Four-year study of roughness patterns using weekly calibrations

In order to evaluate the stability and reproducibility of roughness measurements, calibrations of the same roughness standard were held over four years. Calibrations were performed in the Laboratório de Medição de Superfícies Ópticas (LMSO), on Mondays, between late January to early December every year. Here are presented and analyzed the calibration results and also the measurements of lab temperature and relative humid, at the time of calibration, in order to assess if there is any correlation between these influence factors in the obtained results. The LMSO lab is accredited by INMETRO (Brazilian NMI).     

An empirical study on improving dissimilarity-based classifications using one-shot similarity measure

This paper reports an experimental result obtained by additionally using unlabeled data together with labeled ones to improve the classification accuracy of dissimilarity-based methods, namely, dissimilarity-based classifications (DBC) [25]. In DBC, classifiers among classes are not based on the feature measurements of individual objects, but on a suitable dissimilarity measure among the objects instead. In order to measure the dissimilarity distance between pairwise objects, an approach using the one-shot similarity (OSS) [30] measuring technique instead of the Euclidean distance is investigated in this paper. In DBC using OSS, the unlabeled set can be used to extend the set of prototypes as well as to compute the OSS distance. The experimental results, obtained with artificial and real-life benchmark datasets, demonstrate that designing the classifiers in the OSS dissimilarity matrices instead of expanding the set of prototypes can further improve the classification accuracy in comparison with the traditional Euclidean approach. Moreover, the results demonstrate that the proposed setting does not work with non-Euclidean data.     

Mining human mobility patterns from social geo-tagged data

Online social networks allow users to tag their posts with geographical coordinates collected through the GPS interface of smart phones. The time- and geo-coordinates associated with a sequence of posts/tweets manifest the spatial–temporal movements of people in real life. This paper aims to analyze such movements to discover people and community behavior. To this end, we defined and implemented a novel methodology to mine popular travel routes from geo-tagged posts. Our approach infers interesting locations and frequent travel sequences among these locations in a given geo-spatial region, as shown from the detailed analysis of the collected geo-tagged data.     

《俄勒冈实验》模式原则实施效果评述

C?亚历山大教授在其出版的《俄勒冈实验》一书中，以俄勒冈大学为实验母体，界定出一种设计方式，以适用任何社区的总体规划，并归纳为6种主要原则。文章从现实角度出发，针对俄勒冈大学规划现状，提取6种原则中的模式原则并选择其中较为重要的几项模式对其论述进行比较研究，并依照现有实施状况进行一般性评价。对俄勒冈大学规划现状的研究将为我国高校下一阶段的校园规划和校园更新建设提供一定参考价值。     

The effects of pause software on the temporal characteristics of computer use

The study investigated the natural work–pause pattern of computer users and the possible effects of imposing pause regimes on this pattern. Hereto, the precise timing of computer events was recorded across a large number of days. It was found that the distribution of the pause durations was extremely skewed and that pauses with twice the duration are twice less likely to occur. The effects of imposing pause regimes were studied by performing a simulation of commercially available pause software. It was found that depending on the duration of the introduced pause, the software added 25–57% of the pauses taken naturally. Analysis of the timing of the introduced pauses revealed that a large number of spontaneous pauses were taken close to the inserted pause. Considering the disappointing results of studies investigating the effects of introducing (active) pauses during computer work, this study has cast doubt on the usefulness of introducing short duration pauses.     

A GENERAL APPROACH TO THE STUDY OF SPATIAL SYSTEMS II. Two Examples of Application

The emphasis in this work is on the practical application of ideas set forth in Part I. Two studies involving spatial distribution are discussed: the distribution of human population in the Indianapolis, Indiana Region, and the world distribution of mammals. In the first, populations over the period 1890–1980 of Ihe 393 townships making up the study area are used to produce classifications involving various numbers of classes of township types. A test of the theoretical structure posed in Part I is then detailed. On the theory that the underlying relations involved cannot sustain a real world structure involving more than five functional classes, it is hypothesized that classifications involving more than five classes will be associated with township distribution patterns that conflict with Central Place Theory. This is shown to be clearly so. In the second study, the derivation of a five region partitioning of world mammalian distribution patterns is described. Discussion includes the introduction of a wholly new rationale for taxonomic revision based on biogeographic criteria (and ultimately the principles described in Part I). The study closes with a short argument regarding why the model described in Part I should not be labelled as either social physics or anti-humanistic.     

大战略、大平台、大作为——论西部国家级新区发展对新型城镇化的作用

通过对中规院主持的两江、天府、兰州和贵安等西部国家级(准国家级)新区的前期研究、规划设计和后续实施咨询服务等工作,以及新区相应所在省(直辖市)的省域城镇体系规划的规划编制工作的总结,从实证的角度出发,提出西部国家级(准国家级)新区的设立不是东部先发地区的翻版,而是国家从战略高度给西部发展提供平台,使西部地区发挥国家层面应有作用.     

SDF classifier revisited

This paper is addressing problems related to the construction of classifiers based on the Similarity Discriminant Function (SDF), in which the traditional vector representation of a pattern is replaced with matrix data. We introduce potential modifications of the matrix data structure and propose new variants of the SDF. The algorithms that we present were tested on images of handwritten digits and on photographs of human faces, taken from the ORL and CMU‐PIE databases. The results of experiments show that our modifications significantly improved the performance of the original SDF classifier.