Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Interpolation (2)
- Adaptive (1)
- Adaptive decentralized controller (1)
- Adaptive sampling (1)
- Adversarial attack (1)
-
- Algorithms (1)
- Amour (1)
- Aquanode (1)
- Binary neural network verification (1)
- Chemical Reaction (1)
- Computer vision (1)
- Concentration (1)
- Data fusion (1)
- Enzyme (1)
- Exact reachability analysis (1)
- GIS (1)
- Geostatistics (1)
- Kinetic (1)
- Metabolic Networks (1)
- Metabolic Pathway (1)
- Neural network verification (1)
- Overapproximate reachability analysis (1)
- Path optimization (1)
- Path planning (1)
- Precipitation (1)
- Qualitative verification (1)
- Sensor network (1)
- Sensor placement (1)
- Sign activation (1)
- Simulation (1)
Articles 1 - 5 of 5
Full-Text Articles in Computer Engineering
Star-Based Reachability Analysis Of Binary Neural Networks On Continuous Input, Mykhailo Ivashchenko
Star-Based Reachability Analysis Of Binary Neural Networks On Continuous Input, Mykhailo Ivashchenko
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Deep Neural Networks (DNNs) have become a popular instrument for solving various real-world problems. DNNs’ sophisticated structure allows them to learn complex representations and features. However, architecture specifics and floating-point number usage result in increased computational operations complexity. For this reason, a more lightweight type of neural networks is widely used when it comes to edge devices, such as microcomputers or microcontrollers – Binary Neural Networks (BNNs). Like other DNNs, BNNs are vulnerable to adversarial attacks; even a small perturbation to the input set may lead to an errant output. Unfortunately, only a few approaches have been proposed for verifying …
Design And Implementation Of A Stand-Alone Tool For Metabolic Simulations, Milad Ghiasi Rad
Design And Implementation Of A Stand-Alone Tool For Metabolic Simulations, Milad Ghiasi Rad
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
In this thesis, we present the design and implementation of a stand-alone tool for metabolic simulations. This system is able to integrate custom-built SBML models along with external user’s input information and produces the estimation of any reactants participating in the chain of the reactions in the provided model, e.g., ATP, Glucose, Insulin, for the given duration using numerical analysis and simulations. This tool offers the food intake arguments in the calculations to consider the personalized metabolic characteristics in the simulations. The tool has also been generalized to take into consideration of temporal genomic information and be flexible for simulation …
A Comparative Study Of Underwater Robot Path Planning Algorithms For Adaptive Sampling In A Network Of Sensors, Sreeja Banerjee
A Comparative Study Of Underwater Robot Path Planning Algorithms For Adaptive Sampling In A Network Of Sensors, Sreeja Banerjee
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Monitoring lakes, rivers, and oceans is critical to improving our understanding of complex large-scale ecosystems. We introduce a method of underwater monitoring using semi-mobile underwater sensor networks and mobile underwater robots in this thesis. The underwater robots can move freely in all dimension while the sensor nodes are anchored to the bottom of the water column and can move only up and down along the depth of the water column. We develop three different algorithms to optimize the path of the underwater robot and the positions of the sensors to improve the overall quality of sensing of an area of …
Decaf: A New Event Detection Logic For The Purpose Of Fusing Delineated-Continuous Spatial Information, Kerry Q. Hart
Decaf: A New Event Detection Logic For The Purpose Of Fusing Delineated-Continuous Spatial Information, Kerry Q. Hart
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Geospatial information fusion is the process of synthesizing information from complementary data sources located at different points in space and time. Spatial phenomena are often measured at discrete locations by sensor networks, technicians, and volunteers; yet decisions often require information about locations where direct measurements do not exist. Traditional methods assume the spatial phenomena to be either discrete or continuous, an assumption that underlies and informs all subsequent analysis. Yet certain phenomena defy this dichotomy, alternating as they move across spatial and temporal scales. Precipitation, for example, appears continuous at large scales, but it can be temporally decomposed into discrete …
Adaptive Interpolation Algorithms For Temporal-Oriented Datasets, Jun Gao
Adaptive Interpolation Algorithms For Temporal-Oriented Datasets, Jun Gao
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Spatiotemporal datasets can be classified into two categories: temporal-oriented and spatial-oriented datasets depending on whether missing spatiotemporal values are closer to the values of its temporal or spatial neighbors. We present an adaptive spatiotemporal interpolation model that can estimate the missing values in both categories of spatiotemporal datasets. The key parameters of the adaptive spatiotemporal interpolation model can be adjusted based on experience.