Empirical evidence for ultrametric structure in multi-layer perceptron error surfaces

Combinatorial optimization problems share an interesting property with spin glass systems in that their state spaces can exhibit ultrametric structure. We use sampling methods to analyse the error surfaces of feedforward multi-layer perceptron neural networks learning encoder problems. The third order statistics of these points of attraction are examined and found to be arranged in a highly ultrametric way. This is a unique result for a finite, continuous parameter space. The implications of this result are discussed.

Actively shielded multi-layer gradient coil designs with improved cooling properties

In standard cylindrical gradient coils consisting of a single layer of wires, a limiting factor in achieving very large magnetic field gradients is the rapid increase in coil resistance with efficiency. This is a particular problem in small-bore scanners, such as those used for MR microscopy. By adopting a multi-layer design in which the coil wires are allowed to spread out into multiple layers wound at increasing radii, a more favourable scaling of resistance with efficiency is achieved, thus allowing the design of more powerful gradient coils with acceptable resistance values. Previously this approach has been applied to the design of unshielded, longitudinal, and transverse gradient coils. Here, the multi-layer approach has been extended to allow the design of actively shielded multi-layer gradient coils, and also to produce coils exhibiting enhanced cooling characteristics. An iterative approach to modelling the steady-state temperature distribution within the coil has also been developed. Results indicate that a good level of screening can be achieved in multi-layer coils, that small versions of such coils can yield higher efficiencies at fixed resistance than conventional two-layer (primary and screen) coils, and that performance improves as the number of layers of increases. Simulations show that by optimising multi-layer coils for cooling it is possible to achieve significantly higher gradient strengths at a fixed maximum operating temperature. A four-layer coil of 8 mm inner diameter has been constructed and used to test the steady-state temperature model. (C) 2003 Elsevier Inc. All rights reserved.

Microstructure of MmM(5)/Mg multi-layer hydrogen storage films prepared by magnetron sputtering

Multi-layer hydrogen storage thin films with Mg and MmNi(3.5)(CoAlMn)(1.5) (here Mm denotes La-rich mischmetal) as alternative layers were prepared by direct current magnetron sputtering. Transmission electron microscopy investigation shows that the microstructure of the MmNi(3.5)(CoAlMn)(1.5) and Mg layers are significantly different although their deposition conditions are the same. The MmNi(3.5)(CoAlMn)(1.5) layer is composed of two regions: one is an amorphous region approximately 4 nm thick at the bottom of the layer and the other is a nanocrystalline region on top of the amorphous region. The Mg layer is also composed of two regions: one is a randomly orientated nanocrystalline region 50 nm thick at the bottom of the layer and the other is a columnar crystallite region on top of the nanocrystalline region. These Mg columnar crystallites have their [001] directions parallel to the growth direction and the average lateral size of these columnar crystallites is about 100 nm. A growth mechanism of the multi-layer thin films is discussed based on the experiment results. Wiley-Liss, Inc.

Microstructure of MmM(5)/Mg multi-layer films prepared by magnetron sputtering

Microstructure of MmNi(3.5)(CoAlMn)(1.5)/Mg (here Mm denotes La-rich mischmetal) multi-layer hydrogen storage thin films prepared by direct current magnetron sputtering was investigated by cross-sectional transmission electron microscopy (XTEM). It was shown that the MMM5 layers are composed of two regions: an amorphous region with a thickness of similar to 4nm at the bottom of the layers and a randomly orientated nanocrystallite region on the top of the amorphous region and the Mg layers consist of typical columnar crystallite with their [001] direction nearly parallel to the growth direction. The mechanism for the formation of the above microstructure characteristics in the multi-layer thin films has been proposed. Based on the microstructure feature of the multi-layer films, mechanism for the apparent improvement of hydrogen absorption/desorption kinetics was discussed. (c) 2005 Elsevier B.V. All rights reserved.

The network structure of a regional tourism organization: Application of he social network theory in one region of Queensland

Regional tourism organizations (RTOs) plays a central role in planning, coordinating and marketing tourism in many areas, including Queensland, Australia. RTOs rely on interaction with a network of other organizations for their efficient functioning. This paper describes an exploratory case study that develops a method for use of social network analysis techniques to analyse the inter-organizational network in one RTO region in Queensland. Results indicate that differences exist in the structure of inter-organizational links between commercial tourism organizations and planning organizations, between tourism organizations and other sectoral clusters, and between organizations at local, regional and state levels. The results highlight areas or improvement in the role and responsibilities of RTOs in Queensland.

A probabilistic switch model of information flow in social networks: Application for virtual circuits to organizational design

Network building and exchange of information by people within networks is crucial to the innovation process. Contrary to older models, in social networks the flow of information is noncontinuous and nonlinear. There are critical barriers to information flow that operate in a problematic manner. New models and new analytic tools are needed for these systems. This paper introduces the concept of virtual circuits and draws on recent concepts of network modelling and design to introduce a probabilistic switch theory that can be described using matrices. It can be used to model multistep information flow between people within organisational networks, to provide formal definitions of efficient and balanced networks and to describe distortion of information as it passes along human communication channels. The concept of multi-dimensional information space arises naturally from the use of matrices. The theory and the use of serial diagonal matrices have applications to organisational design and to the modelling of other systems. It is hypothesised that opinion leaders or creative individuals are more likely to emerge at information-rich nodes in networks. A mathematical definition of such nodes is developed and it does not invariably correspond with centrality as defined by early work on networks.

Development and evaluation of neural network freeway incident detection models using field data

This paper discusses a multi-layer feedforward (MLF) neural network incident detection model that was developed and evaluated using field data. In contrast to published neural network incident detection models which relied on simulated or limited field data for model development and testing, the model described in this paper was trained and tested on a real-world data set of 100 incidents. The model uses speed, flow and occupancy data measured at dual stations, averaged across all lanes and only from time interval t. The off-line performance of the model is reported under both incident and non-incident conditions. The incident detection performance of the model is reported based on a validation-test data set of 40 incidents that were independent of the 60 incidents used for training. The false alarm rates of the model are evaluated based on non-incident data that were collected from a freeway section which was video-taped for a period of 33 days. A comparative evaluation between the neural network model and the incident detection model in operation on Melbourne's freeways is also presented. The results of the comparative performance evaluation clearly demonstrate the substantial improvement in incident detection performance obtained by the neural network model. The paper also presents additional results that demonstrate how improvements in model performance can be achieved using variable decision thresholds. Finally, the model's fault-tolerance under conditions of corrupt or missing data is investigated and the impact of loop detector failure/malfunction on the performance of the trained model is evaluated and discussed. The results presented in this paper provide a comprehensive evaluation of the developed model and confirm that neural network models can provide fast and reliable incident detection on freeways. (C) 1997 Elsevier Science Ltd. All rights reserved.