66 resultados para Missions, Danish.

em Queensland University of Technology - ePrints Archive


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Background Birth weight and length have seasonal fluctuations. Previous analyses of birth weight by latitude effects identified seemingly contradictory results, showing both 6 and 12 monthly periodicities in weight. The aims of this paper are twofold: (a) to explore seasonal patterns in a large, Danish Medical Birth Register, and (b) to explore models based on seasonal exposures and a non-linear exposure-risk relationship. Methods Birth weight and birth lengths on over 1.5 million Danish singleton, live births were examined for seasonality. We modelled seasonal patterns based on linear, U- and J-shaped exposure-risk relationships. We then added an extra layer of complexity by modelling weighted population-based exposure patterns. Results The Danish data showed clear seasonal fluctuations for both birth weight and birth length. A bimodal model best fits the data, however the amplitude of the 6 and 12 month peaks changed over time. In the modelling exercises, U- and J-shaped exposure-risk relationships generate time series with both 6 and 12 month periodicities. Changing the weightings of the population exposure risks result in unexpected properties. A J-shaped exposure-risk relationship with a diminishing population exposure over time fitted the observed seasonal pattern in the Danish birth weight data. Conclusion In keeping with many other studies, Danish birth anthropometric data show complex and shifting seasonal patterns. We speculate that annual periodicities with non-linear exposure-risk models may underlie these findings. Understanding the nature of seasonal fluctuations can help generate candidate exposures.

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An onboard payload may be seen in most instances as the “Raison d’Etre” for a UAV. It will define its capabilities, usability and hence market value. Large and medium UAV payloads exhibit significant differences in size and computing capability when compared with small UAVs. The latter have stringent size, weight, and power requirements, typically referred as SWaP, while the former still exhibit endless appetite for compute capability. The tendency for this type of UAVs (Global Hawk, Hunter, Fire Scout, etc.) is to increase payload density and hence processing capability. An example of this approach is the Northrop Grumman MQ-8 Fire Scout helicopter, which has a modular payload architecture that incorporates off-the-shelf components. Regardless of the UAV size and capabilities, advances in miniaturization of electronics are enabling the replacement of multiprocessing, power-hungry general-purpose processors for more integrated and compact electronics (e.g., FPGAs). Payloads play a significant role in the quality of ISR (intelligent, surveillance, and reconnaissance) data, and also in how quick that information can be delivered to the end user. At a high level, payloads are important enablers of greater mission autonomy, which is the ultimate aim in every UAV. This section describes common payload sensors and introduces two examples cases in which onboard payloads were used to solve real-world problems. A collision avoidance payload based on electro optical (EO) sensors is first introduced, followed by a remote sensing application for power line inspection and vegetation management.

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In this paper, the recent results of the space project IMPERA are presented. The goal of IMPERA is the development of a multirobot planning and plan execution architecture with a focus on a lunar sample collection scenario in an unknown environment. We describe the implementation and verification of different modules that are integrated into a distributed system architecture. The modules include a mission planning approach for a multirobot system and modules for task and skill execution within a lunar use-case scenario. The skills needed for the test scenario include cooperative exploration and mapping strategies for an unknown environment, the localization and classification of sample containers using a novel approach of semantic perception, and the skill of transporting sample containers to a collection point using a mobile manipulation robot. Additionally, we present our approach of a reliable communication framework that can deal with communication loss during the mission. Several modules are tested within several experiments in the domain of planning and plan execution, communication, coordinated exploration, perception, and object transportation. An overall system integration is tested on a mission scenario experiment using three robots.

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One of the new challenges in aeronautics is combining and accounting for multiple disciplines while considering uncertainties or variability in the design parameters or operating conditions. This paper describes a methodology for robust multidisciplinary design optimisation when there is uncertainty in the operating conditions. The methodology, which is based on canonical evolution algorithms, is enhanced by its coupling with an uncertainty analysis technique. The paper illustrates the use of this methodology on two practical test cases related to Unmanned Aerial Systems (UAS). These are the ideal candidates due to the multi-physics involved and the variability of missions to be performed. Results obtained from the optimisation show that the method is effective to find useful Pareto non-dominated solutions and demonstrate the use of robust design techniques.

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Principal Topic: In this study we investigate how strategic orientation moderates the impact of growth on profitability for a sample of Danish high growth (Gazelle) firms. ---------- Firm growth has been an essential part of both management research and entrepreneurship research for decades (e.g. Penrose 1959, Birch 1987, Storey 1994). From a societal point of view, firm growth has been perceived as economic generator and job creator. In entrepreneurship research, growth has been an important part of the field (Davidsson, Delmar and Wiklund 2006), and many have used growth as a measure of success. In strategic management, growth has been seen as an approach to achieve competitive advantages and a way of becoming increasing profitable (e.g. Russo and Fouts 1997, Cho and Pucic 2005). However, although firm growth used to be perceived as a natural pathway to profitability recently more skepticism has emerged due to both new theoretical development and new empirical insights. Empirically, studies show inconsistent and inconclusive empirical evidence regarding the impact of growth on profitability. Our review reveals that some studies find a substantial positive relationship, some find a weak positive relationship, some find no relationship and further some find a negative relationship. Overall, two dominant yet divergent theoretical positions can be identified. The first position, mainly focusing on the environmental fit, argues that firms are likely to become more profitable if they enter a market quickly and on a larger scale due to first mover advantages and economic of scale. The second position, mainly focusing the internal fit, argues that growth may lead to a range of internal challenges and difficulties, including rapid change in structure, reward systems, decision making, communication and management style. The inconsistent empirical results together with two divergent theoretical positions call for further investigations into the circumstances by which growth generate profitability and into the circumstances by which growth do not generate profitability. In this project, we investigate how strategic orientations influence the impact of growth on profitability by asking the following research question: How is the impact of growth on profitability moderated by strategic orientation? Based on a literature review of how growth impacts profitability in areas such as entrepreneurship, strategic management and strategic entrepreneurship we develop three hypotheses regarding the growth-profitability relationship and strategic orientation as a potential moderator. ---------- Methodology/Key Propositions: The three hypotheses are tested on data collected in 2008. All firms in Denmark, including all listed and non-listed (VAT-registered) firms who experienced a 100 % growth and had a positive sales or gross profit over a four years period (2004-2007) were surveyed. In total 2,475 fulfilled the requirements. Among those 1,107 firms returned usable questionnaires satisfactory giving us a response rate on 45 %. The financial data together with data on number of employees were obtained from D&B (previously Dun & Bradstreet). The remaining data were obtained through the survey. Hierarchical regression models with ROA (return on assets) as the dependent variable were used to test the hypotheses. In the first model control variables including region, industry, firm age, CEO age, CEO gender, CEO education and number of employees were entered. In the second model, growth measured as growth in employees was entered. Then strategic orientation (differentiation, cost leadership, focus differentiation and focus cost leadership) and then interaction effects of strategic orientation and growth were entered in the model. ---------- Results and Implications: The results show a positive impact of firm growth on profitability and further that this impact is moderated by strategic orientation. Specifically, it was found that growth has a larger impact on profitability when firms do not pursue a focus strategy including both focus differentiation and focus cost leadership. Our preliminary interpretation of the results suggests that the value of growth depends on the circumstances and more specifically 'how much is left to fight for'. It seems like those firms who target towards a narrow segment are less likely to gain value of growth. The remaining market shares to fight for to these firms are not large enough to compensate for the cost of growing. Based on our findings, it therefore seems like growth has a more positive relationship with profitability for those who approach a broad market segment. Furthermore we argue that firms pursuing af Focus strategy will have more specialized assets that decreases the possibilities of further profitable expansion. For firms, CEOs, board of directors etc., the study shows that high growth is not necessarily something worth aiming for. It is a trade-off between the cost of growing and the value of growing. For many firms, there might be better ways of generating profitability in the long run. It depends on the strategic orientation of the firm. For advisors and consultants, the conditional value of growth implies that in-depth knowledge on their clients' situation is necessary before any advice can be given. And finally, for policy makers, it means they have to be careful when initiating new policies to promote firm growth. They need to take into consideration firm strategy and industry conditions.

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In recent years, unmanned aerial vehicles (UAVs) have been widely used in combat, and their potential applications in civil and commercial roles are also receiving considerable attention by industry and the research community. There are numerous published reports of UAVs used in Earth science missions [1], fire-fighting [2], and border security [3] trials, with other speculative deployments, including applications in agriculture, communications, and traffic monitoring. However, none of these UAVs can demonstrate an equivalent level of safety to manned aircraft, particularly in the case of an engine failure, which would require an emergency or forced landing. This may be arguably the main factor that has prevented these UAV trials from becoming full-scale commercial operations, as well as restricted operations of civilian UAVs to only within segregated airspace.

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Recognizing the importance of good nutrition for physical and mental status, the Department of Defense asked the Institute of Medicine to guide the design of the nutritional composition of a ration for soldiers on short-term, high-stress missions. Nutrient Composition of Rations for Short-Term, High-Intensity Combat Operations considers military performance, health concerns, food intake, energy expenditure, physical exercise, and food technology issues. The success of military operations depends to a large extent on the physical and mental status of the individuals involved.

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Port land uses are subjected to unique anthropogenic activities compared to typical urban land uses. This uniqueness results in distinctive stormwater quality characteristics. Such distinction in stormwater quality has made conventional approaches used for pollutant load estimations inaccurate. This is also the case for the Port of Brisbane (PoB). The study discussed in the paper was conducted to estimate the pollutant contributions from Port specific land uses at PoB. For estimation, software modules embedded in Mike URBAN were used. An innovative approach was adopted in modelling where the conventional model calibration step was not needed to be performed to generate suitable site specific parameters. Instead, equations and site specific parameters that replicate pollutant build-up and wash-off were generated from an extensive field investigation. Models were simulated incorporating site specific parameters from six different Port specific land uses and rainfall events from three representative years. Outcomes of the modelling exercise were used to identify the distinct pollutant contributions from different Port land uses.

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Accurate estimation of input parameters is essential to ensure the accuracy and reliability of hydrologic and water quality modelling. Calibration is an approach to obtain accurate input parameters for comparing observed and simulated results. However, the calibration approach is limited as it is only applicable to catchments where monitoring data is available. Therefore, methodology to estimate appropriate model input parameters is critical, particularly for catchments where monitoring data is not available. In the research study discussed in the paper, pollutant build-up parameters derived from catchment field investigations and model calibration using MIKE URBAN are compared for three catchments in Southeast Queensland, Australia. Additionally, the sensitivity of MIKE URBAN input parameters was analysed. It was found that Reduction Factor is the most sensitive parameter for peak flow and total runoff volume estimation whilst Build-up rate is the most sensitive parameter for TSS load estimation. Consequently, these input parameters should be determined accurately in hydrologic and water quality simulations using MIKE URBAN. Furthermore, an empirical equation for Southeast Queensland, Australia for the conversion of build-up parameters derived from catchment field investigations as MIKE URBAN input build-up parameters was derived. This will provide guidance for allowing for regional variations in the estimation of input parameters for catchment modelling using MIKE URBAN where monitoring data is not available.

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This is the first in a series of four articles which will explore different aspects of air pollution, its impact on health and challenges in defining the boundaries between impact and nonimpact on health. Hardly a new topic one might say. Indeed, it’s been an issue for centuries, millennia even! For example, Pliny the Elder (AD 23-79), a Roman officer and author of the ‘Natural History’ recommended that: “…quarry slaves from asbestos mines not be purchased because they die young”, and suggested: “…the use of a respirator, made of transparent bladder skin, to protect workers from asbestos dust.” Closer to modern times, a Danish Proverb states: "Fresh air impoverishes the doctor". While none of these statements are an air quality guideline in a modern sense, they do illustrate that, for a very long time, we have known that there is a link between air quality and health, and that some measures were taken to reduce the impact of the exposure to the pollutants. Obviously, we are much more sophisticated now!

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Effective people management is essential to successful innovation, however no single human resource function or practice can facilitate the development of innovation capacity in an organization. Several studies have argued that different bundles or configurations of human resource practices can improve innovation performance, but there is little empirically based research that provides details of the practices utilized by different types of innovative firms. In this exploratory, qualitative study of innovative Danish firms we examine the profiles of human resource practices evident in a sample of firms recognized for their innovative performance. In examining these profiles, we analyze how characteristics of the organizations, namely their size and the nature of industry specific core capabilities, influence the human resource practices used to support innovation. Our initial findings indicate that in this sample of firms size is not a factor but knowledge-intensive firms have notably different profiles of human resource practices to technology-based firms.

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In recent years, ocean scientists have started to employ many new forms of technology as integral pieces in oceanographic data collection for the study and prediction of complex and dynamic ocean phenomena. One area of technological advancement in ocean sampling if the use of Autonomous Underwater Vehicles (AUVs) as mobile sensor plat- forms. Currently, most AUV deployments execute a lawnmower- type pattern or repeated transects for surveys and sampling missions. An advantage of these missions is that the regularity of the trajectory design generally makes it easier to extract the exact path of the vehicle via post-processing. However, if the deployment region for the pattern is poorly selected, the AUV can entirely miss collecting data during an event of specific interest. Here, we consider an innovative technology toolchain to assist in determining the deployment location and executed paths for AUVs to maximize scientific information gain about dynamically evolving ocean phenomena. In particular, we provide an assessment of computed paths based on ocean model predictions designed to put AUVs in the right place at the right time to gather data related to the understanding of algal and phytoplankton blooms.

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In this paper, we present a control strategy design technique for an autonomous underwater vehicle based on solutions to the motion planning problem derived from differential geometric methods. The motion planning problem is motivated by the practical application of surveying the hull of a ship for implications of harbor and port security. In recent years, engineers and researchers have been collaborating on automating ship hull inspections by employing autonomous vehicles. Despite the progresses made, human intervention is still necessary at this stage. To increase the functionality of these autonomous systems, we focus on developing model-based control strategies for the survey missions around challenging regions, such as the bulbous bow region of a ship. Recent advances in differential geometry have given rise to the field of geometric control theory. This has proven to be an effective framework for control strategy design for mechanical systems, and has recently been extended to applications for underwater vehicles. Advantages of geometric control theory include the exploitation of symmetries and nonlinearities inherent to the system. Here, we examine the posed inspection problem from a path planning viewpoint, applying recently developed techniques from the field of differential geometric control theory to design the control strategies that steer the vehicle along the prescribed path. Three potential scenarios for surveying a ship?s bulbous bow region are motivated for path planning applications. For each scenario, we compute the control strategy and implement it onto a test-bed vehicle. Experimental results are analyzed and compared with theoretical predictions.

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This dissertation is based on theoretical study and experiments which extend geometric control theory to practical applications within the field of ocean engineering. We present a method for path planning and control design for underwater vehicles by use of the architecture of differential geometry. In addition to the theoretical design of the trajectory and control strategy, we demonstrate the effectiveness of the method via the implementation onto a test-bed autonomous underwater vehicle. Bridging the gap between theory and application is the ultimate goal of control theory. Major developments have occurred recently in the field of geometric control which narrow this gap and which promote research linking theory and application. In particular, Riemannian and affine differential geometry have proven to be a very effective approach to the modeling of mechanical systems such as underwater vehicles. In this framework, the application of a kinematic reduction allows us to calculate control strategies for fully and under-actuated vehicles via kinematic decoupled motion planning. However, this method has not yet been extended to account for external forces such as dissipative viscous drag and buoyancy induced potentials acting on a submerged vehicle. To fully bridge the gap between theory and application, this dissertation addresses the extension of this geometric control design method to include such forces. We incorporate the hydrodynamic drag experienced by the vehicle by modifying the Levi-Civita affine connection and demonstrate a method for the compensation of potential forces experienced during a prescribed motion. We present the design method for multiple different missions and include experimental results which validate both the extension of the theory and the ability to implement control strategies designed through the use of geometric techniques. By use of the extension presented in this dissertation, the underwater vehicle application successfully demonstrates the applicability of geometric methods to design implementable motion planning solutions for complex mechanical systems having equal or fewer input forces than available degrees of freedom. Thus, we provide another tool with which to further increase the autonomy of underwater vehicles.