Adaptation and implementation of a process of innovation and design within a SME

A design process is a sequence of design phases, starting with the design requirement and leading to a definition of one or several system architectures. For every design phase, various support tools and resolution methods are proposed in the literature. These tools are however very difficult to implement in an SME, which may often lack resources. In this article we propose a complete design process for new manufacturing techniques, based on creativity and knowledge re-use in searching for technical solutions. Conscious of the difficulties of appropriation in SME, for every phase of our design process we propose resolution tools which are adapted to the context of a small firm. Design knowledge has been capitalized in a knowledge base. The knowledge structuring we propose is based on functional logic and the design process too is based on the functional decomposition of the system, and integrates the simplification of the system architecture, from the early phases of the process. For this purpose, aggregation phases and embodiment are proposed and guided by heuristics

Zero-Shot Crosslingual Sentence Simplification

Sentence simplification aims to make sentences easier to read and understand. Recent approaches have shown promising results with encoder-decoder models trained on large amounts of parallel data which often only exists in English. We propose a zero-shot modeling framework which transfers simplification knowledge from English to another language (for which no parallel simplification corpus exists) while generalizing across languages and tasks. A shared transformer encoder constructs language-agnostic representations, with a combination of task-specific encoder layers added on top (e.g., for translation and simplification). Empirical results using both human and automatic metrics show that our approach produces better simplifications than unsupervised and pivot-based methods

Text Simplification of Scientific Texts for Non-Expert Readers

Reading levels are highly individual and can depend on a text's language, a person's cognitive abilities, or knowledge on a topic. Text simplification is the task of rephrasing a text to better cater to the abilities of a specific target reader group. Simplification of scientific abstracts helps non-experts to access the core information by bypassing formulations that require domain or expert knowledge. This is especially relevant for, e.g., cancer patients reading about novel treatment options. The SimpleText lab hosts the simplification of scientific abstracts for non-experts (Task 3) to advance this field. We contribute three runs employing out-of-the-box summarization models (two based on T5, one based on PEGASUS) and one run using ChatGPT with complex phrase identification.Comment: Paper accepted at SimpleText@CLEF'23, 12 pages, 1 Figure, 4 Table