Latest SFL Scientific has been named Partner of the Year for AI Services Delivery by NVIDIA Partner Network
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A collection of our team's thoughts on data science, machine learning, predictive models, AI, and optimization.
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Press Release 3 MIN

SFL Scientific Named Partner of the Year for AI Services Delivery by NVIDIA Partner Network

SFL Scientific has been selected by the NVIDIA Partner Network as the 2020 AI Services Delivery Partner of the Year for the Americas. This is the third year that SFL Scientific has been honored in this category.   Boston, MA—June 21, 2021—SFL Scientific announced today that it has been selected by the NVIDIA Partner Network […]

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Articles MIN

Leveraging Machine Learning For Nondestructive Testing

What is non-destructive testing? Nondestructive testing is used in many industries to evaluate the properties of components without altering or causing damage to the component being tested. This includes examining its integrity or condition to see if anything might indicate deviations from normal or optimal characteristics. It is a highly valuable tool to help prevent […]
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Case Study MIN

Disaggregation of Energy Usage Data

Business Challenge An energy provider approached SFL about disaggregating overall household energy consumption data into constituent appliance energy expenditures because the energy provider wished to expand its service offerings to customers.  Disaggregating energy data simply means converting raw energy usage data into a list outlining when each individual appliance (i.e. a toaster, refrigerator, heater, etc) […]
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Case Study MIN

Vibration Analysis

Background Vibration analysis is often used to detect potential faults in rotating machinery and structures (e.g., bridges, turbine blades) by evaluating velocity or acceleration data measured from inherent vibrations in the machine or structure of interest. In one nondestructive testing engagement, SFL Scientific utilized 100,000 vibration-testing samples of velocity data that were synthetically generated to […]
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Case Study 2 MIN

Customer Market Segmentation

Segmenting key customer markets to better understand its customers to guide decision making and ultimately drive sales.
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Case Study MIN

Identifying Sleep Apnea with Mobile Devices

Business Challenge Many new companies start out with a clever idea on how to gather and use data but lack the knowledge base to analyze it themselves. The ability of these companies to succeed at their stated goals depends on how well they use their data. Effective algorithms for handling this data allow companies to provide […]
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Case Study 2 MIN

Predicting Sales & Inventory On New Products

Predicting sales and sell-out events for mens’ and womens’ new products 12-months in advance using historical sales data and product metadata.
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Case Study 2 MIN

Preventive Maintenance Optimization

Analyzing both device component service calls and records and examine device utilization logs events to model optimal maintenance schedule thresholds relative to acceptable downtime, costs, and scheduling.
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Case Study 2 MIN

Cancer Diagnosis from Blood Samples

Designing an AI capable model to analyze data from Matrix-assisted laser desorption/ionization (MALDI) and custom LC-MS/MS systems to determine whether patient samples tested positive for certain types of lung cancer.
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Case Study MIN

Algorithm Development for Compression Predictions

Business Challenge The process of tire manufacturing is the product of years of continuous research and advanced feats of engineering. The tire must achieve a balance between safety, comfort, traction, durability, and efficiency. There are hundreds of components that contribute to the tire’s performance and fuel efficiency. Steel and synthetic cords make up its structural […]
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Case Study MIN

Pay Equality Modeling

Business Challenge Wage gaps between gender and ethnic groups receive a lot of media coverage and are a major issue in our society. Identifying and addressing them effectively and accurately shields companies from lawsuits and bad publicity, whilst promoting equality and fairness. For large organizations, it can be difficult to identify these gaps as they […]
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