Error processes in the integration of digital cartographic data in geographic information systems.

Errors within a Geographic Information System (GIS) arise from several factors. In the first instance receiving data from a variety of different sources results in a degree of incompatibility between such information. Secondly, the very processes used to acquire the information into the GIS may in fact degrade the quality of the data. If geometric overlay (the very raison d'etre of many GISs) is to be performed, such inconsistencies need to be carefully examined and dealt with. A variety of techniques exist for the user to eliminate such problems, but all of these tend to rely on the geometry of the information, rather than on its meaning or nature. This thesis explores the introduction of error into GISs and the consequences this has for any subsequent data analysis. Techniques for error removal at the overlay stage are also examined and improved solutions are offered. Furthermore, the thesis also looks at the role of the data model and the potential detrimental effects this can have, in forcing the data to be organised into a pre-defined structure

Relation partition algebra — mathematical aspects of uses and part-of relations

AbstractManaging complexity in software engineering involves modularisation, grouping design objects into modules, subsystems, etc. This gives rise to new design objects with new ‘use relations’. The lower-level design objects relate to these in a ‘part-of’ relation. But how do ‘use relations’ at different levels of the ‘part-of hierarchy’ relate? We formalise our knowledge on uses and part-of relations, looking for mathematical laws about relations and partitions. A central role is played by an operator /. For a “uses” relation r on a set of objects X and a partitioning into modules viewed as an equivalence θ, we form a relation rθ on the set Xθ. We adopt an axiomatic point of view and investigate a variety of models, corresponding to different abstraction mechanisms and different ways of relating high- and low-level uses relations

Policies, methods and tools for visitor management proceedings of the second International Conference on Monitoring and Management of Visitor Flows in Recreational and Protected Areas, June 16 20, 2004, Rovaniemi, Finland

The second International Conference on Monitoring and Management of Visitor Flows in recreational and protected areas (MMV 2) -conference provided a forum for research presentations and for exchange of information and experience of managerial policies, problems, practices and solutions regarding issues related to monitoring and management of visitor flows in recreational and protected areas. These proceedings cover ten research topics, which were chosen to reflect current on-going research work internationally in the field of visitor monitoring and management. Monitoring visitor flows and also other types of recreational inventories are discussed in 16 articles and four posters on visitor monitoring methods, experiences of national, regional and on-site visitor inventories and visitor flow modeling and data management. Nineteen papers and three posters are discussing visitor management research from several perspectives. Articles related to issues of visitor conflicts, implementation of visitor information in management processes, different aspects of sustainability and carrying capacity issues in recreational settings make the largest group of papers. The third major subject group of articles (16) deal with visitor management policy issues, and nature tourism policies in recreational and protected areas. The last topics include economic and social impacts of recreation and nature tourism in the surroundings communities, regions and countries

Extracting Information from Spoken User Input:A Machine Learning Approach

We propose a module that performs automatic analysis of user input in spoken dialogue systems using machine learning algorithms. The input to the module is material received from the speech recogniser and the dialogue manager of the spoken dialogue system, the output is a four-level pragmatic-semantic representation of the user utterance. Our investigation shows that when the four interpretation levels are combined in a complex machine learning task, the performance of the module is significantly better than the score of an informed baseline strategy. However, via a systematic, automatised search for the optimal subtask combinations we can gain substantial improvement produced by both classifiers for all four interpretation subtasks. A case study is conducted on dialogues between an automatised, experimental system that gives information on the phone about train connections in the Netherlands, and its users who speak in Dutch. We find that drawing on unsophisticated, potentially noisy features that characterise the dialogue situation, and by performing automatic optimisation of the formulated machine learning task it is possible to extract sophisticated information of practical pragmatic-semantic value from spoken user input with robust performance. This means that our module can with a good score interpret whether the user of the system is giving slot-filling information, and for which query slots (e.g., departure station, departure time, etc.), whether the user gave a positive or a negative answer to the system, or whether the user signals that there are problems in the interaction.

Flood mitigation, model uncertainty and process diagnostics - Bridging the gap between operational practice and research

This dissertation is about flood mitigation, model uncertainty and process diagnostics. I develop and apply methods relevant for reservoir operation and flood forecasting, I introduce pattern matching procedures for streamflow time series and I analyze a comprehensive environmental dataset with regard to catchment runoff production

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

Statistical Modelling

The book collects the proceedings of the 19th International Workshop on Statistical Modelling held in Florence on July 2004. Statistical modelling is an important cornerstone in many scientific disciplines, and the workshop has provided a rich environment for cross-fertilization of ideas from different disciplines. It consists in four invited lectures, 48 contributed papers and 47 posters. The contributions are arranged in sessions: Statistical Modelling; Statistical Modelling in Genomics; Semi-parametric Regression Models; Generalized Linear Mixed Models; Correlated Data Modelling; Missing Data, Measurement of Error and Survival Analysis; Spatial Data Modelling and Time Series and Econometrics

Maine State Government Administrative Report 1986-1987

https://digitalmaine.com/me_annual_reports/1013/thumbnail.jp