977 resultados para Computer Technologies


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The primary goals of this study are to: embed sustainable concepts of energy consumption into certain part of existing Computer Science curriculum for English schools; investigate how to motivate 7-to-11 years old kids to learn these concepts; promote responsive ICT (Information and Communications Technology) use by these kids in their daily life; raise their awareness of today’s ecological challenges. Sustainability-related ICT lessons developed aim to provoke computational thinking and creativity to foster understanding of environmental impact of ICT and positive environmental impact of small changes in user energy consumption behaviour. The importance of including sustainability into the Computer Science curriculum is due to the fact that ICT is both a solution and one of the causes of current world ecological problems. This research follows Agile software development methodology. In order to achieve the aforementioned goals, sustainability requirements, curriculum requirements and technical requirements are firstly analysed. Secondly, the web-based user interface is designed. In parallel, a set of three online lessons (video, slideshow and game) is created for the website GreenICTKids.com taking into account several green design patterns. Finally, the evaluation phase involves the collection of adults’ and kids’ feedback on the following: user interface; contents; user interaction; impacts on the kids’ sustainability awareness and on the kids’ behaviour with technologies. In conclusion, a list of research outcomes is as follows: 92% of the adults learnt more about energy consumption; 80% of the kids are motivated to learn about energy consumption and found the website easy to use; 100% of the kids understood the contents and liked website’s visual aspect; 100% of the kids will try to apply in their daily life what they learnt through the online lessons.

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Trabalho apresentado em PAEE/ALE’2016, 8th International Symposium on Project Approaches in Engineering Education (PAEE) and 14th Active Learning in Engineering Education Workshop (ALE)

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We propose a model, based on the work of Brock and Durlauf, which looks at how agents make choices between competing technologies, as a framework for exploring aspects of the economics of the adoption of privacy-enhancing technologies. In order to formulate a model of decision-making among choices of technologies by these agents, we consider the following: context, the setting in which and the purpose for which a given technology is used; requirement, the level of privacy that the technology must provide for an agent to be willing to use the technology in a given context; belief, an agent’s perception of the level of privacy provided by a given technology in a given context; and the relative value of privacy, how much an agent cares about privacy in this context and how willing an agent is to trade off privacy for other attributes. We introduce these concepts into the model, admitting heterogeneity among agents in order to capture variations in requirement, belief, and relative value in the population. We illustrate the model with two examples: the possible effects on the adoption of iOS devices being caused by the recent Apple–FBI case; and the recent revelations about the non-deletion of images on the adoption of Snapchat.

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Recent developments in interactive technologies have seen major changes in the manner in which artists, performers, and creative individuals interact with digital music technology; this is due to the increasing variety of interactive technologies that are readily available today. Digital Musical Instruments (DMIs) present musicians with performance challenges that are unique to this form of computer music. One of the most significant deviations from conventional acoustic musical instruments is the level of physical feedback conveyed by the instrument to the user. Currently, new interfaces for musical expression are not designed to be as physically communicative as acoustic instruments. Specifically, DMIs are often void of haptic feedback and therefore lack the ability to impart important performance information to the user. Moreover, there currently is no standardised way to measure the effect of this lack of physical feedback. Best practice would expect that there should be a set of methods to effectively, repeatedly, and quantifiably evaluate the functionality, usability, and user experience of DMIs. Earlier theoretical and technological applications of haptics have tried to address device performance issues associated with the lack of feedback in DMI designs and it has been argued that the level of haptic feedback presented to a user can significantly affect the user’s overall emotive feeling towards a musical device. The outcome of the investigations contained within this thesis are intended to inform new haptic interface.

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Objectives: to evaluate the cognitive learning of nursing students in neonatal clinical evaluation from a blended course with the use of computer and laboratory simulation; to compare the cognitive learning of students in a control and experimental group testing the laboratory simulation; and to assess the extracurricular blended course offered on the clinical assessment of preterm infants, according to the students. Method: a quasi-experimental study with 14 Portuguese students, containing pretest, midterm test and post-test. The technologies offered in the course were serious game e-Baby, instructional software of semiology and semiotechnique, and laboratory simulation. Data collection tools developed for this study were used for the course evaluation and characterization of the students. Nonparametric statistics were used: Mann-Whitney and Wilcoxon. Results: the use of validated digital technologies and laboratory simulation demonstrated a statistically significant difference (p = 0.001) in the learning of the participants. The course was evaluated as very satisfactory for them. The laboratory simulation alone did not represent a significant difference in the learning. Conclusions: the cognitive learning of participants increased significantly. The use of technology can be partly responsible for the course success, showing it to be an important teaching tool for innovation and motivation of learning in healthcare.

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The multi-faced evolution of network technologies ranges from big data centers to specialized network infrastructures and protocols for mission-critical operations. For instance, technologies such as Software Defined Networking (SDN) revolutionized the world of static configuration of the network - i.e., by removing the distributed and proprietary configuration of the switched networks - centralizing the control plane. While this disruptive approach is interesting from different points of view, it can introduce new unforeseen vulnerabilities classes. One topic of particular interest in the last years is industrial network security, an interest which started to rise in 2016 with the introduction of the Industry 4.0 (I4.0) movement. Networks that were basically isolated by design are now connected to the internet to collect, archive, and analyze data. While this approach got a lot of momentum due to the predictive maintenance capabilities, these network technologies can be exploited in various ways from a cybersecurity perspective. Some of these technologies lack security measures and can introduce new families of vulnerabilities. On the other side, these networks can be used to enable accurate monitoring, formal verification, or defenses that were not practical before. This thesis explores these two fields: by introducing monitoring, protections, and detection mechanisms where the new network technologies make it feasible; and by demonstrating attacks on practical scenarios related to emerging network infrastructures not protected sufficiently. The goal of this thesis is to highlight this lack of protection in terms of attacks on and possible defenses enabled by emerging technologies. We will pursue this goal by analyzing the aforementioned technologies and by presenting three years of contribution to this field. In conclusion, we will recapitulate the research questions and give answers to them.

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The research project aims to improve the Design for Additive Manufacturing of metal components. Firstly, the scenario of Additive Manufacturing is depicted, describing its role in Industry 4.0 and in particular focusing on Metal Additive Manufacturing technologies and the Automotive sector applications. Secondly, the state of the art in Design for Additive Manufacturing is described, contextualizing the methodologies, and classifying guidelines, rules, and approaches. The key phases of product design and process design to achieve lightweight functional designs and reliable processes are deepened together with the Computer-Aided Technologies to support the approaches implementation. Therefore, a general Design for Additive Manufacturing workflow based on product and process optimization has been systematically defined. From the analysis of the state of the art, the use of a holistic approach has been considered fundamental and thus the use of integrated product-process design platforms has been evaluated as a key element for its development. Indeed, a computer-based methodology exploiting integrated tools and numerical simulations to drive the product and process optimization has been proposed. A validation of CAD platform-based approaches has been performed, as well as potentials offered by integrated tools have been evaluated. Concerning product optimization, systematic approaches to integrate topology optimization in the design have been proposed and validated through product optimization of an automotive case study. Concerning process optimization, the use of process simulation techniques to prevent manufacturing flaws related to the high thermal gradients of metal processes is developed, providing case studies to validate results compared to experimental data, and application to process optimization of an automotive case study. Finally, an example of the product and process design through the proposed simulation-driven integrated approach is provided to prove the method's suitability for effective redesigns of Additive Manufacturing based high-performance metal products. The results are then outlined, and further developments are discussed.

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The fourth industrial revolution, also known as Industry 4.0, has rapidly gained traction in businesses across Europe and the world, becoming a central theme in small, medium, and large enterprises alike. This new paradigm shifts the focus from locally-based and barely automated firms to a globally interconnected industrial sector, stimulating economic growth and productivity, and supporting the upskilling and reskilling of employees. However, despite the maturity and scalability of information and cloud technologies, the support systems already present in the machine field are often outdated and lack the necessary security, access control, and advanced communication capabilities. This dissertation proposes architectures and technologies designed to bridge the gap between Operational and Information Technology, in a manner that is non-disruptive, efficient, and scalable. The proposal presents cloud-enabled data-gathering architectures that make use of the newest IT and networking technologies to achieve the desired quality of service and non-functional properties. By harnessing industrial and business data, processes can be optimized even before product sale, while the integrated environment enhances data exchange for post-sale support. The architectures have been tested and have shown encouraging performance results, providing a promising solution for companies looking to embrace Industry 4.0, enhance their operational capabilities, and prepare themselves for the upcoming fifth human-centric revolution.

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The discovery of new materials and their functions has always been a fundamental component of technological progress. Nowadays, the quest for new materials is stronger than ever: sustainability, medicine, robotics and electronics are all key assets which depend on the ability to create specifically tailored materials. However, designing materials with desired properties is a difficult task, and the complexity of the discipline makes it difficult to identify general criteria. While scientists developed a set of best practices (often based on experience and expertise), this is still a trial-and-error process. This becomes even more complex when dealing with advanced functional materials. Their properties depend on structural and morphological features, which in turn depend on fabrication procedures and environment, and subtle alterations leads to dramatically different results. Because of this, materials modeling and design is one of the most prolific research fields. Many techniques and instruments are continuously developed to enable new possibilities, both in the experimental and computational realms. Scientists strive to enforce cutting-edge technologies in order to make progress. However, the field is strongly affected by unorganized file management, proliferation of custom data formats and storage procedures, both in experimental and computational research. Results are difficult to find, interpret and re-use, and a huge amount of time is spent interpreting and re-organizing data. This also strongly limit the application of data-driven and machine learning techniques. This work introduces possible solutions to the problems described above. Specifically, it talks about developing features for specific classes of advanced materials and use them to train machine learning models and accelerate computational predictions for molecular compounds; developing method for organizing non homogeneous materials data; automate the process of using devices simulations to train machine learning models; dealing with scattered experimental data and use them to discover new patterns.

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The recent trend of moving Cloud Computing capabilities to the Edge of the network is reshaping how applications and their middleware supports are designed, deployed, and operated. This new model envisions a continuum of virtual resources between the traditional cloud and the network edge, which is potentially more suitable to meet the heterogeneous Quality of Service (QoS) requirements of diverse application domains and next-generation applications. Several classes of advanced Internet of Things (IoT) applications, e.g., in the industrial manufacturing domain, are expected to serve a wide range of applications with heterogeneous QoS requirements and call for QoS management systems to guarantee/control performance indicators, even in the presence of real-world factors such as limited bandwidth and concurrent virtual resource utilization. The present dissertation proposes a comprehensive QoS-aware architecture that addresses the challenges of integrating cloud infrastructure with edge nodes in IoT applications. The architecture provides end-to-end QoS support by incorporating several components for managing physical and virtual resources. The proposed architecture features: i) a multilevel middleware for resolving the convergence between Operational Technology (OT) and Information Technology (IT), ii) an end-to-end QoS management approach compliant with the Time-Sensitive Networking (TSN) standard, iii) new approaches for virtualized network environments, such as running TSN-based applications under Ultra-low Latency (ULL) constraints in virtual and 5G environments, and iv) an accelerated and deterministic container overlay network architecture. Additionally, the QoS-aware architecture includes two novel middlewares: i) a middleware that transparently integrates multiple acceleration technologies in heterogeneous Edge contexts and ii) a QoS-aware middleware for Serverless platforms that leverages coordination of various QoS mechanisms and virtualized Function-as-a-Service (FaaS) invocation stack to manage end-to-end QoS metrics. Finally, all architecture components were tested and evaluated by leveraging realistic testbeds, demonstrating the efficacy of the proposed solutions.

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The overall prevalence of infertility was estimated to be 3.5-16.7% in developing countries and 6.9-9.3% in developed countries. Furthermore, according to reports from some regions of sub-Saharan Africa, the prevalence rate is 30-40%. The consequences of infertility and how it affects the lives of women in poor-resource settings, particularly in developing countries, has become an important issue to be discussed in reproductive health. In some societies, the inability to fulfill the desire to have children makes life difficult for the infertile couple. In many regions, infertility is considered a tragedy that affects not only the infertile couple or woman, but the entire family. This is a position paper which encompasses a review of the needs of low-income infertile couples, mainly those living in developing countries, regarding access to infertility care, including ART and initiatives to provide ART at low or affordable cost. Information was gathered from the databases MEDLINE, CENTRAL, POPLINE, EMBASE, LILACS, and ICTRP with the key words: infertility, low income, assisted reproductive technologies, affordable cost, low cost. There are few initiatives geared toward implementing ART procedures at low cost or at least at affordable cost in low-income populations. Nevertheless, from recent studies, possibilities have emerged for new low-cost initiatives that can help millions of couples to achieve the desire of having a biological child. It is necessary for healthcare professionals and policymakers to take into account these new initiatives in order to implement ART in resource-constrained settings.

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Geographic Data Warehouses (GDW) are one of the main technologies used in decision-making processes and spatial analysis, and the literature proposes several conceptual and logical data models for GDW. However, little effort has been focused on studying how spatial data redundancy affects SOLAP (Spatial On-Line Analytical Processing) query performance over GDW. In this paper, we investigate this issue. Firstly, we compare redundant and non-redundant GDW schemas and conclude that redundancy is related to high performance losses. We also analyze the issue of indexing, aiming at improving SOLAP query performance on a redundant GDW. Comparisons of the SB-index approach, the star-join aided by R-tree and the star-join aided by GiST indicate that the SB-index significantly improves the elapsed time in query processing from 25% up to 99% with regard to SOLAP queries defined over the spatial predicates of intersection, enclosure and containment and applied to roll-up and drill-down operations. We also investigate the impact of the increase in data volume on the performance. The increase did not impair the performance of the SB-index, which highly improved the elapsed time in query processing. Performance tests also show that the SB-index is far more compact than the star-join, requiring only a small fraction of at most 0.20% of the volume. Moreover, we propose a specific enhancement of the SB-index to deal with spatial data redundancy. This enhancement improved performance from 80 to 91% for redundant GDW schemas.

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OBJETIVO: Com a inclusão das novas tecnologias contemporâneas, a Internet e os jogos eletrônicos tornaram-se ferramentas de uso amplo e irrestrito, transformando-se em um dos maiores fenômenos mundiais da última década. Diversas pesquisas atestam os benefícios desses recursos, mas seu uso sadio e adaptativo progressivamente deu lugar ao abuso e à falta de controle ao criar severos impactos na vida cotidiana de milhões de usuários. O objetivo deste estudo foi revisar de forma sistemática os artigos que examinam a dependência de Internet e jogos eletrônicos na população geral. Almejamos, portanto, avaliar a evolução destes conceitos no decorrer da última década, assim como contribuir para a melhor compreensão do quadro e suas comorbidades. MÉTODO: Foi feita uma revisão sistemática da literatura através do MedLine, Lilacs, SciELO e Cochrane usando-se como parâmetro os termos: "Internet addiction", pathological "Internet use", "problematic Internet use", "Internet abuse", "videogame", "computer games" e "electronic games". A busca eletrônica foi feita até dezembro de 2007. DISCUSSÃO: Estudos realizados em diferentes países apontam para prevalências ainda muito diversas, o que provavelmente se deve à falta de consenso e ao uso de diferentes denominações, dando margem à adoção de distintos critérios diagnósticos. Muitos pacientes que relatam o uso abusivo e dependência passam a apresentar prejuízos significativos na vida profissional, acadêmica (escolar), social e familiar. CONCLUSÕES: São necessárias novas investigações para determinar se esse uso abusivo de Internet e de jogos eletrônicos pode ser compreendido como uma das mais novas classificações psiquiátricas do século XXI ou apenas substratos de outros transtornos.

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This paper proposes an architecture for machining process and production monitoring to be applied in machine tools with open Computer numerical control (CNC). A brief description of the advantages of using open CNC for machining process and production monitoring is presented with an emphasis on the CNC architecture using a personal computer (PC)-based human-machine interface. The proposed architecture uses the CNC data and sensors to gather information about the machining process and production. It allows the development of different levels of monitoring systems with mininium investment, minimum need for sensor installation, and low intrusiveness to the process. Successful examples of the utilization of this architecture in a laboratory environment are briefly described. As a Conclusion, it is shown that a wide range of monitoring solutions can be implemented in production processes using the proposed architecture.