光互联网的最新进展

本对光互联网领域最新研究热点进行了综述，主要从光互联网的传输技术、激光技术、光交换技术等方面进行了全面的论述．重点从光互联网传输的损耗、光纤色散、光纤的有效面积、最有发展前途的VCSEL激光器、／VIENS光交换等方面进行综述，目的是让从事光互联网研究把握光互联网的最新发展动态，瞄准当前光互联网研究的方向，掌握国际上光互联网的最新进展和热点，有宜于我国光互联网系统的设计、开发与应用。     

对垂直腔面发射激光器(VCSEL)的应用探讨

VCSEL是美国原厂生产的激光器，是光通信中的一种极具潜力的固体：激光源，是目前市场上最好的VCSEL晶片及芯片组之一，已得到了较为广泛的应用。本文介绍了以GaAs和A1GaAs作为工作物质的垂直腔面发射激光器的结构、特性和在条形码扫描中的应用。     

Analysis and behaviour of FRP-confined short concrete columns subjected to eccentric loading

Fibre-reinforced polymer （FRP） composites were widely utilized in civil engineering structures as the retrofit of reinforced concrete （RC） columns. To design FRP jackets safely and economically, the behaviour of such columns should be predicted first. This paper is concerned with the analysis and behaviour of FRP-confined RC circular and rectangular short columns subjected to eccentric loading. A simple design-oriented stress-strain model for FRP-confined concrete in a section analysis was first proposed. The accuracy was then proved by two test data. Following that, a parametric study including amount of FRP confinement, FRP strain capacity, unconfined concrete strength and shape of column section is provided. Some conclusions were obtained at the end of the paper. The work here will provide a comprehensive understanding of the behaviour of FRP-confined concrete columns. The simplicity of the model also enables a simple equivalent stress block to be developed for direct use in practical design.     

Hypoplasticmodeling of soil-structure interfaces in offshore applications

Cyclic and monotonic loaded offshore structures (e.g. piles, pipelines, cables, and suction-buckets) must be designed and calculated considering the effects of the soil-structure interaction. An advanced constitutive soil model must be used, but a simplified Mohr-Coulomb friction law is applied for the soil-structure interface. The Mohr- Coulomb model is a simple bilinear friction model that cannot take into account monotonic and cyclic interface phenomena. These include hardening, softening, and stiffness degradation under loading. However, we propose two advanced hypoplastic interface models for fine- and coarse-grained soils with intergranular strain concept. The intergranular strain concept has been proven to be an efficient way to model the small-strain deformation and un/reloading behavior of soils. The intergranular strain concept is therefore used to enhance the prediction capabilities of the hypoplastic interface models. Differences of the recent model formulation compared with previous versions are presented and discussed based on simulation. This is followed by an application of different models in finite-element simulations. The new models are used to simulate cyclic direct shear interface tests. Furthermore, the advanced interface model is used for simulation of a torodial penetrometer penetration problem. Several aspects, which are particularly important for offshore structures, are compared with the simple Mohr-Coulomb friction model.     

The development of pattern recognition ability in children

Pattern recognition development was studied in high and low ability preschool, kindergarten, and first-grade youngsters. Pattern recognition was assessed by the administration of 96 pattern tasks which measured the ability of a youngster to find: (a) duplicate patterns and elements to a model; (b) the opposite pattern to a model; and (c) duplicate patterns but different elements than in the model. Aside from main effects for grade level, ability level, and pattern task, a significant three-way interaction was noted. This interaction was analyzed in terms of its component simple effects. The implication of these simple interaction effects for Piagetian theory and educational practice were discussed.     

Different teacher-level effectiveness estimates,different results: inter-model concordance across six generalized value-added models (VAMs)

In this study, researchers compared the concordance of teacher-level effectiveness ratings derived via six common generalized value-added model (VAM) approaches including a (1) student growth percentile (SGP) model, (2) value-added linear regression model (VALRM), (3) value-added hierarchical linear model (VAHLM), (4) simple difference (gain) score model, (5) rubric-based performance level (growth) model, and (6) simple criterion (percent passing) model. The study sample included fourth to sixth grade teachers employed in a large, suburban school district who taught the same sets of students, at the same time, and for whom a consistent set of achievement measures and background variables were available. Findings indicate that ratings significantly and substantively differed depending upon the methodological approach used. Findings, accordingly, bring into question the validity of the inferences based on such estimates, especially when high-stakes decisions are made about teachers as based on estimates measured via different, albeit popular methods across different school districts and states.     

Accounting for Rater Effects With the Hierarchical Rater Model Framework When Scoring Simple Structured Constructed Response Tests

Many large‐scale assessments are designed to yield two or more scores for an individual by administering multiple sections measuring different but related skills. Multidimensional tests, or more specifically, simple structured tests, such as these rely on multiple multiple‐choice and/or constructed responses sections of items to generate multiple scores. In the current article, we propose an extension of the hierarchical rater model (HRM) to be applied with simple structured tests with constructed response items. In addition to modeling the appropriate trait structure, the multidimensional HRM (M‐HRM) presented here also accounts for rater severity bias and rater variability or inconsistency. We introduce the model formulation, test parameter recovery with a focus on latent traits, and compare the M‐HRM to other scoring approaches (unidimensional HRMs and a traditional multidimensional item response theory model) using simulated and empirical data. Results show more precise scores under the M‐HRM, with a major improvement in scores when incorporating rater effects versus ignoring them in the traditional multidimensional item response theory model.     

Electromagnetic Model and Image Reconstruction Algorithms Based on EIT System

Electrical impedance tomography (EIT) tech-niques have been investigated extensively during thepast decades, as a kind of visible multiphase flowmeasurement technique in industry and medical in-strument[1—5]. EIT has several advantages over othertomographic techniques, e. g. low cost, rapid re-sponse, portability, non-invasion, and robustness. Inindustrial field, EIT has found many applications,such as measurement of two-phase ( e. g. gas/liq-uid[6]and gas/solid[7,8]) flows in pipelines or…     

The Effect of Small Sample Size on Two-Level Model Estimates: A Review and Illustration

Multilevel models are an increasingly popular method to analyze data that originate from a clustered or hierarchical structure. To effectively utilize multilevel models, one must have an adequately large number of clusters; otherwise, some model parameters will be estimated with bias. The goals for this paper are to (1) raise awareness of the problems associated with a small number of clusters, (2) review previous studies on multilevel models with a small number of clusters, (3) to provide an illustrative simulation to demonstrate how a simple model becomes adversely affected by small numbers of clusters, (4) to provide researchers with remedies if they encounter clustered data with a small number of clusters, and (5) to outline methodological topics that have yet to be addressed in the literature.     

粒子群算法在重载齿轮多目标设计中的应用

粒子群优化算法是一种基于群智能的优化方法,规则简单,收敛速度快.将此算法应用于重载齿轮的多目标优化设计,建立基于粒子群优化算法的重载齿轮多目标优化设计的数学模型,实践表明可以快速、有效地求得齿轮优化解.     

Neural network method for solving elastoplastic finite element problems

INTRODUCTION An Artificial Neural Network (ANN) is an in-formation-processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. It is composed of a large number of highly interconnected processing elements (neu-rons) working in unison to solve specific problems. In recent years, neural network has been widely applied in the field of engineering construction as a large dimensional nonlinear dynamic system, because of its support for …     

Applications of mathematical learning models to student performance on general chemistry: Microcomputer drill and practice programs

Four drill and practice programs in general chemistry (Butler & Hough, 1982) were altered to keep records of response, scores, and response times as students used the programs. Mathematical learning models were applied to the resulting score and time data. When data for groups of students using the same programs were analyzed using the polynomial fit model of Kerlinger and Pedhazur (1973), significant results were found and in most cases the linear fit provided the only significant explanation for the variance in the data. The performance of individual students on selected programs was also analyzed using a linear model, a simple exponential saturation model, and a more complex model which incorporated ability and motivation factors into the exponential saturation model (Aldridge, 1983). Most of the students improved their performance linearly with time and none exhibited patterns characteristic of the Aldridge model. In some cases, the simple exponential saturation model provided an explanation of the data as probable as that of the linear model. The implications of the findings for science teaching are discussed.     

The Weird World,and Equally Weird Measurement Models: Reactive Indicators and the Validity Revolution

Researchers using structural equation modeling (SEM) aspire to learn about the world by seeking models with causal specifications that match the causal forces extant in the world. This quest for a model matching existing worldly causal forces constitutes an ontology that orients, or perhaps reorients, thinking about measurement validity. This article illustrates several ways the seemingly innocuous quest for structural equation models that mirror “the world beyond” confronts entrenched notions of measurement validity. The article begins by considering simple measurement models and ends by “discovering” a new class of indicators called reactive indicators. Reactive indicators act as both the cause and effect of an underlying latent variable. The identifiability of a simple model containing a reactive indicator is proven and a research example illustrating the use of a reactive indicator is provided. However, the real challenge is to understand how an indicator can be both a cause and effect of the latent it measures. The understanding does not come from complying with the traditional rules for reliability and validity, but from focusing on the quest to make the structural equation model match the structuring of the worldly forces we seek to understand. Valid measurement in the context of a weirdly structured world requires an equally weird structural equation model.     

Identification Constraints and Inference in Factor Models

The choice of constraints used to identify a simple factor model can affect the shape of the likelihood. Specifically, under some nonzero constraints, standard errors may be inestimable even at the maximum likelihood estimate (MLE). For a broader class of nonzero constraints, symmetric normal approximations to the modal region may not be appropriate. A simple graphical technique to gain insight into the relative location of equivalent modes is introduced. Implications for estimation and inference in factor models, and latent trait models more generally, are discussed.     

From pentagon to triangle: A cross‐cultural investigation of an implicit theory of giftedness

The present study examined an implicit theory of giftedness among pre‐service Chinese teachers. Participants were 189 second year students (preservice teachers, 74 male and 115 female, average age 20 years) from China Central Teachers’ University. Participants responded to an inventory based on Stemberg and Zhang's (1995) pentagonal implicit theory of giftedness and a simple questionnaire designed to cross‐validate two of the five criteria in the pentagonal model. Results indicated that in making judgments about giftedness, participants took into consideration three of the five criteria specified in the pentagonal model: excellence, productivity, and value. The excellence and productivity criteria were also confirmed by results from the simple questionnaire. Rarity and demonstrability, the two other criteria specified in the pentagonal model, were not taken into consideration by the participants in their evaluation of giftedness. Implications of these findings are discussed.     

Adapting to Learner Attributes: experiments using an adaptive tutoring system

A composite learner model for adaptive tutoring systems has been developed, which combines a model of learner attributes with a simple overlay model of the learner's domain knowledge state. The model of learner characteristics enables several different forms of psychological and background data about the student to be taken into account, and provides a profile of the learner in terms of pedagogically useful attributes. An Adaptive Tutor Using Learner Attributes (ATULA) has been constructed, which uses the composite learner model. The system is able to select for the learner the optimal form of the learning material for the group of topics about to be presented. Experiments carried out with the adaptive tutoring system over 3 successive academic years with two disparate groups of students are described. User records collected during the experiments provide insight into the operation of the model, both at initialisation and during the student's interaction with the system. Previous users’ records also enable comparisons to be made with the result of previous experiments using a non‐adaptive system.     

基于MATLAB和BP网络的公路软基沉降量预测模型

人工神经网络具有强大的非线性映射能力,文章利用BP神经网络建立了公路软土地基沉降量预测模型,并用MATLAB人工神经网络工具箱进行了实现。根据实测资料,对此预测模型进行训练和预测,试验表明,预测模型具有较好的预测精度,操作简单,具有广阔的工程应用前景。     

Physically-based approach to analyze rainfall-triggered landslide using hydraulic gradient as slide direction

An infinite slope stability numerical model driven by the comprehensive physically-based integrated hydrology model (InHM) is presented. In this approach, the failure plane is assumed to be parallel to the hydraulic gradient instead of the slope surface. The method helps with irregularities in complex terrain since depressions and flat areas are allowed in the model. The present model has been tested for two synthetic single slopes and a small catchment in the Mettman Ridge study area in Oregon, United States, to estimate the shallow landslide susceptibility. The results show that the present approach can reduce the simulation error of hydrological factors caused by the rolling topography and depressions, and is capable of estimating spatial-temporal variations for landslide susceptibilities at simple slopes as well as at catchment scale, providing a valuable tool for the prediction of shallow landslides.