Colletotrichum gossypii var. cephalosporioides, fungo causador da ramulose do algodoerio, é ocorre disperso em quase todo Brasil. Sem um eficiente esquema de aplicação de fungicidas, a ramulose pode provocar severos danos. Outra importante doença para o algodoeiro, em muitas regiões do mundo, é a mancha angular, causada por Xanthomonas axonopodis pv. malvacearum. O objetivo deste trabalho foi desenvolver um índice de favorabilidade baseado em variáveis meteorológicas para estimar a ocorrência da ramulose e da mancha angular (MA) do algodoeiro. O período de incubação, a freqüência de infecção e a severidade das doenças foram avaliados em câmaras de crescimento mantidas a 15, 20, 25 e 30&#176;C e com períodos de câmara úmida de 0, 2, 4, 8, 16, 32, e 64 horas após inoculação com suspensão inóculo de 105 conídios mL-1 e 106 IFC mL-1. Severidade da doença. Severidade (MA) e número de lesões por área (Ramulose) foram modelados como função da duração do período de molhamento (DPM) e da temperatura (T). Em experimentos de campo em Piracicaba, SP, parcelas de algodão foram inoculadas com ramulose e mancha angular, separadamente, a fim de se avaliar semanalmente o progresso das doenças ao longo do tempo. Os dados de temperatura do ar e molhamento foliar no campo foram utilizados no modelo obtido com os resultados de câmaras de crescimento e assim calcular o índice de favorabilidade. As variáveis meteorológicas radiação solar, T, umidade relativa do ar, DPM, chuva e velocidade do vento foram avaliadas como possíveis variáveis explanatórias às taxas de crescimento da doença no campo. Testou-se também, como variável explanatória, o índice de favorabilidade (0,0<IF<1,0), calculado com os modelos de superfície utilizando os dados de T e DPM, obtidos dos experimentos de campo. Em câmaras de crescimento, a temperatura ótima foi de 27&#176;C para ramulose e 22&#176;C para mancha angular, com período de incubação de 10 dias para ramulose e entre 5 e 6 dias para mancha angular. A máxima severidade de ramulose ocorreu entre 25 e 30&#176;C e a máxima severidade de ALS ocorreu entre 20 e 25&#176;C. A severidade de ambas diminui rapidamente em temperaturas maiores ou menores que nessa faixa. A severidade de ramulose aumentou no intervalo de 4 até 32 horas de molhamento enquanto que ocorreu o mesmo com ALS no intervalo de 0 a 8 horas de molhamento. A severidade de ambas foi melhor ajustada por um modelo exponencial logarítmico em função do molhamento que, pela substituição dos parâmetros por funções de temperatura, descreveu a superfície de resposta com elevada precisão e exatidão. No campo, a taxa de crescimento da ramulose foi melhor relacionada ao índice de favorabilidade e à chuva, por regressão não linear, com coeficientes de determinação de 0,89 e 0,91, respectivamente. A taxa de crescimento da mancha angular apresentou razoável relação linear com as variáveis temperatura durante o período de molhamento e vento máximo, com R2 de 0,75 e 0,84 respectivamente. / Colletotrichum gossypii var. cephalosporioides, the fungus that causes ramulosis in cotton crops, is widespread in Brazil. Without an efficient fungicide schedule, ramulosis disease could provoke severe yield losses on cotton. Other important disease to cotton crop in several regions of the world is the bacterial blight also known as angular leaf spot (ALS), caused by Xanthomonas axonopodis pv. malvacearum. The objective of this work was develop a weather based favorability index to each of this diseases. The incubation period, the infection frequency and the severity of both diseases were evaluated in growth-chamber experiments, incubated at 15, 20, 25, 30, and 35&#176;C while exposed to wetness periods of 0, 2, 4, 8, 16, 32 and 64 h after inoculation with 105 conidium mL-1 and 106 CFU mL-1. Disease severity (ALS) and number of lesions per leaf area (ramulosis), was modeled as a function of leaf wetness duration (LWD) and temperature (T). At the field experiments in Piracicaba, cotton plots were inoculated with both pathogens separately, and disease severity was evaluated weekly. LWD and T data from the field trials were used as input to the model from growth chambers results and output the disease favorability index. Weather variables as solar radiation, temperature, relative humidity, wetness duration, rain, and wind speed were also evaluated as possible explanatory variables to the disease growth rate in the field. Was also tested the favorability index (0.0<FI<1.0), as explanatory variable, calculated with the surface models using T and LWD from the field. In growth chambers, the optimum temperature for ramulosis was 27&#176;C and 22&#176;C for ALS and incubation of 10 days to ramulosis and 5 to 6 days do ALS. Maximum ramulosis severity occurred from 20 to 30&#176; C, and between 20 and 25&#176;C to bacterial blight, and both decreased sharply at warmer or cooler temperatures. Ramulosis severity increased as wetness periods were increased from 4 to 32 h. Bacterial blight severity increased from 0 to 8 h of wetness period. The severity of both diseases, were best fitted by a logarithmic exponential model as function of LWD which, by the substitution of parameters for temperature functions, described the surface response with high precision and accuracy, even being a very flexible model. In the field, ramulosis growth rate was strongly correlated with values of the disease favorability index and rainfall with R2=0.89 and R2=0.91, respectively. Bacterial blight growth rate had best linear correlation to temperature during the wetness period and maximum wind with R2=0.75 and R2=0.84, respectively.

Deer-vehicle collisions in the United States (US) have increased dramatically over the last 50 years. Over one million deer-vehicle collisions are estimated to occur throughout the nation annually. These collisions result in hundreds of human deaths, thousands of human injuries, and billions of dollars in motor vehicle damage and health care costs. The increase in deer-vehicle collisions is partly the result of a growing deer population, caused largely by human manipulation of natural ecosystems. Awareness of the hazard deer pose is essential for drivers. Deer represent a dynamic, spatial and temporal hazard. Driver knowledge about deer at any time is critical for hazard awareness. State driver licensing agencies and state departments of transportation are the primary sources of information regarding driving hazards for most drivers. Through driver manuals, driver licensing agencies advise new drivers of hazards and provide strategies for dealing effectively with the hazards. Using nationally standardized warning signs, state departments of transportation advise drivers of potential hazards found along state highway systems. The first extensive nation-wide historical retrospective of the state driver manuals was conducted. The study assessed how new drivers have been informed of the hazard deer pose as this hazard has evolved. The assessment shows, although generally increasing in content, the information provided by state driver licensing agencies has been inconsistent from decade to decade, and from state to state. This inconsistency has left potentially millions of US drivers without fundamental knowledge of the growing deer hazard and/or strategies for dealing with the hazard. Recommendations and an exemplar for improving driver manuals are provided. The first historical retrospective of the standardized warning signs used by state departments of transportation was conducted to assess the effectiveness of these signs for advising drivers of deer hazards. The assessment shows standard deer warning signs used by state departments of transportation provide little temporal information for drivers. The paradigm shifting, risk matrix-based, colour-coded, Wildlife Hazard Rating System® (WildHAZ®) was developed to augment and transform conventional standard static deer warning signs into variable message signs that provide drivers with more consistent and comprehensive warnings about the deer hazard. The results of a web-based questionnaire survey regarding the WildHAZ® system demonstrated the majority of drivers who responded to the survey understand the system and would respond in a manner that should reduce their potential for a wildlife-related motor vehicle collision and/or the potential severity of such a collision. The majority of the survey respondents indicated that they would prefer a system like WildHAZ® to be used on roads and highways. Simulations of the effect of the WildHAZ® system on mean vehicle speeds were conducted. The results of the simulations suggest WildHAZ® system augmented deer warning signs could lead to fewer and less severe deer-vehicle collisions, if mean vehicle speeds were reduced at high risk periods. The risk matrix-based, colour-coded concept incorporated in the WildHAZ® system may have the potential to warn drivers of other spatially and temporally dynamic hazards. / Graduate / 0366 0709 0478 / lookforhelp@shaw.ca

Colletotrichum gossypii var. cephalosporioides, fungo causador da ramulose do algodoerio, é ocorre disperso em quase todo Brasil. Sem um eficiente esquema de aplicação de fungicidas, a ramulose pode provocar severos danos. Outra importante doença para o algodoeiro, em muitas regiões do mundo, é a mancha angular, causada por Xanthomonas axonopodis pv. malvacearum. O objetivo deste trabalho foi desenvolver um índice de favorabilidade baseado em variáveis meteorológicas para estimar a ocorrência da ramulose e da mancha angular (MA) do algodoeiro. O período de incubação, a freqüência de infecção e a severidade das doenças foram avaliados em câmaras de crescimento mantidas a 15, 20, 25 e 30&#176;C e com períodos de câmara úmida de 0, 2, 4, 8, 16, 32, e 64 horas após inoculação com suspensão inóculo de 105 conídios mL-1 e 106 IFC mL-1. Severidade da doença. Severidade (MA) e número de lesões por área (Ramulose) foram modelados como função da duração do período de molhamento (DPM) e da temperatura (T). Em experimentos de campo em Piracicaba, SP, parcelas de algodão foram inoculadas com ramulose e mancha angular, separadamente, a fim de se avaliar semanalmente o progresso das doenças ao longo do tempo. Os dados de temperatura do ar e molhamento foliar no campo foram utilizados no modelo obtido com os resultados de câmaras de crescimento e assim calcular o índice de favorabilidade. As variáveis meteorológicas radiação solar, T, umidade relativa do ar, DPM, chuva e velocidade do vento foram avaliadas como possíveis variáveis explanatórias às taxas de crescimento da doença no campo. Testou-se também, como variável explanatória, o índice de favorabilidade (0,0<IF<1,0), calculado com os modelos de superfície utilizando os dados de T e DPM, obtidos dos experimentos de campo. Em câmaras de crescimento, a temperatura ótima foi de 27&#176;C para ramulose e 22&#176;C para mancha angular, com período de incubação de 10 dias para ramulose e entre 5 e 6 dias para mancha angular. A máxima severidade de ramulose ocorreu entre 25 e 30&#176;C e a máxima severidade de ALS ocorreu entre 20 e 25&#176;C. A severidade de ambas diminui rapidamente em temperaturas maiores ou menores que nessa faixa. A severidade de ramulose aumentou no intervalo de 4 até 32 horas de molhamento enquanto que ocorreu o mesmo com ALS no intervalo de 0 a 8 horas de molhamento. A severidade de ambas foi melhor ajustada por um modelo exponencial logarítmico em função do molhamento que, pela substituição dos parâmetros por funções de temperatura, descreveu a superfície de resposta com elevada precisão e exatidão. No campo, a taxa de crescimento da ramulose foi melhor relacionada ao índice de favorabilidade e à chuva, por regressão não linear, com coeficientes de determinação de 0,89 e 0,91, respectivamente. A taxa de crescimento da mancha angular apresentou razoável relação linear com as variáveis temperatura durante o período de molhamento e vento máximo, com R2 de 0,75 e 0,84 respectivamente. / Colletotrichum gossypii var. cephalosporioides, the fungus that causes ramulosis in cotton crops, is widespread in Brazil. Without an efficient fungicide schedule, ramulosis disease could provoke severe yield losses on cotton. Other important disease to cotton crop in several regions of the world is the bacterial blight also known as angular leaf spot (ALS), caused by Xanthomonas axonopodis pv. malvacearum. The objective of this work was develop a weather based favorability index to each of this diseases. The incubation period, the infection frequency and the severity of both diseases were evaluated in growth-chamber experiments, incubated at 15, 20, 25, 30, and 35&#176;C while exposed to wetness periods of 0, 2, 4, 8, 16, 32 and 64 h after inoculation with 105 conidium mL-1 and 106 CFU mL-1. Disease severity (ALS) and number of lesions per leaf area (ramulosis), was modeled as a function of leaf wetness duration (LWD) and temperature (T). At the field experiments in Piracicaba, cotton plots were inoculated with both pathogens separately, and disease severity was evaluated weekly. LWD and T data from the field trials were used as input to the model from growth chambers results and output the disease favorability index. Weather variables as solar radiation, temperature, relative humidity, wetness duration, rain, and wind speed were also evaluated as possible explanatory variables to the disease growth rate in the field. Was also tested the favorability index (0.0<FI<1.0), as explanatory variable, calculated with the surface models using T and LWD from the field. In growth chambers, the optimum temperature for ramulosis was 27&#176;C and 22&#176;C for ALS and incubation of 10 days to ramulosis and 5 to 6 days do ALS. Maximum ramulosis severity occurred from 20 to 30&#176; C, and between 20 and 25&#176;C to bacterial blight, and both decreased sharply at warmer or cooler temperatures. Ramulosis severity increased as wetness periods were increased from 4 to 32 h. Bacterial blight severity increased from 0 to 8 h of wetness period. The severity of both diseases, were best fitted by a logarithmic exponential model as function of LWD which, by the substitution of parameters for temperature functions, described the surface response with high precision and accuracy, even being a very flexible model. In the field, ramulosis growth rate was strongly correlated with values of the disease favorability index and rainfall with R2=0.89 and R2=0.91, respectively. Bacterial blight growth rate had best linear correlation to temperature during the wetness period and maximum wind with R2=0.75 and R2=0.84, respectively.

<p>Cell Broadcast (CB) is a possible technical realisation of a global emergency alert system. It is a technique used for sending short text messages to all mobile stations (MSs) in a defined geographical area. An potential effect of using CB is the increase in battery consumption of the MS due to the fact that an extra channel has to be used to make the service available even when the network is otherwise congested. Another part of the service which leads to a potential problem is making CB messages available in different languages. Investigating these problems is the objective of this thesis and the studies it includes. During the first part of the thesis, we measured the battery consumption of MSs in different modes of operation in order to analyse how CB affects the amount of current drained. The tests showed that battery consumption increased only slightly when CB messages were being received at the MS. Although some of the results can be, and are, discussed, we believe that CB would have a small effect on the power consumption of an MS, particularly in a context where it would be used for emergency warning messages only. This mentioned, it would however be wishful to confirm the conclusions further through the realisation of long-term testing. The second part of the thesis deals with the investigation of the MSs’ support for CB messages with different coding schemes. Based on the investigation’s result, we have come to the conclusion that in the long term the usage of different coding schemes on the same channel is preferred. However, the usage of one, global, emergency channel is hard to realise since that requires a standardisation between all countries. In our opinion this may be achieved first in the long run and until then, the usage of separate channels seems to be necessary.</p>

During recent years there has been a great focus on the climate changes within the media. More or less every day more newspaper articles are presented about the global warming issue and the effect on us human race. Climate models predict higher temperatures and more rain in the northern part of Europe. It is also predicted that the weather will become more extreme e.g. it will rain a lot during longer periods than has been the norm. If these predictions are correct, the amount of water that is going to be transported away in streams and rivers will increase and so also will the subsoil water level. The latter increases the risk for landslides in areas with fine grained soils. An early warning system that is able to alert people before a landslide take place would be of great interest. The purpose of this work is to develop a complete real-time displacement monitoring system based on observations from several GPS-receivers that could be used as an early warning system. Due to the complex correlation structure of the traditionally used double differences, an alternative method based on undifferenced observations is used. Theoretically this approach shows some advantages and simplifies the correlative structure of observables compared to the double differenced method. A complete model for the undifferenced approach is presented in this thesis including its software implementation. A displacement detection system includes not only the positioning algorithms, but also methods to detect if any displacement occurs. There are many methods available to discriminate displacements, which are used in the traditional control of manufacturing processes. Several of these methods are compared in this thesis, such as the Shewhart chart, different Weighted Moving Average (WMA) charts and the CUmulative SUMmation (CUSUM). Practical tests show that it is possible to detect an abrupt shift on sub centimetre level at the same epoch as the shift occurs. Smaller shifts are also detectable with the applied approach but with a slightly longer detection time. / QC 20100624

Thesis--School of Advanced Airpower Studies, Maxwell Air Force Base, Ala., 1992-93. / Title from title screen (viewed Oct. 28, 2003). "28 June 1993." Includes bibliographical references.

Cell Broadcast (CB) is a possible technical realisation of a global emergency alert system. It is a technique used for sending short text messages to all mobile stations (MSs) in a defined geographical area. An potential effect of using CB is the increase in battery consumption of the MS due to the fact that an extra channel has to be used to make the service available even when the network is otherwise congested. Another part of the service which leads to a potential problem is making CB messages available in different languages. Investigating these problems is the objective of this thesis and the studies it includes. During the first part of the thesis, we measured the battery consumption of MSs in different modes of operation in order to analyse how CB affects the amount of current drained. The tests showed that battery consumption increased only slightly when CB messages were being received at the MS. Although some of the results can be, and are, discussed, we believe that CB would have a small effect on the power consumption of an MS, particularly in a context where it would be used for emergency warning messages only. This mentioned, it would however be wishful to confirm the conclusions further through the realisation of long-term testing. The second part of the thesis deals with the investigation of the MSs’ support for CB messages with different coding schemes. Based on the investigation’s result, we have come to the conclusion that in the long term the usage of different coding schemes on the same channel is preferred. However, the usage of one, global, emergency channel is hard to realise since that requires a standardisation between all countries. In our opinion this may be achieved first in the long run and until then, the usage of separate channels seems to be necessary.

Traditional communication channels like news channels are not able to provide spontaneous information about disasters unlike social networks namely, Twitter. The present research work proposes a framework by mining real-time disaster data from Twitter to predict the path a disaster like a tornado will take. The users of Twitter act as the sensors which provide useful information about the disaster by posting first-hand experience, warnings or location of a disaster. The steps involved in the framework are – data collection, data preprocessing, geo-locating the tweets, data filtering and extrapolation of the disaster curve for prediction of susceptible locations. The framework is validated by analyzing the past events. This framework has the potential to be developed into a full-fledged system to predict and warn people about disasters. The warnings can be sent to news channels or broadcasted for pro-active action.

Laser assisted weapons, such as laser guided bombs, laser guided missiles and laser beam-riding missiles pose a significant threat to military assets in the modern battlefield. Laser beam-riding missiles are particularly hard to detect because they use low power lasers. Most laser warning systems produced so far can not detect laser beam-riding missiles because of their weak emissions which have signals less than 1% of laser range finder power . They are even harder to defeat because current counter-measures are not designed to work against this threat. The aim of this project is to examine the vulnerability of laser warning systems against guided weapons, to build an evaluation tool for laser warning sensors (LWS) and seekers, and try to find suitable counter-measures for laser beam-riding missiles that use low power lasers in their guidance systems. The project comes about because of the unexpected results obtained from extensive field trials carried out on various LWRs in the United Arab Emirates desert, where severe weather conditions may be experienced. The objective was to help find a solution for these systems to do their job in protecting the tanks and armoured vehicles crews from such a threat. In order to approach the subject, a computer model has been developed to enable the assessment of all phases of a laser warning receiver and missile seeker. MATLAB & SIMULINK software have been used to build the model. During this process experimentation and field trials have been carried out to verify the reliability of the model. This project will enable both the evaluation and design of any generic laser warning receiver or missile seeker and specific systems if various parameters are known. Moreover, this model will be used as a guide to the development of reliable countermeasures for laser beam-riding missiles.

Freqüentemente, a população das áreas metropolitanas é surpreendida pela ocorrência de inundações muito rápidas que causam danos diversos. O sistema de alerta antecipado contra inundações é uma ferramenta que visa minimizar tais impactos. O componente de previsão do sistema será abordado neste trabalho. Tal previsão é feita através de um modelo conceitual de previsão hidrometeorológica de precipitação baseado em equações termodinâmicas e modelo simplificado de física das nuvens seguido de um modelo chuva-vazão. A antecedência proporcionada pelo modelo hidrometeorológico aplicado é de 30 minutos para variáveis de entrada observadas. Este tempo pode ser estendido com a inclusão de estimativas futuras das variáveis de entrada. A calibração do modelo foi feita manualmente com o uso de duas medidas de desempenho, esta etapa pode ser aprimorada em pesquisas futuras. Apesar da simplicidade do modelo hidrometeorológico apresentou-se satisfatório em algumas simulações, conseguindo prever o início das precipitações. / Urban population are often surprised by flash floods which cause several kinds of damages. An early warning system is a tool which aims to minimize such impacts. This work will approach the forecast component of this system. A conceptual hydrometeorological precipitation forecasting model, based on thermodynamics equations and simplified cloud physics, will be used to perform the forecast. Model lead time is 30 minutes for measured inputs, this time can be extended by the use of estimated inputs instead of the measured ones. Calibration was performed manually based on conservation of precipitation volume and its distribution in time. This step can be improved on future researches. In spite of model’s simplicity, some simulations presented satisfactory results, being able to forecast precipitation’s beginning.