Most recent publications:


Tomkowski, R., Sorsa, A., Santa-Aho, S., Lundin, P. & Vippola, M. (2019) Statistical Evaluation of Barkhausen Noise Testing (BNT) for Ground Samples. Sensors, Vol. 19(21), 4716. doi: 10.3390/s19214716

Santa-Aho, S., Laitinen, A., Sorsa, A. & Vippola, M. (2019) Barkhausen Noise Probes and Modelling: A Review. Journal of Nondestructive Evaluation, Vol. 38(4), 11 p. doi: 10.1007/s10921-019-0636-z

Tomperi, J. & Leiviskä, K. (2019) Utilizing variable selection methods in modelling potable water quality. Water Science and Technology: Water Supply, 19(4), p. 1187-1194. doi: 10.2166/ws.2018.173

Vuolio, T., Visuri, V.V., Sorsa, A., Paananen, T. & Fabritius, T. (2019) Genetic algorithm‐based variable selection in prediction of hot metal desulfurization kinetics. Steel Research International, 90(8). doi: 10.1002/srin.201900090

Hietaharju, P., Ruusunen, M., Leiviskä, K. & Paavola, M. (2019) Predictive optimization of the heat demand in buildings at the city level. Applied Sciences, 9(10), 1994. doi: 10.3390/app9101994

Sorsa, A., Santa-Aho, S., Aylott, C., Shaw, B.A., Vippola, M. & Leiviskä, K. (2019) Case depth prediction of nitrided samples with Barkhausen noise measurement. Metals, 9(3), 325. doi: 10.3390/met9030325

Hietaharju, P., Ruusunen, M. & Leiviskä, K. (2019) Enabling demand side management: heat demand forecasting at city level. Materials, 12(2), 202. doi: 10.3390/ma12020202

Ohenoja, M., Ruusunen, M. & Leiviskä, K. (2019) Hierarchical control of an integrated fuel processing and fuel cell system. Materials, 12(1), 21. doi: 10.3390/ma12010021

Nikula, R., Karioja, K., Leiviskä, K. & Juuso, E. (2019) Prediction of mechanical stress in roller leveler based on vibration measurements and steel strip properties. Journal of Intelligent Manufacturing, 30(4), p. 1563-1579. doi: 10.1007/s10845-017-1341-3


Publications starting from year 2000