Cyclic Interference Alignment and Cancellation in 3-User X-Networks with Minimal Backhaul

We consider the problem of Cyclic Interference Alignment (IA) on the 3-user X-network and show that it is infeasible to exactly achieve the upper bound of $\frac{K^2}{2K-1}=\frac{9}{5}$ degrees of freedom for the lower bound of n=5 signalling dimensions and K=3 user-pairs. This infeasibility goes beyond the problem of common eigenvectors in invariant subspaces within spatial IA. In order to gain non-asymptotic feasibility with minimal intervention, we first investigate an alignment strategy that enables IA by feedforwarding a subset of messages with minimal rate. In a second step, we replace the proposed feedforward strategy by an analogous Cyclic Interference Alignment and Cancellation scheme with a backhaul network on the receiver side and also by a dual Cyclic Interference Neutralization scheme with a backhaul network on the transmitter side.Comment: 8 pages, short version submitted to ISIT 201

The Degrees-of-Freedom of Multi-way Device-to-Device Communications is Limited by 2

A 3-user device-to-device (D2D) communications scenario is studied where each user wants to send and receive a message from each other user. This scenario resembles a 3-way communication channel. The capacity of this channel is unknown in general. In this paper, a sum-capacity upper bound that characterizes the degrees-of-freedom of the channel is derived by using genie-aided arguments. It is further shown that the derived upper bound is achievable within a gap of 2 bits, thus leading to an approximate sum-capacity characterization for the 3-way channel. As a by-product, interesting analogies between multi-way communications and multi-way relay communications are concluded.Comment: 5 pages, ISIT 201

Deep Denoising for Hearing Aid Applications

Reduction of unwanted environmental noises is an important feature of today's hearing aids (HA), which is why noise reduction is nowadays included in almost every commercially available device. The majority of these algorithms, however, is restricted to the reduction of stationary noises. In this work, we propose a denoising approach based on a three hidden layer fully connected deep learning network that aims to predict a Wiener filtering gain with an asymmetric input context, enabling real-time applications with high constraints on signal delay. The approach is employing a hearing instrument-grade filter bank and complies with typical hearing aid demands, such as low latency and on-line processing. It can further be well integrated with other algorithms in an existing HA signal processing chain. We can show on a database of real world noise signals that our algorithm is able to outperform a state of the art baseline approach, both using objective metrics and subject tests.Comment: submitted to IWAENC 201

Податковий інструментарій зниження ризикованості інноваційної діяльності

Розглянуто ознаки ризикованості інноваційної діяльності і досліджено податкові засоби її зниження. Проведено групування податкових пільг за формами їх надання для інноваційних проектів. Виявлено позитивні і негативні сторони пільгового стимулювання інноваційного розвитку.Found out the positive and negative sides of favourable stimulation of innovative development. The features of risks in innovative activity and tax facilities of its decline are considered. Tax benefits are grouped after the forms of their grant for innovative projects

Microkinetic Modeling of the Oxidation of Methane Over PdO Catalysts—Towards a Better Understanding of the Water Inhibition Effect

Water, which is an intrinsic part of the exhaust gas of combustion engines, strongly inhibits the methane oxidation reaction over palladium oxide-based catalysts under lean conditions and leads to severe catalyst deactivation. In this combined experimental and modeling work, we approach this challenge with kinetic measurements in flow reactors and a microkinetic model, respectively. We propose a mechanism that takes the instantaneous impact of water on the noble metal particles into account. The dual site microkinetic model is based on the mean-field approximation and consists of 39 reversible surface reactions among 23 surface species, 15 related to Pd-sites, and eight associated with the oxide. A variable number of available catalytically active sites is used to describe light-off activity tests as well as spatially resolved concentration profiles. The total oxidation of methane is studied at atmospheric pressure, with space velocities of 160,000 h−1 in the temperature range of 500–800 K for mixtures of methane in the presence of excess oxygen and up to 15% water, which are typical conditions occurring in the exhaust of lean-operated natural gas engines. The new approach presented is also of interest for modeling catalytic reactors showing a dynamic behavior of the catalytically active particles in general

Surface Reaction Kinetics of Steam- and CO₂-Reforming as Well as Oxidation of Methane over Nickel-Based Catalysts

An experimental and kinetic modeling study on the Ni-catalyzed conversion of methane under oxidative and reforming conditions is presented. The numerical model is based on a surface reaction mechanism consisting of 52 elementary-step like reactions with 14 surface and six gas-phase species. Reactions for the conversion of methane with oxygen, steam, and CO₂ as well as methanation, water-gas shift reaction and carbon formation via Boudouard reaction are included. The mechanism is implemented in a one-dimensional flow field description of a fixed bed reactor. The model is evaluated by comparison of numerical simulations with data derived from isothermal experiments in a flow reactor over a powdered nickel-based catalyst using varying inlet gas compositions and operating temperatures. Furthermore, the influence of hydrogen and water as co-feed on methane dry reforming with CO₂ is also investigated

NIRS-based detection and removal of pyrrolizidine alkaloid containing weeds in crop plants after harvest – PA-NIRSort

Pyrrolizindinalkaloide (PAs) sind lebertoxisch wirkende, sekundäre Pflanzeninhaltsstoffe, die den Pflanzen zum Schutz vor Fraßfeinden dienen. In den letzten Jahren sind PAs verstärkt in den Fokus gerückt, da sie als ungewollte Beiernte besonders in Bio- und Kindertees zu zum Teil sehr hohen Alkaloid-Belastungen führten. Inzwischen wurden strenge PA-Grenzwerte vom Bundesinstitut für Arzneimittel und Medizinprodukte (BfArM) publiziert, denn Arzneipflanzen können mit PA-haltigen Unkräu­tern wie verschiedenen Kreuzkraut-Arten, Gemei­nem Natternkopf, Ackervergißmeinnicht, Gewöhnlicher Hundszunge, Wasserdost oder Borretsch verunreinigt sein und so über Arznei- oder Aroma-Tees Menschen potenziell gefährden (BfArM, 2016). Durch diese strengen Grenzwerte genügen unter Umständen vier bis fünf PA-bildende Pflanzen des Gemeinen Greiskrauts (Senecio vulgaris) je Hektar Anbaufläche, um die Verkehrsfähigkeit einer Tonne Medizinaldroge zu gefährden. Dies zu verhindern erfordert eine engmaschige regelmäßige Feldkontrolle und mechanisches Unkrautentfernen, das unter ökonomischen Aspekten kaum realisierbar ist. Daher kommt einer, der Ernte nachgelagerten Qualitätskontrolle zum Entfernen potentieller PA-Beikräuter eine besonders wichtige Rolle zu. Ziel des im März 2019 gestarteten, von der Fachagentur für Nachwachsende Rohstoffe (FNR) geförderten Verbundprojekts des Julius Kühn-Instituts Berlin (Institut für Ökologische Chemie, Pflanzenanalytik und Vorratsschutz) und des Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung (IOSB) ist die Entwicklung einer leistungsfähigen Detektionsmethode auf Basis von Hyperspektral-Nah-Infrarot-Spektroskopie (hyper­spektral-NIRS) zur Erkennung von Verunreinigungen durch PA-haltige Pflanzen(teile) im Erntegut von Arznei- und Gewürzpflanzen. In Kombination mit einer gekoppelten Sortiereinheit (beispielsweise über Druckluftimpulse) soll so eine Abtrennung unerwünschter und poten­tiell toxischer Beikräuter erzielt werden. Am Ende des Projektes soll ein Prototyp zur echtzeitfähigen Rei­nigung der Erntechargen verschiedener Arznei- und Gewürz­pflanzen vorgestellt werden. Ähnliche Systeme sind bereits in der Kunststoff-Abfallsortierung bzw. der Qualitätskontrolle von Weinbeeren auf Basis des Oechsle-Grades etabliert (Freund et al., 2015). Angestrebt wird ein Durchsatz von bis zu 1,5 t/h. Mit einer solchen automatisierten Sortiertechnik ließen sich die gesundheitlichen Risiken durch PA-verunreinigte Arzneipflanzenprodukte für die Anbauer und Verarbeiter von Arzneipflanzen ökologisch und ökonomisch effizient reduzieren. Dies würde auch eine Sicherung der qualitativ hochwertigen und konkurrenzfähigen Produktion pflanzlicher Arzneimittel in Deutschland bedeuten. Erste Ergebnisse zeigen, dass eine Klassifizierung der Pflanzenarten mittels NIR-Spektroskopie zuverlässig möglich ist. Um solche Bildanalysen auch in Echtzeit durchführen zu können, werden die zu verarbeitenden Datenmengen mittels multifaktorieller Datenanalyse auf entscheidende spektrale Merkmale (Faktoren) reduziert.The general objective of the project is the development of an efficient sorting system based on hyperspectral near-infrared spectroscopy (NIRS) for the detection and separation of impurities by pyrrolizidine alkaloid (PA)-containing plant-derived contaminations in cultural plants, e.g. medicinal and aromatic plants. PAs are liver-toxic secondary metabolites that protect plants from predators and have drawn more attention in recent years after harmful concentrations were found in medicinal teas. By now, the German Federal Institute for Drugs and Medical Devices (BfArM) has published strict PA limit values because medicinal plants can be contaminated with PA-containing weeds such as various types of ragwort, groundsel, common viper's head, field forget-me-not, common dog's tongue, water-east or borage and thus, potentially endanger people with medicinal or aromatic teas (BfArM, 2016). Four to five PA-containing plants e.g of Senecio vulgaris per hectare are sufficient to contaminate one ton of the drug by exceeding the critical value of maximum uptake of 0,007 μg PA/kg body weight per day published by HMPC. The planned process will analyze fresh and dried plant material on a flat-conveyer using hyperspectral NIR spectroscopy to detect impurities in the crop. After identification, contaminants should be removed by a sorting technique, e.g. using compressed air pulses. Similar systems have already been established in plastic waste sorting and quality control, for example for grapes (Freund et al., 2015). The aim is to achieve a high throughput of up to 1.5 t/h with such an automated sorting technology, the health risks posed by PA-contaminated medicinal plant products could be reduced ecologically and economically efficient for cultivation and processing of medicinal plants. This would also mean safeguarding high-quality and competitive plant-derived drug production in Germany. First results show that a classification of target plant species and contaminating groundsel using NIR spectroscopy succeeds for various medicinal plants. To be able to carry out such image analyses in real-time, the amount of data to be processed will be reduced to the decisive factors using multifactorial data analysis