Computer Engineering Commons^™

Enhancing Information Architecture With Machine Learning For Digital Media Platforms, Taylor N. Mietzner

Honors College Theses

Modern advancements in machine learning are transforming the technological landscape, including information architecture within user experience design. With the unparalleled amount of user data generated on online media platforms and applications, an adjustment in the design process to incorporate machine learning for categorizing the influx of semantic data while maintaining a user-centric structure is essential. Machine learning tools, such as the classification and recommendation system, need to be incorporated into the design for user experience and marketing success. There is a current gap between incorporating the backend modeling algorithms and the frontend information architecture system design together. The aim of …

Comparative Analytics On Chilli Plant Disease Using Machine Learning Techniques, Sai Abhishta Roy Seelam

Electronic Theses and Dissertations

This thesis concerns the detection of diseases in chilli plants using machine learning techniques. Three algorithms, viz., Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), and Multi-Layer Perceptron (MLP), and their variants have been employed. Chilli-producing countries, India, Mexico, China, Indonesia, Spain, the United States, and Turkey. India has the world’s largest chilli production of about 49% (according to 2020). Andhra Pradesh (Guntur) is the largest market in India, where their varieties are more popular for pungency and color. This study classifies five kinds of diseases that affect the chilli, namely, leaf spot, whitefly, yellowish, healthy, and leaf curl. A …

Fault Diagnosability Of Regular Graphs, Mei-Mei Gu, Rong-Xia Hao, Eddie Cheng

Theory and Applications of Graphs

An interconnection network's diagnosability is an important measure of its self-diagnostic capability. In 2012, Peng et al. proposed a measure for fault diagnosis of the network, namely, the h-good-neighbor conditional diagnosability, which requires that every fault-free node has at least h fault-free neighbors. There are two well-known diagnostic models, PMC model and MM* model. The h-good-neighbor diagnosability under the PMC (resp. MM*) model of a graph G, denoted by t_h^PMC(G) (resp. t_h^MM*(G)), is the maximum value of t such that G is h-good-neighbor t-diagnosable under the PMC (resp. MM*) …

Policy-Preferred Paths In As-Level Internet Topology Graphs, Mehmet Engin Tozal

Theory and Applications of Graphs

Using Autonomous System (AS) level Internet topology maps to determine accurate AS-level paths is essential for network diagnostics, performance optimization, security enforcement, business policy management and topology-aware application development. One significant drawback that we have observed in many studies is simplifying the AS-level topology map of the Internet to an undirected graph, and then using the hop distance as a means to find the shortest paths between the ASes. A less significant drawback is restricting the shortest paths to only valley-free paths. Both approaches usually inflate the number of paths between ASes; introduce erroneous paths that do not conform to …

Mazetec: A Scenario-Based Learning Platform, Daniel Bietz

Electronic Theses and Dissertations

This work presents Mazetec, a scenario-based learning platform for delivering non-linear scenarios format asynchronously. It enables subject matter experts to create interactive, state-dependent case studies or courses with branching logic for online learning and knowledge testing. Mazetec is a complex web application designed to deliver decision-based or case-based educational scenarios and simulations in a time-limited, non-linear format. There are many e-learning systems in the open source and commercial markets, but while these systems may have similar functions, we have found none that are both domain independent and able to deliver state-dependent content asynchronous and non-linearly. Mazetec can serve as …

Wind Turbine Noise And Wind Speed Prediction, Tyler H. Blanchard

Electronic Theses and Dissertations

In order to meet the US Department of Energy projected target of 35% of US energy coming from wind by 2050, there is a strong need to study the management and development of wind turbine technology and its impact on human health, wildlife and environment. The prediction of wind turbine noise and its propagation is very critical to study the impacts of wind turbine noise for long term adoption and acceptance by neighboring communities. The prediction of wind speed is critical in the assessment of feasibility of a potential wind turbine site. This work presents a study on prediction of …

Comparing The Efficiency Of Heterogeneous And Homogeneous Data Center Workloads, Brandon Kimmons

Electronic Theses and Dissertations

Abstract

Information Technology, as an industry, is growing very quickly to keep pace with increased data storage and computing needs. Data growth, if not planned or managed correctly, can have larger efficiency implications on your data center as a whole. The long term reduction in efficiency will increase costs over time and increase operational overhead. Similarly, increases in processor efficiency have led to increased system density in data centers. This can increase cost and operational overhead in your data center infrastructure.

This paper proposes the idea that balanced data center workloads are more efficient in comparison to similar levels of …

Testing Data Vault-Based Data Warehouse, Connard N. Williams

Electronic Theses and Dissertations

Data warehouse (DW) projects are undertakings that require integration of disparate sources of data, a well-defined mapping of the source data to the reconciled data, and effective Extract, Transform, and Load (ETL) processes. Owing to the complexity of data warehouse projects, great emphasis must be placed on an agile-based approach with properly developed and executed test plans throughout the various stages of designing, developing, and implementing the data warehouse to mitigate against budget overruns, missed deadlines, low customer satisfaction, and outright project failures. Yet, there are often attempts to test the data warehouse exactly like traditional back-end databases and legacy …

A Federated Architecture For Heuristics Packet Filtering In Cloud Networks, Ibrahim M. Waziri Jr

Electronic Theses and Dissertations

The rapid expansion in networking has provided tremendous opportunities to access an unparalleled amount of information. Everyone connects to a network to gain access and to share this information. However when someone connects to a public network, his private network and information becomes vulnerable to hackers and all kinds of security threats. Today, all networks needs to be secured, and one of the best security policies is firewall implementation.

Firewalls can be hardware or cloud based. Hardware based firewalls offer the advantage of faster response time, whereas cloud based firewalls are more flexible. In reality the best form of firewall …

Accelerated Data Delivery Architecture, Michael L. Grecol

Electronic Theses and Dissertations

This paper introduces the Accelerated Data Delivery Architecture (ADDA). ADDA establishes a framework to distribute transactional data and control consistency to achieve fast access to data, distributed scalability and non-blocking concurrency control by using a clean declarative interface. It is designed to be used with web-based business applications. This framework uses a combination of traditional Relational Database Management System (RDBMS) combined with a distributed Not Only SQL (NoSQL) database and a browser-based database. It uses a single physical and conceptual database schema designed for a standard RDBMS driven application. The design allows the architect to assign consistency levels to entities …

Application Of Self-Monitoring For Situational Awareness, Christopher Trickler

Electronic Theses and Dissertations

Self-monitoring devices and services are used for physical wellness, personal tracking and self-improvement. These individual devices and services can only provide information based on what they can measure directly or historically without an intermediate system. This paper proposes a self-monitoring system to perform situational awareness which may extend into providing insight into predictable behaviors. Knowing an individual’s current state and likelihood of particular behaviors occurring is a general solution. This knowledge-based solution derived from sensory data has many applications. The proposed system could monitor current individual situational status, automatically provide personal status as it changes, aid personal improvement, contribute to …