Self-organising neural networks for adaptive control

Self-organizing neural networks have been implemented in a wide range of application areas such as speech processing, image processing, optimization and robotics. Recent variations to the basic model proposed by the authors enable it to order state space using a subset of the input vector and to apply a local adaptation procedure that does not rely on a predefined test duration limit. Both these variations have been incorporated into a new feature map architecture that forms an integral part of an Hybrid Learning System (HLS) based on a genetic-based classifier system. Problems are represented within HLS as objects characterized by environmental features. Objects controlled by the system have preset targets set against a subset of their features. The system's objective is to achieve these targets by evolving a behavioural repertoire that efficiently explores and exploits the problem environment. Feature maps encode two types of knowledge within HLS — long-term memory traces of useful regularities within the environment and the classifier performance data calibrated against an object's feature states and targets. Self-organization of these networks constitutes non-genetic-based (experience-driven) learning within HLS. This paper presents a description of the HLS architecture and an analysis of the modified feature map implementing associative memory. Initial results are presented that demonstrate the behaviour of the system on a simple control task.

Williams Syndrome: the extent of agreement between parent and self report of psychological difficulties

Background and Objectives: People with Williams syndrome (WS) have been reported by their carers to have problems with attention, anxiety and social relationships. People with WS have been shown to report their anxieties. This study extends our knowledge of how people with WS see themselves in terms of behaviour and social relationships. Methods: A survey using self and parent report forms of the Strengths and Difficulties Questionnaire. Results: Both parents and individuals with WS (N = 31) reported difficulties in emotional disorder and hyperactivity symptoms and strengths in prosocial behaviours such as altruism and empathy. They disagreed about peer problems. Conclusions: People with WS understand some but not all of their difficulties. In particular they fail to recognize their social difficulties which may lead them to be vulnerable to exploitation.

Autobiographical memory and the self in a case of transient epileptic amnesia

Transient epileptic amnesia (TEA) is characterized by deficits in autobiographical memory (AM). One of the functions of AM is to maintain the self, suggesting that the self may undergo changes as a result of memory loss in temporal lobe epilepsy. To examine this, we used a modification of a task used to assess the relationship between self and memory (the IAM task) in a single case, E.B. Despite complaints of AM loss, E.B. had no difficulty in producing a range of self-images (e.g., I am a husband) and collections of self-defining AMs in support of these statements. E.B. produced fewer episodic memories at times of self-formation, but this did not seem to impact on the maintenance of self. The results support recent work suggesting the self may be maintained in the absence of episodic memory. The application of tasks such as that used here will further elucidate AM impairment in temporal lobe epilepsy. (C) 2011 Elsevier Inc. All rights reserved.

Decentralized PID self-tuning control of industrial robots

A three degrees of freedom industrial robot is controlled by applying PID self-tuning (PID/ST) controllers. This control is considered as a corrective term to a nominal value, centrally computed from an inaccurate and/ or simplified dynamic model. An identification scheme on an assumed linear plant describing the deviation from the desired trajectory is employed in order to tune the controller coefficients and thus accomplish a behaviour prescribed through a desired pole placement. A salient feature of our approach is the decentralized nature of the controllers producing the corrective term for each joint. This opens the way to practical implementation, as recent computing requirement calculations for similar set-ups have shown in the literature. Numerical results are presented.

A micro-level simulation for the prediction of intention and behaviour

In this contribution we aim at anchoring Agent-Based Modeling (ABM) simulations in actual models of human psychology. More specifically, we apply unidirectional ABM to social psychological models using low level agents (i.e., intra-individual) to examine whether they generate better predictions, in comparison to standard statistical approaches, concerning the intentions of performing a behavior and the behavior. Moreover, this contribution tests to what extent the predictive validity of models of attitude such as the Theory of Planned Behavior (TPB) or Model of Goal-directed Behavior (MGB) depends on the assumption that peoples’ decisions and actions are purely rational. Simulations were therefore run by considering different deviations from rationality of the agents with a trembling hand method. Two data sets concerning respectively the consumption of soft drinks and physical activity were used. Three key findings emerged from the simulations. First, compared to standard statistical approach the agent-based simulation generally improves the prediction of behavior from intention. Second, the improvement in prediction is inversely proportional to the complexity of the underlying theoretical model. Finally, the introduction of varying degrees of deviation from rationality in agents’ behavior can lead to an improvement in the goodness of fit of the simulations. By demonstrating the potential of ABM as a complementary perspective to evaluating social psychological models, this contribution underlines the necessity of better defining agents in terms of psychological processes before examining higher levels such as the interactions between individuals.

Policy making without legislating: the self-regulation of commercial property leasing

The terms of a commercial property lease covers aspects such as rent, alterations to premises and the ability to leave; consequently they have a significant impact on cash flow and the ability of a business to develop. In contrast to the heavily-legislated residential sector, commercial landlords and tenants in the UK are largely free to negotiate the terms of their contract. Yet, since the property crash of 1989/90, successive governments have taken an interest in commercial leasing; in particular there is a desire to see landlords being more flexible. UK Government policy in this area has been pursued through industry self-regulation rather than legislation; since 1995 there have been three industry codes of practice on leasing. These codes are sanctioned by government and monitored by them. Yet, 15 years after the first code was launched, many in the industry see the whole code concept as ineffective and unlikely to ever achieve changes to certain aspects of landlord behaviour. This paper is the first step in considering the lease codes in the wider context of industry self-regulation. The aim of the paper is twofold: First a framework is created using the literature on industry self-regulation from various countries and industries which suggests key criteria to explain the effectiveness (or ineffectiveness) of self-regulation. This is then applied to the UK lease codes based on research carried out by the authors for the UK Government to monitor the success of all three codes. The outcome is a clearer understanding of the possibilities and limitations of using a voluntary solution to achieve policy aims within the property industry.

Attention through self-synchronisation in the spiking neuron stochastic diffusion network

The paper discusses ensemble behaviour in the Spiking Neuron Stochastic Diffusion Network, SNSDN, a novel network exploring biologically plausible information processing based on higher order temporal coding. SNSDN was proposed as an alternative solution to the binding problem [1]. SNSDN operation resembles Stochastic Diffusin on Search, SDS, a non-deterministic search algorithm able to rapidly locate the best instantiation of a target pattern within a noisy search space ([3], [5]). In SNSDN, relevant information is encoded in the length of interspike intervals. Although every neuron operates in its own time, ‘attention’ to a pattern in the search space results in self-synchronised activity of a large population of neurons. When multiple patterns are present in the search space, ‘switching of at- tention’ results in a change of the synchronous activity. The qualitative effect of attention on the synchronicity of spiking behaviour in both time and frequency domain will be discussed.

Structural and morphological studies of the dipeptide based L-Pro-L-Val organocatalytic gels and their rheological behaviour

Organocatalytic gels based on the dipeptide sequence L-Pro-L-Val have been studied by two different FTIR techniques. This suggests a different arrangement of the gelator molecules in the self-assembled fibers depending on the organic solvent employed. In acetonitrile and nitromethane the structure of the supramolecular aggregates is similar and provides similar catalytic properties (supramolecularenhancement of basicity). In contrast, the self-assembled fibers obtained in toluene clearly presented a different molecular arrangement consistent with its different catalytic behaviour (enamine-based catalysis). In addition these gels have been studied by microscopy and rheology.

Beyond behaviour: is social anxiety low in Williams syndrome

Individuals with Williams syndrome (WS) exhibit striking social behaviour that may be indicative of abnormally low social anxiety. The present research aimed to determine whether social anxiety is unusually low in WS and to replicate previous findings of increased generalised anxiety in WS using both parent and self report. Fifteen individuals with WS aged 12-28 years completed the Spence Children’s Anxiety Scale (SCAS) and the Children’s Automatic Thoughts Scale (CATS). Their responses were compared to clinically anxious and community comparison groups matched on mental age. The findings suggest that WS is not associated with unusually low social anxiety but that generalised anxiety symptoms and physical threat thoughts are increased in WS, relative to typically developing children.

Bioactive films produced from self-assembling peptide amphiphiles as versatile substrates for tuning cell adhesion and tissue architecture in serum-free conditions

The development of versatile bioactive surfaces able to emulate in vivo conditions is of enormous importance to the future of cell and tissue therapy. Tuning cell behaviour on two-dimensional surfaces so that the cells perform as if they were in a natural three-dimensional tissue represents a significant challenge, but one that must be met if the early promise of cell and tissue therapy is to be fully realised. Due to the inherent complexities involved in the manufacture of biomimetic three-dimensional substrates, the scaling up of engineered tissue-based therapies may be simpler if based upon proven two-dimensional culture systems. In this work, we developed new coating materials composed of the self-assembling peptide amphiphiles (PAs) C16G3RGD (RGD) and C16G3RGDS (RGDS) shown to control cell adhesion and tissue architecture while avoiding the use of serum. When mixed with the C16ETTES diluent PA at 13 : 87 (mol mol-1) ratio at 1.25 times 10-3 M, the bioactive {PAs} were shown to support optimal adhesion, maximal proliferation, and prolonged viability of human corneal stromal fibroblasts ({hCSFs)}, while improving the cell phenotype. These {PAs} also provided stable adhesive coatings on highly-hydrophobic surfaces composed of striated polytetrafluoroethylene ({PTFE)}, significantly enhancing proliferation of aligned cells and increasing the complexity of the produced tissue. The thickness and structure of this highly-organised tissue were similar to those observed in vivo, comprising aligned newly-deposited extracellular matrix. As such, the developed coatings can constitute a versatile biomaterial for applications in cell biology, tissue engineering, and regenerative medicine requiring serum-free conditions.

On univoque points for self-similar sets

Let K⊆R be the unique attractor of an iterated function system. We consider the case where K is an interval and study those elements of K with a unique coding. We prove under mild conditions that the set of points with a unique coding can be identified with a subshift of finite type. As a consequence, we can show that the set of points with a unique coding is a graph-directed self-similar set in the sense of Mauldin and Williams (1988). The theory of Mauldin and Williams then provides a method by which we can explicitly calculate the Hausdorff dimension of this set. Our algorithm can be applied generically, and our result generalises the work of Daróczy, Kátai, Kallós, Komornik and de Vries.

Self-licensing and financial rewards: is morality for sale?

This paper studies the impact of financially rewarding good deeds on self-licensing. We run a between-subjects experiment comprised of an adapted dictator game preceded by paid and unpaid pro-environmental tasks. We find that prefacing the dictator game with an unpaid good deed seems to establish a 'moral rectitude' which licenses subsequent selfish behaviour, whereas a paid good deed dampens this effect. Interestingly, the nature of the initial task has more of an effect on the binary option (give vs. not give) than on the amount donated.

The relationship between challenging parenting behaviour and childhood anxiety disorders

Background: This research investigates the relationship between challenging parenting behaviour and childhood anxiety disorders proposed by Bögels and Phares (2008). Challenging parenting behaviour involves the playful encouragement of children to go beyond their own limits, and may decrease children’s risk for anxiety (Bögels & Phares, 2008). Method: Parents (n = 164 mothers, 144 fathers) of 164 children aged between 3.4 and 4.8 years participated in the current study. A multi-method, multi-informant assessment of anxiety was used, incorporating data from diagnostic interviews as well as questionnaire measures. Parents completed self-report measures of their parenting behaviour (n = 147 mothers, 138 fathers) and anxiety (n = 154 mothers, 143 fathers). Mothers reported on their child’s anxiety via questionnaire as well as diagnostic interview (n = 156 and 164 respectively). Of these children, 74 met criteria for an anxiety disorder and 90 did not. Results: Fathers engaged in challenging parenting behaviour more often than mothers. Both mothers’ and fathers’ challenging parenting behaviour was associated with lower report of child anxiety symptoms. However, only mothers’ challenging parenting behaviour was found to predict child clinical anxiety diagnosis. Limitations: Shared method variance from mothers confined the interpretation of these results. Moreover, due to study design, it is not possible to delineate cause and effect. Conclusions: The finding with respect to maternal challenging parenting behaviour was not anticipated, prompting replication of these results. Future research should investigate the role of challenging parenting behaviour by both caregivers as this may have implications for parenting interventions for anxious children.

Pupils' Interaction with the Exhibits According to the Learning Behaviour Model

Science centres are one of the best opportunities for informal study of natural science. There are many advantages to learn in the science centres compared with the traditional methods: it is possible to motivate and supply visitors with the social experience, to improve people’s understandings and attitudes, thereby bringing on and attaching wider interest towards natural science. In the science centres, pupils show interest, enthusiasm, motivation, self-confidence, sensitiveness and also they are more open and eager to learn. Traditional school-classes however mostly do not favour these capabilities. This research presents the qualitative study in the science centre. Data was gathered from observations and interviews at Science North science centre in Canada. Pupils’ learning behaviours were studied at different exhibits in the science centre. Learning behaviours are classified as follows: labels reading, experimenting with the exhibits, observing others or exhibit, using guide, repeating the activity, positive emotional response, acknowledged relevance, seeking and sharing information. In this research, it became clear that in general pupils do not read labels; in most cases pupils do not use the guides help; pupils prefer exhibits that enable high level of interactivity; pupils display more learning behaviours at exhibits that enable a high level of interactivity.

Triggering Solar-Powered Vehicle Activated Signs using Self Organising Maps with K-means

Solar-powered vehicle activated signs (VAS) are speed warning signs powered by batteries that are recharged by solar panels. These signs are more desirable than other active warning signs due to the low cost of installation and the minimal maintenance requirements. However, one problem that can affect a solar-powered VAS is the limited power capacity available to keep the sign operational. In order to be able to operate the sign more efficiently, it is proposed that the sign be appropriately triggered by taking into account the prevalent conditions. Triggering the sign depends on many factors such as the prevailing speed limit, road geometry, traffic behaviour, the weather and the number of hours of daylight. The main goal of this paper is therefore to develop an intelligent algorithm that would help optimize the trigger point to achieve the best compromise between speed reduction and power consumption. Data have been systematically collected whereby vehicle speed data were gathered whilst varying the value of the trigger speed threshold. A two stage algorithm is then utilized to extract the trigger speed value. Initially the algorithm employs a Self-Organising Map (SOM), to effectively visualize and explore the properties of the data that is then clustered in the second stage using K-means clustering method. Preliminary results achieved in the study indicate that using a SOM in conjunction with K-means method is found to perform well as opposed to direct clustering of the data by K-means alone. Using a SOM in the current case helped the algorithm determine the number of clusters in the data set, which is a frequent problem in data clustering.