SOS Imprensa: 20 anos de exercício de cidadania e educação

Em 2016 o SOS Imprensa completou 20 anos de atuação. Iniciando suas atividades na Faculdade de Comunicação da Universidade de Brasília – UnB (Brasília/Brasil) em 1996, como um projeto de extensão para apoiar vítimas da imprensa, passou em 2000 a ser um observatório e a fazer parte da RENOI – Rede Nacional de Observatórios de Imprensa, lançada em 2005. A propósito da celebração das suas duas décadas de existência, fizemos uma análise do conteúdo de suas publicações no Facebook, refletindo sobre as contribuições que as mesmas podem ter para uma educação para a mídia, considerada por autores como Herrera, Mota e Christofoletti, entre outros, como uma das funções dos observatórios de mídia, conceituados por Bertrand como MAS – Media Accountability Systems (ou MARS – Meios de Assegurar a Responsabilidade Social da Mídia). Entre campanhas, poemas e muitos artigos de opinião encontrados, utilizamos uma abordagem quanti-qualitativa para analisar que temas destacam- -se nessas publicações, quais características mais se aproximam da noção de cidadania e participação que o observatório pretende ter e como esses textos podem nos ajudar a refletir sobre o que seriam boas práticas de jornalismo. Também foram feitos alguns questionários e entrevistas semiestruturadas com pessoas que fazem e fizeram parte da história desse observatório. O que fica claro para nós é que, apesar de oferecer um serviço de extrema importância ao público, a relevância do SOS Imprensa fica limitada devido à falta de conhecimento dos direitos que o cidadão brasileiro tem. E, neste caso específico, do Direito à Comunicação, o que nos faz pensar na urgência cada vez maior de uma Alfabetização Midiática como política pública no país.info:eu-repo/semantics/publishedVersio

Intelligent compaction technology for geomaterials. A demonstration project

Intelligent Compaction (IC), which is a part of Compaction Management, is a real time automatic adjustment and continuous compaction control technology of geomaterials or asphalt layers. The adjustment of the compaction parameters by the equipment is conducted simultaneously to the compaction process, as well as the continuous measurement of a dynamic compaction value, which is an indicator of the material’s degree of compaction. This study seeks to assess the advantages and disadvantages of IC, as well as formulating a comparison with conventional compaction methods in terms of efficiency. This goal was achieved through in situ application of various technologies to two distinct types of material: a soil-rockfill mixture and a sandy soil. Data was obtained and analysed by the IC continuous information, as well as by the application of several different conventional compaction control tests and methods. Results show that the IC technology presents a superior performance, as well as various advantages when compared to conventional compactors.Fundação para a Ciência e a Tecnologia (FCT

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

Una nueva especie de Pagurus (Crustacea: Decapoda: Paguridae), nuevos registros y redescripción de cangrejos ermitaños para el Pacífico mexicano

New records are provided for three species of little-known pagurids. All the material reported was collected by the R/V “El Puma” in the central Gulf of California during the GUAYTEC II cruise. New material is reported for Iridopagurus haigae García-Gómez, 1983, Enallopagurus spinicarpus (Glassell, 1937), and Solenopagurus diomedeae (Faxon, 1893), and these two latter species are redescribed. A new species of hermit crab of the genus Pagurus Fabricius, 1775, is described and illustrated in detail. Among the eastern Pacific species of Pagurus, this new species resembles Pagurus meloi Lemaitre and Cruz Castaño, 2004, P. imarpe Haig, 1974 and P. delsolari Haig, 1974, but differs from these three species in the armature and setation of the chelipeds and second and third pereopods, the shape and armature of the telson, and the number of rows of scales on pereopodal rasp and the presence of a preungual process.Se proporcionan nuevos registros de tres especies de paguridos poco conocidos, Iridopagurus haigae García-Gómez, 1983, Enallopagurus spinicarpus (Glassell, 1937) y Solenopagurus diomedeae (Faxon, 1893) recolectados durante el crucero GUAYTEC II abordo del B/O “El Puma” en el golfo de California central; además se proporciona una redescripción para las dos últimas especies. Se describe e ilustra en detalle una nueva especie de Pagurus Fabricius, 1775. La nueva especie de Pagurus presenta similaridad con Pagurus meloi Lemaitre and Cruz Castaño, 2004, P. imarpe Haig, 1974 y P. delsolari Haig, 1974, pero se diferencia de estas últimas por la armadura y la setación de los quelípedos y los pies ambulatorios, la forma y la armadura del telson, y el número de líneas de escamas sobre la raspa propodal y la presencia de un proceso preungual en los cuartos pereiópodos

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

Development of an intelligent earthwork optimization system

Tese de Doutoramento em Engenharia Civil.Earthworks are often regarded as one of the most costly and time-consuming components of linear infrastructure constructions (e.g., road, railway and airports). Since actual construction requirements originate higher demands for productivity and safety in earthwork constructions, the optimal usage of every resource in these tasks is paramount. The management of resources in an earthwork construction site is, in great part, a function of the allocation of the available equipment, for which there are a vast number of possible equipment allocation combinations. Simultaneously, while there is often high competitiveness, where the pressure is to provide the least possible costs and durations, contractors and project designers often settle for an allocation solution that is mostly based on their own intuition and accumulated experience. This guarantees neither optimal resource usage, nor a solution associated with minimal cost and duration. The optimal 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 fact, 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 plant with the capacity of a truck plant 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 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 analyse and optimize the possible transportation networks. In this context, the use of geographic information systems 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 work explores the integration of different technologies in order to allow for an optimization of the earthworks process. 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). The results stemming from the application of the system to a case study in a Portuguese earthwork construction site are presented. These comprise the assessment of the system performance, including a comparison between different optimization methods. Furthermore, an analysis regarding the improvement of workflow in the construction site after the implementation of the system is discussed, in the context of several comparisons between original (i.e., obtained by manual design) and optimized allocation solutions. Ultimately, these results illustrate the potential and importance of using this kind of technologies in the management and optimization of earthworks.Em projetos de construção de infraestruturas de transporte lineares (e.g., estradas, vias férreas e aeroportos), as terraplenagens são geralmente consideradas um dos componentes com custos e tempos de execução mais elevados. Tendo em conta que cada vez mais é exigido um aumento na produtividade e segurança no contexto das construções de terraplenagens, torna-se fulcral a otimização de todas as tarefas relacionadas com este processo. A gestão de recursos num estaleiro de terraplenagens é, em grande parte, função da alocação do equipamento mecânico disponível, para a qual existe um número quase infinito de soluções possíveis em cada caso. Simultaneamente, embora se verifique um alto nível de competitividade nesta área, onde o objetivo é obter custos e durações de execução o mais baixos possíveis, o planeamento das tarefas de terraplenagens é em grande parte baseado na experiência acumulada dos engenheiros e especialistas. Porém, tais métodos não garantem nem uma utilização ótima dos recursos disponíveis, nem uma solução associada ao custo e duração de execução mínimos. A alocação ótima de equipamento mecânico em tarefas de terraplenagens é um problema complexo que requer o estudo de vários aspectos distintos, assim como o conhecimento de um elevado número de fatores. De facto, estas tarefas são demarcadas por combinações de atividades repetitivas, fortemente baseadas no uso de equipamento mecânico (i.e., recursos), tal como escavadoras, dumpers, espalhadores e compactadores. Para que seja possível a sua alocação ótima, é essencial o conhecimento das suas especificações (e.g., capacidade, peso, potência) e das condições a que estão sujeitos durante a sua atividade (e.g., tipos de material, volumes disponíveis em frentes de escavação e necessários em frentes de aterro). Este conhecimento pode ser traduzido na produtividade de cada equipamento quando sujeito a determinadas condições de trabalho. Para além disso, uma vez que as terraplenagens consistem em tarefas inerentemente sequenciais e interdependentes, a interação entre os equipamentos tem de ser tomada em consideração. Um exemplo típico deste aspecto pode ser ilustrado pela necessidade de sincronizar a produtividade de uma equipa de escavadoras com a de uma equipa de dumpers, para que seja possível um fluxo constande de escavação e transporte de geomateriais das frentes de escavação para as frentes de aterro. Tendo em conta as características não triviais do problema de alocação em terraplenagens, os métodos convencionais de procura de soluções, tais como Investigação Operacional (e.g. programação linear) e busca exaustiva são impraticáveis. Assim, uma potencial solução é a adoção de metaheurísticas – métodos de otimização moderna capazes de efetuar a busca de soluções em espaços de procura extensos com níveis de exigência computacional razoáveis. Embora estes métodos sejam práticos para a otimização de problemas de elevado nível de complexidade, como é o caso das terraplenagens, existe ainda a necessidade de abordar o problema relacionado com a escassez de conhecimento de vários parâmetros necessários à otimização, tais como a produtividade dos equipamentos sujeitos a diferentes condições de trabalho. Considerando os recentes avanços da tecnologia e o aumento da prática de recolha de dados, verifica-se a disponibilidade de extensas bases de dados de construção, incluindo na área de terraplenagens. Neste sentido, tecnologias tais como o data mining (DM) surgem como ferramentas ideais para abordar esse problema. De fato, as capacidades de aprendizagem dos algoritmos de DM podem ser aplicadas às bases de dados existentes com informação relativa à produtividade de vários tipos de equipamento sujeitos a diferentes condições de trabalho. Mediante este processo, o conhecimento extraído pode então ser usado em novos casos para estimar a produtividade de equipamentos em condições semelhantes. Adicionalmente, uma vez que as tarefas de terraplenagens incluem o transporte de materiais de frentes de escavação para frentes de aterro, como previamente referido, torna-se ainda imperativa a análise e otimização das potenciais trajetórias de transporte ao longo do estaleiro. Neste contexto, a utilização de sistemas de informação geográficos providencia um método eficaz de estudo e escolha das melhores trajetórias para o equipamento de transporte, melhorando o fluxo de trabalho no estaleiro. Este trabalho explora a integração de diferentes tecnologias tendo em vista a otimização das tarefas de terraplenagens. Isto concretiza-se sob a forma de um sistema de otimização evolutiva multi-objetivo, capaz de eleger a melhor distribuição dos equipamentos de terraplenagens disponíveis que minimiza um determinado conjunto de objetivos (e.g., custo, duração, impacto ambiental). São apresentados os resultados decorrentes da aplicação do sistema desenvolvido num caso de estudo, associado a um estaleiro de terraplenagens em Portugal. Estes abrangem a avaliação do desempenho do sistema de otimização, incluindo a comparação de vários métodos de otimização. Para além disso, é realizada uma análise relativa ao melhoramento do fluxo de trabalho no estaleiro após a implementação do sistema, sendo enquadrada numa série de comparações entre as soluções originais (i.e., obtidas pelos métodos convencionais de dimensionamento) e as soluções otimizadas correspondentes. Em última análise, estes resultados ilustram o potencial e a importância da utilização deste tipo de tecnologias na gestão e otimização das terraplenagens.Fundação para a Ciência e a Tecnologia (FCT) SFRH/BD/71501/2010

An evolutionary multi-objective optimization system for earthworks

Earthworks involve the levelling or shaping of a target area through the moving or processing of the ground surface. Most construction projects require earthworks, which are heavily dependent on mechanical equipment (e.g., excavators, trucks and compactors). Often, earthworks are the most costly and time-consuming component of infrastructure constructions (e.g., road, railway and airports) and current pressure for higher productivity and safety highlights the need to optimize earthworks, which is a nontrivial task. Most previous attempts at tackling this problem focus on single-objective optimization of partial processes or aspects of earthworks, overlooking the advantages of a multi-objective and global optimization. This work describes a novel optimization system based on an evolutionary multi-objective approach, capable of globally optimizing several objectives simultaneously and dynamically. The proposed system views an earthwork construction as a production line, where the goal is to optimize resources under two crucial criteria (costs and duration) and focus the evolutionary search (non-dominated sorting genetic algorithm-II) on compaction allocation, using linear programming to distribute the remaining equipment (e.g., excavators). Several experiments were held using real-world data from a Portuguese construction site, showing that the proposed system is quite competitive when compared with current manual earthwork equipment allocation.The authors wish to thank FCT for the financial support under the doctoral Grant SFRH/BD/71501/2010, as well as the construction company that kindly provided the real-world data. Also, we wish to thank Olaf Mersmann for kindly providing the R code for the SMS-EMOA algorithm

Segurança privada em França

ResPublica : Revista Lusófona de Ciência Política, Segurança e Relações InternacionaisO conceito de segurança, em abstrato, está geralmente relacionado com perigo ou ameaça e com o sentimento de medo. O termo deriva do latim securitas, referindo-se à qualidade daquilo que é seguro, ou seja, àquilo que está ao abrigo de quaisquer perigos, danos ou riscos. De acordo com o art.º L111-1 do Código da Segurança Interna, «[a] segurança é um direito fundamental e uma das condições do exercício das liberdades individuais e coletivas. O Estado tem o dever de garantir a segurança, zelando, em todo o território da República, pela defesa das instituições e dos interesses nacionais, pelo respeito das leis, pela manutenção da paz e da ordem pública, pela proteção das pessoas e dos bens. Ele associa à política de segurança, no quadro de dispositivos locais cuja estrutura é definida por via regulamentar, as coletividades territoriais e os estabelecimentos públicos de cooperação intercomunal, bem como os representantes das profissões, dos serviços e das associações confrontados com manifestações de delinquência ou trabalhando nos domínios da prevenção, da mediação, da luta contra a exclusão ou da ajuda às vítimas» (França, 2017)