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Full-Text Articles in Physical Sciences and Mathematics

Reliability Improvement On Feasibility Study For Selection Of Infrastructure Projects Using Data Mining And Machine Learning, Xi Hu Apr 2020

Reliability Improvement On Feasibility Study For Selection Of Infrastructure Projects Using Data Mining And Machine Learning, Xi Hu

Theses and Dissertations

With the progressive development of infrastructure construction, conventional analytical methods such as correlation index, quantifying factors, and peer review are no longer satisfactory in support for decision-making of implementing an infrastructure project in the age of big data. This study proposes using a mathematical model named Fuzzy-Neural Comprehensive Evaluation Model (FNCEM) to improve the reliability of the feasibility study of infrastructure projects by using data mining and machine learning. Specifically, the data collection on time-series data, including traffic videos (278 Gigabytes) and historical weather data, uses transportation cameras and online searching, respectively. Meanwhile, the researcher sent out a questionnaire for …


From Cellular To Holistic: Development Of Algorithms To Study Human Health And Diseases, Casey Anne Cole Apr 2020

From Cellular To Holistic: Development Of Algorithms To Study Human Health And Diseases, Casey Anne Cole

Theses and Dissertations

The development of theoretical computational methods and their application has become widespread in the world today. In this dissertation, I present my work in the creation of models to detect and describe complex biological and health related problems. The first major part of my work centers around the creation and enhancement of methods to calculate protein structure and dynamics. To this end, substantial enhancement has been made to the software package REDCRAFT to better facilitate its usage in protein structure calculation. The enhancements have led to an overall increase in its ability to characterize proteins under difficult conditions such as …


Explainable Neural Networks Based Anomaly Detection For Cyber-Physical Systems, Kasun Amarasinghe Jan 2019

Explainable Neural Networks Based Anomaly Detection For Cyber-Physical Systems, Kasun Amarasinghe

Theses and Dissertations

Cyber-Physical Systems (CPSs) are the core of modern critical infrastructure (e.g. power-grids) and securing them is of paramount importance. Anomaly detection in data is crucial for CPS security. While Artificial Neural Networks (ANNs) are strong candidates for the task, they are seldom deployed in safety-critical domains due to the perception that ANNs are black-boxes. Therefore, to leverage ANNs in CPSs, cracking open the black box through explanation is essential.

The main objective of this dissertation is developing explainable ANN-based Anomaly Detection Systems for Cyber-Physical Systems (CP-ADS). The main objective was broken down into three sub-objectives: 1) Identifying key-requirements that an …


Evaluation And Forecast Of Energy Consumption In Different Sectors Of The United States Using Artificial Neural Networks, Arash Kialashaki Dec 2014

Evaluation And Forecast Of Energy Consumption In Different Sectors Of The United States Using Artificial Neural Networks, Arash Kialashaki

Theses and Dissertations

The United States is a country which consumes a vast amount of energy. In order to keep the development of the United States sustainable (diverse and productive over the time) energy planning should be carried out comprehensively and precisely. This dissertation presents a specific mathematical modeling approach towards energy demand modeling of the United States and forecast future energy demand. To generate more detailed and accurate results, this dissertation investigates the energy demand of each sector separately using the analysis of trend for unique set of independent parameters which affect the energy demand in that sector.

In solving a forecast …


Communicating Affective Meaning From Software To Wetware Through The Medium Of Digital Art, R David Norton Aug 2014

Communicating Affective Meaning From Software To Wetware Through The Medium Of Digital Art, R David Norton

Theses and Dissertations

Computational creativity is a new and developing field of artificial intelligence concerned with computational systems that either autonomously produce original and functional products, or that augment the ability of humans to do so. As the role of computers in our daily lives is continuing to expand, the need for such systems is becoming increasingly important. We introduce and document the development of a new “creative” system, called DARCI (Digital ARtist Communicating Intention), that is designed to autonomously create novel artistic images that convey linguistic concepts to the viewer. Within the scope of this work, the system becomes capable of creating …