Deposits of clastic carbonate-dominated (calciclastic) sedimentary slope systems in the rock record have been identified mostly as linearly-consistent carbonate apron deposits, even though most ancient clastic carbonate slope deposits fit the submarine fan systems better. Calciclastic submarine fans are consequently rarely described and are poorly understood. Subsequently, very little is known especially in mud-dominated calciclastic submarine fan systems. Presented in this study are a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) that reveals a >250 m thick calciturbidite complex deposited in a calciclastic submarine fan setting. Seven facies are recognised from core and thin section characterisation and are grouped into three carbonate turbidite sequences. They include: 1) Calciturbidites, comprising mostly of highto low-density, wavy-laminated bioclast-rich facies; 2) low-density densite mudstones which are characterised by planar laminated and unlaminated muddominated facies; and 3) Calcidebrites which are muddy or hyper-concentrated debrisflow deposits occurring as poorly-sorted, chaotic, mud-supported floatstones. These

Phd by thesis

Data Mining Practical Machine Learning Tools and Techniques

Learning Vocabulary in Another Language: Appendixes

Current approaches to the development of natural language dialogue systems are discussed, and it is claimed that they do not sufficiently consider the unique qualities of man-machine interaction as distinct from general human discourse. It is concluded that empirical studies of this unique communication situation are required for the development of user-friendly interactive systems. One way of achieving this is through the use of so-called Wizard of Oz studies. The focus of the work described in the paper is on the practical execution of the studies and the methodological conclusions drawn on the basis of the authors' experience. While the focus is on natural language interfaces, the methods used and the conclusions drawn from the results obtained are of relevance also to other kinds of intelligent interfaces.

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Wizard of Oz studies: why and how

Social intelligence in robots has a quite recent history in artificial intelligence and robotics. However, it has become increasingly apparent that social and interactive skills are necessary requirements in many application areas and contexts where robots need to interact and collaborate with other robots or humans. Research on human–robot interaction (HRI) poses many challenges regarding the nature of interactivity and ‘social behaviour’ in robot and humans. The first part of this paper addresses dimensions of HRI, discussing requirements on social skills for robots and introducing the conceptual space of HRI studies. In order to illustrate these concepts, two examples of HRI research are presented. First, research is surveyed which investigates the development of a cognitive robot companion. The aim of this work is to develop social rules for robot behaviour (a ‘robotiquette’) that is comfortable and acceptable to humans. Second, robots are discussed as possible educational or therapeutic toys for children with autism. The concept of interactive emergence in human–child interactions is highlighted. Different types of play among children are discussed in the light of their potential investigation in human–robot experiments. The paper concludes by examining different paradigms regarding ‘social relationships’ of robots and people interacting with them.

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Socially intelligent robots: dimensions of human-robot interaction.

When developing natural language interfaces, it is important to know the characteristics of the language used. We have developed a set of tools for conducting human-computer natural language dialogue simulations (Wizard of Oz experiments) and for analyzing the data obtained. We report methods used and results obtained from a series of such experiments. The focus of the study was on occasional users and on the structure of the dialogue. Three different background systems were used; one database and two advisory systems of different complexity. The results point to the need for mechanisms for handling connected discourse in interfaces for this user group. They also indicate that there are different classes of dialogue situations requiring discourse representations of different computational complexity.

Talking to a Computer Is Not like Talking to Your Best Friend.

This paper presents a study where Augmented Reality (AR) technology has been used as a tool for supporting collaboration between the rescue services, the police and military personnel in a crisis management scenario. There are few studies on how AR systems should be designed to improve cooperation between actors from different organizations while at the same time support individual needs. In the present study an AR system was utilized for supporting joint planning tasks by providing organisation-specific views of a shared working. The study involved a simulated emergency event conducted in close to real settings with representatives from the organisations for which the system is developed. As a baseline, a series of trials without the AR system was carried out. Results show that the users were positive towards the AR system, and would like to use it in real work. They also experience some performance benefits of using the AR system compared to their traditional tools. Finally, the problem of designing for collaborative work as well as the benefits of using an iterative design processes is discussed.

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Using AR to support cross-organisational collaboration in dynamic tasks

We present the results from a series of experiments aimed at uncovering the discourse structure of man-machine communication in natural language (Wizard of Oz experiments). The results suggest the existence of different classes of dialogue situations, requiring computational discourse representations of various complexity. Important factors seem to be the number of different permissible tasks in the system and to what extent the system takes initiative in the dialogue. We also analyse indexical expressions and especially the use of pronouns, and suggest a psychological explanation of their restricted occurrence in these types of dialogues.

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Empirical studies of discourse representations for natural language interfaces

Natural language interfaces require dialogue models that allow for robust, habitable and efficient interaction. This paper presents such a model for dialogue management for natural language interfaces. The model is based on empirical studies of human computer interaction in various simple service applications. It is shown that for applications belonging to this class the dialogue can be handled using fairly simple means. The interaction can be modeled in a dialogue grammar with information on the functional role of an utterance as conveyed in the linguistic structure. Focusing is handled using dialogue objects recorded in a dialogue tree representing the constituents of the dialogue. The dialogue objects in the dialogue tree can be accessed by the various modules for interpretation, generation and background system access. Focused entities are modeled in entities pertaining to objects or sets of objects, and related domain concept information; properties of the domain objects. A simple copying principle, where a new dialogue object's focal parameters are instantiated with information from the preceding dialogue object, accounts for most context dependent utterances. The action to be carried out by the interface is determined on the basis of how the objects and related properties are specified. This in turn depends on information presented in the user utterance, context information from the dialogue tree and information in the domain model. The use of dialogue objects facilitates customization to the sublanguage utilized in a specific application. The framework has successfully been applied to various background systems and interaction modalities. In the paper results from the customization of the dialogue manager to three typed interaction applications are presented together with results from applying the model to two applications utilizing spoken interaction.

/pdf/a-model-for-habitable-and-efficient-dialogue-management-for-4snb6wezvp.pdf

Arne Jönsson

Papers

Wizard of Oz studies: why and how

Talking to a Computer Is Not like Talking to Your Best Friend.

Using AR to support cross-organisational collaboration in dynamic tasks

Empirical studies of discourse representations for natural language interfaces

A model for habitable and efficient dialogue management for natural language interaction