Reduced Fuel Emissions Through Connected Vehicles And Truck Platooning, 2022 East Tennessee State University
Reduced Fuel Emissions Through Connected Vehicles And Truck Platooning, Paul D. Brummitt
Electronic Theses and Dissertations
Vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication enable the sharing, in real time, of vehicular locations and speeds with other vehicles, traffic signals, and traffic control centers. This shared information can help traffic to better traverse intersections, road segments, and congested neighborhoods, thereby reducing travel times, increasing driver safety, generating data for traffic planning, and reducing vehicular pollution. This study, which focuses on vehicular pollution, used an analysis of data from NREL, BTS, and the EPA to determine that the widespread use of V2V-based truck platooning—the convoying of trucks in close proximity to one another so as to reduce air ...
Development Of Medium Power High Efficiency Multi-Level Buck-Boost Dc-Dc Converter, 2022 School of Electronics and Communication Engineering, Shri Mata Vaishno Devi University, Katra 182320, Jammu and Kashmir, India
Development Of Medium Power High Efficiency Multi-Level Buck-Boost Dc-Dc Converter, Yogesh Singh, Sunny Sharma, Sandeep Tuli
International Journal of Electronics Signals and Systems
Power DC/DC converters or regulators form the backbone of different portable electronic devices like cellular phones, laptops, portable electronic devices which are using batteries as their power supply. Portable devices usually comprise of several sub-circuits that should be supplied with different voltage levels, which are not the same as battery’s voltage level which is the main supply voltage. A new approach of buck-boost converter is presented in this paper, that automatically detects the zero-inductor current & compels the convertor to deliberately switch from Continuous Conduction Mode (CCM) to Discontinuous Conduction Mode (DCM), once the inductor current attempts towards negative ...
Credit Card Fraud Detection Using Machine Learning Techniques, 2022 BIS Helwan University
Credit Card Fraud Detection Using Machine Learning Techniques, Nermin Samy Elhusseny, Shimaa Mohamed Ouf, Amira M. Idrees Ami
Future Computing and Informatics Journal
This is a systematic literature review to reflect the previous studies that dealt with credit card fraud detection and highlight the different machine learning techniques to deal with this problem. Credit cards are now widely utilized daily. The globe has just begun to shift toward financial inclusion, with marginalized people being introduced to the financial sector. As a result of the high volume of e-commerce, there has been a significant increase in credit card fraud. One of the most important parts of today's banking sector is fraud detection. Fraud is one of the most serious concerns in terms of ...
Hvac Hardware Modeling Using Programmable Automatic Controller, 2022 California Polytechnic State University, San Luis Obispo
Hvac Hardware Modeling Using Programmable Automatic Controller, Panthil Ketan Patel, Lumanti Tuladhar
The primary purpose of this project is to use the donated programmable logic controllers (PLC) from Schneider Electric to develop experiments for a future lab class at Cal Poly. Our goal as the first group working on this project is to develop an experiment where the PLC can control the HVAC system based on temperature and humidity sensors and user inputs to maintain a desired consistent temperature. The PLC will be controlled using Unity Pro XLS/Control Expert software for simulations. The overall purpose of the experiments will be to demonstrate the potential of the PLC to minimize manual intervention ...
Barrier Knockdown Test Control System For The Cal Poly Kinesiology Department, 2022 California Polytechnic State University, San Luis Obispo
Barrier Knockdown Test Control System For The Cal Poly Kinesiology Department, Regina M. Chapuis
The goal of this project is to design and implement a new control system for the LEDs and buttons on an existing Barrier Knockdown setup in the Cal Poly Kinesiology department. The Barrier Knockdown test is a testing apparatus in which subjects knock down a series of mechanical barriers in one of three patterns. The computer system times their reaction and movement time, and the test as a whole provides students with data to study the phenomenon of Contextual Interference. This system was previously controlled by an old computer setup that ultimately crashed. This project recreates the logic and user ...
Developing A Miniature Smart Boat For Marine Research, 2022 California Polytechnic State University, San Luis Obispo
Developing A Miniature Smart Boat For Marine Research, Michael Isaac Eirinberg
This project examines the development of a smart boat which could serve as a possible marine research apparatus. The smart boat consists of a miniature vessel containing a low-cost microcontroller to live stream a camera feed, GPS telemetry, and compass data through its own WiFi access point. The smart boat also has the potential for autonomous navigation. My project captivated the interest of several members of California Polytechnic State University, San Luis Obispo’s (Cal Poly SLO) Marine Science Department faculty, who proposed a variety of fascinating and valuable smart boat applications.
Graph-Based Heuristic Solution For Placing Distributed Video Processing Applications On Moving Vehicle Clusters, 2022 South East Technological University
Graph-Based Heuristic Solution For Placing Distributed Video Processing Applications On Moving Vehicle Clusters, Kanika Sharma, Bernard Butler, Brendan Jennings
Vehicular fog computing (VFC) is envisioned as an extension of cloud and mobile edge computing to utilize the rich sensing and processing resources available in vehicles. We focus on slow-moving cars that spend a significant time in urban traffic congestion as a potential pool of onboard sensors, video cameras, and processing capacity. For leveraging the dynamic network and processing resources, we utilize a stochastic mobility model to select nodes with similar mobility patterns. We then design two distributed applications that are scaled in real-time and placed as multiple instances on selected vehicular fog nodes. We handle the unstable vehicular environment ...
A Harmonic Radar System For Honey Bee Tracking To Better Understand Colony Collapse Disorder, 2022 Mississippi State University
A Harmonic Radar System For Honey Bee Tracking To Better Understand Colony Collapse Disorder, William B. Woo
Theses and Dissertations
Honey bees are some of the most important pollinators for agriculture in the world and are pivotal to the health of worldwide ecosystems. Like all insects, bees struggle with exposure to parasites, diseases, and other environmental factors that can negatively affect the overall health of the colony. Recently, a new unexplainable phenomenon called Colony Collapse Disorder (CCD) has been wreaking havoc on bee populations worldwide. As a result, a system capable of tracking bees is required to understand the different contributions of chemicals, parasites, etc. to CCD. This research seeks to show data supporting the development of systems for an ...
Design, Implementation, And Test Of Spacecraft Antennae And A Ground Station For Mesat1, 2022 University of Maine
Design, Implementation, And Test Of Spacecraft Antennae And A Ground Station For Mesat1, Travis Russell
Electronic Theses and Dissertations
MESAT1 is a CubeSat that was proposed by the University of Maine in response to NASA's CubeSat Launch Initiative, and in early 2020 was selected by NASA to be launched into a Low Earth Orbit (LEO) in June of 2022. The satellite will carry four low-cost complementary metal–oxide–semiconductor (CMOS) cameras which serve as sensing instruments for three science missions proposed by K-12 schools in Maine. The cameras will periodically take pictures of Earth to analyze water turbidity, identify urban heat islands, and predict harmful algal blooms. The multi-spectral image data is packed into frames and downlinked as ...
State Estimation—Beyond Gaussian Filtering, 2022 University of New Orleans
State Estimation—Beyond Gaussian Filtering, Haozhan Meng
University of New Orleans Theses and Dissertations
This dissertation considers the state estimation problems with symmetric Gaussian/asymmetric skew-Gaussian assumption under linear/nonlinear systems. It consists of three parts. The first part proposes a new recursive finite-dimensional exact density filter based on the linear skew-Gaussian system. The second part adopts a skew-symmetric representation (SSR) of distribution for nonlinear skew-Gaussian estimation. The third part gives an optimized Gauss-Hermite quadrature (GHQ) rule for numerical integration with respect to Gaussian integrals and applies it to nonlinear Gaussian filters.
We first develop a linear system model driven by skew-Gaussian processes and present the exact filter for the posterior density with fixed ...
Locating Unknown Interference Sources With Time Difference Of Arrival Estimates, 2022 Washington University in St. Louis
Locating Unknown Interference Sources With Time Difference Of Arrival Estimates, Chia Ying Kuo
McKelvey School of Engineering Theses & Dissertations
Adaptive spectrum sharing between different systems and operators is being deployed in order to make use of the wireless spectrum more efficiently. However, when the spectrum is shared, it can create situations in which an operator is unable to determine the identity of an interferer transmitting an unknown signal. This is the situation in which the POWDER testbed found itself in, starting in late 2021. This thesis provides general-purpose tools for operators to locate an unknown signal source in real-world outdoor environments. We used cross-correlation between the signals measured at multiple time-synchronized base stations to estimate the time difference of ...
Structural Checking Tool Restructure And Matching Improvements, 2022 University of Arkansas, Fayetteville
Structural Checking Tool Restructure And Matching Improvements, Derek Taylor
Graduate Theses and Dissertations
With the rising complexity and size of hardware designs, saving development time and cost by employing third-party intellectual property (IP) into various first-party designs has become a necessity. However, using third-party IPs introduces the risk of adding malicious behavior to the design, including hardware Trojans. Different from software Trojan detection, the detection of hardware Trojans in an efficient and cost-effective manner is an ongoing area of study and has significant complexities depending on the development stage where Trojan detection is leveraged. Therefore, this thesis research proposes improvements to various components of the soft IP analysis methodology utilized by the Structural ...
A Novel Data Lineage Model For Critical Infrastructure And A Solution To A Special Case Of The Temporal Graph Reachability Problem, 2022 University of Arkansas, Fayetteville
A Novel Data Lineage Model For Critical Infrastructure And A Solution To A Special Case Of The Temporal Graph Reachability Problem, Ian Moncur
Graduate Theses and Dissertations
Rapid and accurate damage assessment is crucial to minimize downtime in critical infrastructure. Dependency on modern technology requires fast and consistent techniques to prevent damage from spreading while also minimizing the impact of damage on system users. One technique to assist in assessment is data lineage, which involves tracing a history of dependencies for data items. The goal of this thesis is to present one novel model and an algorithm that uses data lineage with the goal of being fast and accurate. In function this model operates as a directed graph, with the vertices being data items and edges representing ...
Live Access Control Policy Error Detection Through Hardware, 2022 University of Arkansas, Fayetteville
Live Access Control Policy Error Detection Through Hardware, Bryce Mendenhall
Graduate Theses and Dissertations
Access Control (AC) is a widely used security measure designed to protect resources and infrastructure in an information system. The integrity of the AC policy is crucial to the protection of the system. Errors within an AC policy may cause many vulnerabilities such as information leaks, information loss, and malicious activities. Thus, such errors must be detected and promptly fixed. However, current AC error detection models do not allow for real-time error detection, nor do they provide the source of errors. This thesis presents a live error detection model called LogicDetect which utilizes emulated Boolean digital logic circuits to provide ...
Cognality Vr: Exploring A Mobile Vr App With Multiple Stakeholders To Reduce Meltdowns In Autistic Children, Louanne E. Boyd, Espen Garner, Ian Kim, Gianna Valencia
Engineering Faculty Articles and Research
Many autistic children can have difficulty communicating, understanding others, and interacting with new and unfamiliar environments. At times they may suffer from a meltdown. The major contributing factor to meltdowns is sensory overwhelm. Technological solutions have shown promise in improving the quality of life for autistic children-however little exists to manage meltdowns. In this work with stakeholders, we design and deploy a low cost, mobile VR application to provide relief during sensory discomfort. Through the analysis of surveys from 88 stakeholders from a variety of groups (i.e., autistic adults, children with autism, parents of autistic individuals, and medical practitioners ...
Efficient Implementation Of Mimo Fbmc/Oqam Scheme Based On Block Spreading, 2022 delta university for science and technology
Efficient Implementation Of Mimo Fbmc/Oqam Scheme Based On Block Spreading, Walid Ali Raslan, Mohamed Abdel-Azim Mohamed, Heba Mohamed Abdel-Atty
Delta University Scientific Journal
Filter bank multicarrier (FBMC) was proposed as an alternative approach to cyclic prefix - orthogonal frequency division multiplexing (CP-OFDM). FBMC is considered a promising non-orthogonal waveform due to its very low out of band radiation and high spectral efficiency. Nevertheless, the orthogonality constraint for FBMC/OQAM is relaxed being limited only to the real field which causes intrinsic interference. The presence of this interference leads to incompatibility between some well-known multiple-input and multiple-output (MIMO) schemes and FBMC/ offset quadrature amplitude modulation (OQAM). From this perspective, we proposed in this paper an efficient implementation for FBMC/OQAM based on block spreading to ...
A Low-Cost, Arduino-Based Platform For Emulating Energy Harvesting In Wireless Sensor Networks, 2022 Ohio Northern University
A Low-Cost, Arduino-Based Platform For Emulating Energy Harvesting In Wireless Sensor Networks, Braden A. Miller
ONU Student Research Colloquium
This paper presents an Arduino-based platform for emulating energy harvesting in Wireless Sensor Networks (WSNs) as a form of hardware-in-the-loop simulation. The platform makes use of a battery monitoring circuit and code implemented on the Arduino as an alternative to using significantly more expensive fully equipped energy harvesting nodes. Using embedded code to emulate the energy harvesting process allows for various energy harvesting models and processes to be tested using the same platform. The main contributions of this paper are the experimental data and analyses demonstrating the energy use characterization of the Arduino-based platform in a three-node relay network using ...
Distributed Control And Learning Of Connected And Autonomous Vehicles Approaching And Departing Signalized Intersections, 2022 Louisiana State University and Agricultural and Mechanical College
Distributed Control And Learning Of Connected And Autonomous Vehicles Approaching And Departing Signalized Intersections, Joshua Onyeka Ogbebor
LSU Master's Theses
This thesis outlines methods for achieving energy-optimal control policies for autonomous vehicles approaching and departing a signalized traffic intersection. Connected and autonomous vehicle technology has gained wide interest from both research institutions and government agencies because it offers immense promise in advancing efficient energy usage and abating hazards that beset the current transportation system. Energy minimization is itself crucial in reducing the greenhouse emissions from fossil-fuel-powered vehicles and extending the battery life of electric vehicles which are presently the major alternative to fossil-fuel-powered vehicles. Two major forms of fuel minimization are studied. First, the eco-driving problem is solved for a ...
Representing And Analyzing The Dynamics Of An Agent-Based Adaptive Social Network Model With Partial Integro-Differential Equations, 2022 Binghamton University, SUNY
Representing And Analyzing The Dynamics Of An Agent-Based Adaptive Social Network Model With Partial Integro-Differential Equations, Hiroki Sayama
Northeast Journal of Complex Systems (NEJCS)
We formulated and analyzed a set of partial integro-differential equations that capture the dynamics of our adaptive network model of social fragmentation involving behavioral diversity of agents. Previous results showed that, if the agents’ cultural tolerance levels were diversified, the social network could remain connected while maintaining cultural diversity. Here we converted the original agent-based model into a continuous equation-based one so we can gain more theoretical insight into the model dynamics. We restricted the node states to 1-D continuous values and assumed the network size was very large. As a result, we represented the whole system as a set ...
Toward Suicidal Ideation Detection With Lexical Network Features And Machine Learning, 2022 Çanakkale Onsekiz Mart University
Toward Suicidal Ideation Detection With Lexical Network Features And Machine Learning, Ulya Bayram, William Lee, Daniel Santel, Ali Minai, Peggy Clark, Tracy Glauser, John Pestian
Northeast Journal of Complex Systems (NEJCS)
In this study, we introduce a new network feature for detecting suicidal ideation from clinical texts and conduct various additional experiments to enrich the state of knowledge. We evaluate statistical features with and without stopwords, use lexical networks for feature extraction and classification, and compare the results with standard machine learning methods using a logistic classifier, a neural network, and a deep learning method. We utilize three text collections. The first two contain transcriptions of interviews conducted by experts with suicidal (n=161 patients that experienced severe ideation) and control subjects (n=153). The third collection consists of interviews conducted ...