NCM: Neutrosophic c-means clustering algorithm

Mathematical Modelling and Computers in Endocrinology

We report on a search for fast radio bursts (FRBs) with the Green BankNorthern Celestial Cap (GBNCC) Pulsar Survey at 350 MHz. Pointingsamounting to a total on-sky time of 61 days were searched to adispersion measure (DM) of 3000 pc cm-3, while the rest(23 days; 29% of the total time) were searched to a DM of 500 pccm-3. No FRBs were detected in the pointings observedthrough 2016 May. We estimate a 95% confidence upper limit on the FRBrate of 3.6× {10}3 FRBs sky-1day-1 above a peak flux density of 0.63 Jy at 350 MHzfor an intrinsic pulse width of 5 ms. We place constraints on thespectral index α by running simulations for differentastrophysical scenarios and cumulative flux density distributions. Thenondetection with GBNCC is consistent with the 1.4 GHz rate reported forthe Parkes surveys for α > +0.35 in the absence of scatteringand free-free absorption and α > -0.3 in thepresence of scattering, for a Euclidean flux distribution. Theconstraints imply that FRBs exhibit either a flat spectrum or a spectralturnover at frequencies above 400 MHz. These constraints also allowestimation of the number of bursts that can be detected with current andupcoming surveys. We predict that CHIME may detect anywhere from severalto ˜50 FRBs per day (depending on model assumptions), making it wellsuited for interesting constraints on spectral index, the logN-log S slope, and pulse profile evolution across its bandwidth(400-800 MHz).

/pdf/a-search-for-fast-radio-bursts-with-the-gbncc-pulsar-survey-his1g128rt.pdf

A Search for Fast Radio Bursts with the GBNCC Pulsar Survey

https://deepblue.lib.umich.edu/bitstream/handle/2027.42/28250/0000703.pdf;sequence=1

The influence of atmospheric transport on precipitation chemistry at two sites in the midwestern United States

: This thesis addresses the problem of categorizing natural objects. To provide a criteria for categorization we propose that the purpose of a categorization is to support the inference of unobserved properties of objects from the observed properties. Because no such set of categories can be constructed in an arbitrary world, we present the Principle of Natural Modes as a claim about the structure of the world. We first define an evaluation function that measures how well a set of categories supports the inference goals of the observer. Entropy measures for property uncertainty and category uncertainty are combined through a free parameter that reflects the goals of the observer. Natural categorizations are shown to be those that are stable with respect to this free parameter. We next develop a categorization paradigm that utilizes the categorization evaluation function in recovering natural categories. A statistical hypothesis generation algorithm is presented that is shown to be an effective categorization procedure. Finally, a method is presented for evaluating the utility of features in recovering natural categories. This method also provides a mechanism for determining which features are constrained by the different processes present in a multiple modal world.

Herman Chernoff

Papers

Cluster Analysis for Applications (Michael R. Anderberg)