The fate of high redshift massive compact galaxies in dense environments

Massive compact galaxies seem to be more common at high redshift than in the local universe, especially in denser environments. To investigate the fate of such massive galaxies identified at z~2 we analyse the evolution of their properties in three cosmological hydrodynamical simulations that form virialised galaxy groups of mass ~10^13 Msun hosting a central massive elliptical/S0 galaxy by redshift zero. We find that at redshift ~2 the population of galaxies with M_*> 2 10^10 Msun is diverse in terms of mass, velocity dispersion, star formation and effective radius, containing both very compact and relatively extended objects. In each simulation all the compact satellite galaxies have merged into the central galaxy by redshift 0 (with the exception of one simulation where one of such satellite galaxy survives). Satellites of similar mass at z = 0 are all less compact than their high redshift counterparts. They form later than the galaxies in the z = 2 sample and enter the group potential at z < 1, when dynamical friction times are longer than the Hubble time. Also, by z = 0 the central galaxies have increased substantially their characteristic radius via a combination of in situ star formation and mergers. Hence in a group environment descendants of compact galaxies either evolve towards larger sizes or they disappear before the present time as a result of the environment in which they evolve. Since the group-sized halos that we consider are representative of dense environments in the LambdaCDM cosmology, we conclude that the majority of high redshift compact massive galaxies do not survive until today as a result of the environment.Comment: 10 pages, 4 figures, submitted to MNRA

Pitching for PIDs: European support for a sustainable PID infrastructure - Avoiding a PIDfall

The TechLib libraries (DTU Copenhagen, ETH Zurich, TIB Hannover and TU Delft) would like to start a community discussion around European support for sustainable PID infrastructures. Please take the time to read our pitch. We would very much appreciate your thoughts and ideas

Participatory privacy: Enabling privacy in participatory sensing

Abstract Participatory Sensing is an emerging computing paradigm that enables the distributed collection of data by self-selected participants. It allows the increasing number of mobile phone users to share local knowledge acquired by their sensor-equipped devices, e.g., to monitor temperature, pollution level or consumer pricing information. While research initiatives and prototypes proliferate, their real-world impact is often bounded to comprehensive user participation. If users have no incentive, or feel that their privacy might be endangered, it is likely that they will not participate. In this article, we focus on privacy protection in Participatory Sensing and introduce a suitable privacy-enhanced infrastructure. First, we provide a set of definitions of privacy requirements for both data producers (i.e., users providing sensed information) and consumers (i.e., applications accessing the data). Then, we propose an efficient solution designed for mobile phone users, which incurs very low overhead. Finally, we discuss a number of open problems and possible research directions

Efficient Mining of Frequent and Distinctive Feature Configurations

We present a novel approach to automatically find spatial configurations of local features occurring frequently on instances of a given object class, and rarely on the background. The approach is based on computationally efficient data mining techniques and can find frequent configurations among tens of thousands of candidates within seconds. Based on the mined configurations we develop a method to select features which have high probability of lying on previously unseen instances of the object class. The technique is meant as an intermediate processing layer to filter the large amount of clutter features returned by lowlevel feature extraction, and hence to facilitate the tasks of higher-level processing stages such as object detection. 1

Combining lanekeeping and vehicle following with hazard maps

Abstract This paper addresses the issues involved with including moving obstacles in a hazard map or potential field framework for driver assistance systems. Under such a framework, control forces must consist of either conservative forces obtained from the gradient of a potential or artificial damping. By treating vehicle following as a combination of a safety distance and a hazard or potential function, common following strategies, such as constant time headway and guaranteed collision avoidance, can be incorporated into this framework without modification. When combining these fields with lateral potential fields for lanekeeping, however, challenges arise due to the natural asymmetry between the longitudinal and lateral velocity of a vehicle. For instance, a decision to change lanes while approaching a slow moving vehicle results in a large amount of undesirable energy transfer into the lateral dynamics. By treating the lateral and longitudinal hazards -described in road-fixed coordinates -as decoupled, however, such transfers can be eliminated. Because of the manner in which the lateral and longitudinal dynamics couple, control with decoupled hazard maps resembles the coupled case when following or lanekeeping while eliminating the problems associated with energy transfer. The paper concludes by discussing the characteristics of the dynamic equations that lead to this result and outlining future work in obtaining rigorous hazard bounds for the decoupled controller

Coresets for Nonparametric Estimation -the Case of DP-Means

Abstract Scalable training of Bayesian nonparametric models is a notoriously difficult challenge. We explore the use of coresets -a data summarization technique originating from computational geometry -for this task. Coresets are weighted subsets of the data such that models trained on these coresets are provably competitive with models trained on the full dataset. Coresets sublinear in the dataset size allow for fast approximate inference with provable guarantees. Existing constructions, however, are limited to parametric problems. Using novel techniques in coreset construction we show the existence of coresets for DP-Means -a prototypical nonparametric clustering problem -and provide a practical construction algorithm. We empirically demonstrate that our algorithm allows us to efficiently trade off computation time and approximation error and thus scale DP-Means to large datasets. For instance, with coresets we can obtain a computational speedup of 45× at an approximation error of only 2.4% compared to solving on the full data set. In contrast, for the same subsample size, the &quot;naive&quot; approach of uniformly subsampling the data incurs an approximation error of 22.5%

Rhapsody. II. Subhalo Properties and the Impact of Tidal Stripping From a Statistical Sample of Cluster-Size Halos

We discuss the properties of subhalos in cluster-size halos, using a high-resolution statistical sample: the Rhapsody simulations introduced in Wu et al. (2012). We demonstrate that the criteria applied to select subhalos have significant impact on the inferred properties of the sample, including the scatter in the number of subhalos, the correlation between the subhalo number and formation time, and the shape of subhalos' spatial distribution and velocity structure. We find that the number of subhalos, when selected using the peak maximum circular velocity in their histories (a property expected to be closely related to the galaxy luminosity), is uncorrelated with the formation time of the main halo. This is in contrast to the previously reported correlation from studies where subhalos are selected by the current maximum circular velocity; we show that this difference is a result of the tidal stripping of the subhalos. We also find that the dominance of the main halo and the subhalo mass fraction are strongly correlated with halo concentration and formation history. These correlations are important to take into account when interpreting results from cluster samples selected with different criteria. Our sample also includes a fossil cluster, which is presented separately and placed in the context of the rest of the sample.Comment: 15 pages, 10 figures; Paper I: arXiv:1209.3309; replaced to match published versio

Wide-Area Power Oscillation Damping Control (POD) in Nordic Equivalent System

Abstract A study is presented on power oscillation damping control (POD) using wide area measurements applied to a single static var compensator (SVC). An equivalent power system model representing key characteristics of the Nordic power system is used. Feedback signals from remote phasor measurment units (PMUs) in Norway and Finland are used to damp the critical inter-area modes through a large SVC unit located in south-east Norway. A comparison between two control design approaches -(i) model based POD (MBPOD) -dependant on accurate system model and (ii) indirect adaptive POD (IAPOD) -which relies only on measurements -is made. For MBPOD an optimization approach is used to obtain the parameters of the controller while the IAPOD is based on online Kalman filter estimation and adaptive pole-shifting control. It is shown that the IAPOD yields almost similar performance as the MBPOD with very little prior information about the system. The performance comparison is verified for several tie-line outages