Computational Sciences and Artificial Intelligence in Industry : New Digital Technologies for Solving Future Societal and Economical Challenges

Novel strategies for data-driven evolutionary optimization Machine learning using distance-based methods Counting cells and predicting immunoscore using gradient boosted convolutional neural networks Kubelka-Munk model and stochastic model comparison in skin physical parameter retrieval using neural networks A combined approach of neural networks and graphical models in skin cancer inference using spectral imaging Using wave propagation simulations and convolutional neural networks to retrieve thin coating's thickness from hyperspectral images Predicting future overweight and obesity from childhood growth data: A case study Variable selection under a value acquisition budget Stochastic approximation by successive piecewise linearization Non-convex robust low-rank matrix recovery Neural network learning via successive piecewise linearization Learning for scienti¿c computing purposes Computational intelligence in design of new nanomaterials Modeling ¿ow, reactive transport and geomechanics in porous media Physics constrained machine learning for industrial applications Parameter and type identi¿cation in partial di¿erential equations using deep neural networks Stability maximization for layered moving web with total mass constraint Similarity solutions for condensation on a non-isothermal vertical plate Enhanced topology optimization approach using moving morphable components coupled with NURBS curves Combined model order reduction and arti¿cial neural network for data assimilation and damage detection in structures Towards the optimization of fuzzy pattern trees by abs - linearization Support vector machines in clusterwise linear regression A Second-order method with enriched hessian information for composite sparse optimization problems Missing value imputation via nonsmooth optimization and clusterwise linear regression Parsimonious neural networks Nobody can stop advancing arti¿cial intelligence (AI) where developing Computational sciences, physics ¿eld theories and geometry Mini-symposium on ethics in AI Essentializing software engineering practices for ethically designing and developing arti¿cial intelligence systems 30 Ethics is important, but how can we implement it? Survey on software developers' views on AI ethics Industrial IoT capabilities in reducing the LCOE of o¿shore wind energy: A review High-Performance data analysis with the Helmholtz Analytics Toolkit (HeAT)  Dynamic data-driven application systems based on tensor factorization: learning the physics of model evolution Predicting customer experience Puhti-AI: Finland's new AI supercomputer Using Arti¿cial Intelligence to Classify Textual Applications for Reporting Purposes  Application of machine learning methods to error control of approximate solutions Iterative data selection strategy in o¿ine data-driven evolutionary multiobjective optimization On surrogate management in interactive multiobjective building energy system design A modi¿ed deep neural network for the rapid inversion of geo-physical resistivity measurements Using agents for automatic meta-modelling algorithm selection in data-driven multiobjective optimization problems Future cooperation between Computational Science and AI in Industrial and Societal Applications - challenges, impact and expectations? Arti¿cial Intelligence, Deep Lea