Some challenges for constraint programming

We propose a number of challenges for future constraint programming systems, including improvements in implementation technology (using global analysis based optimization and parallelism), debugging facilities, and the extensión of the application domain to distributed, global programming. We also briefly discuss how we are exploring techniques to meet these challenges in the context of the development of the CIAO constraint logic programming system.

The impact of sustainable construction and knowledge management on sustainability goals. A review of the venezuelan renewable energy sector

The recognition of the relevance of energy, especially of the renewable energies generated by the sun, water, wind, tides, modern biomass or thermal is growing significantly in the global society based on the possibility it has to improve societies′ quality of life, to support poverty reduction and sustainable development. Renewable energy, and mainly the energy generated by large hydropower generation projects that supply most of the renewable energy consumed by developing countries, requires many technical, legal, financial and social complex processes sustained by innovations and valuable knowledge. Besides these efforts, renewable energy requires a solid infrastructure to generate and distribute the energy resources needed to solve the basic needs of society. This demands a proper construction performance to deliver the energy projects planned according to specifications and respecting environmental and social concerns, which implies the observance of sustainable construction guidelines. But construction projects are complex and demanding and frequently face time and cost overruns that may cause negative impacts on the initial planning and thus on society. The renewable energy issue and the large renewable energy power generation and distribution projects are particularly significant for developing countries and for Latin America in particular, as this region concentrates an important hydropower potential and installed capacity. Using as references the performance of Venezuelan large hydropower generation projects and the Guri dam construction, this research evaluates the tight relationship existing between sustainable construction and knowledge management and their impact to achieve sustainability goals. The knowledge management processes are proposed as a basic strategy to allow learning from successes and failures obtained in previous projects and transform the enhancement opportunites into actions to improve the performance of the renewable energy power generation and distribution projects.

Molecular cloning of the first metazoan beta-1,3 glucanase from eggs of the sea urchin Strongylocentrotus purpuratus.

We report the molecular cloning of the first beta-1,3 glucanase from animal tissue. Three peptide sequences were obtained from beta-1,3 glucanase that had been purified from eggs of the sea urchin Strongylocentrotus purpuratus and the gene was cloned by PCR using oligonucleotides deduced from the peptide sequences. The full-length cDNA shows a predicted enzyme structure of 499 aa with a hydrophobic signal sequence. A 3.2-kb message is present in eggs, during early embryogenesis, and in adult gut tissue. A polyclonal antibody to the native 68-kDa enzyme recognizes a single band during early embryogenesis that reappears in the adult gut, and recognizes a 57-kDa fusion protein made from a full-length cDNA clone for beta-1,3 glucanase. The identity of this molecule as beta-1,3 glucanase is confirmed by sequence homology, by the presence of all three peptide sequences in the deduced amino acid sequence, and by the recognition of the bacterial fusion protein by the antibody directed against the native enzyme. Data base searches show significant homology at the amino acid level to beta-1,3 glucanases from two species of bacteria and a clotting factor from the horseshoe crab. The homology with the bacteria is centered in a 304-aa region in which there are seven scattered regions of high homology between the four divergent species. These four species were also found to have two homologous regions in common with more distantly related plant, fungal, and bacterial proteins. A global phylogeny based on these regions strongly suggests that the glucanases are a very ancient family of genes. In particular, there is an especially deep split within genes taken from the bacterial genus Bacillus.

Climate Conundrums at High Altitude. EU Diplomacy Paper 01/2014, January 2014

The European Union (EU) was the frontrunner for the establishment of the world’s first multinational emissions trading scheme (ETS). Committed to combating climate change, the EU sought to overcome the multilateral paralysis within the International Civil Aviation Organization (ICAO) to mitigate aviation emissions. Unsuccessful in pushing for a global market-based measure (MBM) within the organisation, the EU was ready for take-off to include the sector in the EU emissions trading system (EU ETS). The geographical scope, however, including all flights from and to Europe in their entire trajectory, caused frictions with the international community about sovereignty issues. Ultimately, Climate Commissioner Connie Hedegaard announced a ‘stop-the-clock’ for international flights, a temporary derogation until the 2013 ICAO Assembly in order to find a global agreement. The ’stop-the-clock’ initiative provides ample opportunity to analyse EU leadership in curbing aviation emissions based on an analytical framework specifying different types of leadership. Its shows the global challenge to the EU’s claim of structural leadership on various levels in and beyond ICAO. The paper aims to analyse to what extent the EU is a global leader in mitigating aviation emissions and to identify the kind of EU leadership according to a threefold analytical framework. In addition, it will factor in the 'stop-the-clock' initiative and to what extent it altered the perception of EU leadership in the field. The paper comes to the conclusion that EU leadership in mitigating aviation emissions is not stalling. On the contrary, the EU, by pursuing the extension of the EU ETS, has put aviation emissions on everybody’s radar – and thus showed idea-based leadership. Proving the scheme’s feasibility further underlined EU leadership, in the form of directional leadership. The 'stop-the-clock' decision, however, already indicated what was later on confirmed in the 38th ICAO Assembly: Unilateral structural leadership of the EU in the field of aviation emissions is not credible at the moment.

Knowledge workers and their relationships with organisations

The programme of research examines knowledge workers, their relationships with organisations, and perceptions of management practices through the development of a theoretical model and knowledge worker archetypes. Knowledge worker and non-knowledge worker archetypes were established through an analysis of the extant literature. After an exploratory study of knowledge workers in a small software development company the archetypes were refined to include occupational classification data and the findings from Study 1. The Knowledge Worker Characteristics Model (KWCM) was developed as a theoretical framework in order to analyse differences between the two archetypes within the IT sector. The KWCM comprises of the variables within the job characteristics model, creativity, goal orientation, identification and commitment. In Study 2, a global web based survey was conducted. There were insufficient non-knowledge worker responses and therefore a cluster analysis was conducted to interrogate the archetypes further. This demonstrated, unexpectedly, that that there were marked differences within the knowledge worker archetypes suggesting the need to granulate the archetype further. The theoretical framework and the archetypes were revised (as programmers and web developers) and the research study was refocused to examine occupational differences within knowledge work. Findings from Study 2 identified that there were significant differences between the archetypes in relation to the KWCM. 19 semi-structured interviews were conducted in Study 3 in order to deepen the analysis using qualitative data and to examine perceptions of people management practices. The findings from both studies demonstrate that there were significant differences between the two groups but also that job challenge, problem solving, intrinsic reward and team identification were of importance to both groups of knowledge workers. This thesis presents an examination of knowledge workers’ perceptions of work, organisations and people management practices in the granulation and differentiation of occupational archetypes.

Supply chain management resources, capabilities and execution

This paper identifies inter- and intra-organisational management resources that determine the level of execution of inter-firm alliance supply chain management (SCM). By drawing on network and resource-based view theories, a conceptual model proposes the effects of SCM resources and capabilities as influencing factors on SCM execution. The model was tested using survey data from studies conducted in two European supply chain environments. Variance-based structural equation modelling confirmed the hypothesised hierarchical order of three proposed antecedents: internal SCM resources affect joint SCM resources, which in turn influence collaborative SCM-related processes and finally SCM execution. An importance-performance analysis for both settings shows that providing and investing in internal SCM resources should be a priority when aiming to increase SCM execution. The theoretical contribution of this paper lies in confirming that the improvement of SCM execution follows a clear pathway featuring internal supply chain resources as one of the main drivers. The practical implications of this research include the development of a prioritisation list of measures that elevate SCM execution in the two country settings. © 2014 © 2014 Taylor & Francis.

Análise do comportamento de técnicas de correspondência binocular para imagens em alta definição

This work presents an analysis of the behavior of some algorithms usually available in stereo correspondence literature, with full HD images (1920x1080 pixels) to establish, within the precision dilemma versus runtime applications which these methods can be better used. The images are obtained by a system composed of a stereo camera coupled to a computer via a capture board. The OpenCV library is used for computer vision operations and processing images involved. The algorithms discussed are an overall method of search for matching blocks with the Sum of the Absolute Value of the difference (Sum of Absolute Differences - SAD), a global technique based on cutting energy graph cuts, and a so-called matching technique semi -global. The criteria for analysis are processing time, the consumption of heap memory and the mean absolute error of disparity maps generated.

The application of PCA as a movement pattern recognition technique: A proof of principle

Quantitative methods can help us understand how underlying attributes contribute to movement patterns. Applying principal components analysis (PCA) to whole-body motion data may provide an objective data-driven method to identify unique and statistically important movement patterns. Therefore, the primary purpose of this study was to determine if athletes’ movement patterns can be differentiated based on skill level or sport played using PCA. Motion capture data from 542 athletes performing three sport-screening movements (i.e. bird-dog, drop jump, T-balance) were analyzed. A PCA-based pattern recognition technique was used to analyze the data. Prior to analyzing the effects of skill level or sport on movement patterns, methodological considerations related to motion analysis reference coordinate system were assessed. All analyses were addressed as case-studies. For the first case study, referencing motion data to a global (lab-based) coordinate system compared to a local (segment-based) coordinate system affected the ability to interpret important movement features. Furthermore, for the second case study, where the interpretability of PCs was assessed when data were referenced to a stationary versus a moving segment-based coordinate system, PCs were more interpretable when data were referenced to a stationary coordinate system for both the bird-dog and T-balance task. As a result of the findings from case study 1 and 2, only stationary segment-based coordinate systems were used in cases 3 and 4. During the bird-dog task, elite athletes had significantly lower scores compared to recreational athletes for principal component (PC) 1. For the T-balance movement, elite athletes had significantly lower scores compared to recreational athletes for PC 2. In both analyses the lower scores in elite athletes represented a greater range of motion. Finally, case study 4 reported differences in athletes’ movement patterns who competed in different sports, and significant differences in technique were detected during the bird-dog task. Through these case studies, this thesis highlights the feasibility of applying PCA as a movement pattern recognition technique in athletes. Future research can build on this proof-of-principle work to develop robust quantitative methods to help us better understand how underlying attributes (e.g. height, sex, ability, injury history, training type) contribute to performance.

Estimate of the (R)USLE rainfall erosivity factor from monthly precipitation data in mainland Spain

The need for continuous recording rain gauges makes it difficult to determine the rainfall erosivity factor (R-factor) of the (R)USLE model in areas without good temporal data coverage. In mainland Spain, the Nature Conservation Institute (ICONA) determined the R-factor at few selected pluviographs, so simple estimates of the R-factor are definitely of great interest. The objectives of this study were: (1) to identify a readily available estimate of the R-factor for mainland Spain; (2) to discuss the applicability of a single (global) estimate based on analysis of regional results; (3) to evaluate the effect of record length on estimate precision and accuracy; and (4) to validate an available regression model developed by ICONA. Four estimators based on monthly precipitation were computed at 74 rainfall stations throughout mainland Spain. The regression analysis conducted at a global level clearly showed that modified Fournier index (MFI) ranked first among all assessed indexes. Applicability of this preliminary global model across mainland Spain was evaluated by analyzing regression results obtained at a regional level. It was found that three contiguous regions of eastern Spain (Catalonia, Valencian Community and Murcia) could have a different rainfall erosivity pattern, so a new regression analysis was conducted by dividing mainland Spain into two areas: Eastern Spain and plateau-lowland area. A comparative analysis concluded that the bi-areal regression model based on MFI for a 10-year record length provided a simple, precise and accurate estimate of the R-factor in mainland Spain. Finally, validation of the regression model proposed by ICONA showed that R-ICONA index overpredicted the R-factor by approximately 19%.

Finding the Needle in a Haystack: Who are the Most Central Authors Within a Domain?

The speed at which new scientific papers are published has increased dramatically, while the process of tracking the most recent publications having a high impact has become more and more cumbersome. In order to support learners and researchers in retrieving relevant articles and identifying the most central researchers within a domain, we propose a novel 2-mode multilayered graph derived from Cohesion Network Analysis (CNA). The resulting extended CNA graph integrates both authors and papers, as well as three principal link types: coauthorship, co-citation, and semantic similarity among the contents of the papers. Our rankings do not rely on the number of published documents, but on their global impact based on links between authors, citations, and semantic relatedness to similar articles. As a preliminary validation, we have built a network based on the 2013 LAK dataset in order to reveal the most central authors within the emerging Learning Analytics domain.

Uncertainty assessment approach for composite structures based on global sensitivity indices

The problem of uncertainty propagation in composite laminate structures is studied. An approach based on the optimal design of composite structures to achieve a target reliability level is proposed. Using the Uniform Design Method (UDM), a set of design points is generated over a design domain centred at mean values of random variables, aimed at studying the space variability. The most critical Tsai number, the structural reliability index and the sensitivities are obtained for each UDM design point, using the maximum load obtained from optimal design search. Using the UDM design points as input/output patterns, an Artificial Neural Network (ANN) is developed based on supervised evolutionary learning. Finally, using the developed ANN a Monte Carlo simulation procedure is implemented and the variability of the structural response based on global sensitivity analysis (GSA) is studied. The GSA is based on the first order Sobol indices and relative sensitivities. An appropriate GSA algorithm aiming to obtain Sobol indices is proposed. The most important sources of uncertainty are identified.

2D PCA-Based localization for mobile robots in unstructured environments

In this paper a new PCA-based positioning sensor and localization system for mobile robots to operate in unstructured environments (e. g. industry, services, domestic ...) is proposed and experimentally validated. The inexpensive positioning system resorts to principal component analysis (PCA) of images acquired by a video camera installed onboard, looking upwards to the ceiling. This solution has the advantage of avoiding the need of selecting and extracting features. The principal components of the acquired images are compared with previously registered images, stored in a reduced onboard image database, and the position measured is fused with odometry data. The optimal estimates of position and slippage are provided by Kalman filters, with global stable error dynamics. The experimental validation reported in this work focuses on the results of a set of experiments carried out in a real environment, where the robot travels along a lawn-mower trajectory. A small position error estimate with bounded co-variance was always observed, for arbitrarily long experiments, and slippage was estimated accurately in real time.

The tight grip of a debt based global economy: A study on banking regulation and the implementation of the Basel II Accord in Portugal

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Human capital in a global and knowledge-based economy. Part 2. Asssessment at the EU country level.

This report is an extension and partial update of de la Fuente and Ciccone (2002). It constructs estimates of the private and social rates of return on schooling for fourteen EU countries using microeconometric estimates of Mincerian wage equations, the results of cross-country growth regressions and OECD data on educational expenditures, tax rates and social benefits. The results are used to draw some tentative conclusions regarding the optimality of observed investment patterns and educational subsidy levels.