902 resultados para Digital Library Collection Development Policy
Resumo:
This article describes how - in the processes of responding to participatory storytelling practices - community, public service, and to a lesser extent, commercial media institutions are themselves negotiated and changed. Although there are significant variations in the conditions, durability, extent, motivations and quality of these developments and their impacts, they nonetheless increase the possibilities and pathways of participatory media culture. This description first frames digital storytelling as a ‘co-creative’ media practice. It then discusses the role of community arts and cultural development (CACD) practitioners and networks as co-creative media intermediaries, and then considers their influence in Australian broadcast and Internet media. It looks at how participatory storytelling methods are evolving in the Australian context and explores some of the implications for cultural inclusion arising from a shared interest in ‘co-creative’ media methods and approaches.
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EVE Online, released in 2003 by CCP Games, is a space-themed Massively Multiplayer Online Game (MMOG). This sandbox style MMOG has a reputation for being a difficult game with a punishing learning curve that is fairly impenetrable to new players. This has led to the widely held belief among the larger MMOG community that “EVE players are different”, as only a very particular type of player would be dedicated to learning how to play a game this challenging. Taking a critical approach to the claim that “EVE players are different”, this paper complicates the idea that only a certain type of player capable of playing the most hardcore of games will be attracted to this particular MMOG. Instead, we argue that EVE’s “exceptionalism” is actually the result of conscious design decisions on the part of CCP games, which in turn compel particular behaviours that are continually reinforced as the norm by the game’s relatively homogenous player community.
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An accumulator based on bilinear pairings was proposed at CT-RSA'05. Here, it is first demonstrated that the security model proposed by Lan Nguyen does lead to a cryptographic accumulator that is not collision resistant. Secondly, it is shown that collision-resistance can be provided by updating the adversary model appropriately. Finally, an improvement on Nguyen's identity escrow scheme, with membership revocation based on the accumulator, by removing the trusted third party is proposed.
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A growing number of online journals and academic platforms are adopting light peer review or 'publish then filter' models of scholarly communication. These approaches have the advantage of enabling instant exchanges of knowledge between academics and are part of a wider search for alternatives to traditional peer review and certification processes in scholarly publishing. However, establishing credibility and identifying the correct balance between communication and scholarly rigour remains an important challenge for digital communication platforms targeting academic communities. This paper looks at a highly influential, government-backed, open publishing platform in China: Science Paper Online, which is using transparent post-publication peer-review processes to encourage innovation and address systemic problems in China's traditional academic publishing system. There can be little doubt that the Chinese academic publishing landscape differs in important ways from counterparts in the United States and Western Europe. However, this article suggests that developments in China also provide important lessons about the potential of digital technology and government policy to facilitate a large-scale shift towards more open and networked models of scholarly communication.
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This chapter presents a novel control strategy for trajectory tracking of underwater marine vehicles that are designed using port-Hamiltonian theory. A model for neutrally buoyant underwater vehicles is formulated as a PHS, and then the tracking controller is designed for the horizontal plane-surge, sway and yaw. The control design is done by formulating the error dynamics as a set-point regulation port-Hamiltonian control problem. The control design is formulated in two steps. In the first step, a static-feedback tracking controller is designed, and the second step integral action is added. The global asymptotic stability of the closed loop system is proved and the performance of the controller is illustrated using a model of an open-frame offshore underwater vehicle.
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A comparison of relay power minimisation subject to received signal-to-noise ratio (SNR) at the receiver and SNR maximisation subject to the total transmitted power of relays for a typical wireless network with distributed beamforming is presented. It is desirable to maximise receiver quality-of-service (QoS) and also to minimise the cost of transmission in terms of power. Hence, these two optimisation problems are very common and have been addressed separately in the literature. It is shown that SNR maximisation subject to power constraint and power minimisation subject to SNR constraint yield the same results for a typical wireless network. It proves that either one of the optimisation approaches is sufficient.
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This paper aims to develop a comprehensive approach to innovate urban policymaking and planning to successfully deliver the knowledge-based agenda. The paper, first, examines the concept of knowledge-based urban development, which has become a popular urban development policy and strategy in recent years, through a comprehensive review of the literature. It, then, introduces and discusses a novel methodological approach for effective policymaking and planning mechanism to deliver the knowledge-based agenda of cities. The paper, with the proposed methodology, brings together urban policymaking and planning approaches, and introduces a novel way to assess knowledge-based urban development achievements and potentials of emerging and prosperous knowledge cities. The paper, thus, provides an invaluable instrument to inform local and regional decision and plan making mechanisms to deliver their knowledge-based agendas and help them in moving towards building their sustainable knowledge cities.
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In the TREC Web Diversity track, novelty-biased cumulative gain (α-NDCG) is one of the official measures to assess retrieval performance of IR systems. The measure is characterised by a parameter, α, the effect of which has not been thoroughly investigated. We find that common settings of α, i.e. α=0.5, may prevent the measure from behaving as desired when evaluating result diversification. This is because it excessively penalises systems that cover many intents while it rewards those that redundantly cover only few intents. This issue is crucial since it highly influences systems at top ranks. We revisit our previously proposed threshold, suggesting α be set on a query-basis. The intuitiveness of the measure is then studied by examining actual rankings from TREC 09-10 Web track submissions. By varying α according to our query-based threshold, the discriminative power of α-NDCG is not harmed and in fact, our approach improves α-NDCG's robustness. Experimental results show that the threshold for α can turn the measure to be more intuitive than using its common settings.
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To provide card holder authentication while they are conducting an electronic transaction using mobile devices, VISA and MasterCard independently proposed two electronic payment protocols: Visa 3D Secure and MasterCard Secure Code. The protocols use pre-registered passwords to provide card holder authentication and Secure Socket Layer/ Transport Layer Security (SSL/TLS) for data confidentiality over wired networks and Wireless Transport Layer Security (WTLS) between a wireless device and a Wireless Application Protocol (WAP) gateway. The paper presents our analysis of security properties in the proposed protocols using formal method tools: Casper and FDR2. We also highlight issues concerning payment security in the proposed protocols.
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Over the last two decades we have witnessed the global rise and spread of urban development policies aimed at stimulating the cultural economy. However, with the onset of the global financial crisis and recession, the cultural economy may experience a dramatic reorganization and even decline. Given the attention many cities place on the cultural sectors it is important to examine how they fare following this major economic event. To do so, this article examines the occupational distribution and geographic structure of the cultural economy in the 30 largest US metropolitan areas during recession and captures the changes that have occurred over the last decade. Based on this analysis, we identify a set of key trends, which highlight that while the boom period is generally characterized by widespread and, in some places, extreme growth in the cultural sectors, the recession is a period of selective growth and not a period of total decline. These findings have implications for determining the relevance of the arts and cultural sectors as targets of urban economic development policy in the post-recession era.
Resumo:
Analysing census and industry data at the metro and neighbourhood levels, this paper seeks to identify the location characteristics associated with artistic clusters and determine how these characteristics vary across different places. We find that the arts cannot be taken overall as an urban panacea, but rather that their impact is place-specific and policy ought to reflect these nuances. However, our work also finds that, paradoxically, the arts’ role in developing metro economies is as highly underestimated as it is overgeneralised. While arts clusters exhibit unique industry, scale and place-specific attributes, we also find evidence that they cluster in ‘innovation districts’, suggesting they can play a larger role in economic development. To this end, our results raise important questions and point toward new approaches for arts-based urban development policy that look beyond a focus on the arts as amenities to consider the localised dynamics between the arts and other industries.
Impact of child labor on academic performance : evidence from the program "Edúcame Primero Colombia"
Resumo:
In this study, the effects of different variables of child labor on academic performance are investigated. To this end, 3302 children participating in the child labor eradication program “Edúcame Primero Colombia” were interviewed. The interview format used for the children's enrollment into the program was a template from which socioeconomic conditions, academic performance, and child labor variables were evaluated. The academic performance factor was determined using the Analytic Hierarchy Process (AHP). The data were analyzed through a logistic regression model that took into account children who engaged in a type of labor (n = 921). The results showed that labor conditions, the number of weekly hours dedicated to work, and the presence of work scheduled in the morning negatively affected the academic performance of child laborers. These results show that the relationship between child labor and academic performance is based on the conflict between these two activities. These results do not indicate a linear and simple relationship associated with the recognition of the presence or absence of child labor. This study has implications for the formulation of policies, programs, and interventions for preventing, eradicating, and attenuating the negative effects of child labor on the social and educational development of children.
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Many websites offer the opportunity for customers to rate items and then use customers' ratings to generate items reputation, which can be used later by other users for decision making purposes. The aggregated value of the ratings per item represents the reputation of this item. The accuracy of the reputation scores is important as it is used to rank items. Most of the aggregation methods didn't consider the frequency of distinct ratings and they didn't test how accurate their reputation scores over different datasets with different sparsity. In this work we propose a new aggregation method which can be described as a weighted average, where weights are generated using the normal distribution. The evaluation result shows that the proposed method outperforms state-of-the-art methods over different sparsity datasets.
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Twitter is a very popular social network website that allows users to publish short posts called tweets. Users in Twitter can follow other users, called followees. A user can see the posts of his followees on his Twitter profile home page. An information overload problem arose, with the increase of the number of followees, related to the number of tweets available in the user page. Twitter, similar to other social network websites, attempts to elevate the tweets the user is expected to be interested in to increase overall user engagement. However, Twitter still uses the chronological order to rank the tweets. The tweets ranking problem was addressed in many current researches. A sub-problem of this problem is to rank the tweets for a single followee. In this paper we represent the tweets using several features and then we propose to use a weighted version of the famous voting system Borda-Count (BC) to combine several ranked lists into one. A gradient descent method and collaborative filtering method are employed to learn the optimal weights. We also employ the Baldwin voting system for blending features (or predictors). Finally we use the greedy feature selection algorithm to select the best combination of features to ensure the best results.
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Recommender systems provide personalized advice for customers online based on their own preferences, while reputation systems generate a community advice on the quality of items on the Web. Both systems use users’ ratings to generate their output. In this paper, we propose to combine reputation models with recommender systems to enhance the accuracy of recommendations. The main contributions include two methods for merging two ranked item lists which are generated based on recommendation scores and reputation scores, respectively, and a personalized reputation method to generate item reputations based on users’ interests. The proposed merging methods can be applicable to any recommendation methods and reputation methods, i.e., they are independent from generating recommendation scores and reputation scores. The experiments we conducted showed that the proposed methods could enhance the accuracy of existing recommender systems.