900 resultados para Early Warning System


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A new measure called “implicit rating” is introduced which might be a component of an early warning system. The proposed methodology relies on the aggregation of experts’ knowledge hidden in the transactional data of the interbank market of unsecured loans. Banks are simultaneously assessing the creditworthiness of each other which is reflected in the partner limits and in the interest rates. In the Hungarian interbank market the overall trading volume and the average interest rate did not show any negative trends before the crisis of 2008, however the average implicit partner limit started to decrease several months earlier, hence it might serve as a stress indicator.

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The extensive impact and consequences of the 2010 Deep Water Horizon oil drilling rig failure in the Gulf of Mexico, together with expanding drilling activities in the Cuban Exclusive Economic zone, have cast a spotlight on Cuban oil development. The threat of a drilling rig failure has evolved from being only hypothetical to a potential reality with the commencement of active drilling in Cuban waters. The disastrous consequences of a drilling rig failure in Cuban waters will spread over a number of vital interests of the US and of nations in the Caribbean in the general environs of Cuba. The US fishing and tourist industries will take major blows from a significant oil spill in Cuban waters. Substantial ecological damage and damage to beaches could occur for the US, Mexico, Haiti and other countries as well. The need exists for the US to have the ability to independently monitor the reality of Cuban oceanic oil development. The advantages of having an independent US early warning system providing essential real-time data on the possible failure of a drilling rig in Cuban waters are numerous. An ideal early warning system would timely inform the US that an event has occurred or is likely to occur in, essentially, real-time. Presently operating monitoring systems that could provide early warning information are satellite-based. Such systems can indicate the locations of both drilling rigs and operational drilling platforms. The system discussed/proposed in this paper relies upon low-frequency underwater sound. The proposed system can complement existing monitoring systems, which offer ocean-surface information, by providing sub-ocean surface, near-real time, information. This “integrated system” utilizes and combines (integrates) many different forms of information, some gathered through sub-ocean surface systems, and some through electromagnetic-based remote sensing (satellites, aircraft, unmanned arial vehicles), and other methods as well. Although the proposed integrated system is in the developmental stage, it is based upon well-established technologies.

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El objetivo del artículo es realizar un diagnóstico sobre la percepción de los factores que intervienen en el rendimiento académico de los estudiantes de cinco carreras universitarias en una escuela de educación superior en México, para así reconocer las áreas de oportunidad que permitan sugerir políticas y estrategias para elevar su rendimiento. Se utilizó una muestra de 1651 estudiantes, se obtuvieron los datos a partir de un cuestionario con treinta preguntas que estudian la percepción del rendimiento académico en escala tipo Likert. Se realizó un análisis factorial exploratorio que permitiera reducir los datos, facilitar la interpretación y validar el instrumento. Se identificaron tres factores: a) el rol de los profesores, b) la evaluación y c) la motivación de los estudiantes. Se llevó a cabo un análisis comparativo por carrera. Se encontró que los estudiantes perciben que la mayoría de los maestros no se preocupan por la condición de los jóvenes en situación de reprobación. Además, casi no motivan y carecen de expresiones de sentimientos de orgullo por los logros académicos de los estudiantes. La mitad de los participantes piensa que los docentes no cubren el temario en su totalidad. Se detectó que los estudiantes poseen una alta motivación siendo esto positivo porque son alumnos dedicados y responsables. Se concluye realizando una serie de sugerencias y explicando las implicaciones que tiene este trabajo para las instituciones de educación superior.

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The activity of Fuego volcano during the 1999 - 2013 eruptive episode is studied through field, remote sensing and observatory records. Mapping of the deposits allows quantifying the erupted volumes and areas affected by the largest eruptions during this period. A wide range of volcanic processes results in a diversity of products and associated deposits, including minor airfall tephra, rockfall avalanches, lava flows, and pyroclastic flows. The activity can be characterized by long term, low level background activity, and sporadic larger explosive eruptions. Although the background activity erupts lava and ash at a low rate (~ 0.1 m3/s), the persistence of such activity over time results in a significant contribution (~ 30%) to the eruption budget during the studied period. Larger eruptions produced the majority of the volume of products during the studied period, mainly during three large events (May 21, 1999, June 29, 2003, and September 13, 2012), mostly in the form of pyroclastic flows. A total volume of ~ 1.4 x 108 m3 was estimated from the mapped deposits and the estimated background eruption rate. Posterior remobilization of pyroclastic flow material by stream erosion in the highly confined Barranca channels leads to lahar generation, either by normal rainfall, or by extreme rainfall events. A reassessment of the types of products and volumes erupted during the decade of 1970's allows comparing the activity happening since 1999 with the older activity, and suggests that many of the eruptive phenomena at Fuego may have similar mechanisms, despite the differences in scale between. The deposits of large pyroclastic flows erupted during the 1970's are remarkably similar in appearance to the deposit of pyroclastic flows from the 1999 - 2013 period, despite their much larger volume; this is also the case for prehistoric eruptions. Radiocarbon dating of pyroclastic flow deposits suggests that Fuego has produced large eruptions many times during the last ~ 2 ka, including larger eruptions during the last 500 years, which has important hazard implications. A survey was conducted among the local residents living near to the volcano, about their expectations of possible future crises. The results show that people are aware of the risk they could face in case of a large eruption, and therefore they are willing to evacuate in such case. However, their decision to evacuate may also be influenced by the conditions in which the evacuation could take place. If the evacuation represents a potential loss of their livelihood or property they will be more hesitant to leave their villages during a large eruption. The prospect of facing hardship conditions during the evacuation and in the shelters may further cause reluctance to evacuate. A short discussion on some of the issues regarding risk assessment and management through an early warning system is presented in the last chapter.

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A Cooperative Collision Warning System (CCWS) is an active safety techno- logy for road vehicles that can potentially reduce traffic accidents. It provides a driver with situational awareness and early warnings of any possible colli- sions through an on-board unit. CCWS is still under active research, and one of the important technical problems is safety message dissemination. Safety messages are disseminated in a high-speed mobile environment using wireless communication technology such as Dedicated Short Range Communication (DSRC). The wireless communication in CCWS has a limited bandwidth and can become unreliable when used inefficiently, particularly given the dynamic nature of road traffic conditions. Unreliable communication may significantly reduce the performance of CCWS in preventing collisions. There are two types of safety messages: Routine Safety Messages (RSMs) and Event Safety Messages (ESMs). An RSM contains the up-to-date state of a vehicle, and it must be disseminated repeatedly to its neighbouring vehicles. An ESM is a warning message that must be sent to all the endangered vehi- cles. Existing RSM and ESM dissemination schemes are inefficient, unscalable, and unable to give priority to vehicles in the most danger. Thus, this study investigates more efficient and scalable RSM and ESM dissemination schemes that can make use of the context information generated from a particular traffic scenario. Therefore, this study tackles three technical research prob- lems, vehicular traffic scenario modelling and context information generation, context-aware RSM dissemination, and context-aware ESM dissemination. The most relevant context information in CCWS is the information about possible collisions among vehicles given a current vehicular traffic situation. To generate the context information, this study investigates techniques to model interactions among multiple vehicles based on their up-to-date motion state obtained via RSM. To date, there is no existing model that can represent interactions among multiple vehicles in a speciffic region and at a particular time. The major outcome from the first problem is a new interaction graph model that can be used to easily identify the endangered vehicles and their danger severity. By identifying the endangered vehicles, RSM and ESM dis- semination can be optimised while improving safety at the same time. The new model enables the development of context-aware RSM and ESM dissemination schemes. To disseminate RSM efficiently, this study investigates a context-aware dis- semination scheme that can optimise the RSM dissemination rate to improve safety in various vehicle densities. The major outcome from the second problem is a context-aware RSM dissemination protocol. The context-aware protocol can adaptively adjust the dissemination rate based on an estimated channel load and danger severity of vehicle interactions given by the interaction graph model. Unlike existing RSM dissemination schemes, the proposed adaptive scheme can reduce channel congestion and improve safety by prioritising ve- hicles that are most likely to crash with other vehicles. The proposed RSM protocol has been implemented and evaluated by simulation. The simulation results have shown that the proposed RSM protocol outperforms existing pro- tocols in terms of efficiency, scalability and safety. To disseminate ESM efficiently, this study investigates a context-aware ESM dissemination scheme that can reduce unnecessary transmissions and deliver ESMs to endangered vehicles as fast as possible. The major outcome from the third problem is a context-aware ESM dissemination protocol that uses a multicast routing strategy. Existing ESM protocols use broadcast rout- ing, which is not efficient because ESMs may be sent to a large number of ve- hicles in the area. Using multicast routing improves efficiency because ESMs are sent only to the endangered vehicles. The endangered vehicles can be identified using the interaction graph model. The proposed ESM protocol has been implemented and evaluated by simulation. The simulation results have shown that the proposed ESM protocol can prevent potential accidents from occurring better than existing ESM protocols. The context model and the RSM and ESM dissemination protocols can be implemented in any CCWS development to improve the communication and safety performance of CCWS. In effect, the outcomes contribute to the realisation of CCWS that will ultimately improve road safety and save lives.

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This paper presents an approach for identifying the limit states of resilience in a water supply system when influenced by different types of pressure (disturbing) forces. Understanding of systemic resilience facilitates identification of the trigger points for early managerial action to avoid further loss of ability to provide satisfactory service availability when the ability to supply water is under pressure. The approach proposed here is to illustrate the usefulness of a surrogate measure of resilience depicted in a three dimensional space encompassing independent pressure factors. That enables visualisation of the transition of the system-state (resilience) between high to low resilience regions and acts as an early warning trigger for decision-making. The necessity of a surrogate measure arises as a means of linking resilience to the identified pressures as resilience cannot be measured directly. The basis for identifying the resilience surrogate and exploring the interconnected relationships within the complete system, is derived from a meta-system model consisting of three nested sub-systems representing the water catchment and reservoir; treatment plant; and the distribution system and end-users. This approach can be used as a framework for assessing levels of resilience in different infrastructure systems by identifying a surrogate measure and its relationship to relevant pressures acting on the system.

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Many dynamical systems, including lakes, organisms, ocean circulation patterns, or financial markets, are now thought to have tipping points where critical transitions to a contrasting state can happen. Because critical transitions can occur unexpectedly and are difficult to manage, there is a need for methods that can be used to identify when a critical transition is approaching. Recent theory shows that we can identify the proximity of a system to a critical transition using a variety of so-called `early warning signals', and successful empirical examples suggest a potential for practical applicability. However, while the range of proposed methods for predicting critical transitions is rapidly expanding, opinions on their practical use differ widely, and there is no comparative study that tests the limitations of the different methods to identify approaching critical transitions using time-series data. Here, we summarize a range of currently available early warning methods and apply them to two simulated time series that are typical of systems undergoing a critical transition. In addition to a methodological guide, our work offers a practical toolbox that may be used in a wide range of fields to help detect early warning signals of critical transitions in time series data.

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The advent and evolution of geohazard warning systems is a very interesting study. The two broad fields that are immediately visible are that of geohazard evaluation and subsequent warning dissemination. Evidently, the latter field lacks any systematic study or standards. Arbitrarily organized and vague data and information on warning techniques create confusion and indecision. The purpose of this review is to try and systematize the available bulk of information on warning systems so that meaningful insights can be derived through decidable flowcharts, and a developmental process can be undertaken. Hence, the methods and technologies for numerous geohazard warning systems have been assessed by putting them into suitable categories for better understanding of possible ways to analyze their efficacy as well as shortcomings. By establishing a classification scheme based on extent, control, time period, and advancements in technology, the geohazard warning systems available in any literature could be comprehensively analyzed and evaluated. Although major advancements have taken place in geohazard warning systems in recent times, they have been lacking a complete purpose. Some systems just assess the hazard and wait for other means to communicate, and some are designed only for communication and wait for the hazard information to be provided, which usually is after the mishap. Primarily, systems are left at the mercy of administrators and service providers and are not in real time. An integrated hazard evaluation and warning dissemination system could solve this problem. Warning systems have also suffered from complexity of nature, requirement of expert-level monitoring, extensive and dedicated infrastructural setups, and so on. The user community, which would greatly appreciate having a convenient, fast, and generalized warning methodology, is surveyed in this review. The review concludes with the future scope of research in the field of hazard warning systems and some suggestions for developing an efficient mechanism toward the development of an automated integrated geohazard warning system. DOI: 10.1061/(ASCE)NH.1527-6996.0000078. (C) 2012 American Society of Civil Engineers.

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A study was conducted, in association with the Sapelo Island and North Carolina National Estuarine Research Reserves (NERRs), to evaluate the impacts of coastal development on sentinel habitats (e.g., tidal creek ecosystems), including potential impacts to human health and well-being. Uplands associated with southeastern tidal creeks and the salt marshes they drain are popular locations for building homes, resorts, and recreational facilities because of the high quality of life and mild climate associated with these environments. Tidal creeks form part of the estuarine ecosystem characterized by high biological productivity, great ecological value, complex environmental gradients, and numerous interconnected processes. This research combined a watershed-level study integrating ecological, public health and human dimension attributes with watershed-level land use data. The approach used for this research was based upon a comparative watershed and ecosystem approach that sampled tidal creek networks draining developed watersheds (e.g., suburban, urban, and industrial) as well as undeveloped sites. The primary objective of this work was to clearly define the relationships between coastal development with its concomitant land use changes and non-point source pollution loading and the ecological and human health and well-being status of tidal creek ecosystems. Nineteen tidal creek systems, located along the southeastern United States coast from southern North Carolina to southern Georgia, were sampled during summer (June-August), 2005 and 2006. Within each system, creeks were divided into two primary segments based upon tidal zoning: intertidal (i.e., shallow, narrow headwater sections) and subtidal (i.e., deeper and wider sections), and watersheds were delineated for each segment. In total, we report findings on 24 intertidal and 19 subtidal creeks. Indicators sampled throughout each creek included water quality (e.g., dissolved oxygen concentration, salinity, nutrients, chlorophyll-a levels), sediment quality (e.g., characteristics, contaminants levels including emerging contaminants), pathogen and viral indicators, and abundance and genetic responses of biological resources (e.g., macrobenthic and nektonic communities, shellfish tissue contaminants, oyster microarray responses). For many indicators, the intertidally-dominated or headwater portions of tidal creeks were found to respond differently than the subtidally-dominated or larger and deeper portions of tidal creeks. Study results indicate that the integrity and productivity of headwater tidal creeks were impaired by land use changes and associated non-point source pollution, suggesting these habitats are valuable early warning sentinels of ensuing ecological impacts and potential public health threats. For these headwater creeks, this research has assisted the validation of a previously developed conceptual model for the southeastern US region. This conceptual model identified adverse changes that generally occurred in the physical and chemical environment (e.g., water quality indicators such as indicator bacteria for sewage pollution or sediment chemical contamination) when impervious cover levels in the watershed reach 10-20%. Ecological characteristics responded and were generally impaired when impervious cover levels exceed 20-30%. Estimates of impervious cover levels defining where human uses are impaired are currently being determined, but it appears that shellfish bed closures and the flooding vulnerability of headwater regions become a concern when impervious cover values exceed 10-30%. This information can be used to forecast the impacts of changing land use patterns on tidal creek environmental quality as well as associated human health and well-being. In addition, this study applied tools and technologies that are adaptable, transferable, and repeatable among the high quality NERRS sites as comparable reference entities to other nearby developed coastal watersheds. The findings herein will be of value in addressing local, regional and national needs for understanding multiple stressor (anthropogenic and human impacts) effects upon estuarine ecosystems and response trends in ecosystem condition with changing coastal impacts (i.e., development, climate change). (PDF contaions 88 pages)

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Bridge structures are continuously subject to degradation due to the environment, ageing and excess loading. Periodic monitoring of bridges is therefore a key part of any maintenance strategy as it can give early warning if a bridge becomes unsafe. This article investigates an alternative method for the monitoring of bridge dynamic behaviour: a truck-trailer vehicle system, with accelerometers fitted to the axles of the trailer. The method aims to detect changes in the damping of a bridge, which may indicate the existence of damage. A simplified vehicle-bridge interaction model is used in theoretical simulations to assess the effectiveness of the method in detecting those changes. The influence of road profile roughness on the vehicle vibration is overcome by recording accelerations from both axles of a trailer and then analysing the spectra of the difference in the accelerations between the two axles. The effectiveness of the approach in detecting damage simulated as a loss in stiffness is also investigated. In addition, the sensitivity of the approach to the vehicle speed, road roughness class, bridge span length, changes in the equal axle properties and noise is investigated.

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The necessity and benefits for establishing the international Earth-system Prediction Initiative (EPI) are discussed by scientists associated with the World Meteorological Organization (WMO) World Weather Research Programme (WWRP), World Climate Research Programme (WCRP), International Geosphere–Biosphere Programme (IGBP), Global Climate Observing System (GCOS), and natural-hazards and socioeconomic communities. The proposed initiative will provide research and services to accelerate advances in weather, climate, and Earth system prediction and the use of this information by global societies. It will build upon the WMO, the Group on Earth Observations (GEO), the Global Earth Observation System of Systems (GEOSS) and the International Council for Science (ICSU) to coordinate the effort across the weather, climate, Earth system, natural-hazards, and socioeconomic disciplines. It will require (i) advanced high-performance computing facilities, supporting a worldwide network of research and operational modeling centers, and early warning systems; (ii) science, technology, and education projects to enhance knowledge, awareness, and utilization of weather, climate, environmental, and socioeconomic information; (iii) investments in maintaining existing and developing new observational capabilities; and (iv) infrastructure to transition achievements into operational products and services.

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A flood warning system incorporates telemetered rainfall and flow/water level data measured at various locations in the catchment area. Real-time accurate data collection is required for this use, and sensor networks improve the system capabilities. However, existing sensor nodes struggle to satisfy the hydrological requirements in terms of autonomy, sensor hardware compatibility, reliability and long-range communication. We describe the design and development of a real-time measurement system for flood monitoring, and its deployment in a flash-flood prone 650 km2 semiarid watershed in Southern Spain. A developed low-power and long-range communication device, so-called DatalogV1, provides automatic data gathering and reliable transmission. DatalogV1 incorporates self-monitoring for adapting measurement schedules for consumption management and to capture events of interest. Two tests are used to assess the success of the development. The results show an autonomous and robust monitoring system for long-term collection of water level data in many sparse locations during flood events.

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With the change of the water environment in accordance with climate change, the loss of lives and properties has increased due to urban flood. Although the importance of urban floods has been highlighted quickly, the construction of advancement technology of an urban drainage system combined with inland-river water and its relevant research has not been emphasized in Korea. In addition, without operation in consideration of combined inland-river water, it is difficult to prevent urban flooding effectively. This study, therefore, develops the uncertainty quantification technology of the risk-based water level and the assessment technology of a flood-risk region through a flooding analysis of the combination of inland-river. The study is also conducted to develop forecast technology of change in the water level of an urban region through the construction of very short-term/short-term flood forecast systems. This study is expected to be able to build an urban flood forecast system which makes it possible to support decision making for systematic disaster prevention which can cope actively with climate change.

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Developing scientifically credible tools for measuring the success of ecological restoration projects is a difficult and a non-trivial task. Yet, reliable measures of the general health and ecological integrity of ecosystems are critical for assessing the success of restoration programs. The South Florida Ecosystem Restoration Task Force (Task Force), which helps coordinate a multi-billion dollar multi-organizational effort between federal, state, local and tribal governments to restore the Florida Everglades, is using a small set of system-wide ecological indicators to assess the restoration efforts. A team of scientists and managers identified eleven ecological indicators from a field of several hundred through a selection process using 12 criteria to determine their applicability as part of a system-wide suite. The 12 criteria are: (1) is the indicator relevant to the ecosystem? (2) Does it respond to variability at a scale that makes it applicable to the entire system? (3) Is the indicator feasible to implement and is it measureable? (4) Is the indicator sensitive to system drivers and is it predictable? (5) Is the indicator interpretable in a common language? (6) Are there situations where an optimistic trend with regard to an indicator might suggest a pessimistic restoration trend? (7) Are there situations where a pessimistic trend with regard to an indicator may be unrelated to restoration activities? (8) Is the indicator scientifically defensible? (9) Can clear, measureable targets be established for the indicator to allow for assessments of success? (10) Does the indicator have specificity to be able to result in corrective action? (11) What level of ecosystem process or structure does the indicator address? (12) Does the indicator provide early warning signs of ecological change? In addition, a two page stoplight report card was developed to assist in communicating the complex science inherent in ecological indicators in a common language for resource managers, policy makers and the public. The report card employs a universally understood stoplight symbol that uses green to indicate that targets are being met, yellow to indicate that targets have not been met and corrective action may be needed and red to represent that targets are far from being met and corrective action is required. This paper presents the scientific process and the results of the development and selection of the criteria, the indicators and the stoplight report card format and content. The detailed process and results for the individual indicators are presented in companion papers in this special issue of Ecological Indicators.

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Uninhabited aerial vehicles (UAVs) are a cutting-edge technology that is at the forefront of aviation/aerospace research and development worldwide. Many consider their current military and defence applications as just a token of their enormous potential. Unlocking and fully exploiting this potential will see UAVs in a multitude of civilian applications and routinely operating alongside piloted aircraft. The key to realising the full potential of UAVs lies in addressing a host of regulatory, public relation, and technological challenges never encountered be- fore. Aircraft collision avoidance is considered to be one of the most important issues to be addressed, given its safety critical nature. The collision avoidance problem can be roughly organised into three areas: 1) Sense; 2) Detect; and 3) Avoid. Sensing is concerned with obtaining accurate and reliable information about other aircraft in the air; detection involves identifying potential collision threats based on available information; avoidance deals with the formulation and execution of appropriate manoeuvres to maintain safe separation. This thesis tackles the detection aspect of collision avoidance, via the development of a target detection algorithm that is capable of real-time operation onboard a UAV platform. One of the key challenges of the detection problem is the need to provide early warning. This translates to detecting potential threats whilst they are still far away, when their presence is likely to be obscured and hidden by noise. Another important consideration is the choice of sensors to capture target information, which has implications for the design and practical implementation of the detection algorithm. The main contributions of the thesis are: 1) the proposal of a dim target detection algorithm combining image morphology and hidden Markov model (HMM) filtering approaches; 2) the novel use of relative entropy rate (RER) concepts for HMM filter design; 3) the characterisation of algorithm detection performance based on simulated data as well as real in-flight target image data; and 4) the demonstration of the proposed algorithm's capacity for real-time target detection. We also consider the extension of HMM filtering techniques and the application of RER concepts for target heading angle estimation. In this thesis we propose a computer-vision based detection solution, due to the commercial-off-the-shelf (COTS) availability of camera hardware and the hardware's relatively low cost, power, and size requirements. The proposed target detection algorithm adopts a two-stage processing paradigm that begins with an image enhancement pre-processing stage followed by a track-before-detect (TBD) temporal processing stage that has been shown to be effective in dim target detection. We compare the performance of two candidate morphological filters for the image pre-processing stage, and propose a multiple hidden Markov model (MHMM) filter for the TBD temporal processing stage. The role of the morphological pre-processing stage is to exploit the spatial features of potential collision threats, while the MHMM filter serves to exploit the temporal characteristics or dynamics. The problem of optimising our proposed MHMM filter has been examined in detail. Our investigation has produced a novel design process for the MHMM filter that exploits information theory and entropy related concepts. The filter design process is posed as a mini-max optimisation problem based on a joint RER cost criterion. We provide proof that this joint RER cost criterion provides a bound on the conditional mean estimate (CME) performance of our MHMM filter, and this in turn establishes a strong theoretical basis connecting our filter design process to filter performance. Through this connection we can intelligently compare and optimise candidate filter models at the design stage, rather than having to resort to time consuming Monte Carlo simulations to gauge the relative performance of candidate designs. Moreover, the underlying entropy concepts are not constrained to any particular model type. This suggests that the RER concepts established here may be generalised to provide a useful design criterion for multiple model filtering approaches outside the class of HMM filters. In this thesis we also evaluate the performance of our proposed target detection algorithm under realistic operation conditions, and give consideration to the practical deployment of the detection algorithm onboard a UAV platform. Two fixed-wing UAVs were engaged to recreate various collision-course scenarios to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. Based on this collected data, our proposed detection approach was able to detect targets out to distances ranging from about 400m to 900m. These distances, (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning ahead of impact that approaches the 12.5 second response time recommended for human pilots. Furthermore, readily available graphic processing unit (GPU) based hardware is exploited for its parallel computing capabilities to demonstrate the practical feasibility of the proposed target detection algorithm. A prototype hardware-in- the-loop system has been found to be capable of achieving data processing rates sufficient for real-time operation. There is also scope for further improvement in performance through code optimisations. Overall, our proposed image-based target detection algorithm offers UAVs a cost-effective real-time target detection capability that is a step forward in ad- dressing the collision avoidance issue that is currently one of the most significant obstacles preventing widespread civilian applications of uninhabited aircraft. We also highlight that the algorithm development process has led to the discovery of a powerful multiple HMM filtering approach and a novel RER-based multiple filter design process. The utility of our multiple HMM filtering approach and RER concepts, however, extend beyond the target detection problem. This is demonstrated by our application of HMM filters and RER concepts to a heading angle estimation problem.