Jina Jang
Biographic Data
| ID | 9903739 |
|---|---|
| NAME | Jina Jang |
| GIVEN NAMES | Jina |
| FAMILY NAME | Jang |
| SIGNATURE | JANG J |
| AFFILIATIONS | Kyung Hee University |
| ORCID | 0000-0002-4318-9355 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Uncovering Fishing Area Patterns Using Convolutional Autoencoder and Gaussian Mixture Model on Viirs Nighttime Imagery
The availability of nighttime satellite imagery provides unique opportunities for monitoring fishing activity in data-sparse ocean regions. This study leverages Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band monthly composite imagery to identify and classify recurring spatial patterns of fishing activity in the Korean Exclusive Economic Zone from 2014 to 2024. While prior research has primarily produced static hotspot maps, our …
Quantifying Percent Traffic Congestion (pTC) and Mobility Bottleneck Dynamics at Atlanta’s Spaghetti Junction
Highway interchanges are vulnerable components of transport networks, often prone to congestion and crashes. Traditional monitoring methods like loop detectors or travel time queries often fail to capture the granular spatiotemporal distribution of bottlenecks in detail. To address this gap, this study introduces a new approach to quantify congestion and analyze bottleneck dynamics at Atlanta’s Tom Moreland Interchange, one of the nation’s most c…
No prominent works on this page.
Quantifying Percent Traffic Congestion (pTC) and Mobility Bottleneck Dynamics at Atlanta’s Spaghetti Junction
Highway interchanges are vulnerable components of transport networks, often prone to congestion and crashes. Traditional monitoring methods like loop detectors or travel time queries often fail to capture the granular spatiotemporal distribution of bottlenecks in detail. To address this gap, this study introduces a new approach to quantify congestion and analyze bottleneck dynamics at Atlanta’s Tom Moreland Interchange, one of the nation’s most c…
Uncovering Fishing Area Patterns Using Convolutional Autoencoder and Gaussian Mixture Model on Viirs Nighttime Imagery
The availability of nighttime satellite imagery provides unique opportunities for monitoring fishing activity in data-sparse ocean regions. This study leverages Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band monthly composite imagery to identify and classify recurring spatial patterns of fishing activity in the Korean Exclusive Economic Zone from 2014 to 2024. While prior research has primarily produced static hotspot maps, our …
Autoencoder (1 work) · Automated Road and Building Extraction (1 work) · Bottleneck (1 work) · Congestion management (1 work) · Fishing (1 work) · Geolocation (1 work) · Impact of Light on Environment and Health (1 work) · Marine and coastal ecosystems (1 work) · Mixture model (1 work) · Network congestion (1 work)