38 research outputs found

    LIPIcs, Volume 277, GIScience 2023, Complete Volume

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    LIPIcs, Volume 277, GIScience 2023, Complete Volum

    12th International Conference on Geographic Information Science: GIScience 2023, September 12–15, 2023, Leeds, UK

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    Advancing Urban Mobility with Algorithm Engineering

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    Design of robust slow-speed ships for sustainable operation

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    Phd ThesisMulti-objective optimisation that considers the energy efficiency and economic success is an important aspect of ship design and operation. Both the hydrodynamic and economic performance characteristics need to be addressed in the early stages of the design, and secured during the life span of a ship. Because of the conflicting nature of these two objectives, there are various trade-offs at stake in the goal for making ships more efficient and greener to comply with IMO regulations while reducing the building and operating costs and increasing the profitability at the same time for all stakeholders especially owners and operators. In attempt to reduce the amount of greenhouse gas emissions from ships, and hence to achieve a lower EEDI value, this research approaches the problem of improving the energy efficiency of ships. That is achieved by optimising the hull design over a speed range through parametric modification to reduce resistance and required power, and also through adopting slow steaming concept. Moreover, the research aims to determine the best practice to reduce the annual cost of running a ship and to increase the annual revenue as well as to make the ship a more profitable investment over her life span. The profit per tonne.mile and the net present value NPV are estimated in the economic analysis to be used as indicators to compare alternative designs for different routes and market conditions scenarios. To achieve this aim, the main operational and economic aspects such as the fluctuations in the fright rates and fuel prices in the shipping market are covered in the economic analysis. In addition, the acquiring price and salvage value are included in order to obtain solid comparisons. An optimisation framework using a VBA macro code has been developed based on the concept of Pareto optimality to assess decision making, and to determine robust designs as well as operational profiles based on results from the hydrodynamic model, environmental impact model, and the economic model. The optimisation process is carried out for a Panamax tanker case study using 5 parameters and a set of constraints for the hull parameters and speed. The outcome from the optimisation framework is a set of Pareto optimal solutions where weight factors are appointed to give the flexibility when addressing the importance of each individual function. The solutions are presented graphically to form what is known as Pareto front which determines the design space and the trade-offs between the different competing objective ii functions. This optimisation framework could assist decision making where it is possible to choose a robust design or designs that offer a near-optimum performance regardless any fluctuations in the market and or the operation profile, and eliminate any significant sub-optimal design

    Personality Identification from Social Media Using Deep Learning: A Review

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    Social media helps in sharing of ideas and information among people scattered around the world and thus helps in creating communities, groups, and virtual networks. Identification of personality is significant in many types of applications such as in detecting the mental state or character of a person, predicting job satisfaction, professional and personal relationship success, in recommendation systems. Personality is also an important factor to determine individual variation in thoughts, feelings, and conduct systems. According to the survey of Global social media research in 2018, approximately 3.196 billion social media users are in worldwide. The numbers are estimated to grow rapidly further with the use of mobile smart devices and advancement in technology. Support vector machine (SVM), Naive Bayes (NB), Multilayer perceptron neural network, and convolutional neural network (CNN) are some of the machine learning techniques used for personality identification in the literature review. This paper presents various studies conducted in identifying the personality of social media users with the help of machine learning approaches and the recent studies that targeted to predict the personality of online social media (OSM) users are reviewed
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