A Neural Network Model of Spatio-Temporal Pattern Recognition, Recall and Timing

This paper describes the design of a self~organizing, hierarchical neural network model of unsupervised serial learning. The model learns to recognize, store, and recall sequences of unitized patterns, using either short-term memory (STM) or both STM and long-term memory (LTM) mechanisms. Timing information is learned and recall {both from STM and from LTM) is performed with a learned rhythmical structure. The network, bearing similarities with ART (Carpenter & Grossberg 1987a), learns to map temporal sequences to unitized patterns, which makes it suitable for hierarchical operation. It is therefore capable of self-organizing codes for sequences of sequences. The capacity is only limited by the number of nodes provided. Selected simulation results are reported to illustrate system properties.

Normal and Amnesis Learning, Recognition, and Memory by a Neural Model of Cortico-Hippocampal Interactions

The processes by which humans and other primates learn to recognize objects have been the subject of many models. Processes such as learning, categorization, attention, memory search, expectation, and novelty detection work together at different stages to realize object recognition. In this article, Gail Carpenter and Stephen Grossberg describe one such model class (Adaptive Resonance Theory, ART) and discuss how its structure and function might relate to known neurological learning and memory processes, such as how inferotemporal cortex can recognize both specialized and abstract information, and how medial temporal amnesia may be caused by lesions in the hippocampal formation. The model also suggests how hippocampal and inferotemporal processing may be linked during recognition learning.

A Unified Model of Spatiotemporal Processing in the Retina

A computational model of visual processing in the vertebrate retina provides a unified explanation of a range of data previously treated by disparate models. Three results are reported here: the model proposes a functional explanation for the primary feed-forward retinal circuit found in vertebrate retinae, it shows how this retinal circuit combines nonlinear adaptation with the desirable properties of linear processing, and it accounts for the origin of parallel transient (nonlinear) and sustained (linear) visual processing streams as simple variants of the same retinal circuit. The retina, owing to its accessibility and to its fundamental role in the initial transduction of light into neural signals, is among the most extensively studied neural structures in the nervous system. Since the pioneering anatomical work by Ramón y Cajal at the turn of the last century[1], technological advances have abetted detailed descriptions of the physiological, pharmacological, and functional properties of many types of retinal cells. However, the relationship between structure and function in the retina is still poorly understood. This article outlines a computational model developed to address fundamental constraints of biological visual systems. Neurons that process nonnegative input signals-such as retinal illuminance-are subject to an inescapable tradeoff between accurate processing in the spatial and temporal domains. Accurate processing in both domains can be achieved with a model that combines nonlinear mechanisms for temporal and spatial adaptation within three layers of feed-forward processing. The resulting architecture is structurally similar to the feed-forward retinal circuit connecting photoreceptors to retinal ganglion cells through bipolar cells. This similarity suggests that the three-layer structure observed in all vertebrate retinae[2] is a required minimal anatomy for accurate spatiotemporal visual processing. This hypothesis is supported through computer simulations showing that the model's output layer accounts for many properties of retinal ganglion cells[3],[4],[5],[6]. Moreover, the model shows how the retina can extend its dynamic range through nonlinear adaptation while exhibiting seemingly linear behavior in response to a variety of spatiotemporal input stimuli. This property is the basis for the prediction that the same retinal circuit can account for both sustained (X) and transient (Y) cat ganglion cells[7] by simple morphological changes. The ability to generate distinct functional behaviors by simple changes in cell morphology suggests that different functional pathways originating in the retina may have evolved from a unified anatomy designed to cope with the constraints of low-level biological vision.

A Spectral Network Model of Pitch Perception

A model of pitch perception, called the Spatial Pitch Network or SPINET model, is developed and analyzed. The model neurally instantiates ideas front the spectral pitch modeling literature and joins them to basic neural network signal processing designs to simulate a broader range of perceptual pitch data than previous spectral models. The components of the model arc interpreted as peripheral mechanical and neural processing stages, which arc capable of being incorporated into a larger network architecture for separating multiple sound sources in the environment. The core of the new model transforms a spectral representation of an acoustic source into a spatial distribution of pitch strengths. The SPINET model uses a weighted "harmonic sieve" whereby the strength of activation of a given pitch depends upon a weighted sum of narrow regions around the harmonics of the nominal pitch value, and higher harmonics contribute less to a pitch than lower ones. Suitably chosen harmonic weighting functions enable computer simulations of pitch perception data involving mistuned components, shifted harmonics, and various types of continuous spectra including rippled noise. It is shown how the weighting functions produce the dominance region, how they lead to octave shifts of pitch in response to ambiguous stimuli, and how they lead to a pitch region in response to the octave-spaced Shepard tone complexes and Deutsch tritones without the use of attentional mechanisms to limit pitch choices. An on-center off-surround network in the model helps to produce noise suppression, partial masking and edge pitch. Finally, it is shown how peripheral filtering and short term energy measurements produce a model pitch estimate that is sensitive to certain component phase relationships.

A Self-Organizing Neural Model of Motor Equivalent Reaching and Tool Use by a Multijoint Arm

This paper describes a self-organizing neural model for eye-hand coordination. Called the DIRECT model, it embodies a solution of the classical motor equivalence problem. Motor equivalence computations allow humans and other animals to flexibly employ an arm with more degrees of freedom than the space in which it moves to carry out spatially defined tasks under conditions that may require novel joint configurations. During a motor babbling phase, the model endogenously generates movement commands that activate the correlated visual, spatial, and motor information that are used to learn its internal coordinate transformations. After learning occurs, the model is capable of controlling reaching movements of the arm to prescribed spatial targets using many different combinations of joints. When allowed visual feedback, the model can automatically perform, without additional learning, reaches with tools of variable lengths, with clamped joints, with distortions of visual input by a prism, and with unexpected perturbations. These compensatory computations occur within a single accurate reaching movement. No corrective movements are needed. Blind reaches using internal feedback have also been simulated. The model achieves its competence by transforming visual information about target position and end effector position in 3-D space into a body-centered spatial representation of the direction in 3-D space that the end effector must move to contact the target. The spatial direction vector is adaptively transformed into a motor direction vector, which represents the joint rotations that move the end effector in the desired spatial direction from the present arm configuration. Properties of the model are compared with psychophysical data on human reaching movements, neurophysiological data on the tuning curves of neurons in the monkey motor cortex, and alternative models of movement control.

Differential and numerical models of hysteretic systems with stochastic and deterministic inputs

Many deterministic models with hysteresis have been developed in the areas of economics, finance, terrestrial hydrology and biology. These models lack any stochastic element which can often have a strong effect in these areas. In this work stochastically driven closed loop systems with hysteresis type memory are studied. This type of system is presented as a possible stochastic counterpart to deterministic models in the areas of economics, finance, terrestrial hydrology and biology. Some price dynamics models are presented as a motivation for the development of this type of model. Numerical schemes for solving this class of stochastic differential equation are developed in order to examine the prototype models presented. As a means of further testing the developed numerical schemes, numerical examination is made of the behaviour near equilibrium of coupled ordinary differential equations where the time derivative of the Preisach operator is included in one of the equations. A model of two phenotype bacteria is also presented. This model is examined to explore memory effects and related hysteresis effects in the area of biology. The memory effects found in this model are similar to that found in the non-ideal relay. This non-ideal relay type behaviour is used to model a colony of bacteria with multiple switching thresholds. This model contains a Preisach type memory with a variable Preisach weight function. Shown numerically for this multi-threshold model is a pattern formation for the distribution of the phenotypes among the available thresholds.

The contribution of enterprise systems to core capabilities: the case of asset lifecycle management in the utilities sector

The desire to obtain competitive advantage is a motivator for implementing Enterprise Resource Planning (ERP) Systems (Adam & O’Doherty, 2000). However, while it is accepted that Information Technology (IT) in general may contribute to the improvement of organisational performance (Melville, Kraemer, & Gurbaxani, 2004), the nature and extent of that contribution is poorly understood (Jacobs & Bendoly, 2003; Ravichandran & Lertwongsatien, 2005). Accordingly, Henderson and Venkatraman (1993) assert that it is the application of business and IT capabilities to develop and leverage a firm’s IT resources for organisational transformation, rather than the acquired technological functionality, that secures competitive advantage for firms. Application of the Resource Based View of the firm (Wernerfelt, 1984) and Dynamic Capabilities Theory (DCT) (Teece and Pisano (1998) in particular) may yield insights into whether or not the use of Enterprise Systems enhances organisations’ core capabilities and thereby obtains competitive advantage, sustainable or otherwise (Melville et al., 2004). An operational definition of Core Capabilities that is independent of the construct of Sustained Competitive Advantage is formulated. This Study proposes and utilises an applied Dynamic Capabilities framework to facilitate the investigation of the role of Enterprise Systems. The objective of this research study is to investigate the role of Enterprise Systems in the Core Dynamic Capabilities of Asset Lifecycle Management. The Study explores the activities of Asset Lifecycle Management, the Core Dynamic Capabilities inherent in Asset Lifecycle Management and the footprint of Enterprise Systems on those Dynamic Capabilities. Additionally, the study explains the mechanisms by which Enterprise Systems sustain the Exploitability and the Renewability of those Core Dynamic Capabilities. The study finds that Enterprise Systems contribute directly to the Value, Exploitability and Renewability of Core Dynamic Capabilities and indirectly to their Inimitability and Non-substitutability. The study concludes by presenting an applied Dynamic Capabilities framework, which integrates Alter (1992)’s definition of Information Systems with Teece and Pisano (1998)’s model of Dynamic Capabilities to provide a robust diagnostic for determining the sustained value generating contributions of Enterprise Systems. These frameworks are used in the conclusions to frame the findings of the study. The conclusions go on to assert that these frameworks are free - standing and analytically generalisable, per Siggelkow (2007) and Yin (2003).

Towards a new model of criminal justice system in the era of globalised criminality: the biggest challenges for criminal process legislation

The main objective of this thesis is the critical analysis of the evolution of the criminal justice systems throughout the past decade, with special attention to the fight against transnational terrorism. It is evident – for any observer - that such threats and the associated risk that terrorism entails, has changed significantly throughout the past decade. This perception has generated answers – many times radical ones – by States, as they have committed themselves to warrant the safety of their populations and to ease a growing sentiment of social panic. This thesis seeks to analyse the characteristics of this new threat and the responses that States have developed in the fight against terrorism since 9/11, which have questioned some of the essential principles and values in place in their own legal systems. In such sense, freedom and security are placed into perspective throughout the analysis of the specific antiterrorist legal reforms of five different States: Israel, Portugal, Spain, the United Kingdom and the United States of America. On the other hand, in light of those antiterrorist reforms, it will be questioned if it is possible to speak of the emergence of a new system of criminal justice (and of a process of a convergence between common law and civil law systems), built upon a control and preventive security framework, significantly different from traditional models. Finally, this research project has the fundamental objective to contribute to a better understanding on the economic, social and civilization costs of those legal reforms regarding human rights, the rule of law and democracy in modern States.

MyRoom: A user-centred model of affective responsive architecture

Can my immediate physical environment affect how I feel? The instinctive answer to this question must be a resounding “yes”. What might seem a throwaway remark is increasingly borne out by research in environmental and behavioural psychology, and in the more recent discipline of Evidence-Based Design. Research outcomes are beginning to converge with findings in neuroscience and neurophysiology, as we discover more about how the human brain and body functions, and reacts to environmental stimuli. What we see, hear, touch, and sense affects each of us psychologically and, by extension, physically, on a continual basis. The physical characteristics of our daily environment thus have the capacity to profoundly affect all aspects of our functioning, from biological systems to cognitive ability. This has long been understood on an intuitive basis, and utilised on a more conscious basis by architects and other designers. Recent research in evidence-based design, coupled with advances in neurophysiology, confirm what have been previously held as commonalities, but also illuminate an almost frightening potential to do enormous good, or alternatively, terrible harm, by virtue of how we make our everyday surroundings. The thesis adopts a design methodology in its approach to exploring the potential use of wireless sensor networks in environments for elderly people. Vitruvian principles of “commodity, firmness and delight” inform the research process and become embedded in the final design proposals and research conclusions. The issue of person-environment fit becomes a key principle in describing a model of continuously-evolving responsive architecture which makes the individual user its focus, with the intention of promoting wellbeing. The key research questions are: What are the key system characteristics of an adaptive therapeutic single-room environment? How can embedded technologies be utilised to maximise the adaptive and therapeutic aspects of the personal life-space of an elderly person with dementia?.

Coevolution of capitalism and political representation: The choice of electoral systems

Protocorporatist West European countries in which economic interests were collectively organized adopted PR in the first quarter of the twentieth century, whereas liberal countries in which economic interests were not collectively organized did not. Political parties, as Marcus Kreuzer points out, choose electoral systems. So how do economic interests translate into party political incentives to adopt electoral reform? We argue that parties in protocorporatist countries were representative of and closely linked to economic interests. As electoral competition in single member districts increased sharply up to World War I, great difficulties resulted for the representative parties whose leaders were seen as interest committed. They could not credibly compete for votes outside their interest without leadership changes or reductions in interest influence. Proportional representation offered an obvious solution, allowing parties to target their own voters and their organized interest to continue effective influence in the legislature. In each respect, the opposite was true of liberal countries. Data on party preferences strongly confirm this model. (Kreuzer's historical criticisms are largely incorrect, as shown in detail in the online supplementary Appendix.). © 2010 American Political Science Association.

Real-Time Decision Making and Aggressive Behavior in Youth: A Heuristic Model of Response Evaluation and Decision (RED).

Considerable scientific and intervention attention has been paid to judgment and decision-making systems associated with aggressive behavior in youth. However, most empirical studies have investigated social-cognitive correlates of stable child and adolescent aggressiveness, and less is known about real-time decision making to engage in aggressive behavior. A model of real-time decision making must incorporate both impulsive actions and rational thought. The present paper advances a process model (response evaluation and decision; RED) of real-time behavioral judgments and decision making in aggressive youths with mathematic representations that may be used to quantify response strength. These components are a heuristic to describe decision making, though it is doubtful that individuals always mentally complete these steps. RED represents an organization of social-cognitive operations believed to be active during the response decision step of social information processing. The model posits that RED processes can be circumvented through impulsive responding. This article provides a description and integration of thoughtful, rational decision making and nonrational impulsivity in aggressive behavioral interactions.

A memory-based model of posttraumatic stress disorder: evaluating basic assumptions underlying the PTSD diagnosis.

In the mnemonic model of posttraumatic stress disorder (PTSD), the current memory of a negative event, not the event itself, determines symptoms. The model is an alternative to the current event-based etiology of PTSD represented in the Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; American Psychiatric Association, 2000). The model accounts for important and reliable findings that are often inconsistent with the current diagnostic view and that have been neglected by theoretical accounts of the disorder, including the following observations. The diagnosis needs objective information about the trauma and peritraumatic emotions but uses retrospective memory reports that can have substantial biases. Negative events and emotions that do not satisfy the current diagnostic criteria for a trauma can be followed by symptoms that would otherwise qualify for PTSD. Predisposing factors that affect the current memory have large effects on symptoms. The inability-to-recall-an-important-aspect-of-the-trauma symptom does not correlate with other symptoms. Loss or enhancement of the trauma memory affects PTSD symptoms in predictable ways. Special mechanisms that apply only to traumatic memories are not needed, increasing parsimony and the knowledge that can be applied to understanding PTSD.

Nanoscopic modelling of the adhesion, indentation and fracture characteristics of metallic systems via molecular dynamics simulations

Large-scale molecular dynamics simulations have been performed on canonical ensembles to model the adhesion and indentation characteristics of 3-D metallic nano-scale junctions in tip-substrate geometries, and the crack propagation in 2-D metallic lattices. It is shown that irreversible flows in nano-volumes of materials control the behaviour of the 3-D nano-contacts, and that local diffusional flow constitutes the atomistic mechanism underlying these plastic flows. These simulations show that the force of adhesion in metallic nano-contacts is reduced when adsorbate monolayers are present at the metal—metal junctions. Our results are in agreement with the conclusions of very accurate point-contact experiments carried out in this field. Our fracture simulations reveal that at low temperatures cleavage fractures can occur in both an elemental metal and an alloy. At elevated temperatures, the nucleation of dislocations is shown to cause a brittle-to-ductile transition. Limiting crack propagation velocities are computed for different strain rates and a dynamic instability is shown to control the crack movement beyond this limiting velocity, in line with the recent experimental results.

Obtaining data to validate a model of an induction skull melting furnace

A casting route is often the most cost-effective means of producing engineering components. However, certain materials, particularly those based on Ti, TiAl and Zr alloy systems, are very reactive in the molten condition and must be melted in special furnaces. Induction Skull Melting (ISM) is the most widely-used process for melting these alloys prior to casting components such as turbine blades, engine valves, turbocharger rotors and medical prostheses. A major research project is underway with the specific target of developing robust techniques for casting TiAl components. The aims include increasing the superheat in the molten metal to allow thin section components to be cast, improving the quality of the cast components and increasing the energy efficiency of the process. As part of this, the University of Greenwich (UK) is developing a computer model of the ISM process in close collaboration with the University of Birmingham (UK) where extensive melting trials are being undertaken. This paper describes the experimental measurements to obtain data to feed into and to validate the model. These include measurements of the true RMS current applied to the induction coil, the heat transfer from the molten metal to the crucible cooling water, and the shape of the column of semi-levitated molten metal. Data are presented for Al, Ni and TiAl.

Turbulence modelling for thermal management of electronic systems

The electronics industry is developing rapidly together with the increasingly complex problem of microelectronic equipment cooling. It has now become necessary for thermal design engineers to consider the problem of equipment cooling at some level. The use of Computational Fluid Dynamics (CFD) for such investigations is fast becoming a powerful and almost essential tool for the design, development and optimisation of engineering applications. However turbulence models remain a key issue when tackling such flow phenomena. The reliability of CFD analysis depends heavily on the turbulence model employed together with the wall functions implemented. In order to resolve the abrupt fluctuations experienced by the turbulent energy and other parameters located at near wall regions and shear layers a particularly fine computational mesh is necessary which inevitably increases the computer storage and run-time requirements. This paper will discuss results from an investigation into the accuract of currently used turbulence models. Also a newly formulated transitional hybrid turbulence model will be introduced with comparisonsaagainst experimental data.