BPMN-Sim: A multilevel structural similarity technique for BPMN process models

Garcia, Marcia Tavares; Nunes, Marina Macedo; Fantinato, Marcelo; Peres, Sarajane Marques; Thom, Lucinéia Heloisa

doi:10.1016/j.is.2023.102211

Cited by 3 publications

(1 citation statement)

References 44 publications

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“…However, these techniques have focused on processes that are not automated. The most commonly used sources for analysis are process logs, natural language content, graph structures, Petri Nets, and BPMN notation [11,31]. None of these methods are primarily intended for the RPA area.…”

Section: Introductionmentioning

confidence: 99%

Towards Discovering Erratic Behavior in Robotic Process Automation with Statistical Process Control

Průcha

2023

SSRN Journal

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Section: Introductionmentioning

confidence: 99%

Towards Discovering Erratic Behavior in Robotic Process Automation with Statistical Process Control

Průcha

2023

SSRN Journal

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SiDiTeR: Similarity Discovering Techniques for Robotic Process Automation

Průcha,

Madzík

2023

Lecture Notes in Business Information Processing

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A Novel Standardized Collaborative Online Model for Processing and Analyzing Remotely Sensed Images in Geographic Problems

Zhang,

Wu,

Zhang

et al. 2023

Electronics

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In recent years, remote sensing image processing technology has developed rapidly, and the variety of remote sensing images has increased. Solving a geographic problem often requires multiple remote sensing images to be used together. For an image processing analyst, it is difficult to become proficient in the image processing of multiple types of remote sensing images. Therefore, it is necessary to have multiple image processing analysts collaborate to solve geographic problems. However, as a result of the naturally large volumes of data and the computer resources they consume for analysis, remote sensing images present a barrier in the collaboration of multidisciplinary remote sensing undertakings and analysts. As a result, during the development of the collaborative analysis process, it is necessary to achieve the online processing and analysis of remote sensing images, as well as to standardize the online remote sensing image collaborative analysis process. To address the above issues, a hierarchical collaborative online processing and analysis framework was developed in this paper. This framework defined a clear collaborative analysis structure, and it identifies what kinds of online image processing and analysis activities participants can engage in to successfully conduct collaborative processes. In addition, a collaborative process construction model and an online remote sensing image processing analysis model were developed to assist participants in creating a standard collaborative online image processing and analysis process. In order to demonstrate the feasibility and effectiveness of the framework and model, this paper developed a collaborative online post-disaster assessment process that utilizes radar images and optical remote sensing images for a real forest fire event. This process was based on the BPMN2.0 and OGC dual standards. Based on the results, the proposed framework provides a hierarchical collaborative remote sensing image processing and analysis process with well-defined stages and activities to guide the participants’ mutual collaboration. Additionally, the proposed model can help participants to develop a standardized collaborative online image processing process in terms of process structure and information interactions.

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BPMN-Sim: A multilevel structural similarity technique for BPMN process models

Cited by 3 publications

References 44 publications

Towards Discovering Erratic Behavior in Robotic Process Automation with Statistical Process Control

Towards Discovering Erratic Behavior in Robotic Process Automation with Statistical Process Control

SiDiTeR: Similarity Discovering Techniques for Robotic Process Automation

A Novel Standardized Collaborative Online Model for Processing and Analyzing Remotely Sensed Images in Geographic Problems

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