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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.
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.
Characterising an insect antenna as a receptor for a biosensor by means of impedance spectroscopy
(2001)
A semiconductor field-effect device has been used for an enzymatically catalyzed degradation of biopolymers for the first time. This novel technique is capable to monitor the degradation process of multiple samples in situ and in real-time. As model system, the degradation of the biopolymer poly(D, L-lactic acid) has been monitored in the degradation medium containing the enzyme lipase from Rhizomucor miehei. The obtained results demonstrate the potential of capacitive field-effect sensors for degradation studies of biodegradable polymers.
A sensor system for investigating (bio)degradationprocesses of polymers is presented. The system utilizes semiconductor field-effect sensors and is capable of monitoring the degradation process in-situ and in real-time. The degradation of the polymer poly(d,l-lactic acid) is exemplarily monitored in solutions with different pH value, pH-buffer solution containing the model enzyme lipase from Rhizomucormiehei and cell-culture medium containing supernatants from stimulated and non-stimulated THP-1-derived macrophages mimicking activation of the immune system.