MIC Journal

Modeling, Identification and Control

DOI

DOI INFORMATION FOR 10.4173:


General information about the DOI system can be found here and here. A DOI name is a digital object identifier for any object of intellectual property. A DOI name provides a means of persistently identifying a piece of intellectual property on a digital network and associating it with related current data in a structured extensible way. DOI was accepted as an ISO standard in 2010.
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If you have ever tried to follow an URL in an article older than 5-10 years, more often than not you will find that the URL is no longer active. The DOI system is an attempt to overcome this deficiency by providing stable and permanent references for intellectual property on the web.

The MIC journal has implemented the DOI system for every single article published in MIC since the foundation year in 1980. The DOI prefix for MIC is 10.4173 and an individual article has been assigned a DOI on the following format: 10.4173/mic.year.no.paperno. For example, the first article published in MIC by Oddvar Hallingstad has the following DOI: 10.4173/mic.1980.1.1 and the following permanent URL http://dx.doi.org/10.4173/mic.1980.1.1. This permanent URL links back to the www.mic-journal.no website. If the MIC website is moved in the future, the DOI information will be updated to point to the new address.

Another advantage of the DOI system, is the possibility to register all the references in an article in a structured manner. All the references made in MIC articles starting from 1980 have been submitted into the DOI system. The effect is an increased visibility of MIC articles, which again will lead to a wider audience. MIC also participates in the 'cited-by' system, which can be seen for this article. 'cited-by' shows which other papers have included the actual paper in the reference lists.

The MIC class files for pdfLaTeX found in the Author Information have commands for embedding DOI information in the PDF files. Prospective authors for future MIC articles will receive the DOI identification when the article is accepted. Authors are encouraged to embed the tag into the PDF file themselves using pdflatex prior to publication. Authors are also encouraged to embed DOI tags in their reference lists.

Click on the links below to see the external DOI forward links to MIC:
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DOI Forward Links to MIC for Year: 2022

 Total number of MIC articles in 2022  12
 Total number of DOI citations  33
 Average citations per article   2.75 

2022, Vol. 43, No. 4:
1.David Di Ruscio and Christer Dalen, “On subspace system identification methods”, pp. 119-130
DOI forward links to this article:
[1] Heri Khoeri, Galuh Adeputra and Zerik Sembada (2024), doi:10.33364/konstruksi/v.22-1.1549
2.Rolf Ergon “A BLUP derivation of the multivariate breeder's equation, with an elucidation of errors in BLUP variance estimates, and a prediction method for inbred populations”, pp. 131-140
DOI forward links to this article:
[1] Rolf Ergon (2023), doi:10.1002/ece3.10194
[2] Rolf Ergon (2023), doi:10.4173/mic.2023.3.1
3.Stig Kvaal, Per Østby and Morten Breivik, “DP and the Art of Perfect Positioning”, pp. 141-159
2022, Vol. 43, No. 3:
1.Rolf Ergon “Microevolutionary system identification and climate response predictions”, pp. 91-99
DOI forward links to this article:
[1] Rolf Ergon (2022), doi:10.4173/mic.2022.4.2
[2] Rolf Ergon (2023), doi:10.1002/ece3.10194
[3] Rolf Ergon (2023), doi:10.4173/mic.2023.3.1
2.Peihua Han, Guoyuan Li and Houxiang Zhang, “Leveraging Past Experience for Path planning of Marine Vessel: A Docking Example”, pp. 101-109
DOI forward links to this article:
[1] V. V. Golubov and S. V. Manko (2024), doi:10.32362/2500-316X-2024-12-1-7-14
3.Nour Bargouth, Christer Dalen and David Di Ruscio, “Dynamic positioning, system identification and control of marine vessels”, pp. 111-117
2022, Vol. 43, No. 2:
1.Zhe Ban, Ali Ghaderi, Nima Janatian and Carlos F. Pfeiffer, “Parameter Estimation for a Gas Lifting Oil Well Model Using Bayes' Rule and the Metropolis–Hastings Algorithm”, pp. 39-53
DOI forward links to this article:
[1] Kushila Jayamanne and Bernt Lie (2023), doi:10.4173/mic.2023.1.2
[2] Zhe Ban and Carlos Pfeiffer (2023), doi:10.1002/iis2.13046
[3] Zhe Ban and Carlos Pfeiffer (2024), doi:10.1016/j.geoen.2024.212954
2.Emil H. Thyri and Morten Breivik, “Collision avoidance for ASVs through trajectory planning: MPC with COLREGs-compliant nonlinear constraints”, pp. 55-77
DOI forward links to this article:
[1] Yonghoon Cho, Jinwook Park, Jonghwi Kim and Jinwhan Kim (2023), doi:10.1109/JOE.2023.3296836
[2] Robert Damerius, Johannes R. Marx and Torsten Jeinsch (2023), doi:10.1016/j.ifacol.2023.10.796
[3] Daiyong Zhang, Xiumin Chu, Chenguang Liu, Zhibo He, Pulin Zhang and Wenxiang Wu (2024), doi:10.3390/jmse12010107
[4] Yamin Huang, Hexin Yang, Zhe Du, Linying Chen and Yuanqiao Wen (2024), doi:10.1016/j.oceaneng.2024.117067
[5] Anastasios Tsolakis, Rudy R. Negenborn, Vasso Reppa and Laura Ferranti (2024), doi:10.1109/TITS.2024.3357284
[6] Aksel Trentemoller Frafjord, Ivar Bjorgo Saksvik, Oivind Kare Kjerstad and Erlend M. Coates (2024), doi:10.1016/j.ifacol.2024.10.066
3.Torbjørn Smith and Olav Egeland, “Dynamical Pose Estimation with Graduated Non-Convexity for Outlier Robustness”, pp. 79-89
DOI forward links to this article:
[1] Antonio Boccuto, Ivan Gerace and Valentina Giorgetti (2023), doi:10.3390/app13105861
[2] Giulio Biondi, Antonio Boccuto and Ivan Gerace (2023), doi:10.1007/978-3-031-37117-2_44
[3] Giulio Biondi, Antonio Boccuto and Ivan Gerace (2023), doi:10.1007/978-3-031-37117-2_45
[4] Liangzu Peng, Christian Kummerle and Rene Vidal (2023), doi:10.1109/CVPR52729.2023.01708
[5] Antonio Boccuto, Ivan Gerace, Valentina Giorgetti, Francesca Martinelli and Anna Tonazzini (2024), doi:10.1007/s10851-024-01204-y
2022, Vol. 43, No. 1:
1.Martinius Knudsen, Sverre Hendseth, Gunnar Tufte and Axel Sandvig, “Model-free Control of Partially Observable Underactuated Systems by pairing Reinforcement Learning with Delay Embeddings”, pp. 1-8
DOI forward links to this article:
[1] Wojciech P. Hunek, Pawe Majewski, Jaros aw Zygarlicki, ukasz Nagi, Dariusz Zmarz y, Roman Wiench, Pawe M otek and Piotr Warmuzek (2022), doi:10.3390/s22197271
2.Ola Alstad and Olav Egeland, “Elimination of Reflections in Laser Scanning Systems with Convolutional Neural Networks”, pp. 9-20
DOI forward links to this article:
[1] Jaime Marco-Rider, Andrej Cibicik and Olav Egeland (2022), doi:10.1109/JSEN.2022.3194258
3.Andreas Klausen, Hyunh van Khang and Kjell G. Robbersmyr, “RMS Based Health Indicators for Remaining Useful Lifetime Estimation of Bearings”, pp. 21-38
DOI forward links to this article:
[1] Hong Xiao, Ping Li, Hanlin Zeng, Tiancai Liang, Wenchao Jiang and Zhiming Zhao (2022), doi:10.1002/int.23008
[2] Weili Kong and Hai Li (2022), doi:10.1016/j.asoc.2022.109630
[3] Hai Li and Chaoqun Wang (2023), doi:10.1177/1748006X221147441
[4] Han-Bing Zhang, De-Jun Cheng, Kai-Li Zhou and Sheng-Wen Zhang (2023), doi:10.1016/j.knosys.2023.110391
[5] Cheng Peng, Yuanyuan Zhao, Changyun Li, Zhaohui Tang and Weihua Gui (2023), doi:10.3390/e25111539
[6] Jun Guo, Dapeng Li and Baigang Du (2023), doi:10.1016/j.asoc.2023.111071
[7] Yuxin Li, Jie Liu, Baonan Liu, Fengyuan Zhang, Xiaohui Yuan and Yongchuan Zhang (2024), doi:10.1088/1361-6501/ad1475
[8] Gang Bao, Ranran Zhau, Rui Xu and Yikai Liu (2023), doi:10.1109/NTCI60157.2023.10403696
[9] Dingliang Chen, Yi Chai, Yongfang Mao and Yi Qin (2024), doi:10.1016/j.aei.2024.102863
[10] Junyu Qi, Zhuyun Chen, Yannick Uhlmann and Gernot Schullerus (2025), doi:10.1109/TIM.2024.3497151