Browsing by Subject "machine learning"
Now showing items 21-40 of 54
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An Experimental, Modeling and Machine Learning Based Investigation of Stick-Slip Vibrations
(2022-08-04)Drilling technologies have improved considerably since the first well drilled by Colonel E.L Drake in 1859. Drilling technologies enable us to safely drill complex well profiles with advanced downhole tools and sensors to ... -
Exploring Drug-Use Progression Through Stability Enhanced Clustering
(2022-05)Background and aims: Drug use initiation sequences have been the subject of much research, and theories such as the Gateway Hypothesis have been created to explain patterns of progression from common to dangerous drugs. ... -
Floating-point comparator with relu operator for machine learning enhancement
(2021-05)This article provides various comparator designs that provide comparisons to double, single, half, and bfloat floating-point values as well as provide comparison modes for 32 and 64 bit two's compliment integer encoded ... -
General supervised learning framework for open world classification
(2020-12-18)In machine learning, the most common scenario for classification modeling is when the training set contains all possible classes and the algorithm learns to identify these classes. The problem setting in which the training ... -
Hydrologic peak flow modelling using machine learning
(2020-12-18)The effect of rainfall spatial variability on catchment responses during floods remains poorly understood. The overall objective of this work is to develop a robust understanding of how rainfall spatial variability influences ... -
Intelligent Condition Monitoring and Prognostic Methods with Applications to Dynamic Seals in the Oil & Gas Industry
(2019)The capital-intensive oil & gas industry invests billions of dollars in equipment annually and it is important to keep the equipment in top operating condition to help maintain efficient process operations and improve the ... -
Interpreting natural language processing (NLP) models and lifting their limitations
(2021-07)There have been many advances in the artificial intelligence field due to the emergence of deep learning and big data. In almost all sub-fields, artificial neural networks have reached or exceeded human-level performance. ... -
Kidney OCT 3D images classification using machine learning
(2023-12-15)The goal of this research is to make a classification program for 3D images by using a CNN model. The images to classify are kidney images that have 3 different classes: Pelvis, Medulla and Cortex. To do so, a data ... -
LacSubPred: Predicting subtypes of Laccases, an important lignin metabolism-related enzyme class, using in silico approaches
(BioMed Central, 2014-10-21)Background: Laccases (E.C. 1.10.3.2) are multi-copper oxidases that have gained importance in many industries such as biofuels, pulp production, textile dye bleaching, bioremediation, and food production. Their usefulness ... -
Leveraging atomistic simulations and machine learning for the design of ionic liquids as electrolytes for battery application
(2022-05)Ionic liquids are classes of salts that are often found in a liquid state composed entirely of ions. They have gained widespread interest in the research community because of several unique and desirable features, such as ... -
Machine learning and personality traits: A disturbing contribution from the algorithmic culture to behavioral science
(2018-12)The time has come for behavioral scholars to benefit from the superior prediction accuracy of modern data mining practices over traditional data modeling. The current investigative study uses machine learning techniques ... -
Machine Learning Co-Production in Operational Meteorology
(2022-08)Machine learning, deep learning, and other artificial intelligence (AI) methods are becoming popular tools within the meteorological research community. However, despite the breadth of promising AI research and its ... -
Machine learning enabled query re-optimization algorithms for cloud database systems
(2021-12)In cloud database systems, hardware configurations, data usage, and workload allocations are continuously changing. These changes make it difficult for the query optimizer to obtain an optimal query execution plan (QEP) ... -
Machine Learning Predictions of Flash Floods
(2016-08-12)This dissertation contains a literature review and three studies concerned with the development, assessment, and use of machine learning (ML) algorithms to explore automatically generated predictions of flash floods. The ... -
Mechanical characterization of heterogeneous hyperelastic membrane using inverse methods
(2021-12)Many soft biological tissues are heterogeneous, having different properties at different locations. Characterizing these tissues is very important for virtually testing potential medical technologies or protocols. Some ... -
Model-data fusion in digital twins of large scale dynamical systems
(2022-07)Digital twins (DTs) are virtual entities that serve as the real-time digital counterparts of actual physical systems across their life-cycle. In a typical application of DTs, the physical system provides sensor measurements ... -
Modeling Relationships Between Brain/Muscle Activity and Locomotive Behavior
(2022-12)The dynamics of locomotion involve a fine-tuned, continuous feedback loop between processes in the brain, functioning of the muscles, and interactions with the environment. Neurological or motor disability can often disrupt ... -
Modern process planning for additive manufacturing assisted a 356 aluminum casting
(2023-05)Foundry engineering integrates mechanical design, thermal-fluid dynamics, and material science to cast components of a unique design. This project was intended to apply these concepts to optimize the casting process of an ... -
New stochastic pore-scale simulation and machine learning approach to predicting permeability and tortuosity of heterogeneous porous media
(2023-05)A new 3D stochastic pore-scale simulation approach was introduced in this study to investigate how stochastic pore connectivity impacts the permeability and hydraulic tortuosity of heterogeneous porous media. Multiple ... -
Nurturing as Safe Exploration Promotes the Evolution of Generalized Supervised Learning
(2017-08-01)The ability to learn is often a desirable property of intelligent systems which can make them more adaptive. However, it is difficult to develop sophisticated learning algorithms that are effective. One approach to the ...