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(1 - 7 of 7)
- Title
- Energy Conservation in Heterogeneous Smartphone Ad Hoc Networks
- Creator
- Mariani, James
- Date
- 2018
- Collection
- Electronic Theses & Dissertations
- Description
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In recent years mobile computing has been rapidly expanding to the point that there are now more devices than there are people. While once it was common for every household to have one PC, it is now common for every person to have a mobile device. With the increased use of smartphone devices, there has also been an increase in the need for mobile ad hoc networks, in which phones connect directly to each other without the need for an intermediate router. Most modern smart phones are equipped...
Show moreIn recent years mobile computing has been rapidly expanding to the point that there are now more devices than there are people. While once it was common for every household to have one PC, it is now common for every person to have a mobile device. With the increased use of smartphone devices, there has also been an increase in the need for mobile ad hoc networks, in which phones connect directly to each other without the need for an intermediate router. Most modern smart phones are equipped with both Bluetooth and Wifi Direct, where Wifi Direct has a better transmission range and rate and Bluetooth is more energy efficient. However only one or the other is used in a smartphone ad hoc network. We propose a Heterogeneous Smartphone Ad Hoc Network, HSNet, a framework to enable the automatic switching between Wifi Direct and Bluetooth to emphasize minimizing energy consumption while still maintaining an efficient network. We develop an application to evaluate the HSNet framework which shows significant energy savings when utilizing our switching algorithm to send messages by a less energy intensive technology in situations where energy conservation is desired. We discuss additional features of HSNet such as load balancing to help increase the lifetime of the network by more evenly distributing slave nodes among connected master nodes. Finally, we show that the throughput of our system is not affected due to technology switching for most scenarios. Future work of this project includes exploring energy efficient routing as well as simulation/scale testing for larger and more diverse smartphone ad hoc networks.
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- Title
- MICROBLOG GUIDED CRYPTOCURRENCY TRADING AND FRAMING ANALYSIS
- Creator
- Pawlicka Maule, Anna Paula
- Date
- 2020
- Collection
- Electronic Theses & Dissertations
- Description
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With 56 million people actively trading and investing in cryptocurrency online and globally, there is an increasing need for an automatic social media analysis tool to help understand trading discourse and behavior. Previous works have shown the usefulness of modeling microblog discourse for the prediction of trading stocks and their price fluctuations, as well as content framing. In this work, I present a natural language modeling pipeline that leverages language and social network behaviors...
Show moreWith 56 million people actively trading and investing in cryptocurrency online and globally, there is an increasing need for an automatic social media analysis tool to help understand trading discourse and behavior. Previous works have shown the usefulness of modeling microblog discourse for the prediction of trading stocks and their price fluctuations, as well as content framing. In this work, I present a natural language modeling pipeline that leverages language and social network behaviors for the prediction of cryptocurrency day trading actions and their associated framing patterns. Specifically, I present two modeling approaches. The first determines if the tweets of a 24-hour period can be used to guide day trading behavior, specifically if a cryptocurrency investor should buy, sell, or hold their cryptocurrencies in order to make a trading profit. The second is an unsupervised deep clustering approach to automatically detect framing patterns. My contributions include the modeling pipeline for this novel task, a new dataset of cryptocurrency-related tweets from influential accounts, and a transaction volume dataset. The experiments executed show that this weakly-supervised trading pipeline achieves an 88.78% accuracy for day trading behavior predictions and reveals framing fluctuations prior to and during the COVID-19 pandemic that could be used to guide investment actions.
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- Title
- LIDAR AND CAMERA CALIBRATION USING A MOUNTED SPHERE
- Creator
- Li, Jiajia
- Date
- 2020
- Collection
- Electronic Theses & Dissertations
- Description
-
Extrinsic calibration between lidar and camera sensors is needed for multi-modal sensor data fusion. However, obtaining precise extrinsic calibration can be tedious, computationally expensive, or involve elaborate apparatus. This thesis proposes a simple, fast, and robust method performing extrinsic calibration between a camera and lidar. The only required calibration target is a hand-held colored sphere mounted on a whiteboard. The convolutional neural networks are developed to automatically...
Show moreExtrinsic calibration between lidar and camera sensors is needed for multi-modal sensor data fusion. However, obtaining precise extrinsic calibration can be tedious, computationally expensive, or involve elaborate apparatus. This thesis proposes a simple, fast, and robust method performing extrinsic calibration between a camera and lidar. The only required calibration target is a hand-held colored sphere mounted on a whiteboard. The convolutional neural networks are developed to automatically localize the sphere relative to the camera and the lidar. Then using the localization covariance models, the relative pose between the camera and lidar is derived. To evaluate the accuracy of our method, we record image and lidar data of a sphere at a set of known grid positions by using two rails mounted on a wall. The accurate calibration results are demonstrated by projecting the grid centers into the camera image plane and finding the error between these points and the hand-labeled sphere centers.
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- Title
- 5D Nondestructive Evaluation : Object Reconstruction to Toolpath Generation
- Creator
- Hamilton, Ciaron Nathan
- Date
- 2021
- Collection
- Electronic Theses & Dissertations
- Description
-
The focus of this thesis is to provide virtualization methods for a Cyber-Physical System (CPS) setup that interfaces physical Nondestructive Evaluation (NDE) scanning environments into virtual spaces through virtual-physical interfacing and path planning. In these environments, a probe used for NDE mounted as the end-effector of a robot arm will actuate and acquire data along the surface of a Material Under Test (MUT) within virtual and physical spaces. Such configurations are practical for...
Show moreThe focus of this thesis is to provide virtualization methods for a Cyber-Physical System (CPS) setup that interfaces physical Nondestructive Evaluation (NDE) scanning environments into virtual spaces through virtual-physical interfacing and path planning. In these environments, a probe used for NDE mounted as the end-effector of a robot arm will actuate and acquire data along the surface of a Material Under Test (MUT) within virtual and physical spaces. Such configurations are practical for applications that require damage analysis of certain geometrically complex parts, ranging from automobile to aerospace to military industries. The pipeline of the designed $5D$ actuation system starts by virtually reconstructing the physical MUT and its surrounding environment, generating a toolpath along the surface of the reconstructed MUT, conducting a physical scan along the toolpath which synchronizes the robot's end effector position with retrieved NDE data, and post processing the obtained data. Most of this thesis will focus on virtual topics, including reconstruction from stereo camera images and toolpath planning. Virtual mesh generation of the MUT and surrounding environment are found with stereo camera images, where methods for camera positioning, registration, filtering, and reconstruction are provided. Path planning around the MUT uses a customized path-planner, where a $2D$ grid of rays is generated where each ray intersection across the surface of the MUT's mesh provides the translation and rotation of waypoints for actuation. Experimental setups include both predefined meshes and reconstructed meshes found from several real carbon-fiber automobile components using an Intel RealSense D425i stereo camera, showing both the reconstruction and path planning results. A theoretical review is also included to discuss analytical prospects of the system. The final system is designed to be automated to minimize human interaction to conduct scans, with later reports planned to discuss the scanning and post processing prospects of the system.
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- Title
- Coreference Resolution for Downstream NLP Tasks
- Creator
- Pani, Sushanta Kumar
- Date
- 2021
- Collection
- Electronic Theses & Dissertations
- Description
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Natural Language Processing (NLP) tasks have witnessed a significant improvement in performance by utilizing the power of end-to-end neural network models. An NLP system built for one job can contribute to other closely related tasks. Coreference Resolution (CR) systems work on resolving references and are at the core of many NLP tasks. The coreference resolution refers to the linking of repeated object references in a text. CR systems can boost the performance of downstream NLP tasks, such...
Show moreNatural Language Processing (NLP) tasks have witnessed a significant improvement in performance by utilizing the power of end-to-end neural network models. An NLP system built for one job can contribute to other closely related tasks. Coreference Resolution (CR) systems work on resolving references and are at the core of many NLP tasks. The coreference resolution refers to the linking of repeated object references in a text. CR systems can boost the performance of downstream NLP tasks, such as Text Summarization, Question Answering, Machine Translation, etc. We provide a detailed comparative error analysis of two state-of-the-art coreference resolution systems to understand error distribution in the predicted output. The understanding of error distribution is helpful to interpret the system behavior. Eventually, this will contribute to the selection of an optimal CR system for a specific target task.
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- Title
- COMBINING FACE AND IRIS FOR PRIVACY PRESERVATION
- Creator
- Ledala, Achsah Junia
- Date
- 2021
- Collection
- Electronic Theses & Dissertations
- Description
-
With the extensive use of biometrics for authenticating users, the need to ensure privacy of biometric data is greater than ever before. Biometric authentication systems are vulnerable to attacks and the loss of biometric data will lead to loss of privacy of an individual. Multibiometrics refers to the use of multiple biometric modalities simultaneously in order to perform matching. In this work, we introduce a multibiometric fusion technique which can be used to ensure that the original raw...
Show moreWith the extensive use of biometrics for authenticating users, the need to ensure privacy of biometric data is greater than ever before. Biometric authentication systems are vulnerable to attacks and the loss of biometric data will lead to loss of privacy of an individual. Multibiometrics refers to the use of multiple biometric modalities simultaneously in order to perform matching. In this work, we introduce a multibiometric fusion technique which can be used to ensure that the original raw biometric data are unlikely to be compromised and, at the same time, recognition can be performed. The face and the iris biometric modalities are fused at the feature-level to produce discriminative embeddings that can be used for recognition. The original face or the iris cannot be retrieved from the combined representation, thus preserving the privacy of the individual. We present the results of this approach, provide analysis, discuss the challenges, and list possible future directions.
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- Title
- EMERGENT COORDINATION : ADAPTATION, OPEN-ENDEDNESS, AND COLLECTIVE INTELLIGENCE
- Creator
- Bao, Honglin
- Date
- 2022
- Collection
- Electronic Theses & Dissertations
- Description
-
Agent-based modeling is a widely used computational method for studying the micro-macro bridge issue by simulating the microscopic interactions and observing the macroscopic emergence. This thesis begins with the fundamental methodology of agent-based models: how agents are represented, how agents interact, and how the agent population is structured. Two vital topics, the evolution of cooperation and opinion dynamics are used to illustrate methodological innovation. For the first topic, we...
Show moreAgent-based modeling is a widely used computational method for studying the micro-macro bridge issue by simulating the microscopic interactions and observing the macroscopic emergence. This thesis begins with the fundamental methodology of agent-based models: how agents are represented, how agents interact, and how the agent population is structured. Two vital topics, the evolution of cooperation and opinion dynamics are used to illustrate methodological innovation. For the first topic, we study the equilibrium selection in a coordination game in multi-agent systems. In particular, we focus on the characteristics of agents (supervisors and subordinates versus representative agents), the interactions of agents (reinforcement learning in the games with fixed versus adaptive learning rates according to the supervision and time-varying versus supervision-guided exploration rates), the network of agents (single-layer versus multi-layer networks), and their impact on the emergent behaviors. Regarding the second topic, we examine how opinions evolve and spread in a cognitively heterogeneous agent population with sparse interactions and how the opinion dynamics co-evolve with the open-ended society's structural change. We then discuss the rich insights into collective intelligence in the two proposed models viewed from the interaction-based adaptation and open-ended network structure. We finally link collective emergent intelligence to diverse applications in the realm of computing and other scientific fields in a cross-multidisciplinary manner.
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