PUMA publications for /tag/journalTue Aug 20 11:34:50 CEST 2019International Journal of Heat and Mass Transfer1985--1993A benchmark test model for the validation of the CFD simulations to predict the distribution of gaseous emissions in the indoor environment552019afzal icvt journal merten Fri Aug 16 09:23:33 CEST 2019IEEE Journal of Selected Topics in Quantum Electronics1--6Ultra-Efficient Silicon-on-Insulator Grating Couplers with Backside Metal Mirrors2019Journal int myown pr-photonik-baustein Coupling of light from off-chip into highly complex silicon-based devices is currently focus of efforts and research. In this work, the experimental demonstration of a -0.50 dB (89{\%}) coupling efficiency in the C-band with the help of an aperiodic grating coupler design in a 250 nm silicon-on-insulator (SOI) technology is shown. Further, this work reports about the latest results regarding focusing grating couplers with footprints of only 30 µm x 30 µm and a measured coupling efficiency of up to 0.93~dB (81{\%}) at 1549 nm. Efficient grating coupler arrays are realized by using an expanded backside metal mirror-strip for the application of fiber arrays. In addition, this work presents aperiodic silicon grating couplers with an enhanced bandwidth to overcome the limited usability of grating couplers in wavelength division multiplexing (WDM) systems.Thu Aug 15 09:01:24 CEST 2019Fuzzy Sets and SystemsTheme: Uncertainty Management82 - 95Fuzzy linear least squares for the identification of possibilistic regression models3672019journal The stochastic approach to regression, e.g. the least-squares method, is a commonly used technique in a wide range of disciplines as it offers an intuitive and well-founded solution to the problem of fitting a set of parameters to existing data. Specifically, in the case where the parameters of meta models are identified, the linear least-squares formulation receives wide appreciation among engineers due to its simple yet powerful formulation and solution. Usually, this approach provides a reasonable fit, depending largely on the quality of the model that is employed. However, it has two main drawbacks. From a statistical point of view, the premises justifying its use cannot always be assumed in good faith, and most importantly, the resulting model will almost certainly fail at correctly predicting the output without falling victim to the effect of over-fitting. The presented fuzzy regression algorithm originates from a set of different axioms. For the solution of the linear least-squares problem, it is able to provide the worst-case optimal parameter variation necessary to cover all of the crisp data points while encoding meaningful information in the membership function. This is accomplished by means of a sensible fuzzification procedure of the crisp data points and the application of an exact inverse fuzzy arithmetic for estimating the fuzzy-valued parameters of the model in question.Thu Aug 15 09:00:51 CEST 2019{ASCE}-{ASME} J. Risk and Uncert. in Engrg. Sys., Part B: Mech. Engrg.junRobust Optimization in Possibility Theory2019journal Thu Aug 15 08:52:23 CEST 2019Mechanical Systems and Signal Processing106290Possibilistic calculus as a conservative counterpart to probabilistic calculus1332019journal This contribution is intended to promote possibility theory as a maturing general framework for the quantification of epistemic and aleatory uncertainties. For this purpose, we revisit Zadeh’s Extension Principle in the context of imprecise probabilities. Therein the aggregation of the possibility distributions is performed by the minimum-operator, corresponding to non-interactivity of the uncertain variables. Yet, this notion is not equivalent to well-established terms from probability theory such as stochastic independence. In order to use possibilistic calculus for propagating multivariate imprecise probabilities through models, we present suitable aggregation operations, corresponding to simple modifications of the Extension Principle, and we prove preservation of probability-possibility consistency, the fundamental concept in possibility theory. For the purpose of demonstration, the possibilistic solutions of two benchmark problems of uncertainty quantification are presented.Tue Jun 25 13:34:05 CEST 2019IEEE Electron Device LettersJune6850-853PrxCa1–xMnO3-Based Memory and Si Time-Keeping Selector for Area and Energy Efficient Synapse402019iht j.schulze.iht journal Spike time dependent plasticity (STDP) is a learning rule in biology, where the time-correlation of narrow pre- and post-synaptic spikes (tspike ≈5ms) is tracked across a wide learning window (LW) of time (tLW = ±80ms) by neurotransmitter dynamics at the synapse such that tLW:tspike> 20. In hardware, resistive random access memory (RRAM) (1M)-based synapse shows STDP by the superposition of long preand post-synaptic neural waveforms comparable to the timescale of the learning window. However, this artificially limits the spike rate and needs a complicated peripheral circuit to generate the waveform, which has an area penalty. In this letter, we propose a PrxCa1-xMnO3 (PCMO)-based RRAM (1M) with an impact-ionization (II)based silicon (Si) NIPIN (n-iv-δ p-i-n) selector (1S) diode as a synapse to operate with only short spikes. The NIPIN device transient response is utilized as a clock at the synapse to compute a preand post-spike time correlation, such that the 1M1S synapse requires short pulses instead of long waveforms. We experimentally demonstrate that very short (tspike ~ 80 ns) square pulses are required to generate STDP while the learning window is tLW ≈ ± 1.5 μs, which enables tLW:tspike ≈19. Furthermore, a hardware acceleration of 1000× over biology is shown. The square pulse scheme avoids complex waveforms and related complicated circuits. Thus, the synaptic time-keeping is demonstrated that enables biologically realistic SNN for future brain inspired computing.Mon May 20 10:41:10 CEST 2019International Journal of Microwave and Wireless Technologies1--8Towards a Flexible and Adaptive Wireless Hub by Embedding Power Amplifier Thinned Silicon Chip and Antenna in a Polymer Foil2019int journal pr-fflexcom Mon May 13 11:50:29 CEST 2019Concurrency and Computation: Practice and Experience18An autonomic-computing approach on mapping threads to multi-cores
for software transactional memory302018Wiley journal Wed Mar 06 15:31:13 CET 2019Journal of Fluid Mechanics97-140Viscous fingering phenomena in the early stage of polymer membrane formation8642019hopp icvt journal nieken Currently, the most important preparation process for porous polymer membranes is the phase inversion process. While applied for several decades in industry, the mechanism that leads to diverse morphology is not fully understood today. In this work, we present time resolved experiments using light microscopy that indicate viscous fingering during the early stage of pore formation in porous polymer membranes. Numerical simulations using the smoothed particle hydrodynamics method are also performed based on Cahn–Hilliard and Navier–Stokes equations to investigate the formation of viscous fingers in miscible and immiscible systems. The comparison of pore formation characteristics in the experiment and simulation shows that immiscible viscous fingering is present; however, it is only relevant in specific preparation set-ups similar to Hele-Shaw cells. In experiments, we also observe the formation of Liesegang rings. Enabling diffusive mass transport across the immiscible interface leads to Liesegang rings in the simulation. We conclude that further investigations of Liesegang pattern as a relevant mechanism in the formation of morphology in porous polymer membranes are necessary.Thu Feb 07 21:34:03 CET 2019J. Theor. Biol.91-102On the relationship between cell cycle analysis with ergodic principles
and age-structured cell population models 4142017Journal Papers Cyclic processes, in particular the cell cycle, are of great importance
in cell biology. Continued improvement in cell population analysis
methods like fluorescence microscopy, flow cytometry, CyTOF or single-cell
omics made mathematical methods based on ergodic principles a powerful
tool in studying these processes. In this paper, we establish the
relationship between cell cycle analysis with ergodic principles
and age structured population models. To this end, we describe the
progression of a single cell through the cell cycle by a stochastic
differential equation on a one dimensional manifold in the high dimensional
dataspace of cell cycle markers. Given the assumption that the cell
population is in a steady state, we derive transformation rules which
transform the number density on the manifold to the steady state
number density of age structured population models. Our theory facilitates
the study of cell cycle dependent processes including local molecular
events, cell death and cell division from high dimensional "snapshot"
data. Ergodic analysis can in general be applied to every process
that exhibits a steady state distribution. By combining ergodic analysis
with age structured population models we furthermore provide the
theoretic basis for extensions of ergodic principles to distribution
that deviate from their steady state.journalCommunity for tag(s) journal