Clustering of Gaussian Random Vector Fields in Multiple Trajectory Modelling

This paper concerns the estimation of multiple dynamical models from a set of observed trajectories. It proposes vector valued gaussian random fields, representing dynamical models and their vector fields, combined with a modified k- means clustering algorithm to assign observed trajectories to models. The assignment is done according to a likelihood function obtained from applying the random field associated to a cluster, to the data. The algorithm is shown to have several advantages when compared with others: 1) it does not depend on a grid, region of interest, grid resolution or interpolation method; 2) the estimated vector fields has an associated uncertainty which is given by the algorithm and taken into account. The paper presents results obtained on synthetic trajectories that illustrate the performance of the proposed algorithm

Accessibility and Development in Peripheral Regions. The Case for Beira Interior

Beira Interior is a Portuguese region located at the centre of Portugal, close to the Spanish border, and traditionally seen as a strongly peripheral region. In the last years the decrease in population and weaknesses of the industrial park have been justified on basis of shortness and/or lack of quality in transport infrastructure. In order to evaluate whether there is in fact a case in favour of infrastructure shortage we have developed a methodology that would allow us to identify the accessibility gains in the recent past, the ones foreseeable in the usually adopted planning periods and the ones possible in a asymptotic scenario of strong generalised accessibility, enabling this way to make explicit identification of the gains already achieved and the ones still possible. The evolution of values of the studied region was compared with the corresponding values in the region Litoral Centro – the region that was also used as benchmark in a previous consultation process to industrial key informants operating in Beira Interior. This thematic is extremely important for the region and for the country since the conclusions obtained will enable a better supported discussion on additional investment in transport infrastructure.

Analysis of competitiveness in Colombian family businesses

Purpose: Building on the resource-based view and the configuration theory, the purpose of this study uses a systemic and multidimensional competitiveness index (CI) i.e. that incorporates system constraints among the 10 competitive pillars that form the index to assess the competitiveness level and the connection between competitiveness and economic performance [return on assets (ROA)] in family businesses (FBs). Design/methodology/approach: For the empirical application, the use a unique primary data set drawn from the global competitiveness project (www.gcp.org) that includes information for 77 Colombian FBs for 2017. Cluster analysis is used to evaluate the potential relationship between competitiveness, the configuration of competitive pillars and economic performance (ROA). Findings: The results for the CI show that the main competitive strengths of the analysed firms are related to the introduction of product innovations and networks (suppliers and customers), while the limited use of technologies in their operations and the low online presence are the main competitive weaknesses of these firms. Additionally, the findings of the cluster analysis reveal that different configurations of competitiveness pillars are associated with different performance levels. Therefore, the results contribute to identifying how specific strategies aimed at improving different resources or capabilities contribute to enhance business competitiveness, and ultimately, performance. Originality/value: By using an index number that takes into account the multiple interactions between resources and capabilities, the proposed analysis not only sheds light on the drivers of competitiveness i.e. resources and capabilities, and its connection to performance but also contributes to understanding the boundaries of the businesses’ competitiveness system, as well as the strategies that can potentially enhance competitiveness, and subsequently, business performance.Peer ReviewedPreprin

Staff, Functions, and Staff Costs at Central Banks: An International Comparison with a Labor-demand Model

During the period 2000-2004 central banks sustained a generalized reduction in their staff, which was accompanied, in most cases, with significant increases in staff costs. This could obey to an enhanced interest of central banks in focusing on their core functions. In fact, central banks have changed the ways they perform their operative functions (e.g. currency operations, payment systems operation, printing notes, etc.) through different strategies aimed at gathering the participation of third parties. These strategies differ according to the relationship that central banks have with the financial sector and the government, as well as to their historical tradition and modernization trend. To explain the effect of these changes on the staff, we estimated a short-term labor demand function for 66 central banks using a panel data model with random effects. Results indicate that central banks’ labor demand is strongly determined by the country’s population, economic development level and changes in operative functions, as well as by staff costs. In addition, we found a low employment-wage elasticity suggesting the presence of a flexible budgetary constrain in central banks.Central Banking, Labor Demand, Modernization, Functions, Staff Costs, Panel Data, Random Effects. Classification JEL: E50; J23; J30; C33

Alignment of velocity fields for video surveillance

Velocity fields play an important role in surveillance since they describe typical motion behaviors of video objects (e.g., pedestrians) in the scene. This paper presents an algorithm for the alignment of velocity fields acquired by different cameras, at different time intervals, from different viewpoints. Velocity fields are aligned using a warping function which maps corresponding points and vectors in both fields. The warping parameters are estimated by minimizing a non-linear least squares energy. Experimental tests show that the proposed model is able to compensate significant misalignments, including translation, rotation and scaling