Data storage is an important practice for organisations that want to track their progress. The evolution of data storage technologies from manual methods of storing data on paper or in spreadsheets, to the automated methods of using computers to automatically log data into databases or text files has brought an amount of data that is beyond the level of human interpretation and comprehension. One way of addressing this issue of interpreting large amounts of data is data visualisation, which aims to convert abstract data into images that are easy to interpret. However, people often have difficulty in selecting an appropriate visualisation tool and visualisation techniques that can effectively visualise their data. This research proposes the processes that can be followed to effectively visualise data. Data logged from a mobile learning system is visualised as a proof of concept to show how the proposed processes can be followed during data visualisation. These processes are summarised into a model that consists of three main components: the data, the visualisation techniques and the visualisation tool. There are two main contributions in this research: the model to visualise mobile learning usage data and the visualisation of the usage data logged from a mobile learning system. The mobile learning system usage data was visualised to demonstrate how students used the mobile learning system. Visualisation of the usage data helped to convert the data into images (charts and graphs) that were easy to interpret. The evaluation results indicated that the proposed process and resulting visualisation techniques and tool assisted users in effectively and efficiently interpreting large volumes of mobile learning system usage data.

<p>Visualizing multidimensional spatial data is an essential visual analysis strategy, it helps us interpret and communicate how different variables correlate to geographical information. In this study, we proposed an abstract contextual visualization that encodes data on the boundaries of spatial distributions and developed a new algorithm, AuroraMap. AuroraMap projects the spatial data to the boundaries of the distributions and color-encodes the densities continuously. We further conducted the user experiments, and the results show users can detect the relative locations and scopes of the clusters. Furthermore, users can quantitatively determine the peak value of each cluster’s density. The method provides three contributions: (1) freeing up and saving the graphical visualization space; (2) assisting the users to quantitatively estimate the clusters inside distributions; (3) facilitating the visual comparisons for multiple and multivariate spatial distributions. In the end, we demonstrated two applications with real-world religious infrastructural data by AuroraMap to visualize geospatial data within complex boundaries and compare multiple variables in one graph.</p><p> </p>

Time-series data draw extensive attention from many research domains, such as financial and biomedical engineering. Researchers often face the difficultly of visualizing multiple time-series data simultaneously. The predominant techniques suffer from visual clutter either due to over-plotting or an overwhelming number of small graphs that carries a high cognitive load. This research study proposes a Colored slope, a combination of Tufte's slope graph and time-series heatmap, to visualize multiple time-series data at once, balancing scalability and accuracy. Colored slope inherits the complementary advantages from each method, regarding visualizing temporal changes within a period and identifying precise values. The efficacy, effectiveness, and graphical perception of the Colored slope on visualizing multiple time-series data with publicly accessible stock data were evaluated and compared it to popular time-series visualizations, including line graphs, time-series heatmap, and small multiple spark area graphs. Analyzing the experimental data, this study concludes that Colored slope contributes to (1) allowing users to identify the extreme values (maximum and minimum), co-variability, the general trend of the data, and rate of change effectively for an optimally large number of visual marks(time-series data); (2) capable of display more instances of time-series data with a less visual clutter problem. Finally, several possible applications and limitations with the Colored slope are demonstrated.

In this paper, we present an overview of a number of existing flow visualization methods, developed by the authors in the recent past, that are specifically aimed at integrating and leveraging domain-specific knowledge into the visualization process. These methods transcend the traditional divide between interactive exploration and featurebased schemes and allow a visualization user to benefit from the abstraction properties of feature extraction and topological methods while retaining intuitive and interactive control over the visual analysis process, as we demonstrate on a number of examples.

The world’s path to climate change is inevitable. Activists and legislators, all around the world, are actively working to slow down this process or stop changes. Technology is moving toward a sustainable future of renewable energy and resources to lighten the impact that the human population has on the climate. Whether or not these efforts will slow down the changing climate is unknown, but the world’s scientists, engineers, and designers are preparing for any scenario that comes our way. This thesis uses graphic design to visualize the future of humanity adapting to climate change. Topics that are explored include controlled-environment agriculture, vertical farming, sustainable food production, advancements in the medical industry, advancements in transportation, and sustainable energy production. These elements will come together, in my projects, to visualize one possible future of living in Arizona, where living conditions have become inhospitable for life as we know today. / Includes bibliography. / Thesis (M.F.A.)--Florida Atlantic University, 2020. / FAU Electronic Theses and Dissertations Collection

Indiana University-Purdue University Indianapolis (IUPUI) / Particle Swarm Optimization is a bio-inspired optimization technique used to approximately solve the non-deterministic polynomial (NP) problem of asset allocation in 3D space, frequency, antenna azimuth [1], and elevation orientation [1]. This research uses QT Data Visualization to display the PSO solutions, assets, transmitters in 3D space from the work done in [2]. Elevation and Imagery data was extracted from ARCGIS (a geographic information system (GIS) database) to add overlapping elevation and imagery data to that the 3D visualization displays proper topological data. The 3D environment range was improved and is now dynamic; giving the user appropriate coordinates based from the ARCGIS latitude and longitude ranges. The second part of the research improves the performance of the PSOs runtime, using OpenMP with CPU threading to parallelize the evaluation of the PSO by particle. Lastly, this implementation uses CPU multithreading with 4 threads to improve the performance of the PSO by 42% - 51% in comparison to running the PSO without CPU multithreading. The contributions provided allow for the PSO project to be more realistically simulate its use in the Electronic Warfare (EW) space, adding additional CPU multithreading implementation for further performance improvements.

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第19186号 / 工博第4063号 / 新制||工||1627(附属図書館) / 32178 / 京都大学大学院工学研究科電気工学専攻 / (主査)教授 小山田 耕二, 教授 小林 哲生, 教授 中村 裕一 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

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The purpose of this study was to determine if there is a correlation between spatial skills and creativity in interior design students. Participants were subjects who took a visualization assessment and created the 33 projects used in the study, and 11 judges, professional design experts who rated the projects. The sample of subjects was comprised of interior design students at a FIDER-accredited institution in southwest Virginia. The judges included interior design educators and interior design graduate students having previous practice experience. Subjects completed a pencil-and-paper Visualization Assessment consisting of 36 questions using two-dimensional and three-dimensional drawings (Isham, 1997). A percentage score for spatial skills was calculated for each subject based on the number of correct answers. Design projects created by the students were assessed by subjective ratings on three Dimensions of Judgment taken from the Consensual Technique for Creativity Assessment (Barnard, 1992; Amabile, 1982). The three dimensions used in this study included Appropriateness, Creativity, and Novelty. Ratings were collected in two judging sessions at a local site. Interjudge reliabilities exceeded the established criterion level (.70 or greater) on all three dimensions, with coefficients ranging from .729 to .866. Interjudge reliability for the Creativity dimension was .866, indicating a high level of agreement among judges on creativity. Intercorrelations among the dimensions indicated a high degree of association between the variables with Appropriateness and Novelty both significantly correlated with the Creativity dimension. Pearson product-moment correlation was used to determine if there was a significant correlation between visualization and creativity in interior design students. No significant correlation was found. / Master of Science

My research focused on three projects: (1) investigation of the mental models of students of the microscopic world using a molecular dynamic visualization, (2) evaluation of an online module on students’ skills related to electron-pushing formalism, and (3) a two-part investigation of how 10 essential learning outcomes (LOs) about delocalization were intended, enacted, and achieved. Project 1: Exploring participants mental models of the sub-microscopic level after viewing a molecular dynamic visualization. The effect of two molecular dynamic simulations on students’ mental models about motion, collisions, and probabilistic thinking was investigated via a qualitative study. We administered a worksheet and interviewed the participants both before and after they viewed the visualizations. The analysis showed that (1) participants all had a motion mental model, (2) participants used different mental models depending on the situation, (3) participants had conflicting mental models of randomness of the sub-microscopic level, and (4) participants experienced cognitive dissonance when viewing the simulation. Project 2: Evaluation of OrgChem101.com online module of students’ skills using EPF. We investigated students’ skills on the electron-pushing formalism after using an online learning module called “Organic Mechanisms: Mastering the Arrows” using a quantitative experimental method. There were significant learning gains between the pre- and post-test, especially with questions that asked students to draw the products of a reaction. After using the learning tool, students used more analysis strategies, such as mapping, attempted more questions, and made fewer errors. Project 3.1: Determining essential LOs for delocalization and how they are taught, practiced, and assessed. The 10 LOs about delocalization (i.e., resonance) were determined from a textbook analysis then investigated for how they are being enacted, meaning how they were taught, practiced, assessed. We have found that five themes emerged from the analysis: (1) Several of the essential intended LOs we identified are not represented in the textbooks’ teaching explanations, practice questions, or professors’ assessments; (2) The concepts related to delocalization are often taught, practiced, and assessed without associated justifications; (3) There is a large gap between when delocalization is taught and when it is used in context; (4) The link between delocalization and other concepts (e.g., reactivity) is not explicitly explained in most teaching materials; and (5) The language used around delocalization may be misleading (e.g. resonance, stability). Project 3.2: Investigating how the 10 essential delocalization LOs are achieved on summative examination. We then analyzed how the students achieved the 10 essential LOs about delocalization on a summative assessment by analyzing 12 questions related to the concept. We found that students sometimes struggled to identify when delocalization could occur, that some of the LOs built on one another, and that some strategies (visualizing electrons, listing properties, and expanding the structures) more often led to the correct answer. We also found that when explicitly asked students in organic chemistry one was more successfully than in organic chemistry II and that the opposite occurs when asked within a mechanism. Our analysis of student reasoning showed that the dominant modes of reasoning were aligned with the related expectations and explanations in the course. When asked to justify the contribution of resonance structures to the resonance hybrid, most answers analyzed showed a descriptive mode of reasoning; when asked to explain why a given proton was more acidic than another, most answers contained relational and linear causal reasoning.