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Full-Text Articles in Engineering
Motif-Cluster: A Spatial Clustering Package For Repetitive Motif Binding Patterns, Mengyuan Zhou
Motif-Cluster: A Spatial Clustering Package For Repetitive Motif Binding Patterns, Mengyuan Zhou
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Previous efforts in using genome-wide analysis of transcription factor binding sites (TFBSs) have overlooked the importance of ranking potential significant regulatory regions, especially those with repetitive binding within a local region. Identifying these homogenous binding sites is critical because they have the potential to amplify the binding affinity and regulation activity of transcription factors, impacting gene expression and cellular functions. To address this issue, we developed an open-source tool Motif-Cluster that prioritizes and visualizes transcription factor regulatory regions by incorporating the idea of local motif clusters. Motif-Cluster can rank the significant transcription factor regulatory regions without the need for experimental …
Experimental Study Of Linux Flightsize Estimation, Mingrui Zhang
Experimental Study Of Linux Flightsize Estimation, Mingrui Zhang
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Transmission Control Protocol (TCP) is a fundamental Internet protocol responsible for controlling and coordinating the Internet traffic. As a result, TCP significantly influences the overall performance and stability of the Internet. One critical information required by a TCP connection to make decisions is FlightSize, which is the total amount of outstanding data contributed by the connection to the Internet. The FlightSize information is used by a TCP connection to determine its future sending rate and also avoid traffic congestion and collapse in the Internet. Consequently, an inaccurate estimation of FlightSize can result in degraded performance and instability of the Internet. …
Sim-To-Real Reinforcement Learning Framework For Autonomous Aerial Leaf Sampling, Ashraful Islam
Sim-To-Real Reinforcement Learning Framework For Autonomous Aerial Leaf Sampling, Ashraful Islam
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Using unmanned aerial systems (UAS) for leaf sampling is contributing to a better understanding of the influence of climate change on plant species, and the dynamics of forest ecology by studying hard-to-reach tree canopies. Currently, multiple skilled operators are required for UAS maneuvering and using the leaf sampling tool. This often limits sampling to only the canopy top or periphery. Sim-to-real reinforcement learning (RL) can be leveraged to tackle challenges in the autonomous operation of aerial leaf sampling in the changing environment of a tree canopy. However, trans- ferring an RL controller that is learned in simulation to real UAS …
Leveraging Aruco Fiducial Marker System For Bridge Displacement Estimation Using Unmanned Aerial Vehicles, Mohamed Aly
Leveraging Aruco Fiducial Marker System For Bridge Displacement Estimation Using Unmanned Aerial Vehicles, Mohamed Aly
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
The use of unmanned aerial vehicles (UAVs) in construction sites has been widely growing for surveying and inspection purposes. Their mobility and agility have enabled engineers to use UAVs in Structural Health Monitoring (SHM) applications to overcome the limitations of traditional approaches that require labor-intensive installation, extended time, and long-term maintenance. One of the critical applications of SHM is measuring bridge deflections during the bridge operation period. Due to the complex remote sites of bridges, remote sensing techniques, such as camera-equipped drones, can facilitate measuring bridge deflections. This work takes a step to build a pipeline using the state-of-the-art computer …