Talbot-like bands for a laser diode below threshold

We report on the problems encountered when replacing a tungsten filament lamp with a laser diode in a set-up for displaying Talbot bands using a diffraction grating. It is shown that the band pattern is rather complex and strong interference signals may exist in situations where Talbot bands are not normally expected to appear. In these situations, the period of the bands increases with the optical path difference (OPD). The visibility of bands as dependence on path imbalance is obtained by suitably obstructing halfway into the arms of a Michelson interferometer using opaque screens.

Distributed temperature sensor based on Brillouin loss in an optical fibre for transient threshold monitoring

A distributed temperature sensor for transient threshold monitoring with a 22 km sensing length, based on the Brillouin loss in standard communications fibre, is demonstrated. The system can be used for real-time monitoring of a preset temperature threshold. Good S/N ratios were achieved with only 8–16 sample averages giving a response time of 2 to 4 s with a temperature uncertainty of ±1 °C.

Evolution of competing strategies in a threshold model for task allocation

A nature inspired decentralised multi-agent algorithm is proposed to solve a problem of distributed task allocation in which cities produce and store batches of different mail types. Agents must collect and process the mail batches, without global knowledge of their environment or communication between agents. The problem is constrained so that agents are penalised for switching mail types. When an agent process a mail batch of different type to the previous one, it must undergo a change-over, with repeated change-overs rendering the agent inactive. The efficiency (average amount of mail retrieved), and the flexibility (ability of the agents to react to changes in the environment) are investigated both in static and dynamic environments and with respect to sudden changes. New rules for mail selection and specialisation are proposed and are shown to exhibit improved efficiency and flexibility compared to existing ones. We employ a evolutionary algorithm which allows the various rules to evolve and compete. Apart from obtaining optimised parameters for the various rules for any environment, we also observe extinction and speciation.

Overcoming network overload and redundancy in inter-organizational networks:the roles of potential and latent ties

This paper builds on Granovetter's distinction between strong and weak ties [Granovetter, M. S. 1973. The strength of weak ties. Amer. J. Sociol. 78(6) 1360–1380] in order to respond to recent calls for a more dynamic and processual understanding of networks. The concepts of potential and latent tie are deductively identified, and their implications for understanding how and why networks emerge, evolve, and change are explored. A longitudinal empirical study conducted with companies operating in the European motorsport industry reveals that firms take strategic actions to search for potential ties and reactivate latent ties in order to solve problems of network redundancy and overload. Examples are given, and their characteristics are examined to provide theoretical elaboration of the relationship between the types of tie and network evolution. These conceptual and empirical insights move understanding of the managerial challenge of building effective networks beyond static structural contingency models of optimal network forms to highlight the processes and capabilities of dynamic relationship building and network development. In so doing, this paper highlights the interrelationship between search and redundancy and the scope for strategic action alongside path dependence and structural influences on network processes.

The influence of memory in a threshold model for distributed task assignment

A nature inspired decentralised multi-agent algorithm is proposed to solve a problem of distributed task selection in which cities produce and store batches of different mail types. Agents must collect and process the mail batches, without a priori knowledge of the available mail at the cities or inter-agent communication. In order to process a different mail type than the previous one, agents must undergo a change-over during which it remains inactive. We propose a threshold based algorithm in order to maximise the overall efficiency (the average amount of mail collected). We show that memory, i.e. the possibility for agents to develop preferences for certain cities, not only leads to emergent cooperation between agents, but also to a significant increase in efficiency (above the theoretical upper limit for any memoryless algorithm), and we systematically investigate the influence of the various model parameters. Finally, we demonstrate the flexibility of the algorithm to changes in circumstances, and its excellent scalability.

LRD : Latent Relation Discovery for vector space expansion and information retrieval

In this paper, we propose a text mining method called LRD (latent relation discovery), which extends the traditional vector space model of document representation in order to improve information retrieval (IR) on documents and document clustering. Our LRD method extracts terms and entities, such as person, organization, or project names, and discovers relationships between them by taking into account their co-occurrence in textual corpora. Given a target entity, LRD discovers other entities closely related to the target effectively and efficiently. With respect to such relatedness, a measure of relation strength between entities is defined. LRD uses relation strength to enhance the vector space model, and uses the enhanced vector space model for query based IR on documents and clustering documents in order to discover complex relationships among terms and entities. Our experiments on a standard dataset for query based IR shows that our LRD method performed significantly better than traditional vector space model and other five standard statistical methods for vector expansion.

Multi-level visualisation using Gaussian process latent variable models

Projection of a high-dimensional dataset onto a two-dimensional space is a useful tool to visualise structures and relationships in the dataset. However, a single two-dimensional visualisation may not display all the intrinsic structure. Therefore, hierarchical/multi-level visualisation methods have been used to extract more detailed understanding of the data. Here we propose a multi-level Gaussian process latent variable model (MLGPLVM). MLGPLVM works by segmenting data (with e.g. K-means, Gaussian mixture model or interactive clustering) in the visualisation space and then fitting a visualisation model to each subset. To measure the quality of multi-level visualisation (with respect to parent and child models), metrics such as trustworthiness, continuity, mean relative rank errors, visualisation distance distortion and the negative log-likelihood per point are used. We evaluate the MLGPLVM approach on the ‘Oil Flow’ dataset and a dataset of protein electrostatic potentials for the ‘Major Histocompatibility Complex (MHC) class I’ of humans. In both cases, visual observation and the quantitative quality measures have shown better visualisation at lower levels.

Distributed temperature sensor based on Brillouin loss in an optical fibre for transient threshold monitoring

A distributed temperature sensor for transient threshold monitoring with a 22 km sensing length, based on the Brillouin loss in standard communications fibre, is demonstrated. The system can be used for real-time monitoring of a preset temperature threshold. Good S/N ratios were achieved with only 8–16 sample averages giving a response time of 2 to 4 s with a temperature uncertainty of ±1 °C.

Theoretical study of Talbot-like bands observed using a laser diode below threshold

We report on a theoretical study of an interferometric system in which half of a collimated beam from a broadband optical source is intercepted by a glass slide, the whole beam subsequently being incident on a diffraction grating and the resulting spectrum being viewed using a linear CCD array. Using Fourier theory, we derive the expression of the intensity distribution across the CCD array. This expression is then examined for non-cavity and cavity sources for different cases determined by the direction from which the slide is inserted into the beam and the source bandwidth. The theoretical model shows that the narrower the source linewidth, the higher the deviation of the Talbot bands' visibility (as it is dependent on the path imbalance) from the previously known triangular shape. When the source is a laser diode below threshold, the structure of the CCD signal spectrum is very complex. The number of components present simultaneously increases with the number of grating lines and decreases with the laser cavity length. The model also predicts the appearance of bands in situations not usually associated with Talbot bands.

Talbot-like bands for a laser diode below threshold

We report on the problems encountered when replacing a tungsten filament lamp with a laser diode in a set-up for displaying Talbot bands using a diffraction grating. It is shown that the band pattern is rather complex and strong interference signals may exist in situations where Talbot bands are not normally expected to appear. In these situations, the period of the bands increases with the optical path difference (OPD). The visibility of bands as dependence on path imbalance is obtained by suitably obstructing halfway into the arms of a Michelson interferometer using opaque screens.

Semisupervised learning of hierarchical latent trait models for data visualization

Recently, we have developed the hierarchical Generative Topographic Mapping (HGTM), an interactive method for visualization of large high-dimensional real-valued data sets. In this paper, we propose a more general visualization system by extending HGTM in three ways, which allows the user to visualize a wider range of data sets and better support the model development process. 1) We integrate HGTM with noise models from the exponential family of distributions. The basic building block is the Latent Trait Model (LTM). This enables us to visualize data of inherently discrete nature, e.g., collections of documents, in a hierarchical manner. 2) We give the user a choice of initializing the child plots of the current plot in either interactive, or automatic mode. In the interactive mode, the user selects "regions of interest," whereas in the automatic mode, an unsupervised minimum message length (MML)-inspired construction of a mixture of LTMs is employed. The unsupervised construction is particularly useful when high-level plots are covered with dense clusters of highly overlapping data projections, making it difficult to use the interactive mode. Such a situation often arises when visualizing large data sets. 3) We derive general formulas for magnification factors in latent trait models. Magnification factors are a useful tool to improve our understanding of the visualization plots, since they can highlight the boundaries between data clusters. We illustrate our approach on a toy example and evaluate it on three more complex real data sets. © 2005 IEEE.

Effects of dynamic strain ageing on fatigue crack propagation and threshold behaviour in a Ni-base superalloy

In the temperature range 200-400 degree C the Ni-base superalloy, N901, develops marked dynamic strain ageing effects in its tensile behavior. These include inverse strain rate sensitivity, especially in UTS values, strongly serrated stress-strain curves and a heavily sheared failure mode at the higher test-temperatures. As for steels these effects seem to be due to interactions between the dislocations and the interstitial carbon atoms present. The results of tensile and fatigue threshold tests carried out between 20 degree C and 420 degree C are reported and the fatigue behavior is discussed in terms of the effects of surface roughness induced closure, temperature and strain aging interactions.

Residual stress effects during near-threshold fatigue crack growth

The fatigue crack propagation behaviour of a low alloy, boron-containing steel has been examined after austenitizing at 900°C or 1250°C and tempering at a range of temperatures up to 400°C. Fatigue threshold values were found to vary with austenitizing and tempering treatment in a range between 3.3 to 6 MPa √m when tested at a stress ratio (R) of 0.2. Crack propagation rates in the Paris regime were insensitive to heat treatment variations. The crack propagation path was essentially transgranular in all conditions with small regions of intergranular facets appearing at growth rates around the knee of the da/dN vs ΔK curve. The crack front shape showed marked retardation in the centre of the specimen at low tempering temperatures. Experimental determinations and computer predictions of residual stress levels in the specimens indicated that this was due to a central residual compressive stress resulting from differential cooling rates and the volume change associated with the martensite transformation. The results are discussed in terms of microstructural and residual stress effects on fatigue behaviour. © 1987.