969 resultados para Collaborative environment


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Innovation is considered crucial for enterprises survival and current economic environment demands the best ways of achieving it. However, the development of complex products and services require the utilization of diverse know-how and technology, which enterprises may not hold. An effective strategy for achieving them is to rely in open innovation. Still, open innovation projects may fail for many causes, e.g. due to the dynamics of collaboration between partners. To effectively benefit from open innovation, it is recommended the utilization of adequate risk models. For achieving such models, a preliminary conceptualization of open innovation and risk is necessary, which includes modeling experiments with existing risk models, such as the FMEA.

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Anchored on a systemic perspective of innovation and particularly on the triple helix model, which highlights the state, university and companies as central players, this paper aims to discuss the factors that enable or constrain the processes of innovation, using the system thinking approach to understand the academia-industry symbiosis. The paper's empirical section is based on a case study on Portugal's major highway management concessionaire. In order to ensure a "healthy" co-innovation environment, the archetype studied emphasizes the need to implement coordination mechanisms such as communication routines and metrics to monitor collaborative behavior in addition to the need to develop global goals that align the efforts of the partners.

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During last decades there has been a trend to build collaboration platforms as enablers for groups of enterprises to jointly provide integrated services and products. As a result, the notion of business ecosystem is getting wider acceptance. However, a critical issue that is still open, despite some efforts in this area, is the identification of adequate performance indicators to measure and motivate sustainable collaboration. This work-in-progress addresses this concern, briefly presenting the state of the art of relevant contributing areas such as, collaborative networks, business ecosystems, enterprise performance indicators, social networks analysis, and supply chains. Complementarily, through an assessment of current gaps, the research challenges are identified and an approach for further development is proposed.

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The use of demand response programs enables the adequate use of resources of small and medium players, bringing high benefits to the smart grid, and increasing its efficiency. One of the difficulties to proceed with this paradigm is the lack of intelligence in the management of small and medium size players. In order to make demand response programs a feasible solution, it is essential that small and medium players have an efficient energy management and a fair optimization mechanism to decrease the consumption without heavy loss of comfort, making it acceptable for the users. This paper addresses the application of real-time pricing in a house that uses an intelligent optimization module involving artificial neural networks.

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Harnessing idle PCs CPU cycles, storage space and other resources of networked computers to collaborative are mainly fixated on for all major grid computing research projects. Most of the university computers labs are occupied with the high puissant desktop PC nowadays. It is plausible to notice that most of the time machines are lying idle or wasting their computing power without utilizing in felicitous ways. However, for intricate quandaries and for analyzing astronomically immense amounts of data, sizably voluminous computational resources are required. For such quandaries, one may run the analysis algorithms in very puissant and expensive computers, which reduces the number of users that can afford such data analysis tasks. Instead of utilizing single expensive machines, distributed computing systems, offers the possibility of utilizing a set of much less expensive machines to do the same task. BOINC and Condor projects have been prosperously utilized for solving authentic scientific research works around the world at a low cost. In this work the main goal is to explore both distributed computing to implement, Condor and BOINC, and utilize their potency to harness the ideal PCs resources for the academic researchers to utilize in their research work. In this thesis, Data mining tasks have been performed in implementation of several machine learning algorithms on the distributed computing environment.

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Dissertation to obtain the degree of Doctor in Electrical and Computer Engineering, specialization of Collaborative Networks

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The project started in 2009 with the support of DAAD in Germany and CRUP in Portugal under the “Collaborative German-Portuguese University Actions” programme. One central goal is the further development of a theory of technology assessment applied to robotics and autonomous systems in general that reflects in its methodology the changing conditions of knowledge production in modern societies and the emergence of new robotic technologies and of associated disruptive changes. Relevant topics here are handling broadened future horizons and new clusters of science and technology (medicine, engineering, interfaces, industrial automation, micro-devices, security and safety), as well as new governance structures in policy decision making concerning research and development (R

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The wide use of antibiotics in aquaculture has led to the emergence of resistant microbial species. It should be avoided/minimized by controlling the amount of drug employed in fish farming. For this purpose, the present work proposes test-strip papers aiming at the detection/semi-quantitative determination of organic drugs by visual comparison of color changes, in a similar analytical procedure to that of pH monitoring by universal pH paper. This is done by establishing suitable chemical changes upon cellulose, attributing the paper the ability to react with the organic drug and to produce a color change. Quantitative data is also enabled by taking a picture and applying a suitable mathematical treatment to the color coordinates given by the HSL system used by windows. As proof of concept, this approach was applied to oxytetracycline (OXY), one of the antibiotics frequently used in aquaculture. A bottom-up modification of paper was established, starting by the reaction of the glucose moieties on the paper with 3-triethoxysilylpropylamine (APTES). The so-formed amine layer allowed binding to a metal ion by coordination chemistry, while the metal ion reacted after with the drug to produce a colored compound. The most suitable metals to carry out such modification were selected by bulk studies, and the several stages of the paper modification were optimized to produce an intense color change against the concentration of the drug. The paper strips were applied to the analysis of spiked environmental water, allowing a quantitative determination for OXY concentrations as low as 30 ng/mL. In general, this work provided a simple, method to screen and discriminate tetracycline drugs, in aquaculture, being a promising tool for local, quick and cheap monitoring of drugs.

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Solid-contact sensors for the selective screening of sulfadiazine (SDZ) in aquaculture waters are reported. Sensor surfaces were made from PVC membranes doped with tetraphenylporphyrin-manganese(III) chloride, α-cyclodextrin, β-cyclodextrin, or γ-cyclodextrin ionophores that were dispersed in plasticizer. Some membranes also presented a positive or a negatively charged additive. Phorphyrin-based sensors relied on a charged carrier mechanism. They exhibited a near-Nernstian response with slopes of 52 mV decade−1 and detection limits of 3.91 × 10−5 mol L−1. The addition of cationic lipophilic compounds to the membrane originated Nernstian behaviours, with slopes ranging 59.7–62.0 mV decade−1 and wider linear ranges. Cyclodextrin-based sensors acted as neutral carriers. In general, sensors with positively charged additives showed an improved potentiometric performance when compared to those without additive. Some SDZ selective membranes displayed higher slopes and extended linear concentration ranges with an increasing amount of additive (always <100% ionophore). The sensors were independent from the pH of test solutions within 2–7. The sensors displayed fast response, always <15 s. In general, a good discriminating ability was found in real sample environment. The sensors were successfully applied to the fast screening of SDZ in real waters samples from aquaculture fish farms. The method offered the advantages of simplicity, accuracy, and automation feasibility. The sensing membrane may contribute to the development of small devices allowing in locus measurements of sulfadiazine or parent-drugs.

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The aim of this research was to evaluate the prevalence of Sthaphylococcus spp. and S. aureus in the odontological clinic environment (air), their production of beta-lactamase and antibacterial susceptibility to the major antibiotics utilized in medical particle. During 12 months of samples collect were isolated 9775 CFU by MSA medium suggesting a high amount of Staphylococcus spp. in the clinic environment which can appear through aerosols. A total of 3149 colonies (32.2%) were suggestive of pathogenic staphylococci. Gram coloration, catalase test, colony-mallow growing on chromogenic medium, and coagulase test confirmed the identity of 44 (0.45%) S. aureus isolates. Of these, 35 isolates (79.5%) showed production of beta-lactamase by CefinaseTM discs and resistance to ampicillin, erythromycin (7 isolates) and tetracycline (1 isolate) suggesting the existence of multiresistant isolates. The evaluation of the oxacillin MIC by Etest® assays showed susceptibility patterns suggesting the inexistence of the mecA gene in chromosomal DNA. These results point out to the need of a larger knowledge on the contamination means and propagation of this microorganism into the odontological clinic.

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This paper presents a framework for a robotic production line simulation learning environment using Autonomous Ground Vehicles (AGV). An eLearning platform is used as interface with the simulator. The objective is to introduce students to the production robotics area using a familiar tool, an eLearning platform, and a framework that simulates a production line using AGVs. This framework allows students to learn about robotics but also about several areas of industrial management engineering without requiring an extensive prior knowledge on the robotics area. The robotic production line simulation learning environment simulates a production environment using AGVs to transport materials to and from the production line. The simulator allows students to validate the AGV dynamics and provides information about the whole materials supplying system which includes: supply times, route optimization and inventory management. The students are required to address several topics such as: sensors, actuators, controllers and an high level management and optimization software. This simulator was developed with a known open source tool from robotics community: Player/Stage. This tool was extended with several add-ons so that students can be able to interact with a complex simulation environment. These add-ons include an abstraction communication layer that performs events provided by the database server which is programmed by the students. An eLearning platform is used as interface between the students and the simulator. The students can visualize the effects of their instructions/programming in the simulator that they can access via the eLearning platform. The proposed framework aims to allow students from different backgrounds to fully experience robotics in practice by suppressing the huge gap between theory and practice that exists in robotics. Using an eLearning platform eliminates installation problems that can occur from different computers software distribution and makes the simulator accessible by all students at school and at home.

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Teaching and learning computer programming is as challenging as difficult. Assessing the work of students and providing individualised feedback to all is time-consuming and error prone for teachers and frequently involves a time delay. The existent tools and specifications prove to be insufficient in complex evaluation domains where there is a greater need to practice. At the same time Massive Open Online Courses (MOOC) are appearing revealing a new way of learning, more dynamic and more accessible. However this new paradigm raises serious questions regarding the monitoring of student progress and its timely feedback. This paper provides a conceptual design model for a computer programming learning environment. This environment uses the portal interface design model gathering information from a network of services such as repositories and program evaluators. The design model includes also the integration with learning management systems, a central piece in the MOOC realm, endowing the model with characteristics such as scalability, collaboration and interoperability. This model is not limited to the domain of computer programming and can be adapted to any complex area that requires systematic evaluation with immediate feedback.

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4th International Conference, SIMPAR 2014, Bergamo, Italy, October 20-23, 2014