Blazars are a type of Active Galactic Nucleus (AGN), characterized by the emission of a relativistic jet that points close to our line of sight. They are extremely powerful, variable emitters from radio to gamma-ray wavelengths. By cross-correlating light-curves from different energies, it is possible to determine the physical condition of the blazar emitting region, i.e. mechanism, morphology, distance from block hole to the actual emission, etc. In 2007, the 40m telescope at the Owens Valley Radio Observatory (OVRO) embarked on a new research campaign. In support of the Fermi Gamma-ray Space Telescope, the OVRO 40m telescope is monitoring more than 1800 blazars twice per week. In 2014, a new Ku-band spectropolarimeter receiver, KuPol, was installed on the 40m telescope with the aim of elucidating about potential spectral fluctuations that may arise during the flaring events. In this poster, we will present relevant information and preliminar results from KuPol and the actual status of its calibration, and also as well as the current state of the PSD analysis, where we are applying Fourier Transform to the signals.
Motivation: The Neurosky Mindwave device allows monitoring the electrical signals generated by the brains neural activities. The easy access of this devices opens a new area of researching fields not only in the gamification and disable people but also to understand the cognitive behavior of human beings. The purpose of this study is to investigate the consistency and effectiveness level of a non-invasive consumer product BCI. We investigate the output of the headset data both in quality and quantity of that gathered data and determine how it could be used for human involved research settings. A sample of two participants in terms of an interview and an interviewer interchanging questionnaires. The cognitive tasks and EEG output signals captured by the participants both attentive and meditation values.
Results: The data we collected produces mixed results. The meditation or relaxing level provide a consisting output while the attention level need more to explore due to the nature of every individuals and also the surrounds such as noise, mode distraction levels etc.
Keywords: BCI, Brain activity,EEG,NeuroSky, Attention, Meditation
Understanding dating behavior is intrinsically interesting and practically important for every individual in the society. People want to find someone who they want to share stories and emotions, understand and sympathize, commit the rest of life together. Accordingly, people spend a huge part of life finding "the one" or "soul-mate" who they believe potentially maximize their happiness and satisfaction in life. Ironically, they often end up breaking up and saying "He/She was not the right person". Researchers in many areas have studied dating behavior in varying ways to understand why people repeat the vicious circle and still get in there to find the right person. Here, we investigated dating behavior by analyzing relations between multi-aspect variables that include physical and psychological features of individuals and the probability of match in a speed-dating situation. We used theoretical approach and machine learning approach to investigate the pattern of dating behavior and to find the best predictor of match in dataing. For theory driven approach, we used multilevel linear model and multilevel logistic regression. For machine-learning approach, we used learning vector quantization and extreme gradient boosting.