1,720,979 research outputs found
Adaptive autonomous underwater vehicles: an assessment of their effectiveness for oceanographic applications
Autonomous underwater vehicles (AUVs) are practical tools for ocean observation. However, they tend to operate in an automatic rather than autonomous way. This reflects the attitudes and behaviors that individuals and organizations share when adopting new technology in this industry. This paper clarifies the factors that are preventing one important aspect of autonomy&#x2014;adaptive mission planning (AMP)&#x2014;from transitioning from research to commercial and bespoke AUVs. A total of 25 experts comprising AUV developers and users, with combined 237 years of experience, provided their views in a structured survey covering several different hypotheses. There is insufficient evidence to determine clearly a single reason for failure to adopt AMPs, but a primary cause is the paucity of demonstration trials. This view is irrespective of participants' years of experience. Managers, engineers, and technologists agree on the two most likely causes for failure to adopt AMPs. However, the differences between the assessments provided by researchers and these three professional groups are statistically significant, with p value &lt;0.005. For researchers, complexity is one of the two most important inhibitory factors. We present recommendations to support the integration of AMP into AUVs substantiated by recent examples where government, industry, and researchers have developed and tested AMPs.</p
A copula-based method of risk prediction for autonomous underwater gliders in dynamic environments
Autonomous underwater gliders (AUGs) are effective platforms for oceanic research and environmental monitoring. However, complex underwater environments with uncertainties could pose the risk of vehicle loss during their missions. It is therefore essential to conduct risk prediction to assist decision making for safer operations. The main limitation of current studies for AUGs is the lack of a tailored method for risk analysis considering both dynamic environments and potential functional failures of the vehicle. Hence, this study proposed a copula-based approach for evaluating the risk of AUG loss in dynamic underwater environments. The developed copula Bayesian network (CBN) integrated copula functions into a traditional Bayesian belief network (BBN), aiming to handle nonlinear dependencies among environmental variables and inherent technical failures. Specifically, potential risk factors with causal effects were captured using the BBN. A Gaussian copula was then employed to measure correlated dependencies among identified risk factors. Furthermore, the dependence analysis and CBN inference were performed to assess the risk level of vehicle loss given various environmental observations. The effectiveness of the proposed method was demonstrated in a case study, which considered deploying a Slocum G1 Glider in a real water region. Risk mitigation measures were provided based on key findings. This study potentially contributes a tailored tool of risk prediction for AUGs in dynamic environments, which can enhance the safety performance of AUGs and assist in risk mitigation for decision makers.</p
Going Beyond Counting First Authors in Author Co-citation Analysis
The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
A Review of Risk Analysis Research for the Operations of Autonomous Underwater Vehicles
Risk analysis for autonomous underwater vehicles (AUVs) is essential to assist decision making for safer operations. This study aims to provide a systematic review of risk analysis research to enhance the safety performance of AUVs. Forty-two domain articles were retrieved and analyzed. Critical risk factors and causal relationships of AUV operations were identified. A comparative analysis of evolving methods and models was performed by categorizing them as qualitative, semi-quantitative, and quantitative. Future trends of research in this field were also outlined. The study observes that as AUV technologies gradually mature, environmental factors, human factors, and their interactive impacts are gathering more attention. Quantitative risk analysis methods have recently played a key role in improving the accuracy and handling the uncertainties of risk estimation. The study recommends devoting efforts to dynamic risk analysis, addressing limited historical data, intelligent risk analysis, and multi-vehicles risk analysis for future works. This study is expected to help AUV stakeholders gain comprehensive insights into fundamental concepts and evolving methods for risk analysis of AUVs. At the same time, it is expected to highlight future directions to bridge existing gaps.</p
Risk-based path planning for autonomous underwater vehicles in an oil spill environment
Autonomous underwater vehicles (AUVs) are advanced platforms for detecting and mapping oil spills in deep water. However, their applications in complex spill environments have been hindered by the risk of vehicle loss. Path planning for AUVs is an effective technique for mitigating such risks and ensuring safer routing. Yet previous studies did not address path searching problems for AUVs based on probabilistic risk reasoning. This study aims to propose an offboard risk-based path planning approach for AUVs operating in an oil spill environment. A risk model based on the Bayesian network was developed for probabilistic reasoning of risk states given varied environmental observations. This risk model further assisted in generating a spatially-distributed risk map covering a potential mission area. An A*-based searching algorithm was then employed to plan an optimal-risk path through the constructed risk map. The proposed planner was applied in a case study with a Slocum G1 Glider in a real-world spill environment around Baffin Bay. Simulation results proved that the optimal-risk planner outperforms in risk mitigation while achieving competitive path lengths and mission efficiency. The proposed method is not constrained to AUVs but can be adapted to other marine robotic systems
Variations on the Author
“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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