Reference Data

This paper is organised as follows. CERIF (Common European Research Information Format) has a history described in Section 2. Section 3 describes how it is used currently as a datamodel for CRISs (Current Research Information Systems) in several variants in several countries and raises some issues. A Task Group of the euroCRIS organisation (www.eurocris.org) is now the custodian of CERIF ensuring its integrity, flexibility and usability. Section 4 outlines some of the developmental directions for CERIF and discusses the relationship to the original aims and objectives. Section 5 concludes

Ontologies have been part of developing information systems in Shell for some twenty years, taking the form of data models and reference data used within information systems. A problem in reusing or integrating systems is the context that they assume, which may not be valid beyond the scope of an implementation. Lessons learnt include trying to ensure that the context is explicit, and that what are really local rules in a global context are not defined as global rules in a local context. These lessons have been applied in the development of International Standards to provide an architecture for integration and a data model that includes both a foundation ontology that has been developed on a well defined and consistent basis, and provides a framework for extension of the ontology through reference data.

This paper introduces the current machine learning approach to solving spatial modeling problems in the domain of landslide susceptibility assessment. The latter is introduced as a classification problem, having multiple (geological, morphological, environmental etc.) attributes and one referent landslide inventory map from which to devise the classification rules. Three different machine learning algorithms were compared: Support Vector Machines, Decision Trees and Logistic Regression. A specific area of the Fruška Gora Mountain (Serbia) was selected to perform the entire modeling procedure, from attribute and referent data preparation/processing, through the classifiers' implementation to the evaluation, carried out in terms of the model's performance and agreement with the referent data. The experiments showed that Support Vector Machines outperformed the other proposed methods, and hence this algorithm was selected as the model of choice to be compared with a common knowledge-driven method – the Analytical Hierarchy Process – to create a landslide susceptibility map of the relevant area. The SVM classifier outperformed the AHP approach in all evaluation metrics (κ index, area under ROC curve and false positive rate in stable ground class).► After conducting experiments based on the sampling over the entire area, the SVM turned to be the model of choice. ► In the mapping task on a neighboring terrain, SVM achieved better performance than AHP model in all evaluation measures. ► The results of the 2nd mapping task were weaker in comparison to the 1st one (different distribution of input parameters). ► SVM do not need any feature selection technique as opposed to some other methods such as Decision Trees.

The Inca Empire (AD 1438–1532) made common practice of relocating individuals, households and entire communities throughout their expansive realm for different reasons depending on subjects' assigned social class. Reconstructing patterns of immigration at Inca-period sites could therefore permit some estimation of the social class(es) among their constituents, and thereby provide insights into the functional dynamics of Inca political economy. However, this is a difficult endeavor using only archaeological lines of evidence. This study presents oxygen, strontium and lead isotopic results from the well-preserved, well-contextualized skeletal population (N = 74) from the Inca site of Machu Picchu, Peru. Isotopic data are used to reconstruct patterns of immigration at the site, which are in turn used to directly estimate the social class of the population. The resulting isotopic data are widely distributed with no apparent modality, matching the expected distribution of a particular class of nonelite retainers. A novel application of multivariate statistics coupled with geological and faunal isotopic reference data also permits tentative estimation of individuals' regions of origin. This study provides empirical and analytical frameworks for future research in reconstructing residential movement and class dynamics in the late prehistoric Andes.

Objective The study was conducted to evaluate growth and nutritional status using weight and height based indicators among tea garden adolescent boys and girls of Assam aged between 10–18 years. Methods A cross sectional study was carried out in the tea gardens of Dibrugarh district of Assam through house to house visit. Households were selected through two stage sampling design to reach out the adolescents. Height and weight were measured using standard procedures. Body mass index (BMI) was computed from height and weight. Height-for-age below 3rd percentile values of NCHS reference was classified as stunting. BMI-for-age below 5th percentile values of WHO recommended reference was classified as thinness. Results Total numbers of 605 adolescents (boys-291, girls-314) participated in the study. School enrollment rate was only 59.2%. Prevalence of stunting was 47.4% and 51.9% among boys and girls respectively relative to NCHS reference, which reduced to almost 30% while Indian reference data was used. Prevalence of thinness was higher among boys (59.5%) than girls (41.3%) counterparts. Mean BMI among girls was higher at all ages than boys. Conclusion Almost half of the adolescents were stunted and most of them were thin. Problem of overweight was seen in less than 0.5% of adolescents. Factors typical to underdeveloped society seems to contribute to the moderate to high prevalence of undernutrition among adolescents working in tea gardens.

A methodology to estimate the cost implications of design decisions by integrating cost as a design parameter at an early design stage is presented. The model is developed on a hierarchical basis, the manufacturing cost of aircraft fuselage panels being analysed in this paper. The manufacturing cost modelling is original and relies on a genetic-causal method where the drivers of each element of cost are identified relative to the process capability. The cost model is then extended to life cycle costing by computing the Direct Operating Cost as a function of acquisition cost and fuel burn, and coupled with a semi-empirical numerical analysis using Engineering Sciences Data Unit reference data to model the structural integrity of the fuselage shell with regard to material failure and various modes of buckling. The main finding of the paper is that the traditional minimum weight condition is a dated and sub-optimal approach to airframe structural design.

Accurate identification of the onset of muscle activity is an important element in the biomechanical analysis of human movement. The purpose of this study was to determine if inclusion of the Teager–Kaiser energy operator (TKEO) in signal conditioning would increase the accuracy of popular electromyography (EMG) onset detection methods. Three methods, visual determination, threshold-based method, and approximated generalized likelihood ratio were used to estimate the onset of EMG burst with and without TKEO conditioning. Reference signals, with known onset times, were constructed from EMG signals collected during isometric contraction of the vastus lateralis (n = 17). Additionally, vastus lateralis EMG signals (n = 255) recorded during gait were used to evaluate a clinical application of the TKEO conditioning. Inclusion of TKEO in signal conditioning significantly reduced mean detection error of all three methods compared with signal conditioning without TKEO, using artificially generated reference data (13 vs. 98 ms, p < 0.001) and also compared with experimental data collected during gait (55 vs. 124 ms, p < 0.001). In conclusion, addition of TKEO as a step in conditioning surface EMG signals increases the detection accuracy of EMG burst boundaries.