AN EXPERT SYSTEM FOR SOLVENT-EXTRACTION OF RARE-EARTHS

An expert system for solvent extraction of rare earths has been developed using LISP. The goal of this project was to mimic the chemists' inferential abilities to assist in the process of solvent extraction of rare earths. The system includes frequently used extractants, separation of specific rare earths, recommendation of procedures for the separation of mixtures of rare earths using (2-ethylhexyl)phosphonic acid 2-ethylhexyl monoester, selection of parameters for counter-current extraction and methods for evaluation of the technique, and the economics of the processing. The expert system runs on an IBM-PC/XT.

CIAC COMPREHENSIVE INFORMATION-SYSTEM OF RARE-EARTHS

The CIAC (Changchun Institute of Applied Chemistry) Comprehensive information System of Rare Earths is composed of three subsystems, namely, extraction data, physicochemical properties, and reference data. This paper describes the databases pertaining to the extraction of rare earths and their physicochemical properties and discusses the relationships between data retrieval and optimization and between the structures of the extractants and the efficiency with which they are extracted. Expert systems for rare earth extraction and calculation of thermodynamic parameters are described, and an application of pattern recognition to the problems of classification of compounds of the rare earths and prediction of their properties is reported.

An Empirical Study of the Use of Relevance Information in Inductive Logic Programming

Srinivasan, A., King, R. D. and Bain, M.E. (2003) An Empirical Study of the Use of Relevance Information in Inductive Logic Programming. Journal of Machine Learning Research. 4(Jul):369-383

Evaluating SWICE-R (South West Information for Clinical Effectiveness - Rural). Final report for South West Workforce Development Confederations (Knowledge Resources Development Unit)

Yeoman, A., Durbin, J. & Urquhart, C. (2004). Evaluating SWICE-R (South West Information for Clinical Effectiveness - Rural). Final report for South West Workforce Development Confederations, (Knowledge Resources Development Unit). Aberystwyth: Department of Information Studies, University of Wales Aberystwyth. Sponsorship: South West WDCs (NHS)

Information Fusion and Hierarchical Knowledge Discovery by ARTMAP Neural Networks

Mapping novel terrain from sparse, complex data often requires the resolution of conflicting information from sensors working at different times, locations, and scales, and from experts with different goals and situations. Information fusion methods help resolve inconsistencies in order to distinguish correct from incorrect answers, as when evidence variously suggests that an object's class is car, truck, or airplane. The methods developed here consider a complementary problem, supposing that information from sensors and experts is reliable though inconsistent, as when evidence suggests that an objects class is car, vehicle, or man-made. Underlying relationships among objects are assumed to be unknown to the automated system of 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 hierarchial knowledge structures. The 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.

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.

Requirements and design of an integrated European environmental information communication system, (IEEICS)

The needs for various forms of information systems relating to the European environment and ecosystem are reviewed, and limitations indicated. Existing information systems are reviewed and compared in terms of aims and functionalities. We consider TWO technical challenges involved in attempting to develop an IEEICS. First, there is the challenge of developing an Internet-based communication system which allows fluent access to information stored in a range of distributed databases. Some of the currently available solutions are considered, i.e. Web service federations. The second main challenge arises from the fact that there is general intra-national heterogeneity in the definitions adopted, and the measurement systems used throughout the nations of Europe. Integrated strategies are needed.

The ParaWise expert assistant - widening accessibility to efficient and scalable tool Generated OpenMP code

Despite the apparent simplicity of the OpenMP directive shared memory programming model and the sophisticated dependence analysis and code generation capabilities of the ParaWise/CAPO tools, experience shows that a level of expertise is required to produce efficient parallel code. In a real world application the investigation of a single loop in a generated parallel code can soon become an in-depth inspection of numerous dependencies in many routines. The additional understanding of dependencies is also needed to effectively interpret the information provided and supply the required feedback. The ParaWise Expert Assistant has been developed to automate this investigation and present questions to the user about, and in the context of, their application code. In this paper, we demonstrate that knowledge of dependence information and OpenMP are no longer essential to produce efficient parallel code with the Expert Assistant. It is hoped that this will enable a far wider audience to use the tools and subsequently, exploit the benefits of large parallel systems.

Fast and frugal models of clinical judgement in novice and expert physicians

Our objective was to study whether “compensatory” models provide better descriptions of clinical judgment than fast and frugal models, according to expertise and experience. Fifty practitioners appraised 60 vignettes describing a child with an exacerbation of asthma and rated their propensities to admit the child. Linear logistic (LL) models of their judgments were compared with a matching heuristic (MH) model that searched available cues in order of importance for a critical value indicating an admission decision. There was a small difference between the 2 models in the proportion of patients allocated correctly (admit or not-admit decisions), 91.2% and 87.8%, respectively. The proportion allocated correctly by the LL model was lower for consultants than juniors, whereas the MH model performed equally well for both. In this vignette study, neither model provided any better description of judgments made by consultants or by pediatricians compared to other grades and specialties.

Anatomy and Neurophysiology of Coughing: CHEST Guideline and Expert Panel Report

Bronchopulmonary C-fibers and a subset of mechanically sensitive, acid-sensitive myelinated sensory nerves play essential roles in regulating cough. These vagal sensory nerves terminate primarily in the larynx, trachea, carina and large intrapulmonary bronchi. Other bronchopulmonary sensory nerves, sensory nerves innervating other viscera as well as somatosensory nerves innervating the chest wall, diaphragm and abdominal musculature regulate cough patterning and cough sensitivity. The responsiveness and morphology of the airway vagal sensory nerve subtypes and the extrapulmonary sensory nerves that regulate coughing are described. The brainstem and higher brain control systems that process this sensory information are complex, but our current understanding of them is considerable and increasing. The relevance of these neural systems to clinical phenomena, such as urge to cough and psychological methods for treatment of dystussia, is high and modern imaging methods have revealed potential neural substrates for some features of cough in the human.

Defining the content and delivery of an intervention to Change AdhereNce to treatment in BonchiEctasis (CAN-BE): a qualitative approach incorporating the Theoretical Domains Framework, behavioural change techniques and stakeholder expert panels

Background
Low patient adherence to treatment is associated with poorer health outcomes in bronchiectasis. We sought to use the Theoretical Domains Framework (TDF) (a framework derived from 33 psychological theories) and behavioural change techniques (BCTs) to define the content of an intervention to change patients’ adherence in bronchiectasis (Stage 1 and 2) and stakeholder expert panels to define its delivery (Stage 3).

Methods
We conducted semi-structured interviews with patients with bronchiectasis about barriers and motivators to adherence to treatment and focus groups or interviews with bronchiectasis healthcare professionals (HCPs) about their ability to change patients’ adherence to treatment. We coded these data to the 12 domain TDF to identify relevant domains for patients and HCPs (Stage 1). Three researchers independently mapped relevant domains for patients and HCPs to a list of 35 BCTs to identify two lists (patient and HCP) of potential BCTs for inclusion (Stage 2). We presented these lists to three expert panels (two with patients and one with HCPs/academics from across the UK). We asked panels who the intervention should target, who should deliver it, at what intensity, in what format and setting, and using which outcome measures (Stage 3).

Results
Eight TDF domains were perceived to influence patients’ and HCPs’ behaviours: Knowledge, Skills, Beliefs about capability, Beliefs about consequences, Motivation, Social influences, Behavioural regulation and Nature of behaviours (Stage 1). Twelve BCTs common to patients and HCPs were included in the intervention: Monitoring, Self-monitoring, Feedback, Action planning, Problem solving, Persuasive communication, Goal/target specified:behaviour/outcome, Information regarding behaviour/outcome, Role play, Social support and Cognitive restructuring (Stage 2). Participants thought that an individualised combination of these BCTs should be delivered to all patients, by a member of staff, over several one-to-one and/or group visits in secondary care. Efficacy should be measured using pulmonary exacerbations, hospital admissions and quality of life (Stage 3).

Conclusions
Twelve BCTs form the intervention content. An individualised selection from these 12 BCTs will be delivered to all patients over several face-to-face visits in secondary care. Future research should focus on developing physical materials to aid delivery of the intervention prior to feasibility and pilot testing. If effective, this intervention may improve adherence and health outcomes for those with bronchiectasis in the future.

Role of Automated Open Source Systems in the Intelligence Analysis of a High-Level Domain Expert

The role of implicit theories in the formation of expert opinion in portuguese criminal law

Tese de doutoramento, Ciências e Tecnologias da Saúde (Medicina Legal e Ciências Forenses), Universidade de Lisboa, Faculdade de Medicina, 2014