Difference between revisions of "Applied research"
(→Data Science Research Projects) |
|||
| Line 16: | Line 16: | ||
'''Text processing (Natural Language processing).''' | '''Text processing (Natural Language processing).''' | ||
Effective processing of huge volumes of voice or text messages information by making use of Natural Language Processing and Sentiment Analysis, which utilize all the powers of cutting-edge technologies: | Effective processing of huge volumes of voice or text messages information by making use of Natural Language Processing and Sentiment Analysis, which utilize all the powers of cutting-edge technologies: | ||
| − | + | ||
| − | + | * extracts specific data from long texts (e.g. articles, books, bills) | |
| − | + | * automatically processes invoices, orders, contracts | |
| − | + | * identifies the writer’s emotions and recognizes hate speech | |
| − | + | * improves customer experience with chatbots and virtual assistants | |
| − | |||
| − | |||
| − | |||
'''Predictive Analytics.''' | '''Predictive Analytics.''' | ||
Predictive analytics for organizations incorporates the power of Big Data, AI and Machine Learning (ML) technologies with using the available historical data: | Predictive analytics for organizations incorporates the power of Big Data, AI and Machine Learning (ML) technologies with using the available historical data: | ||
| − | + | ||
| − | + | * study available data and analyze clients’ behaviors to discover patterns | |
| − | + | * make predictions and decisions based on historical records | |
| − | + | * reduces churn by identifying the clients who want to leave | |
| − | + | * increases sales by suggesting what the client wants to buy and determines how much they will buy | |
| − | + | * identifies employees who are likely to leave the company | |
| − | + | * predicts demand for resources, product, and inventory | |
| − | + | * identifies the risk of breakdowns, failures, malfunctions, and errors | |
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
'''Anomaly Detection.''' | '''Anomaly Detection.''' | ||
| Line 50: | Line 41: | ||
''' Diseases diagnosis.''' | ''' Diseases diagnosis.''' | ||
Medical images analysis for diseases diagnosis based on | Medical images analysis for diseases diagnosis based on | ||
| − | + | * X-ray | |
| − | + | * MRI | |
| − | + | * CT | |
| − | |||
| − | |||
| − | |||
'''Face recognition.''' | '''Face recognition.''' | ||
Revision as of 18:13, 17 October 2019
Department of Theoretical and Applied Mechanics > Applied research
Applied research
This page describes the applied research carried out by the Department of Theoretical and Applied Mechanics (Institute of Applied Mathematics and Mechanics, Polytechnical University).
Contents
Nuclear Power Engineering
Researches for the nuclear industry are held in USTC "Technical diagnostics and reliability of nuclear and thermal power plants", headed by Yuri Yevgenyevich Karyakin, Professor of the Department of Theoretical and Applied Mechanics.
Data Science Research Projects
The list of projects carried out for Weatherford, Radar MMS, Factoria LS, "KOSMOS-NEFT-GAS" etc. by the Department of Theoretical and Applied Mechanics:
Text processing (Natural Language processing). Effective processing of huge volumes of voice or text messages information by making use of Natural Language Processing and Sentiment Analysis, which utilize all the powers of cutting-edge technologies:
- extracts specific data from long texts (e.g. articles, books, bills)
- automatically processes invoices, orders, contracts
- identifies the writer’s emotions and recognizes hate speech
- improves customer experience with chatbots and virtual assistants
Predictive Analytics. Predictive analytics for organizations incorporates the power of Big Data, AI and Machine Learning (ML) technologies with using the available historical data:
- study available data and analyze clients’ behaviors to discover patterns
- make predictions and decisions based on historical records
- reduces churn by identifying the clients who want to leave
- increases sales by suggesting what the client wants to buy and determines how much they will buy
- identifies employees who are likely to leave the company
- predicts demand for resources, product, and inventory
- identifies the risk of breakdowns, failures, malfunctions, and errors
Anomaly Detection. Machine Learning based Anomaly Detection implementation for data quality, cybersecurity, fraud detection, and other such business use cases discovering similarities, anomalies and outliers in data, also predicting upcoming possible anomalies in the future.
Computer Vision for remote sensing. Deep learning based approach for classification and semmantic segmentation of remote sensing data obtained from satellites and UAV
Diseases diagnosis. Medical images analysis for diseases diagnosis based on
- X-ray
- MRI
- CT
Face recognition. Automatic staff and secutity control systems based on computer vision approach
Prediction of crack propogation profile during hydraulic fracturing.
Prediction of the mechanical properties of materials.
Hardware defect prediction.
Resonance Enhanced Drilling, RED
The Department of Theoretical and Applied Mechanics and The University of Aberdeen have been collaborating on the topic of rock massif destruction under the action of resonance drilling since 1999. Read more...
High-speed photography
The list of projects carried out for Weatherford, Radar MMS, Factoria LS, "KOSMOS-NEFT-GAS" etc. by the Department of Theoretical and Applied Mechanics:
- Vibrations of the moving parts of the aircraft
- Dynamics of multiphase flows
- Cleaning of metal surfaces by a vacuum arc
- Arc discharges
- Motions of athletes
Oil and Gas
Employees of the Department of Theoretical and Applied Mechanics conducted research for the leading oilfield services companies in the following areas:
- Simulation of hydraulic fracturing and related technological and geomechanical processes
- Studying of the dynamics of proppant in hydraulic fracturing
- Studying of the rheological properties of multiphase mixtures
Equipment for 3D-filming
The Department of Theoretical and Applied Mechanics in association with Photomechanics Ltd. develops professional equipment for creating 3D-images
Fracture
Employees of the Department of Theoretical and Applied Mechanics developed an original technique of modeling the formation and development of cracks in solids, based on the method of particle dynamics. This method was used to describe such processes as:
- Percussive drilling
- Spall fracture
- Hydraulic fracturing
- Punching of a deformable barrier with a striker
- Formation and development of fatigue cracks
Key publications on this topics are provided here.
Construction mechanics
Employees of the Department of Theoretical and Applied Mechanics investigated the stability of thin-walled structures for JORIS IDE.
Extreme sports
The Department of Theoretical and Applied Mechanics in association with AlpineReplay ltd. (USA) are developing sensors, software and mobile applications for use in extreme sports (snowboarding, skateboarding, skiing, surfing, etc.).
Partners and customers
The following Russian and foreign companies are the partners and customers of the department:
- Weatherford
- Sandia National Laboratories
- JORIS IDE
- AlpineReplay
- LINCAS
- ООО ФПК "Космос-Нефть-Газ" (Financial & Industrial Company KOSMOS-NEFT-GAS)
- Конструкторское Бюро Химавтоматики (OSC «Konstruktorskoe Buro Khimavtomatiky»)
- Photomechanics Ltd.
- "GeoScan"
- Radar MMS
- Factoria LS
- Research & Engineering Corporation Mechanobr-Tekhnika
- IPME RAS
- WHO National Research Institute of Influenza
Order a research
To order a research, please contact Vitaly Andreyevich Kuz'kin, the Deputy Head for Research Affairs.
Tel.: +7 906 252 25 54
Email: kuzkinva at gmail.com
