Zobrazeno 1 - 10
of 50
pro vyhledávání: '"William J. Tolone"'
Autor:
William J. Tolone
The Virtual Information-Fabric Infrastructure (VIFI) is a novel cyberinfrastructure that facilitates data-driven discovery from distributed, fragmented, and un-shareable data without requiring the movement of massive amounts of data or directly expos
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5b87240b674da2ad95afea1578e03031
Autor:
Abdullah-Al-Raihan Nayeem, Huikyo Lee, Dongyun Han, Mohammad Elshambakey, William J. Tolone, Todd Dobbs, Daniel Crichton, Isaac Cho
This paper introduces a novel visual analytics approach, DCPViz, to enable climate scientists to explore massive climate data interactively without requiring the upfront movement of massive data. Thus, climate scientists are afforded more effective a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::844b8fa616e0fcac1cd6f3336d25c8fc
Publikováno v:
Future Generation Computer Systems. 100:365-379
This paper presents a semi-supervised, multi-view, active learning method, which uses an optimized set of most informative samples and utilizes domain specific context information to efficiently and effectively identify malicious forum content in web
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1189c1466272492ebafaed19690bed98
https://doi.org/10.1016/j.future.2019.03.015
https://doi.org/10.1016/j.future.2019.03.015
Autor:
Xun Wang, Liping Cai, Yong X. Tao, William J. Tolone, Sreyasee Das Bhattacharjee, Isaac Cho, Zhenhua Huang, Mohammed Elshambakey
Publikováno v:
Journal of Performance of Constructed Facilities. 34
To predict the hazard-induced risks of buildings and infrastructures and assess the losses caused by hazards, the fragility curve method is a common quantitative risk assessment procedure f...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c2795dab8359197c19d876adee922415
https://doi.org/10.1061/(asce)cf.1943-5509.0001414
https://doi.org/10.1061/(asce)cf.1943-5509.0001414
Autor:
Junsong Yuan, Ashish Mahabal, Abdullah al-Raihan Nayeem, Mohammed Elshambakey, Isaac Cho, Sreyasee Das Bhattacharjee, George Djorgovski, William J. Tolone
Publikováno v:
IEEE BigData
In this paper, we propose an effective, multi-view, generative, transfer learning framework for multivariate time-series data. While generative models are demonstrated effective for several machine learning tasks, their application to time-series cla
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::17cdaeeb3ead0efe760c8bc731b0f16e
https://doi.org/10.1109/bigdata47090.2019.9005452
https://doi.org/10.1109/bigdata47090.2019.9005452
Autor:
Khee Poh Lam, William J. Tolone, Suraj Talele, Thomas Spiegelhalter, Richard C. Feiock, Caleb Traylor, Dale Yeatts, Chien-fei Chen, Stan Ingman, Svetlana Pevnitskaya, Mirsad Hadzikadic, Laura M. Arpan, Julia K. Day, Carol C. Menassa, Yong X. Tao, Omer T. Karaguzel, Wei Yan, Cali Curley, Yimin Zhu
Publikováno v:
Frontiers in Energy. 12:314-332
This paper contributes an inclusive review of scientific studies in the field of sustainable human building ecosystems (SHBEs). Reducing energy consumption by making buildings more energy efficient has been touted as an easily attainable approach to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7997e5c102ddb35b7aec395a25d670bd
https://doi.org/10.1007/s11708-017-0530-2
https://doi.org/10.1007/s11708-017-0530-2
Autor:
Omer T. Karaguzel, Wenwen Dou, Tianzhen Hong, Mohammed Elshambakey, Haopeng Wang, Isaac Cho, Yong X. Tao, William J. Tolone, Sreyasee Das Bhattacharjee, Mohamed E. Khalefa, Yimin Zhu, Siliang Lu
Publikováno v:
Journal of Computing in Civil Engineering, vol 33, iss 6
Building energy simulation plays an increasingly important role in building design and operation. This paper presents an open computing infrastructure, Virtual Information Fabric Infrastructure (VIFI), that allows building designers and engineers to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f211ea0da43af4180afe20dd1263c33c
https://doi.org/10.1061/(asce)cp.1943-5487.0000857
https://doi.org/10.1061/(asce)cp.1943-5487.0000857
Autor:
Isaac Cho, William J. Tolone, Ashish Mahabal, Mohammed Elshambakey, George Djorgovski, Sreyasee Das Bhattacharjee
Publikováno v:
COMPSAC (1)
In this paper, we propose an effective, multi-view, deep, transfer learning framework for multivariate time-series data. Though widely used for tasks such as computer vision, the application of transfer learning to time-series classification problems
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::087c52e00068bcbf13f949a3de84c406
https://doi.org/10.1109/compsac.2019.00061
https://doi.org/10.1109/compsac.2019.00061
Autor:
William J Tolone
Publikováno v:
Current Trends in Civil & Structural Engineering. 4
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a168d8c54b9845ccc2fcf2c7dc97f10b
https://doi.org/10.33552/ctcse.2019.04.000585
https://doi.org/10.33552/ctcse.2019.04.000585
Autor:
Isaac Cho, George Djorgovski, Sreyasee Das Bhattacharjee, Mohammed Elshambakey, Ashish Mahabal, William J. Tolone
Publikováno v:
IEEE BigData
In this paper, we propose an effective, multi-view, multivariate deep classification model for time-series data. Multi-view methods show promise in their ability to learn correlation and exclusivity properties across different independent information
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cf7a4c612be28122409f0632d4942131
https://doi.org/10.1109/bigdata.2018.8622253
https://doi.org/10.1109/bigdata.2018.8622253