Research articles, presentations, and other scholarship

Recent Submissions

  • Process-Guided Deep Learning Predictions of Lake Water Temperature 

    Read, Jordan S.; Jia, Xiaowei; Willard, Jared; Appling, Alison P.; Zwart, Jacob A.; Oliver, Samantha K.; Karpatne, Anuj; Hansen, Gretchen J. A.; Hanson, Paul C.; Watkins, William; Steinbach, Michael; Kumar, Vipin (2019-11-08)
    The rapid growth of data in water resources has created new opportunities to accelerate knowledge discovery with the use of advanced deep learning tools. Hybrid models that integrate theory with state-of-the art empirical ...
  • Web Archiving and Digital Libraries 

    Xie, Zhiwu; Klein, Martin; Fox, Edward A. (ACM, 2020-08)
    This workshop will explore integration of Web archiving and digital libraries and cover all stages of its complete life cycle, including creation/authoring, uploading/publishing, crawling, indexing, exploration, and ...
  • Exploring the Consistency of the Quality Scores with Machine Learning for Next-Generation Sequencing Experiments 

    Cosgun, Erdal; Oh, Min (2020-02-26)
    Background. Next-generation sequencing enables massively parallel processing, allowing lower cost than the other sequencing technologies. In the subsequent analysis with the NGS data, one of the major concerns is the ...
  • Measurement of Step Angle for Quantifying the Gait Impairment of Parkinson's Disease by Wearable Sensors: Controlled Study 

    Wang, Jingying; Gong, Dawei; Luo, Huichun; Zhang, Wenbin; Zhang, Lei; Zhang, Han; Zhou, Junhong; Wang, Shouyan (2020-03-20)
    Background: Gait impairments including shuffling gait and hesitation are common in people with Parkinson's disease (PD), and have been linked to increased fall risk and freezing of gait. Nowadays the gait metrics mostly ...
  • A hybrid stochastic model of the budding yeast cell cycle 

    Ahmadian, Mansooreh; Tyson, John J.; Peccoud, Jean; Cao, Yang (2020-03-27)
    The growth and division of eukaryotic cells are regulated by complex, multi-scale networks. In this process, the mechanism of controlling cell-cycle progression has to be robust against inherent noise in the system. In ...
  • Evaluating visual channels for multivariate map visualization 

    Mohammed, A.; Polys, Nicholas F.; Sforza, Peter (EuroGraphics, 2018-06-04)
    Visual differencing, or visual discrimination, is the ability to differentiate between two or more objects in a scene depending on the values of certain attributes. Focusing on multivariate maps visualization, this work ...
  • Three-dimensional Organization of Polytene Chromosomes in Somatic and Germline Tissues of Malaria Mosquitoes 

    George, Phillip; Kinney, Nicholas A.; Liang, Jiangtao; Onufriev, Alexey V.; Sharakhov, Igor V. (MDPI, 2020-02-01)
    Spatial organization of chromosome territories and interactions between interphase chromosomes themselves, as well as with the nuclear periphery, play important roles in epigenetic regulation of the genome function. However, ...
  • Access to Autism Spectrum Disorder Services for Rural Appalachian Citizens 

    Scarpa, Angela; Jensen, Laura S.; Gracanin, Denis; Ramey, Sharon L.; Dahiya, Angela V.; Ingram, L. Maria; Albright, Jordan; Gatto, Alyssa J.; Scott, Jen Pollard; Ruble, Lisa (2020-01)
    Background: Low-resource rural communities face significant challenges regarding availability and adequacy of evidence-based services. Purposes: With respect to accessing evidence-based services for Autism Spectrum ...
  • Hypergraph-based connectivity measures for signaling pathway topologies 

    Franzese, Nicholas; Groce, Adam; Murali, T. M.; Ritz, Anna (2019-10)
    Signaling pathways describe how cells respond to external signals through molecular interactions. As we gain a deeper understanding of these signaling reactions, it is important to understand how molecules may influence ...
  • Unsupervised discovery of solid-state lithium ion conductors 

    Zhang, Ying; He, Xingfeng; Chen, Zhiqian; Bai, Qiang; Nolan, Adelaide M.; Roberts, Charles A.; Banerjee, Debasish; Matsunaga, Tomoya; Mo, Yifei; Ling, Chen (2019-11-20)
    Although machine learning has gained great interest in the discovery of functional materials, the advancement of reliable models is impeded by the scarcity of available materials property data. Here we propose and demonstrate ...
  • Strongly Bent Double-Stranded DNA: Reconciling Theory and Experiment 

    Drozdetski, Aleksander V.; Mukhopadhyay, Abhishek; Onufriev, Alexey V. (2019-11-29)
    The strong bending of polymers is poorly understood. We propose a general quantitative framework of polymer bending that includes both the weak and strong bending regimes on the same footing, based on a single general ...
  • Application and Evaluation of Surrogate Models for Radiation Source Search 

    Cook, Jared A.; Smith, Ralph C.; Hite, Jason M.; Stefanescu, Razvan; Mattingly, John (MDPI, 2019-12-12)
    Surrogate models are increasingly required for applications in which first-principles simulation models are prohibitively expensive to employ for uncertainty analysis, design, or control. They can also be used to approximate ...
  • A Bayesian approach to multivariate adaptive localization in ensemble-based data assimilation with time-dependent extensions 

    Popov, Andrey A.; Sandu, Adrian (Copernicus Publications, 2019-06-14)
    Ever since its inception, the ensemble Kalman filter (EnKF) has elicited many heuristic approaches that sought to improve it. One such method is covariance localization, which alleviates spurious correlations due to finite ...
  • Uncovering missed indels by leveraging unmapped reads 

    Hasan, Mohammad Shabbir; Wu, Xiaowei; Zhang, Liqing (Springer Nature, 2019-07-31)
    In current practice, Next Generation Sequencing (NGS) applications start with mapping/aligning short reads to the reference genome, with the aim of identifying genetic variants. Although existing alignment tools have shown ...
  • Stratified Feature Sampling for Semi-Supervised Ensemble Clustering 

    Tian, Jialin; Ren, Yazhou; Cheng, Xiang (IEEE, 2019)
    Ensemble Clustering (EC), which seeks to generate a consensus clustering by integrating multiple base clusterings, has attracted increasing attentions. However, traditional EC methods typically have three main limitations: ...
  • BRIoT: Behavior Rune Specification-Based Misbehavior Detection for IoT-Embedded Cyber-Physical Systems 

    Sharma, Vishal; You, Ilsun; Vim, Kangbin; Chen, Ing-Ray; Cho, Jin-Hee (IEEE, 2019)
    The identification of vulnerabilities in a mission-critical system is one of the challenges faced by a cyber-physical system (CPS). The incorporation of embedded Internet of Things (IoT) devices makes it tedious to identify ...
  • Identifying Transcriptional Regulatory Modules Among Different Chromatin States in Mouse Neural Stem Cells 

    Banerjee, Sharmi; Zhu, Hongxiao; Tang, Man; Feng, Wu-chun; Wu, Xiaowei; Xie, Hehuang (Frontiers, 2019-01-15)
    Gene expression regulation is a complex process involving the interplay between transcription factors and chromatin states. Significant progress has been made toward understanding the impact of chromatin states on gene ...
  • Acoustic differences between healthy and depressed people: a cross-situation study 

    Wang, Jingying; Zhang, Lei; Liu, Tianli; Pan, Wei; Hu, Bin; Zhu, Tingshao (2019-10-15)
    Abstract Background Abnormalities in vocal expression during a depressed episode have frequently been reported in people with depression, but less is known about if these ...
  • Brain-wide cellular resolution imaging of Cre transgenic zebrafish lines for functional circuit-mapping 

    Tabor, Kathryn M.; Marquart, Gregory D.; Hurt, Christopher; Smith, Trevor S.; Geoca, Alexandra K.; Bhandiwad, Ashwin A.; Subedi, Abhignya; Sinclair, Jennifer L.; Rose, Hannah M.; Polys, Nicholas F.; Burgess, Harold A. (2019-02-08)
    Decoding the functional connectivity of the nervous system is facilitated by transgenic methods that express a genetically encoded reporter or effector in specific neurons; however, most transgenic lines show broad ...
  • Hinge-Loss Markov Random Fields and Probabilistic Soft Logic 

    Bach, Stephen H.; Broecheler, Matthias; Huang, Bert; Getoor, Lise (MIT Press, 2017)
    A fundamental challenge in developing high-impact machine learning technologies is balancing the need to model rich, structured domains with the ability to scale to big data. Many important problem areas are both richly ...

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