171 resultados para Collective Memory


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The symbolic and improvisational nature of Livecoding requires a shared networking framework to be flexible and extensible, while at the same time providing support for synchronisation, persistence and redundancy. Above all the framework should be robust and available across a range of platforms. This paper proposes tuple space as a suitable framework for network communication in ensemble livecoding contexts. The role of tuple space as a concurrency framework and the associated timing aspects of the tuple space model are explored through Spaces, an implementation of tuple space for the Impromptu environment.

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The paper presents a detailed analysis on the collective dynamics and delayed state feedback control of a three-dimensional delayed small-world network. The trivial equilibrium of the model is first investigated, showing that the uncontrolled model exhibits complicated unbounded behavior. Then three control strategies, namely a position feedback control, a velocity feedback control, and a hybrid control combined velocity with acceleration feedback, are then introduced to stabilize this unstable system. It is shown in these three control schemes that only the hybrid control can easily stabilize the 3-D network system. And with properly chosen delay and gain in the delayed feedback path, the hybrid controlled model may have stable equilibrium, or periodic solutions resulting from the Hopf bifurcation, or complex stranger attractor from the period-doubling bifurcation. Moreover, the direction of Hopf bifurcation and stability of the bifurcation periodic solutions are analyzed. The results are further extended to any "d" dimensional network. It shows that to stabilize a "d" dimensional delayed small-world network, at least a "d – 1" order completed differential feedback is needed. This work provides a constructive suggestion for the high dimensional delayed systems.

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A year ago, I became aware of the historical existence of the group CERFI— Le centre d’etudes, de recherches, et de formation institutionelles, or The Study Center for Institutional Research and Formation. CERFI emerged in 1967 under the hand of Lacanian psychiatrist and Trotskyite activist Félix Guattari, whose antonymous journal Recherches chronicled the group’s subversive experiences, experiments, and government-sponsored urban projects. It was a singularly bizarre meeting of the French bureaucracy with militant activist groups, the French intelligentsia, and architectural and planning practitioners at the close of the ‘60s. Nevertheless, CERFI’s analysis of the problems of society was undertaken precisely from the perspective of the state, and the Institute acknowledged a “deep complicity between the intellectual and statesman ... because the first critics of the State, are officials themselves!”1 CERFI developed out of FGERI (The Federation of Groups for Institutional Study and Research), started by Guattari two years earlier. While FGERI was created for the analysis of mental institutions stemming from Guattari’s work at La Borde, an experimental psychiatric clinic, CERFI marks the group’s shift toward urbanism—to the interrogation of the city itself. Not only a platform for radical debate on architecture and the city, CERFI was a direct agent in the development of urban planning schemata for new towns in France. 2 CERFI’s founding members were Guattari, the economist and urban theorist François Fourquet, feminist philosopher Liane Mozère, and urban planner and editor of Multitides Anne Querrien—Guattari’s close friend and collaborator. The architects Antoine Grumback, Alain Fabre, Macary, and Janine Joutel were also members, as well as urbanists Bruno Fortier, Rainier Hoddé, and Christian de Portzamparc. 3 CERFI was the quintessential social project of post-‘68 French urbanism. Located on the Far Left and openly opposed to the Communist Party, this Trotskyist cooperative was able to achieve what other institutions, according to Fourquet, with their “customary devices—the politburo, central committee, and the basic cells—had failed to do.”4 The decentralized institute recognized that any formal integration of the group was to “sign its own death warrant; so it embraced a skein of directors, entangled, forming knots, liquidating all at once, and spinning in an unknown direction, stopping short and returning back to another node.” Allergic to the very idea of “party,” CERFI was a creative project of free, hybrid-aesthetic blocs talking and acting together, whose goal was none other than the “transformation of the libidinal economy of the militant revolutionary.” The group believed that by recognizing and affirming a “group unconscious,” as well as their individual unconscious desires, they would be able to avoid the political stalemates and splinter groups of the traditional Left. CERFI thus situated itself “on the side of psychosis”—its confessed goal was to serve rather than repress the utter madness of the urban malaise, because it was only from this mad perspective on the ground that a properly social discourse on the city could be forged.

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This proposal combines ethnographic techniques and discourse studies to investigating a collective of people engaged with audiovisual productions who collaborate in Curta Favela’s workshops in Rio de Janeiro’s favelas. ‘Favela’ is often translated simply as ‘slum’ or ‘shantytown’, but these terms connote negative characteristics such as shortage, poverty, and deprivation referring to favelas which end up stigmatizing these low income suburbs. Curta Favela (Favela Shorts) is an independent project which all participants join to use photography and participatory audiovisual production as a tool for social change and raising consciousness. As cameras are not affordable for favelas dwellers, Curta Favela’s volunteers teach favela residents how they can use their mobile phones and compact cameras to take pictures and make movies, and afterwards, how they can edit the data using free editing video software programs and publish it on the Internet. To record audio, they use their mp3 or mobile phones. The main aim of this study is to shed light not only on how this project operates, but also to highlight how collective intelligence can be used as a way of fighting against the lack of basic resources.

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This proposal combines ethnographic techniques and discourse studies to investigate a collective of people engaged with audiovisual productions who collaborate in Curta Favela’s workshops in Rio de Janeiro’s favelas. ‘Favela’ is often translated simply as ‘slum’ or ‘shantytown’, but these terms connote negative characteristics such as shortage, poverty, and deprivation which end up stigmatizing these low income suburbs. Curta Favela (Favela Shorts) is an independent project in which all participants join to use photography and participatory audiovisual production as tools for social change and to raise consciousness. As cameras are not affordable for favela dwellers, Curta Favela’s volunteers teach favela residents how they can use their mobile phones and compact cameras to take pictures and make movies, and afterwards, how they can edit the data using free editing video software programs and publish it on the Internet. To record audio, they use their mp3 or mobile phones. The main aim of this study is to shed light not only on how this project operates, but also to highlight how collective intelligence can be used as a way of fighting against a lack of basic resources.

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This paper examines the practice of handover in a large metropolitan hospital. It shows that the handover is a significant site at which to examine how tensions and imperatives derived from the traditional institutional position and role of the nurse are played out in contradiction with emergent professionalism. It identifies handover dimensions and focuses discussion on how the collective narrative of the handover serves to construct patient identities as well as ensure solidarity and cohesion among nurses.

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A recent Australian literature digitisation project uncovered some surprising discoveries in the children’s books that it digitised. The Children’s Literature Digital Resources (CLDR) Project digitised children’s books that were first published between 1851 to 1945 and made them available online through AustLit: The Australian Literature Resource. The digitisation process also preserved, within the pages of those books, a range of bookplates, book labels, inscriptions, and loose ephemera. This material allows us to trace the provenance of some of the digitised works, some of which came from the personal libraries of now-famous authors, and others from less celebrated sources. These extra-textual traces can contribute to cultural memory of the past by providing evidence of how books were collected and exchanged, and what kinds of books were presented as prizes in schools and Sunday schools. They also provide insight into Australian literary and artistic networks, particularly of the first few decades of the 20th century. This article describes the kinds of material uncovered in the digitisation process and suggests that the material provides insights into literary and cultural histories that might otherwise be forgotten. It also argues that the indexing of this material is vital if it is not to be lost to future researchers.

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The process of researching children’s literature from the past is a growing challenge as resources age and are increasingly treated as rare items, stored away within libraries and other research centres. In Australia, researchers and librarians have collaborated with the bibliographic database AustLit: The Australian Literature Resource to produce the Australian Children’s Literature Digital Resources Project (CLDR). This Project aims to address the growing demand for online access to rare children’s literature resources, and demonstrates the research potential of early Australian children’s literature by supplementing the collection with relevant critical articles. The CLDR project is designed with a specific focus and provides access to full text Australian children’s literature from European settlement to 1945. The collection demonstrates a need and desire to preserve literature treasures to prevent losing such collections in a digital age. The collection covers many themes relevant to the conference including, trauma, survival, memory, survival, hauntings, and histories. The resource provides new and exciting ways with which to research children’s literature from the past and offers a fascinating repository to scholars and professionals of ranging disciplines who are in interested in Australian children’s literature.

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Free association norms indicate that words are organized into semantic/associative neighborhoods within a larger network of words and links that bind the net together. We present evidence indicating that memory for a recent word event can depend on implicitly and simultaneously activating related words in its neighborhood. Processing a word during encoding primes its network representation as a function of the density of the links in its neighborhood. Such priming increases recall and recognition and can have long lasting effects when the word is processed in working memory. Evidence for this phenomenon is reviewed in extralist cuing, primed free association, intralist cuing, and single-item recognition tasks. The findings also show that when a related word is presented to cue the recall of a studied word, the cue activates it in an array of related words that distract and reduce the probability of its selection. The activation of the semantic network produces priming benefits during encoding and search costs during retrieval. In extralist cuing recall is a negative function of cue-to-distracter strength and a positive function of neighborhood density, cue-to-target strength, and target-to cue strength. We show how four measures derived from the network can be combined and used to predict memory performance. These measures play different roles in different tasks indicating that the contribution of the semantic network varies with the context provided by the task. We evaluate spreading activation and quantum-like entanglement explanations for the priming effect produced by neighborhood density.

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This work investigates the accuracy and efficiency tradeoffs between centralized and collective (distributed) algorithms for (i) sampling, and (ii) n-way data analysis techniques in multidimensional stream data, such as Internet chatroom communications. Its contributions are threefold. First, we use the Kolmogorov-Smirnov goodness-of-fit test to show that statistical differences between real data obtained by collective sampling in time dimension from multiple servers and that of obtained from a single server are insignificant. Second, we show using the real data that collective data analysis of 3-way data arrays (users x keywords x time) known as high order tensors is more efficient than centralized algorithms with respect to both space and computational cost. Furthermore, we show that this gain is obtained without loss of accuracy. Third, we examine the sensitivity of collective constructions and analysis of high order data tensors to the choice of server selection and sampling window size. We construct 4-way tensors (users x keywords x time x servers) and analyze them to show the impact of server and window size selections on the results.

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Two experiments examine outcomes for sponsor and ambusher brands within sponsorship settings. It is demonstrated that although making consumers aware of the presence of ambusher brands can reduce subsequent event recall to competitor cues, recall to sponsor cues can also suffer. Attitudinal effects are also considered.

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The generation of a correlation matrix from a large set of long gene sequences is a common requirement in many bioinformatics problems such as phylogenetic analysis. The generation is not only computationally intensive but also requires significant memory resources as, typically, few gene sequences can be simultaneously stored in primary memory. The standard practice in such computation is to use frequent input/output (I/O) operations. Therefore, minimizing the number of these operations will yield much faster run-times. This paper develops an approach for the faster and scalable computing of large-size correlation matrices through the full use of available memory and a reduced number of I/O operations. The approach is scalable in the sense that the same algorithms can be executed on different computing platforms with different amounts of memory and can be applied to different problems with different correlation matrix sizes. The significant performance improvement of the approach over the existing approaches is demonstrated through benchmark examples.

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