Designing XML documents from conceptual schemas and workload information

Due to the increase of XML-based applications, XML schema design has become an important task. One approach is to consider conceptual schemas as a basis for generating XML documents compliant to consensual information of specific domains. However, the conversion of conceptual schemas to XML schemas is not a straightforward process and inconvenient design decisions can lead to a poor query processing on XML documents generated. This paper presents a conversion approach which considers data and query workload estimated for XML applications, in order to generate an XML schema from a conceptual schema. Load information is used to produce XML schemas which can respond well to the main queries of an XML application. We evaluate our approach through a case study carried out on a native XML database. The experimental results demonstrate that the XML schemas generated by our methodology contribute to a better query performance than related approaches.

An Application of Advanced Spatio-Temporal Formalisms to Behavioural Ecology

There is great potential for the development of many new applications using data on mobile objects and mobile regions. To promote these kinds of applications advanced data management techniques for the representation and analysis of mobility-related data are needed. Together with application experts (behavioural ecologists), we investigate how two novel data management approaches may help. We focus on a case study concerning the analysis of fauna behaviour, in particular crested porcupines, which represents a typical example of mobile object monitoring. The first technique we experiment with is a recently developed conceptual spatio-temporal data modelling approach, MADS. This is used to model the schema of the database suited to our case study. Relying on this first outcome a subset of the problem is represented in the logical language MuTACLP. This allows us to formalise and solve the queries which enable the behavioural ecologists to derive crested porcupines behaviour from the raw data on animal movements. Finally, we investigate the support from a commercial Geographic Information System (GIS) for the analysis of spatio-temporal data. We present a way to integrate MuTACLP and a GIS, combining the advantages of GIS technology and the expressive power of MuTACLP.

Variable-resolution Compression of Vector Data

The compression of spatial data is a promising solution to reduce the space of data storage and to decrease the transmission time of spatial data over the Internet. This paper proposes a new method for variable-resolution compression of vector data. Three key steps are encompassed in the proposed method, namely, the simplification of vector data via the elimination of vertices, the compression of removed vertices, and the decoding of the compressed vector data. The proposed compression method was implemented and applied to compress vector data to investigate its performance in terms of the compression ratio, distortions of geometric shapes. The results show that the proposed method provides a feasible and efficient solution for the compression of vector data, is able to achieve good compression ratios and maintains the main shape characteristics of the spatial objects within the compressed vector data.

Multicriteria Spatial Decision Analysis in Web GIS Environment

Internet, a client/server system, is a perfect means of GIS data accessing, analyzing and transmission. The World Wide Web, FTP (file transfer protocol) and HTTP programs make it convenient to access and transfer data files across the Internet. Using Internet for GIS makes it easy access to acquire GIS data from diverse data sources in the distributed environment. The geospatial multicriteria decision analysis in a client/server environment is an important and challenging task for the GIS community because of narrow Internet bandwidth for large geospatial data sets. In the present paper, we are developing a multicriteria decision analysis tool for spatial decision making in the web GIS environment. The developed system has been demonstrated for biodiversity conservation and priorities. An attempt has been made to generate the alternative decisions based on priority vectors. The multicriteria technique of Analytic Hierarchy Process (AHP) is used to derive the eigen vectors with the given multiple constraints of conflicting criteria and aims at selecting optimal alternative from the available sets. However, the evaluation recognizes the importance of expert knowledge when assigning the weights for the best spatial priorities. Comparing within classes and alternatives using judgment and decision matrix is based on Saaty’s Pairwise Comparison. The Multicriteria Spatial Decision Support System (MC-SDSS) software development uses ASP, ArcIMS 9.0, ArcSDE9.0 and Oracle 9i data server in the web GIS environment. The database organization of spatial and non-spatial data is done in the RDBMS environment using ArcSDE and Oracle 9i data server.

Clustering multidimensional sequences in spatial and temporal databases

Many environmental, scientific, technical or medical database applications require effective and efficient mining of time series, sequences or trajectories of measurements taken at different time points and positions forming large temporal or spatial databases. Particularly the analysis of concurrent and multidimensional sequences poses new challenges in finding clusters of arbitrary length and varying number of attributes. We present a novel algorithm capable of finding parallel clusters in different subspaces and demonstrate our results for temporal and spatial applications. Our analysis of structural quality parameters in rivers is successfully used by hydrologists to develop measures for river quality improvements.

Ethical regulations on robotics in Europe

There are only a few ethical regulations that deal explicitly with robots, in contrast to a vast number of regulations, which may be applied. We will focus on ethical issues with regard to “responsibility and autonomous robots”, “machines as a replacement for humans”, and “tele-presence”. Furthermore we will examine examples from special fields of application (medicine and healthcare, armed forces, and entertainment). We do not claim to present a complete list of ethical issue nor of regulations in the field of robotics, but we will demonstrate that there are legal challenges with regard to these issues.

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ONTRACK: Dynamically adapting music playback to support navigation

Listening to music on personal, digital devices whilst mobile is an enjoyable, everyday activity. We explore a scheme for exploiting this practice to immerse listeners in navigation cues. Our prototype, ONTRACK, continuously adapts audio, modifying the spatial balance and volume to lead listeners to their target destination. First we report on an initial lab-based evaluation that demonstrated the approach’s efficacy: users were able to complete tasks within a reasonable time and their subjective feedback was positive. Encouraged by these results we constructed a handheld prototype. Here, we discuss this implementation and the results of field-trials. These indicate that even with a low-fidelity realisation of the concept, users can quite effectively navigate complicated routes.

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A Multi-Agent Model and Tabu Search Optimization to Manage Agricultural Territories

This paper proposes a multi-agent model to manage agricultural territories in order to reduce damage caused by runoff and floods processes. The proposed approach consists in optimizing the distribution of crops in a territory based on a multi-agent optimization approach. A group of agents represents each type of crop. The objective of an agent group is to occupy a total surface of parcels to achieve its objectives of production while reducing the value of risk for the whole watershed. Some agronomic, economic and hydrologic constraints restrict the behavior of agents and must be satisfied during the optimization process. The value of runoff risk is evaluated by a spatial hydrological model at the level of the Digital Terrain Model. Three optimization strategies based on Tabu search are developed and tested using real data. They provide satisfactory solutions in various computation times.

The 2007 IEEE CEC simulated car racing competition

This paper describes the simulated car racing competition that was arranged as part of the 2007 IEEE Congress on Evolutionary Computation. Both the game that was used as the domain for the competition, the controllers submitted as entries to the competition and its results are presented. With this paper, we hope to provide some insight into the efficacy of various computational intelligence methods on a well-defined game task, as well as an example of one way of running a competition. In the process, we provide a set of reference results for those who wish to use the simplerace game to benchmark their own algorithms. The paper is co-authored by the organizers and participants of the competition.

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Handheld Augmented Reality for underground infrastructure visualization

In this paper, we present an Augmented Reality (AR) system for aiding field workers of utility companies in outdoor tasks such as maintenance, planning or surveying of underground infrastructure. Our work addresses these issues using spatial interaction and visualization techniques for mobile AR applications and as well as for a new mobile device design. We also present results from evaluations of the prototype application for underground infrastructure spanning various user groups. Our application has been driven by feedback from industrial collaborators in the utility sector, and includes a translation tool for automatically importing data from utility company databases of underground assets.

On Detecting Spatial Outliers

The ever-increasing volume of spatial data has greatly challenged our ability to extract useful but implicit knowledge from them. As an important branch of spatial data mining, spatial outlier detection aims to discover the objects whose non-spatial attribute values are significantly different from the values of their spatial neighbors. These objects, called spatial outliers, may reveal important phenomena in a number of applications including traffic control, satellite image analysis, weather forecast, and medical diagnosis. Most of the existing spatial outlier detection algorithms mainly focus on identifying single attribute outliers and could potentially misclassify normal objects as outliers when their neighborhoods contain real spatial outliers with very large or small attribute values. In addition, many spatial applications contain multiple non-spatial attributes which should be processed altogether to identify outliers. To address these two issues, we formulate the spatial outlier detection problem in a general way, design two robust detection algorithms, one for single attribute and the other for multiple attributes, and analyze their computational complexities. Experiments were conducted on a real-world data set, West Nile virus data, to validate the effectiveness of the proposed algorithms.

Methods for quantitative usability requirements: a case study on the development of the user interface of a mobile phone

Quantitative usability requirements are a critical but challenging, and hence an often neglected aspect of a usability engineering process. A case study is described where quantitative usability requirements played a key role in the development of a new user interface of a mobile phone. Within the practical constraints of the project, existing methods for determining usability requirements and evaluating the extent to which these are met, could not be applied as such, therefore tailored methods had to be developed. These methods and their applications are discussed.

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Interacting with mobile services: an evaluation of camera-phones and visual tags

We present a study of using camera-phones and visual-tags to access mobile services. Firstly, a user-experience study is described in which participants were both observed learning to interact with a prototype mobile service and interviewed about their experiences. Secondly, a pointing-device task is presented in which quantitative data was gathered regarding the speed and accuracy with which participants aimed and clicked on visual-tags using camera-phones. We found that participants’ attitudes to visual-tag-based applications were broadly positive, although they had several important reservations about camera-phone technology more generally. Data from our pointing-device task demonstrated that novice users were able to aim and click on visual-tags quickly (well under 3 s per pointing-device trial on average) and accurately (almost all meeting our defined speed/accuracy tradeoff of 6% error-rate). Based on our findings, design lessons for camera-phone and visual-tag applications are presented.

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E-redesigning of society: towards experiential connectivity of generations in Lithuania

The paper reflects on the unique experience of social and technological development in Lithuania since the regaining of independence as a newly reshaped society constructing a distinctive competitive IST-based model at global level. This has presented Lithuanian pattern of how to integrate different experiences and relations between generations in implementing complex information society approaches. The resulting programme in general is linked to the Lisbon objectives of the European Union. The experience of transitional countries in Europe, each different but facing some common problems, may be useful to developing countries in Africa.

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Protecting business intelligence and customer privacy while outsourcing data mining tasks

Nowadays data mining plays an important role in decision making. Since many organizations do not possess the in-house expertise of data mining, it is beneficial to outsource data mining tasks to external service providers. However, most organizations hesitate to do so due to the concern of loss of business intelligence and customer privacy. In this paper, we present a Bloom filter based solution to enable organizations to outsource their tasks of mining association rules, at the same time, protect their business intelligence and customer privacy. Our approach can achieve high precision in data mining by trading-off the storage requirement. This research was supported by the USA National Science Foundation Grants CCR-0310974 and IIS-0546027.

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Inverse multi-objective robust evolutionary design

In this paper, we present an Inverse Multi-Objective Robust Evolutionary (IMORE) design methodology that handles the presence of uncertainty without making assumptions about the uncertainty structure. We model the clustering of uncertain events in families of nested sets using a multi-level optimization search. To reduce the high computational costs of the proposed methodology we proposed schemes for (1) adapting the step-size in estimating the uncertainty, and (2) trimming down the number of calls to the objective function in the nested search. Both offline and online adaptation strategies are considered in conjunction with the IMORE design algorithm. Design of Experiments (DOE) approaches further reduce the number of objective function calls in the online adaptive IMORE algorithm. Empirical studies conducted on a series of test functions having diverse complexities show that the proposed algorithms converge to a set of Pareto-optimal design solutions with non-dominated nominal and robustness performances efficiently.

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Multimodal support to group dynamics

The complexity of group dynamics occurring in small group interactions often hinders the performance of teams. The availability of rich multimodal information about what is going on during the meeting makes it possible to explore the possibility of providing support to dysfunctional teams from facilitation to training sessions addressing both the individuals and the group as a whole. A necessary step in this direction is that of capturing and understanding group dynamics. In this paper, we discuss a particular scenario, in which meeting participants receive multimedia feedback on their relational behaviour, as a first step towards increasing self-awareness. We describe the background and the motivation for a coding scheme for annotating meeting recordings partially inspired by the Bales’ Interaction Process Analysis. This coding scheme was aimed at identifying suitable observable behavioural sequences. The study is complemented with an experimental investigation on the acceptability of such a service.

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An interorganizational knowledge-sharing security model with breach propagation detection

The increasing adoption of Service Oriented Architecture (SOA) is allowing more and more companies to integrate themselves in interorganizational netchain environments wherein knowledge assets can be electronically shared with selected business partners. The dynamic nature of these environments implies a need for organizations to protect and monitor the flow of their valuable knowledge assets throughout the netchain if they hope to maintain their long-term competitive positions. In this paper, we propose an interorganizational knowledge-sharing security model that integrates the value chain reference model (VCOR), the federated enterprise reference architecture model (FERA), and multidimensional data warehouse technologies to allow for the proactive monitoring of shared knowledge assets across an SOA-based netchain. The proposed architecture is novel In that it supports dynamic policy revision through the automated detection of knowledge-sharing breaches within a netchain—a process whose viability is demonstrated using network flow theory and a series of simulations. Existing business intelligence infrastructures can be readily modified to support the proposed model, as multidimensional data warehousing has already been adopted in many organizations.

Connecting the family with awareness systems

Awareness systems have attracted significant research interest for their potential to support interpersonal relationships. Investigations of awareness systems for the domestic environment have suggested that such systems can help individuals stay in touch with dear friends or family and provide affective benefits to their users. Our research provides empirical evidence to refine and substantiate such suggestions. We report our experience with designing and evaluating the ASTRA awareness system, for connecting households and mobile family members. We introduce the concept of connectedness and its measurement through the Affective Benefits and Costs of communication questionnaire (ABC-Q). We inform results that testify the benefits of sharing experiences at the moment they happen without interrupting potential receivers. Finally, we document the role that lightweight, picture-based communication can play in the range of communication media available.

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Contextualization of Geospatial Database Semantics for Human–GIS Interaction

Human interactions with geographical information are contextualized by problem-solving activities which endow meaning to geospatial data and processing. However, existing spatial data models have not taken this aspect of semantics into account. This paper extends spatial data semantics to include not only the contents and schemas, but also the contexts of their use. We specify such a semantic model in terms of three related components: activity-centric context representation, contextualized ontology space, and context mediated semantic exchange. Contextualization of spatial data semantics allows the same underlying data to take multiple semantic forms, and disambiguate spatial concepts based on localized contexts. We demonstrate how such a semantic model supports contextualized interpretation of vague spatial concepts during human–GIS interactions. We employ conversational dialogue as the mechanism to perform collaborative diagnosis of context and to coordinate sharing of meaning across agents and data sources.