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    Prediction of Structural Deficiency Ratio of Bridges Based on Multiway Data Factorization 

    Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2017:;Volume ( 003 ):;issue: 002
    Author(s): Offei Adarkwa; Nii Attoh-Okine
    Publisher: American Society of Civil Engineers
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    Random Forest–Based Covariate Shift in Addressing Nonstationarity of Railway Track Data 

    Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2021:;Volume ( 007 ):;issue: 003:;page 04021028-1
    Author(s): Ibrahim Balogun; Nii Attoh Okine
    Publisher: ASCE
    Abstract: The multimodal transportation network in which freight rail plays an essential role continues to enhance the United States’ contributions in the global market. For years, track geometry defects data have been often gathered ...
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    Multiway Analytics Applied to Railway Track Geometry and Ballast Conditions 

    Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2025:;Volume ( 011 ):;issue: 001:;page 04024079-1
    Author(s): Petros Woldemariam; Nii Attoh-Okine
    Publisher: American Society of Civil Engineers
    Abstract: Railroad systems generate large amounts of data, which, when effectively analyzed, can significantly enhance maintenance decisions to improve safety and system performance. Tensor decomposition, as an advanced multidimensional ...
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    Using Tensor Factorization to Predict Network-Level Performance of Bridges 

    Source: Journal of Infrastructure Systems:;2017:;Volume ( 023 ):;issue: 003
    Author(s): Offei Adarkwa; Nii Attoh-Okine; Thomas Schumacher
    Publisher: American Society of Civil Engineers
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    Novel Approach in Pipe Condition Scoring 

    Source: Journal of Pipeline Systems Engineering and Practice:;2011:;Volume ( 002 ):;issue: 003
    Author(s): Mary Cate Opila; Nii Attoh-Okine
    Publisher: American Society of Civil Engineers
    Abstract: A major challenge in sewer and water pipe infrastructure management is determining structural condition scores for pipe assets. The methodology used to determine the condition of pipes should be relevant, repeatable, and ...
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    Hybrid Particle Swarm Optimization and K-Means Analysis for Bridge Clustering Based on National Bridge Inventory Data 

    Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2017:;Volume ( 003 ):;issue: 002
    Author(s): Silvia Galvan-Nunez; Nii Attoh-Okine
    Publisher: American Society of Civil Engineers
    Abstract: Because of budget constraints for maintaining highway bridges in the United States, it is necessary to accurately monitor bridge structures so that repair and rehabilitation strategies can be performed. In this paper, an ...
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    Hybrid Particle Swarm Optimization and K-Means Analysis for Bridge Clustering Based on National Bridge Inventory Data 

    Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2017:;Volume ( 003 ):;issue: 002
    Author(s): Silvia Galvan-Nunez; Nii Attoh-Okine
    Publisher: American Society of Civil Engineers
    Abstract: Because of budget constraints for maintaining highway bridges in the United States, it is necessary to accurately monitor bridge structures so that repair and rehabilitation strategies can be performed. In this paper, an ...
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    Bivariate Severity Analysis of Train Derailments using Copula-Based Regression Models 

    Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2018:;Volume ( 004 ):;issue: 004
    Author(s): Martey Emmanuel Nii;Attoh-Okine Nii
    Publisher: American Society of Civil Engineers
    Abstract: The far-reaching consequences of train derailments have been a major concern to industry and government despite their relatively low occurrence. These consequences include injury, loss of life and property, interruption ...
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    Erratum for “Hybrid Particle Swarm Optimization and K-Means Analysis for Bridge Clustering Based on National Bridge Inventory Data” by Silvia Galvan-Nunez and Nii Attoh-Okine 

    Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2017:;Volume ( 003 ):;issue: 003
    Author(s): Silvia Galvan-Nunez; Nii Attoh-Okine
    Publisher: American Society of Civil Engineers
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    Risk and Advantages of Federated Learning for Health Care Data Collaboration 

    Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2020:;Volume ( 006 ):;issue: 003
    Author(s): Anna Bogdanova; Nii Attoh-Okine; Tetsuya Sakurai
    Publisher: ASCE
    Abstract: This paper explores the problem of data collaboration in health care, which is the one of the critical infrastructure sectors designated by the Department of Home Security. Limitations to data sharing in health care obstruct ...
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