Modular transactional memory

Software transactional memory has the potential to greatly simplify development of concurrent software, by supporting safe composition of concurrent shared-state abstractions. However, STM semantics are defined in terms of low-level reads and writes on individual memory locations, so implementations are unable to take advantage of the properties of user-defined abstractions. Consequently, the performance of transactions over some structures can be disappointing. ----- ----- We present Modular Transactional Memory, our framework which allows programmers to extend STM with concurrency control algorithms tailored to the data structures they use in concurrent programs. We describe our implementation in Concurrent Haskell, and two example structures: a finite map which allows concurrent transactions to operate on disjoint sets of keys, and a non-deterministic channel which supports concurrent sources and sinks. ----- ----- Our approach is based on previous work by others on boosted and open-nested transactions, with one significant development: transactions are given types which denote the concurrency control algorithms they employ. Typed transactions offer a higher level of assurance for programmers reusing transactional code, and allow more flexible abstract concurrency control.

Improving matching process in social network using implicit and explicit user information

Personalised social matching systems can be seen as recommender systems that recommend people to others in the social networks. However, with the rapid growth of users in social networks and the information that a social matching system requires about the users, recommender system techniques have become insufficiently adept at matching users in social networks. This paper presents a hybrid social matching system that takes advantage of both collaborative and content-based concepts of recommendation. The clustering technique is used to reduce the number of users that the matching system needs to consider and to overcome other problems from which social matching systems suffer, such as cold start problem due to the absence of implicit information about a new user. The proposed system has been evaluated on a dataset obtained from an online dating website. Empirical analysis shows that accuracy of the matching process is increased, using both user information (explicit data) and user behavior (implicit data).

Technology, memory and experience : virtual reality, motion capture and early modern theatre

This paper investigates virtual reality representations of performance in London’s late sixteenth-century Rose Theatre, a venue that, by means of current technology, can once again challenge perceptions of space, performance, and memory. The VR model of The Rose becomes a Camillo device in that it represents a virtual recreation of this venue in as much detail as possible and attempts to recover graphic demonstrations of the trace memories of the performance modes of the day. The VR model is based on accurate archeological and theatre historical records and is easy to navigate. The introduction of human figures onto The Rose’s stage via motion capture allows us to explore the relationships between space, actor and environment. The combination of venue and actors facilitates a new way of thinking about how the work of early modern playwrights can be stored and recalled. This virtual theatre is thus activated to intersect productively with contemporary studies in performance; as such, our paper provides a perspective on and embodiment of the relation between technology, memory and experience. It is, at its simplest, a useful archiving project for theatrical history, but it is directly relevant to contemporary performance practice as well. Further, it reflects upon how technology and ‘re-enactments’ of sorts mediate the way in which knowledge and experience are transferred, and even what may be considered ‘knowledge.’ Our work provides opportunities to begin addressing what such intermedial confrontations might produce for ‘remembering, experiencing, thinking and imagining.’ We contend that these confrontations will enhance live theatre performance rather than impeding or disrupting contemporary performance practice. This paper intersects with the CFP’s ‘Performing Memory’ and ‘Memory Lab’ themes. Our presentation (which includes a demonstration of the VR model and the motion capture it requires) takes the form of two closely linked papers that share a single abstract. The two papers will be given by two people, one of whom will be physically present in Utrecht, the other participating via Skype.

Implicit online learning

Online learning algorithms have recently risen to prominence due to their strong theoretical guarantees and an increasing number of practical applications for large-scale data analysis problems. In this paper, we analyze a class of online learning algorithms based on fixed potentials and nonlinearized losses, which yields algorithms with implicit update rules. We show how to efficiently compute these updates, and we prove regret bounds for the algorithms. We apply our formulation to several special cases where our approach has benefits over existing online learning methods. In particular, we provide improved algorithms and bounds for the online metric learning problem, and show improved robustness for online linear prediction problems. Results over a variety of data sets demonstrate the advantages of our framework.

Sponsorship-linked marketing: The role of articulation in memory

Corporate sponsorship of events contributes significantly to marketing aims, including brand awareness as measured by recall and recognition of sponsor‐event pairings. Unfortunately, resultant advantages accrue disproportionately to brands having a natural or congruent fit with the available sponsorship properties. In three cued‐recall experiments, the effect of articulation of sponsorship fit on memory for sponsor‐event pairings is examined. While congruent sponsors have a natural memory advantage, results demonstrate that memory improvements via articulation are possible for incongruent sponsor‐event pairings. These improvements are, however, affected by the presence of competitor brands and the way in which memory is accessed.

Time-dependent fractional advection–diffusion equations by an implicit MLS meshless method

Recently, many new applications in engineering and science are governed by a series of fractional partial differential equations (FPDEs). Unlike the normal partial differential equations (PDEs), the differential order in a FPDE is with a fractional order, which will lead to new challenges for numerical simulation, because most existing numerical simulation techniques are developed for the PDE with an integer differential order. The current dominant numerical method for FPDEs is Finite Difference Method (FDM), which is usually difficult to handle a complex problem domain, and also hard to use irregular nodal distribution. This paper aims to develop an implicit meshless approach based on the moving least squares (MLS) approximation for numerical simulation of fractional advection-diffusion equations (FADE), which is a typical FPDE. The discrete system of equations is obtained by using the MLS meshless shape functions and the meshless strong-forms. The stability and convergence related to the time discretization of this approach are then discussed and theoretically proven. Several numerical examples with different problem domains and different nodal distributions are used to validate and investigate accuracy and efficiency of the newly developed meshless formulation. It is concluded that the present meshless formulation is very effective for the modeling and simulation of the FADE.

An implicit RBF meshless approach for time fractional diffusion equations

This paper aims to develop an implicit meshless approach based on the radial basis function (RBF) for numerical simulation of time fractional diffusion equations. The meshless RBF interpolation is firstly briefed. The discrete equations for two-dimensional time fractional diffusion equation (FDE) are obtained by using the meshless RBF shape functions and the strong-forms of the time FDE. The stability and convergence of this meshless approach are discussed and theoretically proven. Numerical examples with different problem domains and different nodal distributions are studied to validate and investigate accuracy and efficiency of the newly developed meshless approach. It has proven that the present meshless formulation is very effective for modeling and simulation of fractional differential equations.

Modelling the activation of words in human memory : the spreading activation, spooky-activation-at-a-distance and the entanglement models compared

Modelling how a word is activated in human memory is an important requirement for determining the probability of recall of a word in an extra-list cueing experiment. The spreading activation, spooky-action-at-a-distance and entanglement models have all been used to model the activation of a word. Recently a hypothesis was put forward that the mean activation levels of the respective models are as follows: Spreading � Entanglment � Spooking-action-at-a-distance This article investigates this hypothesis by means of a substantial empirical analysis of each model using the University of South Florida word association, rhyme and word norms.

The use of semantic priming as a paradigm for the detection of faking on self-report psychological tests

It is recognised that individuals do not always respond honestly when completing psychological tests. One of the foremost issues for research in this area is the inability to detect individuals attempting to fake. While a number of strategies have been identified in faking, a commonality of these strategies is the latent role of long term memory. Seven studies were conducted in order to examine whether it is possible to detect the activation of faking related cognitions using a lexical decision task. Study 1 found that engagement with experiential processing styles predicted the ability to fake successfully, confirming the role of associative processing styles in faking. After identifying appropriate stimuli for the lexical decision task (Studies 2A and 2B), Studies 3 to 5 examined whether a cognitive state of faking could be primed and subsequently identified, using a lexical decision task. Throughout the course of these studies, the experimental methodology was increasingly refined in an attempt to successfully identify the relevant priming mechanisms. The results were consistent and robust throughout the three priming studies: faking good on a personality test primed positive faking related words in the lexical decision tasks. Faking bad, however, did not result in reliable priming of negative faking related cognitions. To more completely address potential issues with the stimuli and the possible role of affective priming, two additional studies were conducted. Studies 6A and 6B revealed that negative faking related words were more arousing than positive faking related words, and that positive faking related words were more abstract than negative faking related words and neutral words. Study 7 examined whether the priming effects evident in the lexical decision tasks occurred as a result of an unintentional mood induction while faking the psychological tests. Results were equivocal in this regard. This program of research aligned the fields of psychological assessment and cognition to inform the preliminary development and validation of a new tool to detect faking. Consequently, an implicit technique to identify attempts to fake good on a psychological test has been identified, using long established and robust cognitive theories in a novel and innovative way. This approach represents a new paradigm for the detection of individuals responding strategically to psychological testing. With continuing development and validation, this technique may have immense utility in the field of psychological assessment.

State convergence and the effectiveness of time-memory-data tradeoffs

Various time-memory tradeoffs attacks for stream ciphers have been proposed over the years. However, the claimed success of these attacks assumes the initialisation process of the stream cipher is one-to-one. Some stream cipher proposals do not have a one-to-one initialisation process. In this paper, we examine the impact of this on the success of time-memory-data tradeoff attacks. Under the circumstances, some attacks are more successful than previously claimed while others are less. The conditions for both cases are established.

Electro-cortical implicit race bias does not vary with participants' race or sex

Earlier research found evidence for electro-cortical race bias towards black target faces in white American participants irrespective of the task relevance of race. The present study investigated whether an implicit race bias generalizes across cultural contexts and racial in- and out-groups. An Australian sample of 56 Chinese and Caucasian males and females completed four oddball tasks that required sex judgements for pictures of male and female Chinese and Caucasian posers. The nature of the background (across task) and of the deviant stimuli (within task) was fully counterbalanced. Event-related potentials (ERPs) to deviant stimuli recorded from three midline sites were quantified in terms of mean amplitude for four components: N1, P2, N2 and a late positive complex (LPC; 350–700 ms). Deviants that differed from the backgrounds in sex or race elicited enhanced LPC activity. These differences were not modulated by participant race or sex. The current results replicate earlier reports of effects of poser race relative to background race on the LPC component of the ERP waveform. In addition, they indicate that an implicit race bias occurs regardless of participant's or poser's race and is not confined to a particular cultural context.

A quantum information retrieval approach to memory

As computers approach the physical limits of information storable in memory, new methods will be needed to further improve information storage and retrieval. We propose a quantum inspired vector based approach, which offers a contextually dependent mapping from the subsymbolic to the symbolic representations of information. If implemented computationally, this approach would provide exceptionally high density of information storage, without the traditionally required physical increase in storage capacity. The approach is inspired by the structure of human memory and incorporates elements of Gardenfors’ Conceptual Space approach and Humphreys et al.’s matrix model of memory.