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14 Papers

An Automated and Intelligent Interface Embracing Process Awareness into User Workspace

Topic: Business Process Management (Modeling, Enactment and Execution)

Authors: Minh Nguyen ¹ , Hanh Tran ^{1

;

2} , Ileana Ober ¹ and Razan Abualsaud ¹

Affiliations: ¹ Institut de Recherche en Informatique de Toulouse (IRIT), Toulouse, France , ² Military Academy of Saint-Cyr Coëtquidan (AMSCC), CReC Saint-Cyr, France

Digital Object Identifier: 10.5220/0013370200003896

Proceedings of MODELSWARD 2025, ISBN: 978-989-758-729-0

Quick Abstract

This paper presents an AI-augmented framework for automated and intelligent process monitoring, addressing the inefficiencies of manual progress reporting in Process Management Systems (PMS), which leads to potential inaccuracies and consumes valuable user time. Our research proposes a novel solution that bridges users’ workspaces and PMS, enabling automatic progress reporting based on users’ actions within their preferred tools. The core innovation of our framework pMage lies in employing Artificial Intelligence (AI) techniques to analyze and interpret sequences of user actions, translating them into accurate task progress updates, which significantly reduce manual input and enhance the accuracy of the reporting, thus making the integration of a PMS smoother and more effective. We demonstrate our framework’s applicability through a case study that uses pMage to monitor a brake system manufacturing process with our prototype. As a smart interface, pMage provides a no-code solution to connect a wide range of user applications to various PMS via their respective APIs. This versatility ensures broad applicability across different organizational contexts and toolsets. Our AI-augmented framework offers a more reliable, efficient, and user-friendly approach than existing monitoring methods.

Toward a Goal-Oriented Methodology for Artifact-Centric Process Modeling

Topic: Business Process Management and Engineering

Authors: Razan Abualsaud , Hanh Tran , Ileana Ober and Minh Khoi Nguyen

Affiliation: Institut de Recherche en Informatique de Toulouse, Toulouse, France

Digital Object Identifier: 10.5220/0011989900003464

Proceedings of ENASE 2023, ISBN: 978-989-758-647-7

Quick Abstract

Process management systems aim to enable a flexible yet systematic control of the execution of a process on the basis of its model. Therefore, a process model should encompass all necessary information for achieving the monitoring goals on the operational process. Up to this time, the research in process modeling has tended to focus on developing process modeling languages to represent process models. However, it lacks concrete guidelines for modelers to systematically define such models with the adequate details to enable an effective control of process execution. In this study, we address this lack by proposing a goal-oriented methodology for systematically modeling processes. Our methodology is dedicated to Artifact-Centric Process Modeling (ACPM). ACPM is an emerging approach that combines both data and process in a holistic manner, thus it’s more suitable to model complex unstructured processes. We illustrate the proposed methodology by applying it practically to model a portion of the Rational Unified Process (RUP) with the intention of enhancing traceability at execution time.

Process Mining to Discover the Global Process from its Fragments’ Executions

Topic: Business Process Management and Engineering

Authors: Minh Khoi Nguyen , Hanh Nhi Tran and Ileana Ober

Affiliation: Institut de Recherche en Informatique de Toulouse, Toulouse, France

Digital Object Identifier: 10.5220/0011044800003176

Proceedings of ENASE 2022, ISBN: 978-989-758-568-5

Quick Abstract

Process analysis to improve performance and detect anomalies is important for process management. However, such an analysis requires a global process model that is sometimes hard to get, especially for complex processes involving various teams. This is also an obstacle for BAPE (Bottom-up Artifact-centric Process Environment), an artifact-centric process management environment that allows splitting a process into several fragments which are separately modeled and enacted by different actors. Thus, the knowledge about the whole process is distributed over the involved teams and an overview on the complete process is missing. This paper presents the integration of process mining into BAPE in order to construct the overall process model from the execution data of process fragments.

Integrating Shared Information into the Sensorial Mapping of Connected and Autonomous Vehicles

Topics: Multi-Agent Systems; Cooperation and Coordination; Autonomous Systems; Simulation

Authors: Filipo Studzinski Perotto , Stephanie Combettes , Valerie Camps , Elsy Kaddoum , Guilhem Marcillaud , Pierre Glize and Marie-Pierre Gleizes

Affiliation: IRIT, University of Toulouse, France

Digital Object Identifier: 10.5220/0010387604540461

Proceedings of ICAART 2021, ISBN: 978-989-758-484-8

Quick Abstract

A connected and autonomous vehicle (CAV) needs to dynamically maintain a map of its environment. Even if the self-positioning and relative localization of static objects (roads, signs, poles, guard-rails, buildings, etc.) can be done with great precision thanks to the help of hd-maps, the detection of the dynamic objects on the scene (other vehicles, bicycles, pedestrians, animals, casual objects, etc.) must be made by the CAV itself based on the interpretation of its low-level sensors (radars, lidars, cameras, etc.). In addition to the need of representing those moving objects around it, the CAV (seen as an agent immersed in that traffic environment) must identify them and understand their behavior in order to anticipate their expected trajectories. The accuracy and completeness of this real-time map, necessary for safely planning its own maneuvers, can be improved by incorporating the information transmitted by other vehicles or entities within the surrounding neighborhood through V2X communications. The implementation of this cooperative perception can be seen as the last phase of perception fusion, after the in-vehicle signals (coming from its diverse sensors) have already been combined. In this position paper, we approach the problem of creating a coherent map of objects by selecting relevant information sent by the neighbor agents. This task requires correctly identifying the position of other communicant agents, based both on the own sensory perception and on the received information, and then correcting and completing the map of perceived objects with the communicated ones. For doing so, the precision and confidence on each information must be taken into account, as well as the trust and latency associated with each source. The broad objective is to model and simulate a fleet of vehicles with different levels of autonomy and cooperation, based on a multi-agent architecture, in order to study and improve road safety, traffic efficiency, and passenger comfort. In the paper, the problem is stated, a brief survey of the state-of-the-art on related topics is given, and the sketch of a solution is proposed.

A Pattern-based Process Management System to Flexibly Execute Collaborative Tasks

Topics: Software Process Improvement; Model-Driven Engineering; Business Process Management and Engineering; Document and Workflow Management; Collaborative Software Engineering

Authors: Mamadou Lakhassane Cisse ¹ , Hanh Nhi Tran ² , Samba Diaw ³ , Bernard Coulette ⁴ and Alassane Bah ³

Affiliations: ¹ IRIT Laboratory, Jean Jaures University, Toulouse, France, UMMISCO, Cheikh Anta Diop University, Dakar and Senegal , ² IRIT Laboratory, Paul Sabatier University, Toulouse and France , ³ UMMISCO, Cheikh Anta Diop University, Dakar and Senegal , ⁴ IRIT Laboratory, Jean Jaures University, Toulouse and France

Digital Object Identifier: 10.5220/0007680702730280

Proceedings of ENASE 2019, ISBN: 978-989-758-375-9

Quick Abstract

Managing collaborations during the execution of a process is complex and challenging, especially for managing the collaboration inside a task having multiple instances performed by various actors. Existing process management approaches propose either a rigid control for conducting such collaborative tasks or no control at all. Aiming at a more flexible way to execute and control multi-instance tasks, we investigate a solution based on late-binding mechanism to allow actors choosing dynamically suitable strategies to perform their collaboration. First, we propose a process modeling language which focuses on describing multi-instance tasks and their dynamic instances at execution time. Second, this language is then used to represent patterns capturing reusable collaboration strategies. A prototype of a pattern-based Process Management System has been developed to demonstrate the possible flexible execution of collaborative tasks.

Related Ontology Subjects/Areas/Topics (6)

Cross-Feeding between Data and Software Engineering		Service-Oriented Software Engineering and Management		Software Engineering Methods and Techniques
Model-Driven Engineering		Software Engineering		Software Process Improvement

Cooperative Multi-agent Approach for Computational Systems of Systems Architecting

Topics: Multi-Agent Systems; Autonomous Systems; Collective Intelligence; Self Organizing Systems

Authors: Teddy Bouziat , Stéphanie Combettes , Valérie Camps and Jeremy Boes

Affiliation: Institut de Recherche en Informatiques de Toulouse, France

Digital Object Identifier: 10.5220/0006190101740181

Proceedings of ICAART 2017, ISBN: 978-989-758-219-6

Quick Abstract

This paper addresses the modeling and design of Systems of Systems (SoS). It presents and illustrates a new generic model to describe formally such systems. This model is used to propose a SoS architecting approach based on adaptive multi-agent systems. In this approach, each component system composing the SoS uses a local cooperative decision process in order to interact with other systems and to collectively give rise to a relevant overall function at the SoS level. The proposed model as well as the proposed approach are instantiated with a simulated unmanned aerial vehicle scenario and compared with another approach dealing with collaboration between systems in a SoS.

Related Ontology Subjects/Areas/Topics (13)

Agents	Distributed and Mobile Software Systems	Multi-Agent Systems
Artificial Intelligence	Enterprise Information Systems	Self Organizing Systems
Artificial Intelligence and Decision Support Systems	Knowledge Engineering and Ontology Development	Software Engineering
Autonomous Systems	Knowledge-Based Systems	Symbolic Systems
Collective Intelligence

Defining and using Collaboration Patterns for Software Process Development

Authors: Tan Thuan Vo , Bernard Coulette , Hanh Nhi Tran and Redouane Lbath

Affiliation: Institut de Recherche en Informatique de Toulouse, France

Digital Object Identifier: 10.5220/0005338705570564

Proceedings of CMDD 2015/MODELSWARD, ISBN: 978-989-758-083-3

Quick Abstract

Collaboration patterns are an efficient way to define, reuse and enact collaborative software development processes. We propose an approach to define and apply collaboration patterns at modelling, instantiation or execution time. Our patterns, inspired from workflow patterns, are described in CMSPEM, a Process Modelling Language developed in our team. In this paper, we briefly describe the CMSPEM metamodel and focus our presentation on two collaboration patterns: Duplicate in Sequence with Multiple Actors, Duplicate in Parallel with Multiple Actors and Merge. The approach is illustrated by a case study concerning the collaborative process “Review a deliverable”.

Using Process Ontology Together with Process Editor - To Facilitate Tool Integration

Authors: Chanh Duc Ngo ¹ , Hanh Nhi Tran ² and Joël Champeau ³

Affiliations: ¹ University of Science of HoChiMinh (HCMUS), Vietnam , ² Institut de Recherche en Informatique de Toulouse (IRIT), France , ³ Ecoles Nationales Supérieures de Techniques Avancées de Bretagne (ENSTA-Bretagne), France

Digital Object Identifier: 10.5220/0005429005650573

Proceedings of CMDD 2015/MODELSWARD, ISBN: 978-989-758-083-3

Quick Abstract

Modern software and system collaborative process involves various teams in different development phases thus need efficient solutions for tools integration. In Model-Driven Development, transformation technique is used to allow exchanging models created by different tools. However, in a process, transformation are often defined manually for a tool-incompatible point and rarely reusable. To facilitate the automatic generation of transformation rules for tool integration, we propose to use process ontology together with process editor when modelling process. The idea is using ontology to stock process assets from various sources so that the relations between similar elements in different technical spaces can be established automatically. The process editor enriches the ontology by process elements captured from modelling activities. Then the integrated ontology helps the editor detect tool integration points and complete the process model as well as generate the mappings between concerned process elements.

COMBINATION OF CORRELATION MEASURES FOR DENSE STEREO MATCHING

Topic: Matching Correspondence and Flow

Authors: Sylvie Chambon ¹ and Alain Crouzil ²

Affiliations: ¹ Institut Français des Sciences et Technologies des Transports and de l’Am´enagement et des Réseaux (IFSTTAR), France , ² Institut de Recherche en Informatique de Toulouse (IRIT), France

Digital Object Identifier: 10.5220/0003333305980603

Proceedings of VISAPP 2011/VISIGRAPP, ISBN: 978-989-8425-47-8

Quick Abstract

In the context of dense stereo matching of pixels, we study the combination of different correlation measures. Considering the previous work about correlation measures, we use some measures that are the most significant in five kinds of measures based on: cross-correlation, classic statistics, image derivatives, nonparametric statistics and robust statistics. More precisely, this study validates the possible improvement of stereo-matching by combining complementary correlation measures and it also highlights the two measures that can be combined in order to take advantage of the different methods: Gradient Correlation measure (GC) and Smooth Median Absolute Deviation measure (SMAD). Finally, we introduce an algorithm of fusion that allows to combine automatically correlation measures.

Related Ontology Subjects/Areas/Topics (3)

Computer Vision, Visualization and Computer Graphics

Matching Correspondence and Flow

Motion, Tracking and Stereo Vision

COMPLEMENTARITY OF FEATURE POINT DETECTORS

Topics: Feature Extraction; Stereo Vision and Structure from Motion

Authors: Guillaume Gales ¹ , Alain Crouzil ¹ and Sylvie Chambon ²

Affiliations: ¹ Univeristé P. Sabatier, France , ² Laboratoire Central des Ponts et Chaussées, France

Digital Object Identifier: 10.5220/0002831703340339

Proceedings of VISAPP 2010/VISIGRAPP, ISBN: 978-989-674-028-3

Quick Abstract

The goal of this paper is to provide a study on complementarity of feature point detectors. Many studies have been proposed on these detectors but none deals with complementarity in details. We introduce an evaluation of eleven well-known detectors based on new criteria used to characterize complementarity. The complementarity is computed with spatial distribution and contribution measures as well as repeatability and distribution gains of the association of two detectors.

Related Ontology Subjects/Areas/Topics (8)

Computer Vision, Visualization and Computer Graphics	Image and Video Analysis	Signal Processing, Sensors, Systems Modeling and Control
Feature Extraction	Informatics in Control, Automation and Robotics	Stereo Vision and Structure from Motion
Features Extraction	Motion, Tracking and Stereo Vision

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