Urban waterscapes as products, media and symbols of change – the re-invention of the Ruhr

Urban waterscapes are today a key element of revitalization strategies as locations for highscale office and housing estates as well as tourism and leisure amenities. Their renaissance is not only related to economic transformations; it also goes hand in hand with the re-establishment of urban waterscapes as important parts of the urban imagery and identity after years of neglect and ecologic devastation. We argue that new urban waterscapes have been and are being constructed as emblematic places for successful urban (re)development, and illustrate this argument with the case of the Ruhr Area in Germany. For several years, this old-industrial region has undertaken serious efforts to re-invent itself after having lost its former economic base and importance. The different dimensions of structural change are illustrated, possibly even explained by the new meaning and relevance of land- and waterscapes and by the way they are restored, re-interpreted and rebuilt. New waters can be considered as products of structural change, media of re-invention and symbols for regional advancement. Our five case studies show the range and variety of water- and landscape planning in the area. We aim to show that water was and still is part of the regional cultural landscape that is highly coined and designed according to its societal uses. Waterscapes are planned according to regional development and planning goals, not only for economic reasons, but also in recognition of attractive waters functioning as key carriers of regional identity

Cloud cover estimation: Use of GOES imagery in development of cloud cover data base for insolation assessment

The potential of using digital satellite data to establish a cloud cover data base for the United States, one that would provide detailed information on the temporal and spatial variability of cloud development are studied. Key elements include: (1) interfacing GOES data from the University of Wisconsin Meteorological Data Facility with the Jet Propulsion Laboratory's VICAR image processing system and IBIS geographic information system; (2) creation of a registered multitemporal GOES data base; (3) development of a simple normalization model to compensate for sun angle; (4) creation of a variable size georeference grid that provides detailed cloud information in selected areas and summarized information in other areas; and (5) development of a cloud/shadow model which details the percentage of each grid cell that is cloud and shadow covered, and the percentage of cloud or shadow opacity. In addition, comparison of model calculations of insolation with measured values at selected test sites was accomplished, as well as development of preliminary requirements for a large scale data base of cloud cover statistics

How England Unified Germany: Geography and the Rise of Prussia After 1815

We analyze the formation oft he German Zollverein as an example how geography can shape institutional change. We show how the redrawing of the European map at the Congress of Vienna-notably Prussia's control over the Rhineland and Westphalia-affected the incentives for policymakers to cooperate. The new borders were not endogenous. They were at odds with the strategy of Prussia, but followed from Britain's intervention at Vienna regarding the Polish-Saxon question. For many small German states, the resulting borders changed the trade-off between the benefits from cooperation with Prussia and the costs of losing political control. Based on GIS data on Central Europe for 1818-1854 we estimate a simple model of the incentives to join an existing customs union. The model can explain the sequence of states joining the Prussian Zollverein extremely well. Moreover we run a counterfactual exercise: if Prussia would have succeeded with her strategy to gain the entire Kingdom of Saxony instead of the western provinces, the Zollverein would not have formed. We conclude that geography can shape institutional change. To put it different, as collateral damage to her intervention at Vienna,"'Britain unified Germany"'

CONFU: Configuration Fuzzing Testing Framework for Software Vulnerability Detection

Many software security vulnerabilities only reveal themselves under certain conditions, i.e., particular configurations and inputs together with a certain runtime environment. One approach to detecting these vulnerabilities is fuzz testing that feeds randomly generated inputs to the software and witnesses its failures. However, typical fuzz testing makes no guarantees regarding the syntactic and semantic validity of the input, or of how much of the input space will be explored. To address these problems, we present a new testing methodology called Configuration Fuzzing. Configuration Fuzzing is a technique whereby the configuration of the running application is mutated at certain execution points, in order to check for vulnerabilities that only arise in certain conditions. As the application runs in the deployment environment, this testing technique continuously fuzzes the configuration and checks "security invariants'' that, if violated, indicate a vulnerability. We discuss the approach and introduce a prototype framework called ConFu (CONfiguration FUzzing testing framework) implementation. We also present the results of case studies that demonstrate the approach's feasibility and evaluate its performance

Cloud cover typing from environmental satellite imagery. Discriminating cloud structure with Fast Fourier Transforms (FFT)

The use of two dimensional Fast Fourier Transforms (FFTs) subjected to pattern recognition technology for the identification and classification of low altitude stratus cloud structure from Geostationary Operational Environmental Satellite (GOES) imagery was examined. The development of a scene independent pattern recognition methodology, unconstrained by conventional cloud morphological classifications was emphasized. A technique for extracting cloud shape, direction, and size attributes from GOES visual imagery was developed. These attributes were combined with two statistical attributes (cloud mean brightness, cloud standard deviation), and interrogated using unsupervised clustering amd maximum likelihood classification techniques. Results indicate that: (1) the key cloud discrimination attributes are mean brightness, direction, shape, and minimum size; (2) cloud structure can be differentiated at given pixel scales; (3) cloud type may be identifiable at coarser scales; (4) there are positive indications of scene independence which would permit development of a cloud signature bank; (5) edge enhancement of GOES imagery does not appreciably improve cloud classification over the use of raw data; and (6) the GOES imagery must be apodized before generation of FFTs

Baseline: Metrics for setting a baseline for web vulnerability scanners

As web scanners are becoming more popular because they are faster and cheaper than security consultants, the trend of relying on these scanners also brings a great hazard: users can choose a weak or outdated scanner and trust incomplete results. Therefore, benchmarks are created to both evaluate and compare the scanners. Unfortunately, most existing benchmarks suffer from various drawbacks, often by testing against inappropriate criteria that does not reflect the user's needs. To deal with this problem, we present an approach called Baseline that coaches the user in picking the minimal set of weaknesses (i.e., a baseline) that a qualified scanner should be able to detect and also helps the user evaluate the effectiveness and efficiency of the scanner in detecting those chosen weaknesses. Baseline's goal is not to serve as a generic ranking system for web vulnerability scanners, but instead to help users choose the most appropriate scanner for their specific needs

Configuration Fuzzing for Software Vulnerability Detection

Many software security vulnerabilities only reveal themselves under certain conditions, i.e., particular configurations of the software together with its particular runtime environment. One approach to detecting these vulnerabilities is fuzz testing, which feeds a range of randomly modified inputs to a software application while monitoring it for failures. However, fuzz testing makes no guarantees regarding the syntactic and semantic validity of the input, or of how much of the input space will be explored. To address these problems, in this paper we present a new testing methodology called configuration fuzzing. Configuration fuzzing is a technique whereby the configuration of the running application is randomly modified at certain execution points, in order to check for vulnerabilities that only arise in certain conditions. As the application runs in the deployment environment, this testing technique continuously fuzzes the configuration and checks "security invariants" that, if violated, indicate a vulnerability; however, the fuzzing is performed in a duplicated copy of the original process, so that it does not affect the state of the running application. In addition to discussing the approach and describing a prototype framework for implementation, we also present the results of a case study to demonstrate the approach's efficiency

CONFU: Configuration Fuzzing Testing Framework for Software Vulnerability Detection

Many software security vulnerabilities only reveal themselves under certain conditions, i.e., particular configurations and inputs together with a certain runtime environment. One approach to detecting these vulnerabilities is fuzz testing. However, typical fuzz testing makes no guarantees regarding the syntactic and semantic validity of the input, or of how much of the input space will be explored. To address these problems, we present a new testing methodology called Configuration Fuzzing. Configuration Fuzzing is a technique whereby the configuration of the running application is mutated at certain execution points, in order to check for vulnerabilities that only arise in certain conditions. As the application runs in the deployment environment, this testing technique continuously fuzzes the configuration and checks "security invariants'' that, if violated, indicate a vulnerability. We discuss the approach and introduce a prototype framework called ConFu (CONfiguration FUzzing testing framework) for implementation. We also present the results of case studies that demonstrate the approach's feasibility and evaluate its performance

Use of ERTS-1 data to assess and monitor change in the Southern California environment

There are no author-identified significant results in this report

Pregnant women\u27s knowledge of weight, weight gain, complications of obesity and weight management strategies in pregnancy

BACKGROUND: Obesity is increasingly common in the obstetric population. Maternal obesity and excess gestational weight gain (GWG) are associated with increased perinatal risk. There is limited published data demonstrating the level of pregnant women's knowledge regarding these problems, their consequences and management strategies.We aimed to assess the level of knowledge of pregnant women regarding: (i) their own weight and body mass index (BMI) category, (ii) awareness of guidelines for GWG, (iii) concordance of women's own expectations with guidelines, (iv) knowledge of complications associated with excess GWG, and (v) knowledge of safe weight management strategies in pregnancy. METHODS: 364 pregnant women from a single center university hospital antenatal clinic were interviewed by an obstetric registrar. The women in this convenience sample were asked to identify their weight category, their understanding of the complications of obesity and excessive GWG in pregnancy and safe and/or effective weight management strategies in pregnancy. RESULTS: Nearly half (47.8%) of the study population were overweight or obese. 74% of obese women underestimated their BMI category. 64% of obese women and 40% of overweight women overestimated their recommended GWG. Women's knowledge of the specific risks associated with excess GWG or maternal obesity was poor. Women also reported many incorrect beliefs about safe weight management in pregnancy. CONCLUSIONS: Many pregnant women have poor knowledge about obesity, GWG, their consequences and management strategies. Bridging this knowledge gap is an important step towards improving perinatal outcomes for all pregnant women, especially those who enter pregnancy overweight or obese