IDENTIFICATION OF COVER SONGS USING INFORMATION THEORETIC MEASURES OF SIMILARITY

13 pages, 5 figures, 4 tables. v3: Accepted version13 pages, 5 figures, 4 tables. v3: Accepted version13 pages, 5 figures, 4 tables. v3: Accepted versio

Mining Heterogeneous Multivariate Time-Series for Learning Meaningful Patterns: Application to Home Health Telecare

For the last years, time-series mining has become a challenging issue for researchers. An important application lies in most monitoring purposes, which require analyzing large sets of time-series for learning usual patterns. Any deviation from this learned profile is then considered as an unexpected situation. Moreover, complex applications may involve the temporal study of several heterogeneous parameters. In that paper, we propose a method for mining heterogeneous multivariate time-series for learning meaningful patterns. The proposed approach allows for mixed time-series -- containing both pattern and non-pattern data -- such as for imprecise matches, outliers, stretching and global translating of patterns instances in time. We present the early results of our approach in the context of monitoring the health status of a person at home. The purpose is to build a behavioral profile of a person by analyzing the time variations of several quantitative or qualitative parameters recorded through a provision of sensors installed in the home

Light Curve Modulation of Low Mass Stars in K2. I. Identification of 508 Fast Rotators in the Solar Neighborhood

The K2 mission is targeting large numbers of nearby (d<100 pc) GKM dwarfs selected from the SUPERBLINK proper motion survey (mu>40 mas yr^-1, V<20). Additionally, the mission is targeting low-mass, high proper motion stars associated with the local (d<500 pc) Galactic halo population also selected from SUPERBLINK. K2 campaigns 0 through 8 monitored a total of 27,382 of these cool main-sequence stars. We used the auto-correlation function to search for fast rotators by identifying short-period photometric modulations in the K2 light curves. We identified 508 candidate fast rotators with rotation periods <4 days that show light curve modulations consistent with star spots. Their kinematics show low average transverse velocities, suggesting they are part of the young disk population. A subset (13) of the fast rotators are found among those targets with colors and kinematics consistent with the local Galactic halo population and may represent stars spun up by tidal interactions in close binary systems. We further demonstrate the M dwarf fast rotators selected from the K2 light curves are significantly more likely to have UV excess, and discuss the potential of the K2 mission to identify new nearby young GKM dwarfs on the basis of their fast rotation rates. Finally, we discuss the possible use of local halo stars as fiducial, non-variable sources in the Kepler fields.Comment: 14 pages, 14 figures, to appear in the Astronomical Journal (AJ

Measuring spike train synchrony

Estimating the degree of synchrony or reliability between two or more spike trains is a frequent task in both experimental and computational neuroscience. In recent years, many different methods have been proposed that typically compare the timing of spikes on a certain time scale to be fixed beforehand. Here, we propose the ISI-distance, a simple complementary approach that extracts information from the interspike intervals by evaluating the ratio of the instantaneous frequencies. The method is parameter free, time scale independent and easy to visualize as illustrated by an application to real neuronal spike trains obtained in vitro from rat slices. In a comparison with existing approaches on spike trains extracted from a simulated Hindemarsh-Rose network, the ISI-distance performs as well as the best time-scale-optimized measure based on spike timing.Comment: 11 pages, 13 figures; v2: minor modifications; v3: minor modifications, added link to webpage that includes the Matlab Source Code for the method (http://inls.ucsd.edu/~kreuz/Source-Code/Spike-Sync.html

HyperLEDA. III. The catalogue of extragalactic distances

We present the compilation catalogue of redshift-independent distances included in the HyperLEDA database. It is actively maintained to be up-to-date, and the current version counts 6640 distance measurements for 2335 galaxies compiled from 430 published articles. Each individual series is recalibrated onto a common distance scale based on a carefully selected set of high-quality measurements. This information together with data on HI line-width, central velocity dispersion, magnitudes, diameters, and redshift is used to derive a homogeneous distance estimate and physical properties of galaxies, such as their absolute magnitudes and intrinsic size.Comment: accepted to A&

Sequential Complexity as a Descriptor for Musical Similarity

We propose string compressibility as a descriptor of temporal structure in audio, for the purpose of determining musical similarity. Our descriptors are based on computing track-wise compression rates of quantised audio features, using multiple temporal resolutions and quantisation granularities. To verify that our descriptors capture musically relevant information, we incorporate our descriptors into similarity rating prediction and song year prediction tasks. We base our evaluation on a dataset of 15500 track excerpts of Western popular music, for which we obtain 7800 web-sourced pairwise similarity ratings. To assess the agreement among similarity ratings, we perform an evaluation under controlled conditions, obtaining a rank correlation of 0.33 between intersected sets of ratings. Combined with bag-of-features descriptors, we obtain performance gains of 31.1% and 10.9% for similarity rating prediction and song year prediction. For both tasks, analysis of selected descriptors reveals that representing features at multiple time scales benefits prediction accuracy.Comment: 13 pages, 9 figures, 8 tables. Accepted versio

Splitting hybrid Make-To-Order and Make-To-Stock demand profiles

In this paper a demand time series is analysed to support Make-To-Stock (MTS) and Make-To-Order (MTO) production decisions. Using a purely MTS production strategy based on the given demand can lead to unnecessarily high inventory levels thus it is necessary to identify likely MTO episodes. This research proposes a novel outlier detection algorithm based on special density measures. We divide the time series' histogram into three clusters. One with frequent-low volume covers MTS items whilst a second accounts for high volumes which is dedicated to MTO items. The third cluster resides between the previous two with its elements being assigned to either the MTO or MTS class. The algorithm can be applied to a variety of time series such as stationary and non-stationary ones. We use empirical data from manufacturing to study the extent of inventory savings. The percentage of MTO items is reflected in the inventory savings which were shown to be an average of 18.1%.Comment: demand analysis; time series; outlier detection; production strategy; Make-To-Order(MTO); Make-To-Stock(MTS); 15 pages, 9 figure

Single-vehicle data of highway traffic - a statistical analysis

In the present paper single-vehicle data of highway traffic are analyzed in great detail. By using the single-vehicle data directly empirical time-headway distributions and speed-distance relations can be established. Both quantities yield relevant information about the microscopic states. Several fundamental diagrams are also presented, which are based on time-averaged quantities and compared with earlier empirical investigations. In the remaining part time-series analyses of the averaged as well as the single-vehicle data are carried out. The results will be used in order to propose objective criteria for an identification of the different traffic states, e.g. synchronized traffic.Comment: 12 pages, 19 figures, RevTe