A new approach to real time traffic sign recognition based on colour information

The automatic interpretation of conventional traffic signs is very complex and time consuming. The paper concerns an automatic warning system for driving assistance. It does not interpret the standard traffic signs on the roadside; the proposal is to incorporate into the existing signs another type of traffic sign whose information will be more easily interpreted by a processor. The type of information to be added is profuse and therefore the most important object is the robustness of the system. The basic proposal of this new philosophy is that the co-pilot system for automatic warning and driving assistance can interpret with greater ease the information contained in the new sign, whilst the human driver only has to interpret the "classic" sign. One of the codings that has been tested with good results and which seems to us easy to implement is that which has a rectangular shape and 4 vertical bars of different colours. The size of these signs is equivalent to the size of the conventional signs (approximately 0.4 m2). The colour information from the sign can be easily interpreted by the proposed processor and the interpretation is much easier and quicker than the information shown by the pictographs of the classic signs

Scalable real-time crisis mapping and analytics of social media streams for disaster management and breaking news

Real-time geoparsing of social media streams (e.g. Twitter, YouTube, Instagram, Flickr, FourSquare) is providing a new 'virtual sensor' capability to end users such as emergency response agencies (e.g. Tsunami early warning centres, Civil protection authorities) and news agencies (e.g. Deutsche Welle, BBC News). Challenges in this area include scaling up natural language processing (NLP) and information retrieval (IR) approaches to handle real-time traffic volumes, reducing false positives, creating real-time infographic displays useful for effective decision support and providing support for trust and credibility analysis using geosemantics. I will present in this seminar on-going work by the IT Innovation Centre over the last 4 years (TRIDEC and REVEAL FP7 projects) in building such systems, and highlights our research towards improving trustworthy and credible of crisis map displays and real-time analytics for trending topics and influential social networks during major news worthy events.

Las alertas tempranas. La prevención de la violencia y las dificultades de la experiencia colombiana

El presente artículo realiza una aproximación al sistema de alertas tempranas que se han constituido en un importante instrumento para evitar el escalamiento de las disputas y sus consecuencias. Los autores realizan un estudio sobre la aplicación de este sistema preventivo en el caso colombiano, analizando el papel del Estado en la implementación de estos mecanismos. Destacan la complejidad del caso colombiano en tanto que el Estado adquiere la doble característica de juez y parte en la implementación de este sistema preventivo, dado que es actor del conflicto y a la vez responsable de su implementación. Así mismo, describen algunas de las dificultades, propias de un contexto de conflicto armado, que tiene la fuerza pública para prestar asistencia pronta y eficaz a las comunidades ante amenazas o ataques de los grupos armados ilegales.-----This article approaches the early alert system, a valuable instrument for avoiding growing conflicts and their consequences. The authors study the implementation of such a system in Colombia by analyzing the role that the State plays in its application. They point out the complexity of the Colombian situation, insofar as the State plays a double role as judge of and participant in the implementation of this preventive system, since it is involved in the conflict and is also responsible for its implementation. In addition, the authors describe some of the difficulties, often found in an armed-conflict context, that the army and the police must face in order to assist communities on time and effectively when the latter are threatened or attacked by illegal armed groups.

Catalase in fluvial biofilms: a comparison between different extraction methods and example of application in a metal-polluted river

Antioxidant enzymes are involved in important processes of cell detoxification during oxidative stress and have, therefore, been used as biomarkers in algae. Nevertheless, their limited use in fluvial biofilms may be due to the complexity of such communities. Here, a comparison between different extraction methods was performed to obtain a reliable method for catalase extraction from fluvial biofilms. Homogenization followed by glass bead disruption appeared to be the best compromise for catalase extraction. This method was then applied to a field study in a metal-polluted stream (Riou Mort, France). The most polluted sites were characterized by a catalase activity 4–6 times lower than in the low-polluted site. Results of the comparison process and its application are promising for the use of catalase activity as an early warning biomarker of toxicity using biofilms in the laboratory and in the field

Nitrogen management is essential to prevent tropical oil palm plantations from causing ozone pollution

More than half the world's rainforest has been lost to agriculture since the Industrial Revolution. Among the most widespread tropical crops is oil palm (Elaeis guineensis): global production now exceeds 35 million tonnes per year. In Malaysia, for example, 13% of land area is now oil palm plantation, compared with 1% in 1974. There are enormous pressures to increase palm oil production for food, domestic products, and, especially, biofuels. Greater use of palm oil for biofuel production is predicated on the assumption that palm oil is an “environmentally friendly” fuel feedstock. Here we show, using measurements and models, that oil palm plantations in Malaysia directly emit more oxides of nitrogen and volatile organic compounds than rainforest. These compounds lead to the production of ground-level ozone (O3), an air pollutant that damages human health, plants, and materials, reduces crop productivity, and has effects on the Earth's climate. Our measurements show that, at present, O3 concentrations do not differ significantly over rainforest and adjacent oil palm plantation landscapes. However, our model calculations predict that if concentrations of oxides of nitrogen in Borneo are allowed to reach those currently seen over rural North America and Europe, ground-level O3 concentrations will reach 100 parts per billion (109) volume (ppbv) and exceed levels known to be harmful to human health. Our study provides an early warning of the urgent need to develop policies that manage nitrogen emissions if the detrimental effects of palm oil production on air quality and climate are to be avoided.

Nitrogen management is essential to prevent tropical oil palm plantations from causing ground-level ozone pollution

More than half the world's rainforest has been lost to agriculture since the Industrial Revolution. Among the most widespread tropical crops is oil palm (Elaeis guineensis): global production now exceeds 35 million tonnes per year. In Malaysia, for example, 13% of land area is now oil palm plantation, compared with 1% in 1974. There are enormous pressures to increase palm oil production for food, domestic products, and, especially, biofuels. Greater use of palm oil for biofuel production is predicated on the assumption that palm oil is an "environmentally friendly'' fuel feedstock. Here we show, using measurements and models, that oil palm plantations in Malaysia directly emit more oxides of nitrogen and volatile organic compounds than rainforest. These compounds lead to the production of ground-level ozone (O-3), an air pollutant that damages human health, plants, and materials, reduces crop productivity, and has effects on the Earth's climate. Our measurements show that, at present, O-3 concentrations do not differ significantly over rainforest and adjacent oil palm plantation landscapes. However, our model calculations predict that if concentrations of oxides of nitrogen in Borneo are allowed to reach those currently seen over rural North America and Europe, ground-level O-3 concentrations will reach 100 parts per billion (10(9)) volume (ppbv) and exceed levels known to be harmful to human health. Our study provides an early warning of the urgent need to develop policies that manage nitrogen emissions if the detrimental effects of palm oil production on air quality and climate are to be avoided.

Simulating the impacts of global warming on wheat in China using a large area crop model

Temperature is one of the most prominent environmental factors that determine plant growth, devel- opment, and yield. Cool and moist conditions are most favorable for wheat. Wheat is likely to be highly vulnerable to further warming because currently the temperature is already close to or above optimum. In this study, the impacts of warming and extreme high temperature stress on wheat yield over China were investigated by using the general large area model (GLAM) for annual crops. The results showed that each 1±C rise in daily mean temperature would reduce the average wheat yield in China by about 4.6%{5.7% mainly due to the shorter growth duration, except for a small increase in yield at some grid cells. When the maximum temperature exceeded 30.5±C, the simulated grain-set fraction declined from 1 at 30.5±C to close to 0 at about 36±C. When the total grain-set was lower than the critical fractional grain-set (0.575{0.6), harvest index and potential grain yield were reduced. In order to reduce the negative impacts of warming, it is crucial to take serious actions to adapt to the climate change, for example, by shifting sowing date, adjusting crop distribution and structure, breeding heat-resistant varieties, and improving the monitoring, forecasting, and early warning of extreme climate events.

Farmers’ attitudes to disease risk management in England: a comparative analysis of sheep and pig farmers

The UK Department for Environment, Food and Rural Affairs (Defra) identified practices to reduce the risk of animal disease outbreaks. We report on the response of sheep and pig farmers in England to promotion of these practices. A conceptual framework was established from research on factors influencing adoption of animal health practices, linking knowledge, attitudes, social influences and perceived constraints to the implementation of specific practices. Qualitative data were collected from nine sheep and six pig enterprises in 2011. Thematic analysis explored attitudes and responses to the proposed practices, and factors influencing the likelihood of implementation. Most feel they are doing all they can reasonably do to minimise disease risk and that practices not being implemented are either not relevant or ineffective. There is little awareness and concern about risk from unseen threats. Pig farmers place more emphasis than sheep farmers on controlling wildlife, staff and visitor management and staff training. The main factors that influence livestock farmers’ decision on whether or not to implement a specific disease risk measure are: attitudes to, and perceptions of, disease risk; attitudes towards the specific measure and its efficacy; characteristics of the enterprise which they perceive as making a measure impractical; previous experience of a disease or of the measure; and the credibility of information and advice. Great importance is placed on access to authoritative information with most seeing vets as the prime source to interpret generic advice from national bodies in the local context. Uptake of disease risk measures could be increased by: improved risk communication through the farming press and vets to encourage farmers to recognise hidden threats; dissemination of credible early warning information to sharpen farmers’ assessment of risk; and targeted information through training events, farming press, vets and other advisers, and farmer groups, tailored to the different categories of livestock farmer.

Examining the large-scale spatial coherence of European drought using regional indicators of precipitation and streamflow deficit

Droughts tend to evolve slowly and affect large areas simultaneously, which suggests that improved understanding of spatial coherence of drought would enable better mitigation of drought impacts through enhanced monitoring and forecasting strategies. This study employs an up-to-date dataset of over 500 river flow time series from 11 European countries, along with a gridded precipitation dataset, to examine the spatial coherence of drought in Europe using regional indicators of precipitation and streamflow deficit. The drought indicators were generated for 24 homogeneous regions and, for selected regions, historical drought characteristics were corroborated with previous work. The spatial coherence of drought characteristics was then examined at a European scale. Historical droughts generally have distinctive signatures in their spatio-temporal development, so there was limited scope for using the evolution of historical events to inform forecasting. Rather, relationships were explored in time series of drought indicators between regions. Correlations were generally low, but multivariate analyses revealed broad continental-scale patterns, which appear to be related to large-scale atmospheric circulation indices (in particular, the North Atlantic Oscillation and the East Atlantic West Russia pattern). A novel methodology for forecasting was developed (and demonstrated with reference to the United Kingdom), which predicts drought from drought i.e. uses spatial coherence of drought to facilitate early warning of drought in a target region, from drought which is developing elsewhere in Europe.Whilst the skill of the methodology is relatively modest at present, this approach presents a potential new avenue for forecasting, which offers significant advantages in that it allows prediction for all seasons, and also shows some potential for forecasting the termination of drought conditions.

Customer retention management in the recession

The purpose of this article is to explore customer retention strategies and tactics implemented by firms in recession. Our investigations show just how big a challenge many organizations face in their ability to manage customer retention effectively. While leading organizations have embedded real-time customer life cycle management, developed accurate early warning systems, price elasticity models and ‘deal calculators’, the organizations we spoke to have only gone as far as calculating the value at risk and building simple predictive models.

Continental and global scale flood forecasting systems

Floods are the most frequent of natural disasters, affecting millions of people across the globe every year. The anticipation and forecasting of floods at the global scale is crucial to preparing for severe events and providing early awareness where local flood models and warning services may not exist. As numerical weather prediction models continue to improve, operational centres are increasingly using the meteorological output from these to drive hydrological models, creating hydrometeorological systems capable of forecasting river flow and flood events at much longer lead times than has previously been possible. Furthermore, developments in, for example, modelling capabilities, data and resources in recent years have made it possible to produce global scale flood forecasting systems. In this paper, the current state of operational large scale flood forecasting is discussed, including probabilistic forecasting of floods using ensemble prediction systems. Six state-of-the-art operational large scale flood forecasting systems are reviewed, describing similarities and differences in their approaches to forecasting floods at the global and continental scale. Currently, operational systems have the capability to produce coarse-scale discharge forecasts in the medium-range and disseminate forecasts and, in some cases, early warning products, in real time across the globe, in support of national forecasting capabilities. With improvements in seasonal weather forecasting, future advances may include more seamless hydrological forecasting at the global scale, alongside a move towards multi-model forecasts and grand ensemble techniques, responding to the requirement of developing multi-hazard early warning systems for disaster risk reduction.

Prospects for biodiversity conservation in the Atlantic Forest: Lessons from aging human-modified landscapes

Recent global assessments have shown the limited coverage of protected areas across tropical biotas, fuelling a growing interest in the potential conservation services provided by anthropogenic landscapes. Here we examine the geographic distribution of biological diversity in the Atlantic Forest of South America, synthesize the most conspicuous forest biodiversity responses to human disturbances, propose further conservation initiatives for this biota, and offer a range of general insights into the prospects of forest species persistence in human-modified tropical forest landscapes worldwide. At the biome scale, the most extensive pre-Columbian habitats across the Atlantic Forest ranged across elevations below 800 masl, which still concentrate most areas within the major centers of species endemism. Unfortunately, up to 88% of the original forest habitat has been lost, mainly across these low to intermediate elevations, whereas protected areas are clearly skewed towards high elevations above 1200 masl. At the landscape scale, most remaining Atlantic Forest cover is embedded within dynamic agro-mosaics including elements such as small forest fragments, early-to-late secondary forest patches and exotic tree mono-cultures. In this sort of aging or long-term modified landscapes, habitat fragmentation appears to effectively drive edge-dominated portions of forest fragments towards an early-successional system, greatly limiting the long-term persistence of forest-obligate and forest-dependent species. However, the extent to which forest habitats approach early-successional systems, thereby threatening the bulk of the Atlantic Forest biodiversity, depends on both past and present landscape configuration. Many elements of human-modified landscapes (e.g. patches of early-secondary forests and tree mono-cultures) may offer excellent conservation opportunities, but they cannot replace the conservation value of protected areas and hitherto unprotected large patches of old-growth forests. Finally, the biodiversity conservation services provided by anthropogenic landscapes across Atlantic Forest and other tropical forest regions can be significantly augmented by coupling biodiversity corridor initiatives with biota-scale attempts to plug existing gaps in the representativeness of protected areas. (C) 2010 Elsevier Ltd. All rights reserved.

Crise fiscal em municípios, indicadores e instrumentos

O objetivo deste artigo é desenvolver um conjunto de indicadores denominado Sistema Preventivo (Earlv Warning System) que permita diagnosticar a crise antes de sua manifestação aguda. atuando sobre o processo antecipadamente. Com base nesses indicadores é possível definir estratégias que permitam agir de modo a deter o processo e prevenir o esgotamento fiscal. Em outras palavras, por tratar-se a crise fiscal de um processo estrutural, é possível submeter o município a um tratamento preventivo. Pretende-se também discutir os instrumentos que podem ser utilizados pelos municípios no caso de estarem enfrentando uma crise fiscal. A segunda seção do artigo descreve as variáveis que causam e condicionam o processo e a manifestação aguda de crise fiscal. A terceira seção desenvolve os indicadores analíticos por meio dos quais será possível detectar de modo antecipado um processo de emergência fiscal, ou seja, o sistema preventivo. Na mesma seção, aplica-se o sistema preventivo descrito A cidade paulista de São José dos Campos, para o período de 1980 a 1990, e avalia-se a situação fiscal da cidade. A quarta seção descreve estratégias e políticas que permitirão agir sobre o processo de crise a fim de revertê-lo e evitar sua evolução.

Indicadores de vulnerabilidade aplicados ao Brasil : uma abordagem empírica

Ao longo da história econômica, as instabilidades financeiras sempre despertaram interesses dos pesquisadores, que visavam entender os motivos pelos quais uma economia se tornava vulnerável em determinadas situações. Outros estudiosos procuravam desvendar as razões que levavam às instabilidades e, além do mais, procuravam relacionar as variáveis que tinham maior poder de explicação nos períodos de instabilidade. O presente trabalho focará nas pesquisas dos early warning indicators aplicados à economia brasileira, com o intuito de estimar quais são os indicadores mais aderentes na explicação dos movimentos da economia. Para tal, o trabalho está dividido da seguinte maneira: No primeiro capítulo, será abordada uma introdução do trabalho. Já no segundo capítulo, serão abordados os referenciais teóricos de autores que estudaram os motivos das instabilidades financeiras. Também consta a revisão dos estudos dos early warning indicators e do exchange market pressure aplicado à economia brasileira. Posteriormente, no terceiro capítulo, é feita uma análise econométrica, com os critérios de seleção dos indicadores. Além da justificativa das escolhas dos indicadores, serão estimados modelos dos impactos dos early warning indicators na economia brasileira. Após isto, também foi calculado o exchange market pressure para a economia brasileira. Por fim, concluí-se que, apesar dos modelos de early warning indicators não serem tão aderentes à realidade brasileira, a sua determinação estatística é de grande importância para o acompanhamento das tendências na economia.