Behavior modeling for a beacon-based indoor location system

In this work we performed a comparison between two different approaches to track a person in indoor environments using a locating system based on BLE technology with a smartphone and a smartwatch as monitoring devices. To do so, we provide the system architecture we designed and describe how the different elements of the proposed system interact with each other. Moreover, we have evaluated the system’s performance by computing the mean percentage error in the detection of the indoor position. Finally, we present a novel location prediction system based on neural embeddings, and a soft-attention mechanism, which is able to predict user’s next location with 67% accuracy

Automation, Protection and Control of Substation Based on IEC 61850

Reliability of power system protection system has been a key issue in the substation operation due to the use of multi-vendor equipment of proprietary features, environmental issues, and complex fault diagnosis. Failure to address these issues could have a significant effect on the performance of the entire electricity grid. With the introduction of IEC 61850 standard, substation automation system (SAS) has significantly altered the scenario in utilities and industries as indicated in this thesis

MOVING: A User-Centric Platform for Online Literacy Training and Learning

Part of the Progress in IS book series (PROIS)In this paper, we present an overview of the MOVING platform, a user-driven approach that enables young researchers, decision makers, and public administrators to use machine learning and data mining tools to search, organize, and manage large-scale information sources on the web such as scientific publications, videos of research talks, and social media. In order to provide a concise overview of the platform, we focus on its front end, which is the MOVING web application. By presenting the main components of the web application, we illustrate what functionalities and capabilities the platform offer its end-users, rather than delving into the data analysis and machine learning technologies that make these functionalities possible

e-Science

This open access book shows the breadth and various facets of e-Science, while also illustrating their shared core. Changes in scientific work are driven by the shift to grid-based worlds, the use of information and communication systems, and the existential infrastructure, which includes global collaboration. In this context, the book addresses emerging issues such as open access, collaboration and virtual communities and highlights the diverse range of developments associated with e-Science. As such, it will be of interest to researchers and scholars in the fields of information technology and knowledge management

Developing artificial intelligence and machine learning to support primary care research and practice

This thesis was motivated by the potential to use everyday data , especially that collected in electronic health records (EHRs) as part of healthcare delivery, to improve primary care for clients facing complex clinical and/or social situations. Artificial intelligence (AI) techniques can identify patterns or make predictions with these data, producing information to learn about and inform care delivery. Our first objective was to understand and critique the body of literature on AI and primary care. This was achieved through a scoping review wherein we found the field was at an early stage of maturity, primarily focused on clinical decision support for chronic conditions in high-income countries, with low levels of primary care involvement and model evaluation in real-world settings. Our second objective was to demonstrate how AI methods can be applied to problems in descriptive epidemiology. To achieve this, we collaborated with the Alliance for Healthier Communities, which provides team-based primary health care through Community Health Centres (CHCs) across Ontario to clients who experience barriers to regular care. We described sociodemographic, clinical, and healthcare use characteristics of their adult primary care population using EHR data from 2009-2019. We used both simple statistical and unsupervised learning techniques, applied with an epidemiological lens. In addition to substantive findings, we identified potential avenues for future learning initiatives, including the development of decision support tools, and methodological considerations therein. Our third objective was to advance interpretable AI methodology that is well-suited for heterogeneous data, and is applicable in clinical epidemiology as well as other settings. To achieve this, we developed a new hybrid feature- and similarity-based model for supervised learning. There are two versions, fit by convex optimization with a sparsity-inducing penalty on the kernel (similarity) portion of the model. We compared our hybrid models with solely feature- and similarity-based approaches using synthetic data and using CHC data to predict future loneliness or social isolation. We also proposed a new strategy for kernel construction with indicator-coded data. Altogether, this thesis progressed AI for primary care in general and for a particular health care organization, while making research contributions to epidemiology and to computer science

Implementing inter-organisational information systems for the integration of construction supply chains

Two trends are currently driving the need for supply chain firms to form closely integrated relationships: collaboration and digitisation. One of the ways to achieve digitisation of supply chain operations is to implement Inter-Organisational Information Systems (IOIS) with selected supply chain partners for a much more efficient, streamlined and orchestrated supply chain operations. Whilst IOIS can be implemented to support various cross-functional business processes (ranging from operational information exchange to pursuing strategic initiatives such as sharing ideas, identifying new market opportunities, and pursing a continuous improvement approach), in the context of this thesis, the purpose of IOIS implementation is to facilitate the inter-firm procurement-related operations with downstream supply chain firms. The study undertaken in this research project was initiated in response to an industry requirement to investigate the implementation of IOIS against a backdrop of improved Supply Chain Management and integration practices by large contractor organisations. A case study research strategy was adopted to investigate the IOIS project related, IOIS (system) related issues encountered in ex-ante and ex-post implementation stages of the IOIS. The study concludes that it is the non-technical factors that are critical to the successful delivery of IOIS projects and provides a guideline on IOIS implementation by large contractor organisations. The findings of this research project have been published in a number of peer-reviewed papers