A cautionary note on tests for overidentifying restrictions

Tests of overidentifying restrictions are widely used in practice. However, there is often confusion about the nature of their null hypothesis and about the interpretation of their outcome. In this note we argue that these tests give little information on whether the instruments are correlated with the errors of the underlaying economic model and on whether they identify parameters of interest.

Biomechanics of the pelvic floor during vaginal delivery

Tese de doutoramento. Engenharia Mecânica. Faculdade de Engenharia. Universidade do Porto, Instituto Superior Técnico. Universidade de Lisboa, Faculdade de Medicina. Universidade do Porto. 200

Um modelo clínico de dados de enfermagem em processos neuromusculares: análise de conteúdo da parametrização portuguesa

This study targets the development of a nursing clinical data model for neuromuscular processes. To achieve this purpose, content analysis based on Bardin’s perspective was performed on the Portuguese nursing local customizations regarding neuromuscular processes, with the International Classification for Nursing Practice concepts and the ISO 18104:2014 used as encoding rules. From analysis of the data, a total of 1766 diagnoses were related to neuromuscular processes. After application of exclusion criteria, a corpus with a total of 900 diagnoses was subjected to content analysis. After application of the encoding rules, a total of 81 context units were obtained, and through an inductive approach, were defined into three categories: clinical findings (e.g. aphasia); negative judgment diagnoses (e.g. impaired communication); transition properties (e.g. preparation and knowledge). These interpretations were validated by experts in the field. This study not only demonstrates the need to standardize data, but also the importance of neuromuscular processes in nursing practice. We hope this study will guide the definition of a nursing clinical data model that will help in increasing complexity in the level of care provided with high impact in the patient’s quality of life.Este estudo tem como objetivo desenvolver um modelo clínico de dados de enfermagem para processos neuromusculares. Uma análise de conteúdo tendo por base a perspetiva de Bardin, foi realizada às parametrizações locais de Enfermagem em Portugal. O processo de codificação teve por base os conceitos da Classificação Internacional para a Prática de Enfermagem e a norma ISSO 18104:2014. Da análise inicial, 1766 diagnósticos encontravam-se relacionados com os processos neuromusculares. Após aplicação dos critérios de exclusão, um corpus de 900 diagnósticos foi sujeito à análise de conteúdo. Após o processo de codificação, 81 unidades de contexto foram obtidas e inseridas, através de processo indutivo, em três categorias: achados clínicos (ex: afasia); diagnósticos com juízo negativo (ex: comunicação comprometida); propriedades de transição (ex: preparação e conhecimento). Estas interpretações foram validadas por peritos na área. Este estudo permitiu evidenciar a importância dos processos neuromusculares, assim como a necessidade de uniformizar os dados. Pretende-se que este estudo oriente a definição de um modelo clínico de dados de Enfermagem que apoiará o aumento da complexidade dos cuidados de Enfermagem prestados, com alto impacto na qualidade de vida da pessoa.info:eu-repo/semantics/publishedVersio

Metaheuristics, data mining and geographic information systems for earthworks equipment allocation

Optimal and sustainable allocation of equipment in earthwork tasks is a complex problem that requires the study of several different aspects, as well as the knowledge of a large number of factors. In truth, earthworks are comprised by a combination of repetitive, sequential, and interdependent activities based on heavy mechanical equipment (i.e., resources), such as excavators, dumper trucks, bulldozers and compactors. In order to optimally allocate the available resources, knowledge regarding their specifications (e.g., capacity, weight, horsepower) and the work conditions to which they will be subjected (e.g., material types, required and available volumes in embankment and excavation fronts, respectively) is essential. This knowledge can be translated into the productivity (i.e., work rate) of each piece of equipment when working under a specific set of conditions. Moreover, since earthwork tasks are inherently sequential and interdependent, the interaction between the allocated equipment must be taken into account. A typical example of this is the need for matching the work rate of an excavator team with the capacity of a truck team to haul the excavated material to the embankment fronts. Given the non-trivial characteristics of the earthwork allocation problem, conventional Operation Research (e.g., linear programming) and blind search methods are infeasible. As such, a potential solution is to adopt metaheuristics – modern optimization methods capable of searching large search space regions under a reasonable use of computational resources. While this may address the issue of optimizing such a complex problem, the lack of knowledge regarding optimization parameters under different work conditions, such as equipment productivity, calls for a different approach. Bearing in mind the availability of large databases, including in the earthworks area, that have been gathered in recent years by construction companies, technologies like data mining (DM) come forward as ideal tools for solving this problem. Indeed, the learning capabilities of DM algorithms can be applied to databases embodying the productivity of several equipment types when subjected to different work conditions. The extracted knowledge can then be used to estimate the productivity of the available equipment under similar work conditions. Furthermore, as previously referred, since earthwork tasks include the material hauling from excavation to embankment fronts, it also becomes imperative to analyze and optimize the possible transportation networks. In this context, the use of geographic information systems (GIS) provides an easy method to study the possible trajectories for transportation equipment in a construction site, ultimately allowing for a choice of the best paths to improve the workflow. This paper explores the advantages of integrating the referred technologies, among others, in order to allow for a sustainable management of earthworks. This is translated in the form of an evolutionary multi-criteria optimization system, capable of searching for the best allocation of the available equipment that minimizes a set of goals (e.g., cost, duration, environmental impact). Results stemming from the validation of the resulting system using real-world data from a Portuguese construction site demonstrate the potential and importance of using this kind of technologies for a sustainable management and optimization of earthworks

Generalised empirical likelihood Kernel Block bootstrapping

This article unveils how the kernel block bootstrap method of Parente and Smith (2018a,2018b) can be applied to make inferences on parameters of models defined through moment restrictions. Bootstrap procedures that resort to generalised empirical likelihood implied probabilities to draw observations are also introduced. We prove the first-order asymptotic validity of bootstrapped test statistics for overidentifying moment restrictions, parametric restrictions and additional moment restrictions. Resampling methods based on such probabilities were shown to be efficient by Brown and Newey (2002). A set of simulation experiments reveals that the statistical tests based on the proposed bootstrap methods perform better than those that rely on first-order asymptotic theoryinfo:eu-repo/semantics/publishedVersio

Quasi-maximum likelihood and the Kernel Block Bootstrap for nonlinear dynamic models

This paper applies a novel bootstrap method, the kernel block bootstrap, to quasi-maximum likelihood estimation of dynamic models with stationary strong mixing data. The method first kernel weights the components comprising the quasi-log likelihood function in an appropriate way and then samples the resultant transformed components using the standard “m out of n” bootstrap. We investigate the first order asymptotic properties of the KBB method for quasi-maximum likelihood demonstrating, in particular, its consistency and the first-order asymptotic validity of the bootstrap approximation to the distribution of the quasi-maximum likelihood estimator. A set of simulation experiments for the mean regression model illustrates the efficacy of the kernel block bootstrap for quasi-maximum likelihood estimation.info:eu-repo/semantics/publishedVersio

Earthwork optimization system for sustainable highway construction

In highway construction, earthworks refer to the tasks of excavation, transportation, spreading and compaction of geomaterial (e.g. soil, rockfill and soil-rockfill mixture). Whereas relying heavily on machinery and repetitive processes, these tasks are highly susceptible to optimization. In this context Artificial Intelligent techniques, such as Data Mining and modern optimization can be applied for earthworks. A survey of these applications shows that they focus on the optimization of specific objectives and/or construction phases being possible to identify the capabilities and limitations of the analyzed techniques. Thus, according to the pinpointed drawbacks of these techniques, this paper describes a novel intelligent earthwork optimization system, capable of integrating DM, modern optimization and GIS technologies in order to optimize the earthwork processes throughout all phases of design and construction work. This integration system allows significant savings in time, cost and gas emissions contributing for a more sustainable construction

L’optimisation moderne dans les travaux de terrassement

Earthworks tasks are often regarded in transportation projects as some of the most demanding processes. In fact, sequential tasks such as excavation, transportation, spreading and compaction are strongly based on heavy mechanical equipment and repetitive processes, thus becoming as economically demanding as they are time-consuming. Moreover, actual construction requirements originate higher demands for productivity and safety in earthwork constructions. Given the percentual weight of costs and duration of earthworks in infrastructure construction, the optimal usage of every resource in these tasks is paramount. Considering the characteristics of an earthwork construction, it can be looked at as a production line based on resources (mechanical equipment) and dependency relations between sequential tasks, hence being susceptible to optimization. Up to the present, the steady development of Information Technology areas, such as databases, artificial intelligence and operations research, has resulted in the emergence of several technologies with potential application bearing that purpose in mind. Among these, modern optimization methods (also known as metaheuristics), such as evolutionary computation, have the potential to find high quality optimal solutions with a reasonable use of computational resources. In this context, this work describes an optimization algorithm for earthworks equipment allocation based on a modern optimization approach, which takes advantage of the concept that an earthwork construction can be regarded as a production line.RÉSUMÉ Les travaux de terrassements sont souvent considérés dans les projets d’infrastructure de transport comme un des processus les plus exigeants. En effet, des tâches séquentielles comme l’excavation, le transport, le régalage et le compactage sont fortement basées sur des équipements mécaniques lourds et des processus répétitifs, dont leur ampleur économique, étant donnée aussi le temps de réalisation. En outre, la construction actuelle est plus exigeante au niveau de la productivité et la sécurité dans les travaux de terrassements. Compte tenu du poids relatif des coûts et de la durée des travaux de terrassement dans les projets de construction d’infrastructures, l’utilisation optimale de toutes les ressources allouées à ces tâches est primordiale. Dans ce contexte les différentes phases des travaux de terrassements peuvent être considérées comme une ligne de production basée sur les ressources (équipement mécanique) et les relations de dépendance entre les tâches séquentielles et donc être susceptible d’optimisation. Jusqu’à présent, le développement des technologies de l’information, comme les bases de données, l’intelligence artificielle et la recherche opérationnelle, a donné lieu à l’émergence de plusieurs technologies applicables à ce bout. Parmi celles-ci, les méthodes modernes d’optimisation, tels que les algorithmes génétiques, sont mises en évidence en raison de leur fiabilité et aussi du réduit effort de calcul. Dans ce contexte, ce travail décrit un algorithme d’optimisation d’affectation de l’équipement de terrassements sur la base des approches d’optimisation modernes, tenant au compte l’idée selon laquelle les travaux de terrassement peut être considérée comme une ligne de production.(undefined

Combining data mining and evolutionary computation for multi-criteria optimization of earthworks

Earthworks tasks aim at levelling the ground surface at a target construction area and precede any kind of structural construction (e.g., road and railway construction). It is comprised of sequential tasks, such as excavation, transportation, spreading and compaction, and it is strongly based on heavy mechanical equipment and repetitive processes. Under this context, it is essential to optimize the usage of all available resources under two key criteria: the costs and duration of earthwork projects. In this paper, we present an integrated system that uses two artificial intelligence based techniques: data mining and evolutionary multi-objective optimization. The former is used to build data-driven models capable of providing realistic estimates of resource productivity, while the latter is used to optimize resource allocation considering the two main earthwork objectives (duration and cost). Experiments held using real-world data, from a construction site, have shown that the proposed system is competitive when compared with current manual earthwork design