946 resultados para Search and rescue operations


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Planning, navigation, and search are fundamental human cognitive abilities central to spatial problem solving in search and rescue, law enforcement, and military operations. Despite a wealth of literature concerning naturalistic spatial problem solving in animals, literature on naturalistic spatial problem solving in humans is comparatively lacking and generally conducted by separate camps among which there is little crosstalk. Addressing this deficiency will allow us to predict spatial decision making in operational environments, and understand the factors leading to those decisions. The present dissertation is comprised of two related efforts, (1) a set of empirical research studies intended to identify characteristics of planning, execution, and memory in naturalistic spatial problem solving tasks, and (2) a computational modeling effort to develop a model of naturalistic spatial problem solving. The results of the behavioral studies indicate that problem space hierarchical representations are linear in shape, and that human solutions are produced according to multiple optimization criteria. The Mixed Criteria Model presented in this dissertation accounts for global and local human performance in a traditional and naturalistic Traveling Salesman Problem. The results of the empirical and modeling efforts hold implications for basic and applied science in domains such as problem solving, operations research, human-computer interaction, and artificial intelligence.

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OBJECTIVE: We sought to study the epidemiologic and medical aspects of alpine helicopter rescue operations involving the winching of an emergency physician to the victim. METHODS: We retrospectively reviewed the medical and operational reports of a single helicopter-based emergency medical service. Data from 1 January 2003 to 31 December 2008 were analysed. RESULTS: A total of 921 patients were identified, with a male:female ratio of 2:1. There were 56 (6%) patients aged 15 or under. The median time from emergency call to helicopter take-off was 7 min (IQR = 5-10 min). 840 (91%) patients suffered from trauma-related injuries, with falls from heights during sports activities the most frequent event. The most common injuries involved the legs (246 or 27%), head (175 or 19%), upper limbs (117 or 13%), spine (108 or 12%), and femur (66 or 7%). Only 81 (9%) victims suffered from a medical emergency, but these cases were, when compared to the trauma victims, significantly more severe according to the NACA index (p<0.001). Overall, 246 (27%) patients had a severe injury or illness, namely, a potential or overt vital threat (NACA score between 4 and 6). A total of 478 (52%) patients required administration of major analgesics: fentanyl (443 patients or 48%), ketamine (42 patients or 5%) or morphine (7 patients or 1%). The mean dose of fentanyl was 188 micrograms (range 25-750, SD 127). Major medical interventions such as administration of vasoactive drugs, intravenous perfusions of more than 1000 ml of fluids, ventilation or intubation were performed on 39 (4%) patients. CONCLUSIONS: The severity of the patients' injuries or illnesses along with the high proportion of medical procedures performed directly on-site validates emergency physician winching for advanced life support procedures and analgesia.

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We have generated transgenic mice that harbor a 140 kb genomic fragment of the human BRCA1 locus (TgN.BRCA1(GEN)). We find that the transgene directs appropriate expression of human BRCA1 transcripts in multiple mouse tissues, and that human BRCA1 protein is expressed and stabilized following exposure to DIVA damage, Such mice are completely normal, with no overt signs of BRCA1 toxicity commonly observed when BRCA1 is expressed from heterologous promoters. Most importantly, however, the transgene rescues the otherwise lethal phenotype associated with the targeted hypomorphic allele (Brca1(Delta exIISA)). Brca1(-/-); TgN.BRCA1(GEN) bigenic animals develop normally and can be maintained as a distinct line. These results show that a 140 kb fragment of chromosome 17 contains all elements necessary for the correct expression, localization, and function of the BRCA1 protein, Further, the model provides evidence that function and regulation of the human BRCA1 gene can be studied and manipulated in a genetically tractable mammalian system.

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This paper discusses a document discovery tool based on Conceptual Clustering by Formal Concept Analysis. The program allows users to navigate e-mail using a visual lattice metaphor rather than a tree. It implements a virtual. le structure over e-mail where files and entire directories can appear in multiple positions. The content and shape of the lattice formed by the conceptual ontology can assist in e-mail discovery. The system described provides more flexibility in retrieving stored e-mails than what is normally available in e-mail clients. The paper discusses how conceptual ontologies can leverage traditional document retrieval systems and aid knowledge discovery in document collections.

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Solving systems of nonlinear equations is a very important task since the problems emerge mostly through the mathematical modelling of real problems that arise naturally in many branches of engineering and in the physical sciences. The problem can be naturally reformulated as a global optimization problem. In this paper, we show that a self-adaptive combination of a metaheuristic with a classical local search method is able to converge to some difficult problems that are not solved by Newton-type methods.

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The non-technical loss is not a problem with trivial solution or regional character and its minimization represents the guarantee of investments in product quality and maintenance of power systems, introduced by a competitive environment after the period of privatization in the national scene. In this paper, we show how to improve the training phase of a neural network-based classifier using a recently proposed meta-heuristic technique called Charged System Search, which is based on the interactions between electrically charged particles. The experiments were carried out in the context of non-technical loss in power distribution systems in a dataset obtained from a Brazilian electrical power company, and have demonstrated the robustness of the proposed technique against with several others natureinspired optimization techniques for training neural networks. Thus, it is possible to improve some applications on Smart Grids.

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In this paper we present a set of field tests for detection of human in the water with an unmanned surface vehicle using infrared and color cameras. These experiments aimed to contribute in the development of victim target tracking and obstacle avoidance for unmanned surface vehicles operating in marine search and rescue missions. This research is integrated in the work conducted in the European FP7 research project Icarus aiming to develop robotic tools for large scale rescue operations. The tests consisted in the use of the ROAZ unmanned surface vehicle equipped with a precision GPS system for localization and both visible spectrum and IR cameras to detect the target. In the experimental setup, the test human target was deployed in the water wearing a life vest and a diver suit (thus having lower temperature signature in the body except hands and head) and was equipped with a GPS logger. Multiple target approaches were performed in order to test the system with different sun incidence relative angles. The experimental setup, detection method and preliminary results from the field trials performed in the summer of 2013 in Sesimbra, Portugal and in La Spezia, Italy are also presented in this work.

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Oceans - San Diego, 2013

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This work presents a low cost RTK-GPS system for localization of unmanned surface vehicles. The system is based on the use of standard low cost L1 band receivers and in the RTKlib open source software library. Mission scenarios with multiple robotic vehicles are addressed as the ones envisioned in the ICARUS search and rescue case where the possibility of having a moving RTK base on a large USV and multiple smaller vehicles acting as rovers in a local communication network allows for local relative localization with high quality. The approach is validated in operational conditions with results presented for moving base scenario. The system was implemented in the SWIFT USV with the ROAZ autonomous surface vehicle acting as a moving base. This setup allows for the performing of a missions in a wider range of environments and applications such as precise 3D environment modeling in contained areas and multiple robot operations.

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Os sistemas autónomos trazem como mais valia aos cenários de busca e salvamento a possibilidade de minimizar a presença de Humanos em situações de perigo e a capacidade de aceder a locais de difícil acesso. Na dissertação propõe-se endereçar novos métodos para perceção e navegação de veículos aéreos não tripulados (UAV), tendo como foco principal o planeamento de trajetórias e deteção de obstáculos. No que respeita à perceção foi desenvolvido um método para gerar clusters tendo por base os voxels gerados pelo Octomap. Na área de navegação, foram desenvolvidos dois novos métodos de planeamento de trajetórias, GPRM (Grid Probabilistic Roadmap) e PPRM (Particle Probabilistic Roadmap), que tem como método base para o seu desenvolvimento o PRM. O primeiro método desenvolvido, GPRM, espalha as partículas numa grid pré-definida, construindo posteriormente o roadmap na área determinada pela grid e com isto estima o trajeto mais curto até ao ponto destino. O segundo método desenvolvido, PPRM, espalha as partículas pelo cenário de aplicação, gera o roadmap considerando o mapa total e atribui uma probabilidade que irá permitir definir a trajetória otimizada. Para analisar a performance de cada método em comparação com o PRM, efetua-se a sua avaliação em três cenários distintos com recurso ao simulador MORSE.

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We study pair-wise decentralized trade in dynamic markets with homogeneous, non-atomic, buyers and sellers that wish to exchange one unit. Pairs of traders are randomly matched and bargaining a price under rules that offer the freedom to quit the match at any time. Market equilbria, prices and trades over time, are characterized. The asymptotic behavior of prices and trades as frictions (search costs and impatience) vanish, and the conditions for (non) convergence to walrasian prices are explored. As a side product of independent interest, we present a self-contained theory of non-cooperative bargaining with two-sided, time-varying, outside options.

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This paper evaluates the effects of policy interventions on sectoral labour markets and the aggregate economy in a business cycle model with search and matching frictions. We extend the canonical model by including capital-skill complementarity in production, labour markets with skilled and unskilled workers and on-the-job-learning (OJL) within and across skill types. We first find that, the model does a good job at matching the cyclical properties of sectoral employment and the wage-skill premium. We next find that vacancy subsidies for skilled and unskilled jobs lead to output multipliers which are greater than unity with OJL and less than unity without OJL. In contrast, the positive output effects from cutting skilled and unskilled income taxes are close to zero. Finally, we find that the sectoral and aggregate effects of vacancy subsidies do not depend on whether they are financed via public debt or distorting taxes.

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Northern Ireland's Fire and Rescue Service - Consultation

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Classical treatments of problems of sequential mate choice assume that the distribution of the quality of potential mates is known a priori. This assumption, made for analytical purposes, may seem unrealistic, opposing empirical data as well as evolutionary arguments. Using stochastic dynamic programming, we develop a model that includes the possibility for searching individuals to learn about the distribution and in particular to update mean and variance during the search. In a constant environment, a priori knowledge of the parameter values brings strong benefits in both time needed to make a decision and average value of mate obtained. Knowing the variance yields more benefits than knowing the mean, and benefits increase with variance. However, the costs of learning become progressively lower as more time is available for choice. When parameter values differ between demes and/or searching periods, a strategy relying on fixed a priori information might lead to erroneous decisions, which confers advantages on the learning strategy. However, time for choice plays an important role as well: if a decision must be made rapidly, a fixed strategy may do better even when the fixed image does not coincide with the local parameter values. These results help in delineating the ecological-behavior context in which learning strategies may spread.