A finder and representation system for knowledge carriers based on granular computing

In one of his publications Aristotle states ”All human beings by their nature desire to know” [Kraut 1991]. This desire is initiated the day we are born and accompanies us for the rest of our life. While at a young age our parents serve as one of the principle sources for knowledge, this changes over the course of time. Technological advances and particularly the introduction of the Internet, have given us new possibilities to share and access knowledge from almost anywhere at any given time. Being able to access and share large collections of written down knowledge is only one part of the equation. Just as important is the internalization of it, which in many cases can prove to be difficult to accomplish. Hence, being able to request assistance from someone who holds the necessary knowledge is of great importance, as it can positively stimulate the internalization procedure. However, digitalization does not only provide a larger pool of knowledge sources to choose from but also more people that can be potentially activated, in a bid to receive personalized assistance with a given problem statement or question. While this is beneficial, it imposes the issue that it is hard to keep track of who knows what. For this task so-called Expert Finder Systems have been introduced, which are designed to identify and suggest the most suited candidates to provide assistance. Throughout this Ph.D. thesis a novel type of Expert Finder System will be introduced that is capable of capturing the knowledge users within a community hold, from explicit and implicit data sources. This is accomplished with the use of granular computing, natural language processing and a set of metrics that have been introduced to measure and compare the suitability of candidates. Furthermore, are the knowledge requirements of a problem statement or question being assessed, in order to ensure that only the most suited candidates are being recommended to provide assistance

HIERARCHICAL-GRANULARITY HOLONIC MODELLING

This thesis aims to introduce an agent-based system engineering approach, named Hierarchical-Granularity Holonic Modelling, to support intelligent information processing at multiple granularity levels. The focus is especially on complex hierarchical systems. Nowadays, due to ever growing complexity of information systems and processes, there is an increasing need of a simple self-modular computational model able to manage data and perform information granulation at different resolutions (i.e., both spatial and temporal). The current literature lacks to provide such a methodology. To cite a relevant example, the object-oriented paradigm is suitable for describing a system at a given representation level; notwithstanding, further design effort is needed if a more synthetical of more analytical view of the same system is required. In the literature, the agent paradigm represents a viable solution in complex systems modelling; in particular, Multi-Agent Systems have been applied with success in a countless variety of distributed intelligence settings. Current agent-oriented implementations however suffer from an apparent dichotomy between agents as intelligent entities and agents\u2019 structures as superimposed hierarchies of roles within a given organization. The agents\u2019 architectures are often rigid and require intense re-engineering when the underpinning ontology is updated to cast new design criteria. The latest stage in the evolution of modelling frameworks is represented by Holonic Systems, based on the notion of \u2018holon\u2019 and \u2018holarchy\u2019 (i.e., hierarchy of holons). A holon, just like an agent, is an intelligent entity able to interact with the environment and to take decisions to solve a specific problem. Contrarily to agent, holon has the noteworthy property of playing the role of a whole and a part at the same time. This reflects at the organizational level: holarchy functions first as autonomous wholes in supra-ordination to their parts, secondly as dependent parts in sub-ordination to controls on higher levels, and thirdly in coordination with their local environment. These ideas were originally devised by Arthur Koestler in 1967. Since then, Holonic Systems have gained more and more credit in various fields such as Biology, Ecology, Theory of Emergence and Intelligent Manufacturing. Notwithstanding, with respect to these disciplines, fewer works on Holonic Systems can be found in the general framework of Artificial and Computational Intelligence. Moreover, the distance between theoretic models and actual implementation is still wide open. In this thesis, starting from the Koestler\u2019s original idea, we devise a novel agent-inspired model that merges intelligence with the holonic structure at multiple hierarchical-granularity levels. This is made possible thanks to a rule-based knowledge recursive representation, which allows the holonic agent to carry out both operating and learning tasks in a hierarchy of granularity levels. The proposed model can be directly used in terms of hardware/software applications. This endows systems and software engineers with a modular and scalable approach when dealing with complex hierarchical systems. In order to support our claims, exemplar experiments of our proposal are shown and prospective implications are commented

A Granular-based Approach for Semisupervised Web Information Labeling

A key issue when mining web information is the labeling problem: data is abundant on the web but is unlabelled. In this thesis, we address this problem by proposing i) a novel theoretical granular model that structures categorical noun phrase instances as well as semantically related noun phrase pairs from a given corpus representing unstructured web pages with a variant of Tolerance Rough Sets Model (TRSM), ii) a semi-supervised learning algorithm called Tolerant Pattern Learner (TPL) that labels categorical instances as well as relations. TRSM has so far been successfully employed for document retrieval and classification, but not for learning categorical and relational phrases. We use the ontological information from the Never Ending Language Learner (Nell) system. We compared the performance of our algorithm with Coupled Bayesian Sets (CBS) and Coupled Pattern Learner (CPL) algorithms for categorical and relational labeling, respectively. Experimental results suggest that TPL can achieve comparable performance with CBS and CPL in terms of precision.Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery grant 194376.Master of Science in Applied Computer Scienc

Voice Station: A Portfolio of Four Works Exploring Radio Art and Its Mediated Voices

This study pertains to the creative explorations of the human voice and the radio medium through a portfolio of four projects titled Voice Station. The research and creative processes of the portfolio draw on the practices of radio art, a genre that encompasses a wide range of artistic experimentations with the conventions and complexities of the medium. Voice Station centres the human voice as the only compositional material to investigate how recorded and mediated voices can be used artistically in diverse radio environments by employing distinct platforms and technologies: Voice Station I (2019-21) is a fixed-medium composition that offers a sonic vocabulary for the portfolio and, thus, establishes its conceptual and technological foundations; Voice Station II (2021-22) is a web-based, participatory live stream comprising vocal materials contributed and curated by the participants; Voice Station III (2022) is a radio installation that invites visitors to an interactive listening experience via the radio dial in a gallery environment; finally, selected episodes of my ongoing radio program at CJSW FM, Vocal Cords, provide an examination of the relationships between radio and voice from a broader perspective of campus and community broadcasting. The vocal catalogue, audio processing methods, and formal strategies emerging from each project are recycled and evaluated throughout the portfolio. This iterative practice uncovers sonic and metaphorical similarities between the two core concepts of this study, radio and voice, and presents a structural model shared by each project

A framework for assistive communications technology in cross-cultural healthcare

Rural and remote Australian Aboriginal communities suffer seriously adverse life expectancy rates, lifestyle disease complications and hospital treatment needs due to type 2 diabetes. In great part this is due to communications barriers arising from the lack of equitable acculturation within patient-practitioner consultations. This research presents a framework foundation for a computerised patient-practitioner lingua franca. Behavioural and design science ontology development delivers an intercultural patient-practitioner type 2 diabetes assistive communications system, known as P-PAC

Hierarchical Graphs as Organisational Principle and Spatial Model Applied to Pedestrian Indoor Navigation

In this thesis, hierarchical graphs are investigated from two different angles – as a general modelling principle for (geo)spatial networks and as a practical means to enhance navigation in buildings. The topics addressed are of interest from a multi-disciplinary point of view, ranging from Computer Science in general over Artificial Intelligence and Computational Geometry in particular to other fields such as Geographic Information Science. Some hierarchical graph models have been previously proposed by the research community, e.g. to cope with the massive size of road networks, or as a conceptual model for human wayfinding. However, there has not yet been a comprehensive, systematic approach for modelling spatial networks with hierarchical graphs. One particular problem is the gap between conceptual models and models which can be readily used in practice. Geospatial data is commonly modelled - if at all - only as a flat graph. Therefore, from a practical point of view, it is important to address the automatic construction of a graph hierarchy based on the predominant data models. The work presented deals with this problem: an automated method for construction is introduced and explained. A particular contribution of my thesis is the proposition to use hierarchical graphs as the basis for an extensible, flexible architecture for modelling various (geo)spatial networks. The proposed approach complements classical graph models very well in the sense that their expressiveness is extended: various graphs originating from different sources can be integrated into a comprehensive, multi-level model. This more sophisticated kind of architecture allows for extending navigation services beyond the borders of one single spatial network to a collection of heterogeneous networks, thus establishing a meta-navigation service. Another point of discussion is the impact of the hierarchy and distribution on graph algorithms. They have to be adapted to properly operate on multi-level hierarchies. By investigating indoor navigation problems in particular, the guiding principles are demonstrated for modelling networks at multiple levels of detail. Complex environments like large public buildings are ideally suited to demonstrate the versatile use of hierarchical graphs and thus to highlight the benefits of the hierarchical approach. Starting from a collection of floor plans, I have developed a systematic method for constructing a multi-level graph hierarchy. The nature of indoor environments, especially their inherent diversity, poses an additional challenge: among others, one must deal with complex, irregular, and/or three-dimensional features. The proposed method is also motivated by practical considerations, such as not only finding shortest/fastest paths across rooms and floors, but also by providing descriptions for these paths which are easily understood by people. Beyond this, two novel aspects of using a hierarchy are discussed: one as an informed heuristic exploiting the specific characteristics of indoor environments in order to enhance classical, general-purpose graph search techniques. At the same time, as a convenient by- product of this method, clusters such as sections and wings can be detected. The other reason is to better deal with irregular, complex-shaped regions in a way that instructions can also be provided for these spaces. Previous approaches have not considered this problem. In summary, the main results of this work are: • hierarchical graphs are introduced as a general spatial data infrastructure. In particular, this architecture allows us to integrate different spatial networks originating from different sources. A small but useful set of operations is proposed for integrating these networks. In order to work in a hierarchical model, classical graph algorithms are generalised. This finding also has implications on the possible integration of separate navigation services and systems; • a novel set of core data structures and algorithms have been devised for modelling indoor environments. They cater to the unique characteristics of these environments and can be specifically used to provide enhanced navigation in buildings. Tested on models of several real buildings from our university, some preliminary but promising results were gained from a prototypical implementation and its application on the models

New Fundamental Technologies in Data Mining

The progress of data mining technology and large public popularity establish a need for a comprehensive text on the subject. The series of books entitled by "Data Mining" address the need by presenting in-depth description of novel mining algorithms and many useful applications. In addition to understanding each section deeply, the two books present useful hints and strategies to solving problems in the following chapters. The contributing authors have highlighted many future research directions that will foster multi-disciplinary collaborations and hence will lead to significant development in the field of data mining

Expanding the Horizons of Manufacturing: Towards Wide Integration, Smart Systems and Tools

This research topic aims at enterprise-wide modeling and optimization (EWMO) through the development and application of integrated modeling, simulation and optimization methodologies, and computer-aided tools for reliable and sustainable improvement opportunities within the entire manufacturing network (raw materials, production plants, distribution, retailers, and customers) and its components. This integrated approach incorporates information from the local primary control and supervisory modules into the scheduling/planning formulation. That makes it possible to dynamically react to incidents that occur in the network components at the appropriate decision-making level, requiring fewer resources, emitting less waste, and allowing for better responsiveness in changing market requirements and operational variations, reducing cost, waste, energy consumption and environmental impact, and increasing the benefits. More recently, the exploitation of new technology integration, such as through semantic models in formal knowledge models, allows for the capture and utilization of domain knowledge, human knowledge, and expert knowledge toward comprehensive intelligent management. Otherwise, the development of advanced technologies and tools, such as cyber-physical systems, the Internet of Things, the Industrial Internet of Things, Artificial Intelligence, Big Data, Cloud Computing, Blockchain, etc., have captured the attention of manufacturing enterprises toward intelligent manufacturing systems

Polyphonic structures : modular models and modular forms (a creative investigation of mobile musical architectures)

Polyphonic Structures: Modular models and modular forms is a creative research project that 1 exploits the relations between independent pieces, structures and sonic events as self-contained moments. The dissertation describes a number of general and particular compositional strategies, techniques and constructivist explorations which are intimately related to the compositions included in the portfolio as a single body of work. The doctoral research includes a portfolio of the following compositions; Apposition (figures of disorder), Archipiélago, 24-Modular Cells, Free Module Study nº1, Systematic Double Bind and Within Modular Objects. Combining different pieces as polyphonic structures, in part or in total, to create new works, and the development of novel compositional strategies through interrelated pieces, have been explored by many composers. The most influential of these is Karlheinz Stockhausen. His ideas to interconnect pieces within a distinctive variety of compositional procedures have been the prime musical concepts from which the research dissertation and original works germinated. However the exploration of the ideas develop by Iannis Xenakis in theory of grains of sounds and Curtis Roads in Microsound has been crucial to define the modularity. Ultimately, the conception of Brian Ferneyhough’s figure and gesture has been crucial to incorporate micro-modules as self-contained singularities. Moreover, the research is an attempt to establish methodological linkages between self-contained and self-sufficient units. In this manner, the study of Bertrand Russell’s logical atomism help me to define the smaller unit in a musical context. Accordingly, modularity has been used as a key element to define the structural and analytical method throughout the dissertation. Furthermore, Gilles Deleuze and Pierre-Félix Guattari’s rhizome theory turned out to provide a valuable framework to establish a conceptual link generator.Thus, the commentary summarises a personal approach to some of the principal issues related to contextual discontinuity and multi-layer structuralism. However, no matter how vital rhizome theory has been, the use of dichotomies and the linear process has not been completely avoided.The inquiry into new forms of interaction has led the research to map possible strategies to break the traditional binary thinking and linear unidirectional processes. The documentation of the compositional techniques, concepts and structures presented in the following dissertation has the sole intention of defining a particular and personal methodological framework

Ubiquitous User Modeling

More and more interactions take place between humans and mobile or connected IT-systems in daily life. This offers a great opportunity, especially to user modeling, to reach better adaptation with ongoing evaluation of user behavior. This work develops a complete framework to realize the newly defined concept of ubiquitous user modeling. The developed tools cover methods for the uniform exchange and the semantic integration of partial user models. They also account for the extended needs for privacy and the right of every human for introspection and control of their collected data. The SITUATIONALSTATEMENTS and the exchange language USERML have been developed on the syntactical level, while the general user model ontology GUMO and the UBISWORLD ontology have been developed on the semantical level. A multilevel conflict resolution method, which handles the problem of contradictory statements, has been implemented together with a web-based user model service, such that the road capability and the scalability can be proven with this approach.Immer häufiger auftretende Interaktionen im täglichen Leben zwischen Menschen und vernetzten oder mobilen IT-Systemen bieten insbesondere für die Benutzermodellierung eine große Chance, durch ständige Evaluation des Benutzerverhaltens verbesserte Adaptionsleistungen zu erzielen. Die vorliegende Arbeit entwickelt ein komplettes Rahmensystem, um dieses neu definierte Konzept der ubiquitären Benutzermodellierung zu realisieren. Die erarbeiteten Werkzeuge umfassen Methoden zum einheitlichen Austausch und zur semantischen Integration von partiellen Benutzermodellen. Sie berücksichtigen aber auch die erhöhten Anforderungen an die Privatsphäre, sowie das Recht der Menschen auf Introspektion und Kontrolle über die erhobenen Daten. Auf syntaktischer Ebene werden die situationsbeschreibenden Aussagen sowie die Austauschsprache UserML entworfen. Auf semantischer Ebene werden die allgemeine Benutzermodell-Ontologie GUMO und die UBISWELT-Ontologie entwickelt. Ein mehrstufiger Konfliktlösungsmechanismus, der das Problem sich widersprechender Aussagen bearbeitet, wird zusammen mit einem webbasierten Benutzermodell-Service implementiert, sodass die Praxistauglichkeit und die Skalierbarkeit dieses Ansatzes an mehreren Beispielen gezeigt werden kann