1,035 research outputs found

    A decision-making approach for the health-aware energy management of ship hybrid power plants

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    Although autonomous shipping has attracted increasing interest, its further develop-ment requires innovative solutions to operate autonomous ships without the direct in-tervention of human operators. This study aims to develop a health-aware energy management (HAEM) approach for ship hybrid power plants, integrating the health monitoring information from reliability tools with the energy management tools. This approach employs the equivalent consumption minimisation strategy (ECMS) along with a Dynamic Bayesian network (DBN), as well as the utopia decision-making meth-od and a model for the ship hybrid power plant. The HAEM approach is demonstrated for a parallel hybrid power plant of a pilot boat considering realistic operating profiles. The results demonstrate that by employing HAEM approach for the investigated ship power plant operating for 300 hours reduces its failure rate almost fourfold at the cost of fuel consumption increase of around 1.5 %, compared to the respective operation with the ECMS. This study is expected to contribute towards the development of su-pervisory control of autonomous power plants

    Use of emerging technologies to help measure fjordic biodiversity and blue carbon: mini-manned submarines and autonomous underwater vehicle swarms

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    Meaningful protection of global oceans lags far behind that of land and has taken little consideration of climate mitigation potential to date (such as through assessment of blue carbon stocks and change). With the new emphasis on synergistic approaches to the identification and conservation of both carbon- and species- rich habitats, we need much better knowledge of the geography and status of blue carbon habitats beyond coastal wetlands. In subpolar and polar regions, some blue carbon habitats are still emerging and work as negative (mitigating) feedback on climate change, yet remain unprotected despite strong evidence of threat overlap. Scientific research expeditions are gradually increasing our understanding, but appropriate vessels are a limiting factor due to high costs and carbon footprints. Even when available such vessels cannot access all areas (e.g., remote fjords with sills) and may struggle to measure certain aspects of habitats (e.g., steep or vertical surfaces). New technologies and opportunities have advanced to aid some of these problems, and here, two of them are considered, mini-manned submersibles and autonomous underwater vehicles. These two platforms have both become much more available and affordable (through novel partnerships) while also being much more scientifically capable. This technology has the potential to reduce the carbon footprint of science and particularly aid in assessing biology and environment status and change on steep sides, such as fjord walls

    Computing complexity measures of degenerate graphs

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    We show that the VC-dimension of a graph can be computed in time nlogd+1dO(d)n^{\log d+1} d^{O(d)}, where dd is the degeneracy of the input graph. The core idea of our algorithm is a data structure to efficiently query the number of vertices that see a specific subset of vertices inside of a (small) query set. The construction of this data structure takes time O(d2dn)O(d2^dn), afterwards queries can be computed efficiently using fast M\"obius inversion. This data structure turns out to be useful for a range of tasks, especially for finding bipartite patterns in degenerate graphs, and we outline an efficient algorithms for counting the number of times specific patterns occur in a graph. The largest factor in the running time of this algorithm is O(nc)O(n^c), where cc is a parameter of the pattern we call its left covering number. Concrete applications of this algorithm include counting the number of (non-induced) bicliques in linear time, the number of co-matchings in quadratic time, as well as a constant-factor approximation of the ladder index in linear time. Finally, we supplement our theoretical results with several implementations and run experiments on more than 200 real-world datasets -- the largest of which has 8 million edges -- where we obtain interesting insights into the VC-dimension of real-world networks.Comment: Accepted for publication in the 18th International Symposium on Parameterized and Exact Computation (IPEC 2023

    A Comprehensive Review of the GNSS with IoT Applications and Their Use Cases with Special Emphasis on Machine Learning and Deep Learning Models

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    This paper presents a comprehensive review of the Global Navigation Satellite System (GNSS) with Internet of Things (IoT) applications and their use cases with special emphasis on Machine learning (ML) and Deep Learning (DL) models. Various factors like the availability of a huge amount of GNSS data due to the increasing number of interconnected devices having low-cost data storage and low-power processing technologies - which is majorly due to the evolution of IoT - have accelerated the use of machine learning and deep learning based algorithms in the GNSS community. IoT and GNSS technology can track almost any item possible. Smart cities are being developed with the use of GNSS and IoT. This survey paper primarily reviews several machine learning and deep learning algorithms and solutions applied to various GNSS use cases that are especially helpful in providing accurate and seamless navigation solutions in urban areas. Multipath, signal outages with less satellite visibility, and lost communication links are major challenges that hinder the navigation process in crowded areas like cities and dense forests. The advantages and disadvantages of using machine learning techniques are also highlighted along with their potential applications with GNSS and IoT

    A framework for the economic-environmental feasibility assessment of short-sea shipping autonomous vessels

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    Despite the pursued autonomous ships initiatives, the lack of information on emerging technologies and their costs along with the limited investigations of the autonomy effects on logistics render these vessels feasibility assessment challenging. This study aims at developing an overarching framework to support decisions for the transition to autonomous shipping. The ship lifetime capital, operational and voyage expenditures are estimated to quantify the economic-environmental impact and required investments. Several scenarios are defined to address the input data uncertainty. The case of a short-sea shipping cargo vessel operating in the Norwegian waters is studied, considering its conversion to operate autonomously, as well as the next generation crewless ship design. The derived results demonstrate that the converted autonomous ships can reduce the lifetime present value by 1–12% and the carbon emissions by 4%, whereas the new autonomous design leads to their further reductions by 3–4% and 4–7%, respectively. These savings can further increase by 6–7% by reducing the autonomous ships sailing speed, as crew replacement periods are not required. The estimated economic margin indicates that the next-generation autonomous ships can adopt greener technologies, such as hydrogen or green ammonia, to achieve the targeted carbon emissions reduction

    Culture Enhancement for Exergames for Individuals with Intellectual Disability

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    Background: Individuals with intellectual disabilities (ID) often face barriers when trying to engage in physical activity. Exergames, which combine physical exercise with gaming technology, have shown the potential to promote physical activity among this group of individuals. However, the suitability of exergames for individuals with ID from different cultural backgrounds has received limited attention. Objective: This project is aimed to investigate cultural aspects of exergames for individuals with ID. The main goals were to explore how cultural factors affect engagement and experience, pinpoint culturally suitable design elements, cre- ate guidelines for cultural sensitivity, and look at the effects of culture-enhanced exergames. Methods: A mixed-methods approach was used. This was a literature review, interviews with individuals with ID from a different cultural background than Norway, expert consultations, and an iterative design process. Results: The research showed a few cultural factors affecting the engagement and experience of individuals with ID in exergames, such as language prefer- ences and, specifically to one exergame, local waste sorting regularities. The evaluation of culture-enhanced exergames gave positive impacts on the users’ physical activity levels and overall well-being. Conclusions: The project examines the impact of cultural variety in the design of exergames for individuals with ID. By addressing these factors, exergames can be made more engaging and accessible to more users in the world

    Polyphenols-Ensured Accessibility from Food to the Human Metabolism by Chemical and Biotechnological Treatments

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    Polyphenols are plant-based compounds famous for their positive impact on both human health and the quality of food products. The benefits of polyphenols are related to reducing cardiovascular diseases, cholesterol management, cancers, and neurological disorders in humans and increasing the shelf life, management of oxidation, and anti-microbial activity in food products. The bioavailability and bio-accessibility of polyphenols are of the highest importance to secure their impact on human and food health. This paper summarizes the current state-of-the-art approaches on how polyphenols can be made more accessible in food products to contribute to human health. For example, by using food processing methods including various technologies, such as chemical and biotechnological treatments. Food matrix design and simulation procedures, in combination with encapsulation of fractionated polyphenols utilizing enzymatic and fermentation methodology, may be the future technologies to tailor specific food products with the ability to ensure polyphenol release and availability in the most suitable parts of the human body (bowl, intestine, etc.). The development of such new procedures for utilizing polyphenols, combining novel methodologies with traditional food processing technologies, has the potential to contribute enormous benefits to the food industry and health sector, not only reducing food waste and food-borne illnesses but also to sustain human health

    The University Press phenomenon : new conditions and questions on the institutional publishing of research

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    This paper is, in part, an extrapolation from an internal research report that was commissioned to survey the new landscape of university-based publishing, aiming to define new development pathways for the longtime established University of Warwick Press. The report featured reference to other past internal reports and discussions on the same subject, and also reference to internal governance issues, which, added to interview and survey material, provides an overview of the current state of university publishing. Its purpose is to provide a basis for a specific research study on the future of university published journals

    Digital Twin in Naval Environment

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    A naval vessel is usually engaged in demanding operations that take place in a multifaceted environment. This requires a solid design of the ship as a platform and a prompt decision-making response. To support both the design and operation phases, digital tools and techniques have been widely implemented, along with a significant number of sensors and probes installed onboard. All of these features pave the way for the development of a Digital Twin model, which will be beneficial for the naval sector. In this work, relevant applications and a use case have been presented and discussed, with the goal of highlighting the added value and critical issues in the perspective of gathering them in a Digital Twin environment. The steps required to develop a shared reference digital architecture have been identified, as well as the gaps that need to be filled
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