Change impact on a product and its redesign process: A tool for knowledge capture and reuse

Change propagates, potentially affecting many aspects of a design and requiring much rework to implement. This article introduces a cross-domain approach to decompose a design and identify possible change propagation linkages, complemented by an interactive tool that generates dynamic checklists to assess change impact. The approach considers the information domains of requirements, functions, components, and the detail design process. Laboratory experiments using a vacuum cleaner suggest that cross-domain modelling helps analyse a design to create and capture the information required for change prediction. Further experiments using an electronic product show that this information, coupled with the interactive tool, helps to quickly and consistently assess the impact of a proposed change. © 2012 Springer-Verlag London Limited.

The Role of Knowledge in Visual Shape Representation

This report shows how knowledge about the visual world can be built into a shape representation in the form of a descriptive vocabulary making explicit the important geometrical relationships comprising objects' shapes. Two computational tools are offered: (1) Shapestokens are placed on a Scale-Space Blackboard, (2) Dimensionality-reduction captures deformation classes in configurations of tokens. Knowledge lies in the token types and deformation classes tailored to the constraints and regularities ofparticular shape worlds. A hierarchical shape vocabulary has been implemented supporting several later visual tasks in the two-dimensional shape domain of the dorsal fins of fishes.

A Study of Qualitative and Geometric Knowledge in Reasoning about Motion

Reasoning about motion is an important part of our commonsense knowledge, involving fluent spatial reasoning. This work studies the qualitative and geometric knowledge required to reason in a world that consists of balls moving through space constrained by collisions with surfaces, including dissipative forces and multiple moving objects. An analog geometry representation serves the program as a diagram, allowing many spatial questions to be answered by numeric calculation. It also provides the foundation for the construction and use of place vocabulary, the symbolic descriptions of space required to do qualitative reasoning about motion in the domain. The actual motion of a ball is described as a network consisting of descriptions of qualitatively distinct types of motion. Implementing the elements of these networks in a constraint language allows the same elements to be used for both analysis and simulation of motion. A qualitative description of the actual motion is also used to check the consistency of assumptions about motion. A process of qualitative simulation is used to describe the kinds of motion possible from some state. The ambiguity inherent in such a description can be reduced by assumptions about physical properties of the ball or assumptions about its motion. Each assumption directly rules out some kinds of motion, but other knowledge is required to determine the indirect consequences of making these assumptions. Some of this knowledge is domain dependent and relies heavily on spatial descriptions.

A dichotomic search algorithm for mining and learning in domain-specific logics

Ferr?, S. and King, R. D. (2004) A dichotomic search algorithm for mining and learning in domain-specific logics. Fundamenta Informaticae. IOS Press. To appear

The Australian aboriginal and the Christian church

http://www.archive.org/details/australianaborig00pittuoft

Self-Organizing Information Fusion and Hierarchical Knowledge Discovery: A New Framework Using Artmap Neural Networks

Classifying novel terrain or objects from sparse, complex data may require the resolution of conflicting information from sensors woring at different times, locations, and scales, and from sources with different goals and situations. Information fusion methods can help resolve inconsistencies, as when eveidence variously suggests that and object's class is car, truck, or airplane. The methods described her address a complementary problem, supposing that information from sensors and experts is reliable though inconsistent, as when evidence suggests that an object's class is car, vehicle, and man-made. Underlying relationships among classes are assumed to be unknown to the autonomated system or the human user. The ARTMAP information fusion system uses distributed code representations that exploit the neural network's capacity for one-to-many learning in order to produce self-organizing expert systems that discover hierachical knowlege structures. The fusion system infers multi-level relationships among groups of output classes, without any supervised labeling of these relationships. The procedure is illustrated with two image examples, but is not limited to image domain.

Hazard and early warning analysis based on domain specific modeling technologies

An aim of proactive risk management strategies is the timely identification of safety related risks. One way to achieve this is by deploying early warning systems. Early warning systems aim to provide useful information on the presence of potential threats to the system, the level of vulnerability of a system, or both of these, in a timely manner. This information can then be used to take proactive safety measures. The United Nation’s has recommended that any early warning system need to have four essential elements, which are the risk knowledge element, a monitoring and warning service, dissemination and communication and a response capability. This research deals with the risk knowledge element of an early warning system. The risk knowledge element of an early warning system contains models of possible accident scenarios. These accident scenarios are created by using hazard analysis techniques, which are categorised as traditional and contemporary. The assumption in traditional hazard analysis techniques is that accidents are occurred due to a sequence of events, whereas, the assumption of contemporary hazard analysis techniques is that safety is an emergent property of complex systems. The problem is that there is no availability of a software editor which can be used by analysts to create models of accident scenarios based on contemporary hazard analysis techniques and generate computer code that represent the models at the same time. This research aims to enhance the process of generating computer code based on graphical models that associate early warning signs and causal factors to a hazard, based on contemporary hazard analyses techniques. For this purpose, the thesis investigates the use of Domain Specific Modeling (DSM) technologies. The contributions of this thesis is the design and development of a set of three graphical Domain Specific Modeling languages (DSML)s, that when combined together, provide all of the necessary constructs that will enable safety experts and practitioners to conduct hazard and early warning analysis based on a contemporary hazard analysis approach. The languages represent those elements and relations necessary to define accident scenarios and their associated early warning signs. The three DSMLs were incorporated in to a prototype software editor that enables safety scientists and practitioners to create and edit hazard and early warning analysis models in a usable manner and as a result to generate executable code automatically. This research proves that the DSM technologies can be used to develop a set of three DSMLs which can allow user to conduct hazard and early warning analysis in more usable manner. Furthermore, the three DSMLs and their dedicated editor, which are presented in this thesis, may provide a significant enhancement to the process of creating the risk knowledge element of computer based early warning systems.

TEACHING HIGH SCHOOL STUDENTS THE BEST CHORAL REPERTOIRE FROM THE GREAT COMPOSERS: MASTERWORKS AVAILABLE FOR IMMEDIATE, FREE ACCESS FROM THE CHORAL PUBLIC DOMAIN LIBRARY

Studying the choral works of the great composers of the past is always a worthy endeavor. For those aspiring to create an excellent high school choral program, it is critical to a student's musical foundation and heritage. Choral educators who teach high school are often bombarded with the most recently published new choral works, when they have a trove of excellent pieces right at their fingertips through websites like the Choral Public Domain Library (CPDL), all available at no cost. This project will explore the pedagogical reasons why this canon of public domain choral music should be taught at the high school level. A thorough guide to CPDL and an anthology of 200 works available on CPDL will provide the conductor with resources for programming this music. Though choral music in the public domain is free to all, publishers still publish this music and adhere copyright claims. This can create mistrust of legitimate editions on CPDL; why are they available at no cost when publishers are claiming copyright on similar editions? These issues will be thoroughly discussed in this project. For any given work on CPDL, there may be multiple editions available on the site. Choosing the right edition requires knowledge about basic editorial principles, especially for works written during the Renaissance period. A detailed discussion of these principles will provide the conductor with the tools needed to choose the best edition for his or her ensemble.

A knowledge-based system to represent spatial reasoning for fire modelling

This paper describes the architecture of the knowledge based system (KBS) component of Smartfire, a fire field modelling tool for use by members of the fire safety engineering community who are not expert in modelling techniques. The KBS captures the qualitative reasoning of an experienced modeller in the assessment of room geometries, so as to set up the important initial parameters of the problem. Fire modelling expertise is an example of geometric and spatial reasoning, which raises representational problems. The approach taken in this project is a qualitative representation of geometric room information based on Forbus’ concept of a metric diagram. This takes the form of a coarse grid, partitioning the domain in each of the three spatial dimensions. Inference over the representation is performed using a case-based reasoning (CBR) component. The CBR component stores example partitions with key set-up parameters; this paper concentrates on the key parameter of grid cell distribution.

A framework to integrate design knowledge reuse and requirements management in engineering design

This paper presents a framework to integrate requirements management and design knowledge reuse. The research approach begins with a literature review in design reuse and requirements management to identify appropriate methods within each domain. A framework is proposed based on the identified requirements. The framework is then demonstrated using a case study example: vacuum pump design. Requirements are presented as a component of the integrated design knowledge framework. The proposed framework enables the application of requirements management as a dynamic process, including capture, analysis and recording of requirements. It takes account of the evolving requirements and the dynamic nature of the interaction between requirements and product structure through the various stages of product development.

Design process knowledge reuse challenges and issues

Product knowledge support needs are compared in two companies with different production volumes and product complexity. Knowledge support requirements identified include: function, performance data, requirements data, common parts, regulatory guidelines and layout data. A process based data driven knowledge reuse method is evaluated in light of the identified product knowledge needs. The evaluation takes place through developing a pilot case with each company. It is found that the method provides more benefit to the high complexity design domain, in which a significant amount of work takes place at the conceptual design stages, relying on a conceptual product representation. There is not such a clear value proposition in a design environment whose main challenge is layout design and the application of standard parts and features. The method supports the requirement for conceptual product representation but does not fully support a standard parts library.

Effects of training peer tutors in content knowledge versus tutoring skills on giving feedback to help tutees’ complex tasks

This study aims to investigate the effectiveness of training tutors in content knowledge of a particular domain versus training them in tutoring skills of pedagogical knowledge when tutoring on a complex tutee task. Forty-seven tutor-tutee pairs of fourth year secondary school students were created and assigned to one of two treatments. Twenty-two tutors received training in content knowledge and the other twenty-five tutors in tutoring skills. Tutors formulated written feedback immediately after the training. Tutees first interpreted the tutor feedback and then used it to revise their research questions. The results showed that tutors trained in tutoring skills formulated more effective feedback than tutors trained in content knowledge. In addition, tutees helped by tutoring-skills tutors found the feedback more motivating than those helped by content- knowledge tutors. However, no differences were found in tutee performance on revision. The findings are discussed in terms of the set-up of this study and implications for improving the effectiveness of peer tutoring.

Belief, Knowledge and Expertise. The emergence of the lay expert in medical sociology

The paper has three main aims. First, to trace – through the pages of the Journal – the changing ways in which lay understandings of health and illness have been represented during the 1979-2002 period. Second, to say something about the limits of lay knowledge (and particularly lay expertise) in matters of health and medicine. Third, to call for a re-assessment of what lay people can offer to a democratised and customer sensitive system of health care and to attempt to draw a boundary around the domain of expertise. In following through on those aims, the author calls upon data derived from three current projects. These latter concern the diagnosis of Alzheimer’s disease in people with Down’s syndrome; the development of an outcome measure for people who have suffered a traumatic brain injury; and a study of why older people might reject annual influenza vaccinations. Key words: Lay health beliefs, lay expertise, Alzheimer’s, Traumatic Brain Injury, Vaccinations

Patient safety and communication: A new assessment for doctors trained in countries where language differs from that of the host country: Results of a pilot using a domain-based assessment

Objective

Global migration of healthcare workers places responsibility on employers to comply with legal employment rights whilst ensuring patient safety remains the central goal. We describe the pilot of a communication assessment designed for doctors who trained and communicated with patients and colleagues in a different language from that of the host country. It is unique in assessing clinical communication without assessing knowledge.

A 14-station OSCE was developed using a domain-based marking scheme, covering professional communication and English language skills (speaking, listening, reading and writing) in routine, acute and emotionally challenging contexts, with patients, carers and healthcare teams. Candidates (n = 43), non-UK trained volunteers applying to the UK Foundation Programme, were provided with relevant station information prior to the exam.

The criteria for passing the test included achieving the pass score and passing 10 or more of the 14 stations. Of the 43 candidates, nine failed on the station criteria. Two failed the pass score and also the station criteria. The Cronbach's alpha coefficient was 0.866.

This pilot tested ‘proof of concept’ of a new domain-based communication assessment for non-UK trained doctors.

The test would enable employers and regulators to verify communication competence and safety in clinical contexts, independent of clinical knowledge, for doctors who trained in a language different from that of the host country.

Knowledge Management Techniques to Augment Textual CBR (PhD Thesis)

The past decade had witnessed an unprecedented growth in the amount of available digital content, and its volume is expected to continue to grow the next few years. Unstructured text data generated from web and enterprise sources form a large fraction of such content. Many of these contain large volumes of reusable data such as solutions to frequently occurring problems, and general know-how that may be reused in appropriate contexts. In this work, we address issues around leveraging unstructured text data from sources as diverse as the web and the enterprise within the Case-based Reasoning framework. Case-based Reasoning (CBR) provides a framework and methodology for systematic reuse of historical knowledge that is available in the form of problemsolution
pairs, in solving new problems. Here, we consider possibilities of enhancing Textual CBR systems under three main themes: procurement, maintenance and retrieval. We adapt and build upon the stateof-the-art techniques from data mining and natural language processing in addressing various challenges therein. Under procurement, we investigate the problem of extracting cases (i.e., problem-solution pairs) from data sources such as incident/experience
reports. We develop case-base maintenance methods specifically tuned to text targeted towards retaining solutions such that the utility of the filtered case base in solving new problems is maximized. Further, we address the problem of query suggestions for textual case-bases and show that exploiting the problem-solution partition can enhance retrieval effectiveness by prioritizing more useful query suggestions. Additionally, we illustrate interpretable clustering as a tool to drill-down to domain specific text collections (since CBR systems are usually very domain specific) and develop techniques for improved similarity assessment in social media sources such as microblogs. Through extensive empirical evaluations, we illustrate the improvements that we are able to
achieve over the state-of-the-art methods for the respective tasks.