Using triangulation to identify word senses

Word sense disambiguation is the task of determining which sense of a word is intended from its context. Previous methods have found the lack of training data and the restrictiveness of dictionaries' choices of senses to be major stumbling blocks. A robust novel algorithm is presented that uses multiple dictionaries, the Internet, clustering and triangulation to attempt to discern the most useful senses of a given word and learn how they can be disambiguated. The algorithm is explained, and some promising sample results are given.

Algorithm for generating defective graphene sheets

An algorithm is presented for the generation of molecular models of defective graphene fragments, containing a majority of 6-membered rings with a small number of 5- and 7-membered rings as defects. The structures are generated from an initial random array of points in 2D space, which are then subject to Delaunay triangulation. The dual of the triangulation forms a Voronoi tessellation of polygons with a range of ring sizes. An iterative cycle of refinement, involving deletion and addition of points followed by further triangulation, is performed until the user-defined criteria for the number of defects are met. The array of points and connectivities are then converted to a molecular structure and subject to geometry optimization using a standard molecular modeling package to generate final atomic coordinates. On the basis of molecular mechanics with minimization, this automated method can generate structures, which conform to user-supplied criteria and avoid the potential bias associated with the manual building of structures. One application of the algorithm is the generation of structures for the evaluation of the reactivity of different defect sites. Ab initio electronic structure calculations on a representative structure indicate preferential fluorination close to 5-ring defects.

Realistic mean field forward predictions for the integration of co-registered EEG/fMRI

Brain activity can be measured non-invasively with functional imaging techniques. Each pixel in such an image represents a neural mass of about 105 to 107 neurons. Mean field models (MFMs) approximate their activity by averaging out neural variability while retaining salient underlying features, like neurotransmitter kinetics. However, MFMs incorporating the regional variability, realistic geometry and connectivity of cortex have so far appeared intractable. This lack of biological realism has led to a focus on gross temporal features of the EEG. We address these impediments and showcase a "proof of principle" forward prediction of co-registered EEG/fMRI for a full-size human cortex in a realistic head model with anatomical connectivity, see figure 1. MFMs usually assume homogeneous neural masses, isotropic long-range connectivity and simplistic signal expression to allow rapid computation with partial differential equations. But these approximations are insufficient in particular for the high spatial resolution obtained with fMRI, since different cortical areas vary in their architectonic and dynamical properties, have complex connectivity, and can contribute non-trivially to the measured signal. Our code instead supports the local variation of model parameters and freely chosen connectivity for many thousand triangulation nodes spanning a cortical surface extracted from structural MRI. This allows the introduction of realistic anatomical and physiological parameters for cortical areas and their connectivity, including both intra- and inter-area connections. Proper cortical folding and conduction through a realistic head model is then added to obtain accurate signal expression for a comparison to experimental data. To showcase the synergy of these computational developments, we predict simultaneously EEG and fMRI BOLD responses by adding an established model for neurovascular coupling and convolving "Balloon-Windkessel" hemodynamics. We also incorporate regional connectivity extracted from the CoCoMac database [1]. Importantly, these extensions can be easily adapted according to future insights and data. Furthermore, while our own simulation is based on one specific MFM [2], the computational framework is general and can be applied to models favored by the user. Finally, we provide a brief outlook on improving the integration of multi-modal imaging data through iterative fits of a single underlying MFM in this realistic simulation framework.

The roles and competencies of HR managers in Slovenian multinational companies

Purpose – The HRM literature provides various typologies of the HR managers’ roles in organizations. The purpose of this paper is to examine how the roles and required competencies of HR managers in Slovenian multinational companies change when these companies enter the international arena. Design/methodology/approach – The authors explored the total population of 25 Slovenian multinational companies (MNCs) operating in Serbia. In these companies the authors conducted interviews with 16 expatriates working in branches in Serbia, sent questionnaires to the CEOs, and conducted a survey of 50 HR managers and interviews with 15 of them. The authors used a triangulation approach and analyzed the results by multivariate methods and content analysis. Findings – The authors found that the complexity of HR managers’ roles, and expectations of their competencies, increases with an increasing level of internationalization of companies. Orientation to people and conflict resolution are seen as elementary competencies needed in all stages of internationalization. The key competence is seen to be strategic thinking that, according to CEOs and expatriates, goes hand in hand with cultural sensitivity, openness to change and a comprehensive understanding of the international environment and business processes. Practical implications – These results can potentially be used for assessing the HRM roles and competencies in different stages of company internationalization, especially MNCs operating in the ex-communist states of Europe, and will help HR managers to support expatriates, CEOs and other employees working in branches abroad more efficiently. Originality/value – This study contributes to the review and evaluation of the quite limited research on HR managers’ roles and competencies in MNCs. It focuses on MNCs and outward internationalization in the Central and Eastern European region. It contributes to studies of the HR managers’ roles and competencies and is the first study to establish a set of roles and competencies for HR managers in Slovenian MNCs.

Typographic layout and first impressions: testing how changes in text layout influence reader's judgments of documents

This study explores how the typographic layout of information influences readers' impressions of magazine contents pages. Thirteen descriptors were used in a paired comparison procedure that assessed whether participants' rhetorical impressions of a set of six controlled documents change in relation to variations in layout. The combinations of layout attributes tested were derived from the structural attributes associated with three patterns of typographic differentiation (high, moderate, and low) described in a previous study (see Moys, 2014). The content and the range of stylistic attributes applied to the test material were controlled in order to focus on layout attributes. Triangulation of the quantitative and qualitative data indicates that, even within the experimental confines of limited stylistic differentiation, the layout attributes associated with patterns of high, moderate, and low typographic differentiation do influence readers' rhetorical judgments. In addition, the findings emphasize the importance of considering inter-relationships between clusters of typographic attributes rather than testing isolated variables.

Researching farmer behaviour in climate change adaptation and sustainable agriculture: lessons learned from five case studies

Understanding farmer behaviour is needed for local agricultural systems to produce food sustainably while facing multiple pressures. We synthesize existing literature to identify three fundamental questions that correspond to three distinct areas of knowledge necessary to understand farmer behaviour: 1) decision-making model; 2) cross-scale and cross-level pressures; and 3) temporal dynamics. We use this framework to compare five interdisciplinary case studies of agricultural systems in distinct geographical contexts across the globe. We find that these three areas of knowledge are important to understanding farmer behaviour, and can be used to guide the interdisciplinary design and interpretation of studies in the future. Most importantly, we find that these three areas need to be addressed simultaneously in order to understand farmer behaviour. We also identify three methodological challenges hindering this understanding: the suitability of theoretical frameworks, the trade-offs among methods and the limited timeframe of typical research projects. We propose that a triangulation research strategy that makes use of mixed methods, or collaborations between researchers across mixed disciplines, can be used to successfully address all three areas simultaneously and show how this has been achieved in the case studies. The framework facilitates interdisciplinary research on farmer behaviour by opening up spaces of structured dialogue on assumptions, research questions and methods employed in investigation.

'Rules of engagement’: how experiential learning facilitates the formation of a public–private partnership in Russia

Purpose – The purpose of this paper is to investigate to what extent one can apply experiential learning theory (ELT) to the public-private partnership (PPP) setting in Russia and to draw insights regarding the learning cycle ' s nature. Additionally, the paper assesses whether the PPP case confirms Kolb ' s ELT. Design/methodology/approach – The case study draws upon primary data which the authors collected by interviewing informants including a PPP operator ' s managers, lawyers from Russian law firms and an expert from the National PPP Centre. The authors accomplished data source triangulation in order to ensure a high degree of research validity. Findings – Experiential learning has resulted in a successful and a relatively fast PPP project launch without the concessionary framework. The lessons learned include the need for effective stakeholder engagement; avoiding being stuck in bureaucracy such as collaboration with Federal Ministries and anti-trust agency; avoiding application for government funding as the approval process is tangled and lengthy; attracting strategic private investors; shaping positive public perception of a PPP project; and making continuous efforts in order to effectively mitigate the public acceptance risk. Originality/value – The paper contributes to ELT by incorporating the impact of social environment in the learning model. Additionally, the paper tests the applicability of ELT to learning in the complex organisational setting, i.e., a PPP.