IFIP Open Access Digital Library
Not a member yet
22614 research outputs found
Sort by
Coalgebraic Methods in Computer Science: 17th IFIP WG 1.3 International Workshop, CMCS 2024, Colocated with ETAPS 2024, Luxembourg City, Luxembourg, April 6–7, 2024
No full textInternational audienceBook Front Matter of LNCS 1461
Correspondence Between Composite Theories and Distributive Laws
No full textInternational audienceComposite theories are the algebraic equivalent of distributive laws. In this paper, we delve into the details of this correspondence and concretely show how to construct a composite theory from a distributive law and vice versa. Using term rewriting methods, we also describe when a minimal set of equations axiomatises the composite theory
A Categorical Approach to Coalgebraic Fixpoint Logic
No full textInternational audienceWe define a framework for incorporating alternation-free fixpoint logics into the dual-adjunction setup for coalgebraic modal logics. We achieve this by using order-enriched categories. We give a least-solution semantics as well as an initial algebra semantics, and prove they are equivalent. We also show how to place the alternation-free coalgebraic μ-calculus in this framework, as well as PDL and a logic with a probabilistic dynamic modality
Skills, Technical and Organizational Support Needed for Collaborative Networks 5.0
No full textPart 8: Collaborative Networks as Driver of Innovation in Organizations 5.0: ParticipationInternational audienceThe transition to Industry 5.0 has redefined the innovation requirements of organisations, emphasising sustainable, resilient and humancentred dimensions. The fifth industrial revolution also prioritises the co-creation of value within Collaborative Networks (CNs). By bringing together different socio-economic actors, organisations can leverage synergies to drive innovation and address complex global challenges more effectively. To operate efficiently within collaborative networks, a collaborative mindset, supported by specific technical and organisational resources, is essential. This study presents the findings of a European survey that investigated the innovation requirements of organizations transitioning towards Industry 5.0 and the resources necessary for collaborative 5.0 networks. The analysis showed that different regions and sectors have different needs, highlighting the necessity of tailoring approaches to each organisation's context. The results of the study emphasize the urgent requirement for multiple interventions to promote efficient collaboration and innovation in the transition to 5.0 organisations
Applications à la française de l'intelligence artificielle à la santé humaine dans un contexte européen
No full textInternational audienceIn this paper, we discuss the applications of artificial intelligence tohuman health and the problems this poses in France. We explore the field ofapplication of weak artificial intelligence to human health problems in relation toquestions of socio-economic development, law and ethics. We also look at issuesarising from strong Artificial Intelligence.We present a few examples of applicationsof weak artificial intelligence in various fields: predictive medicine, precisionmedicine, diagnostic and therapeutic assistance, supportive care, computerassistedsurgery, epidemic prevention and pharmacovigilance, and access to care.Within the European regulatory context of the single digital market and the personaldata protection regulation, we illustrate the societal issues surrounding theapplication of artificial intelligence.We conclude with the prospects for the developmentof artificial intelligence applications in human health in France within aEuropean context
The Practice of Enterprise Modeling: 16th IFIP Working Conference, PoEM 2023, Vienna, Austria, November 28 – December 1, 2023, Proceedings
No full textInternational audienceBook Front Matter of LNBIP 49
A New TRIZ-Based Approach to Design an Innovative Production System by Integrating Lean Tools and Functionalities
No full textPart 1: Sustainable and Industrial Design with TRIZInternational audienceThe aim of this article is to improve the performance of production systemsby integrating Lean tools and functionalities from the design phase, therebyreducing the need to apply them during the use phase of future manufacturingsystems. This implies a change of mindset; instead of reacting to problems asthey arise and then implementing Lean to remedy them, companies should proactivelyintegrate it from the design phase. However, trying to integrate several Leantools and functionalities into the design of a production system to satisfy multipleperformance criteria can generate contradictions. For this reason, we propose anew methodology: Lean Parameter IntegrationMatrix (LPIM), which can be usedto resolve the different types of problems. LPIM contains a set of generalizedLean parameters extracted from the Lean tools most used in companies. It allowsthe simultaneous identification of technical and physical contradictions that mayarise from the integration of multiple Lean tools and their functionalities, andprovides guidance for their resolution, using the principles of TRIZ methodologyfor resolving technical and physical contradictions
Contributions on the Interoperability of Sub-National Service Provision Through the Integration of Common Procedures
No full textPart 4: Customer Experience and Service Innovation with TRIZInternational audienceWhen public services are provided to organizations and citizens in the most efficient way possible, favorable conditions are created that lead to increased trust in government and the strengthening of e-government. Investing in and using the capacity to integrate the IT systems that underpin these services is key. In this article, we discuss the notion of shared processes in organizations through the prism of information technology and interoperability. The term ‘process integration’ refers to the process of redesigning a service by evaluating and optimizing the workflow, pre- and post-service, of each element of the service. In terms of information technology solutions, data is frequently modeled from a single perspective; it is therefore, not possible to exchange and reuse data across multiple applications and processes. Adopting an interoperability framework is necessary to achieve this. This framework will include both theoretical and practical proposals that address all levels of system interconnection, including legal, organizational, semantic, and technical systems. Interoperability refers to the ability of organizations to work together, to exchange information and knowledge, and to use information technologies in the context of the work processes they support when working together. Relevant models for achieving information exchange between information systems in the local and area service provision sector are examined, with a particular focus on the influence, coordination, and contribution of an organization managing local and area road infrastructure
The Impact of Artificial Intelligence in the Project Manager Role
No full textPart 4: Customer Experience and Service Innovation with TRIZInternational audienceThe integration of Artificial Intelligence (AI) into the comprehensive project management field is revolutionizing the landscape of nowadays organizations. This paper explores the transformative role of AI in reshaping the responsibilities and functions of project managers. With AI’s capabilities to automate tasks, enhance data analysis, and improve risk assessment, there is a significant shift in traditional project management practices that potentially offers limitless opportunities for organizational enhancement.This study specifically examines how AI is impacting project management across various dimensions including planning, execution, monitoring, and control. Utilizing both qualitative and quantitative data collected from a questionnaire distributed among professionals in different fields, the research analyzes the specific areas of project management that benefit most from AI technologies. The analysis aims to understand the practical impact of these technologies on project results and the evolution of the project manager role. The findings are expected to indicate a shift towards a more oversight-driven role where project managers are increasingly reliant on AI tools to handle operational tasks while they strategize and navigate complex project landscapes. This shift is reshaping the skill set required for successful project management, emphasizing the need for strong analytical skills and a deep understanding of AI capabilities and limitations. The empirical evidence gathered through this research will underscore the significant advantages that AI integration brings to project management across various industries. These include increased efficiency, improved accuracy in project tracking and forecasting, and enhanced risk management—all contributing to more successful project outcomes. However, the transition also necessitates a reevaluation of the project manager’s role, shifting from traditional task management to more strategic and analytical functions. This transformation, driven by AI, prepares practitioners for more dynamic and effective project management practices, ultimately leading to greater project success and organizational efficiency
Enhancing Cosmetic Supply Chain Efficiency Through Demand Forecasting Using Machine Learning
No full textPart 2: Digital Transformation, Industry 4.0, and Predictive AnalyticsInternational audienceThe cosmetic industry is characterized by its dynamic nature, influenced by ever-changing consumer preferences and trends. In this context, accurate demand forecasting plays a pivotal role in optimizing the cosmetic supply chain. There is a lack of comprehensive research on the applicability and effectiveness of various demand forecasting techniques within the cosmetic supply chain, considering seasonality as a factor. This paper explores the existing literature on demand forecasting within the cosmetic industry, emphasizing the significance of predictive analytics and advanced forecasting models. Through a case study of real-world data on a cosmetic product, this research assesses the applicability and effectiveness of various forecasting algorithms using machine learning. This study provides a comprehensive understanding of the challenges faced by cosmetic supply chains in demand forecasting, identifies key factors influencing demand and their impact on forecasting accuracy, and evaluates the effectiveness of different forecasting techniques in the context of cosmetic products