Messen mentaler Auslastung in einer VR-Umgebung basierend auf Eyetrackingdaten

Hainke C, Pfeiffer T. Messen mentaler Auslastung in einer VR-Umgebung basierend auf Eyetrackingdaten. In: Dörner R, Kruse R, Mohler B, Weller R, eds. Virtuelle und Erweiterte Realität - 14. Workshop der GI-Fachgruppe VR/AR. Berichte aus der Informatik. Aachen: Shaker Verlag; 2017: 43-54.Ein aufmerksamer Assistent liefert proaktiv relevante Informationen immer genau zum richtigen Zeitpunkt. Er muss dafür über den aktuellen Handlungskontext und das erforderliche Domänenwissen verfügen und in der Lage sein, die aktuelle kognitive Situation des Nutzers gut einschätzen zu können. Die vorliegende Arbeit untersucht unter Einsatz eines Head-Mounted-Displays (HMDs) mit integriertem Eyetracker, ob die kognitive Belastung über die Echtzeitanalyse der Pupillengröße verlässlich geschätzt werden kann. Es wird gezeigt, dass es in einer VR-Umgebung möglich ist, mit diesen Mitteln die Pupillengröße mit der kognitiven Belastung in Zusammenhang zu setzen, da sie sich bei erhöhter Belastung vergrößert. Ausgenutzt wird dabei, dass die Helligkeit der Umgebung primär durch den Inhalt auf dem HMD-Display bestimmt wird und sich diese damit zur Laufzeit leicht bestimmen lässt

Stellar and substellar initial mass function: a model that implements gravoturbulent fragmentation and accretion

In this work, we derive the stellar initial mass function (IMF) from the superposition of mass distributions of dense cores, generated through gravoturbulent fragmentation of unstable clumps in molecular clouds (MCs) and growing through competitive accretion. MCs are formed by the turbulent cascade in the interstellar medium at scales L from 100 down to ~0.1 pc. Their internal turbulence is essentially supersonic and creates clumps with a lognormal distribution of densities n. Our model is based on the assumption of a power-law relationship between clump mass and clump density: n~m^x, where x is a scale-free parameter. Gravitationally unstable clumps are assumed to undergo isothermal fragmentation and produce protostellar cores with a lognormal mass distribution, centred around the clump Jeans mass. Masses of individual cores are then assumed to grow further through competitive accretion until the rest of the gas within the clump is being exhausted. The observed IMF is best reproduced for a choice of x=0.25, for a characteristic star formation timescale of ~5 Myr, and for a low star formation efficiency of ~10 %.Comment: 11 pages, 7 figures; accepted for publication in MNRA

Coulomb dissociation of N 20,21

Neutron-rich light nuclei and their reactions play an important role in the creation of chemical elements. Here, data from a Coulomb dissociation experiment on N20,21 are reported. Relativistic N20,21 ions impinged on a lead target and the Coulomb dissociation cross section was determined in a kinematically complete experiment. Using the detailed balance theorem, the N19(n,γ)N20 and N20(n,γ)N21 excitation functions and thermonuclear reaction rates have been determined. The N19(n,γ)N20 rate is up to a factor of 5 higher at

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Combination of terrestrial Laser Scanning with high resolution panoramic Images for Investigations in Forest Applications and tree species recognition

The management and planning of forests presumes the availability of up-to-date informaion on their current state. The relevant parameters like tree species, diameter of the bowl in defined heights an positions are usually represented by a forest inventory. In order to allow the collection of these inventory parameters, an approach aiming on the integration of a terrestrial laser scanner and a high resolution panoramic camera has been developed. The integration of these sensors provides geometric information from distance measurement and high resolution radiometric information from the panoramic images. In order to enable a combined evaluation, in the first processing step a soregistration of both data sets is required. Afterwards geometric quantities like position an diameter of trees can be derived from the LIDAR data, where as texture parameters as derived from the high resolution panoramic imagery can be applied for tree species recogition

Image analysis of self-organized multicellular patterns : multicellular pattern formation on compliant elastomer surfaces as model system

Analysis of multicellular patterns is required to understand tissue organizational processes. By using a multi-scale object oriented image processing method, the spatial information of cells can be extracted automatically. Instead of manual segmentation or indirect measurements, such as general distribution of contrast or flow, the orientation and distribution of individual cells is extracted for quantitative analysis. Relevant objects are identified by feature queries and no low-level knowledge of image processing is required

Resource Efficiency of Hardware Extensions of a 4-issue VLIW Processor for Elliptic Curve Cryptography

Jungeblut T, Puttmann C, Dreesen R, et al. Resource Efficiency of Hardware Extensions of a 4-issue VLIW Processor for Elliptic Curve Cryptography. Advances in Radio Science. 2010;8:295-305.The secure transmission of data plays a significant role in todays information era. Especially in the area of public-key-cryptography methods, which are based on elliptic curves (ECC), gain more and more importance. Compared to asymmetric algorithms, like RSA, ECC can be used with shorter key lengths, while achieving an equal level of security. The performance of ECC-algorithms can be increased significantly by adding application specific hardware extensions. Due to their fine grained parallelism, VLIW-processors are well suited for the execution of ECC algorithms. In this work, we extended the fourfold parallel CoreVA-VLIW-architecture by several hardware accelerators to increase the resource efficiency of the overall system. For the designspace exploration we use a dual design flow, which is based on the automatic generation of a complete C-compiler based tool chain from a central processor specification. Using the hardware accelerators the performance of the scalar multiplication on binary fields can be increased by the factor of 29. The energy consumption can be reduced by up to 90%. The extended processor hardware was mapped on a current 65 nm low-power standard-cell-technology. The chip area of the CoreVA-VLIW-architecture is 0.24mm2 at a power consumption of 29 mW/MHz. The performance gain is analyzed in respect to the increased hardware costs, as chip area or power consumption

Detecting lamellipodia in epithelial cell clusters using a fully convolutional neural network for phase contrast microscopy images

We present an approach for segmenting individual cells and lamellipodia in epithelial cell clusters using fully convolutional neural networks. The method will set the basis for measuring cell cluster dynamics and expansion to improve the investigation of collective cell migration phenomena. The fully learning-based front-end avoids classical feature engineering, yet the network architecture needs to be designed carefully. Our network predicts how likely each pixel belongs to one of the classes and, thus, is able to segment the image. Besides characterizing segmentation performance, we discuss how the network will be further employed