E-scooter riders have an increased crash risk compared to cyclists [1 ]. Hospital data finds increasing numbers of injured e-scooter riders, with head injuries as one of the most common injury types [2]. To decrease this high prevalence of head injuries, the use of e-scooter helmets could present a potential countermeasure [3]. Despite this, studies show a generally low rate of helmet use rates in countries without mandatory helmet use laws [4][5][6]. In countries with mandatory helmet use laws for e-scooter riders, helmet use rates are higher, but generally remain lower than bicycle use rates [7]. As the helmet use rate is a central factor for the safety of e-scooter riders in case of a crash and a key performance indicator in the European Commission's Road Safety Policy Framework 2021-2030 [8], efficient e-Scooter helmet use data collection methods are needed. However, currently, human observers are used to register e-scooter helmet use either in direct roadside observations or in indirect video-based observation, which is time-consuming and costly. In this study, a deep learning-based method for the automated detection of e-scooter helmet use in video data was developed and tested, with the aim to provide an efficient data collection tool for road safety researchers and practitioners.

Since the innovation of computers some 40 years ago and the introduction of microcomputers in 1975, computers are playing an active role in education processes and altering the pattern of interaction between teacher and student in the classroom. Computer assisted learning has been seen as a revolution in education. In this research, the author has studied the impact of using microcomputers on mathematical education, particularly at the Hong Kong tertiary level, in different perspectives. Two computer software packages have been developed on the microcomputer. The consideration of the topic to be used in the computer assisted learning was arrived at in earlier surveys with students who thought that computers could give very accurate solutions to calculations. The two software packages, demonstrating on the spot the error that would be incurred by the computer, have been used by the students. They are both interactive and make use of the advantages of the microcomputer's functions over other teaching media, such as graphics facility and random number generator, to draw to the students' attention awareness of errors that may be obtained using computers in numerical solutions. Much emphasis is put on the significance and effectiveness of using computer packages in learning and teaching. Measurements are based on questionnaires, conversations with students, and tests on content material after the packages have been used. Feedback and subjective opinion of using computers in mathematical education have also been obtained from both students and other teachers. The research then attempts to examine the suitability of applying computer assisted learning in Hong Kong education sectors. Some studies on the comments made by students who participated in the learning process are undertaken. The successes and failures in terms of student accomplishment and interest in the subject area as a result of using a software package is described. Suggestions and recommendations are given in the concluding chapter.

Object category detection, the task of determining if one or more instances of a category are present in an image with their corresponding locations, is one of the fundamental problems of computer vision. The task is very challenging because of the large variations in imaged object appearance, particularly due to the changes in viewpoint, illumination and intra-class variance. Although successful solutions exist for learning object category detectors, they require massive amounts of training data. Transfer learning builds upon previously acquired knowledge and thus reduces training requirements. The objective of this work is to develop and apply novel transfer learning techniques specific to the object category detection problem. This thesis proposes methods which not only address the challenges of performing transfer learning for object category detection such as finding relevant sources for transfer, handling aspect ratio mismatches and considering the geometric relations between the features; but also enable large scale object category detection by quickly learning from considerably fewer training samples and immediate evaluation of models on web scale data with the help of part-based indexing. Several novel transfer models are introduced such as: (a) rigid transfer for transferring knowledge between similar classes, (b) deformable transfer which tolerates small structural changes by deforming the source detector while performing the transfer, and (c) part level transfer particularly for the cases where full template transfer is not possible due to aspect ratio mismatches or not having adequately similar sources. Building upon the idea of using part-level transfer, instead of performing an exhaustive sliding window search, part-based indexing is proposed for efficient evaluation of templates enabling us to obtain immediate detection results in large scale image collections. Furthermore, easier and more robust optimization methods are developed with the help of feature maps defined between proposed transfer learning formulations and the “classical” SVM formulation.

Currently, many educators are focusing on the development of Web-based material and the quality of such material needs to be evaluated. Expert review, as a formative evaluation method, is an important method to evaluate the material prior to release. Other studies have described the use of Subject-Matter Experts (SMEs) and also domain students, with enough knowledge in the subject area, as a way of enhancing the quality of the reviewed material. In addition to the SMEs and domain students a lecturer and graduate student, both in the subject discipline area, were used to review Web-based lectures on Advanced Computer Architectures. Both additional reviewers had sufficient knowledge of the discipline. The research investigates three main hypotheses: I) whether a review conducted by domain reviewers (SME and domain student) or discipline reviewers improves the quality of material, 2) whether using discipline reviewers improves the quality of the material more than domain reviewers and 3) whether there are differences in the quality of the material resulting from students' and lecturers' review. Five versions of the material were developed and used as inputs to an experiment that was designed to test the hypotheses by using questionnaires and tests. In summary, the findings of the research were that: SME reviewer and discipline reviewers were effective in producing higher quality than the unreviewed material. However, rather interestingly, the domain student was shown to be the least effective in enhancing the material. The investigation also found that there was no significant difference in the quality of the material resulting from students' and lecturers' review. Furthermore, it was found that the media used to present the material was more useful when the quality of that media was perceived to be high. Finally 90% of the subjects were willing to study Web-based lectures as part of the course.

This thesis investigates the vocabulary learning behavior of Romanian high school students in a digital context. The research identifies the vocabulary learning strategies used by EFL high school students and focuses on how the choice of vocabulary learning strategies varies across four independent variables: students' age, gender, academic profile (math-ICT, humanities, science and economic-technical) and language program (intensive English, bilingual, normal). These variables are hypothesized to influence learners' vocabulary behavior. Furthermore, the study examines the technology enhanced tools (computer and mobile assisted language learning tools) used by these students in their vocabulary learning as well as their attitudes towards using technology in vocabulary learning. Likewise, the study analyzes how students' choice of technology enhanced tools and their attitudes towards them vary across the four independent variables. The study is a mixed methods investigation with 1,239 participants (60% female, 40% male, aged 14-19 years old) learning English as a foreign language in nine Romanian secondary schools. Of the 1,239 participants who filled in the self-reported questionnaire, 43 also participated in focus group discussions prior to the administration of the questionnaire. The quantitative data were analyzed using descriptive and inferential statistics procedures whereas the qualitative data were analyzed thematically. The results from both phases were integrated in the results chapter. The main findings indicated that Romanian high school students prefer social strategies, followed by determination, metacognitive, cognitive and memory strategies. However, the usage of the strategies in these categories is medium towards low. As for individual vocabulary learning strategies, the participants reported that the impact of a new word, English media, guessing from context, associating the word with a picture and using cognates are frequently used strategies. The results also indicated that students' use of vocabulary learning strategies varies across the four independent variables. As far as the use of digital tools for vocabulary learning, the findings indicated that the students in this particular cultural context use few available digital tools with a preference for online dictionaries, games and social networking web sites. The results showed that overall Romanian students are not very familiar with computer and mobile assisted language learning tools, their attitudes towards the use of digital tools for vocabulary learning are neutral and they mostly associate the use of personal devices with their personal space, suggesting that they may not want to embed learning in their everyday activities. The results enrich existing knowledge of vocabulary learning strategies in a Romanian cultural context and they also give us an insight into how high school students use computer and mobile assisted language tools in their vocabulary learning. Implications for theory and practice are also discussed.

This thesis is about appearance-based topological mapping for mobile robots using vision and laser. Our goal is life-long continual operation in outdoor unstruc- tured workspaces. We present a new probabilistic framework for appearance-based mapping and navigation incorporating spatial and visual appearance. Locations are encoded prob- abilistically as random graphs possessing latent distributions over visual features and pair-wise euclidean distances generating observations modeled as 3D constellations of features observed via noisy range and visual detectors. Multi-modal distributions over inter-feature distances are learnt using non-parametric kernel density estima- tion. Inference is accelerated by executing a Delaunay tessellation of the observed graph with minimal loss in performance, scaling log-linearly with scene complexity. Next, we demonstrate how a robot can, through introspection and then targeted data retrieval, improve its own place recognition performance. We introduce the idea of a dynamic sampling set, the onboard workspace representation, that adapts with increasing visual experience of continually operating robot. Based on a topic based probabilistic model of images, we use a measure of perplexity to evaluate how well a working set of background images explains the robot’s online view of the world. O/ine, the robot then searches an external resource to seek additional background images that bolster its ability to localize in its environment when used next. Finally, we present an online and incremental approach allowing an exploring robot to generate apt and compact summaries of its life experience using canon- ical images that capture the essence of the robot’s visual experience-illustrating both what was ordinary and what was extraordinary. Leveraging probabilistic topic models and an incremental graph clustering technique we present an algorithm that scales well with time and variation of experience, generating a summary that evolves incrementally with the novelty of data.

The following question and sub-question guide this thesis project: 1) How does a service-learning approach in an arts-based technology course increase pre-service teacher receptivity to teaching technology? 2.) What are some barriers to teaching technology for pre-service teachers? A positive service-learning experience provides good learning models which have the potential to address the barriers to teaching technology for pre-service teachers by influencing their self-efficacy. Included in this thesis is a unit plan which responds to these research questions. There are many barriers to teaching technology for teachers including lack of funds, availability and quality of computer hardware and software, teaching models for using computer technology in instruction, time to learn to use computer technology, and teacher attitude (Rogers, 2000). A service-learning approach in an arts-based technology course could increase pre-service teacher receptivity to teaching technology by addressing these needs, the most important of which is providing pre-service teachers with a model for using computer technology in their instruction. Computer hardware and software availability is a problem which the teacher educator can address through writing a grant for funds, computer hardware and software, introducing the pre-service teachers to free and open source software, and negotiating with the partner school's administration and classroom teachers. Equally important is discussing this process with the pre-service teachers so they may learn from that experience. A positive experience teaching using computer technology has the potential to change pre-service teacher attitude about the ability of a teacher to influence students and their personal ability as a teacher (Wade, 1995; Root & Furco, 2001). Through service-learning, K-12 students and pre-service teachers have the opportunity to teach each other about digital art. It is through these unit plans that a mutual relationship is formed, which enables learning to occur on both ends. Throughout the unit plan, pre-service teachers are given time to reflect on their learning experiences and discuss what they are learning by working with the students. When teaching digital art to pre-service teachers, while it is important to give goals, guidelines and some basic instruction to lay the ground work for future discoveries, pre-service teachers and students alike need the opportunity to find the solutions to their own technical and artistic problems. The curricular ideas and unit plans contained within this thesis may serve as idea-generators for teacher educators interested in enriching their computer technology curriculum for pre-service teachers by incorporating service-learning into their practice. The big ideas were chosen to emphasize the idea of a learning community. Students and pre-service teachers develop a relationship over the course of teaching in which both learn from each other through the pre-service teachers' lessons and how the lessons are interpreted by the students. In effect, these unit plans are a beginning for future projects which integrate service-learning and the digital arts.

Guiding a representation towards capturing temporally coherent aspects present invideo improves object identity encoding. Existing models apply temporal coherenceuniformly over all features based on the assumption that optimal encoding of objectidentity only requires temporally stable components. We test the validity of this assumptionby exploring the effects of applying a mixture of temporally coherent invariantfeatures, alongside variable features, in a single 'mixed' representation. Applyingtemporal coherence to different proportions of the available features, we evaluate arange of models on a supervised object classification task. This series of experimentswas tested on three video datasets, each with a different complexity of object shape andmotion. We also investigated whether a mixed-representation improves the capture ofinformation components associated with object position, alongside object identity, ina single representation. Tests were initially applied using a single layer autoencoderas a test bed, followed by subsequent tests investigating whether similar behaviouroccurred in the more abstract features learned by a deep network. A representationapplying temporal coherence in some fashion produced the best results in all tests,on both single layered and deep networks. The majority of tests favoured a mixed representation,especially in cases where the quantity of labelled data available to thesupervised task was plentiful. This work is the first time a mixed-representation hasbeen investigated, and demonstrates its use as a method for representation learning.

The primary aim of this study was to validate interactive computer-assisted learning packages (ICALP) in a self operated computer controlled educational resource (SOCCER) to undergraduate (UG) physiotherapy students of anatomy. The development of ICALP, Test and FeedBack items for SOCCER are described, as well as the mechanism of delivery with continuous positive reinforcement to randomly selected students. To meet this requirement, a computer managed learning environment (CMLE) was established to affirm the value of ICALP and SOCCER materials to replace traditional lectures in anatomy. Quantitative data is given to verify this hypothesis during the education of UG physiotherapy students of anatomy. Throughout 1992, the UG population was randomly divided into Lecture and ICALP groups, with mutual exclusion of each to the other, for ten areas of study. These results were validated by re-application to the succeeding UG population in 1993. The secondary aim of this study was in two-parts. Firstly, to verify that ICALP materials can be applied to transfer 2-D cognitive anatomical information in a self-paced format of autonomous learning. Secondly, to investigate a premise that previously acquired 2-D anatomical information may be transferred into a 3-D psycho-motor skill. Ample data is given to verify the first hypothesis, with sufficient evidence to support the second. The subsidiary aim of this study compared the educational and administrative cost-effectiveness of ICALP and SOCCER with traditional lectures used in anatomy. Evidence is given to demonstrate that the time saved in lectures can be replaced by a lecture-seminar approach to problem-based learning to empower UG2 students to achieve at a level beyond that which would normally be expected. Sufficient data is provided to affirm the cost-benefits of ICALP and SOCCER to academic staff, individual students, and ++ / administrators. The untested belief held by schools of anatomy that high ranking pre-entrants in English, English Literature, and Human Biology, are more likely to transpose 2-D anatomical information into a 3-D skill than high ranking pre-entrants in Mathematics, Chemistry and Physics was also investigated. Scrutiny of these data could not determine any discriminatory differences of ability to succeed in UG anatomy by either of these two categories.

Thesis (M.S.)--Oregon State University, 2010. / Printout. Includes bibliographical references (leaves 48-51). Also available on the World Wide Web.