Publikationen

2024

  • M. Jelali: Deep learning networks-based tomato disease and pest detection: A first review of research studies using real field datasets. Frontiers Plant Science 2024, 15, 1493322. (Peer-reviewed/Open Access) DOI: 10.3389/fpls.2024.1493322
  • R. Rosenthal, S. Koldorf, E. Shvydkii, N. Albersmann, L. Al-Shrouf, M. Jelali: Improving Steel Quality in Continuous Casting: A Novel Machine Learning-based Framework for Guide Roll Alignment Control and Quality Prediction. 11th European Continuous Casting Conference (ECCC), October 7–11, 2024, Essen, Germany
  • F. Schneider, J. W. Swiatek, M. Jelali: Detection of Growth Stages of Chilli Plants in a Hydroponic Grower Using Machine Vision and YOLOv8 Deep Learning Algorithms. Sustainability 2024, 16, 6424. (Peer-reviewed/Open Access)  DOI: 10.3390/su16156420
  • M. Jelali, K. Papadopoulos: Inline Inspection of Packaged Food Using Microwave/Terahertz Sensing—An Overview With Focus on Confectionery Products. Processes 2024, 12(4), 712. (Peer-reviewed/Open Access) DOI: 10.3390/pr12040712
  • R. Rosenthal, F. Gerz, L. Al-Shrouf, M. Jelali: Innovative machine learning based approach for reliable and accurate measurement of guide roll alignment in continuous casting plants. Proceedings of the 11th European Workshop on Structural Health Monitoring (EWSHM 2024), June 10-13, 2024, Potsdam, Germany (EWSHM 2024). (Peer-reviewed) DOI: 10.58286/2978
  • M. Ateeq, R. Feuser, H. Ratjen, F. Ziegler, L. Al-Shrouf, M. Jelali: Mathematical Modeling of Thermal Behavior of PCBs in a Modular Magazine Convection Oven. Automation, Robotics & Communications for Industry 4.0/5.0 (ARCI‘ 2024): 4th IFSA Winter Conference, February 7–9, 2024, Innsbruck, Austria, pp. 189–194. (Peer-reviewed) DOI: 10.13140/RG.2.2.20923.18722

2023

  • K. Papadopoulos, M. Jelali: A Comparative Study on Recent Progress of Machine Learning-based Human Activity Recognition with Radar. Applied Sciences 2023, 13(23), 12728. (Peer-reviewed/Open Access) DOI: 10.3390/app132312728 
  • M. Jelali, L. Al-Shrouf: Urban-, Vertical- oder Indoor Farming. Impulsvortrag beim Parlamentarischen Frühstück (KI und Nachhaltigkeit) im NRW-Landtag, 13. Dezember 2023. https://www.hn-nrw.de/aktivitaeten/veranstaltungen/

  • M. Jelali: Stand und Zukunft des industriellen Vertical Indoor Farming. Vortrag, Workshop „KI revolutioniert die Landwirtschaft!“ des Mittelstand-Digital Zentrum Rheinland in Kooperation mit dem Rheinischen LandFrauenverband e.V. und dem Mittelstand-Digital Zentrum Lingen.Münster.Osnabrück, 24. November 2023, TH Köln

  • M. Jelali: Einführung in Indoor Vertical Farming. Vortrag, Workshop „KI revolutioniert die Landwirtschaft!“ des Mittelstand-Digital Zentrum Rheinland in Kooperation mit dem Rheinischen LandFrauenverband e.V. und dem Mittelstand-Digital Zentrum Lingen.Münster.Osnabrück, 24. November 2023, TH Köln

  • F. Gerz, M. Jelali, F. Kuthe: Neuartiges Lehrkonzept für Machine Learning mit Industrial IoT-Plattfom. Teaching & learning draft – Entwurfsmuster, TURN Conference, 13.–15. September 2023, TH Köln. (Peer-reviewed)
  • F. Gerz, L. Al-Shrouf, M. Jelali: A comparative analysis of concept drift detection methods with a systematic and innovative approach of method selection. 14th International Workshop on Structural Health Monitoring (IWSHM), Stanford University, CA, USA, September 12–14, 2023. (Peer-reviewed) [Online]. Available:
    https://iwshm2023.stanford.edu/proceedings
  • H. Al Joumaa, L. Al-Shrouf, M. Jelali: Novel approach for imaging time series for the improvement of classification results „Grayscale Fingerprint Features Field Imaging (G3FI)”. 14th International Workshop on Structural Health Monitoring (IWSHM), Stanford University, CA, USA, September 12–14, 2023. (Peer-reviewed) [Online]. Available: https://iwshm2023.stanford.edu/proceedings
  • M. Ateeq, R. Feuser, L. Al-Shrouf, M. Jelali: Review of various curing processes and techniques of Printed Circuit Board (PCB) and introduction of new innovative thermal curing technique. 14th International Workshop on Structural Health Monitoring (IWSHM), Stanford University, CA, USA, September 12–14, 2023. (Peer-reviewed) [Online]. Available: https://iwshm2023.stanford.edu/proceedings
  • J. W. Swiatek, F. Kuthe, L. Al-Shrouf, M. Jelali: Development of a hydroponics simulator to generate guidelines for data collection in hydroponics for machine learning applications. Agriculture & Food – 11th International Conference, Burgas, Bulgaria, August 14–17, 2023. [Online]. Available: https://www.scientificpublications.net/en/article/1002676/
  • L. Al-Shrouf, J. A. Krauland, F. Schneider, J. T. Wonneberger, M. Mushoff, J. W. Swiatek, M. Jelali: Analysis of environmental and growing conditions for maximum yield of chickpeas cultivation in vertical hydroponic systems. Agriculture & Food – 11th International Conference, Burgas, Bulgaria, August 14–17, 2023. [Online]. Available: https://www.scientific-publications.net/en/article/1002658/

2022

  • Weber, J. Denker, M. Jelali: A learning procedure for detection of process anomalies in the production of metallic long products and a new industrial case study. 1st IFAC Workshop on Control of Complex Systems (COSY 2022), Bologna, Italy, November 24–25, 2022. (Peer-reviewed) DOI: 10.1016/j.ifacol.2023.01.093

  • F. Gerz; T. R. Bastürk, J. Kirchhoff, J. Denker, L. Al-Shrouf, M. Jelali: A comparative study and a new industrial platform for decentralized anomaly detection using machine learning algorithms. IEEE World Congress on Computational Intelligence (WCCI) / International Joint Conference on Neural Networks (IJNN), Padua, Italy, 18–23 Juli, 2022. (Peer-reviewed) DOI: 10.1109/IJCNN55064.2022.9892939
  • J. Denker; V. Iannino, C. Laudenberg, A. Tenner, M. Daun, M. Jelali: Improved temperature monitoring and control of production lines in casting through BaSyx framework and edge intelligence. IEEE World Congress on Computational Intelligence (WCCI) / International Joint Conference on Neural Networks (IJNN), Padua, Italy, 18–23 Juli, 2022. (Peer-reviewed) DOI: 10.1109/IJCNN55064.2022.9891962
  • L. Al-Shrouf, M. Jelali, J. Denker, B. Baumann, K. Wachsmann: Revolutionäre Messtechnik für extreme Betriebsbedingungen – Hochpräzise Radarsensoren und Radarmesssysteme für Warmbandwalzwerke. Stahl + Technik 2022, 4:28–33
  • M. Jelali, L. Al-Shrouf, D. Zander: Revolutionäre Messtechnik für extreme Betriebsbedingungen – Neue Radarmesssysteme zur Materialdetektion und Breitenmessung in Warmwalzwerken. Stahl + Technik 2022, 1/2:38–41
  • M.-L. Chung, M. Widdel, J. Kirchhoff, J. Sellin, M. Jelali, F. Geiser, M. Mücke, R. Conrad: Risk factors for pressure ulcers in adult patients: A meta-analysis on sociodemographic factors and the Braden scale. Journal of Clinical Nursing, Feb 2022. (Peer-reviewed/Open Access) DOI: 10.1111/jocn.16260 
  • M.-L. Chung, M. Widdel, J. Kirchhoff, J. Sellin, M. Jelali, F. Geiser, M. Mücke, R. Conrad: Risk factors for pressure ulcers in adult patients: A narrative synthesis. International Journal of Environmental Research and Public Health 2022, 19(2), 761. (Peer-reviewed/Open Access) DOI: 10.3390/ijerph19020761

2010–2017

  • A. Bathelt, D. Söffker, M. Jelali (2017): An approach to recursive subspace identification. IEEE Conference on Decision and Control, 12–15 Dec., Melbourne, Australia. (Peer-reviewed)

  • M. Bauer, A. Horch, L. Xie, M. Jelali, Thornhill N. (2016): The current state of control loop performance monitoring – A survey of application in industry. Journal of Process Control 38:1–10. (Peer-reviewed) DOI: 10.1016/j.jprocont.2015.11.002

  • M. Jelali, D. Zander, D. Nüßler (2016): Inlinemessung mit Radartechnik – eine neue Revolution in der Prozessautomation?. Stahl und Eisen 136(1):60–68

  • S. Zareba, A. Wolff, M. Jelali (2016): Mathematical modelling and parameter identification of a stainless steel annealing furnace. Simulation Modelling Practice and Theory 60:15–39. (Peer-reviewed) DOI: 10.1016/j.simpat.2015.09.008

  • A. Rother, M. Jelali, D. Söffker (2015): A brief review and a first application of time-frequency-based analysis methods with application to strip rolling mills. Journal of Process Control 35:65–79. (Peer-reviewed) DOI: 10.1016/j.jprocont.2015.08.010

  • A. Bathelt, D. Söffker, M. Jelali (2015): A combined algorithm of the subspace identification methods ORT and CCA. IEEE Conference on Decision and Control, 15–18 Dec., Osaka, Japan. (Peer-reviewed) DOI: 10.1109/CDC.2017.8264344

  • T. Friebel, K. Zabet, R. Haber, M. Jelali (2015): Predictive functional control of tandem cold metal rolling. Proc. IEEE Multi-Conference on Systems and Control (MSC), 21–23 Sept., Sydney, Australia. (Peer-reviewed) DOI: 10.1109/CCA.2015.7320649

  • A. Bathelt, N. L. Ricker, M. Jelali (2015): Revision of the Tennessee Eastman process model. International Symposium on Advanced Control of Chemical Processes (ADCHEM), 7–10 June, Whistler, Canada. (Peer-reviewed) DOI: 10.1016/j.ifacol.2015.08.199

  • A. Rother, M. Jelali, D. Söffker (2015): Signal-based fault prognosis approach applied to industrial data. IWSHM 10th International Workshop on Structural Health Monitoring, 1–3 Sept., Stanford, USA. (Peer-reviewed)

  • C. Bartholdt, F. Kopin, M. Jelali (2015): Modellbasierte Auslegung und Optimierung von Kaltwalzwerken. Walzen von Flachprodukten, Bauer G., Schadt W. (Eds.), Springer-Verlag

  • C. Bartholdt, F. Kopin, M. Jelali (2014): Universelles Planheitsmodell zur Prozessoptimierung in Kaltwalzwerken. Stahl und Eisen 134(11):182–188

  • A. Bathelt, M. Jelali (2014): Comparative study of subspace identification methods on the Tennessee Eastman process under disturbance effects. Proc. International Symposium on Advanced Control of Industrial Processes (ADCONIP), 28–30 May, Hiroshima, Japan. (Peer-reviewed)

  • S. Zareba, S. Lakshminarayana, M. Jelali (2014): A new controller tuning method based on the relative damping index. Proc. International Symposium on Advanced Control of Industrial Processes (ADCONIP), 28–30 May, Hiroshima, Japan. (Peer-reviewed)

  • A. Rother, M. Jelali, D. Söffker (2014): Development of a fault detection approach based on SVM applied to industrial data. Proc. Le Cam, Vincent and Mevel, Laurent and Schoefs, Franck. EWSHM – European Workshop on Structural Health Monitoring, 8–11 July, Nantes, France. (Peer-reviewed)

  • S. Zareba S., M. Chemnitz, A. Vollmer, M. Jelali (2014): Fehlerdiagnose von hydraulischen Stellantrieben in Walzanlagen mittels eines Unscented Kalman-Filters. Aachener Kolloquium für Instandhaltung, Diagnose und Anlagenüberwachung (AKIDA), 19–20 Nov., Aachen, Germany

  • A. Rother, M. Jelali, D. Söffker (2014): Entwicklung eines Verfahrens zur Fehlerdiagnose mittels Support Vector Machine auf Basis von gemessenen Betriebsdaten. Aachener Kolloquium für Instandhaltung, Diagnose und Anlagenüberwachung (AKIDA), 19–20 Nov., Aachen, Germany

  • C. Pinno, H. Krambeer, M. Jelali, W. Klos (2014): Analyse und Optimierung der Warmwalzstufe an einer Bandgießanlage bzgl. Bandplanheit. XXXIII. Verformungskundliches Kolloquium, 15–18.03., Montanuniversität Leoben, Austria

  • M. Jelali, R. Dittmar (2014): Control Performance Monitoring (CPM). Handbuch der Prozessautomatisierung – Prozessleittechnik für verfahrenstechnische Anlagen, Früh K.F., Maier U., Schaufel D. (Eds.), Chapter 3.5, Vulkan Verlag

  • L. Al-Shrouf, J. Gedenk, M. Jelali, D. Söffker (2013): Modular signal-based condition monitoring of a hydraulic servo-system. Proc. International Workshop on Structural Health Monitoring (IWSHM), Stanford, CA, USA, 10–12 Sept. (Peer-reviewed)

  • J. Gedenk, S. Zareba, M. Jelali (2013): Condition monitoring for hydraulic systems in rolling mills using unscented Kalman filter. Proc. International Workshop on Structural Health Monitoring (IWSHM), 10–12 Sept., Stanford, CA, USA. (Peer-reviewed)

  • M. Jelali (2013): Control Performance Management in Industrial Automation: Assessment, Diagnosis and Improvement of Control Loop Performance. Springer-Verlag, London

  • J. Polzer, M. Jelali (2011): Mehrgrößenregelung mit Entkopplung von Banddicke und Bandplanheit in 20-Rollen-Kaltwalzwerken. at–Automatisierungstechnik 59:730–737. (Peer-reviewed)

  • M. Jelali, S. Karra (2010): Automatische Diagnose oszillierender Regelkreise in komplexen industriellen Anlagen. at–Automatisierungstechnik 57:206–216. (Peer-reviewed)

  • S. Karra, M. Jelali, M. N. Karim, A. Horch (2010): Detection of Oscillating Control Loops. Detection and Diagnosis of Stiction in Control Loops: State of the Art and Advanced Methods, Jelali M., Huang B. (Eds.), Chapter 4, Springer-Verlag, London

  • M. Jelali (2010): Estimation of Valve Stiction Using Separable Least-squares and Global Search Algorithms. Detection and Diagnosis of Stiction in Control Loops: State of the Art and Advanced Methods, Jelali M., Huang B. (Eds.), Chapter 10, Springer-Verlag, London

  • M. Jelali, C. Scali (2010): Comparative Study of Valve-stiction-detection Methods. Detection and Diagnosis of Stiction in Control Loops: State of the Art and Advanced Methods, Jelali M., Huang B. (Eds.), Chapter 13, Springer-Verlag, London

  • M. Jelali, B. Huang (Eds.) (2010): Detection and Diagnosis of Stiction in Control Loops: State of the Art and Advanced Methods. Springer-Verlag, London