Semantic Transparency,Brain Monitoring and Evaluation of Hybrid Cognitive Architectures

In constructing hybrid systems, there is a need for a principled basis to determine the relative roles or functions of artificial neural network and symbolic approaches. The primary objective of the work to be reported is the construction of a conceptual and methodological framework that permits an iterative sequence in which a hybrid model predicts the basis of cognitive performance and an objective analysis of performance provides empirical data, evaluating (and thus constraining) the structure and processes of the model. In seeking a linkage between a hybrid model of cognition and human performance the concept of “semantic transparency” has been adopted, since it can be used in analyzing and describing both the chracteristics of a model of cognition and the processes underlying human performance. An overview of a specific, ”strong” hybrid architecture is presented. The characteristics of the virtual machines which compose it and the nature of their interaction are illustrated. An approach to the questions of evaluation is described based on empirical data obtained by brain monitoring of subjects during cognitive performance.     

CHARACTERISATION OF PATTERNS OF CHEWING BEHAVIOUR IN HUMAN SUBJECTS AND THEIR INFLUENCE ON TEXTURE PERCEPTION

Electromyography was used as a noninvasive and unobtrusive technique to characterise chewing patterns for a range of foods. Differences between subjects for a variety of aspects of chewing sequence are recorded for a range of foods (carrot, apple, roast pork, salami, biscuit and toast). Identifiable subgroups of subjects differing in chewing behaviour existed within the random sample of 52 dentate subjects. The five subgroups accounted for 52%, 21%, 11%, 10% and 6% of the sample population. Major discriminating factors between the behavioural groups lie in their chewing time and the muscle work rate during chewing. Sensory ratings for firmness and rubberiness of model foods differed significantly between the subjects exhibiting different chewing behaviours. Chewing behaviour may influence consumers' perceptions about the texture of a food.     

High-pressure-induced changes in bovine milk: a review

High-pressure (HP) treatment of food products is a novel processing technique during which the product is treated in a vessel of suitable strength at a high pressure, generally in the range 100–1000 MPa. As a result, several constituents and properties of the treated product are altered. HP-induced changes in the constituents and properties of milk are arguably among the most extensive of the range of food products studied to date. HP treatment of milk induces solubilization of minerals associated with the casein micelles, denatures whey proteins and, depending on pressure, can either induce aggregation or disruption of the casein micelles. These HP-induced changes in milk constituents affect the properties of the milk; cheesemaking properties of milk can be enhanced considerably, indicating potential application of HP treatment in this area; furthermore, encouraging results have also been reported for HP treatment of milk prior to yogurt manufacture. HP treatment of milk also affects its microflora; however, considerable variation in baroresistance between bacterial species and strains exists. Further applied research appears warranted to establish the full commercial potential of HP treatment of milk.     

Stability of Aqueous α-Al2O3 Suspensions with Poly(methacrylic acid) Polyelectrolyte

Stability of aqueous α-Al₂O₃ suspensions with Na⁺ salt of poly(methacrylic acid) (PMAA-Na) polyelectrolyte was studied as a function of pH. At a given pH, the transition from the flocculated to the dispersed state corresponded to the adsorption saturation limit of the powders by the PMAA. As the pH was decreased, the adsorption saturation limit increased until insolubility and charge neutralization of the PMAA was approached. The critical amount of PMAA required to achieve stability is outlined in a stability map.     

CASTLES IN TORONTO'S SKY: CONDO‐ISM AS URBAN TRANSFORMATION

This article analyzes the evolution and spatial dynamics of condominium development in Toronto, the largest housing market in Canada and the site of a rapid take‐up of condominium tenure and construction over the last 40 years. The article probes the most influential policies that fostered and regulated condominium growth, and explores the implications for the continued restructuring of the city. A host of factors, including neoliberal state policies, have played a decisive role in fostering what we term condo‐ism, referring to an emerging nexus of economic development, finance, and consumption sector interests that have coalesced around condominium construction and culture. Policies have redirected growth to the urban core, channeled capital investments and young residents, and promoted gentrification, ultimately transforming the character of Toronto's central business district. The article explores these changes, and discusses their implications for contemporary emerging forms of capitalist urbanization and restructuring of the city.     

COUNTERCONDITIONING THERAPY USING FREE ASSOCIATION: A PILOT STUDY.

DESCRIBES THE TREATMENT OF 2 SEVERELY NEUROTIC PATIENTS BY DESENSITIZATION USING FREE ASSOCIATION IN CONJUNCTION WITH MUSCLE RELAXATION. THIS THERAPY USED NO PREPLANNED FEAR HIERARCHIES; RATHER, THE SS SELECTED THEIR OWN MATERIAL AND THE RATE AT WHICH THEY DEALT WITH THAT MATERIAL IN EACH SESSION. PROCEDURES FOR TEACHING MORE EFFECTIVE INTERPERSONAL BEHAVIOR WERE USED WITH BOTH SS FOLLOWING COMPLETION OF COUNTERCONDITIONING. IN BOTH CASES, THE RATE OF IMPROVEMENT DURING COUNTERCONDITIONING WAS AT LEAST AS RAPID AS THAT REPORTED FOR COUNTERCONDITIONING USING HIERARCHIES OF SCENES. THE USE OF FREE ASSOCIATION OFFERS IMPORTANT ADVANTAGES WHERE AN S'S SOURCES OF ANXIETY ARE DIFFICULT TO ISOLATE AND SCALE FOR INTENSITY. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A ROUGH SET/FUZZY LOGIC BASED DECISION MAKING SYSTEM FOR MEDICAL APPLICATIONS

Abstract

A method of performing prognostic modeling of disease states is proposed. The technique uses rough sets to extract rules from a database. The data is then reformatted into a fuzzy logic template, and a learning algorithm is used to adjust the fuzzy set membership functions. The method is applied to the POSCH problem, which looks at risk factors associated with the progression of coronary artery disease. The POSCH data has several shortcomings, including a limited number of cases, correlated inputs, as well as noise on both the inputs and outcome. The problem was to predict progression of atherosclerosis in the LAD three years after baseline based on physiologic data available at baseline. The proposed rough/fuzzy set method correctly predicted progression of atherosclerotic disease in 69% of the patients, which is statistically better than neural network, rough set and logistic models performed.