Effect of Channel Changes in the St. Clair River During the Present Century

Periodic man-made changes in the outlet of Lake Huron through the St. Clair River date back to the middle of the last century. These artificial channel changes have been well documented during the present century. They consist of dredging for commercial gravel removal in the upper river during 1908–25 and uncompensated navigation improvements for the 7.6-m (25-ft) and 8.2-m (27-ft) projects completed in 1933 and 1962, respectively. The total effect of these changes on the levels of Lakes Michigan and Huron (hydraulically one lake) and on the upper St. Clair River profile was determined with dynamic flow models. The ultimate effect of the above dredging was a permanent lowering of the Lake Michigan-Huron levels 0.27 m (0.89 ft), which represents a tremendous loss of freshwater resource [32 km³ (7.7 mi³)].     

From hospital to municipal cogeneration systems: an Italian case study

A mixed integer linear programming model combined with a more traditional design by scenarios is proposed to optimize facilities size and operation mode of a municipal energy system involving significant civil centres and a hospital. Moving from the need of a new heat and power station for the local hospital due to the construction of new pavilions, the opportunity of involving other centres in the neighbourhood in a distributed cogeneration system is analysed, increasing system complexity step by step. Smaller cogeneration units tailored to hospital needs are rewarding ventures with relatively low risks but, in a country whose traditional power generation systems heavily rely on fossil fuels and where energy policy and market conditions can make it profitable to sell surplus power, district heating systems foster the installation of larger cogenerators and lead thereby to higher profits and to better performance as for primary energy savings and greenhouse gases emission reduction. Copyright © 2006 John Wiley & Sons, Ltd.     

温度调谐LBO晶体光参量振荡器

本文详细研究０．５３２μｍ激光泵浦、温度调谐Ⅱ型非临界相位匹配ＬＢＯ光参量振荡器。当温度从２０℃升高到２００℃时，其信号波和闲置波的调谐范围分别为１．００２～０．８９８μｍ和１．１３４～１．３０６μｍ。本装置最吸引人之处是本征输出线宽比Ⅰ型情形小一个量级。     

Measurement selection for parametric IC fault diagnosis

This article presents experimental results which show feedforward neural networks are well-suited for analog IC fault diagnosis. Boundary band data (BBD) measurement selection is used to reduce the computational overhead of the FFN training phase. We compare the diagnostic accuracy between traditional statistical classifiers and feedforward neural networks trained with various measurement selection criteria. The feedforward networks consistently perform as well as or better than the other classifiers in term of accuracy. Training using BBD consistently reduces the FFN training efforts without degrading the performance. Experimental results suggest that feedforward networks provide a cost efficient method for IC fault diagnosis in a large scale production testing environment.This work is supported by NSF-IUC CDADIC, Project 90-1.     

Techniques for estimating test length under random test

When a circuit is tested using random or pseudorandom patterns, it is essential to determine the amount of time (test length) required to test it adequately. We present a methodology for predicting different statistics of random pattern test length. While earlier methods allowed estimation only of upper bounds of test length and only for exhaustive fault coverage, the technique presented here is capable of providing estimates of all statistics of interest (including expected value and variance) for all coverage specifications.Our methodology is based on sampling models developed for fault coverage estimation [1]. Test length is viewed as awaiting time on fault coverage. Based on this relation we derive the distribution of test length as a function of fault coverage. Methods of approximating expected value and variance of test length are presented. Accuracy of these approximations can be controlled by the user. A practical technique for predicting expected test length is developed. This technique is based on clustering faults into equal detectability subsets. A simple and effective algorithm for fault clustering is also presented. The sampling model is applied to each cluster independently and the results are then aggregated to yield test lengths for the whole circuit. Results of experiments with several circuits (both ISCAS '85 benchmarks and other practical circuits) are also provided.This work was done while the author was with the Department of Electrical Engineering, Southern Illinois University, Carbondale, IL 62901.     

npn AlGaN/GaN HBT模型与特性分析

基于实验数据对GaN材料的少子寿命和碰撞电离率进行了建模,应用漂移-扩散传输模型开展了npnAlGaN/GaN异质结双极晶体管的特性研究,给出了器件导通电压、偏移电压和饱和电压的解析式.结果表明:实际器件导通电压、偏移电压及饱和电压较大的原因主要是高基区电阻和基区接触的非欧姆特性,为器件的工艺制造提供了理论指导.     

Is the Promissory Note of Personality as Vulnerability to Depression in Default? Reply to Zuroff, Mongrain, and Santor (2004).

In contrast to D. C. Zuroff, M. Mongrain, and D. A. Santor (2004), the current authors find the promissory note of dependency-sociotropy (DEP-SOC) and self-criticism-autonomy (SC-AUT) as a model of risk for depression to be in default. The authors propose reorganizing what has been cast as unitary effort into 3 distinct endeavors: a psychoanalytic clinical theory, development of a refined empirical model of risk for clinical depression, and research examining the effects of DEP-SOC and SC-AUT on interpersonal relationships in nonclinical samples. The authors identify some issues that need to be accommodated regardless of whether the assessment of Zuroff et al. (2004) or their own is accepted. DEP-SOC and SC-AUT are best construed as correlated, continuous dimensions. Future work also needs to accommodate depression as chronic recurrent condition, advances in developmental psychopathology, and more stringent criteria for positing a risk factor for clinical disorder. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Improving Measurement Precision of Test Batteries Using Multidimensional Item Response Models.

A conventional way to analyze item responses in multiple tests is to apply unidimensional item response models separately, one test at a time. This unidimensional approach, which ignores the correlations between latent traits, yields imprecise measures when tests are short. To resolve this problem, one can use multidimensional item response models that use correlations between latent traits to improve measurement precision of individual latent traits. The improvements are demonstrated using 2 empirical examples. It appears that the multidimensional approach improves measurement precision substantially, especially when tests are short and the number of tests is large. To achieve the same measurement precision, the multidimensional approach needs less than half of the comparable items required for the unidimensional approach. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Geometry-Dependent R-Curve for Quasi-Brittle Materials

Fracture of quasi-brittle materials such as ceramics and cement-based materials can be described by an R -curve, defined as fracture resistance. The R -curve can be constructed as the envelope of the strain energy release rates ( G ). In this study, R -curve is defined as an envelope of G -curves obtained by varying the dimensions of identical specimens, while keeping the geometry and the initial flaw size constant. By approximating the G -curve with a second-order function of the crack length, a simple formulation of the R -curve is derived by solving a differential equation. Three parameters are needed for the proposed R -curve. These parameters can be obtained by testing a notched-beam specimen and using linear elastic fracture mechanics. The proposed R -curve simulates well the geometry dependency as well as other characteristics of the fracture response of quasi-brittle materials.     

Design of statistical databases: A methodology for the conceptual step

The aim of the conceptual step in database design is to describe data involving in the application in a formal and abstract way, without any concern to the specific model and language chosen for the implementation. In statistical applications, data are described at different levels of aggregation, from elementary facts of the reality to complex aggregations such as classifications, time series, indexes. The paper describes a methodology for conceptual design of statistical databases that provides the designer suitable strategies for defining such different levels of aggregation starting from user requirements, and checking the completeness, coherence and minimality of the conceptual schema at the different levels. The methodology makes use of two data models for the representation of data: for elementary data the Entity-Relationship model, widely used in database applications, and for summary data a new model is proposed, designed to be an effective trade-off between expressive power and simplicity of use.