Capture and Maintenance of Constraints in Engineering Design

The thesis investigates two domains, initially the kite domain and then part of a more demanding Rolls-Royce domain (jet engine design). Four main types of refinement rules that use the associated application conditions and domain ontology to support the maintenance of constraints are proposed. The refinement rules have been implemented in ConEditor and the extended system is known as ConEditor+. With the help of ConEditor+, the thesis demonstrates that an explicit representation of application conditions together with the corresponding constraints and the domain ontology can be used to detect inconsistencies, redundancy, subsumption and fusion, reduce the number of spurious inconsistencies and prevent the identification of inappropriate refinements of redundancy, subsumption and fusion between pairs of constraints.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Knowledge-based best of breed approach for automated detection of clinical events based on German free text digital hospital discharge letters

OBJECTIVES: The secondary use of medical data contained in electronic medical records, such as hospital discharge letters, is a valuable resource for the improvement of clinical care (e.g. in terms of medication safety) or for research purposes. However, the automated processing and analysis of medical free text still poses a huge challenge to available natural language processing (NLP) systems. The aim of this study was to implement a knowledge-based best of breed approach, combining a terminology server with integrated ontology, a NLP pipeline and a rules engine. METHODS: We tested the performance of this approach in a use case. The clinical event of interest was the particular drug-disease interaction "proton-pump inhibitor [PPI] use and osteoporosis". Cases were to be identified based on free text digital discharge letters as source of information. Automated detection was validated against a gold standard. RESULTS: Precision of recognition of osteoporosis was 94.19%, and recall was 97.45%. PPIs were detected with 100% precision and 97.97% recall. The F-score for the detection of the given drug-disease-interaction was 96,13%. CONCLUSION: We could show that our approach of combining a NLP pipeline, a terminology server, and a rules engine for the purpose of automated detection of clinical events such as drug-disease interactions from free text digital hospital discharge letters was effective. There is huge potential for the implementation in clinical and research contexts, as this approach enables analyses of very high numbers of medical free text documents within a short time period

Developmental changes in the critical information used for facial expression processing

Facial expression recognition skills are known to improve across childhood and adolescence, but the mechanisms driving the development of these important social abilities remain unclear. This study investigates directly whether there are qualitative differences in child and adult processing strategies for these emotional stimuli. With a novel adaptation of the Bubbles reverse-correlation paradigm (Gosselin & Schyns, 2001), we added noise to expressive face stimuli and presented sub-sets of randomly sampled information from each image at different locations and spatial frequency bands across experimental trials. Results from our large developmental sample: 71 young children (6 -9 years), 69 older children (10-13 years) and 54 adults, uniquely reveal flexible profiles of strategic information-use for categorisations of fear, sadness, happiness and anger at all ages. All three groups relied upon a distinct set of key facial features for each of these expressions, with fine-tuning of this diagnostic information (features and spatial frequency) observed across developmental time. Reported variability in the developmental trajectories for different emotional expressions is consistent with the notion of functional links between the refinement of information-use and processing ability

Conceptual model of sport-specific classification for para-athletes with intellectual impairment

The present paper describes the conceptual basis of evidence-based classification of para-athletes with intellectual impairment (II). An extensive description of the theoretical and conceptual foundation of the system as currently conceived is provided, as are examples of its applications in the three sports included in the Paralympic programme for II-athletes in 2020 (i.e., athletics, swimming and table tennis). Evidence based classification for II-athletes is driven by two central questions: i. How can intellectual impairment be substantiated in a valid and reliable way, and ii. Does intellectual impairment limit optimal sport proficiency? Evolution of the system and current best practice for addressing these questions are described, and suggestions for future research and development are provided. Challenges of understanding and assessing a complex (multifaceted and intersectional) impairment in the context of sport also are considered

A knowledge acquisition assistant for the expert system shell Nexpert-Object

This study addresses the problems of knowledge acquisition in expert system development examines programs whose goal is to solve part of these problems. Among them are knowledge acquisition tools, which provide the knowledge engineer with a set of Artificial Intelligence primitives, knowledge acquisition aids, which offer to the knowledge engineer a guidance in knowledge elicitation, and finally, automated systems, which try to replace the human interviewer with a machine interface. We propose an alternative technique to these approaches: an interactive syntactic analyzer of an emerging knowledge base written with the expert system shell called Nexpert Object. This program intends to help the knowledge engineer during the editing of a knowledge base, both from a knowledge engineering and a knowledge representation point of view. The implementation is a Desk Accessory written in C, running on Macintosh concurrently with Nexpert Object

Overview of modern contributions in vehicle noise and vibration refinement with special emphasis on diagnostics

U ovom radu prikazana su određena razmatranja vezana za karakteristike buke i vibracija savremenih motornih vozila. Pored naučnog, problematika se razmatra i sa praktičnog aspekta u cilju struktuiranja potrebnih znanja, neophodnih za pravilnu dijagnostiku problema. Takođe se razmatraju napredne analize signala buke i vibracija. Ova sinergija naučnog i praktičnog pristupa predstavlja osnovu za dalja napredna istraživanja.This paper presents certain considerations related to noise, vibration and harshness issues on modern motor vehicles. The first, practical aspect was used toward structuring of the acquired knowledge and relationships, required for proper problem diagnosis. On the other hand, advanced signal analyses are considered. The influence on human body is processed and certain noise and vibration analyzers are presented. This synergy of scientific and applicative approach represents a basis for further research related to this important automotive branch