Quasirandom Rumor Spreading: An Experimental Analysis

We empirically analyze two versions of the well-known "randomized rumor spreading" protocol to disseminate a piece of information in networks. In the classical model, in each round each informed node informs a random neighbor. In the recently proposed quasirandom variant, each node has a (cyclic) list of its neighbors. Once informed, it starts at a random position of the list, but from then on informs its neighbors in the order of the list. While for sparse random graphs a better performance of the quasirandom model could be proven, all other results show that, independent of the structure of the lists, the same asymptotic performance guarantees hold as for the classical model. In this work, we compare the two models experimentally. This not only shows that the quasirandom model generally is faster, but also that the runtime is more concentrated around the mean. This is surprising given that much fewer random bits are used in the quasirandom process. These advantages are also observed in a lossy communication model, where each transmission does not reach its target with a certain probability, and in an asynchronous model, where nodes send at random times drawn from an exponential distribution. We also show that typically the particular structure of the lists has little influence on the efficiency.Comment: 14 pages, appeared in ALENEX'0

Efficient Exchange of Metadata Information in Geo-Distributed Fog Systems

Metadata information is crucial for efficient geo-distributed fog computing systems. Many existing solutions for metadata exchange overlook geo-awareness or lack adequate failure tolerance, which are vital in such systems. To address this, we propose HFCS, a novel hybrid communication system that combines hierarchical and peer-to-peer elements, along with edge pools. HFCS utilizes a gossip protocol for dynamic metadata exchange. In simulation, we investigate the impact of node density and edge pool size on HFCS performance. We observe a significant performance improvement for clustered node distributions, aligning well with real-world scenarios. Additionally, we compare HFCS with a hierarchical system and a peer-to-peer broadcast approach. HFCS outperforms both in task fulfillment at the cost of an average 16\% detected failures due to its peer-to-peer structures

NIHAO XX: The impact of the star formation threshold on the cusp-core transformation of cold dark matter haloes

We use cosmological hydrodynamical galaxy formation simulations from the NIHAO project to investigate the impact of the threshold for star formation on the response of the dark matter (DM) halo to baryonic processes. The fiducial NIHAO threshold, $n=10\, {\rm cm}^{-3}$, results in strong expansion of the DM halo in galaxies with stellar masses in the range $10^{7.5} < M_{star} < 10^{9.5} M_{\odot}$. We find that lower thresholds such as $n=0.1$ (as employed by the EAGLE/APOSTLE and Illustris/AURIGA projects) do not result in significant halo expansion at any mass scale. Halo expansion driven by supernova feedback requires significant fluctuations in the local gas fraction on sub-dynamical times (i.e., < 50 Myr at galaxy half-light radii), which are themselves caused by variability in the star formation rate. At one per cent of the virial radius, simulations with $n=10$ have gas fractions of $\simeq 0.2$ and variations of $\simeq 0.1$, while $n=0.1$ simulations have order of magnitude lower gas fractions and hence do not expand the halo. The observed DM circular velocities of nearby dwarf galaxies are inconsistent with CDM simulations with $n=0.1$ and $n=1$, but in reasonable agreement with $n=10$. Star formation rates are more variable for higher $n$, lower galaxy masses, and when star formation is measured on shorter time scales. For example, simulations with $n=10$ have up to 0.4 dex higher scatter in specific star formation rates than simulations with $n=0.1$. Thus observationally constraining the sub-grid model for star formation, and hence the nature of DM, should be possible in the near future.Comment: 18 pages, 13 figures, accepted to MNRA

Voice recognition and processing interface for an interactive guide robot in an university scenario

This paper presents a voice user interface consisting of several modules for a mobile service robot, which is used to guide people and provide information on a university campus. The recognition and processing system is based on cloud services to convert from speech to text and vice versa and a dialogue system to allow for natural interaction. An approach to combine these modules with a data management system for meal plan, public transit, and location information is presented. We evaluate the system in different environments, each with their individual reverberation times, proving the functionality under conditions typical for the intended use case. In a user study with 13 participants we show the usability of the system, by letting the participants freely interact with the robot. In 86 % of all cases the desired output can be achieved at least once per user and request. A questionnare shows that most users agree with a good usability of the system

The edge of galaxy formation III: The effects of warm dark matter on Milky Way satellites and field dwarfs

In this third paper of the series, we investigate the effects of warm dark matter with a particle mass of $m_\mathrm{WDM}=3\,\mathrm{keV}$ on the smallest galaxies in our Universe. We present a sample of 21 hydrodynamical cosmological simulations of dwarf galaxies and 20 simulations of satellite-host galaxy interaction that we performed both in a Cold Dark Matter (CDM) and Warm Dark Matter (WDM) scenario. In the WDM simulations, we observe a higher critical mass for the onset of star formation. Structure growth is delayed in WDM, as a result WDM haloes have a stellar population on average two Gyrs younger than their CDM counterparts. Nevertheless, despite this delayed star formation, CDM and WDM galaxies are both able to reproduce the observed scaling relations for velocity dispersion, stellar mass, size, and metallicity at $z=0$. WDM satellite haloes in a Milky Way mass host are more susceptible to tidal stripping due to their lower concentrations, but their galaxies can even survive longer than the CDM counterparts if they live in a dark matter halo with a steeper central slope. In agreement with our previous CDM satellite study we observe a steepening of the WDM satellites' central dark matter density slope due to stripping. The difference in the average stellar age for satellite galaxies, between CDM and WDM, could be used in the future for disentangling these two models.Comment: 10 pages, 11 figures, accepted for publication on MNRA

Distraction Potential of Vehicle-Based On-Road Projection

With regard to autonomous driving, on-road projections cannot only be used for communication with the driver but also with other road users. Our study aims to investigate the distraction potential for other road users when on-road projections (e.g., for driver assistance) are used to communicate with the driver of the projecting vehicle. We perform this investigation in a blind study with 38 test persons who are overtaken six times on a constant motorway section by the projection vehicle. The distraction potential is examined with an eye-tracking system, which detects the direction of the subjects’ gaze. In addition, the subjects’ physiological perception of the headlight projection is recorded with a questionnaire afterward. Several test subjects looked at the projection for less than one second, which is well below the critical threshold for the distraction of 1.6 s. In the interviews, on the other hand, only one of the 38 test persons stated that a projection on the road was recognized. For the examined scenario, it is therefore deduced that on-road projections with the selected symbol shape and brightness do not lead to critical distraction

End-to-end Learning for Image-based Detection of Molecular Alterations in Digital Pathology

Current approaches for classification of whole slide images (WSI) in digital pathology predominantly utilize a two-stage learning pipeline. The first stage identifies areas of interest (e.g. tumor tissue), while the second stage processes cropped tiles from these areas in a supervised fashion. During inference, a large number of tiles are combined into a unified prediction for the entire slide. A major drawback of such approaches is the requirement for task-specific auxiliary labels which are not acquired in clinical routine. We propose a novel learning pipeline for WSI classification that is trainable end-to-end and does not require any auxiliary annotations. We apply our approach to predict molecular alterations for a number of different use-cases, including detection of microsatellite instability in colorectal tumors and prediction of specific mutations for colon, lung, and breast cancer cases from The Cancer Genome Atlas. Results reach AUC scores of up to 94% and are shown to be competitive with state of the art two-stage pipelines. We believe our approach can facilitate future research in digital pathology and contribute to solve a large range of problems around the prediction of cancer phenotypes, hopefully enabling personalized therapies for more patients in future.Comment: MICCAI 2022; 8.5 Pages, 4 Figure

Map Management Approach for SLAM in Large-Scale Indoor and Outdoor Areas

This work presents a semantic map management approach for various environments by triggering multiple maps with different simultaneous localization and mapping (SLAM) configurations. A modular map structure allows to add, modify or delete maps without influencing other maps of different areas. The hierarchy level of our algorithm is above the utilized SLAM method. Evaluating laser scan data (e.g. the detection of passing a doorway) triggers a new map, automatically choosing the appropriate SLAM configuration from a manually predefined list. Single independent maps are connected by link-points, which are located in an overlapping zone of both maps, enabling global navigation over several maps. Loop- closures between maps are detected by an appearance-based method, using feature matching and iterative closest point (ICP) registration between point clouds. Based on the arrangement of maps and link-points, a topological graph is extracted for navigation purpose and tracking the global robot's position over several maps. Our approach is evaluated by mapping a university campus with multiple indoor and outdoor areas and abstracting a metrical-topological graph. It is compared to a single map running with different SLAM configurations. Our approach enhances the overall map quality compared to the single map approaches by automatically choosing predefined SLAM configurations for different environmental setups

Report of Collection of Fish Eggs and Larvae in Coron, Palawan, from January to December 2019

This report is under the SEAFDEC/UNEP/GEF Project on “Establishment and Operation of a Regional System of Fisheries Refugia in the South China Sea and Gulf of Thailand”Collection of Fish Eggs and Larvae in Coron, Palawan, from January to December 2019UNEP/GE