Now showing items 1-10 of 10

    • Algorithmic Approaches for Determining Spatial Patterns in Several Biomedical Applications 

      Chen, Zihe (State University of New York at Buffalo, 2019)
      Finding the structural pattern from a set of objects is a commonly encountered prototype learning problem and has a wide range of applications in machine learning and pattern recognition. In cell biology, there is growing ...
    • Algorithms for Relation Extraction from Biomedical Texts 

      Liu, Sijia; 0000-0001-9763-1164 (State University of New York at Buffalo, 2019)
      The boost in the capacity and volume of biomedical texts, including biomedical literatures and electronic health records (EHRs), has created a tremendous opportunity for biomedical research and practice. It is widely ...
    • Application of Inertial Measurement Unit (IMU) in Advanced Human Health and Safety Surveillance: A Data Fusion and Machine Learning Approach 

      Baghdadi, Amir; 0000-0001-7245-8270 (State University of New York at Buffalo, 2019)
      Accurate and reliable quantification of human physical and physiological state using wearable sensing devices is paramount in health monitoring and safety surveillance, which necessitates the measurement of relevant signals ...
    • Approaches to Extract Deep Phenotypes from Clinical Data 

      Luong, Duc Thanh Anh; 0000-0003-4768-5089 (State University of New York at Buffalo, 2019)
      Computational phenotyping is an emerging topic in health informatics. An important catalyst of this emergence is the increasing volume of clinical data available for analysis. However, clinical data typically consists of ...
    • Efficient and Scalable Metadata Access for Distributed Applications from Edge to the Cloud 

      Zhang, Bing; 0000-0002-5590-0001 (State University of New York at Buffalo, 2019)
      We are witnessing a new era that offers new opportunities to conduct data-intensive scientific research with the help of recent advancements in computational, storage, and network technologies. With the rapid deployment ...
    • Flexible Data Management on Mobile Systems 

      Chandrashekhara, Sharath; 0000-0002-9952-320 (State University of New York at Buffalo, 2019)
      Mobile systems have gradually become the predominant platform for everyday computing, and their capabilities are getting powerful by the day. Apps on mobile systems employ sophisticated data management solutions by making ...
    • GPGPU–Based Fast Counting in Machine Learning Applications 

      Greenbaum, Marc (State University of New York at Buffalo, 2019)
      We propose a new method to execute counting queries using General Purpose Graphical Processing Units (GPGPUs). Counting queries are used to provide conditional probabilities in machine learning applications, but are ...
    • Moral Psychology: An Ontological Approach 

      Otte, Jeff; 0000-0001-7925-2064 (State University of New York at Buffalo, 2019)
      In information science, an ontology is a controlled vocabulary that provides names and definitions for the classes and relations among entities within a realm of discourse, and which can then be used to make interoperable ...
    • Multi-omic integrative network analysis 

      Ma, Tianle; 0000-0003-2309-1489 (State University of New York at Buffalo, 2019)
      With advanced biotechnology, we have accumulated vast amounts of genomic, epigenomic, transcriptomic, and proteomic data -- collectively called multi-omic data. Integrating and analyzing these multi-omic data poses great ...
    • TOWARDS DEPENDABLE NETWORK FUNCTION VIRTUALIZATION SERVICES 

      Fan, Jingyuan (State University of New York at Buffalo, 2019)
      Despite the great momentum NFV has gained over the last few years, a closer look under the hood reveals that NFV introduces numerous dependability challenges. Compared to traditional IT applications with the availability ...