Governors State University
Biola University
Gettysburg College
Macalester College
Bryant University
Utah State University
Loyola Marymount University
University of New Haven
Leveraging Aruco Fiducial Marker System For Bridge Displacement Estimation Using Unmanned Aerial Vehicles,
2023
University of Nebraska-Lincoln
Leveraging Aruco Fiducial Marker System For Bridge Displacement Estimation Using Unmanned Aerial Vehicles, Mohamed Aly
Computer Science and Engineering: Theses, Dissertations, and Student Research
The use of unmanned aerial vehicles (UAVs) in construction sites has been widely growing for surveying and inspection purposes. Their mobility and agility have enabled engineers to use UAVs in Structural Health Monitoring (SHM) applications to overcome the limitations of traditional approaches that require labor-intensive installation, extended time, and long-term maintenance. One of the critical applications of SHM is measuring bridge deflections during the bridge operation period. Due to the complex remote sites of bridges, remote sensing techniques, such as camera-equipped drones, can facilitate measuring bridge deflections. This work takes a step to build a pipeline using the state-of-the-art computer …
A Generative Neural Network For Discovering Near Optimaldynamic Inductive Power Transfer Systems,
2023
Utah State University
A Generative Neural Network For Discovering Near Optimaldynamic Inductive Power Transfer Systems, Md Shain Shahid Chowdhury Oni
All Graduate Theses and Dissertations
An urgent need is to electrify transportation to lower carbon emissions into the atmosphere. Wireless charging makes electrical vehicles (EVs) more convenient and cheaper because energy is transferred to the vehicle without the need to plug it in. Dynamic wireless charging is particularly interesting, where the vehicle does not need to stop to receive the energy. This technology requires the EV and the roadway to include coils of wire, where the roadway coil is energized as the vehicle passes over it to induce an electrical current in the EV coil through electromagnetic induction. However, the problem of designing the two …
Using Object Detection To Navigate A Game Playfield,
2023
Marquette University
Using Object Detection To Navigate A Game Playfield, Peter Kearnan Hyde-Smith
Master's Theses (2009 -)
Perhaps the crown jewel of AI is the self-navigating agent. To take many sources of data as input and use it to traverse complex and varied areas while mitigating risk and damage to the vehicle that is being controlled, visual object detection is a key part of the overall suite of this technology. While much efforts are being put towards real-world applications, for example self-driving cars, healthcare related issues and automated manufacturing, we apply object detection in a different way; the automation of movement across a video game play field. We take the TensorFlow Object Detection API and use it …
The Vehicle Routing Problem With Simultaneous Pickup And Delivery And Occasional Drivers,
2023
Singapore Management University
The Vehicle Routing Problem With Simultaneous Pickup And Delivery And Occasional Drivers, Vincent F. Yu, Grace Aloina, Panca Jodiawan, Aldy Gunawan, Tsung-C. Huang
Research Collection School Of Computing and Information Systems
This research addresses the Vehicle Routing Problem with Simultaneous Pickup and Delivery and Occasional Drivers (VRPSPDOD), which is inspired from the importance of addressing product returns and the emerging notion of involving available crowds to perform pickup and delivery activities in exchange for some compensation. At the depot, a set of regular vehicles is available to deliver and/or pick up customers’ goods. A set of occasional drivers, each defined by their origin, destination, and flexibility, is also able to help serve the customers. The objective of VRPSPDOD is to minimize the total traveling cost of operating regular vehicles and total …
Session11: Skip-Gcn : A Framework For Hierarchical Graph Representation Learning,
2023
SDSMT
Session11: Skip-Gcn : A Framework For Hierarchical Graph Representation Learning, Jackson Cates, Justin Lewis, Randy Hoover, Kyle Caudle
SDSU Data Science Symposium
Recently there has been high demand for the representation learning of graphs. Graphs are a complex data structure that contains both topology and features. There are first several domains for graphs, such as infectious disease contact tracing and social media network communications interactions. The literature describes several methods developed that work to represent nodes in an embedding space, allowing for classical techniques to perform node classification and prediction. One such method is the graph convolutional neural network that aggregates the node neighbor’s features to create the embedding. Another method, Walklets, takes advantage of the topological information stored in a graph …
Temporal Tensor Factorization For Multidimensional Forecasting,
2023
SDSMT
Temporal Tensor Factorization For Multidimensional Forecasting, Jackson Cates, Karissa Scipke, Randy Hoover, Kyle Caudle
SDSU Data Science Symposium
In the era of big data, there is a need for forecasting high-dimensional time series that might be incomplete, sparse, and/or nonstationary. The current research aims to solve this problem for two-dimensional data through a combination of temporal matrix factorization (TMF) and low-rank tensor factorization. From this method, we propose an expansion of TMF to two-dimensional data: temporal tensor factorization (TTF). The current research aims to interpolate missing values via low-rank tensor factorization, which produces a latent space of the original multilinear time series. We then can perform forecasting in the latent space. We present experimental results of the proposed …
A Proposed Meta-Reality Immersive Development Pipeline: Generative Ai Models And Extended Reality (Xr) Content For The Metaverse,
2023
Lindenwood University
A Proposed Meta-Reality Immersive Development Pipeline: Generative Ai Models And Extended Reality (Xr) Content For The Metaverse, Jeremiah Ratican, James Hutson, Andrew Wright
Faculty Scholarship
The realization of an interoperable and scalable virtual platform, currently known as the “metaverse,” is inevitable, but many technological challenges need to be overcome first. With the metaverse still in a nascent phase, research currently indicates that building a new 3D social environment capable of interoperable avatars and digital transactions will represent most of the initial investment in time and capital. The return on investment, however, is worth the financial risk for firms like Meta, Google, and Apple. While the current virtual space of the metaverse is worth $6.30 billion, that is expected to grow to $84.09 billion by the …
Enhanced Convolutional Neural Network For Non-Small Cell Lung Cancer Classification,
2023
Jordan University of Science and Technology
Enhanced Convolutional Neural Network For Non-Small Cell Lung Cancer Classification, Yahya Tashtoush, Rasha Obeidat, Abdallah Al-Shorman, Omar Darwish, Mohammad A. Al-Ramahi, Dirar Darweesh
Computer Information Systems Faculty Publications
Lung cancer is a common type of cancer that causes death if not detected
early enough. Doctors use computed tomography (CT) images to diagnose
lung cancer. The accuracy of the diagnosis relies highly on the doctor's
expertise. Recently, clinical decision support systems based on deep learning
valuable recommendations to doctors in their diagnoses. In this paper, we
present several deep learning models to detect non-small cell lung cancer in
CT images and differentiate its main subtypes namely adenocarcinoma,
large cell carcinoma, and squamous cell carcinoma. We adopted standard
convolutional neural networks (CNN), visual geometry group-16 (VGG16),
and VGG19. Besides, we …
Towards Carbon Neutrality: Prediction Of Wave Energy Based On Improved Gru In Maritime Transportation,
2023
Qingdao Institute of Bioenergy and Bioprocess Technology
Towards Carbon Neutrality: Prediction Of Wave Energy Based On Improved Gru In Maritime Transportation, Zhihan Lv, Nana Wang, Ranran Lou, Yajun Tian, Mohsen Guizani
Machine Learning Faculty Publications
Efficient use of renewable energy is one of the critical measures to achieve carbon neutrality. Countries have introduced policies to put carbon neutrality on the agenda to achieve relatively zero emissions of greenhouse gases and to cope with the crisis brought about by global warming. This work analyzes the wave energy with high energy density and wide distribution based on understanding of various renewable energy sources. This study provides a wave energy prediction model for energy harvesting. At the same time, the Gated Recurrent Unit network (GRU), Bayesian optimization algorithm, and attention mechanism are introduced to improve the model's performance. …
Effects Of Supply Chain Transparency, Alignment, Adaptability, And Agility On Blockchain Adoption In Supply Chain Among Smes,
2023
Edith Cowan University
Effects Of Supply Chain Transparency, Alignment, Adaptability, And Agility On Blockchain Adoption In Supply Chain Among Smes, Mohammad Iranmanesh, Parisa Maroufkhani, Shahla Asadi, Morteza Ghobakhloo, Yogesh K. Dwivedi, Ming-Lang Tseng
Research outputs 2022 to 2026
This study aims to investigate the extent to which the contributions of blockchain technology to supply chain parameters influence blockchain adoption among SMEs. Drawing on contingency theory, the study investigates the moderating effect of market turbulence. The data were collected from 204 SMEs in Malaysia's manufacturing sector and analysed using the partial least squares technique. The results showed that the intention of SMEs’ managers to adopt blockchain is influenced by the contributions of blockchain to supply chain transparency and agility. Supply chain transparency, alignment, adaptability, and agility are interrelated. Market turbulence moderates positively the association between agility and intention to …
Learning Comprehensive Global Features In Person Re-Identification: Ensuring Discriminativeness Of More Local Regions,
2023
Singapore Management University
Learning Comprehensive Global Features In Person Re-Identification: Ensuring Discriminativeness Of More Local Regions, Jiali Xia, Jianqiang Huang, Shibao Zheng, Qin Zhou, Bernt Schiele, Xian-Sheng Hua, Qianru Sun
Research Collection School Of Computing and Information Systems
Person re-identification (Re-ID) aims to retrieve person images from a large gallery given a query image of a person of interest. Global information and fine-grained local features are both essential for the representation. However, global embedding learned by naive classification model tends to be trapped in the most discriminative local region, leading to poor evaluation performance. To address the issue, we propose a novel baseline network that learns strong global feature termed as Comprehensive Global Embedding (CGE), ensuring more local regions of global feature maps to be discriminative. In this work, two key modules are proposed including Non-parameterized Local Classifier …
Online Hyperparameter Optimization For Class-Incremental Learning,
2023
Singapore Management University
Online Hyperparameter Optimization For Class-Incremental Learning, Yaoyao Liu, Yingying Li, Bernt Schiele, Qianru Sun
Research Collection School Of Computing and Information Systems
Class-incremental learning (CIL) aims to train a classification model while the number of classes increases phase-by-phase. An inherent challenge of CIL is the stability-plasticity tradeoff, i.e., CIL models should keep stable to retain old knowledge and keep plastic to absorb new knowledge. However, none of the existing CIL models can achieve the optimal tradeoff in different data-receiving settings—where typically the training-from-half (TFH) setting needs more stability, but the training-from-scratch (TFS) needs more plasticity. To this end, we design an online learning method that can adaptively optimize the tradeoff without knowing the setting as a priori. Specifically, we first introduce the …
Safe Delivery Of Critical Services In Areas With Volatile Security Situation Via A Stackelberg Game Approach,
2023
Singapore Management University
Safe Delivery Of Critical Services In Areas With Volatile Security Situation Via A Stackelberg Game Approach, Tien Mai, Arunesh Sinha
Research Collection School Of Computing and Information Systems
Vaccine delivery in under-resourced locations with security risks is not just challenging but also life threatening. The COVID pandemic and the need to vaccinate added even more urgency to this issue. Motivated by this problem, we propose a general framework to set-up limited temporary (vaccination) centers that balance physical security and desired (vaccine) service coverage with limited resources. We set-up the problem as a Stackelberg game between the centers operator (defender) and an adversary, where the set of centers is not fixed a priori but is part of the decision output. This results in a mixed combinatorial and continuous optimization …
A Fair Incentive Scheme For Community Health Workers,
2023
Singapore Management University
A Fair Incentive Scheme For Community Health Workers, Avinandan Bose, Tracey Li, Arunesh Sinha, Tien Mai
Research Collection School Of Computing and Information Systems
Community health workers (CHWs) play a crucial role in the last mile delivery of essential health services to under-served populations in low-income countries. Many non-governmental organizations (NGOs) provide training and support to enable CHWs to deliver health services to their communities, with no charge to the recipients of the services. This includes monetary compensation for the work that CHWs perform, which is broken down into a series of well-defined tasks. In this work, we partner with a NGO D-Tree International to design a fair monetary compensation scheme for tasks performed by CHWs in the semi-autonomous region of Zanzibar in Tanzania, …
A Non-Reference Evaluation Of Underwater Image Enhancement Methods Using A New Underwater Image Dataset,
2023
Michigan Technological University
A Non-Reference Evaluation Of Underwater Image Enhancement Methods Using A New Underwater Image Dataset, Ashraf Saleem, Sidike Paheding, Nathir Rawashdeh, Ali Awad, Navjot Kaur
Michigan Tech Publications
The rise of vision-based environmental, marine, and oceanic exploration research highlights the need for supporting underwater image enhancement techniques to help mitigate water effects on images such as blurriness, low color contrast, and poor quality. This paper presents an evaluation of common underwater image enhancement techniques using a new underwater image dataset. The collected dataset is comprised of 100 images of aquatic plants taken at a shallow depth of up to three meters from three different locations in the Great Lake Superior, USA, via a Remotely Operated Vehicle (ROV) equipped with a high-definition RGB camera. In particular, we use our …
Codebase Relationship Visualizer: Visualizing Relationships Between Source Code Files,
2023
Southern Adventist University
Codebase Relationship Visualizer: Visualizing Relationships Between Source Code Files, Jesse Hines
MS in Computer Science Project Reports
Understanding relationships between files and their directory structure is a fundamental part of the software development process. However, it can be hard to grasp these relationships without a convenient way to visualize how files are connected and how they fit into the directory structure of the codebase. In this paper we describe CodeBase Relationship Visualizer (CBRV), a Visual Studio Code extension that interactively visualizes the relationships between files. CBRV displays the relationships between files as arrows superimposed over a diagram of the codebase's directory structure. CBRV comes bundled with visualizations of the stack trace path, a dependency graph for Python …
Combinatorics Syllabus,
2023
City University of New York (CUNY)
Combinatorics Syllabus, Tugce Ozdemir
Open Educational Resources
No abstract provided.
Completeness Of Nominal Props,
2023
Runtime Verication Inc.
Completeness Of Nominal Props, Samuel Balco, Alexander Kurz
Engineering Faculty Articles and Research
We introduce nominal string diagrams as string diagrams internal in the category of nominal sets. This leads us to define nominal PROPs and nominal monoidal theories. We show that the categories of ordinary PROPs and nominal PROPs are equivalent. This equivalence is then extended to symmetric monoidal theories and nominal monoidal theories, which allows us to transfer completeness results between ordinary and nominal calculi for string diagrams.
Artificial Intelligence, Basic Skills, And Quantitative Literacy,
2023
Pomona College
Artificial Intelligence, Basic Skills, And Quantitative Literacy, Gizem Karaali
Numeracy
The introduction in November 2022 of ChatGPT, a freely available language-based artificial intelligence, has led to concerns among some educators about the feasibility and benefits of teaching basic writing and critical thinking skills to students in the context of easily accessed, AI-based cheating mechanisms. As of now, ChatGPT can write pretty convincing student-level prose, but it is still not very good at answering quantitatively rich questions. Therefore, for the time being, the preceding concerns may not be shared by a large portion of the numeracy education community. However, as Google and WolframAlpha are definitely capable of answering standard and some …
Teaching By Practice: Shaping Secure Coding Mentalities Through Cybersecurity Ctfs,
2023
Arcadia University
Teaching By Practice: Shaping Secure Coding Mentalities Through Cybersecurity Ctfs, Jazmin Collins, Vitaly Ford
Journal of Cybersecurity Education, Research and Practice
The use of the Capture the Flag (CTF)-style competitions has grown popular in a variety of environments as a method to improve or reinforce cybersecurity techniques. However, while these competitions have shown promise in student engagement, enjoyment, and the teaching of essential workforce cybersecurity concepts, many of these CTF challenges have largely focused on cybersecurity as a general topic. Further, most in-school CTF challenges are designed with technical institutes in mind, prepping only experienced or upper-level students in cybersecurity studies for real-world challenges. Our paper aims to focus on the setting of a liberal arts institute, emphasizing secure coding as …
