Cases studies

Sectors
z = −1 + i nα = θ + 2πk f(x) = 3x − 2 z = r (cosθ + isinθ) z = r (cosθ + isinθ) ax + by + cz + d = 0 2x + 2y + z + 4t = 0 C = {z = x + iy x, y ∈ IR}

Making forecasts to optimize the electricity grid management

Accurate forecasts that support operators in making effective decisions for managing electricity grid.

z = −1 + i nα = θ + 2πk u = ρ (cosα + isinα) ax + by + cz + d = 0 a (f(x + T) = f(x), ∀ x ∈ IR) (f(−x) = f(x), ∀ x ∈ D) 2x + 2y + z + 4t = 0 C = {z = x + iy x, y ∈ IR}

Customer credit behavior prediction

A tool that allows to have a complete view of customers.

a (f(x + T) = f(x), ∀ x ∈ IR) (f(−x) = f(x), ∀ x ∈ D) −x + 2y + z + t = −1 2x + 2y + z + 4t = 0 C = {z = x + iy x, y ∈ IR} (f(−x) = f(x), ∀ x ∈ D) 2x + 2y + z + 4t = 0 C = {z = x + iy x, y ∈ IR}

Mathematical models to reduce customer churn rate

Allowing customer service to take targeted actions to prevent and refine the offer.

z = −1 + i nα = θ + 2πk u = ρ (cosα + isinα) f(x) = 3x − 2 −x + 2y + z + t = −1 2x + 2y + z + 4t = 0 C = {z = x + iy x, y ∈ IR} [x0 −r, x0 + r] (cosnα + isinnα) = (cosα + isinα)n

Forecasting in natural gas logistics

Enhancement of forecasting tools for different market clusters.

z = −1 + i nα = θ + 2πk f(x) = 3x − 2 z = r (cosθ + isinθ) (f(−x) = f(x), ∀ x ∈ D) ax + by + cz + d = 0 −x + 2y + z + t = −1 2x + 2y + z + 4t = 0 C = {z = x + iy x, y ∈ IR}

Mathematics to optimize advertising investments

An accurate measure of the return of online and offline advertising investments

z = −1 + i f(x) = 3x − 2 z = r (cosθ + isinθ) ax + by + cz + d = 0 nα = θ + 2πk −x + 2y + z + t = −1 2x + 2y + z + 4t = 0 C = {z = x + iy x, y ∈ IR}

Market analysis for anti-influenza products

Better plan your marketing campaigns in correspondence with the peak periods of influenza.

u = ρ (cosα + isinα) f(x) = 3x − 2 z = r (cosθ + isinθ) a (f(x + T) = f(x), ∀ x ∈ IR) (f(−x) = f(x), ∀ x ∈ D) 2x + 2y + z + 4t = 0 C = {z = x + iy x, y ∈ IR}

Data science at the service of hospitals

SmartAid Medical Solution, a digital platform based on artificial intelligence algorithms.

z = −1 + i nα = θ + 2πk u = ρ (cosα + isinα) u = ρ (cosα + isinα) f(x) = 3x − 2' −x + 2y + z + t = −1 2x + 2y + z + 4t = 0 C = {z = x + iy x, y ∈ IR}

Machine learning for public and private tenders

Improve the activities of building a pre-competitive scenario for tenders.

ax + by + cz + d = 0 (f(−x) = f(x), ∀ x ∈ D) [x0 −r, x0 + r] (cosnα + isinnα) = (cosα + isinα)n z = −1 + i nα = θ + 2πk z = r (cosθ + isinθ) (f(−x) = f(x), ∀ x ∈ D) 2x + 2y + z + 4t = 0 C = {z = x + iy x, y ∈ IR}

Mathematics to choose the most suitable protesis

Algorithm to support surgeons in choosing the best prosthesis for each patient.

−x + 2y + z + t = −1 2x + 2y + z + 4t = 0 C = {z = x + iy x, y ∈ IR} z = −1 + i u = ρ (cosα + isinα) ax + by + cz + d = 0 −x + 2y + z + t = −1 2x + 2y + z + 4t = 0 C = {z = x + iy x, y ∈ IR}

Algorithms at the service of diagnostic imaging

Automatically detect the presence of possible anomalies in medical imaging.

ax + by + cz + d = 0 a (f(x + T) = f(x), ∀ x ∈ IR) (f(−x) = f(x), ∀ x ∈ D) −x + 2y + z + t = −1 2x + 2y + z + 4t = 0 C = {z = x + iy x, y ∈ IR} [x0 −r, x0 + r] (cosnα + isinnα) = (cosα + isinα)n

Virtual prototyping in the design process

Standardize the design process and to be able to create the layout of a new plant in less time.

z = −1 + i nα = θ + 2πk u = ρ (cosα + isinα) f(x) = 3x − 2 ax + by + cz + d = 0 C = {z = x + iy x, y ∈ IR} [x0 −r, x0 + r] (cosnα + isinnα) = (cosα + isinα)n

Production scheduling optimization

Create scheduling software for rapid and effective planning of processes.

z = −1 + i nα = θ + 2πk z = r (cosθ + isinθ) 2x + 2y + z + 4t = 0 [x0 −r, x0 + r] (cosnα + isinnα) = (cosα + isinα)n 2x + 2y + z + 4t = 0 −x + 2y + z + t = −1 C = {z = x + iy x, y ∈ IR}

Mathematical modeling applied to liquid packaging machinery

Simulation algorithms that allow to test the various parameters and different configurations of the production machine.

z = r (cosθ + isinθ) 2x + 2y + z + 4t = 0 C = {z = x + iy x, y ∈ IR} z = −1 + i f(x) = 3x − 2 ax + by + cz + d = 0 C = {z = x + iy x, y ∈ IR} [x0 −r, x0 + r] (cosnα + isinnα) = (cosα + isinα)n

A mathematical estimator for the design of large plants

Estimate the types and quantities of materials needed for a new project in a shorter time.

nα = θ + 2πk u = ρ (cosα + isinα) f(x) = 3x − 2' z = r (cosθ + isinθ) x + by + cz + d = 0' f(x) = 3x − 2 z = r (cosθ + isinθ) ax + by + cz + d = 0

Early warning to identify and manage product defects

Promptly identify and manage any problems in production batches.

x + by + cz + d = 0' a (f(x + T) = f(x), ∀ x ∈ IR) z = −1 + i (f(−x) = f(x), ∀ x ∈ D) −x + 2y + z + t = −1 2x + 2y + z + 4t = 0 C = {z = x + iy x, y ∈ IR} [x0 −r, x0 + r] (cosnα + isinnα) = (cosα + isinα)n

Remote monitoring of household appliances’ operation

Predict when a failure will occur and which component of the washing machine will fail.

nα = θ + 2πk u = ρ (cosα + isinα) a (f(x + T) = f(x), ∀ x ∈ IR) (f(−x) = f(x), ∀ x ∈ D) −x + 2y + z + t = −1 2x + 2y + z + 4t = 0 C = {z = x + iy x, y ∈ IR} [x0 −r, x0 + r] (cosnα + isinnα) = (cosα + isinα)n

Anomaly detection during flight tests

Identification and removal of anomalous data recorded by on-board sensors during prototype flight tests.

z = −1 + i nα = θ + 2πk u = ρ (cosα + isinα) f(x) = 3x − 2 z = r (cosθ + isinθ) ax + by + cz + d = 0 f(x) = 3x − 2' 2x + 2y + z + 4t = 0

Real time monitoring of energy cables’ health status

Controlled, automatic and reliable detection of electrical cable anomalies.

z = r (cosθ + isinθ) ax + by + cz + d = 0 a (f(x + T) = f(x), ∀ x ∈ IR) (f(−x) = f(x), ∀ x ∈ D) −x + 2y + z + t = −1 2x + 2y + z + 4t = 0 C = {z = x + iy x, y ∈ IR}

Mathematical models to optimize process and product quality

Support engineers in monitoring, predicting and improving all aspects of the manufacturing process that affect the quality of a product.

f(x) = 3x − 2 z = r (cosθ + isinθ) a (f(x + T) = f(x), ∀ x ∈ IR) (f(−x) = f(x), ∀ x ∈ D) −x + 2y + z + t = −1 2x + 2y + z + 4t = 0 [x0 −r, x0 + r] (cosnα + isinnα) = (cosα + isinα)n

Mobile advertising strategies

Deep profiling algorithm capable of classifying users with respect to their offline behaviors.

z = r (cosθ + isinθ) ax + by + cz + d = 0 a (f(x + T) = f(x), ∀ x ∈ IR) −x + 2y + z + t = −1 2x + 2y + z + 4t = 0 C = {z = x + iy x, y ∈ IR} [x0 −r, x0 + r] (cosnα + isinnα) = (cosα + isinα)n

Mathematics to predict audience ratings

Predict the audience in the short term, in order to better plan schedules and purchases of audiovisual content.

z = −1 + i nα = θ + 2πk f(x) = 3x − 2 z = −1 + i −x + 2y + z + t = −1 2x + 2y + z + 4t = 0 C = {z = x + iy x, y ∈ IR} [x0 −r, x0 + r] (cosnα + isinnα) = (cosα + isinα)n

Support to the planning of a television schedule

Decision support tool for channel manager scheduling.

z = −1 + i (f(−x) = f(x), ∀ x ∈ D) u = ρ (cosα + isinα) z = r (cosθ + isinθ) ax + by + cz + d = 0 a (f(x + T) = f(x), ∀ x ∈ IR) (f(−x) = f(x), ∀ x ∈ D) C = {z = x + iy x, y ∈ IR}

Algorithms for school publishing

Support teachers in selecting and adopting the best textbooks for their students.

C = {z = x + iy x, y ∈ IR} z = −1 + i nα = θ + 2πk u = ρ (cosα + isinα) f(x) = 3x − 2 ax + by + cz + d = 0 [x0 −r, x0 + r] (cosnα + isinnα) = (cosα + isinα)n

Allocation of products in the fashion & luxury goods sector

Automate and improve the process of allocating products in stock to retailers.

z = −1 + i nα = θ + 2πk u = ρ (cosα + isinα) f(x) = 3x − 2 z = r (cosθ + isinθ) ax + by + cz + d = 0 C = {z = x + iy x, y ∈ IR}

Virtual coach: artificial intelligence on the bench

Suggest to the coach the best tactic to adopt, monitoring the opponents' play and their vulnerabilities.

z = −1 + i nα = θ + 2πk u = ρ (cosα + isinα) z = r (cosθ + isinθ) ax + by + cz + d = 0 −x + 2y + z + t = −1 C = {z = x + iy x, y ∈ IR}

Mathematics applied to fundraising for a non-profit organization

A dynamic, fast and concise view of donations and fundraising campaigns through a web platform.