Natural Language Processing in-and-for Design Research

We review the scholarly contributions that utilise Natural Language Processing (NLP) methods to support the design process. Using a heuristic approach, we collected 223 articles published in 32 journals and within the period 1991-present. We present state-of-the-art NLP in-and-for design research by reviewing these articles according to the type of natural language text sources: internal reports, design concepts, discourse transcripts, technical publications, consumer opinions, and others. Upon summarizing and identifying the gaps in these contributions, we utilise an existing design innovation framework to identify the applications that are currently being supported by NLP. We then propose a few methodological and theoretical directions for future NLP in-and-for design research

Data-Driven Environmentally Sustainable Product Design: A Shift Toward Increased use of Sustainable Design Activities in the Early Design Phase

Modern product design drives the boundaries of innovation by encompassing complex Design-for-X objectives, and the inclusion of multidimensional stakeholders. This growing complexity in product design has left design teams unequipped, as classical design theory is bounded by designer experience, expertise, and cognition. One novel approach to tackling product complexity is to leverage data into improved design processes through data-driven design methods. In this dissertation, data-driven design approaches are presented as a means to explore applied knowledge discovery in product data, with a particular focus on function-based design, life cycle inventory, and life cycle assessment data. Using artificial intelligence approaches ranging from decision trees to graph neural networks, and statistical methods such as kernel density estimation, function-based sustainable design is more readily achievable. This dissertation presents methods for introducing sustainable design knowledge in the early stages of product design through the use of data-driven approaches on historic LCA product data. Here, functional modeling is identified as the entry point to the early design phase that can be altered to meet sustainable design objectives. By using data-driven design methods, components are related to functional performance and estimated environmental impact. The culmination of this work is the creation of a probabilistic data-driven methodology that assesses the environmental impact of functional chains and provides component suggestions that reduce potential environmental impact. The research presented in this dissertation begins with an introduction to data-driven design literature and research opportunities (manuscript one). From these opportunities, manuscripts two and three introduce two function-based design methods for aiding in component function assignment and automated functional modeling. Manuscripts four and five introduce novel sustainable methods that realize the goals of this dissertation to create data-driven sustainable design methods applicable to the early design phase. Expanding on this work, the disparity in product data encourages the exploration of richer data sets. By leveraging multiple data sources, including manufacturing, digital, and other life cycle data, we can look forward to novel approaches in data-driven design for knowledge enrichment in function-based sustainable design

Responsible AI and Analytics for an Ethical and Inclusive Digitized Society

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Understanding the role of knowledge management on organisational functionality at Ezemvelo KZN Wildlife.

Masters Degree. University of KwaZulu-Natal, Durban.The study explores the role of Knowledge Management (KM) on organisational functionality at EKZNW organisation. The main research questions of the study are establishing if EKZNW has the KM practices, what they are, and if they have been and are of any benefit to the service delivery efficiency and strong competitive advantage of the organisation in the market. The main aim of the study is essentially exploring the role of all the KM practices of the organisation as to how they impact on the overall functionality of the organisation. It can therefore be briefly highlighted that KM translates into how the organisation attracts talent, how it preserves such talent, and how it ensures a smooth diffusion of such talent amongst the employees, which all ideally must result in heightened levels of innovation and efficiency, and sustained customer satisfaction and strong competitive advantage for the organisation. The data was collected from the employees of this (EKZNW) organisation. The employees that formed the population of the study were exclusively those who occupy management positions within their respective departments. The research methodology the study adopted is the qualitative approach with constructivism as the research paradigm. The researcher’s decision opting for the combination of these two elements of research, the qualitative method and the constructivist paradigm, has been motivated by the nature and purpose of the research study. It was therefore ascertained through the study, inter alia, that the incentive programmes and the reward systems of the organisation, almost invariably, yield positive results in the employees’ execution of their work, and heightened levels of motivation to share their knowledge and empower one another. This therefore underpinned the significance for the organisation to establish and institutionalise relevant and likely-to-yield-positive-outcomes KM practices which, inter alia, are exemplified by the training and skills-capacity-enhancing programmes. The study further reveals the importance of the time that the employees stay with the organisation and how that positively impacts on the overall performance of the staff. It transpires that the longer the employees stay with the organisation, the more knowledge and experience get acquired over time, and that essentially translate into the elevated overall productivity of the staff. This therefore necessitates that establishment of a highly conducive and encouraging working environment by the top management to ensure that the entire staff relish working for the organisation, and therefore get encouraged to stay longer with the organisation

Fuzzy Sets, Fuzzy Logic and Their Applications

The present book contains 20 articles collected from amongst the 53 total submitted manuscripts for the Special Issue “Fuzzy Sets, Fuzzy Loigic and Their Applications” of the MDPI journal Mathematics. The articles, which appear in the book in the series in which they were accepted, published in Volumes 7 (2019) and 8 (2020) of the journal, cover a wide range of topics connected to the theory and applications of fuzzy systems and their extensions and generalizations. This range includes, among others, management of the uncertainty in a fuzzy environment; fuzzy assessment methods of human-machine performance; fuzzy graphs; fuzzy topological and convergence spaces; bipolar fuzzy relations; type-2 fuzzy; and intuitionistic, interval-valued, complex, picture, and Pythagorean fuzzy sets, soft sets and algebras, etc. The applications presented are oriented to finance, fuzzy analytic hierarchy, green supply chain industries, smart health practice, and hotel selection. This wide range of topics makes the book interesting for all those working in the wider area of Fuzzy sets and systems and of fuzzy logic and for those who have the proper mathematical background who wish to become familiar with recent advances in fuzzy mathematics, which has entered to almost all sectors of human life and activity