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Nii Attoh-Okine

As seen in: MDPI, Railway Track & Structures
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Articles

Railway Track Quality Assessment Using Topological Data Analysis

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By Petros Woldemariam, Nii Attoh-Okine, F.ASCEAuthor Affiliations
| ascelibrary.org
Practical Applications The topological track index (TTI) provides a practical enhancement to existing railway track monitoring and maintenance practices by capturing spatially structured geometric irregularities that may be underrepresented by conventional track quality indices (TQI). Current industry workflows rely primarily on statistical measures derived from track geometry inspection data to identify locations requiring corrective action.
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Topological Data Analysis for Railway Track Geometry Safety and Maintenance

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By Nii Attoh-Okine, F.ASCE Affiliations, Petros Woldemariam
| ascelibrary.org
: Journal of Computing in Civil Engineering Volume 39, Issue 5 Get full access to this article View all available purchase options and get full access to this article. Data Availability Statement Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
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Predicting Fatty Acid Classes in Popular US Snacks Using NHANES Data and Machine Learning Approaches

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By Nii Attoh-Okine, Daniel Obiri-Ananey, Nii Adjetey Tawiah, Christabel Y. E
| MDPI
This is an early access version, the complete PDF, HTML, and XML versions will be available soon. Open AccessArticle by Christabel Y. E. Tachie 1, Daniel Obiri-Ananey 2, Nii Adjetey Tawiah 3, Nii Attoh-Okine 4 and Alberta N. A.
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