虚拟专用网VPN管理研究

随着网络技术的广泛应用以及网络安全的日益重要,虚拟专用网VPN得到广泛应用。如何对VPN网络进行有效管理成为一个迫切需要解决的问题。本文从实际需求出发,提出了一个对VPN网络进行策略管理的模型,该模型效率较高,具有较大的现实意义。     

社会稳定的系统动态分析及其定量化研究

社会稳定历来就是执政者和普通百姓都十分关注的问题。我国正处于社会转型期,社会稳定问题理所当然备受关注。但是,如何维护社会稳定?如何创造出一种对社会稳定的测量方法,能够在社会将要失稳之前就超前预警和预控社会的政治局面?这无疑是一个既有现实意义,又有理论价值的重大课题。对此,采用系统动态分析的方法和社会指标技术,建立一套能够对社会稳定的程度进行计量的工具——社会稳定指标体系,对于国家各级政府完善社会预警机制,维护社会稳定会大有裨益。     

中国城市社区组织管理模式的构建与创新

我国城市社区建设与管理工作已取得了很大成绩,各地也形成了各具特色的社区组织管理模式。但综观全国城市社区组织管理的现状,大多处于初级的经验型层面,存在着很多问题。因此,有必要从科学的组织管理理念出发,构建一种新型的城市社区组织管理模式,使城市社区组织管理逐步由行政管理体制向法制保障下的社区居民自治体制转变,并且随着社区建设的发展而不断完善。     

TRAJECTORIES OF CRIME AT PLACES: A LONGITUDINAL STUDY OF STREET SEGMENTS IN THE CITY OF SEATTLE*

Studies of crime at micro places have generally relied on cross‐sectional data and reported the distributions of crime statistics over short periods of time. In this paper we use official crime data to examine the distribution of crime at street segments in Seattle, Washington, over a 14‐year period. We go beyond prior research in two ways. First, we view crime trends at places over a much longer period than other studies that have examined micro places. Second, we use group‐based trajectory analysis to uncover distinctive developmental trends in our data. Our findings support the view that micro places generally have stable concentrations of crime events over time. However, we also find that a relatively small proportion of places belong to groups with steeply rising or declining crime trajectories and that these places are primarily responsible for overall city trends in crime. These findings are particularly important given the more general decline in crime rates observed in Seattle and many other American cities in the 1990s. Our study suggests that the crime drop can be understood not as a general process that occurred across the city landscape but one that was generated in a relatively small group of micro places with strong declining crime trajectories over time.     

构建学习型政府的基础、核心与保障

构建学习型政府是当代社会经济发展的客观要求.结构再造是构建学习型政府的基础,文化重塑是构建学习型政府的核心,机制创建是构建学习型政府的保障.     

Stature estimation using foot dimensions via 3D scanning in Taiwanese male adults

In forensic identification, the use of foot dimensions to predict stature is a requisite. For Taiwanese male stature prediction, available information about stature estimation using foot dimensions is still lacking. Therefore, the primary purpose of this study was to establish Taiwanese adult male stature prediction models for various foot dimensions. A total of 2,072 male 3D foot models were collected and the subjects' ages ranged from 18 to 59 years old. Thirteen foot dimensions for each foot were utilized in this study. Bilateral differences were tested using paired t-tests. Stature predictions based on different foot dimensions were conducted using simple linear and stepwise regression methods. The results showed significant bilateral differences in the majority of the selected foot dimensions (p < 0.001). Foot length had the highest positive correlation with stature in the right and left foot. Using length-related dimensions generated better prediction accuracy (0.356 < R² < 0.533, 4.193 < SEE < 4.928), whereas the worst accuracy was observed with angle-related dimensions (0.001 < R² < 0.023; 6.072 < SEE < 6.137) when employing a single foot dimension to estimate Taiwanese male stature. Stepwise regression analysis results indicated that the coefficient of determination was improved to 0.590 and 0.593 by applying five and six foot parameters to predict stature, respectively. The findings of the present study suggest that these stature estimation equations can be applied to predict Taiwanese male stature in the forensic science field.     

基于角膜图像的人体死亡时间推断模型初探

目的尸体角膜随死后时间延长发生的形态学变化是规律性较好的指标,常用来判断死亡时间(postmortem interval,PMI)。本文尝试用机器视觉代替人的肉眼主观判断,收集尸体样本以建立通过人体角膜图像推断PMI的模型。方法收集实际案例建立包含505例人体死后角膜图像的数据库,PMI范围为0.24h(约死后14min)至492h(约死后20.5d),大致分为三类(依次为:0~<6h、6~<20h、20h及以上)或二类(0~<15h、15h及以上);使用由华盛顿大学陈天奇博士提出的Xgboost模型分别进行二分类与三分类分析;使用多种卷积神经网络模型分别进行分类和回归学习,并通过比较最终选择了由微软研究院提出的ResNet模型进行分析。结果Xgboost在三分类时预测准确率依次为71.8%、40.7%、65.7%,二分类时为90%、48.5%。ResNet分类模型中,精准率、召回率在三分类时分别依次为:81%、75%,30%、50%,61%、71%,二分类时为:70%、92%,76%、38%。ResNet回归模型中,比较整个模型的预测结果,0~6h内的预测值与真实值较为接近,均值误差为0.5616,均方误差为0.5873,6h之后开始出现较大误差。结论分类和回归模型都在0~6h之内得到了很好的结果,说明在此时间段内,角膜图像噪声较低,可预测性强。     

Desire for Smart Growth: A Survey of Residential Preferences in the Salt Lake Region of Utah

As an alternative to sprawling development, smart growth combines proximity to work, proximity to shopping and other destinations, neighborhood housing mix, shared and paid parking, complete street designs, and proximity to public transit. This article uses a stated-choice experiment to determine residents' attitudes toward these various aspects of smart growth in the Salt Lake region of Utah. Utah is a conservative state, where attitudes toward auto-oriented suburbia may be more positive than in other parts of the United States. So, one might wonder whether changing national attitudes toward smart growth, documented in several surveys, apply to residents of the Salt Lake region. In this stated-choice experiment, respondents were asked to choose between pairs of housing scenarios with different attributes and different prices. Mixed logit (random parameters logit) was used to relate individuals' choices to attributes, prices, and sociodemographic characteristics of respondents. The results show that, generally, respondents have positive attitudes toward most aspects of smart growth but still express preferences for single-family neighborhoods with free parking in their own driveways or garages. Different life cycle cohorts have different preferences. Proximity to work is more important for childless young adults. Young families with children place higher value on living in a neighborhood with only single-family homes and transit access. Retired empty nesters favor a mix of housing types over single-family housing on one-acre-plus lots. The results suggest that while residents of the Salt Lake region like suburban neighborhoods with primarily single-family houses, they would also like to have improved accessibility to amenities in the suburbs.     

Residential Segregation,Housing Submarkets,and Spatial Analysis: St. Louis and Cincinnati as a Case Study

This article considers how spatial analysis of housing submarkets can advance research into residential segregation. While an emphasis on housing submarkets has been proposed as a new construct for modeling housing prices, its use in analyzing residential segregation has been limited. Recent advances in spatial analysis and geographic information systems present new opportunities for researchers to exploit the potential of housing submarkets as constructs that offer a more precise way to examine residential segregation. The article synthesizes literature related to residential segregation and housing submarkets and demonstrates how to delineate housing submarkets using publicly available data. It examines the spatial distribution of housing submarkets and how the socially disadvantaged are represented across housing submarkets in St. Louis, Missouri, and Cincinnati, Ohio, to conclude that St. Louis's housing market is more polarized and racially segregated than Cincinnati's. Spatial analysis of housing submarkets, in conjunction with archival analysis, provides a promising avenue for identifying residential segregation as a multidimensional phenomenon, and a means to explore local processes of urban inequality.     

The faces of death: regional differentiation in cause-specific mortality in the past

In mortality research, much attention has been paid to the strong geographical differentials in mortality levels and in modern mortality decline, as the analysis of this geographical differentiation might hold the key to explaining the determinants of mortality change. The use of historical cause-specific mortality data has proved a challenging, although very insightful, means to this end. The four contributions to this special issue focus on cause-specific mortality in the past, both to reassess older data using new insights and to challenge existing insights by using new data and methods. These papers, of which earlier versions were presented during the thirty-eighth Social Science History Association (SSHA) Meeting in Chicago, 21–24 November 2013, explore mortality at different stages of the life course, ranging from early infancy to old age. Moreover, each paper revolves around a different group of causes of death. Although the papers are in many ways rather different, together they demonstrate how different data, theoretical frameworks and methodologies can push the boundaries of research into the trends and determinants of historical mortality patterns.