A5070614665- Remote Sensing and LiDAR Applications
- Plant Water Relations and Carbon Dynamics
- Remote Sensing in Agriculture
- Sparse and Compressive Sensing Techniques
- Flood Risk Assessment and Management
- Urban Stormwater Management Solutions
- Advanced Optical Sensing Technologies
- Respiratory Support and Mechanisms
- Water Systems and Optimization
- Non-Invasive Vital Sign Monitoring
- Landslides and related hazards
- Geophysical Methods and Applications
- Spectroscopy Techniques in Biomedical and Chemical Research
- Cryospheric studies and observations
- Adaptive Control of Nonlinear Systems
- COVID-19 and Mental Health
- Photoacoustic and Ultrasonic Imaging
- Microwave Imaging and Scattering Analysis
- Optical Imaging and Spectroscopy Techniques
- Water resources management and optimization
- Sepsis Diagnosis and Treatment
- Advanced Control Systems Optimization
- Hemodynamic Monitoring and Therapy
- Synthetic Aperture Radar (SAR) Applications and Techniques
- Spectroscopy and Chemometric Analyses
University of Delaware
2022-2025
Universidad de Los Andes
2015-2024
Universidad de La Sabana
2024
LiDAR remote sensing systems are deployed in various platforms including satellites, airplanes, and drones — which, essence, determines the sampling characteristics of underlying imaging system. Low-altitude LiDARs provide high photon count spatial resolution but only very localized patches. Satellite LiDARs, on other hand, measurements at a global scale limited by low their samples sparsely apart along swath line trajectories that far between. This paper describes new class satellite aimed...
Spaceborne LiDAR systems are crucial for Earth observation but face hardware constraints, thus limiting resolution and data processing. We propose integrating compressed sensing diffusion generative models to reconstruct high-resolution satellite within the Hyperheight Data Cube (HHDC) framework. Using a randomized illumination pattern in imaging model, we achieve efficient sampling compression, reducing onboard computational load optimizing transmission. Diffusion then detailed HHDCs from...
Compressive satellite LiDAR (CS-LiDAR) has been recently introduced as a radically different computational sensing and reconstruction approach for of Earth. It is based on NASA's adaptive wavelength scanning (AWSL) system. Rather than measuring 1D line footprints over satellite's swath path the norm today, CS-LiDAR adopts sparse coded laser illumination 2D wide field-of-view. The objective to compressively sense Earth from hundreds km above then computationally reconstruct 3D imagery with...
The COVID-19 pandemic in Latin America generated the need to develop low-cost, fast-manufacturing mechanical ventilators. Universidad de La Sabana and Fundacion Neumologica Colombiana designed manufactured Unisabana-HERONS (USH) ventilator. Here, we present preclinical clinical study results evaluate its effectiveness safety characteristics an animal model (Y
This paper presents a nonlinear model predictive control (NMPC) strategy combined with constraint satisfactions for quadcopter. The full dynamics of the quadcopter describing attitude and position are nonlinear, which quite sensitive to changes inputs disturbances. By means satisfactions, partial nonlinearities modeling errors control-oriented can be transformed into inequality constraints. Subsequently, controlled by an NMPC controller updated constraints generated satisfactions. Finally,...
Coded aperture snapshot spectral imager (CASSI) senses the information of a 2-D scene and captures set coded measurement data that can be used to reconstruct 3-D spatio-spectral datacube input by compressive sensing algorithms. The (CA) in CASSI plays crucial role modulating spatial information. pixels CA are typically square, switched binary ON–OFF, aligned with focal plane array (FPA). Instead this modulation, letter explores simple yet effective approach enabling an equivalent grayscale...
Urban drainage systems (UDSs) are complex large-scale that carry stormwater and wastewater throughout urban areas. During heavy rain scenarios, UDSs not able to handle the amount of extra water enters network flooding occurs. Usually, this might happen because is being used efficiently, i.e., some structures remain underused while many others overused. This paper proposes a control methology based on differential game theory aims efficiently use existing elements in order minimize overflows...
A co-simulation framework that uses two software tools (i.e., Matlab, Python or LabVIEW, and SWMM) is presented. The performed thanks to a tool has been developed, which the main contribution of this work. This approach storm water management model (SWMM), becoming solution lack test controllers for urban drainage systems (UDS). Specifically, MatSWMM, an open source can be used end, Additionally, in order illustrate features methodology, some issues using control-oriented models (COM) are...
Low-altitude airborne lidars deliver high spatial resolution swath mapping using dense laser footprint sampling but only in limited areas, while satellite offer global are hampered by low due to sparse footprints. This work presents a novel approach lidar remote sensing designed address the leveraging principles of compressive and machine learning applied highly efficient, adaptive capable sampling. Compressive enables distribution footprints across with density appropriate recover features...