Extending boosting for large scale spoken language understanding

We propose three methods for extending the Boosting family of classifiers motivated by the real-life problems we have encountered. First, we propose a semisupervised learning method for exploiting the unlabeled data in Boosting. We then present a novel classification model adaptation method. The goal of adaptation is optimizing an existing model for a new target application, which is similar to the previous one but may have different classes or class distributions. Finally, we present an efficient and effective cost-sensitive classification method that extends Boosting to allow for weighted classes. We evaluated these methods for call classification in the AT&;T VoiceTone^® spoken language understanding system. Our results indicate that it is possible to obtain the same classification performance by using 30% less labeled data when the unlabeled data is utilized through semisupervised learning. Using model adaptation we can achieve the same classification accuracy using less than half of the labeled data from the new application. Finally, we present significant improvements in the “important” (i.e., higher weighted) classes without a significant loss in overall performance using the proposed cost-sensitive classification method.     

Prediction and quality control of the melt index during production of high-density polyethylene

In polyolefin processes the melt index (MI) is the most important control variable indicating product quality. Because of the difficulty in the on-line measurement of MI, a lot of MI estimation and correlation methods have been proposed. In this work a new dynamic MI estimation scheme is developed based on system identification techniques. The empirical MI estimation equation proposed in the present study is derived from the 1 ^st -order dynamic models. Effectiveness of the present estimation scheme was illustrated by numerical simulations based on plant operation data including grade change operations in high density polyethylene (HDPE) processes. From the comparisons with other estimation methods it was found that the proposed estimation scheme showed better performance in MI predictions. The virtual sensor model developed based on the estimation scheme was combined with the virtual on-line analyzer (VOA) to give a quality control system to be implemented in the actual HDPE plant. From the application of the present control system, significant reduction of transition time and the amount of off-spec during grade changes was achieved     

Sandia National Laboratories Validation Workshop: Structural dynamics application

This article specifies a virtual structural dynamic subsystem and some systems, as well as mathematical models that approximately simulate them. The purpose is to define a setting for model validations conceived by participants in the Sandia National Laboratories Validation Workshop. Some broad guidelines for the model validations are set, as well as a regulatory requirement to be satisfied by the target system. Participants are directed to present techniques for subsystem model validation, to analytically predict whether or not the regulatory requirement will be met, and to estimate the likelihood of accuracy of the prediction.     

Modelling the FEBEX THM experiment using a state surface approach

Buffer materials being considered as engineered barriers in nuclear fuel waste (NFW) disposal systems possess a pronounced nonlinear behaviour in the unsaturated state. In order to simulate such non-linear responses,the authors adopted an incrementally nonlinear poro-elastic approach where the coefficients of the governing equations are assumed to be functions of suction and the void ratio. These functions are in turn developed from a state-surface equation obtained from suction-controlled oedometric tests. In this paper we show the derivation of the governing equations of the poro-elastic model. A finite element computer code, FRACON, was developed by the authors to numerically solve the above equations. We first use the code to simulate laboratory tests to characterize the swelling properties of a typical bentonite. That same bentonite was used in the FEBEX in-situ heater experiment, conducted at the Grimsel site, Switzerland. The FRACON code was also used to perform blind predictions of the FEBEX heater experiment. It is shown that the model correctly predicts drying of the bentonite near the heaters and re-saturation near the rock interface. The evolution of temperature and the heater thermal output were also reasonably well predicted by the model. The trends in the total stresses developed in the bentonite were correctly predicted; the absolute values however were underestimated probably due to the omission of pore pressure build-up in the rock mass.     

Estimation for the number of components in a mixture model using stepwise split-and-merge EM algorithm

The main difficulty with EM algorithm for mixture model concerns the number of components, say g. This is the question of model selection, and the EM algorithm itself could not estimate g. On the contrary, the algorithm requires g to be specified before the remaining parameters can be estimated. To solve this problem, a new algorithm, which is called stepwise split-and-merge EM (SSMEM) algorithm, is proposed. The SSMEM algorithm alternately splits and merges components, estimating g and other parameters of components simultaneously. Also, two novel criteria are introduced to efficiently select the components for split or merge. Experimental results on simulated and real data demonstrate the effectivity of the proposed algorithm.     

Realization of Tapered Waveguide by Stretching the Rod Waveguide

By stretching the rod waveguide with different velocities in opposite directions, the tapered waveguide can be fabricated. In condition of taking no account of volume expansion caused by heating and under the assumptions of volume conservation,the rod waveguide can be stretched freely in the heated region without being stretched outside of the heated region. A model,which shows the relation of the transition shape and the two factors, that is the ratio of two velocity and the heated region length, is presented for the shape of the taper transition through mathematic deduction. Based on this model, a desired tapered waveguide can be fabricated. The tapered waveguide are widely used for fabricating tapered fiber couplers and sensors. In addition, the conclusion can be used for fabricating fused fiber coupler.     

宏蜂窝模型的传播模型校正研究

详细介绍了 宏蜂窝传播模 型校正的基本操作流程 结果分析及注意事项 对工程 ,人员了解和开展模型校正工作有一定的指导作用 。     

核电站中椭圆柱形屏蔽体辐射衰减率的仿真研究

为了预测核电站中椭圆柱形屏蔽体的辐射衰减率，该文用数值解析法对放射线源到评价点的放射线所穿透椭圆柱形屏蔽物体的交点进行了研究。首先用空间解析法建立了椭圆柱形物体的数学模型。然后解曲面方程求出交点。在判断放射线是否穿透此椭圆柱体时，该文又提出了椭圆柱形屏蔽体的假想外接长方体的建模方法，将曲面方程联立解的复杂计算简化为一次代数方程的简单计算，大幅度地缩短了计算时间。     

FluNet: A hybrid internet simulator for fast queue regimes

Motivated by the scale and complexity of simulating large-scale networks, recent research has focused on hybrid fluid/packet simulators, where fluid models are combined with packet models in order to reduce simulation complexity as well as to track dynamics of end-sources accurately. However, these simulators still need to track the queuing dynamics of network routers, leading to considerable simulation complexity in a large-scale network model. In this paper, we propose a new hybrid simulator – FluNet – where queueing dynamics are not tracked, but instead, an equivalent rate-based model is used. The FluNet simulator is predicated on a fast-queueing regime at bottleneck routers, where the queue length fluctuates on a faster time-scale than end systems. This allows us to simulate large-scale systems, where the simulation “time step-size” is governed only by the time-scale of the end-systems, and not by that of the intermediate routers; whereas a queue-tracking based fluid simulator would require decreasingly smaller step-sizes as the system scale size increases. We validate our model using a ns-2 based implementation. Our results indicate a good match between packet systems and the associated FluNet system.     

Building a user model implicitly from a cooperative advisory dialog

This paper reviews existing methods for building user models to support adaptive, interactive systems, identifies sigificant problems with these approaches, and describes a new method for implicitly acquiring user models from an ongoing user-system dialog. Existing explicit user model acquisition methods, such as user edited models or model building dialogs put additional burden on the user and introduce artificial model acquisition dialogs. Hand coding stereotypes, another explicit acquisition method, is a tedious and error-prone process. On the other hand, implicit acquisition techniques such as computing presuppositions or entailments either draw too few inferences to be generally useful, or too many to be trusted.In contrast, this paper describes GUMAC, a General User Model Acquisition Component that uses heuristic rules to make default inferences about users' beliefs from their interaction with an advisory expert system. These rules are based on features of human action and conversation that constrain people's behavior and establish expectations about their knowledge. The application of these rules is illustrated with two examples of extended dialogs between users and an investment advisory system. During the course of these conversations, GUMAC is able to acquire an extensive model of the users' beliefs about the aspects of the domain considered in the dialog. These models, in turn, provide the sort of information needed by an explanation generator to tailor explanations the advisory system gives to its users.