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2 2024

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Optimizing Public Service Delivery Through Automated Stakeholder Interaction: Low-code BPM Implementation

Oleś-Filiks Małgorzata, Waszkowski Robert

Decision Making in Manufacturing and Services

2024

Special Issue: Business Process Management

83--93

For years, public institutions have been characterized by a complex and specific structure that requires the applications of bureaucratic procedures that are in accordance with the law and the professional preparations of officials. Nowadays, public institutions have high requirements for implementing intelligent IT systems, which allow the handling of documents in electronic form and the automatic flow of the information that is contained in them. This article presents a set of business processes that have been implemented in a public institution (dealing with the implementation of tasks in agricultural and food markets) that was performed in the BPMN notation. In addition to a description of the system, the article presents the positive impact of the implementation on the work of the authority. The article presents how business-process modeling and simulation support an enterprise in creating an integrated information-processing system. It concludes with a presentation of the effects and changes that have occurred in the authority following the implementation of a business-process-management system.

Computational system for evaluating human perception in video steganography

Pery Marcin, Waszkowski Robert

Applied Computer Science

2024

Vol. 20, no. 4

63--76

This paper presents a comprehensive computational system designed to evaluate the undetectability of video steganography from human perspective. The system assesses the perceptibility of steganographic modifications to the human eye while simultaneously determining the minimum encoding level required for successful automated decoding of hidden messages. The proposed architecture comprises four subsystems: steganogram database preparation, human evaluation, automated decoding, and comparative analysis. The system was tested using example steganographic techniques applied to a dataset of video files. Experimental results revealed the thresholds of human-level undetectability and automated decoding for each technique, enabling the identification of critical differences between human and algorithmic detection capabilities. This research contributes to the field of steganography by offering a novel framework for evaluating the trade-offs between human perception and automated decoding in video-based information hiding. The system serves as a tool for advancing the development of more secure and reliable video steganographic techniques.