Open Access. Powered by Scholars. Published by Universities.®
- Institution
-
- Walden University (17)
- University of Arkansas, Fayetteville (16)
- Air Force Institute of Technology (9)
- Singapore Management University (7)
- California Polytechnic State University, San Luis Obispo (6)
-
- Chulalongkorn University (6)
- Georgia Southern University (4)
- New Jersey Institute of Technology (4)
- Old Dominion University (4)
- Purdue University (4)
- California State University, San Bernardino (3)
- Nova Southeastern University (3)
- Western University (3)
- City University of New York (CUNY) (2)
- Munster Technological University (2)
- University of Louisville (2)
- University of Massachusetts Amherst (2)
- University of New Haven (2)
- University of New Orleans (2)
- Virginia Commonwealth University (2)
- Clemson University (1)
- Colby College (1)
- Embry-Riddle Aeronautical University (1)
- Grand Valley State University (1)
- La Salle University (1)
- Louisiana State University (1)
- Marquette University (1)
- Stephen F. Austin State University (1)
- The University of Akron (1)
- The University of Southern Mississippi (1)
- Keyword
-
- Cybersecurity (8)
- Machine learning (6)
- Applied sciences (5)
- Computer Science (4)
- Machine Learning (4)
-
- Artificial Intelligence (3)
- Blockchain (3)
- Cloud Computing (3)
- Databases (3)
- Deep Learning (3)
- Neural networks (3)
- Security (3)
- #antcenter (2)
- Algorithmic fairness (2)
- Android (2)
- Computer Vision (2)
- Critical Infrastructure (2)
- Database security (2)
- DevSecOps (2)
- Embedded Systems (2)
- General Application of AI (2)
- Information Technology (2)
- Internet of Things (2)
- IoT (2)
- Java (2)
- Long short-term memory (2)
- Manufacturing (2)
- Mobile (2)
- NoSQL (2)
- Python (2)
- Publication Year
- Publication
-
- Walden Dissertations and Doctoral Studies (17)
- Graduate Theses and Dissertations (13)
- Theses and Dissertations (12)
- Dissertations and Theses Collection (Open Access) (7)
- Electronic Theses and Dissertations (7)
-
- Chulalongkorn University Theses and Dissertations (Chula ETD) (6)
- Dissertations (5)
- Computer Engineering (4)
- Engineering Management & Systems Engineering Theses & Dissertations (4)
- CCE Theses and Dissertations (3)
- Electronic Theses, Projects, and Dissertations (3)
- Electronic Thesis and Dissertation Repository (3)
- Honors Theses (3)
- Master's Theses (3)
- Open Access Theses (3)
- Computer Science and Computer Engineering Undergraduate Honors Theses (2)
- Theses (2)
- University of New Orleans Theses and Dissertations (2)
- All Dissertations (1)
- Capstones (1)
- Chancellor’s Honors Program Projects (1)
- Computer Science and Engineering Theses (1)
- Computer Science and Software Engineering (1)
- Culminating Experience Projects (1)
- Dissertations (1934 -) (1)
- Dissertations and Theses (1)
- Doctoral Dissertations (1)
- Doctoral Dissertations and Master's Theses (1)
- Graduate Student Theses, Dissertations, & Professional Papers (1)
- HON499 projects (1)
Articles 1 - 30 of 123
Full-Text Articles in Engineering
Development Of A Collaborative Research Platform For Efficient Data Management And Visualization Of Qubit Control, Devanshu Brahmbhatt
Development Of A Collaborative Research Platform For Efficient Data Management And Visualization Of Qubit Control, Devanshu Brahmbhatt
Computer Science and Engineering Theses
This thesis introduces QubiCSV, a pioneering open-source platform for quantum computing field. With an emphasis on collaborative research, QubiCSV addresses the critical need for specialized data management and visualization tools in qubit control. The platform is crafted to overcome the challenges posed by the high costs and complexities associated with quantum experimental setups. It emphasizes efficient utilization of resources through shared ideas, data, and implementation strategies. One of the primary obstacles in quantum computing research has been the ineffective management of extensive calibration data and the inability to visualize complex quantum experiment outcomes effectively. QubiCSV fills this gap by offering …
Railroad Condition Monitoring Using Distributed Acoustic Sensing And Deep Learning Techniques, Md Arifur Rahman
Railroad Condition Monitoring Using Distributed Acoustic Sensing And Deep Learning Techniques, Md Arifur Rahman
Electronic Theses and Dissertations
Proper condition monitoring has been a major issue among railroad administrations since it might cause catastrophic dilemmas that lead to fatalities or damage to the infrastructure. Although various aspects of train safety have been conducted by scholars, in-motion monitoring detection of defect occurrence, cause, and severity is still a big concern. Hence extensive studies are still required to enhance the accuracy of inspection methods for railroad condition monitoring (CM). Distributed acoustic sensing (DAS) has been recognized as a promising method because of its sensing capabilities over long distances and for massive structures. As DAS produces large datasets, algorithms for precise …
Ensuring Non-Repudiation In Long-Distance Constrained Devices, Ethan Blum
Ensuring Non-Repudiation In Long-Distance Constrained Devices, Ethan Blum
Honors Theses
Satellite communication is essential for the exploration and study of space. Satellites allow communications with many devices and systems residing in space and on the surface of celestial bodies from ground stations on Earth. However, with the rise of Ground Station as a Service (GsaaS), the ability to efficiently send action commands to distant satellites must ensure non-repudiation such that an attacker is unable to send malicious commands to distant satellites. Distant satellites are also constrained devices and rely on limited power, meaning security on these devices is minimal. Therefore, this study attempted to propose a novel algorithm to allow …
Damage Detection With An Integrated Smart Composite Using A Magnetostriction-Based Nondestructive Evaluation Method: Integrating Machine Learning For Prediction, Christopher Nelon
Damage Detection With An Integrated Smart Composite Using A Magnetostriction-Based Nondestructive Evaluation Method: Integrating Machine Learning For Prediction, Christopher Nelon
All Dissertations
The development of composite materials for structural components necessitates methods for evaluating and characterizing their damage states after encountering loading conditions. Laminates fabricated from carbon fiber reinforced polymers (CFRPs) are lightweight alternatives to metallic plates; thus, their usage has increased in performance industries such as aerospace and automotive. Additive manufacturing (AM) has experienced a similar growth as composite material inclusion because of its advantages over traditional manufacturing methods. Fabrication with composite laminates and additive manufacturing, specifically fused filament fabrication (fused deposition modeling), requires material to be placed layer-by-layer. If adjacent plies/layers lose adhesion during fabrication or operational usage, the strength …
Data-Driven 2d Materials Discovery For Next-Generation Electronics, Zeyu Zhang
Data-Driven 2d Materials Discovery For Next-Generation Electronics, Zeyu Zhang
Dissertations
The development of material discovery and design has lasted centuries in human history. After the concept of modern chemistry and material science was established, the strategy of material discovery relies on the experiments. Such a strategy becomes expensive and time-consuming with the increasing number of materials nowadays. Therefore, a novel strategy that is faster and more comprehensive is urgently needed. In this dissertation, an experiment-guided material discovery strategy is developed and explained using metal-organic frameworks (MOFs) as instances. The advent of 7r-stacked layered MOFs, which offer electrical conductivity on top of permanent porosity and high surface area, opened up new …
Blockchain Security: Double-Spending Attack And Prevention, William Henry Scott Iii
Blockchain Security: Double-Spending Attack And Prevention, William Henry Scott Iii
Electronic Theses and Dissertations
This thesis shows that distributed consensus systems based on proof of work are vulnerable to hashrate-based double-spending attacks due to abuse of majority rule. Through building a private fork of Litecoin and executing a double-spending attack this thesis examines the mechanics and principles behind the attack. This thesis also conducts a survey of preventative measures used to deter double-spending attacks, concluding that a decentralized peer-to-peer network using proof of work is best protected by the addition of an observer system whether internal or external.
Rattus Norvegicus As A Biological Detector Of Clandestine Remains And The Use Of Ultrasonic Vocalizations As A Locating Mechanism, Gabrielle M. Johnston
Rattus Norvegicus As A Biological Detector Of Clandestine Remains And The Use Of Ultrasonic Vocalizations As A Locating Mechanism, Gabrielle M. Johnston
Master's Theses
In investigations, locating missing persons and clandestine remains are imperative. One way that first responder and police agencies can search for the remains is by using cadaver dogs as biological detectors. Cadaver dogs are typically used due to their olfactory sensitivity and ability to detect low concentrations of volatile organic compounds produced by biological remains. Cadaver dogs are typically chosen for their stamina, agility, and olfactory sensitivity. However, what is not taken into account often is the size of the animal and the expense of maintaining and training the animal. Cadaver dogs are typically large breeds that cannot fit in …
Trace Dna Detection Using Diamond Dye: A Recovery Technique To Yield More Dna, Leah Davis
Trace Dna Detection Using Diamond Dye: A Recovery Technique To Yield More Dna, Leah Davis
Master's Theses
This study aspires to find a new screening approach to trace DNA recovery techniques to yield a higher quantity of trace DNA from larger items of evidence. It takes the path of visualizing trace DNA on items of evidence with potential DNA so analysts can swab a more localized area rather than attempting to recover trace DNA through the general swabbing technique currently used for trace DNA recovery. The first and second parts consisted of observing trace DNA interaction with Diamond Dye on porous and non-porous surfaces.
The third part involved applying the Diamond Dye solution by spraying it onto …
Connecting The Dots For Contextual Information Retrieval, Pei-Chi Lo
Connecting The Dots For Contextual Information Retrieval, Pei-Chi Lo
Dissertations and Theses Collection (Open Access)
There are many information retrieval tasks that depend on knowledge graphs to return contextually relevant result of the query. We call them Knowledgeenriched Contextual Information Retrieval (KCIR) tasks and these tasks come in many different forms including query-based document retrieval, query answering and others. These KCIR tasks often require the input query to contextualized by additional facts from a knowledge graph, and using the context representation to perform document or knowledge graph retrieval and prediction. In this dissertation, we present a meta-framework that identifies Contextual Representation Learning (CRL) and Contextual Information Retrieval (CIR) to be the two key components in …
Strategies To Increase Competitive Advantage In The Automotive Manufacturing Supply Chain, Amber Willis
Strategies To Increase Competitive Advantage In The Automotive Manufacturing Supply Chain, Amber Willis
Walden Dissertations and Doctoral Studies
Some automotive manufacturing supply chain leaders lack strategies that are needed to implement information technology (IT) systems. Business leaders are concerned with implementing IT systems to achieve and maintain a competitive advantage. Grounded in the resource-based view theory (RBV), the purpose of this qualitative single case study was to explore information system strategies used by leaders in the automotive manufacturing supply chain to achieve competitive advantage. Participants were five leaders of an automotive manufacturing supply chain organization who implemented IT systems. Data were collected through semistructured interviews and a review of organization project documents. Through thematic analysis, five themes were …
Ai Usage In Development, Security, And Operations, Maurice Ayidiya
Ai Usage In Development, Security, And Operations, Maurice Ayidiya
Walden Dissertations and Doctoral Studies
Artificial intelligence (AI) has become a growing field in information technology (IT). Cybersecurity managers are concerned that the lack of strategies to incorporate AI technologies in developing secure software for IT operations may inhibit the effectiveness of security risk mitigation. Grounded in the technology acceptance model, the purpose of this qualitative exploratory multiple case study was to explore strategies cybersecurity professionals use to incorporate AI technologies in developing secure software for IT operations. The participants were 10 IT professionals in the United States with at least 5 years of professional experience working in DevSecOps and managing teams of at least …
Ai Usage In Development, Security, And Operations, Maurice Ayidiya
Ai Usage In Development, Security, And Operations, Maurice Ayidiya
Walden Dissertations and Doctoral Studies
Artificial intelligence (AI) has become a growing field in information technology (IT). Cybersecurity managers are concerned that the lack of strategies to incorporate AI technologies in developing secure software for IT operations may inhibit the effectiveness of security risk mitigation. Grounded in the technology acceptance model, the purpose of this qualitative exploratory multiple case study was to explore strategies cybersecurity professionals use to incorporate AI technologies in developing secure software for IT operations. The participants were 10 IT professionals in the United States with at least 5 years of professional experience working in DevSecOps and managing teams of at least …
Hybrid Life Cycles In Software Development, Eric Vincent Schoenborn
Hybrid Life Cycles In Software Development, Eric Vincent Schoenborn
Culminating Experience Projects
This project applied software specification gathering, architecture, work planning, and development to a real-world development effort for a local business. This project began with a feasibility meeting with the owner of Zeal Aerial Fitness. After feasibility was assessed the intended users, needed functionality, and expected user restrictions were identified with the stakeholders. A hybrid software lifecycle was selected to allow a focus on base functionality up front followed by an iterative development of expectations of the stakeholders. I was able to create various specification diagrams that express the end projects goals to both developers and non-tech individuals using a standard …
Finding Top-M Leading Records In Temporal Data, Yiyi Wang
Finding Top-M Leading Records In Temporal Data, Yiyi Wang
Dissertations and Theses Collection (Open Access)
A traditional top-k query retrieves the records that stand out at a certain point in time. On the other hand, a durable top-k query considers how long the records retain their supremacy, i.e., it reports those records that are consistently among the top-k in a given time interval. In this thesis, we introduce a new query to the family of durable top-k formulations. It finds the top-m leading records, i.e., those that rank among the top-k for the longest duration within the query interval. Practically, this query assesses the records based on how long …
Supervised Representation Learning For Improving Prediction Performance In Medical Decision Support Applications, Phawis Thammasorn
Supervised Representation Learning For Improving Prediction Performance In Medical Decision Support Applications, Phawis Thammasorn
Graduate Theses and Dissertations
Machine learning approaches for prediction play an integral role in modern-day decision supports system. An integral part of the process is extracting interest variables or features to describe the input data. Then, the variables are utilized for training machine-learning algorithms to map from the variables to the target output. After the training, the model is validated with either validation or testing data before making predictions with a new dataset. Despite the straightforward workflow, the process relies heavily on good feature representation of data. Engineering suitable representation eases the subsequent actions and copes with many practical issues that potentially prevent the …
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 …
Optimized Damage Assessment And Recovery Through Data Categorization In Critical Infrastructure System., Shruthi Ramakrishnan
Optimized Damage Assessment And Recovery Through Data Categorization In Critical Infrastructure System., Shruthi Ramakrishnan
Graduate Theses and Dissertations
Critical infrastructures (CI) play a vital role in majority of the fields and sectors worldwide. It contributes a lot towards the economy of nations and towards the wellbeing of the society. They are highly coupled, interconnected and their interdependencies make them more complex systems. Thus, when a damage occurs in a CI system, its complex interdependencies make it get subjected to cascading effects which propagates faster from one infrastructure to another resulting in wide service degradations which in turn causes economic and societal effects. The propagation of cascading effects of disruptive events could be handled efficiently if the assessment and …
Implementing The Cms+ Sports Rankings Algorithm In A Javafx Environment, Luke Welch
Implementing The Cms+ Sports Rankings Algorithm In A Javafx Environment, Luke Welch
Industrial Engineering Undergraduate Honors Theses
Every year, sports teams and athletes get cut from championship opportunities because of their rank. While this reality is easier to swallow if a team or athlete is distant from the cut, it is much harder when they are right on the edge. Many times, it leaves fans and athletes wondering, “Why wasn’t I ranked higher? What factors when into the ranking? Are the rankings based on opinion alone?” These are fair questions that deserve an answer. Many times, sports rankings are derived from opinion polls. Other times, they are derived from a combination of opinion polls and measured performance. …
Bayesian Convolutional Neural Network With Prediction Smoothing And Adversarial Class Thresholds, Noah M. Miller
Bayesian Convolutional Neural Network With Prediction Smoothing And Adversarial Class Thresholds, Noah M. Miller
Theses and Dissertations
Using convolutional neural networks (CNNs) for image classification for each frame in a video is a very common technique. Unfortunately, CNNs are very brittle and have a tendency to be over confident in their predictions. This can lead to what we will refer to as “flickering,” which is when the predictions between frames jump back and forth between classes. In this paper, new methods are proposed to combat these shortcomings. This paper utilizes a Bayesian CNN which allows for a distribution of outputs on each data point instead of just a point estimate. These distributions are then smoothed over multiple …
Factors Influencing The Effectiveness Of Managing Human–Robot Teams, Theodore B. Terry
Factors Influencing The Effectiveness Of Managing Human–Robot Teams, Theodore B. Terry
Walden Dissertations and Doctoral Studies
Certain factors can influence the capabilities of a robot–human team by affecting their social and behavioral dynamics in a work environment. But these factors were not known due to the progressive nature of human–robot partnerships and a lack of peer-reviewed literature on the topic. This e-Delphi study aimed to identify and understand these unknown influential factors based on the participants’ insights. The overarching research question asked about the need to determine factors that might influence the effectiveness of managing human-robot teams. The basis for the conceptual framework for this study was the theory of communication used in organizational management. Twelve …
Use Of Human–Computer Interaction Devices And Web 3.0 Skills Among Engineers, Dr. Robbie L. Walker
Use Of Human–Computer Interaction Devices And Web 3.0 Skills Among Engineers, Dr. Robbie L. Walker
Walden Dissertations and Doctoral Studies
Despite massive company investments in human–computer interaction devices and software, such as Web 3.0 technologies, engineers are not demonstrating measurable performance and productivity increases. There is a lack of knowledge and understanding related to the motivation of engineers to use Web 3.0 technologies including the semantic web and cloud applications for increased performance. The purpose of this quantitative correlational study was to investigate whether the use of human–computer interaction devices predict Web 3.0 skills among engineers. Solow’s information technology productivity paradox was the theoretical foundation for this study. Convenience sampling was used for a sample of 214 participants from metropolitan …
Integration Of Blockchain Technology Into Automobiles To Prevent And Study The Causes Of Accidents, John Kim
Integration Of Blockchain Technology Into Automobiles To Prevent And Study The Causes Of Accidents, John Kim
Electronic Theses, Projects, and Dissertations
Automobile collisions occur daily. We now live in an information-driven world, one where technology is quickly evolving. Blockchain technology can change the automotive industry, the safety of the motoring public and its surrounding environment by incorporating this vast array of information. It can place safety and efficiency at the forefront to pedestrians, public establishments, and provide public agencies with pertinent information securely and efficiently. Other industries where Blockchain technology has been effective in are as follows: supply chain management, logistics, and banking. This paper reviews some statistical information regarding automobile collisions, Blockchain technology, Smart Contracts, Smart Cities; assesses the feasibility …
Integration Of Internet Of Things And Health Recommender Systems, Moonkyung Yang
Integration Of Internet Of Things And Health Recommender Systems, Moonkyung Yang
Electronic Theses, Projects, and Dissertations
The Internet of Things (IoT) has become a part of our lives and has provided many enhancements to day-to-day living. In this project, IoT in healthcare is reviewed. IoT-based healthcare is utilized in remote health monitoring, observing chronic diseases, individual fitness programs, helping the elderly, and many other healthcare fields. There are three main architectures of smart IoT healthcare: Three-Layer Architecture, Service-Oriented Based Architecture (SoA), and The Middleware-Based IoT Architecture. Depending on the required services, different IoT architecture are being used. In addition, IoT healthcare services, IoT healthcare service enablers, IoT healthcare applications, and IoT healthcare services focusing on Smartwatch …
Enabling Declarative And Scalable Prescriptive Analytics In Relational Data, Matteo Brucato
Enabling Declarative And Scalable Prescriptive Analytics In Relational Data, Matteo Brucato
Doctoral Dissertations
Constrained optimization problems are at the heart of significant applications in a broad range of domains, including finance, transportation, manufacturing, and healthcare. They are often found at the final step of business analytics, namely prescriptive analytics, to allow businesses to transform a rich understanding of data, typically provided by advanced predictive models, into actionable decisions. Modeling and solving these problems has relied on application-specific solutions, which are often complex, error-prone, and do not generalize. Our goal is to create a domain-independent, declarative approach, supported and powered by the system where the data relevant to these problems typically resides: the database. …
Data-Driven Based Automatic Routing Planning For Mass, Qingwu Wang
Data-Driven Based Automatic Routing Planning For Mass, Qingwu Wang
Maritime Safety & Environment Management Dissertations (Dalian)
No abstract provided.
Multilateration Index., Chip Lynch
Multilateration Index., Chip Lynch
Electronic Theses and Dissertations
We present an alternative method for pre-processing and storing point data, particularly for Geospatial points, by storing multilateration distances to fixed points rather than coordinates such as Latitude and Longitude. We explore the use of this data to improve query performance for some distance related queries such as nearest neighbor and query-within-radius (i.e. “find all points in a set P within distance d of query point q”). Further, we discuss the problem of “Network Adequacy” common to medical and communications businesses, to analyze questions such as “are at least 90% of patients living within 50 miles of a covered emergency …
Signal Processing And Data Analysis For Real-Time Intermodal Freight Classification Through A Multimodal Sensor System., Enrique J. Sanchez Headley
Signal Processing And Data Analysis For Real-Time Intermodal Freight Classification Through A Multimodal Sensor System., Enrique J. Sanchez Headley
Graduate Theses and Dissertations
Identifying freight patterns in transit is a common need among commercial and municipal entities. For example, the allocation of resources among Departments of Transportation is often predicated on an understanding of freight patterns along major highways. There exist multiple sensor systems to detect and count vehicles at areas of interest. Many of these sensors are limited in their ability to detect more specific features of vehicles in traffic or are unable to perform well in adverse weather conditions. Despite this limitation, to date there is little comparative analysis among Laser Imaging and Detection and Ranging (LIDAR) sensors for freight detection …
Promoting Diversity In Academic Research Communities Through Multivariate Expert Recommendation, Omar Salman
Promoting Diversity In Academic Research Communities Through Multivariate Expert Recommendation, Omar Salman
Graduate Theses and Dissertations
Expert recommendation is the process of identifying individuals who have the appropriate knowledge and skills to achieve a specific task. It has been widely used in the educational environment mainly in the hiring process, paper-reviewer assignment, and assembling conference program committees. In this research, we highlight the problem of diversity and fair representation of underrepresented groups in expertise recommendation, factors that current expertise recommendation systems rarely consider. We introduce a novel way to model experts in academia by considering demographic attributes in addition to skills. We use the h-index score to quantify skills for a researcher and we identify five …
Privacy-Preserving Cloud-Assisted Data Analytics, Wei Bao
Privacy-Preserving Cloud-Assisted Data Analytics, Wei Bao
Graduate Theses and Dissertations
Nowadays industries are collecting a massive and exponentially growing amount of data that can be utilized to extract useful insights for improving various aspects of our life. Data analytics (e.g., via the use of machine learning) has been extensively applied to make important decisions in various real world applications. However, it is challenging for resource-limited clients to analyze their data in an efficient way when its scale is large. Additionally, the data resources are increasingly distributed among different owners. Nonetheless, users' data may contain private information that needs to be protected.
Cloud computing has become more and more popular in …
A Machine Learning Approach To Understanding Emerging Markets, Namita Balani
A Machine Learning Approach To Understanding Emerging Markets, Namita Balani
Graduate Theses and Dissertations
Logistic providers have learned to efficiently serve their existing customer bases with optimized routes and transportation resource allocation. The problem arises when there is potential for logistics growth in an emerging market with no previous data. The purpose of this work is to use industry data for previously known and well-documented markets to apply data analytic techniques such as machine learning to investigate the uncertainty in a new market. The thesis looks into machine learning techniques to predict miles per stop given historical data. It mainly focuses on Random Forest Regression Analysis, but concludes that additional techniques, such as Polynomial …