357 research outputs found

    The Culling

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    The Culling is an animated, short film graduate thesis. It explores ideas of perception by examining an anthropomorphic tribal group of lobsters that live in the fish tank of a New England seafood restaurant. The story is told through the experiences of a new comer to this lobster tribe. It focuses on his reactions to the odd traditions and beliefs of his peers in this new and strange place. The film is a 2D animation that has been produced digitally using various video, audio and animation software. The goal of this paper is to outline the production of this thesis film from concept to completion, as well as provide some supplementary materials used in the creative process

    My Actions Speak Louder Than Your Words: When User Behavior Predicts Their Beliefs about Agents' Attributes

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    An implicit expectation of asking users to rate agents, such as an AI decision-aid, is that they will use only relevant information -- ask them about an agent's benevolence, and they should consider whether or not it was kind. Behavioral science, however, suggests that people sometimes use irrelevant information. We identify an instance of this phenomenon, where users who experience better outcomes in a human-agent interaction systematically rated the agent as having better abilities, being more benevolent, and exhibiting greater integrity in a post hoc assessment than users who experienced worse outcome -- which were the result of their own behavior -- with the same agent. Our analyses suggest the need for augmentation of models so that they account for such biased perceptions as well as mechanisms so that agents can detect and even actively work to correct this and similar biases of users.Comment: HCII 202

    Deep Reinforcement-Learning-based Driving Policy for Autonomous Road Vehicles

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    In this work the problem of path planning for an autonomous vehicle that moves on a freeway is considered. The most common approaches that are used to address this problem are based on optimal control methods, which make assumptions about the model of the environment and the system dynamics. On the contrary, this work proposes the development of a driving policy based on reinforcement learning. In this way, the proposed driving policy makes minimal or no assumptions about the environment, since a priori knowledge about the system dynamics is not required. Driving scenarios where the road is occupied both by autonomous and manual driving vehicles are considered. To the best of our knowledge, this is one of the first approaches that propose a reinforcement learning driving policy for mixed driving environments. The derived reinforcement learning policy, firstly, is compared against an optimal policy derived via dynamic programming, and, secondly, its efficiency is evaluated under realistic scenarios generated by the established SUMO microscopic traffic flow simulator. Finally, some initial results regarding the effect of autonomous vehicles' behavior on the overall traffic flow are presented.Comment: 19 pages. arXiv admin note: substantial text overlap with arXiv:1905.0904

    Bladder rapture as commonly misdiagnosed pathology - case report

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    The non-traumatic urine bladder rapture is a very rare life-threatening condition. The diagnosis of this pathology provides many difficulties as the signs and symptoms are not specific and the role of some diagnostic methods is insufficient. We describe the case of 77-year-old male patient admitted to the Emergency Department due to dyspnea, breathing difficulties, urinary difficulties and significantly distended abdomen. The patient had numerous cardiovascular diseases, moreover the interview disclosed recently diagnosed stage III prostate cancer. The laboratory tests results suggested an acute kidney failure. Due to severe condition patient was transferred to the Intensive Care Unit (ICU), where intravenous treatment with ceftriaxone and metronidazole was done for the first 2 days. Afterwards therapy was modified by introducing tienam and vancomycin. On the 4th day of hospitalization the sudden deterioration in the patient's condition occurred and the abdominal US revealed free fluid in peritoneal cavity, which was not visible in previous examinations. The CT-cystography revealed connection between the bladder and the retroperitoneal space in the right part of anterior wall. Despite the urgent laparotomy, the patient died due to multiple organ dysfunction syndrome in the course of neoplastic process as cause

    Evolucijski algoritam temeljen na off-line planeru putanje za navigaciju bespilotnih letjelica

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    An off-line path planner for Unmanned Air Vehicles is presented. The planner is based on Evolutionary Algorithms, in order to calculate a curved pathline with desired characteristics in a three-dimensional environment. The pathline is represented using B-Spline curves, with the coordinates of its control points being the genes of the Evolutionary Algorithm artificial chromosome. The method was tested in an artificial three-dimensional terrain, for different starting and ending points, providing very smooth pathlines under difficult constraints.Predstavljen je off-line planer putanje za bespilotne letjelice. Planer je temeljen na evolucijskim algoritmima za proračun zakrivljene putanje sa željenim karakteristikama u 3D prostoru. Putanja je predstavljena pomoću B-spline krivulja, gdje su koordinate kontrolnih točaka geni umjetnih kromosoma evolucijskih algoritama. Metoda je provjerena na umjetnom 3D prostoru s različitim početnim i konačnim točkama, gdje su dobivene vrlo glatke putanje uz zadovoljenje strogih ograničenja

    On Microscopic Modelling of Adaptive Cruise Control Systems

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    AbstractThe Adaptive Cruise Control (ACC) system, is one of the emerging vehicle technologies that has already been deployed in the market. Although it was designed mainly to enhance driver comfort and passengers’ safety, it also affects the dynamics of traffic flow. For this reason, a strong research interest in the field of modelling and simulation of ACC-equipped vehicles has been increasingly observed in the last years. In this work, previous modelling efforts reported in the literature are reviewed, and some critical aspects to be considered when designing or simulating such systems are discussed. Moreover, the integration of ACC-equipped vehicle simulation in the commercial traffic simulator Aimsun is described; this is subsequently used to run simulations for different penetration rates of ACC-equipped vehicles, different desired time-gap settings and different networks, to assess their impact on traffic flow characteristics

    Haar wavelet-based adaptive finite volume shallow water solver

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    This paper presents the formulation of an adaptive finite volume (FV) model for the shallow water equations. A Godunov-type reformulation combining the Haar wavelet is achieved to enable solutiondriven resolution adaptivity (both coarsening and refinement) by depending on the wavelet’s threshold value. The ability to properly model irregular topographies and wetting/drying are transferred from the (baseline) FV uniform mesh model, with no extra notable efforts. Selected hydraulic tests are employed to analyse the performance of the Haar wavelet FV shallow water solver considering adaptivity and practical issues including choice for the threshold value driving the adaptivity, mesh convergence study, shock and wet/dry front capturing abilities. Our findings show that Haar wavelet-based adaptive FV solutions offer great potential to improve the reliability of multiscale shallow water models
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