Engineering Commons^™

Technical Report: A Framework For Confusion Mitigation In Task-Oriented Interactions, Na Li, Robert J. Ross

Articles

Confusion is a mental state that can be triggered in task-oriented interactions and which can if left unattended lead to boredom, frustration, or disengagement from the task at hand. Since previous work has demonstrated that confusion can be detected in embodied situated interactions from visual and auditory cues, in this technique report, we propose appropriate interaction structures which should be used to mitigate confusion. We motivate and describe this dialogue mechanism through an information state-style policy with examples, and also outline the approach we are taking to integrate such a meta-conversational goal alongside core task-oriented considerations in modern data driven …

Potential Of Mirnas In Plasma Extracellular Vesicle For The Stratification Of Prostate Cancer In A South African Population, Dada Oluwaseyi Temilola, Martha Wium, Juliano Paccez, Azola Samkele Salukazana, Hasan H. Otu, Giuseppina M. Carbone, Lisa Kaestner, Stefano Cacciatore, Luiz Fernando Zerbini

Department of Electrical and Computer Engineering: Faculty Publications

Prostate cancer (PCa) is the most common cause of cancer death among African men. The analysis of microRNAs (miRNAs) in plasma extracellular vesicles (EVs) can be utilized as a non-invasive tool for the diagnosis of PCa. In this study, we used small RNA sequencing to profile miRNAs cargo in plasma EVs from South African PCa patients. We evaluated the differential expression of miRNAs between low and high Gleason scores in the plasma EVs of South African patients and in the prostatic tissue from data available in the Cancer Genome Atlas (TCGA) Data Portal. We identified 7 miRNAs differently expressed in …

Integration Of Meta-Multi-Omics Data Using Probabilistic Graphs And External Knowledge, Handan Can, Sree K. Chanumolu, Barbara D. D., Sophie Alvarez, Michael J. Naldrett, Gülhan Ünlü, Hasan H. Otu

Department of Electrical and Computer Engineering: Faculty Publications

Multi-omics has the promise to provide a detailed molecular picture of biological systems. Although obtaining multi-omics data is relatively easy, methods that analyze such data have been lagging. In this paper, we present an algorithm that uses probabilistic graph representations and external knowledge to perform optimal structure learning and deduce a multifarious interaction network for multi-omics data from a bacterial community. Kefir grain, a microbial community that ferments milk and creates kefir, represents a self-renewing, stable, natural microbial community. Kefir has been shown to have a wide range of health benefits. We obtained a controlled bacterial community using the two …

Sel4 On Risc-V - Developing High Assurance Platforms With Modular Open-Source Architectures, Michael A. Doran Jr

Masters Theses

Virtualization is now becoming an industry standard for modern embedded systems. Modern embedded systems can now support multiple applications on a single hardware platform while meeting power and cost requirements. Virtualization on an embedded system is achieved through the design of the hardware-software interface. Instruction set architecture, ISA, defines the hardware-software interface for an embedded system. At the hardware level the ISA, provides extensions to support virtualization.

In addition to an ISA that supports hypervisor extensions it is equally important to provide a hypervisor completely capable of exploiting the benefits of virtualization for securing modern embedded systems. Currently there does …

Controllable Language Generation Using Deep Learning, Rohola Zandie

Electronic Theses and Dissertations

The advent of deep neural networks has sparked a revolution in Artificial Intelligence (AI), notably with the creation of Transformer models like GPT-X and ChatGPT. These models have surpassed previous methods in various Natural Language Processing (NLP) tasks. As the NLP field evolves, there is a need to further understand and question the capabilities of these models. Text generation, a crucial part of NLP, remains an area where our comprehension is limited while being critical in research.

This dissertation focuses on the challenging problem of controlling the general behaviors of language models such as sentiment, topical focus, and logical reasoning. …

Terrain And Adversary-Aware Autonomous Robot Navigation, Aniekan Ufot Inyang

Electronic Theses and Dissertations

In autonomous robot navigation, the robot is able to understand the environment around it for intelligent navigation. From its world model of this environment, it generates a global plan for navigation from a position to a goal based on different factors. This research aims to implement autonomous robot navigation by learning terrain affordances: traversability (moving quickly) and concealment (staying hidden from an adversary) using the Preference-based Inverse Reward Learning (PbIRL) methodology. The PbIRL methodology reduces the barrier of generating initial demonstration data to learn the terrain affordances by using a human expert’s preferences to learn individual weights over the terrain …

Mastering Enterprise Networks, Mathew J. Heath Van Horn

OER Main

The book starts by providing you with step-by-step instructions to create your own virtual environment on any modest PC or laptop running Windows. After setting up your own learning space, we will walk you through many real-world networking concepts that culminate with you building your own enterprise network. Once you are comfortable with creating computer networks, we will then show you how to attack your own network and then how to defend your network against those attacks.

Visualizing Transaction-Level Modeling Simulations Of Deep Neural Networks, Nataniel Farzan, Emad Arasteh

Engineering Technical Reports

The growing complexity of data-intensive software demands constant innovation in computer hardware design. Performance is a critical factor in rapidly evolving applications such as artificial intelligence (AI). Transaction-level modeling (TLM) is a valuable technique used to represent hardware and software behavior in a simulated environment. However, extracting actionable insights from TLM simulations is not a trivial task. We present Netmemvisual, an interactive, cross-platform visualization tool for exposing memory bottlenecks in TLM simulations. We demonstrate how Netmemvisual helps system designers rapidly analyze complex TLM simulations to find memory contention. We describe the project’s current features, experimental results with two state-of-the-art deep …

Understanding The Role Of Interactivity And Explanation In Adaptive Experiences, Lijie Guo

All Dissertations

Adaptive experiences have been an active area of research in the past few decades, accompanied by advances in technology such as machine learning and artificial intelligence. Whether the currently ongoing research on adaptive experiences has focused on personalization algorithms, explainability, user engagement, or privacy and security, there is growing interest and resources in developing and improving these research focuses. Even though the research on adaptive experiences has been dynamic and rapidly evolving, achieving a high level of user engagement in adaptive experiences remains a challenge. %????? This dissertation aims to uncover ways to engage users in adaptive experiences by incorporating …

Performance Modeling Of Inline Compression With Software Caching For Reducing The Memory Footprint In Pysdc, Sansriti Ranjan

All Theses

Modern HPC applications compute and analyze massive amounts of data. The data volume is growing faster than memory capabilities and storage improvements leading to performance bottlenecks. An example of this is pySDC, a framework for solving collocation problems iteratively using parallel-in-time methods. These methods require storing and exchanging 3D volume data for each parallel point in time. If a simulation consists of M parallel-in-time stages, where the full spatial problem has to be stored for the next iteration, the memory demand for a single state variable is M ×Nx ×Ny ×Nz per time-step. For an application simulation with many state …

A Study Of 5g Cellular Connectivity To Unmanned Aerial Vehicles, Jackson Murrin

All Theses

The market of unmanned aerial vehicles (UAVs) has seen significant growth in the past ten years on both the commercial and military sides. The applications for UAVs are endless and options by manufacturers allow users to modify their drones for their specific goals. This industry has opened up the excitement of piloting vehicles in the air, photography, videography, exploration of nature from a different point of view and many other hobbies assisted by the emergence of UAVs. The growth of this industry coincides with the roll out of new 5G cellular network technology. This upgrade in cellular network infrastructure allows …

Generalizable Deep-Learning-Based Wireless Indoor Localization, Ali Owfi

All Theses

The growing interest in indoor localization has been driven by its wide range of applications in areas such as smart homes, industrial automation, and healthcare. With the increasing reliance on wireless devices for location-based services, accurate estimation of device positions within indoor environments has become crucial. Deep learning approaches have shown promise in leveraging wireless parameters like Channel State Information (CSI) and Received Signal Strength Indicator (RSSI) to achieve precise localization. However, despite their success in achieving high accuracy, these deep learning models suffer from limited generalizability, making them unsuitable for deployment in new or dynamic environments without retraining. To …

Seek And Classify: End-To-End Joint Multi-Signal Detection And Classification Using Deep Learning, Prashant Subedi

School of Computing: Dissertations, Theses, and Student Research

The rise in the use of wireless communication has led to the problem of spectrum scarcity in licensed bands. The popularity of Internet of Things (IoT) requires innovative solutions that maximize the use of available spectrum to support the increasing number of connected devices. This thesis tackles two significant problems in wireless communication: the need for efficient spectrum sensing techniques and the scarcity of large, diverse raw in-phase (I) and quadrature (Q) datasets.

The ability to detect and classify modulation of the signals efficiently can enable a cognitive radio to monitor the spectrum activity in real time and utilize unused …

Mirror Position Detection In A Catoptric Surface, Run Zhang

McKelvey School of Engineering Graduate Student Theses & Dissertations

The Catoptric Surface research project is a pioneering exploration of controlling daylight effects within built environments. In this thesis, we focus on the mirror position detection problem, which plays a vital role in achieving dynamic control over the direction of reflected light within a space. To address the challenge of mirror position detection, we employ computer vision techniques, specifically edge detection and the RANdom SAmple Consensus (RANSAC) algorithm. Edge detection is utilized to identify significant changes in intensity or color, corresponding to object boundaries, while RANSAC is applied for ellipse fitting. By iteratively selecting minimal subsets of points and fitting …

Virtual Prototyping Of Pebb Based Power Electronics System For Ground Vehicles, Yi Li

All Theses

Power electronics are heavily involved in power and energy systems in plenty of applications nowadays. The increase of demand brings more challenges into simulations for development. Considering the complexity of the systems and high frequency operational conditions, this paper presents comprehensive research on modeling, simulating, and validation on ground vehicle propulsion system applications.

To reduce the computational burden, the Power Electronics Building Blocks concept is utilized to simplify the structure of modeling under different conversion scenarios in ground vehicle systems. In addition, the Average and Switching versions models are included. To speedup the simulation, the engagement of advanced computing technique …

Faults Segmentation In Levee Systems Using Deep Learning Approaches, Manisha Panta

LSU New Orleans Theses and Dissertations

Levees are earthen structures constructed to mitigate flooding in low-lying areas. Although levee systems can reduce flood risks, they cannot completely eliminate them. Failures within flood control systems due to inadequate maintenance or strong water currents can lead to significant property damage and catastrophic loss of life, as was seen during Hurricane Katrina. Consequently, regular inspections are essential to identify and address any issues with the levees promptly. However, current inspection methods rely on manual techniques that are time-consuming, labor-intensive, and prone to human error. Therefore, this study proposes using deep learning models for more efficient and frequent assessment of …

Robust Control Of Contact-Rich Robots Via Neural Bayesian Inference, Nardos Ayele Ashenafi

Boise State University Theses and Dissertations

We provide several data-driven control design frameworks for contact-rich robotic systems. These systems exhibit continuous state flows and discrete state transitions, which are governed by distinct equations of motion. Hence, it is difficult to design a single policy that can control the system in all modes. Typically, hybrid systems are controlled by multi-modal policies, each manually triggered based on observed states. However, as the number of potential contacts increase, the number of policies can grow exponentially and the control-switching scheme becomes too complicated to parameterize. To address this issue, we design contact-aware data-driven controllers given by deep-net mixture of experts. …

Experimental Study Of Linux Flightsize Estimation, Mingrui Zhang

School of Computing: Dissertations, Theses, and Student Research

Transmission Control Protocol (TCP) is a fundamental Internet protocol responsible for controlling and coordinating the Internet traffic. As a result, TCP significantly influences the overall performance and stability of the Internet. One critical information required by a TCP connection to make decisions is FlightSize, which is the total amount of outstanding data contributed by the connection to the Internet. The FlightSize information is used by a TCP connection to determine its future sending rate and also avoid traffic congestion and collapse in the Internet. Consequently, an inaccurate estimation of FlightSize can result in degraded performance and instability of the Internet. …

Cyberinet: Integrated Semi-Modular Sensors For The Computer-Augmented Clarinet, Matthew Bardin

LSU Doctoral Dissertations

The Cyberinet is a new Augmented instrument designed to easily and intuitively provide a method of computer-enhanced performance to the Clarinetist to allow for greater control and expressiveness in a performance. A performer utilizing the Cyberinet is able to seamlessly switch between a traditional performance setting and an augmented one. Towards this, the Cyberinet is a hardware replacement for a portion of a Clarinet containing a variety of sensors embedded within the unit. These sensors collect various real time data motion data of the performer and air fow within the instrument. Additional sensors can be connected to the Cyberinet to …

Reinforcing Digital Trust For Cloud Manufacturing Through Data Provenance Using Ethereum Smart Contracts, Trupti Narayan Rane

Engineering Management & Systems Engineering Theses & Dissertations

Cloud Manufacturing(CMfg) is an advanced manufacturing model that caters to fast-paced agile requirements (Putnik, 2012). For manufacturing complex products that require extensive resources, manufacturers explore advanced manufacturing techniques like CMfg as it becomes infeasible to achieve high standards through complete ownership of manufacturing artifacts (Kuan et al., 2011). CMfg, with other names such as Manufacturing as a Service (MaaS) and Cyber Manufacturing (NSF, 2020), addresses the shortcoming of traditional manufacturing by building a virtual cyber enterprise of geographically distributed entities that manufacture custom products through collaboration.

With manufacturing venturing into cyberspace, Digital Trust issues concerning product quality, data, and intellectual …

An Advanced Simulation Architecture For Testing Autonomous And Connected Vehicles Enabled By Virtual Reality, Defu Cui

Electrical & Computer Engineering Theses & Dissertations

With the advancement of intelligent transportation systems, autonomous driving and connected driving are seen as potential solutions to alleviate traffic congestion, enhance traffic safety, and improve efficiency. Extensive testing and validation of autonomous vehicles (AVs) and connected vehicles (CVs) including connected autonomous vehicles are crucial to ensure their safety and reliability. However, testing and validating AVs and CVs on public roads faces challenges such as high costs, inadequate support from transportation infrastructure with communication technologies, and safety concerns, among others. Simulations have become essential tools for testing autonomous driving and connected driving. As mixed traffic involves multiple domains including traffic …

Data-Driven Predictive Modeling To Enhance Search Efficiency Of Glowworm-Inspired Robotic Swarms In Multiple Emission Source Localization Tasks, Payal Nandi

Mechanical & Aerospace Engineering Theses & Dissertations

In time-sensitive search and rescue applications, a team of multiple mobile robots broadens the scope of operational capabilities. Scaling multi-robot systems (< 10 agents) to larger robot teams (10 – 100 agents) using centralized coordination schemes becomes computationally intractable during runtime. One solution to this problem is inspired by swarm intelligence principles found in nature, offering the benefits of decentralized control, fault tolerance to individual failures, and self-organizing adaptability. Glowworm swarm optimization (GSO) is unique among swarm-based algorithms as it simultaneously focuses on searching for multiple targets. This thesis presents GPR-GSO—a modification to the GSO algorithm that incorporates Gaussian Process Regression (GPR) based data-driven predictive modeling—to improve the search efficiency of robotic swarms in multiple emission source localization tasks. The problem formulation and methods are presented, followed by numerical simulations to illustrate the working of the algorithm. Results from a comparative analysis show that the GPR-GSO algorithm exceeds the performance of the benchmark GSO algorithm on evaluation metrics of swarm size, search completion time, and travel distance.

A Data-Driven Multi-Regime Approach For Predicting Real-Time Energy Consumption Of Industrial Machines., Abdulgani Kahraman

Electronic Theses and Dissertations

This thesis focuses on methods for improving energy consumption prediction performance in complex industrial machines. Working with real-world industrial machines brings several challenges, including data access, algorithmic bias, data privacy, and the interpretation of machine learning algorithms. To effectively manage energy consumption in the industrial sector, it is essential to develop a framework that enhances prediction performance, reduces energy costs, and mitigates air pollution in heavy industrial machine operations. This study aims to assist managers in making informed decisions and driving the transition towards green manufacturing. The energy consumption of industrial machinery is substantial, and the recent increase in CO2 …

Robust And Uncertainty-Aware Software Vulnerability Detection Using Bayesian Recurrent Neural Networks, Orune Aminul

Theses and Dissertations

Software systems are prone to code defects or vulnerabilities, resulting in several cyberattacks such as hacking, identity breach and information leakage leading to system failure. Vulnerabilities in software systems have severe societal implications, including threats to public safety, financial damage, and even risks to national security. Identifying and mitigating software vulnerabilities is critical to protect organizations and societies from potential threats. Machine learning algorithms have been employed to detect and classify potential vulnerabilities in software source code automatically. However, these algorithms are not robust to noise or malicious attacks and cannot quantify uncertainty in the model’s output. Quantifying uncertainty in …

Sales And Stock Management System, Rashmika Gaddam Ms

Electronic Theses, Projects, and Dissertations

ABSTRACT

Grocery stores using Excel for managing sales and stock management could involve maintaining separate sheets for sales and stock data, with revenue/cost. This system could provide a basic level of tracking and analysis, allowing the grocery store to monitor sales trends and stock levels. However, using Excel for this purpose is not without its challenges. For example, the manual nature of data entry in excel can result in errors and inconsistencies, particularly if multiple people are involved in maintaining the sheets. Additionally, as the volume of sales and stock data grows, the Excel spreadsheet can become unwieldy and slow, …

Context-Aware Event Forecasting Via Graph Disentanglement, Yunshan Ma, Chenchen Ye, Zijian Wu, Xiang Wang, Yixin Cao, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Event forecasting has been a demanding and challenging task throughout the entire human history. It plays a pivotal role in crisis alarming and disaster prevention in various aspects of the whole society. The task of event forecasting aims to model the relational and temporal patterns based on historical events and makes forecasting to what will happen in the future. Most existing studies on event forecasting formulate it as a problem of link prediction on temporal event graphs. However, such pure structured formulation suffers from two main limitations: 1) most events fall into general and high-level types in the event ontology, …

The Heterogeneous Vehicle Routing Problem With Multiple Time Windows For The E-Waste Collection Problem, Aldy Gunawan, Minh P.K Nguyen, Vincent F. Yu, Dang Viet Anh Nguyen

Research Collection School Of Computing and Information Systems

Waste from electrical and electronic equipment (WEEE) or e-waste describes end-of-life electronic products that are discarded. Due to their toxic and negative impacts to humans' health, many publications have been proposed to handle, however, studies related to e-waste collection and transportation to waste disposal sites are not widely studied so far. This study proposes a mixed integer linear programming (MILP) model to solve the e-waste collecting problem by formulating it as the heterogeneous vehicle routing problem with multiple time windows (HVRPMTW). The model is validated with newly developed benchmark instances that are solved by commercial software, CPLEX. The model is …

Finserv Android Application, Harsh Piyushkumar Shah

Electronic Theses, Projects, and Dissertations

The FINSERV Android application is a mobile tool designed for individuals to manage and track their finances. In financially complex world, many people struggle to maintain a clear overview of their income, expenses, and financial goals. This application aims to bridge that gap by providing users with a powerful and user-friendly platform to efficiently monitor and optimize their personal finances.

With the Personal Finance Tracking Android Application, users can effortlessly track their income and expenses, categorize transactions, and gain valuable insights into their spending patterns. The application offers features such as expense categorization and real-time expense tracking.

To enhance usability …

Transaction Management Sysyem For A Publisher, Hassain Shareef Mohammed Jr

Electronic Theses, Projects, and Dissertations

Managing the day-to-day operations of a publishing house isn't easy. For example, it's hard to keep track of stocks, manage vendor orders, and maintain transaction records. Our project titled Transaction Management System aims to solve these problems by offering a single tool that helps standardize and digitize publishing operations. It assists in automating and improving the efficiency of the various processes involved in a publishing house. The Transaction Management System is a full-stack web application that can be accessed through an internet browser. The user experience and interface are simple and easy to use so that users can find information …

Accurate Orientation Control Of Tendon Driven Continuum Robots That Exhibit Elasticity, Manu Srivastava

All Dissertations

This dissertation makes new contributions to the modeling and implementation of Tendon Driven Continuum Robots (TDCRs). Specifically, motivated by 3D printing of concrete using a continuum hose robot in construction applications, we focus on TDCRs featuring compliance in the robot backbone and actuating tendons, e.g. surgical robots/endoscopes/catheters with tendon actuation. We expand previous mechanics-based models to show how and why such compliance significantly restricts performance when traditional kinematics-based planning and control techniques are applied.

The main contribution of this work is a new Elasticity Compensation(EC) model that explains why the ad hoc approach of preloading/pretensioning the tendons compensates for compliance …