Browsing by Author "Samavati, Faramarz Famil"

Now showing 1 - 7 of 7
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    Efficient Calculation of Distance Transform on Discrete Global Grid Systems and Its Application in Automatic Soil Sampling Site Selection
    (2023-09-20) Kazemi, Meysam; Samavati, Faramarz Famil; Stefanakis, Emmanuel; Maleki, Farhad; Runions, Adam Drew
    Geospatial data analysis often requires the computing of a distance transform (DT) for a given vector feature. For instance, in wildfire management, it is helpful to find the distance of all points in an area from the wildfire’s boundary. Computing a distance transform on traditional Geographic Information Systems (GIS) is usually adopted from image processing methods, albeit prone to distortion resulting from flat maps. Discrete Global Grid Systems (DGGS) are relatively new low-distortion globe-based GIS that discretize the Earth into highly regular cells using multiresolution grids. In this thesis, we introduce an efficient DT algorithm for DGGS. Our novel algorithm heavily exploits the hierarchy of a DGGS and its mathematical properties and applies to many different DGGSs. We evaluate our method by comparing its distortion with the DT methods used in traditional GIS and its speed with the application of general 3D mesh DT algorithms on the DGGS grid. We demonstrate that our method is efficient and has lower distortion. To evaluate our DT algorithm further, we have used a real-world case study of selecting soil test points within agricultural fields. Multiple criteria including the distance of soil test points to different features should be considered to select representative points in a field. We show that DT can help to automate the process of selecting test points, by allowing us to efficiently calculate objectives for a representative test point. DT also allows for efficient calculation of buffers from certain features such as farm headlands and underground pipelines, to avoid certain regions when selecting the test points.
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    Evaluation of Data Sufficiency for Crop Classification Model Transfer
    (2024-12-18) Osouli, Mohammadreza; Samavati, Faramarz Famil; Runions, Adam Drew; Maleki, Farhad
    This thesis investigates the effectiveness of using varying data sizes to transfer crop type classification models from one year to the other, with a focus on balancing data sufficiency and model accuracy. The significance of crop detection through satellite imaging lies in its potential to enhance agricultural productivity and resource management. Machine learning techniques, particularly long short-term memory (LSTM) models, have become instrumental in interpreting satellite data due to their predictive accuracy and adaptability. However, applying models trained in one year to subsequent years poses challenges due to variations in environmental conditions and agricultural practices. To address these challenges, in this thesis, we explore the cost-benefit of fine-tuning existing models versus developing new ones based on the quantity of new data. Using smaller datasets for fine-tuning is more computationally efficient and reduces the cost of data collection. Experiments conducted using satellite data from farms in southern Alberta reveal that smaller datasets, with fewer than 25 fields per class, can effectively fine-tune models for accurate interannual classification, while larger datasets are more conducive to training new models. This highlights the key challenge of optimizing data usage for crop classification, balancing data sufficiency and computational efficiency. Additionally, this thesis contributes to the field by selecting the best combination of bands and information from Sentinel-1 and Sentinel-2 satellites. Another significant contribution is the incorporation of crop rotation as a feature for crop classification, which enhances the model's predictive capabilities. The findings of this research offer valuable insights for optimizing data use in crop classification, benefiting both academic research and practical agricultural applications.
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    Incorporating the Concept of Distance into PageRank's Notion of Teleportation
    (2024-04-15) Bowater, David William; Stefanakis, Emmanuel; Wang, Xin; Liang, Hung-Ling (Steve); Samavati, Faramarz Famil; Jabari, Shabnam
    Centrality measures are a valuable tool for analysing complex networks because they help us to identify the most important or central nodes in a network. One of the most popular measures of centrality is PageRank which, despite being originally introduced for ranking web pages, has found widespread use in applications far beyond the web due to its simplicity and generality. However, in many real-world networks, the notion of teleportation is counterintuitive because it implies that whatever is moving around the network will jump or 'teleport' directly from one node to any other, without considering how far apart the nodes are. Therefore, the focus of this thesis is to incorporate the concept of distance into the notion of teleportation, which is accomplished by drawing upon recent advances in non-local random walks. First, an existing PageRank-based centrality measure is extended to improve its suitability for urban street networks. Then, a general measure of PageRank centrality is proposed which can be tailored for various real-world networks and applications. To evaluate the proposed measures, experiments on a variety of real-world spatial and social networks are performed. Finally, to improve our understanding of distance-based teleportation in real-world networks, an analysis of the effect of the damping factor on the rating and ranking of nodes is provided.
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    LifeBrush: An Illustrative Simulation Canvas for the Biological Mesoscale
    (2020-01) Davison, Timothy; Jacob, Christian; Samavati, Faramarz Famil; Costa Sousa, Mario; Olson, Arthur; Willett, Wesley J.; Herzog, W.
    At the mesoscale, molecular machines assemble structure and orchestrate the processes of life. It is a chaotic and alien world whose scale makes communicating scientific findings a daunting challenge. Scientific illustrators confront the challenges with static illustration and video animations. With \lifeBrush{}, a virtual reality tool, we bring those static illustrations to life as interactive illustrative simulations. \lifeBrush{} is an illustrative simulation canvas, for sketching, simulating and visualizing the biological mesoscale. Like an artists paint palette, we design molecular arrangements, self-assembly rules, and generative procedures in an interactive palette. Then, we use our palette and generative algorithms to sketch illustrative simulations. We developed a novel realtime algorithm for painting and synthesizing element arrangements from a palette into virtual worlds. Our synthesis algorithm has applications for virtual world construction, and for interactively constructing illustrative mesoscale simulations. We synthesize networks of interconnected proteins filaments with sketch-based swarm grammars. To model macromolecular self-assembly, and to interactively construct macromolecular structures with our sketch-based system, we propose a realtime physics approximation based on spatial rules designed in the palette. We use our system to sketch and simulate cytoskeletal filaments in our illustrative simulation canvas. With our system, we structurally recreate, simulate and step inside some famous illustrations by the structural biologist David Goodsell.
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    Open-source isogeometric composite module with continuum degradation model
    (2024-09-16) Shevtsov, Vadym; Korobenko, Artem; Korobenko, Artem; Wong, Joanna; Samavati, Faramarz Famil
    This thesis introduces an open-source module developed using the FEniCS platform for analyzing composite materials with varying properties across the computational domain and throughout the analysis. It incorporates the tIGAr library for Isogeometric Analysis (IGA) and PENGoLINS for multi-patch connectivity. The capability of the module to efficiently work with variable properties is demonstrated through the implemented Continuum Damage Model (CDM). Tests under various loading scenarios have shown that the implemented damage module enhances predictive accuracy. These tests also highlight unique platform challenges, such as mesh distortion and variable definition, and common issues in damage models, such as stress localization. These challenges have been partially addressed, laying the groundwork for future enhancements. The findings highlight the advantages of using open-source tools to develop advanced material models, paving the way for broader applications, the use of more complex geometries, and other types of analysis, importantly, Fluid-Structure Interactions (FSI).
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    Sensing Rhythm: Synchronizing Auditory Feedback and Movement
    (2016) Godbout, Andrew Joseph; Boyd, Jeffrey; Samavati, Faramarz Famil; Katz, Larry
    This thesis explores auditory feedback, designed around the ability of people to entrain their movements with a rhythm. Phase denotes the progression through a movement and thus tracking phase tracks progression through a movement. We show how to track phase using sensors and develop a novel visual synchronization system that works with RGB-depth cameras. We use phase tracking to produce auditory feedback that is synchronized with a user. Applications to walking, running, cycling and speed skating demonstrate the methods and thirteen speed skating athletes test the robustness and provide qualitative feedback of two of our synchronous auditory feedback systems.
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    A Variational Multiscale Framework for Analysis of Wind Turbines in Complex Terrain
    (2019-12) Ravensbergen, Michael; Korobenko, Artem; Wood, David H.; Mohamad, Abdulmajeed Abd; Samavati, Faramarz Famil
    Current industry tools for analyzing the flow field around wind turbines in complex terrain do not include all the non-linear physical effects present in reality. A residual based variational multi-scale (VMS) modeling framework is applied to simulate atmospheric flow over complex environmental terrain. This is coupled with the actuator line method (ALM) which represents the effects of the turbine blades on the flow as a distributed body force. To validate the VMS framework for complex terrain, we use three test cases. For a Gaussian hill (normally distributed surface), stream-wise velocity aligns well with published data. The second validation case is the Bolund hill, for which experimental field study data exists. Simulation results compare well in most regions. For both test cases, the VMS framework is applied to linear finite element and quadratic NURBS (Non-uniform rational b-splines). NURBS elements have been shown to give better results than linear finite elements and that is also found here. Finally we simulate flow over the double ridges at Perdigao, Portugal. To validate the ALM-VMS implementation, the National Renewable Energy Lab (NREL) 5MW reference turbine is simulated under uniform inflow conditions to investigate the effect of model parameters such as the width of the body force projection and the mesh resolution. Additionally, the wind turbine from the Norwegian University of Science and Technology and the NREL Phase VI wind turbines are simulated and compared with results from the corresponding wind tunnel experiments. Velocity deficit and turbulence kinetic energy in the wake region between three and five down-stream diameters show good agreement with experimental data. Finally, we simulate an NREL 5MW turbine in the complex terrain at Perdigao, highlighting the ability of the developed framework for wind turbine applications in complex terrain.