765 resultados para Wireless Sensor and Actuator Networks. Simulation. Reinforcement Learning. Routing Techniques


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Community networks are IP-based computer networks that are operated by a community as a common good. In Europe, the most well-known community networks are Guifi in Catalonia, Freifunk in Berlin, Ninux in Italy, Funkfeuer in Vienna and the Athens Wireless Metropolitan Network in Greece. This paper deals with community networks as alternative forms of Internet access and alternative infrastructures and asks: What does sustainability and unsustainability mean in the context of community networks? What advantages do such networks have over conventional forms of Internet access and infrastructure provided by large telecommunications corporations? In addition what disadvantages do they face at the same time? This article provides a framework for thinking dialectically about the un/sustainability of community networks. It provides a framework of practical questions that can be asked when assessing power structures in the context of Internet infrastructures and access. It presents an overview of environmental, economic, political and cultural contradictions that community networks may face as well as a typology of questions that can be asked in order to identify such contradictions.

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Different types of serious games have been used in elucidating computer science areas such as computer games, mobile games, Lego-based games, virtual worlds and webbased games. Different evaluation techniques have been conducted like questionnaires, interviews, discussions and tests. Simulation have been widely used in computer science as a motivational and interactive learning tool. This paper aims to evaluate the possibility of successful implementation of simulation in computer programming modules. A framework is proposed to measure the impact of serious games on enhancing students understanding of key computer science concepts. Experiments will be held on the EEECS of Queen’s University Belfast students to test the framework and attain results.

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A major weakness among loading models for pedestrians walking on flexible structures proposed in recent years is the various uncorroborated assumptions made in their development. This applies to spatio-temporal characteristics of pedestrian loading and the nature of multi-object interactions. To alleviate this problem, a framework for the determination of localised pedestrian forces on full-scale structures is presented using a wireless attitude and heading reference systems (AHRS). An AHRS comprises a triad of tri-axial accelerometers, gyroscopes and magnetometers managed by a dedicated data processing unit, allowing motion in three-dimensional space to be reconstructed. A pedestrian loading model based on a single point inertial measurement from an AHRS is derived and shown to perform well against benchmark data collected on an instrumented treadmill. Unlike other models, the current model does not take any predefined form nor does it require any extrapolations as to the timing and amplitude of pedestrian loading. In order to assess correctly the influence of the moving pedestrian on behaviour of a structure, an algorithm for tracking the point of application of pedestrian force is developed based on data from a single AHRS attached to a foot. A set of controlled walking tests with a single pedestrian is conducted on a real footbridge for validation purposes. A remarkably good match between the measured and simulated bridge response is found, indeed confirming applicability of the proposed framework.

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Traditional heuristic approaches to the Examination Timetabling Problem normally utilize a stochastic method during Optimization for the selection of the next examination to be considered for timetabling within the neighbourhood search process. This paper presents a technique whereby the stochastic method has been augmented with information from a weighted list gathered during the initial adaptive construction phase, with the purpose of intelligently directing examination selection. In addition, a Reinforcement Learning technique has been adapted to identify the most effective portions of the weighted list in terms of facilitating the greatest potential for overall solution improvement. The technique is tested against the 2007 International Timetabling Competition datasets with solutions generated within a time frame specified by the competition organizers. The results generated are better than those of the competition winner in seven of the twelve examinations, while being competitive for the remaining five examinations. This paper also shows experimentally how using reinforcement learning has improved upon our previous technique.

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As a way to gain greater insights into the operation of online communities, this dissertation applies automated text mining techniques to text-based communication to identify, describe and evaluate underlying social networks among online community members. The main thrust of the study is to automate the discovery of social ties that form between community members, using only the digital footprints left behind in their online forum postings. Currently, one of the most common but time consuming methods for discovering social ties between people is to ask questions about their perceived social ties. However, such a survey is difficult to collect due to the high investment in time associated with data collection and the sensitive nature of the types of questions that may be asked. To overcome these limitations, the dissertation presents a new, content-based method for automated discovery of social networks from threaded discussions, referred to as ‘name network’. As a case study, the proposed automated method is evaluated in the context of online learning communities. The results suggest that the proposed ‘name network’ method for collecting social network data is a viable alternative to costly and time-consuming collection of users’ data using surveys. The study also demonstrates how social networks produced by the ‘name network’ method can be used to study online classes and to look for evidence of collaborative learning in online learning communities. For example, educators can use name networks as a real time diagnostic tool to identify students who might need additional help or students who may provide such help to others. Future research will evaluate the usefulness of the ‘name network’ method in other types of online communities.

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Background: This paper is a commentary to a debate article entitled: "Are we overpathologizing everyday life? A tenable blueprint for behavioral addiction research", by Billieux et al. (2015). Methods and aim: This brief response focused on the necessity to better characterize psychological and related neurocognitive determinants of persistent deleterious actions associated or not with substance utilization. Results: A majority of addicted people could be driven by psychological functional reasons to keep using drugs, gambling or buying despite the growing number of related negative consequences. In addition, a non-negligible proportion of them would need assistance to restore profound disturbances in basic learning processes involved in compulsive actions. Conclusions: The distinction between psychological functionality and compulsive aspects of addictive behaviors should represent a big step towards more efficient treatments.

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Professional coaching is a rapidly expanding field with interdisciplinary roots and broad application. However, despite abundant prescriptive literature, research into the process of coaching is minimal. Similarly, although learning is inherently recognised in the process of coaching, the process of learning in coaching is little understood and learning theory makes up only a small part of the evidence-based coaching literature. In this grounded theory study of coaches and their clients, the process of learning in coaching across a range of coaching models is examined and discussed. The findings demonstrate how learning in coaching emerged as a process of discovering, applying and integrating new knowledge, which culminated in a process of developing. This process occurred through eight key coaching processes shared between coaches and clients and combined a multitude of learning theories.

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Tertiary education is increasingly a contested space where advances in Information Communications Technologies and their application to technology-mediated e-learning environments have forced university administrators and educators to dislocate themselves from traditional correspondence modes of student engagement. Compounding this paradigmatic shift within the traditional sphere of distance education pedagogy are multiple and conflicting pressures on academics to develop flexible, engaging, cost-effective and sustainable interactive learning resources that incorporate both multimedia and hypermedia. This chapter reports on a study that examined factors that influence educators’ decision to adopt and integrate educational technology and convert traditional print-based distance education materials into interactive multimodal e-learning formats. Although the broader study was conducted in a single Australian university and investigated pedagogical, institutional and individual factors, this chapter restricts its focus to solely the pedagogical motivations and concerns of educators. It is argued that findings from the study have significance at the institutional level, particularly in terms of developing an underlying pedagogical rationale that can permeate the e-learning culture throughout the university, while at the same time, providing a roadmap for educators who are yet to fully engage with the e-learning format.

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This paper discusses about effectiveness of blogs for reflective learning in design education. Students in two animation units were asked to complete their online journal via blog in terms of reflective learning. Students were encouraged to respond their weekly outcomes and project development process to their blog and share it with other students. A survey was undertaken to evaluate their learning experience and one of the key outcomes indicates that interaction design for social network is significantly important to blog based learning design.