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

Zadeh–MacFarlane–Jamshidi theorems on decoupling of a fuzzy rule base

AbstractThis paper outlines the inspiration received by the author from the Zadeh–MacFarlane–Jamshidi trio in his pursuit concerning the theory and Application of fuzzy logic. Beginning with Zadeh’s pioneering work, a hierarchical control system was developed, in collaboration with MacFarlane, for application in robotic manipulators. Subsequently, the work was extended to an analytical basis for controller tuning using fuzzy decision making. On the prompting of Jamshidi to address the issue of knowledge-base simplification, theorems were developed related to decoupling a fuzzy rule base. These developments provided a theoretical basis for applying single-context decision making to a problem governed by the knowledge base of coupled fuzzy rules. The developed theorems establish an analytical equivalence between the decisions made from a coupled set of fuzzy rules and an uncoupled set of fuzzy rules concerning the same problem domain. These developments have been applied to supervisory control of an industrial fish cutting machine. The paper presents the pertinent theory and illustrative examples

Engineering simulations for cancer systems biology

Computer simulation can be used to inform in vivo and in vitro experimentation, enabling rapid, low-cost hypothesis generation and directing experimental design in order to test those hypotheses. In this way, in silico models become a scientific instrument for investigation, and so should be developed to high standards, be carefully calibrated and their findings presented in such that they may be reproduced. Here, we outline a framework that supports developing simulations as scientific instruments, and we select cancer systems biology as an exemplar domain, with a particular focus on cellular signalling models. We consider the challenges of lack of data, incomplete knowledge and modelling in the context of a rapidly changing knowledge base. Our framework comprises a process to clearly separate scientific and engineering concerns in model and simulation development, and an argumentation approach to documenting models for rigorous way of recording assumptions and knowledge gaps. We propose interactive, dynamic visualisation tools to enable the biological community to interact with cellular signalling models directly for experimental design. There is a mismatch in scale between these cellular models and tissue structures that are affected by tumours, and bridging this gap requires substantial computational resource. We present concurrent programming as a technology to link scales without losing important details through model simplification. We discuss the value of combining this technology, interactive visualisation, argumentation and model separation to support development of multi-scale models that represent biologically plausible cells arranged in biologically plausible structures that model cell behaviour, interactions and response to therapeutic interventions

Інтелектуальний аналіз природномовних текстів у процесі формування бази знань адаптивних систем дистанційного навчання

У статті описано алгоритм і програмну реалізацію модуля автоматизованого квантування лекційного матеріалу на основі інтелектуального аналізу природномовних текстів в процесі побудови бази знань адаптивних систем дистанційного навчання. Результатом даного дослідження є спрощення процедури підготовки лекційного матеріалу до імпорту в БЗ; встановлення взаємозв’язків між окремими елементами БЗ, визначення властивостей і їх подальше використання для побудови індивідуальної траєкторії навчання.В статье описаны алгоритм и программная реализация модуля автоматизированного квантования лекционного материала на основе интеллектуального анализа естественно-языковых текстов в процессе построения базы знаний адаптивных систем дистанционного обучения. Результатом данного исследования является упрощение процедуры подготовки лекционного материала к импорту в базу знаний, установление взаимосвязей между отдельными элементами базы знаний и определение их свойств для дальнейшего использования при построении индивидуальной траектории обучения.This article describes the algorithm and program realization of the module for automated quantization of the lecture material based on natural-language texts in the process of building of knowledge base for adaptive e-learning. The result of this research is simplification the preparation of lecture material to be imported into the knowledge base, establishing of relationships between the individual elements of the knowledge base, and determination of their properties for future use in the construction of an individual trajectory of study

Integrating Transformer and Paraphrase Rules for Sentence Simplification

Sentence simplification aims to reduce the complexity of a sentence while retaining its original meaning. Current models for sentence simplification adopted ideas from machine translation studies and implicitly learned simplification mapping rules from normalsimple sentence pairs. In this paper, we explore a novel model based on a multi-layer and multi-head attention architecture and we propose two innovative approaches to integrate the Simple PPDB (A Paraphrase Database for Simplification), an external paraphrase knowledge base for simplification that covers a wide range of real-world simplification rules. The experiments show that the integration provides two major benefits: (1) the integrated model outperforms multiple stateof-the-art baseline models for sentence simplification in the literature (2) through analysis of the rule utilization, the model seeks to select more accurate simplification rules. The code and models used in the paper are available at https://github.com/ Sanqiang/text_simplification

A new fuzzy set merging technique using inclusion-based fuzzy clustering

This paper proposes a new method of merging parameterized fuzzy sets based on clustering in the parameters space, taking into account the degree of inclusion of each fuzzy set in the cluster prototypes. The merger method is applied to fuzzy rule base simplification by automatically replacing the fuzzy sets corresponding to a given cluster with that pertaining to cluster prototype. The feasibility and the performance of the proposed method are studied using an application in mobile robot navigation. The results indicate that the proposed merging and rule base simplification approach leads to good navigation performance in the application considered and to fuzzy models that are interpretable by experts. In this paper, we concentrate mainly on fuzzy systems with Gaussian membership functions, but the general approach can also be applied to other parameterized fuzzy sets