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With the increased interest for interstellar exploration after the discovery of exoplanets and the proposal by Breakthrough Starshot, this paper investigates the optimisation of photon-sail trajectories in Alpha Centauri. The prime objective is to find the optimal steering strategy for a photonic sail to get captured around one of the stars after a minimum-time transfer from Earth. By extending the idea of the Breakthrough Starshot project with a deceleration phase upon arrival, the mission’s scientific yield will be increased. As a secondary objective, transfer trajectories between the stars and orbit-raising manoeuvres to explore the habitable zones of the stars are investigated. All trajectories are optimised for minimum time of flight using the trajectory optimisation software InTrance. Depending on the sail technology, interstellar travel times of 77.6-18,790 years can be achieved, which presents an average improvement of 30% with respect to previous work. Still, significant technological development is required to reach and be captured in the Alpha-Centauri system in less than a century. Therefore, a fly-through mission arguably remains the only option for a first exploratory mission to Alpha Centauri, but the enticing results obtained in this work provide perspective for future long-residence missions to our closest neighbouring star system.
Für die Verarbeitung von natürlicher Sprache ist ein wichtiger Zwischenschritt das Parsing, bei dem für Sätze der natürlichen Sprache Ableitungsbäume bestimmt werden. Dieses Verfahren ist vergleichbar zum Parsen formaler Sprachen, wie z. B. das Parsen eines Quelltextes. Die Parsing-Methoden der formalen Sprachen, z. B. Bottom-up-Parser, können nicht auf das Parsen der natürlichen Sprache übertragen werden, da keine Formalisierung der natürlichen Sprachen existiert [3, 12, 23, 30].
In den ersten Programmen, die natürliche Sprache verarbeiten [32, 41], wurde versucht die natürliche Sprache mit festen Regelmengen zu verarbeiten. Dieser Ansatz stieß jedoch schnell an seine Grenzen, da die Regelmenge nicht vollständig sowie nicht minimal ist und wegen der benötigten Menge an Regeln schwer zu verwalten ist. Die Korpuslinguistik [22] bot die Möglichkeit, die Regelmenge durch Supervised-Machine-Learning-Verfahren [2] abzulösen.
Teil der Korpuslinguistik ist es, große Textkorpora zu erstellen und diese mit sprachlichen Strukturen zu annotieren. Zu diesen Strukturen gehören sowohl die Wortarten als auch die Ableitungsbäume der Sätze. Vorteil dieser Methodik ist es, dass repräsentative Daten zur Verfügung stehen. Diese Daten werden genutzt, um mit Supervised-Machine-Learning-Verfahren die Gesetzmäßigkeiten der natürliche Sprachen zu erlernen.
Das Maximum-Entropie-Verfahren ist ein Supervised-Machine-Learning-Verfahren, das genutzt wird, um natürliche Sprache zu erlernen. Ratnaparkhi [25] nutzt Maximum-Entropie, um Ableitungsbäume für Sätze der natürlichen Sprache zu erlernen. Dieses Verfahren macht es möglich, die natürliche Sprache (abgebildet als Σ∗) trotz einer fehlenden formalen Grammatik zu parsen.
This paper presents NLP Lean Programming
framework (NLPf), a new framework
for creating custom natural language processing
(NLP) models and pipelines by utilizing
common software development build systems.
This approach allows developers to train and
integrate domain-specific NLP pipelines into
their applications seamlessly. Additionally,
NLPf provides an annotation tool which improves
the annotation process significantly by
providing a well-designed GUI and sophisticated
way of using input devices. Due to
NLPf’s properties developers and domain experts
are able to build domain-specific NLP
applications more efficiently. NLPf is Opensource
software and available at https://
gitlab.com/schrieveslaach/NLPf.
Research collaborations provide opportunities for both practitioners and researchers: practitioners need solutions for difficult business challenges and researchers are looking for hard problems to solve and publish. Nevertheless, research collaborations carry the risk that practitioners focus on quick solutions too much and that researchers tackle theoretical problems, resulting in products which do not fulfill the project requirements.
In this paper we introduce an approach extending the ideas of agile and lean software development. It helps practitioners and researchers keep track of their common research collaboration goal: a scientifically enriched software product which fulfills the needs of the practitioner’s business model.
This approach gives first-class status to application-oriented metrics that measure progress and success of a research collaboration continuously. Those metrics are derived from the collaboration requirements and help to focus on a commonly defined goal.
An appropriate tool set evaluates and visualizes those metrics with minimal effort, and all participants will be pushed to focus on their tasks with appropriate effort. Thus project status, challenges and progress are transparent to all research collaboration members at any time.
Mit dem Projekt wird sich dem Problem der weltweiten Lebensmittelverschwendung angenommen und versucht Abfälle in Privathaushalten primär industrialisierter Staaten zu reduzieren. Mit jährlich 1,3 Milliarden Tonnen landet circa ein Drittel aller weltweit produzierten Lebensmittel im Müll. Einen Großteil dieser Abfälle ist vermeidbar, besonders dort, wo man im Überfluss lebt.
Das konzipierte Möbelstück soll die Lagerungsmöglichkeiten des Nutzers optimieren und somit für die Wertschätzung von Lebensmitteln sensibilisieren. Für das Möbelstück werden ausschließlich natürliche Materialien verwendet, welche in ihrer Charakteristik optimal zum Funktionsumfang passen, der für die Lagerung benötigt wird. Das Material Terracotta ermöglicht es, mittels Verdunstungskühlung stromlos Gemüse kalt zu halten. Antibakterielles Holz tötet schädliche Bakterien ab. Die Konstruktion ermöglicht somit eine fachgerechte Lebensmittelagerung und ermöglicht sowohl sehr flexible Nutzung, wie auch leichte Reparatur.
The Gram-positive endospore-forming bacterium Bacillus licheniformis can be found widely in nature and it is exploited in industrial processes for the manufacturing of antibiotics, specialty chemicals, and enzymes. Both in its varied natural habitats and in industrial settings, B. licheniformis cells will be exposed to increases in the external osmolarity, conditions that trigger water efflux, impair turgor, cause the cessation of growth, and negatively affect the productivity of cell factories in biotechnological processes. We have taken here both systems-wide and targeted physiological approaches to unravel the core of the osmostress responses of B. licheniformis. Cells were suddenly subjected to an osmotic upshift of considerable magnitude (with 1 M NaCl), and their transcriptional profile was then recorded in a time-resolved fashion on a genome-wide scale. A bioinformatics cluster analysis was used to group the osmotically up-regulated genes into categories that are functionally associated with the synthesis and import of osmostress-relieving compounds (compatible solutes), the SigB-controlled general stress response, and genes whose functional annotation suggests that salt stress triggers secondary oxidative stress responses in B. licheniformis. The data set focusing on the transcriptional profile of B. licheniformis was enriched by proteomics aimed at identifying those proteins that were accumulated by the cells through increased biosynthesis in response to osmotic stress. Furthermore, these global approaches were augmented by a set of experiments that addressed the synthesis of the compatible solutes proline and glycine betaine and assessed the growth-enhancing effects of various osmoprotectants. Combined, our data provide a blueprint of the cellular adjustment processes of B. licheniformis to both sudden and sustained osmotic stress.
Characterising an insect antenna as a receptor for a biosensor by means of impedance spectroscopy
(2001)
Performance Investigations of the IP Multicast Architecture / Hermanns, Oliver ; Schuba, Marko
(1995)
Cybersecurity of Industrial Control Systems (ICS) is an important issue, as ICS incidents may have a direct impact on safety of people or the environment. At the same time the awareness and knowledge about cybersecurity, particularly in the context of ICS, is alarmingly low. Industrial honeypots offer a cheap and easy to implement way to raise cybersecurity awareness and to educate ICS staff about typical attack patterns. When integrated in a productive network, industrial honeypots may not only reveal attackers early but may also distract them from the actual important systems of the network. Implementing multiple honeypots as a honeynet, the systems can be used to emulate or simulate a whole Industrial Control System. This paper describes a network of honeypots emulating HTTP, SNMP, S7communication and the Modbus protocol using Conpot, IMUNES and SNAP7. The nodes mimic SIMATIC S7 programmable logic controllers (PLCs) which are widely used across the globe. The deployed honeypots' features will be compared with the features of real SIMATIC S7 PLCs. Furthermore, the honeynet has been made publicly available for ten days and occurring cyberattacks have been analyzed
Smartphone Forensik
(2012)