4,259 research outputs found

    Intensity Noise Optimization of a Mid-Infrared Frequency Comb Difference Frequency Generation Source

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    We experimentally demonstrate in a difference-frequency generation mid-infrared frequency comb source the effect of temporal overlap between pump- and signal- pulse to the relative intensity noise (RIN) of the idler pulse. When scanning the temporal delay between our 130 fs long signal- and pump pulses, we observe a RIN minimum with a 3 dB width of 20 fs delay and an RIN increase of 20 dB in 40 fs delay at the edges of this minimum. We also demonstrate active long-term stabilization of the mid-infrared frequency comb source to the temporal overlap setting corresponding to the lowest RIN operation point by an on-line RIN-detector and active feedback control of the pump-signal- pulse delay. This active stabilization set-up allowed us to dramatically increase the signal-to-noise ratio of mid-infrared absorption spectra

    Identifying Risk Patterns in Brazilian Police Reports Preceding Femicides: A Long Short Term Memory (LSTM) Based Analysis

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    Femicide refers to the killing of a female victim, often perpetrated by an intimate partner or family member, and is also associated with gender-based violence. Studies have shown that there is a pattern of escalating violence leading up to these killings, highlighting the potential for prevention if the level of danger to the victim can be assessed. Machine learning offers a promising approach to address this challenge by predicting risk levels based on textual descriptions of the violence. In this study, we employed the Long Short Term Memory (LSTM) technique to identify patterns of behavior in Brazilian police reports preceding femicides. Our first objective was to classify the content of these reports as indicating either a lower or higher risk of the victim being murdered, achieving an accuracy of 66%. In the second approach, we developed a model to predict the next action a victim might experience within a sequence of patterned events. Both approaches contribute to the understanding and assessment of the risks associated with domestic violence, providing authorities with valuable insights to protect women and prevent situations from escalating.Comment: IEEE Global Humanitarian Technology Conference (GHTC) 202

    Small MAD families whose Isbell-Mr\'owka spaces are pseudocompact

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    Given a countable transitive model MM for ZFC+CH, we prove that one can produce a maximal almost disjoint family in MM whose Vietoris Hyperspace of its Isbell-Mr\'owka space is pseudocompact on every Cohen extension of MM. We also show that a classical example of ω1\omega_1-sized maximal almost disjoint family obtained by a forcing iteration of length ω1\omega_1 in a model of non CH is such that the Vietoris Hyperspace of its Isbell-Mr\'owka space is pseudocompact.Comment: 14

    Kantoswki-Sachs model with a running cosmological constant and radiation

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    The simplest anisotropic model of the early Universe is the one with two conformal factors, which can be identified as Kantowski-Sachs metric, or the reduced version of the Bianchi-I metric. To fit the existing observational data, it is important that the anisotropy is washed out in the early stage of the evolution. We explore the possible effect of the running cosmological constant (RCC) on the dynamics of isotropy, in the case of the space filled by radiation.Comment: The paper has 16 pages and 16 figure

    A Model-Predictive Motion Planner for the IARA Autonomous Car

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    We present the Model-Predictive Motion Planner (MPMP) of the Intelligent Autonomous Robotic Automobile (IARA). IARA is a fully autonomous car that uses a path planner to compute a path from its current position to the desired destination. Using this path, the current position, a goal in the path and a map, IARA's MPMP is able to compute smooth trajectories from its current position to the goal in less than 50 ms. MPMP computes the poses of these trajectories so that they follow the path closely and, at the same time, are at a safe distance of eventual obstacles. Our experiments have shown that MPMP is able to compute trajectories that precisely follow a path produced by a Human driver (distance of 0.15 m in average) while smoothly driving IARA at speeds of up to 32.4 km/h (9 m/s).Comment: This is a preprint. Accepted by 2017 IEEE International Conference on Robotics and Automation (ICRA
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