The impact of architecture on the performance of artificial neural networks

A number of researchers have investigated the impact of network architecture on the performance of artificial neural networks. Particular attention has been paid to the impact on the performance of the multi-layer perceptron of architectural issues, and the use of various strategies to attain an optimal network structure. However, there are still perceived limitations with the multi-layer perceptron and networks that employ a different architecture to the multi-layer perceptron have gained in popularity in recent years, particularly, networks that implement a more localised solution, where the solution in one area of the problem space does not impact, or has a minimal impact, on other areas of the space. In this study, we discuss the major architectural issues affecting the performance of a multi-layer perceptron, before moving on to examine in detail the performance of a new localised network, namely the bumptree. The work presented here examines the impact on the performance of artificial neural networks of employing alternative networks to the long established multi-layer perceptron. In particular, networks that impose a solution where the impact of each parameter in the final network architecture has a localised impact on the problem space being modelled are examined. The alternatives examined are the radial basis function and bumptree neural networks, and the impact of architectural issues on the performance of these networks is examined. Particular attention is paid to the bumptree, with new techniques for both developing the bumptree structure and employing this structure to classify patterns being examined.

Dynamic causal modeling of load-dependent modulation of effective connectivity within the verbal working memory network

Neuroimaging studies have consistently shown that working memory (WM) tasks engage a distributed neural network that primarily includes the dorsolateral prefrontal cortex, the parietal cortex, and the anterior cingulate cortex. The current challenge is to provide a mechanistic account of the changes observed in regional activity. To achieve this, we characterized neuroplastic responses in effective connectivity between these regions at increasing WM loads using dynamic causal modeling of functional magnetic resonance imaging data obtained from healthy individuals during a verbal n-back task. Our data demonstrate that increasing memory load was associated with (a) right-hemisphere dominance, (b) increasing forward (i.e., posterior to anterior) effective connectivity within the WM network, and (c) reduction in individual variability in WM network architecture resulting in the right-hemisphere forward model reaching an exceedance probability of 99% in the most demanding condition. Our results provide direct empirical support that task difficulty, in our case WM load, is a significant moderator of short-term plasticity, complementing existing theories of task-related reduction in variability in neural networks. Hum Brain Mapp, 2013. © 2013 Wiley Periodicals, Inc.

Spatial-spectral flexible optical networking:enabling switching solutions for a simplified and efficient SDM network platform

The traffic carried by core optical networks grows at a steady but remarkable pace of 30-40% year-over-year. Optical transmissions and networking advancements continue to satisfy the traffic requirements by delivering the content over the network infrastructure in a cost and energy efficient manner. Such core optical networks serve the information traffic demands in a dynamic way, in response to requirements for shifting of traffics demands, both temporally (day/night) and spatially (business district/residential). However as we are approaching fundamental spectral efficiency limits of singlemode fibers, the scientific community is pursuing recently the development of an innovative, all-optical network architecture introducing the spatial degree of freedom when designing/operating future transport networks. Spacedivision- multiplexing through the use of bundled single mode fibers, and/or multi-core fibers and/or few-mode fibers can offer up to 100-fold capacity increase in future optical networks. The EU INSPACE project is working on the development of a complete spatial-spectral flexible optical networking solution, offering the network ultra-high capacity, flexibility and energy efficiency required to meet the challenges of delivering exponentially growing traffic demands in the internet over the next twenty years. In this paper we will present the motivation and main research activities of the INSPACE consortium towards the realization of the overall project solution. © 2014 Copyright SPIE.

Editorial

This special issue of the Journal of the Operational Research Society is dedicated to papers on the related subjects of knowledge management and intellectual capital. These subjects continue to generate considerable interest amongst both practitioners and academics. This issue demonstrates that operational researchers have many contributions to offer to the area, especially by bringing multi-disciplinary, integrated and holistic perspectives. The papers included are both theoretical as well as practical, and include a number of case studies showing how knowledge management has been implemented in practice that may assist other organisations in their search for a better means of managing what is now recognised as a core organisational activity. It has been accepted by a growing number of organisations that the precise handling of information and knowledge is a significant factor in facilitating their success but that there is a challenge in how to implement a strategy and processes for this handling. It is here, in the particular area of knowledge process handling that we can see the contributions of operational researchers most clearly as is illustrated in the papers included in this journal edition. The issue comprises nine papers, contributed by authors based in eight different countries on five continents. Lind and Seigerroth describe an approach that they call team-based reconstruction, intended to help articulate knowledge in a particular organisational. context. They illustrate the use of this approach with three case studies, two in manufacturing and one in public sector health care. Different ways of carrying out reconstruction are analysed, and the benefits of team-based reconstruction are established. Edwards and Kidd, and Connell, Powell and Klein both concentrate on knowledge transfer. Edwards and Kidd discuss the issues involved in transferring knowledge across frontières (borders) of various kinds, from those borders within organisations to those between countries. They present two examples, one in distribution and the other in manufacturing. They conclude that trust and culture both play an important part in facilitating such transfers, that IT should be kept in a supporting role in knowledge management projects, and that a staged approach to this IT support may be the most effective. Connell, Powell and Klein consider the oft-quoted distinction between explicit and tacit knowledge, and argue that such a distinction is sometimes unhelpful. They suggest that knowledge should rather be regarded as a holistic systemic property. The consequences of this for knowledge transfer are examined, with a particular emphasis on what this might mean for the practice of OR Their view of OR in the context of knowledge management very much echoes Lind and Seigerroth's focus on knowledge for human action. This is an interesting convergence of views given that, broadly speaking, one set of authors comes from within the OR community, and the other from outside it. Hafeez and Abdelmeguid present the nearest to a 'hard' OR contribution of the papers in this special issue. In their paper they construct and use system dynamics models to investigate alternative ways in which an organisation might close a knowledge gap or skills gap. The methods they use have the potential to be generalised to any other quantifiable aspects of intellectual capital. The contribution by Revilla, Sarkis and Modrego is also at the 'hard' end of the spectrum. They evaluate the performance of public–private research collaborations in Spain, using an approach based on data envelopment analysis. They found that larger organisations tended to perform relatively better than smaller ones, even though the approach used takes into account scale effects. Perhaps more interesting was that many factors that might have been thought relevant, such as the organisation's existing knowledge base or how widely applicable the results of the project would be, had no significant effect on the performance. It may be that how well the partnership between the collaborators works (not a factor it was possible to take into account in this study) is more important than most other factors. Mak and Ramaprasad introduce the concept of a knowledge supply network. This builds on existing ideas of supply chain management, but also integrates the design chain and the marketing chain, to address all the intellectual property connected with the network as a whole. The authors regard the knowledge supply network as the natural focus for considering knowledge management issues. They propose seven criteria for evaluating knowledge supply network architecture, and illustrate their argument with an example from the electronics industry—integrated circuit design and fabrication. In the paper by Hasan and Crawford, their interest lies in the holistic approach to knowledge management. They demonstrate their argument—that there is no simple IT solution for organisational knowledge management efforts—through two case study investigations. These case studies, in Australian universities, are investigated through cultural historical activity theory, which focuses the study on the activities that are carried out by people in support of their interpretations of their role, the opportunities available and the organisation's purpose. Human activities, it is argued, are mediated by the available tools, including IT and IS and in this particular context, KMS. It is this argument that places the available technology into the knowledge activity process and permits the future design of KMS to be improved through the lessons learnt by studying these knowledge activity systems in practice. Wijnhoven concentrates on knowledge management at the operational level of the organisation. He is concerned with studying the transformation of certain inputs to outputs—the operations function—and the consequent realisation of organisational goals via the management of these operations. He argues that the inputs and outputs of this process in the context of knowledge management are different types of knowledge and names the operation method the knowledge logistics. The method of transformation he calls learning. This theoretical paper discusses the operational management of four types of knowledge objects—explicit understanding; information; skills; and norms and values; and shows how through the proposed framework learning can transfer these objects to clients in a logistical process without a major transformation in content. Millie Kwan continues this theme with a paper about process-oriented knowledge management. In her case study she discusses an implementation of knowledge management where the knowledge is centred around an organisational process and the mission, rationale and objectives of the process define the scope of the project. In her case they are concerned with the effective use of real estate (property and buildings) within a Fortune 100 company. In order to manage the knowledge about this property and the process by which the best 'deal' for internal customers and the overall company was reached, a KMS was devised. She argues that process knowledge is a source of core competence and thus needs to be strategically managed. Finally, you may also wish to read a related paper originally submitted for this Special Issue, 'Customer knowledge management' by Garcia-Murillo and Annabi, which was published in the August 2002 issue of the Journal of the Operational Research Society, 53(8), 875–884.

A constructive learning algorithm based on back-propagation

There are been a resurgence of interest in the neural networks field in recent years, provoked in part by the discovery of the properties of multi-layer networks. This interest has in turn raised questions about the possibility of making neural network behaviour more adaptive by automating some of the processes involved. Prior to these particular questions, the process of determining the parameters and network architecture required to solve a given problem had been a time consuming activity. A number of researchers have attempted to address these issues by automating these processes, concentrating in particular on the dynamic selection of an appropriate network architecture.The work presented here specifically explores the area of automatic architecture selection; it focuses upon the design and implementation of a dynamic algorithm based on the Back-Propagation learning algorithm. The algorithm constructs a single hidden layer as the learning process proceeds using individual pattern error as the basis of unit insertion. This algorithm is applied to several problems of differing type and complexity and is found to produce near minimal architectures that are shown to have a high level of generalisation ability.

On bandwidth request mechanism with piggyback in fixed IEEE 802.16 networks

This paper investigates the random channel access mechanism specified in the IEEE 802.16 standard for the uplink traffic in a Point-to-MultiPoint (PMP) network architecture. An analytical model is proposed to study the impacts of the channel access parameters, bandwidth configuration and piggyback policy on the performance. The impacts of physical burst profile and non-saturated network traffic are also taken into account in the model. Simulations validate the proposed analytical model. It is observed that the bandwidth utilization can be improved if the bandwidth for random channel access can be properly configured according to the channel access parameters, piggyback policy and network traffic.

Nonlinear penalties in long-haul optical networks employing dynamic transponders

We report for the first time, the impact of cross phase modulation in WDM optical transport networks employing dynamic 28 Gbaud PM-mQAM transponders (m = 4, 16, 64, 256). We demonstrate that if the order of QAM is adjusted to maximize the capacity of a given route, there may be a significant degradation in the transmission performance of existing traffic for a given dynamic network architecture. We further report that such degradations are correlated to the accumulated peak-to-average power ratio of the added traffic along a given path, and that managing this ratio through pre-distortion reduces the impact of adjusting the constellation size of neighboring channels. (C) 2011 Optical Society of America

Evaluating the performance of a EuroDivisia index using artificial intelligence techniques

We compare two methods in order to predict inflation rates in Europe. One method uses a standard back propagation neural network and the other uses an evolutionary approach, where the network weights and the network architecture is evolved. Results indicate that back propagation produces superior results. However, the evolving network still produces reasonable results with the advantage that the experimental set-up is minimal. Also of interest is the fact that the Divisia measure of money is superior as a predictive tool over simple sum.

Evaluating the performance of a EuroDivisia index using artificial intelligence techniques

This paper compares two methods to predict in°ation rates in Europe. One method uses a standard back propagation neural network and the other uses an evolutionary approach, where the network weights and the network architecture are evolved. Results indicate that back propagation produces superior results. However, the evolving network still produces reasonable results with the advantage that the experimental set-up is minimal. Also of interest is the fact that the Divisia measure of money is superior as a predictive tool over simple sum.

Storage capacity of ultrametric committee machines

The problem of computing the storage capacity of a feed-forward network, with L hidden layers, N inputs, and K units in the first hidden layer, is analyzed using techniques from statistical mechanics. We found that the storage capacity strongly depends on the network architecture αc ∼ (log K)1-1/2L and that the number of units K limits the number of possible hidden layers L through the relationship 2L - 1 < 2log K. © 2014 IOP Publishing Ltd.

DISCUS : an end-to-end solution for ubiquitous broadband optical access

Fiber to the premises has promised to increase the capacity in telecommunications access networks for well over 30 years. While it is widely recognized that optical-fiber-based access networks will be a necessity in the shortto medium-term future, its large upfront cost and regulatory issues are pushing many operators to further postpone its deployment, while installing intermediate unambitious solutions such as fiber to the cabinet. Such high investment cost of both network access and core capacity upgrade often derives from poor planning strategies that do not consider the necessity to adequately modify the network architecture to fully exploit the cost benefit that a fiber-centric solution can bring. DISCUS is a European Framework 7 Integrated Project that, building on optical-centric solutions such as long-reach passive optical access and flat optical core, aims to deliver a cost-effective architecture for ubiquitous broadband services. DISCUS analyzes, designs, and demonstrates end-to-end architectures and technologies capable of saving cost and energy by reducing the number of electronic terminations in the network and sharing the deployment costs among a larger number of users compared to current fiber access systems. This article describes the network architecture and the supporting technologies behind DISCUS, giving an overview of the concepts and methodologies that will be used to deliver our end-to-end network solution. © 2013 IEEE.

Towards the distributed core for ubiquitous superfast broadband optical access

In this paper, we describe recent architectural and technological advances of the end to end optical network architecture proposed by the DISCUS project (the DIStributed Core for unlimited bandwidth supply for all Users and Services). The two main targets of DISCUS are the principle of equivalence in the access and the reduction of optical-to-electronic conversions in the metro-core network. Technological advances and techno-economic evaluation of Long-Reach Passive Optical Networks (LR-PON), as well as the optimal metro-core node architecture and the required network control plane framework are reported. Network infrastructure sharing challenges are also discussed. © 2014 IEEE.

Quality assessment of video transmission in heterogeneous networks as applied to real-time telecare

This work looks into video quality assessment applied to the field of telecare and proposes an alternative metric to the more traditionally used PSNR based on the requirements of such an application. We show that the Pause Intensity metric introduced in [1] is also relevant and applicable to heterogeneous networks with a wireless last hop connected to a wired TCP backbone. We demonstrate through our emulation testbed that the impairments experienced in such a network architecture are dominated by continuity based impairments rather than artifacts, such as motion drift or blockiness. We also look into the implication of using Pause Intensity as a metric in terms of the overall video latency, which is potentially problematic should the video be sent and acted upon in real-time. We conclude that Pause Intensity may be used alongside the video characteristics which have been suggested as a measure of the overall video quality. © 2012 IEEE.

Spatially orthogonal chemical functionalization of a hierarchical pore network for catalytic cascade reactions

The chemical functionality within porous architectures dictates their performance as heterogeneous catalysts; however, synthetic routes to control the spatial distribution of individual functions within porous solids are limited. Here we report the fabrication of spatially orthogonal bifunctional porous catalysts, through the stepwise template removal and chemical functionalization of an interconnected silica framework. Selective removal of polystyrene nanosphere templates from a lyotropic liquid crystal-templated silica sol–gel matrix, followed by extraction of the liquid crystal template, affords a hierarchical macroporous–mesoporous architecture. Decoupling of the individual template extractions allows independent functionalization of macropore and mesopore networks on the basis of chemical and/or size specificity. Spatial compartmentalization of, and directed molecular transport between, chemical functionalities affords control over the reaction sequence in catalytic cascades; herein illustrated by the Pd/Pt-catalysed oxidation of cinnamyl alcohol to cinnamic acid. We anticipate that our methodology will prompt further design of multifunctional materials comprising spatially compartmentalized functions.

Parallel implementation of image segmentation algorithms on a network of transputers

Image segmentation is one of the most computationally intensive operations in image processing and computer vision. This is because a large volume of data is involved and many different features have to be extracted from the image data. This thesis is concerned with the investigation of practical issues related to the implementation of several classes of image segmentation algorithms on parallel architectures. The Transputer is used as the basic building block of hardware architectures and Occam is used as the programming language. The segmentation methods chosen for implementation are convolution, for edge-based segmentation; the Split and Merge algorithm for segmenting non-textured regions; and the Granlund method for segmentation of textured images. Three different convolution methods have been implemented. The direct method of convolution, carried out in the spatial domain, uses the array architecture. The other two methods, based on convolution in the frequency domain, require the use of the two-dimensional Fourier transform. Parallel implementations of two different Fast Fourier Transform algorithms have been developed, incorporating original solutions. For the Row-Column method the array architecture has been adopted, and for the Vector-Radix method, the pyramid architecture. The texture segmentation algorithm, for which a system-level design is given, demonstrates a further application of the Vector-Radix Fourier transform. A novel concurrent version of the quad-tree based Split and Merge algorithm has been implemented on the pyramid architecture. The performance of the developed parallel implementations is analysed. Many of the obtained speed-up and efficiency measures show values close to their respective theoretical maxima. Where appropriate comparisons are drawn between different implementations. The thesis concludes with comments on general issues related to the use of the Transputer system as a development tool for image processing applications; and on the issues related to the engineering of concurrent image processing applications.