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Seabem: An Artificial Intelligence Powered Web Application To Predict Cover Crop Biomass, Aime Christian Tuyishime, Andrea Basche 2022 University of Nebraska - Lincoln

Seabem: An Artificial Intelligence Powered Web Application To Predict Cover Crop Biomass, Aime Christian Tuyishime, Andrea Basche

Honors Theses, University of Nebraska-Lincoln

SEABEM, the Stacked Ensemble Algorithms Biomass Estimator Model, is a web application with a stacked ensemble of Machine Learning (ML) algorithms running on the backend to predict cover crop biomass for locations in Sub-Saharan. The SEABEM model was developed using a previously developed database of crop growth and yield that included site characteristics such as latitude, longitude, soil texture (sand, silt, and clay percentages), temperature, and precipitation. The goal of SEABEM is to provide global farmers, mainly small-scale African farmers, the knowledge they need before practicing and benefiting from cover crops while avoiding the expensive and time-consuming operations that come …


A Deep Learning-Based Approach To Extraction Of Filler Morphology In Sem Images With The Application Of Automated Quality Inspection, Md. Fashiar Rahman, Tzu-Liang Bill Tseng, Jianguo Wu, Yuxin Wen, Yirong Lin 2022 The University of Texas at El Paso

A Deep Learning-Based Approach To Extraction Of Filler Morphology In Sem Images With The Application Of Automated Quality Inspection, Md. Fashiar Rahman, Tzu-Liang Bill Tseng, Jianguo Wu, Yuxin Wen, Yirong Lin

Engineering Faculty Articles and Research

Automatic extraction of filler morphology (size, orientation, and spatial distribution) in Scanning Electron Microscopic (SEM) images is essential in many applications such as automatic quality inspection in composite manufacturing. Extraction of filler morphology greatly depends on accurate segmentation of fillers (fibers and particles), which is a challenging task due to the overlap of fibers and particles and their obscure presence in SEM images. Convolution Neural Networks (CNNs) have been shown to be very effective at object recognition in digital images. This paper proposes an automatic filler detection system in SEM images, utilizing a Mask Region-based CNN architecture. The proposed system …


Efficient Information Retrieval For Software Bug Localization, Saket Khatiwada 2022 Louisiana State University and Agricultural and Mechanical College

Efficient Information Retrieval For Software Bug Localization, Saket Khatiwada

LSU Doctoral Dissertations

Software systems are often shipped with defects. When a bug is reported, developers use the information available in the associated report to locate source code fragments that need to be modified to fix the bug. However, as software systems evolve in size and complexity, bug localization can become a tedious and time-consuming process. Contemporary bug localization tools utilize Information Retrieval (IR) methods for automated support to minimize the manual effort. IR methods exploit the textual content of bug reports to capture and rank relevant buggy source files. However, for an IR-based bug localization tool to be useful, it must achieve …


Three Wave Mixing In Epsilon-Near-Zero Plasmonic Waveguides For Signal Regeneration, Nicholas Mirchandani, Mark C. Harrison 2022 Chapman University

Three Wave Mixing In Epsilon-Near-Zero Plasmonic Waveguides For Signal Regeneration, Nicholas Mirchandani, Mark C. Harrison

Engineering Faculty Articles and Research

Vast improvements in communications technology are possible if the conversion of digital information from optical to electric and back can be removed. Plasmonic devices offer one solution due to optical computing’s potential for increased bandwidth, which would enable increased throughput and enhanced security. Plasmonic devices have small footprints and interface with electronics easily, but these potential improvements are offset by the large device footprints of conventional signal regeneration schemes, since surface plasmon polaritons (SPPs) are incredibly lossy. As such, there is a need for novel regeneration schemes. The continuous, uniform, and unambiguous digital information encoding method is phase-shift-keying (PSK), so …


A Date With Cheemis: Bullying In The Virtual Space, Nicholas Roger Nolasco 2022 California Polytechnic State University, San Luis Obispo

A Date With Cheemis: Bullying In The Virtual Space, Nicholas Roger Nolasco

Liberal Arts and Engineering Studies

A Date With Cheemis is an alternative game mode for the social platform VRChat designed in the Unity real-time 3D development platform. The project is an experience where the player meets many non-playable characters (NPCs) and makes decisions based on different scenarios. The game tells the story of a VRChat user named Cheemis who is bullied for the avatar they use and how they interact with other characters. The player must make choices of how to react to the way the NPCs treat Cheemis, whether that be defending him or being a bystander. This experience is only available through the …


Smart Hospitality And Secure Tourism Management Using Blockchain Technology: Beshostm Approach, Asik Rahaman Jamader Mr, Puja Das Ms., Biswaranjan Acharya Mr., Sandhya Makkar Dr. 2022 Dept. of Tourism & Hotel Management, Penguin School of Hotel Management, Kolkata, India

Smart Hospitality And Secure Tourism Management Using Blockchain Technology: Beshostm Approach, Asik Rahaman Jamader Mr, Puja Das Ms., Biswaranjan Acharya Mr., Sandhya Makkar Dr.

International Journal of Computer Science and Informatics

Throughout the age of 5G technology, the majority of contactless banking is made via software that is enabled by a wide range of financial platforms. Several alternative financing channels provide access to a variety of services. The opportunity for hackers to engage in nefarious behaviour such as payment account hacking, identity theft, and payment system assaults stages of clearances with e-tourism, monetary information is kept in a database. Payment issues can be caused by a centralised cloud server. Throughout the periods of heavy congestion, the abovementioned problems are solvable by utilising a decentralised system like blockchain, it allows for the …


Extractive Text Summarization On Single Documents Using Deep Learning, Shehab Mostafa Abdel-Salam Mohamed 2022 American University in Cairo

Extractive Text Summarization On Single Documents Using Deep Learning, Shehab Mostafa Abdel-Salam Mohamed

Theses and Dissertations

The task of summarization can be categorized into two methods, extractive and abstractive summarization. Extractive approach selects highly meaningful sentences to form a summary while the abstractive approach interprets the original document and generates the summary in its own words. The task of generating a summary, whether extractive or abstractive, has been studied with different approaches such as statistical-based, graph-based, and deep-learning based approaches. Deep learning has achieved promising performance in comparison with the classical approaches and with the evolution of neural networks such as the attention network or commonly known as the Transformer architecture, there are potential areas for …


Adding Temporal Information To Lidar Semantic Segmentation For Autonomous Vehicles, Mohammed Anany 2022 The American University in Cairo AUC

Adding Temporal Information To Lidar Semantic Segmentation For Autonomous Vehicles, Mohammed Anany

Theses and Dissertations

Semantic segmentation is an essential technique to achieve scene understanding for various domains and applications. Particularly, it is of crucial importance in autonomous driving applications. Autonomous vehicles usually rely on cameras and light detection and ranging (LiDAR) sensors to gain contextual information from the environment. Semantic segmentation has been employed to process images and point clouds that were captured from cameras and LiDAR sensors respectively. One important research direction to consider is investigating the impact of utilizing temporal information in the domain of semantic segmentation. Many contributions exist in the field with regards to utilizing temporal information for semantic segmentation …


Interpretable And Anti-Bias Machine Learning Models For Human Event Sequence Data, Zihan Zhou 2022 Louisiana State University

Interpretable And Anti-Bias Machine Learning Models For Human Event Sequence Data, Zihan Zhou

LSU Doctoral Dissertations

Growing volumes and varieties of human event sequence data are available in many applications such as recommender systems, social network, medical diagnosis, and predictive policing. Human event sequence data is usually clustered and exhibits self-exciting properties. Machine learning models especially deep neural network models have shown great potential in improving the prediction accuracy of future events. However, current approaches still suffer from several drawbacks such as model transparency, unfair prediction and the poor prediction accuracy due to data sparsity and bias. Another issue in modeling human event data is that data collected from real word is usually incomplete, and even …


A Neural Network Based Proportional Hazard Model For Iot Signal Fusion And Failure Prediction, Yuxin Wen, Xingxin Guo, Junbo Son, Jianguo Wu 2022 Chapman University

A Neural Network Based Proportional Hazard Model For Iot Signal Fusion And Failure Prediction, Yuxin Wen, Xingxin Guo, Junbo Son, Jianguo Wu

Engineering Faculty Articles and Research

Accurate prediction of remaining useful life (RUL) plays a critical role in optimizing condition-based maintenance decisions. In this paper, a novel joint prognostic modeling framework that simultaneously combines both time-to-event data and multi-sensor degradation signals is proposed. With the increasing use of IoT devices, unprecedented amounts of diverse signals associated with the underlying health condition of in-situ units have become easily accessible. To take full advantage of the modern IoT-enabled engineering systems, we propose a specialized framework for RUL prediction at the level of individual units. Specifically, a Bayesian linear regression model is developed for the multi-sensor degradation signals and …


Eye-Gaze-Controlled Hmds And Mfd For Military Aircraft, LRD Murthy, Abhishek Mukhopadhyay, Somnath Arjun, Varshith Yelleti, Peter Thomas, Dilli Babu Mohan, Pradipta Biswas 2022 Indian Institute of Science

Eye-Gaze-Controlled Hmds And Mfd For Military Aircraft, Lrd Murthy, Abhishek Mukhopadhyay, Somnath Arjun, Varshith Yelleti, Peter Thomas, Dilli Babu Mohan, Pradipta Biswas

Journal of Aviation Technology and Engineering

Eye-gaze-controlled interfaces allow the direct manipulation of a graphical user interface by looking at it. This technology has great potential in military aviation, in particular, operating different displays in situations where pilots’ hands are occupied with flying the aircraft. This paper reports studies on analyzing the accuracy of eye-gaze-controlled interfaces inside aircraft undertaking representative flying missions. We report that using eye-gaze-controlled interfaces, pilots can undertake representative pointing and selection tasks at less than two seconds on average in a transport aircraft. Further, we analyzed the accuracy of eye-gaze-tracking glasses under various G load factors and analyzed the failure modes. We …


Icu Liberation: Early Mobility And Exercise, LeAnn Volkers, Holly Kockler, Kristi Patterson 2022 St. Cloud Hospital, CentraCare Health

Icu Liberation: Early Mobility And Exercise, Leann Volkers, Holly Kockler, Kristi Patterson

Nursing Posters

The aim of this project was to streamline and standardize the delivery of the follow up Important Message from Medicare (IMM) for IP admissions across CC and Carris-RWF in compliance with regulatory standards of care.

Key drivers identified:

  • Site specific variation
  • Underutilization of Epic functionality
  • Use of data to understand performance


Intelligent Voice Guidance In Vr: Understanding The Value Of Nlp In Virtual Environments, Zhiyu Xiao 2022 Dartmouth College

Intelligent Voice Guidance In Vr: Understanding The Value Of Nlp In Virtual Environments, Zhiyu Xiao

Dartmouth College Master’s Theses

Virtual assistants such as Google Assistant, Alexa and Siri emerged because of the growth of NLP(natural language processing) technology. At the same time, virtual reality has developed rapidly in recent years and has become a crucial tool in engineering product development procedures. However, people feel overwhelmed in some complicated VR environments. Thus, this thesis tries to incorporate NLP technology into the VR environment and explores the value of intelligent voice guidance in VR environments. In this thesis, a car repair training system with intelligent voice guidance is designed: users can utilize voice to perform various tasks in this system, such …


Sok: Analysis Of Software Supply Chain Security By Establishing Secure Design Properties, Chinenye Okafor, Taylor R. Schorlemmer, Santiao Torres-Arias, James C. Davis 2022 Purdue University

Sok: Analysis Of Software Supply Chain Security By Establishing Secure Design Properties, Chinenye Okafor, Taylor R. Schorlemmer, Santiao Torres-Arias, James C. Davis

Department of Electrical and Computer Engineering Faculty Publications

This paper systematizes knowledge about secure software supply chain patterns. It identifies four stages of a software supply chain attack and proposes three security properties crucial for a secured supply chain: transparency, validity, and separation. The paper describes current security approaches and maps them to the proposed security properties, including research ideas and case studies of supply chains in practice. It discusses the strengths and weaknesses of current approaches relative to known attacks and details the various security frameworks put out to ensure the security of the software supply chain. Finally, the paper highlights potential gaps in actor and operation-centered …


Dielectrophoretic Trapping Of Carbon Nanotubes For Temperature Sensing, Kaylee Burdette 2022 Marshall University

Dielectrophoretic Trapping Of Carbon Nanotubes For Temperature Sensing, Kaylee Burdette

Theses, Dissertations and Capstones

Conventional sensors are rapidly approaching efficiency limitations at their current size. In designing more efficient sensors, low dimensional materials such as carbon nanotubes (CNTs), quantum dots, and DNA origami can be used to enable higher degrees of sensitivity. Because of the high atomic surface to core ratio, these materials can be used to detect slight changes in chemical composition, strain, and temperature. CNTs offer unique advantages in different types of sensors due to their electromechanical properties. In temperature sensing, the high responsiveness to temperature and durability can be used to produce an accurate, reliable sensor in even extreme temperatures. This …


An Efficient Ar Model-Based Method For The Detection Of Forced Oscillations In Power Networks: Implementation And Analysis, Maria Waleska Suarez 2022 West Virginia University

An Efficient Ar Model-Based Method For The Detection Of Forced Oscillations In Power Networks: Implementation And Analysis, Maria Waleska Suarez

Graduate Theses, Dissertations, and Problem Reports

An active research topic is the detection of various oscillations that may lead to instability and potential disruption in the operation of a power network. Forced Oscillations (FOs) play a unique role in power system stability among various oscillations. They are perturbances that change the system’s state and are caused for many reasons, including but not limited to persistent load changes and oscillatory load or generation, fault, triplane, and other mechanical anomalies. These factors can hugely affect the power grid by either increasing or decreasing the amplitude, causing corrupt modes leading to blackouts, affecting the equipment involved, delivering poor power …


Synthesizing Dysarthric Speech Using Multi-Speaker Tts For Dsyarthric Speech Recognition, Mohammad Soleymanpour 2022 University of Kentucky

Synthesizing Dysarthric Speech Using Multi-Speaker Tts For Dsyarthric Speech Recognition, Mohammad Soleymanpour

Theses and Dissertations--Electrical and Computer Engineering

Dysarthria is a motor speech disorder often characterized by reduced speech intelligibility through slow, uncoordinated control of speech production muscles. Automatic Speech recognition (ASR) systems may help dysarthric talkers communicate more effectively. However, robust dysarthria-specific ASR requires a significant amount of training speech is required, which is not readily available for dysarthric talkers.

In this dissertation, we investigate dysarthric speech augmentation and synthesis methods. To better understand differences in prosodic and acoustic characteristics of dysarthric spontaneous speech at varying severity levels, a comparative study between typical and dysarthric speech was conducted. These characteristics are important components for dysarthric speech modeling, …


Book Review: This Is How They Tell Me The World Ends: The Cyberweapons Arms Race (2020) By Nicole Perlroth, Amy C. Gaudion 2022 Penn State Dickinson Law

Book Review: This Is How They Tell Me The World Ends: The Cyberweapons Arms Race (2020) By Nicole Perlroth, Amy C. Gaudion

Dickinson Law Review (2017-Present)

No abstract provided.


Deepfakes, Shallowfakes, And The Need For A Private Right Of Action, Eric Kocsis 2022 Penn State Dickinson Law

Deepfakes, Shallowfakes, And The Need For A Private Right Of Action, Eric Kocsis

Dickinson Law Review (2017-Present)

For nearly as long as there have been photographs and videos, people have been editing and manipulating them to make them appear to be something they are not. Usually edited or manipulated photographs are relatively easy to detect, but those days are numbered. Technology has no morality; as it advances, so do the ways it can be misused. The lack of morality is no clearer than with deepfake technology.

People create deepfakes by inputting data sets, most often pictures or videos into a computer. A series of neural networks attempt to mimic the original data set until they are nearly …


Design Project: 3d Printer/Injection Molder Hybrid, Lee Paolucci, Luke Everhart, Brandon Leap, Karson Lorey 2022 The University of Akron

Design Project: 3d Printer/Injection Molder Hybrid, Lee Paolucci, Luke Everhart, Brandon Leap, Karson Lorey

Williams Honors College, Honors Research Projects

In the realm of rapid, small-scale prototyping, there are a few main factors that drive decisions to invest resources in technology to make that prototyping possible. Cost and ease of use are two of the most influential when looking at most SMEs (Small to Medium-sized Enterprises). The U.S. Small Business Administration defines an SME as smaller than 1,250 employees. According to An Assessment of Implementation of Entry-Level 3D Printers from the Perspective of Small Businesses, 59% of small manufacturers had implemented 3D printers as of 2014. However, no matter what technology is used in rapid prototyping, there are common …


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