430 XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3
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for Modelling of Open-Cell Aluminum under
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10.1155/2020/2834317.
Kolacz, J., 2014. Advanced sorting system for minerals with
multiple sensing features. In: Proceedings of Sensor
Based Sorting Conference, 11–13 March, Aachen,
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recognition: the new powerful tool in mineral. process-
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Kolacz, J., 2015. Dry coal beneficiation by sensor based
sorting. In: Proceedings of Mineral Engineering.
Conference, 14–17 September 2015, Szczawnica, Poland.
Kolacz, J., 2016. Efficient scale up of sensor based sorting
systems. In Proceedings of XXVIII.
International Mineral Processing Congress, 11–15
September, Quebec, Canada.
Kolacz, J., 2018. Operating cost of the sensor based sorting
systems—major limitations and optimization poten-
tial. In Proceedings of XXIX International Mineral
Processing Congress, 15–21 September, Moscow,
Russia.
Kolacz, J., 2019. New high definition X-ray sorting system
based on X-MINE detection technology.
In: Proceedings of Mineral Engineering Conference, 16–19
September 2019, Kocierz, Poland.
Madsen K., Nielsen H., Tingleff O., Methods for non-
linear least squares problems. In Informatics and
Mathematical Modelling Technical University of
Denmark. 2nd ed. April 2004. Available online:
http://www2.imm.dtu.dk/pubdb/edoc/imm3215.pdf
(accessed on 15th Oct 2018).
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BMJ, 2012 345:e4483 doi: 10.1136/bmj.e4483, July
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Polansky, S., Doubravova, D., Jakubek, J., Jakubek, M.,
Soukup, P., Turecek, D., 2018. High-sensitivity on-
line imaging analysis of mining ore extraction by X-ray
multichannel transmission radiography. In: proceed-
ings of IEEE Nuclear Science Symposium and Medical
Imaging Conference, Sydney, Australia.
Progorowicz, J., Skoczylas, A., Anufriiev, S., Dudzik, M.,
Stefaniak, P. Estimation of Final Product.
Concentration in Metalic Ores Using Convolutional
Neural Networks. Minerals 2022, 12, 1480. doi:
10.3390/min12121480, Link: https://www.mdpi.
com/2075-163X/12/12/1480.
Wieniewski, A., Szczerba, E., Nad, A., Luczak, R., Kolacz,
J., Szewczuk, A., 2015. Evaluation of the application
possibilities of modern separation techniques for pre-
concentration of the Zn-Pb ore. In: Proceedings of XI
International Non-Ferrous Metals Conference ICNOP.
27–29 May, Trzebieszowice, Poland.
Wills, B.A., 2006. An Introduction to the Practical Aspects
of Ore Treatment and Mineral Recovery. In:.
Wills’ Mineral Processing Technology: Seventh Edition,
Chapter 11: Dense Medium Separation.
REFERENCES
Dudzik M., Towards Characterization of Indoor
Environment in Smart Buildings: Modelling PMV
Index.
Using Neural Network with One Hidden Layer.Sustainability,
2020, 12, 6749, doi: 10.3390/su12176749, https://
www.mdpi.com/2071-1050/12/17/6749.
Dudzik M., Stręk A.M., ANN Architecture Specifications
for Modelling of Open-Cell Aluminum under
Compression, Mathematical Problems in Engineering,
Volume 2020 Article ID 2834317, 2020-02-28, doi:
10.1155/2020/2834317.
Kolacz, J., 2014. Advanced sorting system for minerals with
multiple sensing features. In: Proceedings of Sensor
Based Sorting Conference, 11–13 March, Aachen,
Germany.
Kolacz, J., 2014. Sensor based sorting with signal pattern
recognition: the new powerful tool in mineral. process-
ing. In: Proceedings of XXVII International Mineral
Processing Congress, Santiago, Chile, p106–115.
Kolacz, J., 2015. Dry coal beneficiation by sensor based
sorting. In: Proceedings of Mineral Engineering.
Conference, 14–17 September 2015, Szczawnica, Poland.
Kolacz, J., 2016. Efficient scale up of sensor based sorting
systems. In Proceedings of XXVIII.
International Mineral Processing Congress, 11–15
September, Quebec, Canada.
Kolacz, J., 2018. Operating cost of the sensor based sorting
systems—major limitations and optimization poten-
tial. In Proceedings of XXIX International Mineral
Processing Congress, 15–21 September, Moscow,
Russia.
Kolacz, J., 2019. New high definition X-ray sorting system
based on X-MINE detection technology.
In: Proceedings of Mineral Engineering Conference, 16–19
September 2019, Kocierz, Poland.
Madsen K., Nielsen H., Tingleff O., Methods for non-
linear least squares problems. In Informatics and
Mathematical Modelling Technical University of
Denmark. 2nd ed. April 2004. Available online:
http://www2.imm.dtu.dk/pubdb/edoc/imm3215.pdf
(accessed on 15th Oct 2018).
Philip S., Pearson’s correlation coefficient. ENDGAMES,
BMJ, 2012 345:e4483 doi: 10.1136/bmj.e4483, July
2012.
Polansky, S., Doubravova, D., Jakubek, J., Jakubek, M.,
Soukup, P., Turecek, D., 2018. High-sensitivity on-
line imaging analysis of mining ore extraction by X-ray
multichannel transmission radiography. In: proceed-
ings of IEEE Nuclear Science Symposium and Medical
Imaging Conference, Sydney, Australia.
Progorowicz, J., Skoczylas, A., Anufriiev, S., Dudzik, M.,
Stefaniak, P. Estimation of Final Product.
Concentration in Metalic Ores Using Convolutional
Neural Networks. Minerals 2022, 12, 1480. doi:
10.3390/min12121480, Link: https://www.mdpi.
com/2075-163X/12/12/1480.
Wieniewski, A., Szczerba, E., Nad, A., Luczak, R., Kolacz,
J., Szewczuk, A., 2015. Evaluation of the application
possibilities of modern separation techniques for pre-
concentration of the Zn-Pb ore. In: Proceedings of XI
International Non-Ferrous Metals Conference ICNOP.
27–29 May, Trzebieszowice, Poland.
Wills, B.A., 2006. An Introduction to the Practical Aspects
of Ore Treatment and Mineral Recovery. In:.
Wills’ Mineral Processing Technology: Seventh Edition,
Chapter 11: Dense Medium Separation.