eduGraph: A Dashboard for Personalised Feedback in Massive Open Online Courses

Learning Analytics is concerned with the design and implementation of tools and processes for collecting, analysing, and communicating information about teaching and learning. It is enabled by data, but not driven by it, rather it tries to empower human judgements by presenting meaningful facts. This thesis explores the data generated in Open edX courses to understand how it can be analysed and used to impact learners' motivation in online courses. It is carried out using Design Science, a research methodology aiming to produce artefacts that can improve the interaction with problems. In this thesis I present the eduGraph dashboard, a dashboard that uses Learning Analytics to present meaningful insights about learners' learning process in Massive Open Online Courses (MOOCs). Results indicate that learners perceive the dashboard as useful and effective at motivating them to take part in online courses, and that it enables them to keep track of their progress in the courses. I posit that the biggest problem facing Learning Analytics today are the lack of accessible data, and that it is possible for reasearchers to create more accurate learner models by using Learning Anaytics theories and methods in combination with the iterative and technical process of Information Systems development.Masteroppgave i informasjonsvitenskapINFO390MASV-INF

Predicting parking space availability based on heterogeneous data using Machine Learning techniques

Abstract. These days, smart cities are focused on improving their services and bringing quality to everyday life, leveraging modern ICT technologies. For this reason, the data from connected IoT devices, environmental sensors, economic platforms, social networking sites, governance systems, and others can be gathered for achieving such goals. The rapid increase in the number of vehicles in major cities of the world has made mobility in urban areas difficult, due to traffic congestion and parking availability issues. Finding a suitable parking space is often influenced by various factors such as weather conditions, traffic flows, and geographical information (markets, hospitals, parks, and others). In this study, a predictive analysis has been performed to estimate the availability of parking spaces using heterogeneous data from Cork County, Ireland. However, accumulating, processing, and analysing the produced data from heterogeneous sources is itself a challenge, due to their diverse nature and different acquisition frequencies. Therefore, a data lake has been proposed in this study to collect, process, analyse, and visualize data from disparate sources. In addition, the proposed platform is used for predicting the available parking spaces using the collected data from heterogeneous sources. The study includes proposed design and implementation details of data lake as well as the developed parking space availability prediction model using machine learning techniques

Moving towards in-line metrology : evaluation of a Laser Radar system for in-line dimensional inspection for automotive assembly systems

The increasing interest towards intelligent systems has led to a demand for the development of zero-defect strategies, with a paradigm shift from off-line and dedicated to in-line metrology with integrated robotic systems. However, a major barrier preventing the systematic uptake of in-line metrology is the lack of evaluation of system capability in terms of accuracy, repeatability and measurement time, when compared to the well-established coordinate measuring machine (CMM). In this study, a robotic Laser Radar (LR) solution is assessed in the context of automotive dimensional inspection of Body-In-White (BIW) applications. The objective is both to understand the effect of robot re-positioning error on measurement accuracy and repeatability and to compare measurement results against a CMM. Eighty-one surface points, six edge points, twenty-five holes and sixteen slots were selected from an industry standard measurement plan. Whilst LR exhibits a lower measurement accuracy than twin-column CMM, its repeatability is well within the specification limits for body shell quality inspection. Therefore, as a real-time in-line metrology tool, it is a genuine prospect to exploit. This research makes a significant contribution toward in-line metrology for dimensional inspection, for automotive application, for rapid detection and for correction of assembly defects in real time, with subsequent reduction of scrap and number of repairs/re-works

"Not the Usual Suspects": A Study of Factors Reducing the Effectiveness of CCTV

Previous research on the effectiveness of Closed Circuit Television (CCTV) has focused on critically assessing police and government claims that CCTV is effective in reducing crime. This paper presents a field study that investigates the relationship between CCTV system design and the performance of operator tasks. We carried out structured observations and interviews with 13 managers and 38 operators at 13 CCTV control rooms. A number of failures were identified, including the poor configuration of technology, poor quality video recordings, and a lack of system integration. Stakeholder communication was poor, and there were too many cameras and too few operators. These failures have been previously identified by researchers; however, no design improvements have been made to control rooms in the last decade. We identify a number of measures to improve operator performance, and contribute a set of recommendations for security managers and practitioners. Security Journal (2010) 23, 134-154. doi:10.1057/sj.2008.2; published online 6 October 200

Evaluating the capability of laser scanning to measure an automotive artefact : a comparison study of touch trigger probe and laser-scanning

Abstract: In the automotive industry dimensional quality control is an important part of the production process, often carried out using coordinate measuring machines (CMMs). However, CMMs used in conjunction with touch probes have a relatively low measurement speed. There is also a close link between the cost of measurement and the number of discrete points captured, leading to a trade-off between the number of points that can be measured and the measurement time. Laser scanners offer a faster alternative to touch probe measurement, but have certain limitations. A number of studies have considered the accuracy of laser scanning using small artefacts; however, little work has been done on the verification of on-CMM laser scanning systems for large volume, industry-relevant measurement applications. In this research, a nominal representation of a vehicle body was used and 104 standard features were measured. The results show that the laser scanning sensor and CMM used in this study would, for the majority of measurements, provide a level of accuracy and repeatability better than which is typically required by automotive manufacturers for body shell quality inspection applications

Understanding multispectral imaging of cultural heritage:Determining best practice in MSI analysis of historical artefacts

Although multispectral imaging (MSI) of cultural heritage, such as manuscripts, documents and artwork, is becoming more popular, a variety of approaches are taken and methods are often inconsistently documented. Furthermore, no overview of the process of MSI capture and analysis with current technology has previously been published. This research was undertaken to determine current best practice in the deployment of MSI, highlighting areas that need further research, whilst providing recommendations regarding approach and documentation. An Action Research methodology was used to characterise the current pipeline, including: literature review; unstructured interviews and discussion of results with practitioners; and reflective practice whilst undertaking MSI analysis. The pipeline and recommendations from this research will improve project management by increasing clarity of published outcomes, the reusability of data, and encouraging a more open discussion of process and application within the MSI community. The importance of thorough documentation is emphasised, which will encourage sharing of best practice and results, improving community deployment of the technique. The findings encourage efficient use and reporting of MSI, aiding access to historical analysis. We hope this research will be useful to digitisation professionals, curators and conservators, allowing them to compare and contrast current practices