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24 pages, 1018 KB

Open AccessArticle

Analysis and Synthesis of Theoretical and Practical Implications of Case Management Model and Notation

by Mateja Bule and Gregor Polančič

Information 2025, 16(4), 310; https://doi.org/10.3390/info16040310 - 14 Apr 2025

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Case Management Model and Notation (CMMN) is a graphical notation used to model less predictable, highly flexible processes that may behave differently in each instance. It uses an event-centred approach and expands on what can be modelled with procedural modelling notations. Nearly a decade since the occurrence of CMMN, its practical use is questionable. We performed this research to identify possible reasons for this and to classify the potential advantages and disadvantages of CMMN. With the aforementioned objectives, we conducted a systematic literature review, which provided a broad insight into the state of the investigated object along with techniques for analysing qualitative data, coding, and successive approximation. From an initial set of 942 articles, 43 remain relevant. The results of the analysis and synthesis of the obtained data from relevant articles were generalised codes, which were used to explicitly answer the research questions. The results indicate that CMMN has good foundations in the declarative modelling approach and within the Case Management paradigm. Nevertheless, some issues were identified with the notation and elements of CMMN and with its complement—Business Process Model and Notation (BPMN). Full article

(This article belongs to the Section Information Applications)

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20 pages, 17221 KB

Open AccessArticle

Big Data-Driven 3D Visualization Analysis System for Promoting Regional-Scale Digital Geological Exploration

by Yiping Tian, Jiongqi Wu, Genshen Chen, Gang Liu and Xialin Zhang

Appl. Sci. 2025, 15(7), 4003; https://doi.org/10.3390/app15074003 - 4 Apr 2025

Viewed by 975

Abstract

As geological exploration technology advances, geoscience relies on digitization and intelligence to address challenges such as data fragmentation, multi-source heterogeneity, and visual analysis. This study develops a big data-driven 3D visual analysis system for regional-scale applications. The system integrates three core technological components: (1) a heterogeneous cloud resource scheduling method employing an optimized CMMN algorithm with unified cloud API standardization to enhance task distribution efficiency; (2) a block model-based dynamic data aggregation approach utilizing semantic unification and attribute mapping for multi-source geological data integration; (3) a GPU-accelerated rendering framework implementing occlusion culling and batch processing to optimize 3D visualization performance. Experimental validation shows the improved CMMN algorithm reduces cloud task completion time by 2.37% while increasing resource utilization by 0.652% compared with conventional methods. The dynamic data model integrates 12 geological data types across eight categories through semantic mapping. Rendering optimizations achieve a 93.7% memory reduction and 60.6% faster visualization compared with baseline approaches. This system provides robust decision support and reliable tools for the digital transformation of geoscience work. Full article

(This article belongs to the Special Issue Technologies and Methods for Exploitation of Geological Resources)

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12 pages, 2250 KB

Open AccessArticle

Adaptive Stochastic Filtration Based on the Estimation of the Covariance Matrix of Measurement Noises Using Irregular Accurate Observations

by Sergey Sokolov, Arthur Novikov and Marianna Polyakova

Inventions 2021, 6(1), 10; https://doi.org/10.3390/inventions6010010 - 21 Jan 2021

Cited by 4 | Viewed by 2362

Abstract

In measurement systems operating under various disturbances the probabilistic characteristics of measurement noises are usually known approximately. To improve the observation accuracy, a new approach to the Kalman’s filter adaptation is proposed. In this approach, the Covariance Matrix of Measurement Noises (CMMN) is estimated by accurate measurements detected irregularly by the mobile object observation system (from radiofrequency identifiers, etalon reference, fixed points etc.). The problem of adaptive estimation of the observer’s noises covariance matrix in the Kalman filter is solved analytically for two cases: mutual noises correlation, and its absence. The numerical example for adaptive filtration of complexing navigation system parameters of a mobile object using irregular accurate measurements is given to illustrate the effectiveness of the proposed algorithm. Coordinate estimating errors have changed in comparison with the traditional scheme from 100 m to 2 m in latitude, and from 200 m to 1.5 m in longitude. Full article

(This article belongs to the Special Issue Intelligent Control Theory and Applications)

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16 pages, 2307 KB

Open AccessArticle

Process Discovery in Business Process Management Optimization

by Paweł Dymora, Maciej Koryl and Mirosław Mazurek

Information 2019, 10(9), 270; https://doi.org/10.3390/info10090270 - 29 Aug 2019

Cited by 10 | Viewed by 6206

Abstract

Appropriate business processes management (BPM) within an organization can help attain organizational goals. It is particularly important to effectively manage the lifecycle of these processes for organizational effectiveness in improving ever-growing performance and competitivity-building across the company. This paper presents a process discovery and how we can use it in a broader framework supporting self-organization in BPM. Process discovery is intrinsically associated with the process lifecycle. We have made a pre-evaluation of the usefulness of our facts using a generated log file. We also compared visualizations of the outcomes of our approach with different cases and showed performance characteristics of the cash loan sales process. Full article

(This article belongs to the Section Information Systems)

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