Browsing by Author "Wang, Ming"

Now showing 1 - 6 of 6
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    Bridging Cognitive Gaps Between User and Model in Interactive Dimension Reduction
    Wang, Ming (Virginia Tech, 2020-05-05)
    High-dimensional data is prevalent in all domains but is challenging to explore. Analysis and exploration of high-dimensional data are important for people in numerous fields. To help people explore and understand high-dimensional data, Andromeda, an interactive visual analytics tool, has been developed. However, our analysis uncovered several cognitive gaps relating to the Andromeda system: users do not realize the necessity of explicitly highlighting all the relevant data points; users are not clear about the dimensional information in the Andromeda visualization; and the Andromeda model cannot capture user intentions when constructing and deconstructing clusters. In this study, we designed and implemented solutions to address these gaps. Specifically, for the gap in highlighting all the relevant data points, we introduced a foreground and background view and distance lines. Our user study with a group of undergraduate students revealed that the foreground and background views and distance lines could significantly alleviate the highlighting issue. For the gap in understanding visualization dimensions, we implemented a dimension-assist feature. The results of a second user study with students with various backgrounds suggested that the dimension-assist feature could make it easier for users to find the extremum in one dimension and to describe correlations among multiple dimensions; however, the dimension-assist feature had only a small impact on characterizing the data distribution and assisting users in understanding the meanings of the weighted multidimensional scaling (WMDS) plot axes. Regarding the gap in creating and deconstructing clusters, we implemented a solution utilizing random sampling. A quantitative analysis of the random sampling strategy was performed, and the results demonstrated that the strategy improved Andromeda's capabilities in constructing and deconstructing clusters. We also applied the random sampling to two-point manipulations, making the Andromeda system more flexible and adaptable to differing data exploration tasks. Limitations are discussed, and potential future research directions are identified.
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    Bridging cognitive gaps between user and model in interactive dimension reduction
    Wang, Ming; Wenskovitch, John; House, Leanna L.; Polys, Nicholas F.; North, Christopher L. (2021-06)
    Interactive machine learning (ML) systems are difficult to design because of the "Two Black Boxes" problem that exists at the interface between human and machine. Many algorithms that are used in interactive ML systems are black boxes that are presented to users, while the human cognition represents a second black box that can be difficult for the algorithm to interpret. These black boxes create cognitive gaps between the user and the interactive ML model. In this paper, we identify several cognitive gaps that exist in a previously-developed interactive visual analytics (VA) system, Andromeda, but are also representative of common problems in other VA systems. Our goal with this work is to open both black boxes and bridge these cognitive gaps by making usability improvements to the original Andromeda system. These include designing new visual features to help people better understand how Andromeda processes and interacts with data, as well as improving the underlying algorithm so that the system can better implement the intent of the user during the data exploration process. We evaluate our designs through both qualitative and quantitative analysis, and the results confirm that the improved Andromeda system outperforms the original version in a series of high-dimensional data analysis tasks. (C) 2021 The Author(s). Published by Elsevier B.V. on behalf of Zhejiang University and Zhejiang University Press Co. Ltd.
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    Exploration of Shape Memory Polymer for Automotive Coating Applications
    Wang, Ming (Virginia Tech Department of Materials Science and Engineering, 2015-01-01)
    Shape memory polymer (SMP) is one special kind of polymer which can recover back to permanent shape after being mechanically deformed. As for automotive coating, most of the defects occurs on the clear coat layer, if it can be replaced by shape memory polymer, the defects can be easily removed due to the self-healing ability of shape memory polymer. In this experiment, the self-healing ability of epoxy based shape memory polymer thin lm (around 100μm) is examined. Five indents on the thin lm shape memory polymer with depths from 4.9μm to 5.5μm are all disappeared after 15 minutes heating at 70oC. The average hardness of the polymer is 165 ± 2MPa and the modulus is 5.76 ± 0.02GPa (assume Possion’s ratio 0.4).
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    Isolation and Structure Elucidation of Antiproliferative and Antiplasmodial Natural Products from Plants
    Wang, Ming (Virginia Tech, 2016-12-19)
    As part of an International Cooperative Biodiversity Group (ICBG) program and a collaborative research project with the Natural Products Discovery Institute, four plant extracts were investigated for their antiproliferative and antiplasmodial activities. With the guidance of bioassay guided fractionation, two known antiproliferative terpenoids (2.1 and 2.2) were isolated from Hypoestes sp. (Acanthaceae), four known antiplasmodial liminoids (3.1-3.4) were isolated from Carapa guianensis (Meliaceae), one inactive terpenoid (4.1) was isolated from Erica maesta (Ericaceae), and four cerebrosides (4.2-4.5) were obtained from Hohenbergia antillana (Bromeliaceae). The structures of these compounds were elucidated by using 1D (1H and 13C), 2D (HMBC, HSQC, COSY, NOESY) NMR spectroscopy and mass spectrometry. The structures of the compounds were also confirmed by comparing them with reported values from the literature. Compounds 2.1 and 2.2 showed moderate antiproliferative activity against the A2780 human ovarian cancer cell line with IC50 values of 6.9 uM and 3.4 uM, respectively. They also exhibited moderate antiplasmodial activity against chloroquine-resistant Plasmodium falciparum strain Dd2 with IC50 values of 9.9 ± 1.4 uM and 2.8 ± 0.7 uM, respectively. Compounds 3.1 to 3.4 had moderate antiplasmodial activity against Plasmodium falciparum Dd2 strain with IC50 values of 2.0 ± 0.3 uM, 2.1 ± 0.1 uM, 2.1 ± 0.2 uM and 2.8 ± 0.2 uM, respectively. Compounds 4.1 and 4.2 showed very weak antiplasmodial activity against Plasmodium falciparum Dd2 strain, with IC50 values between 5 and 10 ug/mL.
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