Improvement of a dynamic accumulator at ICICS 07 and its application in multi-user keyword-based retrieval on encrypted data

A dynamic accumulator is an algorithm, which merges a large set of elements into a constant-size value such that for an element accumulated, there is a witness confirming that the element was included into the value, with a property that accumulated elements can be dynamically added and deleted into/from the original set. Recently Wang et al. presented a dynamic accumulator for batch updates at ICICS 2007. However, their construction suffers from two serious problems. We analyze them and propose a way to repair their scheme. We use the accumulator to construct a new scheme for common secure indices with conjunctive keyword-based retrieval.

Semantic context and visual feature effects in object naming : an fMRI study using arterial spin labeling

Previous behavioral studies reported a robust effect of increased naming latencies when objects to be named were blocked within semantic category, compared to items blocked between category. This semantic context effect has been attributed to various mechanisms including inhibition or excitation of lexico-semantic representations and incremental learning of associations between semantic features and names, and is hypothesized to increase demands on verbal self-monitoring during speech production. Objects within categories also share many visual structural features, introducing a potential confound when interpreting the level at which the context effect might occur. Consistent with previous findings, we report a significant increase in response latencies when naming categorically related objects within blocks, an effect associated with increased perfusion fMRI signal bilaterally in the hippocampus and in the left middle to posterior superior temporal cortex. No perfusion changes were observed in the middle section of the left middle temporal cortex, a region associated with retrieval of lexical-semantic information in previous object naming studies. Although a manipulation of visual feature similarity did not influence naming latencies, we observed perfusion increases in the perirhinal cortex for naming objects with similar visual features that interacted with the semantic context in which objects were named. These results provide support for the view that the semantic context effect in object naming occurs due to an incremental learning mechanism, and involves increased demands on verbal self-monitoring.

Optimizing I/O cost and managing memory for composition vector method based on correlation matrix calculation in bioinformatics

The generation of a correlation matrix for set of genomic sequences is a common requirement in many bioinformatics problems such as phylogenetic analysis. Each sequence may be millions of bases long and there may be thousands of such sequences which we wish to compare, so not all sequences may fit into main memory at the same time. Each sequence needs to be compared with every other sequence, so we will generally need to page some sequences in and out more than once. In order to minimize execution time we need to minimize this I/O. This paper develops an approach for faster and scalable computing of large-size correlation matrices through the maximal exploitation of available memory and reducing the 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 bioinformatics problems with different correlation matrix sizes. The significant performance improvement of the approach over previous work is demonstrated through benchmark examples.

Paradoxical enhancement of fear extinction memory and synaptic plasticity by inhibition of the histone acetyltransferase p300

It is well established that the coordinated regulation of activity-dependent gene expression by the histone acetyltransferase (HAT) family of transcriptional coactivators is crucial for the formation of contextual fear and spatial memory, and for hippocampal synaptic plasticity. However, no studies have examined the role of this epigenetic mechanism within the infralimbic prefrontal cortex (ILPFC), an area of the brain that is essential for the formation and consolidation of fear extinction memory. Here we report that a postextinction training infusion of a combined p300/CBP inhibitor (Lys-CoA-Tat), directly into the ILPFC, enhances fear extinction memory in mice. Our results also demonstrate that the HAT p300 is highly expressed within pyramidal neurons of the ILPFC and that the small-molecule p300-specific inhibitor (C646) infused into the ILPFC immediately after weak extinction training enhances the consolidation of fear extinction memory. C646 infused 6 h after extinction had no effect on fear extinction memory, nor did an immediate postextinction training infusion into the prelimbic prefrontal cortex. Consistent with the behavioral findings, inhibition of p300 activity within the ILPFC facilitated long-term potentiation (LTP) under stimulation conditions that do not evoke long-lasting LTP. These data suggest that one function of p300 activity within the ILPFC is to constrain synaptic plasticity, and that a reduction in the function of this HAT is required for the formation of fear extinction memory.

Toward an object-based semantic memory for long-term operation of mobile service robots

Throughout a lifetime of operation, a mobile service robot needs to acquire, store and update its knowledge of a working environment. This includes the ability to identify and track objects in different places, as well as using this information for interaction with humans. This paper introduces a long-term updating mechanism, inspired by the modal model of human memory, to enable a mobile robot to maintain its knowledge of a changing environment. The memory model is integrated with a hybrid map that represents the global topology and local geometry of the environment, as well as the respective 3D location of objects. We aim to enable the robot to use this knowledge to help humans by suggesting the most likely locations of specific objects in its map. An experiment using omni-directional vision demonstrates the ability to track the movements of several objects in a dynamic environment over an extended period of time.

Document clustering algorithms, representations and evaluation for information retrieval

This thesis presents new methods for classification and thematic grouping of billions of web pages, at scales previously not achievable. This process is also known as document clustering, where similar documents are automatically associated with clusters that represent various distinct topic. These automatically discovered topics are in turn used to improve search engine performance by only searching the topics that are deemed relevant to particular user queries.

Predicting transactive memory systems in multidisciplinary teams : The interplay between team and professional identities

In explaining how communication quality predicts TMS in multidisciplinary teams, we drew on the social identity approach to investigate the mediating role of team identification and the moderating role of professional identification. Recognizing that professional identification could trigger intergroup biases among professional subgroups, or alternatively, could bring resources to the team, we explored the potential moderating role of professional identification in the relationship between team identification and TMS. Using data collected from 882 healthcare personnel working in 126 multidisciplinary hospital teams, results supported our hypothesis that perceived communication quality predicted TMS through team identification. Furthermore, findings provided support for a resource view of professional subgroup identities with results indicating that high levels of professional identification compensated for low levels of team identification in predicting TMS. We provide recommendations on how social identities may be used to promote TMS in multidisciplinary teams.

Writing embodied practice from the inside : outside the exegesis

The textual turn is a good friend of expert spectating, where it assumes the role of writing-productive apparatus, but no friend at all of expert practices or practitioners (Melrose, 2003). Introduction The challenge of time-based embodied performance when the artefact is unstable As a former full-time professional practitioner with an embodied dance practice as performer, choreographer and artistic director for three decades, I somewhat unexpectedly entered the world of academia in 2000 after completing a practice-based PhD, which was described by its examiners as ‘pioneering’. Like many artists my intention was to deepen and extend my practice through formal research into my work and its context (which was intercultural) and to privilege the artist’s voice in a research world where it was too often silent. Practice as research, practice-based research, and practice-led research were not yet fully named. It was in its infancy and my biggest challenge was to find a serviceable methodology which did not betray my intentions to keep practice at the centre of the research. Over the last 15 years, practice led doctoral research, where examinable creative work is placed alongside an accompanying (exegetical) written component, has come a long way. It has been extensively debated with a range of theories and models proposed (Barrett & Bolt, 2007, Pakes, 2003 & 2004, Piccini, 2005, Philips, Stock & Vincs 2009, Stock, 2009 & 2010, Riley & Hunter 2009, Haseman, 2006, Hecq, 2012). Much of this writing is based around epistemological concerns where the research methodologies proposed normally incorporate a contextualisation of the creative work in its field of practice, and more importantly validation and interrogation of the processes of the practice as the central ‘data gathering’ method. It is now widely accepted, at least in the Australian creative arts context, that knowledge claims in creative practice research arise from the material activities of the practice itself (Carter, 2004). The creative work explicated as the tangible outcome of that practice is sometimes referred to as the ‘artefact’. Although the making of the artefact, according to Colbert (2009, p. 7) is influenced by “personal, experiential and iterative processes”, mapping them through a research pathway is “difficult to predict [for] “the adjustments made to the artefact in the light of emerging knowledge and insights cannot be foreshadowed”. Linking the process and the practice outcome most often occurs through the textual intervention of an exegesis which builds, and/or builds on, theoretical concerns arising in and from the work. This linking produces what Barrett (2007) refers to as “situated knowledge… that operates in relation to established knowledge” (p. 145). But what if those material forms or ‘artefacts’ are not objects or code or digitised forms, but live within the bodies of artist/researchers where the nature of the practice itself is live, ephemeral and constantly transforming, as in dance and physical performance? Even more unsettling is when the ‘artefact’ is literally embedded and embodied in the work and in the maker/researcher; when subject and object are merged. To complicate matters, the performing arts are necessarily collaborative, relying not only on technical mastery and creative/interpretive processes, but on social and artistic relationships which collectively make up the ‘artefact’. This chapter explores issues surrounding live dance and physical performance when placed in a research setting, specifically the complexities of being required to translate embodied dance findings into textual form. Exploring how embodied knowledge can be shared in a research context for those with no experiential knowledge of communicating through and in dance, I draw on theories of “dance enaction” (Warburton, 2011) together with notions of “affective intensities” and “performance mastery” (Melrose, 2003), “intentional activity” (Pakes, 2004) and the place of memory. In seeking ways to capture in another form the knowledge residing in live dance practice, thus making implicit knowledge explicit, I further propose there is a process of triple translation as the performance (the living ‘artefact’) is documented in multi-facetted ways to produce something durable which can be re-visited. This translation becomes more complex if the embodied knowledge resides in culturally specific practices, formed by world views and processes quite different from accepted norms and conventions (even radical ones) of international doctoral research inquiry. But whatever the combination of cultural, virtual and genre-related dance practices being researched, embodiment is central to the process, outcome and findings, and the question remains of how we will use text and what forms that text might take.

A tag-based personalized item recommendation system using tensor modeling and topic model approaches

This research falls in the area of enhancing the quality of tag-based item recommendation systems. It aims to achieve this by employing a multi-dimensional user profile approach and by analyzing the semantic aspects of tags. Tag-based recommender systems have two characteristics that need to be carefully studied in order to build a reliable system. Firstly, the multi-dimensional correlation, called as tag assignment , should be appropriately modelled in order to create the user profiles [1]. Secondly, the semantics behind the tags should be considered properly as the flexibility with their design can cause semantic problems such as synonymy and polysemy [2]. This research proposes to address these two challenges for building a tag-based item recommendation system by employing tensor modeling as the multi-dimensional user profile approach, and the topic model as the semantic analysis approach. The first objective is to optimize the tensor model reconstruction and to improve the model performance in generating quality rec-ommendation. A novel Tensor-based Recommendation using Probabilistic Ranking (TRPR) method [3] has been developed. Results show this method to be scalable for large datasets and outperforming the benchmarking methods in terms of accuracy. The memory efficient loop implements the n-mode block-striped (matrix) product for tensor reconstruction as an approximation of the initial tensor. The probabilistic ranking calculates the probabil-ity of users to select candidate items using their tag preference list based on the entries generated from the reconstructed tensor. The second objective is to analyse the tag semantics and utilize the outcome in building the tensor model. This research proposes to investigate the problem using topic model approach to keep the tags nature as the “social vocabulary” [4]. For the tag assignment data, topics can be generated from the occurrences of tags given for an item. However there is only limited amount of tags availa-ble to represent items as collection of topics, since an item might have only been tagged by using several tags. Consequently, the generated topics might not able to represent the items appropriately. Furthermore, given that each tag can belong to any topics with various probability scores, the occurrence of tags cannot simply be mapped by the topics to build the tensor model. A standard weighting technique will not appropriately calculate the value of tagging activity since it will define the context of an item using a tag instead of a topic.

The monadic environment : evoking emotion and memory in participatory performance

This practice-led research project examined the audience experience of immersive environments in participatory performance. Drawing upon the work of artist Ilya Kabakov, Gaston Bachelard's Poetics of Space (1964) and Leibniz's theory of the monad, the study investigated how an immersive space can be constructed to evoke emotion and memory recall in participants. The research consisted of two cycles of creative experimentation resulting in the presentation of a final piece entitled Dulcet. The research contributes new terminology to the discourse surrounding the participant experience in immersive environments, specifically space-as-memory, the role of ambiguity in spatial design and the construct of the monadic environment.

Double-strand breaks and the concept of short- and long-term epigenetic memory

Double-strand breaks represent an extremely cytolethal form of DNA damage and thus pose a serious threat to the preservation of genetic and epigenetic information. Though it is well-known that double-strand breaks such as those generated by ionising radiation are among the principal causative factors behind mutations, chromosomal aberrations, genetic instability and carcino-genesis, significantly less is known about the epigenetic consequences of double-strand break formation and repair for carcinogenesis. Double-strand break repair is a highly coordinated process that requires the unravelling of the compacted chromatin structure to facilitate repair machinery access and then restoration of the original undamaged chromatin state. Recent experimental findings have pointed to a potential mechanism for double-strand break-induced epigenetic silencing. This review will discuss some of the key epigenetic regulatory processes involved in double-strand break (DSB) repair and how incomplete or incorrect restoration of chromatin structure can leave a DSB-induced epigenetic memory of damage with potentially pathological repercussions

Memory management and parallelization of data intensive all-to-all comparison in shared-memory systems

This thesis presents a novel program parallelization technique incorporating with dynamic and static scheduling. It utilizes a problem specific pattern developed from the prior knowledge of the targeted problem abstraction. Suitable for solving complex parallelization problems such as data intensive all-to-all comparison constrained by memory, the technique delivers more robust and faster task scheduling compared to the state-of-the art techniques. Good performance is achieved from the technique in data intensive bioinformatics applications.

Text mining with semantic annotation : using enriched text representation for entity-oriented retrieval, semantic relation identification and text clustering

This project is a step forward in the study of text mining where enhanced text representation with semantic information plays a significant role. It develops effective methods of entity-oriented retrieval, semantic relation identification and text clustering utilizing semantically annotated data. These methods are based on enriched text representation generated by introducing semantic information extracted from Wikipedia into the input text data. The proposed methods are evaluated against several start-of-art benchmarking methods on real-life data-sets. In particular, this thesis improves the performance of entity-oriented retrieval, identifies different lexical forms for an entity relation and handles clustering documents with multiple feature spaces.

In-memory business process management

In-memory databases have become a mainstay of enterprise computing offering significant performance and scalability boosts for online analytical and (to a lesser extent) transactional processing as well as improved prospects for integration across different applications through an efficient shared database layer. Significant research and development has been undertaken over several years concerning data management considerations of in-memory databases. However, limited insights are available on the impacts of applications and their supportive middleware platforms and how they need to evolve to fully function through, and leverage, in-memory database capabilities. This paper provides a first, comprehensive exposition into how in-memory databases impact Business Pro- cess Management, as a mission-critical and exemplary model-driven integration and orchestration middleware. Through it, we argue that in-memory databases will render some prevalent uses of legacy BPM middleware obsolete, but also open up exciting possibilities for tighter application integration, better process automation performance and some entirely new BPM capabilities such as process-based application customization. To validate the feasibility of an in-memory BPM, we develop a surprisingly simple BPM runtime embedded into SAP HANA and providing for BPMN-based process automation capabilities.