124,382 research outputs found

    Towards improving web service repositories through semantic web techniques

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    The success of the Web services technology has brought topicsas software reuse and discovery once again on the agenda of software engineers. While there are several efforts towards automating Web service discovery and composition, many developers still search for services via online Web service repositories and then combine them manually. However, from our analysis of these repositories, it yields that, unlike traditional software libraries, they rely on little metadata to support service discovery. We believe that the major cause is the difficulty of automatically deriving metadata that would describe rapidly changing Web service collections. In this paper, we discuss the major shortcomings of state of the art Web service repositories and, as a solution, we report on ongoing work and ideas on how to use techniques developed in the context of the Semantic Web (ontology learning, mapping, metadata based presentation) to improve the current situation

    Dirichlet belief networks for topic structure learning

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    Recently, considerable research effort has been devoted to developing deep architectures for topic models to learn topic structures. Although several deep models have been proposed to learn better topic proportions of documents, how to leverage the benefits of deep structures for learning word distributions of topics has not yet been rigorously studied. Here we propose a new multi-layer generative process on word distributions of topics, where each layer consists of a set of topics and each topic is drawn from a mixture of the topics of the layer above. As the topics in all layers can be directly interpreted by words, the proposed model is able to discover interpretable topic hierarchies. As a self-contained module, our model can be flexibly adapted to different kinds of topic models to improve their modelling accuracy and interpretability. Extensive experiments on text corpora demonstrate the advantages of the proposed model.Comment: accepted in NIPS 201

    Social capital theory: a cross-cutting analytic for teacher/therapist work in integrating children's services?

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    Reviewing relevant policy, this article argues that the current 'integration interlude' is concerned with reformation of work relations to create new forms of 'social capital'. The conceptual framework of social capital has been used by government policy-makers and academic researchers to examine different types, configurations and qualities of relationships, including professional relations, and how these may function as resources. Focusing on the co-work of teachers and speech and language therapists, this analysis introduces social capital as a means of understanding the impact of integrating children's services on professional practitioner groups and across agencies. Social capital theory is compared to alternative theoretical perspectives such as systems and discourse theories and explored as an analytic offering a multi-level typology and conceptual framework for understanding the effects of policy and governance on interprofessional working and relationships. A previous application of social capital theory in a literature review is introduced and analysed, and instances of the additionality provided by a social capital analysis is offered. The article concludes that amongst the effects of current policy to re-design children's services are the reconstruction of professionals' knowledge/s and practices, so it is essential that such policy processes that have complex and far-reaching effects are transparent and coherent. It is also important that new social capital relations in children's services are produced by groups representative of all involved, importantly including those practitioner groups charged in policy to work differently together in future integrated services

    Reclaiming Public Education: Common Sense Approaches

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    Bob Cornett, a former state budget director for Kentucky, describes himself as a "retired bureaucrat." But as a parent, grandparent, and a person who has been involved in education reform for more than 20 years, he's come to understand that, if public education policies are to be corrected, the impetus has to come from the citizenry.In this report, Cornett describes his journey to this realization, formed in part by observing how the small communities in Eastern Kentucky learn and educate. In Linefork, Kentucky, for example, an intergenerational community project aims to restore the American chestnut tree to the surrounding forests and has allowed the older community members to share their cultural legacy with the young people growing up there.Bob and his family have put on the Festival of the Blue­grass in Lexington, Kentucky, for more than 40 years, and he writes of the opportunities such festivals can provide by making use of traditional music in the education of young people. The Wise Village Pickers, from Stanton, Kentucky, is a bluegrass group made up of school children, from kindergarten to fifth grade. Every year, the group performs at the festival. Cornett writes, "Our rural musical legacy can be a powerful tool for strengthening communities. . . . young people learn much better when they are active participants in things that matter in their communities."Seeing the failure of top-down approaches to education reform, Cornett advises, "We citizens need to do everything we can at the community level to encourage and support professional educators who are committed to making students active partners in learning. . . . with our support, those educators will be better able to resist the pressures from the top-down hierar­chies. But there is another reason for citizens to work hard to connect with educators. The field of education, at its best, has much to offer to the learning that communities need to do. The Linefork community, to use my favorite example once again, is being educated. It is learning about itself. The best of our nation's educators have know-how that can contribute to a community's learning about itself.

    Designing Service-Learning to Enhance Social Justice Commitments: A Critical Reflection Tool

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    The COVID-19 pandemic—coupled with ongoing prominent injustice related to race, poverty, healthcare, and education—has highlighted the interlocking and reinforcing nature of systemic oppression. Now more than ever, facilitators of experiential learning are galvanized to explore and deepen their understanding of systemic change and to enhance their teaching of justice concepts, perspectives, and skills. Advancing social justice was a part of the original vision for service-learning (Stanton et al., 1999). However, scholars have long identified the ways in which service-learning can perpetuate inequitable social hierarchies, be miseducative in teaching simplistic understandings of solutions to social problems, and not equip students to participate in social movements for justice (Eby, 1998; Mitchell and Latta, 2020). By incorporating critical pedagogy, action, and reflection in and beyond the classroom, “critical service-learning” seeks to increase understanding of oppression, redistribute power, and find solutions to social issues through community-campus partnerships (Mitchell, 2008; Santiago-Ortiz, 2019). However, many service-learning practitioners report uncertainty about how to take concrete steps to align their courses with justice orientated techniques and pedagogy. In order to address this need, students, staff, and faculty in Duke Service-Learning began creating a tool to support the implementation of critical pedagogy and justice in service-learning courses in 2016 (Stith et al., 2018). For the past 8 months an expanded group has worked to update that original tool. The resulting tool organizes course design choices into five themes: reckoning with systems, authentic relationships, redistribution of power, equitable classrooms & cognitive justice, and social change skills. The resulting tool generates concrete, actionable questions for service-learning and experiential learning to interrogate how their pedagogy and practices incorporate social, economic, environmental, and racial justice. Our article summarizes the advances in our understanding and of the literature on implementing justice aligned experiential education and links to the current version of our tool. Further, our article will summarize lessons learned from conversations with practitioners who use and reflect on the implications of the tool for their own pedagogy. We will also reflect on holding the tensions in balancing the various aspects of course designs and our commitments to anti-oppressive practices. Finally, we will reflect on further implications for service-learning and experiential education that the process of creating this tool has surfaced

    Learning Task Priorities from Demonstrations

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    Bimanual operations in humanoids offer the possibility to carry out more than one manipulation task at the same time, which in turn introduces the problem of task prioritization. We address this problem from a learning from demonstration perspective, by extending the Task-Parameterized Gaussian Mixture Model (TP-GMM) to Jacobian and null space structures. The proposed approach is tested on bimanual skills but can be applied in any scenario where the prioritization between potentially conflicting tasks needs to be learned. We evaluate the proposed framework in: two different tasks with humanoids requiring the learning of priorities and a loco-manipulation scenario, showing that the approach can be exploited to learn the prioritization of multiple tasks in parallel.Comment: Accepted for publication at the IEEE Transactions on Robotic

    Analysis and evaluation of uncertainty for conducted and radiated emissions tests

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    Whenever an EMC measurement is made, there are numerous uncertainties in different parts of the measurement system and even in the EMC performance of the equipment under test (EUT) which is being measured. It is important to be able to estimate the overall uncertainty, in particular, the test setup and measurement equipment uncertainty. However, making repetitive measurements can reduce the measurement uncertainty, but often economics of time do not permit that. Therefore, a practical process, which is used to evaluate uncertainty in EMC measurement a, according to the principle of uncertainty and conditions in EMC measurement is presented. In this study, an efficient analysis of uncertainty for both radiated and conducted emissions tests is performed. The uncertainty of each contributor had been calculated and evaluating the reported expanded uncertainty of measurement is stated as the standard uncertainty of measurement. This standard uncertainty is multiplied by the coverage factor k=2, which for a normal distribution corresponds to a coverage probability of approximately 95%. The result of calculating the uncertainty for both conducted and radiated emission tests showed that the overall uncertainty of the system is high and it must be lowered by reducing the expanded uncertainty for the dominant contributors for both tests. In addition, the result of applying the concept of CISPR uncertainty for both conducted and radiated emission tests showed that non-compliance is deemed to occur for both EUT of both tests. This is due to the result that the measured disturbances increased by ( ), above the disturbance limit

    Using non-speech sounds to provide navigation cues

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    This article describes 3 experiments that investigate the possibiity of using structured nonspeech audio messages called earcons to provide navigational cues in a menu hierarchy. A hierarchy of 27 nodes and 4 levels was created with an earcon for each node. Rules were defined for the creation of hierarchical earcons at each node. Participants had to identify their location in the hierarchy by listening to an earcon. Results of the first experiment showed that participants could identify their location with 81.5% accuracy, indicating that earcons were a powerful method of communicating hierarchy information. One proposed use for such navigation cues is in telephone-based interfaces (TBIs) where navigation is a problem. The first experiment did not address the particular problems of earcons in TBIs such as “does the lower quality of sound over the telephone lower recall rates,” “can users remember earcons over a period of time.” and “what effect does training type have on recall?” An experiment was conducted and results showed that sound quality did lower the recall of earcons. However; redesign of the earcons overcame this problem with 73% recalled correctly. Participants could still recall earcons at this level after a week had passed. Training type also affected recall. With personal training participants recalled 73% of the earcons, but with purely textual training results were significantly lower. These results show that earcons can provide good navigation cues for TBIs. The final experiment used compound, rather than hierarchical earcons to represent the hierarchy from the first experiment. Results showed that with sounds constructed in this way participants could recall 97% of the earcons. These experiments have developed our general understanding of earcons. A hierarchy three times larger than any previously created was tested, and this was also the first test of the recall of earcons over time

    Game Theoretic Approaches to Massive Data Processing in Wireless Networks

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    Wireless communication networks are becoming highly virtualized with two-layer hierarchies, in which controllers at the upper layer with tasks to achieve can ask a large number of agents at the lower layer to help realize computation, storage, and transmission functions. Through offloading data processing to the agents, the controllers can accomplish otherwise prohibitive big data processing. Incentive mechanisms are needed for the agents to perform the controllers' tasks in order to satisfy the corresponding objectives of controllers and agents. In this article, a hierarchical game framework with fast convergence and scalability is proposed to meet the demand for real-time processing for such situations. Possible future research directions in this emerging area are also discussed
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