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Anomaly Detection in Time Series Brain Data Collected Using Functional Near-Infrared Spectroscopy
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Exploring Machine Learning Methods for Nuclear Export Sequence Identification
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Towards a More Inclusive World: Enhanced Augmentative and Alternative Communication For People With Disabilities UsingAI and NLP
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Developing Models to Visualize and Analyze User Interaction for Financial Technology Websites
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Applying HCI Design Practices to the Development of the BrainEx User-Interface to Facilitate fNIRS Research
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Developing Models to Visualize & Analyze User Interaction for Financial Technology Websites
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Applying HCI Design Practices to the Design of the BrainEx User-Interface to facilitate fNIRS Research
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NirsAutoML: Building an automated classification platform for fNIRS data
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Brain Wave Analysis
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BrainEx: Visual Exploration and Discovery in Time Series Data
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Creating an App for Audio Journal's Print Disabled Listeners
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App for Audio Journal
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Development and Assessment of a Mindfulness-Based Stress Reduction Mobile Application
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Advancement of 3D Printed Aluminum Alloys for the Aerospace Industry Using Machine Learning
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Audio Journal App Continuation
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Cleaning On Demand with a Recommender System (CODeRS)
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Nanomechanical Method Development for UNiT: Universal Nanoindentation Toolkit
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Automatizing Inspection and Defect Detection for Metal Additive Manufacturing Using Deep Learning Techniques
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UNiT: a universal toolkit for nanoindentation exploration
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NAML : An Easy-to-Deploy Application for Time Series Analysis
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Automatizing Inspection and Defect Detection for Metal Additive Manufacturing Using Deep Learning Techniques
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Goatconnect
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Developing a 3D Food Printer
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Audio Journal Android Application
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Audio Journal – Empowering Visually Impaired People to Access Exhibits at the Worcester Museum of Art
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Coarse-Grain Lattice Technique for Studying Protein-Ligand Binding
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Additive Manufacturing Design: Developing a 3D Food Printer
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Audio Journal – empowering visually impaired people to access exhibits at the Worcester Museum of Art
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Distribution-Driven Augmentation of Real-World Datasets for Improved Cancer Diagnostics With Machine Learning
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