A Method of Functional Alignment Verification in Hierarchical Enterprise Models

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Metal Forming is a basic and essential industrial process to provide materials for constructing complex products. To design an efficient metal forming process, the functional requirements and operational performance are two important aspects to be consider ...

Enterprises collect data in large volumes and leverage them to drive numerous concurrent decisions and business processes. Their teams deploy multiple applications that often operate concurrently on the same data and infrastructure but have widely differen ...

In a collaboration between Ecole Polytechnique Fédérale de Lausanne (EPFL) and CEA, in the fall of 2020, the experimental Programme d’Étude en Transmission de l’Acier Lourd et ses Eléments (PETALE) was successfully carried out in the CROCUS reactor of EPFL ...

The desire and ability to place AI-enabled applications on the edge has grown significantly in recent years. However, the compute-, area-, and power-constrained nature of edge devices are stressed by the needs of the AI-enabled applications, due to a gener ...

Modern power distribution systems are experiencing a large-scale integration of Converter-Interfaced Distributed Energy Resources (CIDERs). Their presence complicates the analysis and mitigation of harmonics, whose creation and propagation may be amplified ...

Deep learning (DL) has recently been proposed as a novel approach for 21cm foreground removal. Before applying DL to real observations, it is essential to assess its consistency with established methods, its performance across various simulation models, an ...

A review is given on the highlights of a scatter-shot approach of developing machine-learning methods and artificial neural networks based fast predictors for the application to fusion exhaust. The aim is to enable and facilitate optimized and improved mod ...

The paper details the process of developing the ITER Plasma Control System (PCS), that is, how to design and deploy it systematically, in the most efficient and effective manner. The integrated nature of the ITER PCS, with its multitude of coupled control ...

Fuzzing reliably and efficiently finds bugs in software, including operating system kernels. In general, higher code coverage leads to the discovery of more bugs. This is why most existing kernel fuzzers adopt strategies to generate a series of inputs that ...

We study socio-political systems in representative democracies. Motivated by problems that affect the proper functioning of the system, we build computational methods to answer research questions regarding the phenomena occurring in them. For each phenomen ...

Physics-informed machine learning (PIML) is a set of methods and tools that systematically integrate machine learning (ML) algorithms with physical constraints and abstract mathematical models developed in scientific and engineering domains. As opposed to ...

In this work, we propose an open-hardware low-power coarse-grained reconfigurable array connected to a lightweight microcontroller and enclosed in an application mapping framework. The latter provides complete support to configure kernels in the reconfigur ...

With the continuous improvement of system scale and complexity, model-based system engineering (MBSE) is of great importance in the practice of system engineering (SE). MBSE has been widely concerned in industry, especially in the field of complex equipmen ...

During the design phase of an aircraft manufacturing system, different industrial scenarios need to be evaluated according to key performance indicators to achieve the optimal system performance. It is a highly complex process involving multidisciplinary s ...

While software applications, programming languages, and hardware have changed, operating systems have not. Widely-used commodity operating systems are still modeled after the ones designed in the seventies. The accumulated burden of backward compatibility ...

As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented attention because of its promise to further optimize process design, quality control, health monitoring, decision- and policy-making, and more, by comprehensively m ...

Supply Chain Finance (SCF) refers to the financial service in which banks rely on core enterprises to manage the capital flow and logistics of upstream and downstream enterprises. SCF adopts a self-testing and closed-loop credit model to control funds and ...

To build biophysically detailed models of brain cells, circuits, and regions, a data-driven approach is increasingly being adopted. This helps to obtain a simulated activity that reproduces the experimentally recorded neural dynamics as faithfully as possi ...

Homomorphic Encryption (HE) enables computations to be executed directly on encrypted data. As such, it is an auspicious solution for protecting the confidentiality of sensitive data without impeding its usability. However, HE does not provide any guarant ...

Modeling in neuroscience occurs at the intersection of different points of view and approaches. Typically, hypothesis-driven modeling brings a question into focus so that a model is constructed to investigate a specific hypothesis about how the system work ...

A Method of Functional Alignment Verification in Hierarchical Enterprise Models

Chat with Graph Search

A semantic model-based systems engineering approach for assessing the operational performance of metal forming process

Oligolithic Cross-task Optimizations across Isolated Workloads

High-Resolution Modeling Without Computation Slowdown for PETALE in CROCUS

Exploring High-Performance and Energy-Efficient Architectures for Edge AI-Enabled Applications

Unified Harmonic Power-Flow and Stability Analysis of Power Grids with Converter-Interfaced Distributed Energy Resources

The stability of deep learning for 21cm foreground removal across various sky models and frequency-dependent systematics

Data-driven models in fusion exhaust: AI methods and perspectives

Strategy to systematically design and deploy the ITER plasma control system: A system engineering and model-based design approach

ACTOR: Action-Guided Kernel Fuzzing

How Words Move Hearts: Interpretable Machine Learning Models of Bias, Engagement, and Influence in Socio-Political Systems

Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems

An Open-Hardware Coarse-Grained Reconfigurable Array for Edge Computing

Model-based Systems Engineering Papers Analysis based on Word Cloud Visualization

A semantic-driven tradespace framework to accelerate aircraft manufacturing system design

Dynamic Linkers Are the Narrow Waist of Operating Systems

A comprehensive review of digital twin-part 2: roles of uncertainty quantification and optimization, a battery digital twin, and perspectives

A blockchain and IoT-based lightweight framework for enabling information transparency in supply chain finance

Online interoperable resources for building hippocampal neuron models via the Hippocampus Hub

Thwarting Malicious Adversaries in Homomorphic Encryption Pipelines

Combining hypothesis- and data-driven neuroscience modeling in FAIR workflows