5 papers
STDiff: A State Transition Diffusion Framework for Time Series Imputation in Industrial Systems
Gary Simethy, Daniel Ortiz-Arroyo, Petar Durdevic
Incomplete sensor data is a major obstacle in industrial time-series analytics. In wastewater treatment plants (WWTPs), key sensors show long, irregular gaps caused by fouling, mai…
CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text
Anju Rani, Daniel Ortiz-Arroyo, Petar Durdevic
Understanding the temporal dynamics of biological growth is critical across diverse fields such as microbiology, agriculture, and biodegradation research. Although vision-language…
FungalZSL: Zero-Shot Fungal Classification with Image Captioning Using a Synthetic Data Approach
Anju Rani, Daniel O. Arroyo, Petar Durdevic
The effectiveness of zero-shot classification in large vision-language models (VLMs), such as Contrastive Language-Image Pre-training (CLIP), depends on access to extensive, well-a…
Synthetic Fungi Datasets: A Time-Aligned Approach
A. Rani, D. O. Arroyo, P. Durdevic
Fungi undergo dynamic morphological transformations throughout their lifecycle, forming intricate networks as they transition from spores to mature mycelium structures. To support…
Application of Soft Actor-Critic Algorithms in Optimizing Wastewater Treatment with Time Delays Integration
Esmaeel Mohammadi, Daniel Ortiz-Arroyo, Aviaja Anna Hansen +4
Wastewater treatment plants face unique challenges for process control due to their complex dynamics, slow time constants, and stochastic delays in observations and actions. These…