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  • Machine Learning

The Future of Your Organization Is in Machine Intelligence

Array offers world-class technology enabling intelligent applications across all business sectors. We'll work with you, hand-in-hand, to set challenging goals and objectives for enhancing your business performance through applications of our predictive analytics, machine learning, optimization and on-going automated performance enhancement.

  • Agriculture, Forestry, Fishing and Hunting
    Agriculture, Forestry, Fishing and Hunting
    Using sensors and remote sensing, Array can extract new insights and knowledge to increase sales, profits and quality. Array’s expertise in Biomass and soil moisture... read more
    Agriculture, Forestry, Fishing and Hunting
    Using sensors and remote sensing, Array can extract new insights and knowledge to increase sales, profits and quality. Array’s expertise in Biomass and soil moisture estimates can help those in agriculture make informed decisions about:
    • Which crops may perform best given the soil moisture
    • Where forest fires are more likely due to biomass levels
    • Where are the best logging locations by identifying tree density
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  • Mining, Quarrying, and Oil & Gas Extraction
    Mining, Quarrying, and Oil & Gas Extraction
    Using sensors in pipelines, mines, rigs, and remote sensing Array can extract new insights and knowledge to increase sales, profits and quality. Using machine learning algorithm... read more
    Mining, Quarrying, and Oil & Gas Extraction
    Using sensors in pipelines, mines, rigs, and remote sensing Array can extract new insights and knowledge to increase sales, profits and quality. Using machine learning algorithm combined with interferometric synthetic aperture radar techniques, Array can help oil and gas companies monitor changes in surface elevation to indicate levels of oil/gas extraction. We are also capable of predicting refinery sensor failure and streamlining refinery and distribution.
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  • Manufacturing
    Manufacturing
    Using customer behavior records, sensors on manufacturing and supply we can extract new insights and knowledge to increase sales, profits and quality. Your organization can... read more
    Manufacturing
    Using customer behavior records, sensors on manufacturing and supply we can extract new insights and knowledge to increase sales, profits and quality. Your organization can also benefit from machine learning algorithms to extract informaton organizations, people and events from unstructured text. Machine Learning can be used for continuous process improvement and scrap reduction.
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  • Wholesale Trade
    Wholesale Trade
    Using customer behavior records, receipts, internal records Array can extract new insights and knowledge to increase sales, profits and quality. Array can also perform Anomaly... read more
    Wholesale Trade
    Using customer behavior records, receipts, internal records Array can extract new insights and knowledge to increase sales, profits and quality. Array can also perform Anomaly Detection- to flag any malpractice in very high volume high frequency data transactions / communications.
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  • Retail Trade
    Retail Trade
    In Retail Trade, Array's software can:
    • Develop ad optimization & pricing
    • Use user traffic data to decide which ads to display, when, to whom, for how...
    • read more
      Retail Trade
      In Retail Trade, Array's software can:
      • Develop ad optimization & pricing
      • Use user traffic data to decide which ads to display, when, to whom, for how much
      • Exploit users’ buying patterns and offer real-time item recommendations
      • Recommend items, target ads to likely buyers and parse lists into customer segments with similar buying habits
      • Minimize customer churn, and identifying customer segmentation
      • Using customer behavior records, receipts, internal records to extract new insights and knowledge to increase sales, profits and quality
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  • Transportation and Warehousing
    Transportation and Warehousing
    Machine Learning can be used to generative probabilistic graphical model to describe multivariate continuous densities such as observed traffic patterns. Data collected... read more
    Transportation and Warehousing
    Machine Learning can be used to generative probabilistic graphical model to describe multivariate continuous densities such as observed traffic patterns. Data collected from highways enables us to bring supervised learning approaches to incident detection. It has been shown that a support vector machine learner can outperform manually calibrated solutions. Array can also assist in:
    • Predicting Near Future Traffic Jams and Hot Spots of Congestion
    • Predicting secondary incident location (warning and planning
    • Incident duration prediction
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  • Finance and Insurance
    Finance and Insurance
    Array can use Machine Learning to generate predictive models that unlock intrinsic patterns in data and reveal key guidance for when to trade, which clients are of a higher... read more
    Finance and Insurance
    Array can use Machine Learning to generate predictive models that unlock intrinsic patterns in data and reveal key guidance for when to trade, which clients are of a higher risk profile and how assets should be allocated. Machine Learning are also at play to flag any malpractice in very high volume high frequency data transactions / communications, to identify what unique behaviors or attributes in a customers digital journey are closely correlated with revenue generating events and to extract new insights and knowledge to increase sales, profits and quality.
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  • Real Estate Rental and Leasing Companies
    Real Estate Rental and Leasing Companies
    Array can use machine learning to track your site visitors and leads’ behavior to help you determine whether they are looking to buy, sell, or rent or home. From there you’ll be... read more
    Real Estate Rental and Leasing Companies
    Array can use machine learning to track your site visitors and leads’ behavior to help you determine whether they are looking to buy, sell, or rent or home. From there you’ll be able to better segment and target your leads to send them relevant information. Algorithms can show agents which houses a particular buyer is most likely to buy. What's more is that Array's software can also be used for the prediction of the average rent price of certain real estate units.
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  • Accommodation and Food Services
    Accommodation and Food Services
    In the Acoomodation and Food Services industry, Machine Learning can be used for:
    • The application of food quality inspection, when combined with...
    • read more
      Accommodation and Food Services
      In the Acoomodation and Food Services industry, Machine Learning can be used for:
      • The application of food quality inspection, when combined with computer vision techniques
      • Recommending items, target ads to likely buyers and parse lists into customer segments with similar buying habits
      • Tood evaluation. Among the applications of learning algorithms in computer vision for food quality evaluation, most of them are for classification and prediction.
      • Demand forecasting in the Hospitality industry
      • Price Optimization for hotel rooms based on the person doing the renting
      • Identify what unique behaviors or attributes in a visitor’s digital journey are closely correlated with revenue generating events
      • Help marketing departments integrate digital data with offline guest profiles, which is used for modeling to support personalized content delivery, offers and recommendations digitally as well as when the guest is on property
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  • Health Care
    Health Care
    Machine Learning can be used to expedite patient triage and general hospital procedure optimization to prognosticating adverse reactions to drugs. In addition, Array's... read more
    Health Care
    Machine Learning can be used to expedite patient triage and general hospital procedure optimization to prognosticating adverse reactions to drugs. In addition, Array's software can be exploited to:
    • Devise novel tools to support decision-making and research
    • Integrate activities in medical, software and cognitive sciences
    • Offer a content-rich discipline for future scientific medical community.
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  • Aerospace and Defence
    Aerospace and Defence
    Array has been supporting the Canadian defense industry though research and development projects in Sonar, Radar & Remote Sensing, and Transportation for over... read more
    Aerospace and Defence
    Array has been supporting the Canadian defense industry though research and development projects in Sonar, Radar & Remote Sensing, and Transportation for over 35 years. Array has built simulation tools promoting our core areas of Sonar and Radar. Most recently Array has developed simulation tools to support various Human Factors research at DRDC-Toronto in the areas of Mobile GIS Symbology, as well as modifying and enhancing software simulation tools for the underwater warfare domain (range detection and estimation, multi-static sonar analysis, etc.).
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  • Information and Cultural Industries
    Information and Cultural Industries
    Machine Learning are at play to flag any malpractice in very high volume high frequency data transactions / communications. Using internal records... read more
    Information and Cultural Industries
    Machine Learning are at play to flag any malpractice in very high volume high frequency data transactions / communications. Using internal records Array can extract new insights and knowledge to increase sales, profits and quality.
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    Contact us now for a 1-hour free requirements discussion with one of our experts!

Machine Learning

Array has been developing modeling and simulation tools using big data and machine learning techniques for over 20 years. Starting in the 1990s Array used Artificial Neural Networks for detection of hidden contraband (gun, knives, etc.) in luggage from X-ray images. Array uses Kalman and Particle Filters to estimate the hidden state space models used for tracking ships and submarines on their naval tactical displays, as well as for performing time motion analysis (TMA) (for localizing position and speed of sonar contacts) from only their sonar bearing estimates.

More recently, working with DRDC, Array has developed software tools for Social Network Analysis and Semantic Analysis. This approach used the Latent Semantic Analysis bag-of-words approach to determine the semantic content of text documents. We have successfully completed several projects working with the European Space Agency (ESA), Agriculture Canada, and Natural Resources Canada to develop big data classifiers using Support Vector Machines (SVM) on large data sets of Synthetic Aperture Radar (SAR) satellite imagery. Our software platform will help expert and non-expert users alike to interpret and analyze SAR imagery.

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Related Projects:

We partner with clients worldwide:

  • European Space Agency
  • Canadian Forest Service
  • Natural Resources Canada
  • Agriculture and Agri-Food Canada
  • Brockmann Consult
  • Defence Research and Development Canada
  • Università degli Studi di Trento

    Meet Our Experts

    Array's qualified team is comprised of industry veterans with expertise in providing proven software solutions to military, governmental and scientific organizations worldwide.

     

    • Rajesh Jha
    • Kristopher Huber
    • Luis Veci
    • Jun Lu
    • Rajesh Jha

      Rajesh Jha

      Rajesh Jha is the Director of Programs at Array. He brings his experience in understanding customer requirements, ensuring that these are translated and met by the development team and ensuring customer satisfaction in addition to his wide technical experience. His technical experience covers signal processing, image processing, modeling and simulation, parallel computation, machine learning. In particular for machine learning he brings his knowledge of Neural Networks, Probabilistic Graphical Models, Support Vector Machines to help find the best solution to address customer needs to understand data and improve business performance.

      Rajesh has an M.A.Sc. degree in Engineering from the University of Toronto and B.Tech. degree in Engineering from the Indian Institute of Technology (IIT), Delhi. He also has his Project Management Professional (PMP) Certification.

    • Kristopher Huber

      Kristopher Huber

      As the Chief Technology Officer (CTO) of Array, Kris surveys and assesses the impact of new and emerging technologies on the company. He guides the company on its technical direction, and through consultation with clients and stakeholders develops new technologies and strategies for improving the company's competitive performance within a given industry.

      Kris has 10 years of R&D expertise emphasizing the development of relevant and innovative research initiatives. Before becoming the CTO of Array, Kris was the Manager of R&D at Array Systems. Kris received his PhD in Electrical Engineering in 2005 from McMaster University.

    • Luis Veci

      Luis Veci

      Luis Veci has worked at Array for over 15 years as a software lead designing and developing software for Earth Observation and sonar processing. During his academic career, Luis has designed and implemented reinforcement learning and ant colony optimization algorithms for subsumption architecture robotic simulations. Luis also developed genetic algorithms for route planning software as well as for handwriting recognition. While at Array, Luis has lead the design and development of various projects involving machine learning for Earth Observation including the use of support vector machines with active learning, decision trees, random forest, feature extraction and advanced image processing.
    • Jun Lu

      Jun Lu

      Dr. Jun Lu has worked at Array for over fifteen years as a signal processing specialist. He brings a strong theoretical grounding gained from his Ph.D. in Electrical Engineering and significant design and implementation experience gained delivering successful projects and products. He has used machine learning to implement solutions for information analysis and data analytics. Techniques he has expertise with include Support Vector Machines (SVM), Random Forests, K-Nearest Neighbour (KNN), Maximum Likelihood (ML). A recent example is the development of feature extraction and analysis of EO data using SVM and Active Learning algorithms.