Modeling Strategies for Categorical Data: Examples from Housing and Tenure Choice

Models to investigate categorical data can be divided into preprocessing, limited parameterization, and formal logit models. To illustrate the advantages of preprocessing and limited parameterization models they are applied to a data set of tenure and type of housing choice before the data are examined with hierarchical logit and nested logit models. The preprocessing approaches are useful in selecting optimal subsets of independent variables with respect to the dependent variable. The ease of application and interpretation of a limited parameterization approach extends the clarity of the results from the preprocessing approaches. Because some variables are only relevant at specific levels of other independent variables, nonstandard (nested) logit models are necessary to understand the nested relationships.     

The Neolithic Transition in the Iberian Peninsula: Data Analysis and Modeling

We apply GIS techniques to analyze a carefully selected database of 93 Early Neolithic sites in the Iberian Peninsula. This allows us to study the spatial dynamics of the Neolithic transition in Iberia. We study how the Neolithic was introduced into the peninsula in order to test the hypothesis that the Neolithic was introduced almost simultaneously from two sources: one at the northeast (via the Mediterranean coast) and another one at the south (possibly from Northern Africa). We also analyze how the expansion of the Neolithic transition took place within the Iberian Peninsula and measure local rates of spread in order to identify regions with fast and slow rates (such as the slowdown at the Cantabrian coast). In addition, we attempt to reproduce the main results obtained from the GIS analysis by applying reaction–dispersal models to the expansion of the Neolithic transition in the Iberian Peninsula. We conclude that a model with two sources is a reasonable assumption that agrees better with the archaeological data available at present than a model with a single source.     

Numerical Modeling of a Church Nave Wall Subjected to Differential Settlements: Soil-Structure Interaction,Time-Dependence and Sensitivity Analysis

ABSTRACT

Historic masonry structures are particularly sensitive to differential soil settlements. These settlements may be caused by deformable soil, shallow or inadequate foundation, structural additions in the building and changes in the underground water table due to the large-scale land use change in urban areas.

This paper deals with the numerical modeling of a church nave wall subjected to differential settlement caused by a combination of the above factors. The building in question, the church of Saint Jacob in Leuven, has suffered extensive damage caused by centuries-long settlement. A numerical simulation campaign is carried out in order to reproduce and interpret the cracking damage observed in the building.

The numerical analyses are based on material and soil property determination, the monitoring of settlement in the church over an extended period of time and soil-structure interaction. A sensitivity study is carried out, focused on the effect of material parameters on the response in terms of settlement magnitude and crack width and extent. Soil consolidation over time is considered through an analytical approach. The numerical results are compared with the in-situ observed damage and with an analytical damage prediction model.     

说方豆与宥坐之器

在楚地的东周墓葬中常常出土有一种方形盘的豆形器,因其盘是方形的,其下部有柄和座,与东周常见的圆盘豆相同,故人们常因其形而将其称之为方豆,根据其铭文,本论认为是欹器,但不是周庙之欹器或宥坐之器,而应是在欹器的基础之上演变的一种新器种,仍名之为欹,同时认为,所见这类器物应属楚器。     

A Dynamic Analysis of Interaction Data: U.S. Rail Freight Flows, 1972-81

The purpose of this paper is to extend Poisson regression to the analysis of spatial interactions over time. The methodology involves derivation of models using information methods and calibration using Poisson regression. Poisson regression is then used to analyze interannual variation in U.S. rail freight flows, 1972-81. Findings indicate that import and export variability is less important than is flow variability. Import and export variability is highest for the northeastern United States, but flow variability is highest for the southern and western United States. This has implications for the specification of dynamic models of commodity flow.     

南京博物院藏曾昭燏师友书札考略（上）

曾昭燏是一位勤于书翰的人,无论是在建国之前,还是在建国后。她每天都要处理各方面来函,也写了大量的书信给各方面人士。可惜的是因为十年动乱等原因,她写给各方面的书信要收集起来,也不是件易事。幸好南京博物院图书馆,珍藏了一批曾昭烯师友们写给她的书信,这些信对研究她的生平思想是颇有帮助的。这里刊发一部分,略做考订。     

Neural Network Modeling of Constrained Spatial Interaction Flows: Design, Estimation, and Performance Issues

In this paper a novel modular product unit neural network architecture is presented to model singly constrained spatial interaction flows. The efficacy of the model approach is demonstrated for the origin constrained case of spatial interaction using Austrian interregional telecommunication traffic data. The model requires a global search procedure for parameter estimation, such as the Alopex procedure. A benchmark comparison against the standard origin constrained gravity model and the two–stage neural network approach, suggested by Openshaw (1998), illustrates the superiority of the proposed model in terms of the generalization performance measured by ARV and SRMSE.     

永乐甜白方高足杯

本文介绍了永乐甜白方足高足杯的形制特点。     

Topic Modeling and Text Analysis for Qualitative Policy Research

This paper contributes to a critical methodological discussion that has direct ramifications for policy studies: how computational methods can be concretely incorporated into existing processes of textual analysis and interpretation without compromising scientific integrity. We focus on the computational method of topic modeling and investigate how it interacts with two larger families of qualitative methods: content and classification methods characterized by interest in words as communication units and discourse and representation methods characterized by interest in the meaning of communicative acts. Based on analysis of recent academic publications that have used topic modeling for textual analysis, our findings show that different mixed‐method research designs are appropriate when combining topic modeling with the two groups of methods. Our main concluding argument is that topic modeling enables scholars to apply policy theories and concepts to much larger sets of data. That said, the use of computational methods requires genuine understanding of these techniques to obtain substantially meaningful results. We encourage policy scholars to reflect carefully on methodological issues, and offer a simple heuristic to help identify and address critical points when designing a study using topic modeling.     

Using Spatial Filters and Exploratory Data Analysis to Enhance Regression Models of Spatial Data

Residual spatial autocorrelation is a situation frequently encountered in regression analysis of spatial data. The statistical problems arising due to this phenomenon are well‐understood. Original developments in the field of statistical analysis of spatial data were meant to detect spatial pattern, in order to assess whether corrective measures were required. An early development was the use of residual autocorrelation as an exploratory tool to improve regression analysis of spatial data. In this note, we propose the use of spatial filtering and exploratory data analysis as a way to identify omitted but potentially relevant independent variables. We use an example of blood donation patterns in Toronto, Canada, to demonstrate the proposed approach. In particular, we show how an initial filter used to rectify autocorrelation problems can be progressively replaced by substantive variables. In the present case, the variables so retrieved reveal the impact of urban form, travel habits, and demographic and socio‐economic attributes on donation rates. The approach is particularly appealing for model formulations that do not easily accommodate positive spatial autocorrelation, but should be of interest as well for the case of continuous variables in linear regression.     

Modeling and Seismic Response Analysis of Italian Code-Conforming Reinforced Concrete Buildings

ABSTRACT

This study investigates the seismic response of reinforced concrete buildings designed according to the current Italian building code. Number of stories, site hazard, presence and distribution of masonry infill panels, and type of lateral resisting system are the key investigated parameters. The main issues related to design and modeling are discussed. Two Limit States are considered, namely Global Collapse and Usability-Preventing Damage. The main aim of the study is a comparison between the seismic response of the buildings, investigated through nonlinear static and dynamic analyses. Irregularity in the distribution of infill panels and site hazard emerge as the most influential parameters.     

Modeling and Seismic Response Analysis of RC Precast Italian Code-Conforming Buildings

ABSTRACT

In this study, industrial single-story RC precast buildings are investigated. Twenty-four case studies have been considered, in which the column height, the beam spans and the seismic hazard level are varied. The seismic design of the selected case studies is performed according to the Italian building code and additional technical documentation. Three-dimensional nonlinear models are defined to perform static and dynamic analyses for the seismic assessment of the selected case studies. Demand/capacity ratios in terms of the selected engineering demand parameters are computed for ten increasing values of the seismic input return period.     

Modeling and Seismic Response Analysis of Italian Code-Conforming Single-Storey Steel Buildings

ABSTRACT

This article describes the structural design, nonlinear modeling, and seismic analysis of prototype single-storey non-residential steel buildings made of moment-resisting portal frames in the transverse direction and concentric braces in the longitudinal direction. Various design parameters (building geometry, seismic hazard, foundation soil category) and different modeling assumptions (bare frame model, model including cladding elements, ground motions including vertical accelerations, and modeling uncertainties) were considered to investigate their effects on the simulated seismic performance.     

Geography, Spatial Data Analysis, and Geostatistics: An Overview

Geostatistics is a distinctive methodology within the field of spatial statistics. In the past, it has been linked to particular problems (e.g., spatial interpolation by kriging) and types of spatial data (attributes defined on continuous space). It has been used more by physical than human geographers because of the nature of their types of data. The approach taken by geostatisticians has several features that distinguish it from the methods typically used by human geographers for analyzing spatial variation associated with regional data, and we discuss these. Geostatisticians attach much importance to estimating and modeling the variogram to explore and analyze spatial variation because of the insight it provides. This article identifies the benefits of geostatistics, reviews its uses, and examines some of the recent developments that make it valuable for the analysis of data on areal supports across a wide range of problems.     

Cyclic Behavior of Smooth Steel Reinforcing Bars: Experimental Analysis and Modeling Issues

This article presents the results of an experimental campaign on the cyclic behavior of smooth steel bars, used as internal reinforcement of existing Reinforced Concrete (RC) structures; the stress-strain relationship is analyzed for different values of L/D ratio, where L is the stirrup spacing and D is the longitudinal bar diameter. Most of the experimental tests concerned smooth bars with L/D ratios ranging between 5 and 100. The analysis of the test results is complemented by some comparisons of the curves obtained by experimental tests on smooth steel bars with those obtained by experimental tests on ribbed steel bars. The theoretical predictions obtained by existing models available in the literature on the cyclic behavior of ribbed steel bars are then discussed. Our review of these formulations underlines their range of applicability as well as their potential to predict the damage and buckling that occur for different L/D ratios of the smooth steel bars.     

Toward Hybrid Modeling and Automatic Planimetry for Graphic Documentation of the Archaeological Heritage: The Cortina Family Pantheon in the Cemetery of Valencia

ABSTRACT

The current trend toward the hybrid methodology of combining terrestrial laser scanner (TLS) with close-range and UAV-assisted photogrammetry is becoming the most effective method for the complete capture of archaeological sites. In this article, we consider three objectives in this regard: first, to check an integration procedure, based on different capture techniques, to obtain the best possible complete digital model in different situations related to size, lighting, and occlusions. Second, a “laser scanning with the help of photogrammetry” strategy for the operation with the different data sources, which allows to adapt the processes of photogrammetric orientation, cloud registration, and automatic texturing, to the characteristics of each capture model. Finally, to present the digital edition of these models through automatic technical projections and realistic visualizations, to show their ability to interpret their geometry or share their knowledge, respectively.     

基于 Web 数据挖掘的旅游需求分析与预测

文探讨了Web数据应用于旅游需求预测的优势,构建了旅游Web信息组织和旅游需求之间的映射关系,并由此探讨了如何利用Web数据挖掘技术进行旅游需求分析和预测,和建立基于旅游Web数据分析(预测)的知识库的规则,从而明确了其分析和预测流程,并以陕西省为例进行了实证分析.     

Target-Density Weighting Interpolation and Uncertainty Evaluation for Temporal Analysis of Census Data

Conducting temporal analysis of census data often requires applying areal interpolation to integrate data that have been spatially aggregated using incompatible zoning systems. This article introduces a method of areal interpolation, target-density weighting (TDW), that is useful for long-term temporal analysis because it requires only readily available historical data and basic geographic information system operations. Then, through regression analysis of a large sample of U.S. census tract data, a model is produced that relates the error in TDW estimates of tract population to four basic properties of tracts. An analysis of model residuals combined with theorized absolute limits on interpolation error yields formulas with which we can compute upper and lower prediction bounds on the population in a tract of one census at the time of a different census. These prediction intervals enable the interpretation of different interpolated estimates with appropriately varying degrees of uncertainty.