Choosing the optimal bandwidth in case of correlated data

In case of estimating growth curves nonparametrically onc faces the fact that the data driven bandwidth selectors published in standard textbooks mostly choose bandwidths much too low. This is due to the positive autocorrelation observed in growth data. This paper introduces an easy way to incorporate this effect in the known concept of penalizing functions. --

Learning Less is More - 6D Camera Localization via 3D Surface Regression

Popular research areas like autonomous driving and augmented reality have renewed the interest in image-based camera localization. In this work, we address the task of predicting the 6D camera pose from a single RGB image in a given 3D environment. With the advent of neural networks, previous works have either learned the entire camera localization process, or multiple components of a camera localization pipeline. Our key contribution is to demonstrate and explain that learning a single component of this pipeline is sufficient. This component is a fully convolutional neural network for densely regressing so-called scene coordinates, defining the correspondence between the input image and the 3D scene space. The neural network is prepended to a new end-to-end trainable pipeline. Our system is efficient, highly accurate, robust in training, and exhibits outstanding generalization capabilities. It exceeds state-of-the-art consistently on indoor and outdoor datasets. Interestingly, our approach surpasses existing techniques even without utilizing a 3D model of the scene during training, since the network is able to discover 3D scene geometry automatically, solely from single-view constraints.Comment: CVPR 201

Whisper: Fast Flooding for Low-Power Wireless Networks

This paper presents Whisper, a fast and reliable protocol to flood small amounts of data into a multi-hop network. Whisper relies on three main cornerstones. First, it embeds the message to be flooded into a signaling packet that is composed of multiple packlets. A packlet is a portion of the message payload that mimics the structure of an actual packet. A node must intercept only one of the packlets to know that there is an ongoing transmission. Second, Whisper exploits the structure of the signaling packet to reduce idle listening and, thus, to reduce the radio-on time of the nodes. Third, it relies on synchronous transmissions to quickly flood the signaling packet through the network. Our evaluation on the Flocklab testbed shows that Whisper achieves comparable reliability but significantly lower radio-on time than Glossy -- a state-of-the-art flooding algorithm. Specifically, Whisper can disseminate data in FlockLab twice as fast as Glossy with no loss in reliability. Further, Whisper spends 30% less time in channel sampling compared to Glossy when no data traffic must be disseminated

The directed flow maximum near c(s) = 0

We investigate the excitation function of quark-gluon plasma formation and of directed in-plane flow of nucleons in the energy range of the BNLAGS and for the Ekin Lab = 40A GeV Pb+Pb collisions performed recently at the CERN-SPS. We employ the three-fluid model with dynamical unification of kinetically equilibrated fluid elements. Within our model with first-order phase transition at high density, droplets of QGP coexisting with hadronic matter are produced already at BNL-AGS energies, Ekin Lab C 10A GeV. A substantial decrease of the isentropic velocity of sound, however, requires higher energies, Ekin Lab C 40A GeV. We show the e ect on the flow of nucleons in the reaction plane. According to our model calculations, kinematic requirements and EoS effects work hand-in-hand at Ekin Lab = 40A GeV to allow the observation of the dropping velocity of sound via an increase of the directed flow around midrapidity as compared to top BNL-AGS energy

Choosing the optimal bandwidth in case of correlated data

In case of estimating growth curves nonparametrically onc faces the fact that the data driven bandwidth selectors published in standard textbooks mostly choose bandwidths much too low. This is due to the positive autocorrelation observed in growth data. This paper introduces an easy way to incorporate this effect in the known concept of penalizing functions

Highly reliable, low-latency communication in low-power wireless networks

Low-power wireless networks consist of spatially distributed, resource-constrained devices – also referred to as nodes – that are typically equipped with integrated or external sensors and actuators. Nodes communicate with each other using wireless transceivers, and thus, relay data – e. g., collected sensor values or commands for actuators – cooperatively through the network. This way, low-power wireless networks can support a plethora of different applications, including, e. g., monitoring the air quality in urban areas or controlling the heating, ventilation and cooling of large buildings. The use of wireless communication in such monitoring and actuating applications allows for a higher flexibility and ease of deployment – and thus, overall lower costs – compared to wired solutions. However, wireless communication is notoriously error-prone. Message losses happen often and unpredictably, making it challenging to support applications requiring both high reliability and low latency. Highly reliable, low-latency communication – along with high energy-efficiency – are, however, key requirements to support several important application scenarios and most notably the open-/closed-loop control functions found in e. g., industry and factory automation applications. Communication protocols that rely on synchronous transmissions have been shown to be able to overcome this limitation. These protocols depart from traditional single-link transmissions and do not attempt to avoid concurrent transmissions from different nodes to prevent collisions. On the contrary, they make nodes send the same message at the same time over several paths. Phenomena like constructive interference and capture then ensure that messages are received correctly with high probability. While many approaches relying on synchronous transmissions have been presented in the literature, two important aspects received only little consideration: (i) reliable operation in harsh environments and (ii) support for event-based data traffic. This thesis addresses these two open challenges and proposes novel communication protocols to overcome them

Nichtparametrische Analyse parametrischer Wachstumsfunktionen: Eine Anwendung auf das Wachstum des globalen Netzwerks Internet

Besonders in der betriebswirtschaftlich relevanten Marktanalyse besteht ein großer Bedarf an möglichst einfachen Prognoseverfahren z. B. in Form von endogenen, d. h. alleine von der Zeit abhängigen, Wachstumsfunktionen. Der hier vorgestellte Test dient dazu, diejenigen Funktionen auszuwählen, welche den vorliegenden Sachverhalt hinreichend gut zu beschreiben vermögen. Dabei zeigt sich in einer empirischen Anwendung, daß dasWachstum des globalen Netzwerks Internet tatsächlich durch Exponential- bzw. logistische Funktionen zu beschreiben ist

Photothermal effects in ultra-precisely stabilized tunable microcavities

We study the mechanical stability of a tunable high-finesse microcavity under ambient conditions and investigate light-induced effects that can both suppress and excite mechanical fluctuations. As an enabling step, we demonstrate the ultra-precise electronic stabilization of a microcavity. We then show that photothermal mirror expansion can provide high-bandwidth feedback and improve cavity stability by almost two orders of magnitude. At high intracavity power, we observe self-oscillations of mechanical resonances of the cavity. We explain the observations by a dynamic photothermal instability, leading to parametric driving of mechanical motion. For an optimized combination of electronic and photothermal stabilization, we achieve a feedback bandwidth of $500\,$kHz and a noise level of $1.1 \times 10^{-13}\,$m rms

Heterogeneous biomedical database integration using a hybrid strategy: a p53 cancer research database.

Complex problems in life science research give rise to multidisciplinary collaboration, and hence, to the need for heterogeneous database integration. The tumor suppressor p53 is mutated in close to 50% of human cancers, and a small drug-like molecule with the ability to restore native function to cancerous p53 mutants is a long-held medical goal of cancer treatment. The Cancer Research DataBase (CRDB) was designed in support of a project to find such small molecules. As a cancer informatics project, the CRDB involved small molecule data, computational docking results, functional assays, and protein structure data. As an example of the hybrid strategy for data integration, it combined the mediation and data warehousing approaches. This paper uses the CRDB to illustrate the hybrid strategy as a viable approach to heterogeneous data integration in biomedicine, and provides a design method for those considering similar systems. More efficient data sharing implies increased productivity, and, hopefully, improved chances of success in cancer research. (Code and database schemas are freely downloadable, http://www.igb.uci.edu/research/research.html.)