Minimum spanning trees for valley and ridge characterization in digital elevation maps

Texture synthesis employs neighbourhood matching to generate appropriate new content. Terrain synthesis has the added constraint that new content must be geographically plausible. The profile recognition and polygon breaking algorithm (PPA) [Chang et al. 1998] provides a robust mechanism for characterizing terrain as systems of valley and ridge lines in digital elevation maps. We exploit this to create a terrain characterization metric that is robust, efficient to compute and is sensitive to terrain properties.

Terrain regions are characterized as a minimum spanning tree derived from a graph created from the sample points of the elevation map which are encoded as weights in the edges of the graph. This formulation allows us to provide a single consistent feature definition that is sensitive to the pattern of ridges and valleys in the terrain Alternative formulations of these weights provide richer characteristicmeasures and we provide examples of alternate definitions based on curvature and contour measures.

We show that the measure is robust, with a significant portion derived directly from information local to the terrain sample. Global terrain characteristics introduce the issue of over- and underconnected valley/ridge lines when working with sub-regions. This is addressed by providing two graph construction strategies, which respectively provide an upper bound on connectivity as a single spanning tree, and a lower bound as a forest of trees.

Efficient minimum spanning tree algorithms are adapted to the context of terrain data and are shown to provide substantially better performance than previous PPA implementations. In particular, these are able to characterize valley and ridge behaviour at every point even in large elevation maps, providing a measure sensitive to terrain features at all scales.

The resulting graph based formulation provides an efficient and elegant algorithm for characterizing terrain features. The measure can be calculated efficiently, is robust under changes of neighbourhood position, size and resolution and the hybrid measure is sensitive to terrain features both locally and globally.

A unified formalism for landmark based representation of maps and navigation plans

We present a unified formalism for representing maps and using them for constructing plans of navigation for an autonomous agent. The foundation of this work lies in addressing key questions that an agent is confronted with when navigating. That is, besides the main task of how to reach the intended destination from the current position, the agent faces other questions like: where am I? what landmarks can I see? where is my destination relative to me and the landmarks I am seeing? Fundamental to this representation is the use of visual landmarks, which are used as pivotal points in the landscape being described. Further, in the representation of spatial information and navigation there are three different viewpoints: first, the localized representation from the viewpoint of a sighted, mobile agent; second, the static representation seen by the map-maker; and third, the view of an external agent giving directions on the basis of his own experience/knowledge. The major contribution of this map model and the associated navigation method lies in the framework which unifies these three different points of view. This unification enables the agent to make no distinction in terms of following implicit instructions contained in a map and the directions given by external agents.

Reliability maps and probabilistic guarantee of task motion for robotic manipulators

There are many applications for which reliable and safe robots are desired. For example, assistant robots for disabled or elderly people and surgical robots are required to be safe and reliable to prevent human injury and task failure. However, different levels of safety and reliability are required for different tasks so that understanding the reliability of robots is paramount. Currently, it is possible to guarantee the completion of a task when the robot is fault tolerant and the task remains in the fault-tolerant workspace (FTW). The traditional definition of FTW does not consider different reliabilities for the robotic manipulator's different joints. The aim of this paper is to extend the concept of a FTW to address the reliability of different joints. Such an extension can offer a wider FTW while maintaining the required level of reliability. This is achieved by associating a probability with every part of the workspace to extend the FTW. As a result, reliable fault-tolerant workspaces (RFTWs) are introduced by using the novel concept of conditional reliability maps. Such a RFTW can be used to improve the performance of assistant robots while providing the confidence that the robot remains reliable for completion of its assigned tasks. © 2012 Copyright Taylor & Francis and The Robotics Society of Japan.

Institutional environment, innovation capacity and firm performance in Russia

Purpose – Following the demise of the Soviet Union in 1992, Russia undertook major institutional and market-oriented reforms to enhance the competitive advantage of domestic enterprises. Although Russia has experienced rapid growth over the last two decades, the extent to which institutions in Russia impact on firm innovation and performance remains poorly understood due to a lack of research on the subject. This paper seeks to contribute to the literature on the competitiveness of Russian firms by focussing specifically on the extent to which the state of the regulatory quality, rule of law, and corruption affect the innovation capacity and performance of firms in Russia.

Design/methodology/approach – The study uses structural equation modelling and data from a large-scale firm level survey (n=787) of firms in Russia undertaken by the World Bank in 2009. It investigates the direct and indirect perceptions of respondents of the effects the current institutional environment has on the innovation capacity and performance of their respective organisations.

Findings – The results show that regulatory quality, rule of law and corruption have strong direct and negative impacts on both the innovation capacity and performance of firms, and that innovation capacity strongly mediates the effects of institutions on firm performance. The results suggest that the current state of the regulatory quality, rule of law and corruption in Russia inhibit firm innovation and their resulting performance.

Research limitations/implications – The findings should be interpreted with caution to the extent that the study is limited to only three elements of the formal institutional environment and does not take into consideration the role of informal institutions. These two limitations present avenues for future research.

Originality/value – The study is one of the first to provide empirical evidence based on a large-scale survey of the extent to which formal institutions inhibit innovation and firm performance in Russia, and provides valuable guidance to business policy-makers in Russia on possible avenues for enhancing the overall competitiveness of Russian firms.

Quantitative experimental comparison of single-beam, sidescan, and multibeam benthic habitat maps

Map comparison is a relatively uncommon practice in acoustic seabed classification to date, contrary to the field of land remote sensing, where it has been developed extensively over recent decades. The aim here is to illustrate the benefits of map comparison in the underwater realm with a case study of three maps independently describing the seabed habitats of the Te Matuku Marine Reserve (Hauraki Gulf, New Zealand). The maps are obtained from a QTC View classification of a single-beam echosounder (SBES) dataset, manual segmentation of a sidescan sonar (SSS) mosaic, and automatic classification of a backscatter dataset from a multibeam echosounder (MBES). The maps are compared using pixel-to-pixel similarity measures derived from the literature in land remote sensing. All measures agree in presenting the MBES and SSS maps as the most similar, and the SBES and SSS maps as the least similar. The results are discussed with reference to the potential of MBES backscatter as an alternative to SSS mosaic for imagery segmentation and to the potential of joint SBES–SSS survey for improved habitat mapping. Other applications of map-similarity measures in acoustic classification of the seabed are suggested.

Analysing stillbirth data using dynamic self organizing maps

Even with the presence of modern obstetric care, stillbirth rate seems to stay stagnant or has even risen slightly in countries such as England and has become a significant public health concern [1]. In the light of current medical research, maternal risk factors such as diabetes and hypertensive disease were identified as possible risk factors and are taken into consideration in antenatal care. However, medical practitioners and researchers suspect possible relationships between trends in maternal demographics, antenatal care and pregnancy information of current stillbirth in consideration [2]. Although medical data and knowledge is available appropriate computing techniques to analyze the data may lead to identification of high risk groups. In this paper we use an unsupervised clustering technique called Growing Self organizing Map (GSOM) to analyse the stillbirth data and present patterns which can be important to medical researchers.