Mining structured Petri nets for the visualization of process behavior

Visualization is essential for understanding the models obtained by process mining. Clear and efficient visual representations make the embedded information more accessible and analyzable. This work presents a novel approach for generating process models with structural properties that induce visually friendly layouts. Rather than generating a single model that captures all behaviors, a set of Petri net models is delivered, each one covering a subset of traces of the log. The models are mined by extracting slices of labelled transition systems with specific properties from the complete state space produced by the process logs. In most cases, few Petri nets are sufficient to cover a significant part of the behavior produced by the log.Peer ReviewedPostprint (author's final draft

Data-driven design of intelligent wireless networks: an overview and tutorial

Data science or "data-driven research" is a research approach that uses real-life data to gain insight about the behavior of systems. It enables the analysis of small, simple as well as large and more complex systems in order to assess whether they function according to the intended design and as seen in simulation. Data science approaches have been successfully applied to analyze networked interactions in several research areas such as large-scale social networks, advanced business and healthcare processes. Wireless networks can exhibit unpredictable interactions between algorithms from multiple protocol layers, interactions between multiple devices, and hardware specific influences. These interactions can lead to a difference between real-world functioning and design time functioning. Data science methods can help to detect the actual behavior and possibly help to correct it. Data science is increasingly used in wireless research. To support data-driven research in wireless networks, this paper illustrates the step-by-step methodology that has to be applied to extract knowledge from raw data traces. To this end, the paper (i) clarifies when, why and how to use data science in wireless network research; (ii) provides a generic framework for applying data science in wireless networks; (iii) gives an overview of existing research papers that utilized data science approaches in wireless networks; (iv) illustrates the overall knowledge discovery process through an extensive example in which device types are identified based on their traffic patterns; (v) provides the reader the necessary datasets and scripts to go through the tutorial steps themselves

The Baryon Oscillation Spectroscopic Survey: Precision measurements of the absolute cosmic distance scale

BOSS, the Baryon Oscillation Spectroscopic Survey, is a 5-year program to measure the absolute cosmic distance scale and expansion rate with percent-level precision at redshifts z<0.7 and z~2.5. BOSS uses the "standard ruler" provided by baryon acoustic oscillations (BAO). BOSS will achieve a near optimal measurement of the BAO scale at z<0.7, with a redshift survey of 1.5 million luminous galaxies. It will pioneer a new method of BAO measurement at high redshift, using the LyA forest to 160,000 QSOs in the redshift range 2.1<z<3.0. The forecast measurement precision for angular diameter distance d_A is 1.0%, 1.0%, and 1.5% at z=0.35, 0.6, and 2.5, respectively, and the forecast precision for the Hubble parameter H(z) is 1.8%, 1.7%, and 1.2% at the same redshifts. These measurements will provide powerful constraints on the nature of dark energy and the curvature of space, complementing the constraints obtained from other probes. BOSS will also provide a superb data set for studying large- and small-scale clustering, the evolution of massive galaxies and the luminosity function and clustering of QSOs at 2.3 < z < 6.5. BOSS is one of four surveys that comprise SDSS-III (the Sloan Digital Sky Survey III), a 6-year program that will use highly multiplexed spectrographs on the 2.5-m Sloan Foundation Telescope to investigate cosmological parameters, the history and structure of the Milky Way galaxy, and the population of giant planet systems.Comment: Unpublished SDSS-III white paper for the US Decadal Survey. See http://www.sdss3.org for details of the international SDSS-III projec

Recording single-channel activity of inositol trisphosphate receptors in intact cells with a microscope, not a patch clamp.

Optical single-channel recording is a novel tool for the study of individual Ca2+-permeable channels within intact cells under minimally perturbed physiological conditions. As applied to the functioning and spatial organization of IP3Rs, this approach complements our existing knowledge, which derives largely from reduced systems - such as reconstitution into lipid bilayers and patch clamping of IP3Rs on the membrane of excised nuclei - where the spatial arrangement and interactions among IP3Rs via CICR are disrupted. The ability to image the activity of single IP3R channels with millisecond resolution together with localization of their positions with a precision of a few tens of nanometers both raises several intriguing questions and holds promise of answers. In particular, what mechanism underlies the anchoring of puffs and blips to static locations; why do these Ca2+ release events appear to involve only a very small fraction of the IP3Rs within a cell; and how can we reconcile the relative immotility of functional IP3Rs with numerous studies reporting free diffusion of IP3R protein in the ER membrane