Specializing pedestrian maps to address the needs of people using wheelchairs: a case study in community-sustainable information systems

Gemstone Team FASTR (Finding Alternative Specialized Travel Routes)

Real-Time and Data-Driven Operation Optimization and Knowledge Discovery for an Enterprise Information System

An enterprise information system (EIS) is an integrated data-applications platform characterized by diverse, heterogeneous, and distributed data sources. For many enterprises, a number of business processes still depend heavily on static rule-based methods and extensive human expertise. Enterprises are faced with the need for optimizing operation scheduling, improving resource utilization, discovering useful knowledge, and making data-driven decisions.

This thesis research is focused on real-time optimization and knowledge discovery that addresses workflow optimization, resource allocation, as well as data-driven predictions of process-execution times, order fulfillment, and enterprise service-level performance. In contrast to prior work on data analytics techniques for enterprise performance optimization, the emphasis here is on realizing scalable and real-time enterprise intelligence based on a combination of heterogeneous system simulation, combinatorial optimization, machine-learning algorithms, and statistical methods.

On-demand digital-print service is a representative enterprise requiring a powerful EIS.We use real-life data from Reischling Press, Inc. (RPI), a digit-print-service provider (PSP), to evaluate our optimization algorithms.

In order to handle the increase in volume and diversity of demands, we first present a high-performance, scalable, and real-time production scheduling algorithm for production automation based on an incremental genetic algorithm (IGA). The objective of this algorithm is to optimize the order dispatching sequence and balance resource utilization. Compared to prior work, this solution is scalable for a high volume of orders and it provides fast scheduling solutions for orders that require complex fulfillment procedures. Experimental results highlight its potential benefit in reducing production inefficiencies and enhancing the productivity of an enterprise.

We next discuss analysis and prediction of different attributes involved in hierarchical components of an enterprise. We start from a study of the fundamental processes related to real-time prediction. Our process-execution time and process status prediction models integrate statistical methods with machine-learning algorithms. In addition to improved prediction accuracy compared to stand-alone machine-learning algorithms, it also performs a probabilistic estimation of the predicted status. An order generally consists of multiple series and parallel processes. We next introduce an order-fulfillment prediction model that combines advantages of multiple classification models by incorporating flexible decision-integration mechanisms. Experimental results show that adopting due dates recommended by the model can significantly reduce enterprise late-delivery ratio. Finally, we investigate service-level attributes that reflect the overall performance of an enterprise. We analyze and decompose time-series data into different components according to their hierarchical periodic nature, perform correlation analysis,

and develop univariate prediction models for each component as well as multivariate models for correlated components. Predictions for the original time series are aggregated from the predictions of its components. In addition to a significant increase in mid-term prediction accuracy, this distributed modeling strategy also improves short-term time-series prediction accuracy.

In summary, this thesis research has led to a set of characterization, optimization, and prediction tools for an EIS to derive insightful knowledge from data and use them as guidance for production management. It is expected to provide solutions for enterprises to increase reconfigurability, accomplish more automated procedures, and obtain data-driven recommendations or effective decisions.

Managing digital libraries using semantic web technologies

The aim of this work is to improve retrieval and navigation services on bibliographic data held in digital libraries. This paper presents the design and implementation of OntoBib¸ an ontology-based bibliographic database system that adopts ontology-driven search in its retrieval. The presented work exemplifies how a digital library of bibliographic data can be managed using Semantic Web technologies and how utilizing the domain specific knowledge improves both search efficiency and navigation of web information and document retrieval.

Use and access to ICT in students of public secondary schools in Chihuahua City, Mexico: inclusion in teaching and digital literacy

This paper addresses the issue of the digital divide in students of public secondary schools at Chihuahua City, Mexico. It seeks to identify potential inequality of opportunities with regards to subjects’ access to information, knowledge and education through the ICT (internet, mobile telephony, broadband and television). The study takes three schools as investigative stage, using the survey as a data collection instrument, identifying patterns of behavior regarding: general knowledge of them, access to computer equipment and internet, and characterization of their use. Other aspects of analysis are the identification of the educational level of parents and access to technology resources available for academic and non-academic purposes in various application areas (home, school and social environment). The proposal concludes, that it is through the recollection of alternatives suggested by the teachers themselves to incorporate ICT for teaching purposes in a systematic and planned fashion, whose greatest reflection manifests in better digital literacy indicators.

Lifelong learning through digital storytelling in corporate training

In this paper we discuss collaborative learning strategies based on the use of digital stories in corporate training and lifelong learning. The text starts with a concise review on theoretical and technical foundations about the use of digital technologies in collaborative strategies in lifelong learning. We will also discuss if the corporate training may be improved by the use of individual audio-visual experience in learning process. Careful planning, scripting and production of audio-visual digital stories can help in the construction of collaborative learning spaces in which adults are in the context of vocational training throughout life. Our analysis concludes emphasizing on the need to experience the routing performance of digital stories in the context of corporate training, following the reference levels mentioned here, so we can have in a future more theoretical and empirical elements for the validation and conceptualization in the use of digital stories in the context of corporate training. Ultimately we believe that lifelong learning can be improved with the use of strategies that promote the production of personal audio-visual for those involved in teaching and learning process in organizational context.

Analysis of the admissions tests for teacher training in Spain and Finland: knowledge or competences

One of the most decisive factors in the quality of education and academic performance of students is quality, preparation and dedication of the teachers. The exquisite system of selecting candidates for teacher training programs is one of the fundamentals of success of the Finnish Education System. The responsibility of choosing the best students to convert them into teachers is a challenge that involves a significant reform of university admission. Achieving this goal involves the choice of strategies and educational tools in accordance to the complexity of the demands presented by the teaching profession in the digital age. This study describes, analyzes and compares the admission tests in the University of Spain (PAU) and Finland (VAKAVA), for those who wish to become professional educators, in order to understand the possible influence of these tests to select the most suitable candidates to develop into future teaching professionals. The results showed that in Spain, the entrance test to universities is developed in a general way for all the students that aspire to any field of knowledge, while in Finland, the test is specific and particular for students aspiring to the field of education. The results of this study can guide and encourage the necessary changes that have to be done in the admission tests to Spanish university in general and to teacher education faculties in particular.

An Integration Methodology for Automated Recurring Cost Prediction using Digital Manufacturing Technology

The need to account for the effect of design decisions on manufacture and the impact of manufacturing cost on the life cycle cost of any product are well established. In this context, digital design and manufacturing solutions have to be further developed to facilitate and automate the integration of cost as one of the major driver in the product life cycle management. This article is to present an integration methodology for implementing cost estimation capability within a digital manufacturing environment. A digital manufacturing structure of knowledge databases are set out and the ontology of assembly and part costing that is consistent with the structure is provided. Although the methodology is currently used for recurring cost prediction, it can be well applied to other functional developments, such as process planning. A prototype tool is developed to integrate both assembly time cost and parts manufacturing costs within the same digital environment. An industrial example is used to validate this approach.

Inscribing value on business model innovations: Insights from industrial projects commercializing disruptive digital innovations

In this paper we seek to show how marketing activities inscribe value on business model innovation, representative of an act, or sequence of socially interconnecting acts. Theoretically we ask two interlinked questions: (1) how can value inscriptions contribute to business model innovations? (2) how can marketing activities support the inscription of value on business model innovations? Semi-structured in-depth interviews were conducted with the thirty-seven members from across four industrial projects commercializing disruptive digital innovations. Various individuals from a diverse range of firms are shown to cast relevant components of their agency and knowledge on business model innovations through negotiation as an ongoing social process. Value inscription is mutually constituted from the marketing activities, interactions and negotiations of multiple project members across firms and functions to counter destabilizing forces and tensions arising from the commercialization of disruptive digital innovations. This contributes to recent conceptual thinking in the industrial marketing literature, which views business models as situated within dynamic business networks and a context-led evolutionary process. A contribution is also made to debate in the marketing literature around marketing's boundary-spanning role, with marketing activities shown to span and navigate across functions and firms in supporting value inscriptions on business model innovations.

Merging Knowledge Bases in Possibilistic Logic by Lexicographic Aggregation

Belief merging is an important but difficult problem in Artificial Intelligence, especially when sources of information are pervaded with uncertainty. Many merging operators have been proposed to deal with this problem in possibilistic logic, a weighted logic which is powerful for handling inconsistency and deal-ing with uncertainty. They often result in a possibilistic knowledge base which is a set of weighted formulas. Although possibilistic logic is inconsistency tolerant, it suffers from the well-known "drowning effect". Therefore, we may still want to obtain a consistent possibilistic knowledge base as the result of merging. In such a case, we argue that it is not always necessary to keep weighted information after merging. In this paper, we define a merging operator that maps a set of possibilistic knowledge bases and a formula representing the integrity constraints to a classical knowledge base by using lexicographic ordering. We show that it satisfies nine postulates that generalize basic postulates for propositional merging given in [11]. These postulates capture the principle of minimal change in some sense. We then provide an algorithm for generating the resulting knowledge base of our merging operator. Finally, we discuss the compatibility of our merging operator with propositional merging and establish the advantage of our merging operator over existing semantic merging operators in the propositional case.

Knowledge Exchange, Spatial Analysis & Healthy Urban Environments (KESUE): Project Report

The Knowledge Exchange, Spatial Analysis and Healthy Urban Environments (KESUE) project has extended work previously undertaken by a QUB team of inter-disciplinary researchers engaged with the Physical Activity in the Regeneration of Connswater (PARC) project (Tully et al, 2013). The PARC project focussed on parts of East Belfast to assess the health impact of the Connswater Community Greenway. The KESUE project has aimed to extend some of the tools used initially in East Belfast so that they have data coverage of all of Belfast and Derry-Londonderry. The purpose of this has been to enable the development of evidence and policy tools that link features of the built environment with physical activity in these two cities. The project has used this data to help shape policy decisions in areas such as physical activity, park management, public transport and planning.

Working with a range of local partners who part-funded the project (City Councils in Belfast and Derry-Londonderry, Public Health Agency, Belfast Healthy Cities and Department of Regional Development), this project has mapped all the footpaths in the two cities (covering 37% of the NI population) and employed this to develop evidence used in strategies related to healthy urban planning. Using Geographic Information Systems (GIS), the footpath network has been used as a basis for a wide range of policy-relevant analyses including pedestrian accessibility to public facilities, site options for new infrastructure and assessing how vulnerable groups can access services such as pharmacies. Key outputs have been Accessibility Atlases and maps showing how walkability of the built environment varies across the two cities.

In addition to generating this useful data, the project included intense engagement with potential users of the research, which has led to its continued uptake in a number of policies and strategies, creating a virtuous circle of research, implementation and feedback. The project has proved so valuable to Belfast City Council that they have now taken on one of the researchers to continue the work in-house.

Knowledge Management Techniques to Augment Textual CBR (PhD Thesis)

The past decade had witnessed an unprecedented growth in the amount of available digital content, and its volume is expected to continue to grow the next few years. Unstructured text data generated from web and enterprise sources form a large fraction of such content. Many of these contain large volumes of reusable data such as solutions to frequently occurring problems, and general know-how that may be reused in appropriate contexts. In this work, we address issues around leveraging unstructured text data from sources as diverse as the web and the enterprise within the Case-based Reasoning framework. Case-based Reasoning (CBR) provides a framework and methodology for systematic reuse of historical knowledge that is available in the form of problemsolution
pairs, in solving new problems. Here, we consider possibilities of enhancing Textual CBR systems under three main themes: procurement, maintenance and retrieval. We adapt and build upon the stateof-the-art techniques from data mining and natural language processing in addressing various challenges therein. Under procurement, we investigate the problem of extracting cases (i.e., problem-solution pairs) from data sources such as incident/experience
reports. We develop case-base maintenance methods specifically tuned to text targeted towards retaining solutions such that the utility of the filtered case base in solving new problems is maximized. Further, we address the problem of query suggestions for textual case-bases and show that exploiting the problem-solution partition can enhance retrieval effectiveness by prioritizing more useful query suggestions. Additionally, we illustrate interpretable clustering as a tool to drill-down to domain specific text collections (since CBR systems are usually very domain specific) and develop techniques for improved similarity assessment in social media sources such as microblogs. Through extensive empirical evaluations, we illustrate the improvements that we are able to
achieve over the state-of-the-art methods for the respective tasks.

Promoting self-regulated learning in technology enhanced learning environments : keeping a digital track of the learning process

Tese de doutoramento (co-tutela), Psicologia (Psicologia da Educação), Faculdade de Psicologia da Universidade de Lisboa, Faculdade de Psicologia e de Ciências da Educação da Universidade de Coimbra, Technial University of Darmstadt, 2014

An algebra and conceptual model for semantic tagging of collaborative digital libraries

Cost-effective semantic description and annotation of shared knowledge resources has always been of great importance for digital libraries and large scale information systems in general. With the emergence of the Social Web and Web 2.0 technologies, a more effective semantic description and annotation, e.g., folksonomies, of digital library contents is envisioned to take place in collaborative and personalised environments. However, there is a lack of foundation and mathematical rigour for coping with contextualised management and retrieval of semantic annotations throughout their evolution as well as diversity in users and user communities. In this paper, we propose an ontological foundation for semantic annotations of digital libraries in terms of flexonomies. The proposed theoretical model relies on a high dimensional space with algebraic operators for contextualised access of semantic tags and annotations. The set of the proposed algebraic operators, however, is an adaptation of the set theoretic operators selection, projection, difference, intersection, union in database theory. To this extent, the proposed model is meant to lay the ontological foundation for a Digital Library 2.0 project in terms of geometric spaces rather than logic (description) based formalisms as a more efficient and scalable solution to the semantic annotation problem in large scale.

Theorising and analysing digital labour: from global value chains to modes of production

This paper considers the following question—where do computers, laptops and mobile phones come from and who produced them? Specific cases of digital labour are examined—the extraction of minerals in African mines under slave-like conditions; ICT manufacturing and assemblage in China (Foxconn); software engineering in India; call centre service work; software engineering at Google within Silicon Valley; and the digital labour of internet prosumers/users. Empirical data and empirical studies concerning these cases are systematically analysed and theoretically interpreted. The theoretical interpretations are grounded in Marxist political economy. The term ‘global value chain’ is criticised in favour of a complex and multidimensional understanding of Marx’s ‘mode of production’ for the purposes of conceptualizing digital labour. This kind of labour is transnational and involves various modes of production, relations of production and organisational forms (in the context of the productive forces). There is a complex global division of digital labour that connects and articulates various forms of productive forces, exploitation, modes of production, and variations within the dominant capitalist mode of production.

Gold, power, protest: Digital and social media and protests against large-scale mining projects in Colombia

Colombia’s Internet connectivity has increased immensely. Colombia has also ‘opened for business’, leading to an influx of extractive projects to which social movements object heavily. Studies on the role of digital media in political mobilisation in developing countries are still scarce. Using surveys, interviews, and reviews of literature, policy papers, website and social media content, this study examines the role of digital and social media in social movement organisations and asks how increased digital connectivity can help spread knowledge and mobilise mining protests. Results show that the use of new media in Colombia is hindered by socioeconomic constraints, fear of oppression, the constraints of keyboard activism and strong hierarchical power structures within social movements. Hence, effects on political mobilisation are still limited. Social media do not spontaneously produce non-hierarchical knowledge structures. Attention to both internal and external knowledge sharing is therefore conditional to optimising digital and social media use.