R-processes in which workload marks for an individual jobstream form a stationary sequence of discrete random variables having a (generally non-Markovian) mixed moving average-autoregressive dependency structure. For such models we provide a method for obtaining from a single simulation run point and interval estimates for general characteristics of job response times.     

COMPONENTS OF PREDICTION ERRORS FOR A STATIONARY PROCESS WITH ESTIMATED PARAMETERS

Abstract. An alternative approach to the estimation of prediction error using linear time series models, whose parameters are also estimated, is presented. Recurrence relationships are given which are rather less unwieldy operationally than the Kronecker matrix forms used by Yamamoto and Reinsel. We extend somewhat the class of models to other than the purely finite autoregressive models studied by these authors.     

Mathematical models of the thermal decomposition of coal: 3. Density,porosity and contraction behaviour

Mathematical models are proposed to predict the true density of coal, semi-coke and coke and the porosity of a coke oven charge during carbonization. These models are combined in a further model which predicts the hitherto unexplained ‘twin-peaked’ contraction curve observed for semi-coke. It is found that the first contraction peak results from the relatively high rate of mass loss occurring towards the end of the primary devolatilization stage. The second peak occurs because of the increase in true density arising from the elimination of hydrogen from the semi-coke.     

The determination of molecular orientation in uniaxially compressed PMMA by X-ray scattering

A procedure is presented for obtaining full molecular orientation information from wide angle X-ray scattering patterns of deformed non-crystalline polymers. The method is based on the analysis of experimental and calculated scattering patterns into their spherical harmonics. The results obtained for PMMA are compared with values predicted by the pseudo affine and affine deformation schemes.     

Optimal control of a solar collector loop using a distributed-lumped model

This paper considers the optimal control of a solar collector loop described by a bilinear distributed parameter model for the collector fluid temperature and a bilinear lumped parameter model for the storage fluid temperature. The objective is to control the collector fluid velocity so as to maximize the net energy collected over a fixed time period. Necessary conditions for optimality, given by a set of equations whose solution yields the optimal control, are derived. It is shown that the optimal control is an open-loop, bang-bang control which depends on two terms: a measurable quantity which depends on the state of the collector fluid, and a quantity which depends on a future knowledge of the weather data. It is also shown that for the case in which only two switches occur during the period of operation, the optimal control depends only on the temperature difference across the collector. Thus, one can construct a feedback on/off controller for the system provided that it is known a priori that only two switches will occur during the time interval under consideration.     

立筒式复合制袋机组内成型器的曲面设计

根据立筒式复合制袋机组对设计内成型器的要求，研讨了新型内成型器的曲面设计原理，对其数学模型进行了推导，使衬料成型过程中经向受力不均匀的问题得到缓解。     

Evaluation of apple texture with contact acoustic emission detector: A study on performance of calibration models

Performance of calibration models for evaluation of apples sensory texture with contact acoustic emission detector (CAED) was studied. For model evaluation and testing, 2500 apples of 19 cultivars were harvested over two seasons. Apples were stored at normal atmosphere (NA), controlled atmosphere (CA) for different periods or were treated with 1-methylcyclopropene (1-MCP) in order to obtain a high variability of texture and fruit maturity. Apples were tested simultaneously in two distinct laboratories. The models were created and validated on averaged values from 10 fruits using simple linear regression, multiple linear regression (MLR) and principal component regression (PCR). Performance statistics of the models were expressed in terms of determination coefficient (R²), root mean square errors of cross validation (RMSECV) or prediction (RMSEP) and ratio of prediction to deviation (RPD). Firmness and total acoustic emission counts were predictors of sensory texture in the models. MLR and PCR models show better performance for prediction of sensory data than simple linear regression models however PCR models show the best results among models tested in this study. Common PCR models for several cultivars allow for successful prediction of hardness (RPD > 2.0), crispness and overall texture (1.5 < RPD < 2.0). The single-cultivar PCR models, constructed on data sets containing 26-39 averaged values, reveal significantly better performance (RPD > 2.0 for most of the cases) than the common PCR models for many varieties.     

Weight loss of frozen bread dough under isothermal and fluctuating temperature storage conditions

Evaporative weight loss from food leads to both loss of saleable weight and quality deterioration so it need to be minimized. The effect of isothermal and fluctuating conditions on frozen dough weight loss was measured and compared with kinetic, physical and artificial neural network (ANN) models. Frozen dough samples were regularly weighed during storage for up to 112 days in loose-fitting plastic bags. The storage temperatures were in the range of −8 to −25 °C with fluctuations of ±0.1 °C (isothermal), ±1, ±3 or ±5 °C about the mean. For each combination of temperature and fluctuation amplitude, the rate of dough weight loss was constant. The rate of weight loss at constant temperature was nearly proportional to water vapour pressure consistent with standard theories for evaporative weight loss from packaged foods but was also accurately fitted by Arrhenius kinetics. Weight loss increased with amplitude of temperature fluctuations. The increase could not be fully explained by either the physic model based on water vapour pressure differences or the kinetic model alone. An ANN model with six neurons in the input layer, six neurons in hidden layers and one neuron in the output layer, achieved a good fit between experimental and predicted data for all trials. However, the ANN model may not be accurate for product, packaging and storage systems different to that studied.     

纳滤技术用于玉米降血压肽的脱盐研究

为了使经超滤分级分离的玉米降血压肽水解液的盐分脱除,本研究采用纳滤技术对水解液进行了脱盐处理,通过测定料液的肽截留率、盐(Na+)截留率,经综合比较,首先确定了最佳操作压力;并考察了3种渗滤模型的脱盐效果。结果显示最佳操作压力为8 bar;3种模型一般经过1 h处理,其肽截留率均可达96%以上,其中以连续恒容渗滤模型脱盐效果最佳,在初始条件下(约pH8.0),经90 min处理后,脱盐率可达到76.82%;之后比较了玉米肽在不同酸度条件下的脱盐率。研究表明:在8 bar的压力下,采用连续恒容渗滤模型,于pH 7条件下脱盐效果最好9,0 min处理后,脱盐率可达到87.80%。