In this thesis we present our research project on an augmented environment developed using the technology available in the field of Augmented Reality, capable of delivering learning contents on Information and Communication Technologies and e-services to older adults without computer and digital literacy. The learning environment is meant to provide a contribution in solving a problem of social exclusion in older adults. In recent years, technology has helped older adults in many ways to slow down the effects of ageing. Yet, at the same time, technology has also created new problems for older adults. Indeed, technology has transformed society into a strongly technological-based e-society, in which citizens without competences on the use of computer and digital tools, such as older adults, are progressively pushed to the margins, and run the risk of being socially excluded. Learning is the key-concept for a possible solution to such a problem. Older adults can still learn, even in older age. Learning is beneficial to older adults in many ways. So, why not using learning for teaching older adults the basic of technology necessary to make them citizens of e-society? That is the purpose of our research: our learning environment is meant to teach older adults the basic of technology through a technological device. We designed our augmented environment specifically for older adults without computer and digital literacy: it takes into account older adults’ needs and possible disabilities; it does not require any particular psycho-physical competence to be used; it does not require any technological knowledge. In this thesis we show how we designed a learning augmented environment with such features, how we developed it, and how we tested it on a group of older adults to ensure that what we have developed meets the requirements we set during the design process.

Network analysts have long used two-dimensional security visualizations to make sense of network data. As networks grow larger and more complex, two-dimensional visualizations become more convoluted, potentially compromising user situational awareness of cyber threats. To combat this problem, augmented reality (AR) can be employed to visualize data within a cyber-physical context to restore user perception and improve comprehension; thereby, enhancing cyber situational awareness. Multiple generations of prototypes, known collectively as Mobile Augmented Reality for Cyber Security, or MARCS, were developed to study the impact of AR on cyber situational awareness. First generation prototypes were subjected to a formative pilot study of 44 participants, to generate user-centric performance data and feedback, which motivated the design and development of second generation prototypes and provided initial insight into the potentially beneficial impact of AR on cyber situational awareness. Second generation prototypes were subjected to a summative secondary study by 50 participants, to compare the impact of AR and non-AR visualizations on cyber situational awareness. Results of the secondary study suggest that employing AR to visualize cyber threats in a cyber-physical context collectively improves user threat perception and comprehension, indicating that, in some cases, AR security visualizations improve user cyber situational awareness over non-AR security visualizations. / Master of Science / Augmented Reality can be a powerful medium with which to communicate visual information to human beings. By overlaying digital projections on the visual world, augmented reality can leverage the context of the natural world to intuitively communicate information to people who may not have an innate understanding of the underlying data. Mobile augmented reality for cybersecurity (MARCS) visualizes cybersecurity information using augmented reality to give users a unique perspective of cybersecurity information. Experimentation yielded quantitative and qualitative data that suggest that MARCS positively impacted user awareness of cybersecurity data implicating augmented reality as a viable visualization strategy for cyber and network security data.

The rise in technology and reduced costs has led to more research on the use of Augmented Reality (AR). However, applications for AR Head Mounted Display (HMD) systems are still being defined. AR HMD systems have potential to help users interact and experience information in a way that could improve their performance. In the construction sector, workers use black and white construction level of detail drawings for assembly and inspection tasks. For this thesis, Microsoft HoloLens was used in an experiment to see the effects of AR models on user performance and comprehension. There were three conditions for this study, two of the conditions used AR model displays and the third condition used a traditional paper drawing of the model. This study measured participants' accuracy and comprehension of the model presented to them. The conclusion of this thesis is that using 3D AR models may improve participants' comprehension of construction drawings. / Master of Science / The rise in technology and reduced costs has led to more research on the use of Augmented Reality (AR). However, applications for AR Head Mounted Display (HMD) systems are still being defined. AR HMD systems have potential to help users interact and experience information in a way that could improve their performance. In the construction sector, workers use black and white construction level of detail drawings for assembly and inspection tasks. For this thesis, Microsoft HoloLens was used in an experiment to see the effects of AR models on user performance and comprehension. There were three conditions for this study, two of the conditions used AR model displays and the third condition used a traditional paper drawing of the model. This study measured participants’ accuracy and comprehension of the model presented to them. The conclusion of this thesis is that using 3D AR models may improve participants’ comprehension of construction drawings.

Augmented Reality (AR) is a powerful tool for the visualisation of, and interaction with, digital information, and has been successfully deployed in a number of consumer applications. Despite this, AR has had limited success in industrial applications as the combined precision, accuracy, scalability and robustness of the systems are not up to industry standards. With these characteristics in mind, we present a concept Industrial AR (IAR) framework for use in outdoor environments. Within this concept IAR framework, we focus on the improving the precision and accuracy of consumer level devices by focusing on the issue of localisation, utilising LiDAR based point clouds generated as part of normal surveying and engineering workflow. We evaluate key design points to optimise the localisation solution, including the impact of increased field of view on feature matching performance, the filtering of feature matches between real imagery and an observed point cloud, and how pose can be estimated from 2D to 3D point correspondences. The overall accuracy of this localisation algorithm with respect to ground-truth observations is determined, with unfiltered results indicating an on par horizontal accuracy and significantly improved vertical accuracy with best-case consumer GNSS solutions. When additional filtering is applied, results of localisation show a higher accuracy than best-case consumer GNSS.

This thesis explores a way of increasing the perception of reality within an ''Augmented Reality'' application by making real objects able to obstruct the view of virtual objects. This mimics how real opaque objects occlude each other and thus making virtual objects behave the same way will improve the user experience of Augmented Reality users. The solution uses Unity as the engine with plugins for ARKit and OpenCV. ARKit provides the Augmented Reality experience and can detect real world flat surfaces on which virtual objects can be placed. OpenCV is used for image processing to detect real world objects which can then be translated into virtual silhouettes within Unity that can interact with, and occlude, the virtual objects. The end result is a system that can handle the occlusion in real time, while allowing both the real and virtual objects to translate and rotate within the scene while still maintaining the occlusion. The big drawback of the solution is that it requires a well defined environment without visual clutter and with even lighting to work as intended. This makes it unsuitable for outdoor usage.

ITC/USA 2015 Conference Proceedings / The Fifty-First Annual International Telemetering Conference and Technical Exhibition / October 26-29, 2015 / Bally's Hotel & Convention Center, Las Vegas, NV / This paper describes a new way to look at telemetry data. Northern Arizona University (NAU) students are researching a new approach to apply virtual reality (VR) to evaluate data from a collection of stored signals. Each signal will have limits attached which we will use to view the parts of the waveform which contain abnormalities. A program to illustrate the technique is being developed by NAU students. Initially, we were working with Vizard 5, using the Python language. However, there is another program, Unity, which will perhaps be more useful for the application we wish to achieve. Additionally, we are examining a technique to accurately access the telemetry data collected. The amount of telemetry data collected has increased over the years resulting in difficulties in identifying the relevant information. We are searching for a better approach to store and access big data and will demonstrate this approach by utilizing Oculus Rift and Microsoft Kinect.

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Investigating the possibility of customizing off-the-shelf tests to provide various kinds of information is becoming increasingly interesting due to high information demands in the current testing environment. Comparing examinee achievement status on a national basis using such tests may provide a cost-effective solution for some practical problems. However, the normative estimates based on customized tests may be very different from those based on intact tests, and the validity of customized norms may be seriously compromised. The primary purpose of this study was to investigate the impact of various factors on the validity of customized norms. These factors included customizing strategy, estimating items, test length, correlations of latent abilities assessed by items from an intact test and new items, and test dimensional structures. Monte Carlo simulation techniques were used to examine the accuracy of the customized norms. Both unidimensional and multidimensional data sets were generated and calibrated using unidimensional item response theory models. The five factors cited above were manipulated in a partially crossed design, with a total of 44 combinations of conditions. The outcomes of interest included estimated ability distributions and correlations, mean differences, mean absolute differences of ability and percentile estimates derived from intact tests and customized tests. Based on the results of this study, it was concluded that: (1) customized instruments with all items from intact tests provided more accurate normative estimates than instruments having some items from intact tests removed; (2) using only items from intact tests to derive norms yielded more accurate estimates than using all items in customized tests; (3) lengthened customized tests yielded more accurate estimates than shortened tests; (4) the higher the correlation of latent abilities measured by items from intact tests and new items, the more accurate the normative estimates; (5) the impacts of the various factors were small when the unidimensionality assumption was satisfied; the differences increased when data structures became more complicated.

Under the Common Core State Standard (CCSS) initiative, states that voluntarily adopt the common core standards work together to develop a common assessment in order to supplement and replace existing state assessments. However, the common assessment may not cover all state standards, so states within the consortium can augment the assessment using locally developed items that align with state-specific standards to ensure that all necessary standards are measured. The purpose of this dissertation was to evaluate the linking accuracy of the augmented tests using the common-item nonequivalent groups design. Pseudo-test analyses were conducted by splitting a large-scale math assessment in half, creating two parallel common assessments, and by augmenting two sets of state-specific items from a large-scale science assessment. Based upon some modifications of the pseudo-data, a simulated study was also conducted. For the pseudo-test analyses, three factors were investigated: (1) the difference in ability between the new and old test groups, (2) the differential effect size for the common assessment and state-specific item set, and (3) the number of common items. For the simulation analyses, the latent-trait correlations between the common assessment and state-specific item set as well as the differential latent-trait correlations between the common assessment and state-specific item set were used in addition to the three factors considered for the pseudo-test analyses. For each of the analyses, four equating methods were used: the frequency estimation, chained equipercentile, item response theory (IRT) true score, and IRT observed score methods. The main findings of this dissertation were as follows: (1) as the group ability difference increased, bias also increased; (2) when the effect sizes differed for the common assessment and state-specific item set, larger bias was observed; (3) increasing the number of common items resulted in less bias, especially for the frequency estimation method when the group ability differed; (4) the frequency estimation method was more sensitive to the group ability difference than the differential effect size, while the IRT equating methods were more sensitive to the differential effect size than the group ability difference; (5) higher latent-trait correlation between the common assessment and state-specific item set was associated with smaller bias, and if the latent-trait correlation exceeded 0.8, the four equating methods provided adequate linking unless the group ability difference was large; (6) differential latent-trait correlations for the old and new tests resulted in larger bias than the same latent-trait correlations for the old and new tests, and (7) when the old and new test groups were equivalent, the frequency estimation method provided the least bias, but IRT true score and observed score equating resulted in smaller bias than the frequency estimation and chained equipercentile methods when group ability differed.

Today there are many technical solutionsfor the e-commerce industry, incombination with a change in behavior ofthe end user. The consumer of todaydemands more availability andconvenience.This Master’s thesis has examined thecritical aspects of e-commercecompanies, as well as how they candevelop their e-commerce to create valuefor the end user. The aim has been toidentify the more and less importantfactors of the e-commerce business, andto investigate the extent to which thesefactors are used in the e-commerceindustry. To answer these questions, aninteractive, online questionnairecustomized for e-commerce companies wasdeveloped. It covers the areas oftraditional e-commerce, social media,mobile commerce and multiple channels.The individual results are presented atthe end of the questionnaire andcompared to the average result of thecompanies that have completed it. Aliterature review and an interview isthe basis for the questionnaire. Aweighting and a quantification of thequestions enabled comparison and wasconducted in order to generate businessvalue. Thereafter a pilot study wasconducted, in which thousands of ecommercecompanies were asked to fill inthe questionnaire, eventually resultingin 12 companies accepting the inquiry.A part of the results of the thesis isthe web questionnaire itself, where thecritical factors are presented. The webquestionnaire was weighted by the totalknowledge gathered by the literature andinterview study. The prioritized factorscan be seen in the questionnaire. Theresults of the pilot study show that 12companies have great potential toimprove their e-commerce since none ofthe entrants reached less than half ofthe questionnaire’s maximum points.