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Articles 631 - 660 of 10019
Full-Text Articles in Entire DC Network
Blockchain Applications And Industrial Development, Hamad Aiman
Blockchain Applications And Industrial Development, Hamad Aiman
Theses
World economies and industries are witnessing a rapid yet discreet change in the perception of data, information, and finance, paradigms that have been static for centuries. This shift is fueled by the expansive network of the internet, which is still far from being fully utilized. Emerging from this digital expanse, blockchain technology today influences how finance, services, and data collection are conducted. In a dynamically evolving economy, this innovative development prompts organizations and individuals with high stakes to accelerate their digital transformation. This research paper aims to educate readers about the potential impact of blockchain technology and digital assets across …
Faculty Library News - April 2024, Rit Libraries
Faculty Library News - April 2024, Rit Libraries
RIT Digital Archives
No abstract provided.
Box Packaging Waste Reduction By Largest Area First Fit Algorithm And Minimum Cuboid Estimation Of Irregular Shape Products, Jimmy Kwon, Sungmin Kwon
Box Packaging Waste Reduction By Largest Area First Fit Algorithm And Minimum Cuboid Estimation Of Irregular Shape Products, Jimmy Kwon, Sungmin Kwon
Journal of Applied Packaging Research
Nowadays, packaging waste is a prevalent issue due to the increase in deliveries from online shopping. In this research paper, a new approach to the issue of cardboard box packaging waste is proposed by selecting an optimal box that will contain both regular and irregular products while minimizing wasted volume. The method can be utilized so that packaging workers can select an appropriate, yet sustainable box. For computing a minimal cuboid of irregular objects, the system setup with two cameras is prepared to capture the overhead and sideview images, estimating the box's width, depth, and height in pixels. The proposed …
A New Vicarious Technique For Radiometric And Spatial Calibration Of Drone-Based Multispectral And Hyperspectral Imaging Systems, David N. Conran
A New Vicarious Technique For Radiometric And Spatial Calibration Of Drone-Based Multispectral And Hyperspectral Imaging Systems, David N. Conran
Theses
A new technology (convex mirrors) used for radiometric and spatial characterization of remote sensing imaging systems has demonstrated equal, but unique results when compared to Lambertian targets for vicarious calibration. Using convex mirrors to characterize the radiometric and spatial response of hyperspectral and multispectral imaging systems has yet to be thoroughly investigated for drone-based platforms. When imaged, a convex mirror produces a known radiant intensity source that can characterizes the radiometric and spatial performance of an imaging system. The simultaneous assessment supports a unique understanding of the hyperspectral and multispectral instrument’s response for vicarious characterization. Assessing a new technique for …
Enhancing Pump Efficiency And Reducing Energy Consumption At The Sea Water Distillation Plant Of An Aluminium Company, Essa Binshaqooi
Enhancing Pump Efficiency And Reducing Energy Consumption At The Sea Water Distillation Plant Of An Aluminium Company, Essa Binshaqooi
Theses
The objective of this project is to enhance pump efficiency by at least 10% and reduce energy consumption by 5% in the Sea Water Distillation Unit of a major Aluminium Company. Challenges include progressive wear, abrasion, and sea water scaling, which contribute to major losses in pumps, leading to inefficient performance and increased operational costs. Failure Mode Analysis (FMA) and Root Cause Analysis (RCA) were conducted on both Sea Water Pumps (SWPs) and Brine Circulation Pumps (BRPs) to identify these major losses. Strategic improvements recommended for both pumps include the required pump rating, changes in composition, and performance monitoring. Detailed …
Design And Test Of Wpum Topography Monitor For Iqos, Rawah Azeez
Design And Test Of Wpum Topography Monitor For Iqos, Rawah Azeez
Theses
With the emergence of diverse tobacco product forms, such as electronic cigarettes and heat-not-burn, the global user base has surged to an estimated 1.3 billion. In the United States, 28.3 million adults and 3.08 million middle and high school adolescents engage in tobacco product use. However, our understanding of the usage behaviors of these various products is lacking. Puff topography, which measures the inhalation patterns of tobacco products, provides a wealth of information, including puff flow rate, duration, volume, and more. This information is crucial in understanding the health effects of tobacco products and the influence of usage behavior on …
Supercook: Design Interactive Culinary Experiences With Ai Technology, Yize Peng
Supercook: Design Interactive Culinary Experiences With Ai Technology, Yize Peng
Theses
The project 'SuperCook' is a groundbreaking design project that explores the integration of AI with culinary apps. It aims to revolutionize the kitchen experience by connecting users to new and accessible culinary adventures through personalized recipe recommendations, real-time cooking guidance, and interactive meal planning. By leveraging AI technology, 'SuperCook' not only enhances user convenience and efficiency but also fosters a deeper engagement with cooking and promotes healthier eating habits. This thesis delves into the design process, user testing, and iterative improvements that culminated in a user-centered, intuitive, and visually appealing UI/UX solution for modern cooking enthusiasts. In designing 'SuperCook,' attention …
Using Data Analytics To Predict Government Employee Turnover, Aisha Alshamsi
Using Data Analytics To Predict Government Employee Turnover, Aisha Alshamsi
Theses
Employee turnover is a significant problem in many organizations, resulting in increased costs, decreased productivity, and decreased morale. The aim of this research is to predict employee turnover using data analysis algorithms and develop a predictive model that can be used to identify employees who are at risk of leaving the organization. This study preprocesses data on employee turnover rates, employee demographics, employee satisfaction, and other relevant factors, and uses data analysis machine learning algorithms such as Logistic regression, Decision tree, and XGBoost to analyze the data and develop a predictive model. The result of the study helps impact on …
Novel Methods For Modeling And Treating Biofilm Infections, Emily Lazarus
Novel Methods For Modeling And Treating Biofilm Infections, Emily Lazarus
Theses
Biofilms are responsible for the development of chronic infections, which are 10-1000 times more resistant to antimicrobial agents than two-dimensional (2D) planktonic culture. Traditionally, 2D planktonic cultures are used to study efficacy of antimicrobial treatments but 2D cultures have several shortcomings such as increased sensitivity to treatments, lack of complexity of the three-dimensional (3D) environment, limited host defense mechanisms, and lack the structural thickness of natural biofilms. Biofilm-related infections play a critical role in the delayed healing process of chronic skin wounds, and while treatments for chronic skin wounds exist, including negative pressure wound healing (NPWT), biofilm infections still prevail. …
Low Power Logic Locking Using Design Space Modeling To Achieve System-Wide Security, Long Lam
Low Power Logic Locking Using Design Space Modeling To Achieve System-Wide Security, Long Lam
Theses
Rising design complexity and smaller technology nodes are escalating fabrication costs, prompting design houses to outsource to untrusted external facilities, which raises trust and privacy concerns. These concerns stem from the risk of security breaches like IP piracy, reverse engineering, and hardware trojans. The critical need to protect design intellectual property prompted the development of logic locking, a combinational hardware security technique that corrupts the functionality of a design without the correct secret key. However, the effectiveness of logic locking varies substantially based on how and where it is implemented within a system, including the specific technique families selected, the …
Adjoining Gates: Mitigating Optical Side-Channel Attacks On Integrated Circuits Through Security-Aware Placement, Thomas Wojtal
Adjoining Gates: Mitigating Optical Side-Channel Attacks On Integrated Circuits Through Security-Aware Placement, Thomas Wojtal
Theses
With the rise of outsourcing in Integrated Circuit (IC) fabrication processes, vulnerabilities in chip security have become a growing concern. These vulnerabilities can lead to attacks such as reverse-engineering, piracy, overproduction, and malicious modification of high-value intellectual property (IP) in a design. In light of this, a method called logic locking has been developed to protect chips prior to end-user shipment. Logic locking incorporates additional logic gates in a design to conceal a chip’s functionality during manufacture and test processes. However, recent developments have shown logic locking to be vulnerable to optical side-channel attacks. In this work, we explore these …
Improving Adaptation Of Deep Learning With Inductive Bias, Xiajun Jiang
Improving Adaptation Of Deep Learning With Inductive Bias, Xiajun Jiang
Theses
Human intelligence is strong at adapting to a small number of observations, partially because of the human ability to 1) use given knowledge and 2) distill knowledge from related but different data to guide learning for future tasks, where such ability is the inductive bias during learning. Deep learning shows a promising solution to artificial intelligence. However, generalizing or adapting deep learning models to heterogeneous tasks remains an open question. Existing data-driven models often ignore prior knowledge about the underlying problems of interest, or have limitations in incorporating complex knowledge into neural networks. The one-size-fit-all formula assumes the training and …
An Intelligent Framework For Efficiently Utilizing Distributed Heterogeneous Resources To Improve Hpc Application Performance, Moiz Arif
Theses
High-Performance Computing (HPC) workloads are being widely used to solve complex problems in scientific applications from diverse domains, such as weather forecasting, medical diagnostics, and fluid dynamics simulation. HPC workloads are traditionally executed on baremetal HPC systems, containers, functions, or as workflows or ensembles. These workloads consume a large amount of data and have large memory and storage requirements that typically exceed the limited amount of main memory and storage available on an HPC system. HPC workloads such as deep learning (DL) are executed on platforms such as TensorFlow or PyTorch, are oblivious to the availability and performance profiles of …
Predictive Maintenance On Drone Batteries Failure Using Machine Learning, Khalifa Jamal Almannaei
Predictive Maintenance On Drone Batteries Failure Using Machine Learning, Khalifa Jamal Almannaei
Theses
Predictive maintenance, powered by machine learning models, presents an innovative solution to address the limitations of drone battery maintenance. The core aim of this study is to design and implement machine learning models suitable for drone batteries, predict battery health, and prescribe maintenance actions. The ultimate scope is to improve operational reliability, safety, and cost-efficiency for drone applications while advancing sustainability and efficiency within the drone industry. By integrating predictive maintenance, the management of drone batteries can be optimized, leading to more reliable, and cost-effective drone operations, the proposal will seek to identify different factors that impacts the health and …
Optimizing V2v Energy Exchange Using Ai, Marwa Alghawi
Optimizing V2v Energy Exchange Using Ai, Marwa Alghawi
Theses
A key factor in promoting sustainable economies, industries, and society is the use of electric vehicles (EVs). They are an important step toward a greener future since they reduce greenhouse gas emissions, improve air quality, and encourage energy independence. The demand for charging stations (CSs) will undoubtedly rise as the global EV market continues to grow over the next few decades, requiring significant investments from both public and private players. By creating a cutting-edge AI model, this work tackles the crucial problems of EVs range prediction and charging optimization decisions. The contributions are summarized as the below: 1. Developed AI …
Optimizing Supply Chain Dynamics Using Machine Learning, Mohammad Zubin Siddiqui
Optimizing Supply Chain Dynamics Using Machine Learning, Mohammad Zubin Siddiqui
Theses
Supply chains face many challenges in today’s business environment. This paper examines how advanced analytics can be used to improve supply chain efficiency and resilience with a particular focus on demand forecasting and late delivery analysis. The thesis focuses on two areas, which are forecasting demand and analyzing late deliveries. With the help of data-driven models for forecasting demand and pinpointing reasons behind delayed shipments, establishments can take appropriate measures that will reduce risks and enhance operational efficiency. A complete analytic framework is suggested that integrates sophisticated analytics into supply chain management so that organizations can optimize all their operations …
Robust Machine Learning Under Vulnerable Cyberinfrastructure And Varying Data Quality, Sergei Chuprov
Robust Machine Learning Under Vulnerable Cyberinfrastructure And Varying Data Quality, Sergei Chuprov
Theses
In our study, we investigate Machine Learning (ML) application robustness in ML Integrated with Network (MLIN) systems. We consider MLIN as an integration of three major components and interrelations between them: data sources, network facilities, and ML application. In contrast to the conventional approaches that focus on each separate component, we concentrate on their interrelationships, and consider them from the system integration perspective. We formulate our primary goal as to develop methods and tools aimed at assuring ML application performance towards Data Quality (DQ) variation in MLIN through improving ML application robustness. We examine the prior work on ML robustness …
Learning From Disagreement In Human-Annotated Datasets, Tharindu Cyril Weerasooriya
Learning From Disagreement In Human-Annotated Datasets, Tharindu Cyril Weerasooriya
Theses
Artificial intelligence (AI) systems frequently need to learn from human decision makers, which aids in scaling systems for mass use. We see this in automated financial decisions, manufacturing processes, self- driving cars, and content moderation on social networks. These systems are built on human values and trained to mimic human decision-making through human annotation. However, different groups of human annotators, including domain experts, annotate content differently, leading to disagreements. Some practitioners treat dissenting opinions as “label noise”. A common approach to dealing with disagreement is to consider a majority vote, which effectively conceals the disagreements from the trained model. Although …
Predictive Analytics Of Road Traffic Incidents, A Machine Learning Approach, Maryam Essa Jaji
Predictive Analytics Of Road Traffic Incidents, A Machine Learning Approach, Maryam Essa Jaji
Theses
Traffic accidents rank among the world's most serious concerns due to the high number of deaths, injuries, and fatalities as well as the enormous financial losses they cause every year. Road travel is a necessary component of modern civilization, but because of the rise in traffic accidents, it costs the world economy billions of dollars and over a million deaths annually. Road accidents can be caused by a variety of elements. It can be possible to take action to lessen the severity and extent of the effects if these elements are better recognized and predicted. The goal of this project …
“Art For The Millions:” The Evolution Of Informal Learning From The Charleston Museum To The New Deal, Kristen Walker
“Art For The Millions:” The Evolution Of Informal Learning From The Charleston Museum To The New Deal, Kristen Walker
Theses
The advent of the first museum in the United States in 1773, The Charleston Museum, sparked a shift in the way education is perceived and how it can be conducted. However, only recently has the intentional implementation of programs and exhibitions been created in a digestible way for the public. This thesis discusses how informal learning has evolved since the establishment of the Charleston Museum and the legacy of the Federal Art Project regarding informal learning and art education. Key research methods include the examination of primary and secondary resources, including oral histories held by the Smithsonian Archives of American …
Transfer Learning Across Domains And Sensing Modalities, Chowdhury Sadman Jahan
Transfer Learning Across Domains And Sensing Modalities, Chowdhury Sadman Jahan
Theses
Transfer learning facilitates the training of a deep learning (DL) model with limited or no labeled data, by initializing the network parameters using a similar model already trained on a different but related dataset or task. This dissertation examines two special cases of transfer learning for image classification tasks: cross-modal supervised learning, and cross-domain unsupervised adaptation. This dissertation proposes to apply cross-modal transfer learning to guide the training process of a DL model on Synthetic Aperture Radar (SAR) images via knowledge distillation from a DL model trained on corresponding electro-optical (EO) images. Furthermore, this approach explores class-balanced sampling strategies and …
Learning About Ai: Level Up Your Skills Without Overwhelming Your Mind, Jennifer Freer, Lara Nicosia
Learning About Ai: Level Up Your Skills Without Overwhelming Your Mind, Jennifer Freer, Lara Nicosia
Presentations and other scholarship
OpenAI and deep learning and neural networks, oh my! The swiftly developing landscape of artificial intelligence, combined with its rapid integration into our work and personal lives, can feel confusing and overwhelming. This session will help you think about AI in your own work and plan your own personal AI learning journey, while also providing thoughtful recommendations on how both you and your users can get started. The presenters will discuss common terminology, user-friendly resources for understanding AI, questions to ask when exploring AI tools, and ideas on how to start building your own knowledge on this topic. The information …
On The Use Of Gauge Functions To Obtain Convergent Power Series Solutions To Nonlinear Odes, Nastaran Naghshineh
On The Use Of Gauge Functions To Obtain Convergent Power Series Solutions To Nonlinear Odes, Nastaran Naghshineh
Theses
This dissertation examines the power series solutions---and their analytic continuation via gauge transformations---of three classical nonlinear ordinary differential equations arising in fluid mechanics that are mathematically related by their large-distance asymptotic behaviors in semi-infinite domains. The first problem examines the influence of surface tension and gravitational forces to form a static air--liquid interface that intersects a flat wall at a given contact angle and limits to a flat pool away from the wall. The second problem considers the related configuration of an axisymmetric air--liquid interface formed when the flat wall is replaced with a right circular cylinder. In both problems, …
Frequency Multiplication Of Microwave Signals Via The Photonic Domain, Mohamed R. Maafa
Frequency Multiplication Of Microwave Signals Via The Photonic Domain, Mohamed R. Maafa
Theses
Microwave signals play key roles in modern communication systems and frequency multiplication provide a way to create higher microwave-signal frequencies. Using the photonics domain to perform frequency multiplication can, in principle, take advantage of the low loss and high bandwidth features of the photonic domain. However, most research to date is limited by photonic system having too many active components, complicated means of frequency selectibility, and reliance on filters. I explore, model, and experimentally demonstrate new techniques of microwave signal multiplication, leveraging the notions of polarization diversity and multiplexing in the photonic domain. For doubling and quadrupling techniques, I demonstrate …
Bitcoin Short-Term Price Prediction Using Time Series Analysis, Alanood Alkamali
Bitcoin Short-Term Price Prediction Using Time Series Analysis, Alanood Alkamali
Theses
This thesis explores the application of Autoregressive Integrated Moving Average (ARIMA) model to predict Bitcoin prices, a prominent and volatile cryptocurrency. The research falls within the context of financial forecasting, focusing specifically on the cryptocurrency markets. The primary research question is: “Can time series analysis be used to predict the future price of Bitcoin?” To answer this question, historical Bitcoin daily price data from 17/09/2014 to 17/09/2023 was obtained from Kaggle and analyzed. The study employs ARIMA modeling techniques to capture the autocorrelation, seasonality, and trend present in Bitcoin price time series. As a prerequisite for ARIMA modeling, the data …
Faculty Library News - February 2024, Rit Libraries
Faculty Library News - February 2024, Rit Libraries
RIT Digital Archives
No abstract provided.
Student Library News - February 2024, Rit Libraries
Student Library News - February 2024, Rit Libraries
RIT Digital Archives
No abstract provided.
An Afrocentric Source Code For Afrofuturism: Welcome To Neosankofa, Aaron X. Smith
An Afrocentric Source Code For Afrofuturism: Welcome To Neosankofa, Aaron X. Smith
Third Stone
This research investigates the potentialities for ancient African wisdom to guide humanity into a more harmonious, advanced Afrofuturistic positive coexistence. The research presented herein, investigates the long unbroken emphasis on the art and cultural strategy of looking back in order to optimally move forward as a community, a nation, and an international collective. A guiding question in this historical investigation is, how does the African past inform, empower, and elevate us into the future. The results of this Afrocentric ethnographic interrogation unearth little known connections to the subject Afrocentric Futurism, from previous Academics who expressed similar notions later defined under …
Sustainable Futures-Integrating Indigenous Perspectives Into An Environmental Assessment Framework: An Analysis Of The Mauri Model, Anna Bettini
Journal of Environmental Sustainability
The twin concepts of sustainable development and sustainability have been key points in new policies. Nonetheless, only the Western scientific perspective is typically considered, excluding other voices and leading to a very narrow vision of “sustainability”. The following article investigates the benefits to including indigenous knowledge and principles, considering their values rather than limitations and presents two specific case studies using the Mauri Model Decision Making Framework, a tool applied for environmental assessment, seen as a more cultural-friendly sustainable approach.
Mid-Infrared Dust Reverberation Mapping Of Active Galactic Nuclei, Ashley Frank
Mid-Infrared Dust Reverberation Mapping Of Active Galactic Nuclei, Ashley Frank
Theses
One of the main components of the unified model of AGN (active galactic nuclei) is the circumnuclear dusty torus. The torus often obscures our view of the ''central engine" of the AGN, therefore it is important to understand its size and structure. Reverberation mapping can be used to constrain the size of the torus, and relies on the response of the torus dust emission to the variations in the driving optical/UV emission of the accretion disk. The time lag between the optical emission and the infrared response can be used to constrain the distance between the inner region of the …