@inproceedings{nurgazina_distributed_2020, address = {Warwick, UK}, title = {Distributed ledger technology applications for improved traceability of food supply chains}, url = {https://warwick.ac.uk/fac/sci/wmg/news-and-events/events/wmgevents/euroma2020/proceedings/1936_exordo-euroma2020-version-1.pdf}, abstract = {Food provenance is critical for establishing consumer and stakeholder trust and overall company reputation and competitiveness. There are many benefits distributed ledger technologies can provide for improved food traceability, such as decreasing fraud,automating processes, providing reliable information of food origin and condition with sensor technologies, thereby ensuring product quality and safety. This paper provides a review of current best practices of distributed ledger technology (DLT) applications in the food domain addressing current challenges and gaps in research and implications for value adoption in food supply chains. The developed research framework provides an initial outlook on suggested DLT integration.}, language = {EN}, booktitle = {Proceedings of the 27th {EurOMA} {Conference}}, author = {Nurgazina, Jamilya and Felberbauer, Thomas and Moser, Thomas and Reiner, Gerald}, year = {2020}, note = {Projekt: DataVisBlock}, keywords = {Blockchain, Forschungsgruppe Digital Technologies, Institut für Creative Media Technologies, Vortrag, Wiss. Beitrag, best, peer-reviewed, ⛔ No DOI found}, pages = {532--541}, } @inproceedings{nurgazina_modeling_2022, address = {Innsbruck, Austria}, title = {Modeling food waste mitigation enabled by distributed ledger technologies}, abstract = {Distributed ledger technologies (DLTs), such as blockchain, can contribute towards achieving more sustainable, transparent, and resilient food supply chains (FSCs). There are social, environmental, and economic benefits for FSCs arising from the application of the DLTs. Specifically, various issues of food fraud, food security and safety, food quality, health and welfare, and economic development can be tackled and addressed. However, the aspects of measuring the effects, the performance metrics and the long-term sustainability benefits have not been widely investigated. In particular, empirical studies addressing the aspects of DLT effects on FSC waste reduction are currently scarce. This study applies system dynamics to investigate food waste mitigation effects in FSC processes, addressing the environmental sustainability effects on FSC performance in the long-term perspective. This paper contributes with a development of a model for food waste mitigation approaches enabled by the integration of DLTs in FSCs. The findings derived by the model based on primary and secondary-based empirical data include recommendations to managers and policy-makers how tackling food waste can subsequently contribute towards the achievement of sustainable development goals of the United Nations.}, language = {en}, author = {Nurgazina, Jamilya and Kazantsev, Nikolai and Moser, Thomas and Reiner, Gerald}, year = {2022}, note = {Projekt: DataVisBlock}, keywords = {Blockchain, Forschungsgruppe Digital Technologies, ICMT, Institut für Creative Media Technologies, Vortrag, Wiss. Beitrag, peer-reviewed, submitted, ⛔ No DOI found}, } @inproceedings{nurgazina_visualization_2022, address = {Hagenberg, Austria}, title = {Visualization and clustering for rolling forecast quality verification: {A} case study in the automotive industry}, volume = {200}, copyright = {CC BY-NC-ND}, url = {https://www.sciencedirect.com/science/article/pii/S1877050922003131}, doi = {https://doi.org/10.1016/j.procs.2022.01.304}, language = {en}, booktitle = {Procedia {Computer} {Science}}, publisher = {Elsevier B.V.}, author = {Nurgazina, Jamilya and Felberbauer, Thomas and Asprion, Bernward and Pinnamaraju, Pavan}, year = {2022}, note = {Project: InnoFIT}, keywords = {Center for Artificial Intelligence, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Data Intelligence, Institut für Creative Media Technologies, Institut für IT Sicherheitsforschung, SP IT Sec Applied Security \& Data Science, Vortrag, Wiss. Beitrag, best, peer-reviewed, ⛔ No DOI found}, pages = {1048--1057}, } @inproceedings{nurgazina_visualization_2019, address = {Fraunhofer IWU, Chemnitz, Germany}, title = {Visualization and {Analysis} of {Customer} {Provided} {Forecasts}}, isbn = {978-3-95735-114-2}, url = {http://www.asim-fachtagung-spl.de/asim2019/papers/43_Proof_121.pdf}, booktitle = {Simulation in {Produktion} und {Logistik} 2019}, publisher = {Verlag Wissenschaftliche Scripten}, author = {Nurgazina, Jamilya and Felberbauer, Thomas and Altendorfer, Klaus and Zeiml, Sarah}, editor = {Putz, Matthias and Schlegel, Andreas}, year = {2019}, note = {Projekt: InnoFIT}, keywords = {Data Science, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Digital Technologies, Institut für Creative Media Technologies, Smart Manufacturing, Vortrag, Wiss. Beitrag}, pages = {445--454}, } @article{nurgazina_distributed_2021, title = {Distributed {Ledger} {Technology} {Applications} in {Food} {Supply} {Chains}: {A} {Review} of {Challenges} and {Future} {Research} {Directions}}, volume = {13}, copyright = {Open Access}, url = {https://www.mdpi.com/2071-1050/13/8/4206}, doi = {https://doi.org/10.3390/su13084206}, language = {en}, number = {8}, journal = {Sustainability}, author = {Nurgazina, Jamilya and Pakdeetrakulwong, Udsanee and Moser, Thomas and Reiner, Gerald}, month = apr, year = {2021}, note = {Projekt: DataVisBlock}, keywords = {Blockchain, Forschungsgruppe Digital Technologies, Institut für Creative Media Technologies, Wiss. Beitrag, peer-reviewed}, pages = {4206}, } @inproceedings{zeiml_simulation_2019, address = {National Harbor, Maryland, USA}, title = {Simulation {Based} {Forecast} {Data} {Generation} and {Evaluation} of {Forecast} {Error} {Measures}}, url = {http://meetings2.informs.org/wordpress/wsc2019/files/2019/12/WSC-2019-Final-Program_Full-Book.pdf}, doi = {10/gh377n}, abstract = {Production planning is usually performed based on customer orders or demand forecasts. The demand forecasts in production systems can either be generated by manufacturing companies themselves, i.e. forecast prediction, or they can be provided by customers. For both alternatives, forecast prediction, as well as the customer-provided forecasts, the quality of those forecasts is critical for success. In this paper, a simulation model to generate forecast data that mimic different forecast behaviors is presented. In detail, an independent forecast distribution and a forecast evolution model are investigated to discuss the value of customer-provided forecasts in comparison to the simple moving average forecast prediction method. Main findings of the paper are that Root-Mean-Square-Error and Mean-Absolute-Percentage-Error describe the forecast error well if no systematic effects are present and Mean-Percentage-Error provides a good measure for systematic effects. Furthermore, systematic effects like overbooking are significantly reducing the value of customer-provided forecast information.}, booktitle = {Proceedings of the 2019 {Winter} {Simulation} {Conference}}, author = {Zeiml, Sarah and Altendorfer, Klaus and Felberbauer, Thomas and Nurgazina, Jamilya}, year = {2019}, note = {Projekt: InnoFIT}, keywords = {Data Science, Forschungsgruppe Digital Technologies, Institut für Creative Media Technologies, Smart Manufacturing, Vortrag, Wiss. Beitrag, peer-reviewed}, } @inproceedings{jandl_sensitrack_2019, address = {Zaragossa,Spain}, title = {{SensiTrack} - {A} {Privacy} by {Design} {Concept} for industrial {IoT} {Applications}}, abstract = {In the course of further digitization of industrial manufacturing, companies are using tracking systems to monitor their production processes. This creates a large amount of data with location references, having an influence on the employees privacy – especially if personal references to employees are possible. To investigate this topic, a use case was carried out in an industrial environment. Therefore, a self-developed asset tracking (AT) system was developed and compared with a Commercialof- the-shelf (COTS) AT-System with regard to functionality and employee privacy. One mayor finding was that the Bluetooth Low Energy (BLE) based legacy system has weaknesses with regard to privacy, e.g. the advertising-data of mobile devices of the employees were stored in the cloud application of the system provider. This data can be used to determine the position of employees. With the self-developed system these weaknesses were avoided by using a Privacy by Design (PbD) approach. Therefore, this paper focuses on employee privacy in industrial AT applications and provides a PbD concept for wireless sensor networks in industrial environments.}, publisher = {IEEE Xplore}, author = {Jandl, Christian and Nurgazina, Jamilya and Schöffer, Lucas and Reichl, Christian and Wagner, Markus and Moser, Thomas}, month = sep, year = {2019}, note = {Projekt: SensiTrack}, keywords = {Forschungsgruppe Digital Technologies, Institut für Creative Media Technologies, Smart Manufacturing, Vortrag, Wiss. Beitrag, peer-reviewed}, }