Map Coordinate Referencing and the use of GPS Datasets in Ghana

The concepts of coordinate systems required to identify points in space and represent them on maps uses mathematical methods of assigning numbers, called coordinates to each point in space. There are different coordinate systems the commonest being the system of latitudes, longitudes and ellipsoidal heights. The situation is complicated because the latitudes and longitudes of the same point differ slightly depending on the geodetic coordinate system of a country, the result being that different systems of latitude and longitude in use for the same point can disagree in coordinates by more than 200 metres. The GPS for instance uses a WGS84 system and gives latitude and longitude values which can not be integrated directly into the mapping system of a country without suitable mathematical conversions. Similarly, it is not possible to just measure distances from a graticule map without appropriate projection conversions. In order to use data obtained from GPS measurements correctly and effectively in Ghana, we need to use appropriate transformation parameters that relate our Ghana National Survey Mapping coordinate system to that used for the Global Positioning System (GPS). Datum transformation parameters define functional relationship between two reference frames. This paper looked at geodetic coordinate systems and transformations between the WGS84 and the coordinate systems used in Ghana (the Ghana war office system and also the Clarke1880 system) using the Bursa-Wolf model. Particular attention was given to the derivation of ellipsoidal heights through the use of the Abridged Molodensky formulas. Keywords: Coordinate Systems, ellipsoidal heights, Global positioning System, WGS84, Transformation parameters Journal of Science and Technology Vol. 28 (1) 2008 pp. 116-12

Content & Watkins's account of natural axiomatizations

This paper briefly recounts the importance of the notion of natural axiomatizations for explicating hypothetico-deductivism, empirical significance, theoretical reduction, and organic fertility. Problems for the account of natural axiomatizations developed by John Watkins in Science and Scepticism and the revised account developed by Elie Zahar are demonstrated. It is then shown that Watkins's account can be salvaged from various counter-examples in a principled way by adding the demand that every axiom of a natural axiomatization should be part of the content of the theory being axiomatized. The crucial point here is that content cannot simply be identified with the set of logical consequences of a theory, but must be restricted to a proper subset of the consequence set. It is concluded that the revised Watkins account has certain advantages over the account of natural axiomatizations offered in Gemes (1993)

Young children's research: children aged 4-8 years finding solutions at home and at school

Children's research capacities have become increasingly recognised by adults, yet children remain excluded from the academy, with reports of their research participation generally located in adults' agenda. Such practice restricts children's freedom to make choices in matters affecting them, underestimates children’s capabilities and denies children particular rights. The present paper reports on one aspect of a small-scale critical ethnographic study adopting a constructivist grounded approach to conceptualise ways in which children's naturalistic behaviours may be perceived as research. The study builds on multi-disciplinary theoretical perspectives, embracing 'new' sociology, psychology, economics, philosophy and early childhood education and care (ECEC). Research questions include: 'What is the nature of ECEC research?' and 'Do children’s enquiries count as research?' Initially, data were collected from the academy: professional researchers (n=14) confirmed 'finding solutions' as a research behaviour and indicated children aged 4-8 years, their practitioners and primary carers as 'theoretical sampling'. Consequently, multi-modal case studies were constructed with children (n=138) and their practitioners (n=17) in three ‘good’ schools, with selected children and their primary carers also participating at home. This paper reports on data emerging from children aged 4-8 years at school (n=17) and at home (n=5). Outcomes indicate that participating children found diverse solutions to diverse problems, some of which they set themselves. Some solutions engaged children in high order thinking, whilst others did not; selecting resources and trialing activities engaged children in 'finding solutions'. Conversely, when children's time, provocations and activities were directed by adults, the quality of their solutions was limited, they focused on pleasing adults and their motivation to propose solutions decreased. In this study, professional researchers recognised 'finding solutions' as research behaviour and children aged 4-8 years naturalistically presented with capacities for finding solutions; however, the children's encounters with adults affected the solutions they found

Hip fracture risk assessment: Artificial neural network outperforms conditional logistic regression in an age- and sex-matched case control study

Copyright @ 2013 Tseng et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background - Osteoporotic hip fractures with a significant morbidity and excess mortality among the elderly have imposed huge health and economic burdens on societies worldwide. In this age- and sex-matched case control study, we examined the risk factors of hip fractures and assessed the fracture risk by conditional logistic regression (CLR) and ensemble artificial neural network (ANN). The performances of these two classifiers were compared. Methods - The study population consisted of 217 pairs (149 women and 68 men) of fractures and controls with an age older than 60 years. All the participants were interviewed with the same standardized questionnaire including questions on 66 risk factors in 12 categories. Univariate CLR analysis was initially conducted to examine the unadjusted odds ratio of all potential risk factors. The significant risk factors were then tested by multivariate analyses. For fracture risk assessment, the participants were randomly divided into modeling and testing datasets for 10-fold cross validation analyses. The predicting models built by CLR and ANN in modeling datasets were applied to testing datasets for generalization study. The performances, including discrimination and calibration, were compared with non-parametric Wilcoxon tests. Results - In univariate CLR analyses, 16 variables achieved significant level, and six of them remained significant in multivariate analyses, including low T score, low BMI, low MMSE score, milk intake, walking difficulty, and significant fall at home. For discrimination, ANN outperformed CLR in both 16- and 6-variable analyses in modeling and testing datasets (p?<?0.005). For calibration, ANN outperformed CLR only in 16-variable analyses in modeling and testing datasets (p?=?0.013 and 0.047, respectively). Conclusions - The risk factors of hip fracture are more personal than environmental. With adequate model construction, ANN may outperform CLR in both discrimination and calibration. ANN seems to have not been developed to its full potential and efforts should be made to improve its performance.National Health Research Institutes in Taiwa

Novel autoantigens immunogenic in COPD patients

<p>Abstract</p> <p>Background</p> <p>Chronic obstructive pulmonary disease (COPD) is a respiratory inflammatory condition with autoimmune features including IgG autoantibodies. In this study we analyze the complexity of the autoantibody response and reveal the nature of the antigens that are recognized by autoantibodies in COPD patients.</p> <p>Methods</p> <p>An array of 1827 gridded immunogenic peptide clones was established and screened with 17 sera of COPD patients and 60 healthy controls. Protein arrays were evaluated both by visual inspection and a recently developed computer aided image analysis technique. By this computer aided image analysis technique we computed the intensity values for each peptide clone and each serum and calculated the area under the receiver operator characteristics curve (AUC) for each clone and the separation COPD sera versus control sera.</p> <p>Results</p> <p>By visual evaluation we detected 381 peptide clones that reacted with autoantibodies of COPD patients including 17 clones that reacted with more than 60% of the COPD sera and seven clones that reacted with more than 90% of the COPD sera. The comparison of COPD sera and controls by the automated image analysis system identified 212 peptide clones with informative AUC values. By <it>in silico </it>sequence analysis we found an enrichment of sequence motives previously associated with immunogenicity.</p> <p>Conclusion</p> <p>The identification of a rather complex humoral immune response in COPD patients supports the idea of COPD as a disease with strong autoimmune features. The identification of novel immunogenic antigens is a first step towards a better understanding of the autoimmune component of COPD.</p

Machine Learning Classification of Females Susceptibility to Visceral Fat Associated Diseases

The problem of classifying subjects into risk categories is a common challenge in medical research. Machine Learning (ML) methods are widely used in the areas of risk prediction and classification. The primary objective of these algorithms is to predict dichotomous responses (e.g. healthy/at risk) based on several features. Similarly to statistical inference models, also ML models are subject to the common problem of class imbalance. Therefore, they are affected by the majority class increasing the false-negative rate. In this paper, we built and evaluated eighteen ML models classifying approximately 4300 female participants from the UK Biobank into three categorical risk statuses based on responses for the discretised visceral adipose tissue values from magnetic resonance imaging. We also examined the effect of sampling techniques on classification modelling when dealing with class imbalance. Results showed that the use of sampling techniques had a significant impact. They not only drove an improvement in predicting patients risk status but also facilitated an increase in the information contained within each variable. Based on domain experts criteria, the three best models for classification were finally identified. These encouraging results will guide further developments of classification models for predicting visceral adipose tissue without the need for a costly scan

Metacognition and lifelong e-learning: a contextual and cyclical process

Metacognition is arguably an important conceptualisation within the area of lifelong e- learning, with many theorists and practitioners claiming that it enhances the learning process. However, the lifelong, cyclical and flexible aspects of 'before', 'during' and 'after' metacognitions within lifelong e-learning (inclusive of whether an 'input' necessarily leads to a completed 'output') seem marginal within current areas of practical and theoretical debate. This article analyses Reeves's (1997) model of web-based learning in the context of the ADAPT project; a study of lifelong learners based in small and medium sized enterprises. The article focuses upon an analysis of this model's view of metacognition, and in the light of the project findings and literature review, aims to put forward an extended and expanded version of the model with reference to lifelong e-learnin