Fuzzy Natural Logic in IFSA-EUSFLAT 2021

The present book contains five papers accepted and published in the Special Issue, “Fuzzy Natural Logic in IFSA-EUSFLAT 2021”, of the journal Mathematics (MDPI). These papers are extended versions of the contributions presented in the conference “The 19th World Congress of the International Fuzzy Systems Association and the 12th Conference of the European Society for Fuzzy Logic and Technology jointly with the AGOP, IJCRS, and FQAS conferences”, which took place in Bratislava (Slovakia) from September 19 to September 24, 2021. Fuzzy Natural Logic (FNL) is a system of mathematical fuzzy logic theories that enables us to model natural language terms and rules while accounting for their inherent vagueness and allows us to reason and argue using the tools developed in them. FNL includes, among others, the theory of evaluative linguistic expressions (e.g., small, very large, etc.), the theory of fuzzy and intermediate quantifiers (e.g., most, few, many, etc.), and the theory of fuzzy/linguistic IF–THEN rules and logical inference. The papers in this Special Issue use the various aspects and concepts of FNL mentioned above and apply them to a wide range of problems both theoretically and practically oriented. This book will be of interest for researchers working in the areas of fuzzy logic, applied linguistics, generalized quantifiers, and their applications

Eco-design decision making : towards sustainable engineering design of large made-to-order products

Sustainable design provides an holistic, life-cycle approach by which design engineers can minimise negative impacts and maximise positive impacts, thus ensuring that current industrial progress is not achieved at the expense of future generations. In the context of sustainable design, large made-to-order (LMTO) product sectors must address some unique issues: " The design process may be in the order of years, involving the client, the design contractors, co-venturers, suppliers and regulators. 9 The one-off nature of the design may limit the opportunity for reuse of design knowledge. 11 The existenceo f the possibility of catastrophico ut-of-envelopee ventsl eading to large scale safety and environmental impacts. " There is potential for high energy and resource consumption. " . Some LMTO products may cause local and transboundary environmental impacts. 0 There may be long term, post-decommissioning impacts. 0 Some aspects of the product life-cycle may give rise to impacts on social welfare. Engineering design is a process of decision making both during option synthesis and option selection. The first part of this research examined the current integration of environmental objectives and attributes with industrial design decision making processes using qualitative research methods. In particular, design selection was considered as the case-study focused on the activities of two case-study design contractors. The second part of the research proposed a framework to assist the consideration of environmental and societal impacts using transparent, systematic methodologies based on Multiple Attribute Decision Making (MADM) approaches. Two MADM methods were compared in relation to a case-study regarding the selection of an option for a produced water treatment system; Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Concordance and Discordance Analyses by Similarity to Ideal Solution (CODASID). Due to the subjectivity and uncertainty associated with information relating to sustainable design, a fuzzy set-based methodology was also investigated. In order to simulate the intuitive processes of human decision makers, the application of linguistic terms to evaluate sustainable design attributes was explored. This method was applied to a group decision making case-study to determine the best option for replacing a heat exchanger situated in a pond water cooling system. Comparisons were made between the fuzzy MADM method and the decision obtained from a group-based discussion. Finally, the third part of the research specifically addressed perceived risk attributed by the public to proposed large made-to-order products or processes, accommodating the societal element of sustainable design. Public risk perception was decomposed into measurable indices which were suitable for application to the fuzzy MADM method. The final aggregated evaluation, representing the overall perceived risk associated with the product in question, was then examined under different tolerance scenarios in order to make an informed judgement with respect to product viability. These three core research elements provide the foundation for managing the environmental and societal aspects of sustainable engineering design of large made-toorder products, thus providing an important addition to the wider concept of integrated product design.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Measuring and assessing indeterminacy and variation in the morphology-syntax distinction (advance online)

We provide a discussion of some of the challenges in using statistical methods to investigate the morphology-syntax distinction cross-linguistically. The paper is structured around three problems related to the morphology-syntax distinction: (i) the boundary strength problem; (ii) the composition problem; (iii) the architectural problem. The boundary strength problem refers to the possibility that languages vary in terms of how distinct morphology and syntax are or the degree to which morphology is autonomous. The composition problem refers to the possibility that languages vary in terms of how they distinguish morphology and syntax: what types of properties distinguish the two systems. The architecture problem refers to the possibility that languages vary in terms of whether a global distinction between morphology and syntax is motivated at all and the possibility that languages might partition phenomena in different ways. This paper is concerned with providing an overarching review of the methodological problems involved in addressing these three issues. We illustrate the problems using three statistical methods: correlation matrices, random forests with different choices for the dependent variable, and hierarchical clustering with validation techniques

Proceedings of the 1st Doctoral Consortium at the European Conference on Artificial Intelligence (DC-ECAI 2020)

1st Doctoral Consortium at the European Conference on Artificial Intelligence (DC-ECAI 2020), 29-30 August, 2020 Santiago de Compostela, SpainThe DC-ECAI 2020 provides a unique opportunity for PhD students, who are close to finishing their doctorate research, to interact with experienced researchers in the field. Senior members of the community are assigned as mentors for each group of students based on the student’s research or similarity of research interests. The DC-ECAI 2020, which is held virtually this year, allows students from all over the world to present their research and discuss their ongoing research and career plans with their mentor, to do networking with other participants, and to receive training and mentoring about career planning and career option

Enhancements onMultiword Extraction and Inclusion of Relevant SingleWords on LocalMaxs

The digital information available to us reproduces itself in an overwhelmingly rapid way. Following advances in Text Mining, this large amount of information can now be processed and understood more swiftly by people. For this purpose, the concept of extracting Relevant Expressions and Keywords from a text becomes an important task. This process consists in retrieving the most important ideas from a document or set of documents, which can be done using statistical and/or linguistic tools, being the first the focus of this work. In order to extract these terminologies using statistical methodologies, one must take advantage of patterns that indicate importance in a word/expression. Relevant Expressions tend to present some singularities, as the words therein, seem to have, for example, high values of cohesion between them, conveying importance. The LocalMaxs is an algorithm that uses this cohesion metric between words to capture meaningful Multi Word Expressions from a text, with an average Precision close to 70%, but it is not able to extract 1-grams (single words). This dissertation aims at improving the performance of this algorithm, as well as including the newly added Relevant Single Words, which is an important factor specially in languages where relevant compound nouns come in long words (i.e. German). These improvements must be made keeping language independence.A informação disponível em forma digital aumenta a uma velocidade estonteante, tornando difícil o seu processamento e acompanhamento. Utilizando técnicas de Text Mining, esta grande quantidade de informação pode ser lida e compreendida de forma mais expedita por Humanos. A extração de Expressões e Termos Relevantes é um processo crucial para a decomposição de um documento ou grupo de documentos, e consiste na recolha dos conceitos mais importantes dos mesmos. Este processo é realizado através da utilização de ferramentas estatísticas (focadas neste trabalho) e/ou linguísticas. Para extrair estas terminologias utilizando métodos estatísticos, têm que ser encontrados padrões que indiquem e apontem para a importância e relevância de uma palavra/ expressão. Expressões Relevantes apresentam várias características que as definem, sendo uma das quais a verificação de altos valores de coesão estatística entre as palavras que as compõem. O algoritmo LocalMaxs utiliza estes valores de coesão entre palavras para extraír Expressões Relevantes de um texto, com uma precisão de aproximadamente 70%. Não consegue, no entanto, extrair 1-gramas (palavras isoladas) Relevantes. Esta dissertação tem como objetivo melhorar a performance na extração de Expressões Relevantes do algoritmo LocalMaxs, bem como criar mecanismos que o permitam extrair 1-gramas relevantes. Estes melhoramentos devem manter o algoritmo independente da língua do texto em análise

KNOWLEDGE-BASED DECISION SUPPORT SYSTEM QUALITY FUNCTION DEPLOYMENT (KBDSS-QFD) TOOL FOR ASSESSMENT OF BUILDING ENVELOPE MATERIALS AND DESIGNS IN THE EARLY DESIGN STAGE

Ph.DDOCTOR OF PHILOSOPH

Discrete element and artificial intelligence modeling of rock properties and formation failure in advance of shovel excavation

Rock tests are performed before the start of every mining or civil engineering project as part of a detailed feasibility study. The feasibility study is costly and it comprises drilling, sample collection, sample handling and laboratory testing. Numerical modeling techniques, such as Particle Flow Code (PFC), can be used to provide reliable estimates of rock strength values. The numerical models for unconfined compressive strength (UCS), direct tension, and Brazilian tests were developed in PFC, and validated using data from literature. A particle size range of 3-5 mm with Dmax/Dmin = 1.67 gave the best results. The numerical errors were in the range of 6-22% for UCS, 21-80% for direct tension, and 5- 10% for Brazilian tests. About 1,800 confined compression tests were also performed in PFC to obtain formation material properties. However, the PFC algorithm takes a very long computational time to complete the process, and thus, there is a need for more efficient and faster methods. In this research, the author uses artificial intelligence methods including, Artificial Neural Network, Mamdani Fuzzy Logic, and Hybrid neural Fuzzy Inference System (HyFIS) to solve this problem. These methods, along with the Multiple Linear Regression method, were used for the predictive analysis. Based on R2 and RMSE statistics for the testing phase, HyFIS is the best predictive model. This study is the first attempt to develop self-learning artificial intelligent models for predicting formation material properties. In addition, this research study investigates the shovel excavation process using the discrete element technique in PFC to examine the shovel digging phase. The shovel excavation simulator provides a tool for optimizing strategies for maximizing its performance that provides a major breakthrough in the shovel excavation frontier --Abstract, page iii

A decision support system for ground improvement method selection

Abstract unavailable please refer to PD