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Full-Text Articles in Databases and Information Systems
Information Architecture For A Chemical Modeling Knowledge Graph, Adam R. Luxon
Information Architecture For A Chemical Modeling Knowledge Graph, Adam R. Luxon
Theses and Dissertations
Machine learning models for chemical property predictions are high dimension design challenges spanning multiple disciplines. Free and open-source software libraries have streamlined the model implementation process, but the design complexity remains. In order better navigate and understand the machine learning design space, model information needs to be organized and contextualized. In this work, instances of chemical property models and their associated parameters were stored in a Neo4j property graph database. Machine learning model instances were created with permutations of dataset, learning algorithm, molecular featurization, data scaling, data splitting, hyperparameters, and hyperparameter optimization techniques. The resulting graph contains over 83,000 nodes …
Evaluating Machine Learning Techniques For Smart Home Device Classification, Angelito E. Aragon Jr.
Evaluating Machine Learning Techniques For Smart Home Device Classification, Angelito E. Aragon Jr.
Theses and Dissertations
Smart devices in the Internet of Things (IoT) have transformed the management of personal and industrial spaces. Leveraging inexpensive computing, smart devices enable remote sensing and automated control over a diverse range of processes. Even as IoT devices provide numerous benefits, it is vital that their emerging security implications are studied. IoT device design typically focuses on cost efficiency and time to market, leading to limited built-in encryption, questionable supply chains, and poor data security. In a 2017 report, the United States Government Accountability Office recommended that the Department of Defense investigate the risks IoT devices pose to operations security, …
Exploring Data Mining Techniques For Tree Species Classification Using Co-Registered Lidar And Hyperspectral Data, Julia K. Marrs
Exploring Data Mining Techniques For Tree Species Classification Using Co-Registered Lidar And Hyperspectral Data, Julia K. Marrs
Theses and Dissertations
NASA Goddard’s LiDAR, Hyperspectral, and Thermal imager provides co-registered remote sensing data on experimental forests. Data mining methods were used to achieve a final tree species classification accuracy of 68% using a combined LiDAR and hyperspectral dataset, and show promise for addressing deforestation and carbon sequestration on a species-specific level.