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Knowledge representation and reasoning

Related publications (17)

Ontology-based Knowledge Representation for Traditional Martial Arts

Yumeng Hou, Sarah Irene Brutton Kenderdine

Traditional martial arts are treasures of humanity's knowledge and critical carriers of sociocultural memories throughout history. However, such treasured practices have encountered various challenges in knowledge transmission and now feature many entries ...

2024

An aircraft assembly process formalism and verification method based on semantic modeling and MBSE

Dimitrios Kyritsis, Xiaochen Zheng, Jinzhi Lu

The aircraft assembly system is highly complex involving different stakeholders from multiple domains. The design of such a system requires comprehensive consideration of various industrial scenarios aiming to optimize key performance indicators. Tradition ...

Elsevier Sci Ltd2024

Design ontology for cognitive thread supporting traceability management in model-based systems engineering

Dimitrios Kyritsis, Yan Yan, Jinzhi Lu

Industrial information integration engineering (IIIE) is an interdisciplinary field to facilitate the industrial information integration process. In the age of complex and large-scale systems, model-based systems engineering (MBSE) is widely adopted in ind ...

Elsevier2024

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

Dimitrios Kyritsis, Jinzhi Lu

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 ...

Pergamon-Elsevier Science Ltd2024

Orthologic with Axioms

Viktor Kuncak, Simon Guilloud

We study the proof theory and algorithms for orthologic, a logical system based on ortholattices, which have shown practical relevance in simplification and normalization of verification conditions. Ortholattices weaken Boolean algebras while having polyno ...

Association for Computing Machinery2024

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Mattia Atzeni

The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

EPFL2024

Martial Arts MAsters Knowledge Graph (MA2KG) dataset release

Yumeng Hou

Releasing the Martial Arts MAsters Knowledge Graph (MA2KG) dataset, including the core ontologies and RDF dataset, accompanied with scripts for developing the Martial Art MAsters Knowledge Graph (MA2KG). ...

Zenodo2023

Building a Knowledge Graph of Chinese Kung Fu Masters From Heterogeneous Bilingual Data

Lin Yuan, Yumeng Hou, Lin Yuan

Various endeavours into semantic web technologies and ontology engineering have been made within the organisation of cultural data, facilitating public access to digital assets. Although models for conceptualising objects have reached a certain level of ma ...

2023

An Ontology-based Engineering system to support aircraft manufacturing system design

Xiaochen Zheng, Jinzhi Lu

During the conceptual design phase of an aircraft manufacturing system, different industrial scenarios need to be evaluated against performance indicators in a collaborative engineering process. Domain experts' knowledge and the motivations for decision-ma ...

ELSEVIER SCI LTD2023

The Facets of Intangible Heritage in Southern Chinese Martial Arts: Applying a Knowledge-Driven Cultural Contact Detection Approach

Yumeng Hou

Investigating the intangible nature of a cultural domain can take multiple forms, addressing for example the aesthetic, epistemic and social dimensions of its phenomenology. The context of Southern Chinese martial arts is of particular significance as it c ...

Association for Computing Machinery2023

Co-encoding embodied knowledge in Southern Chinese martial arts: a collaboration between computists, experts, and digital models

Yumeng Hou

This research, within the framework of computational archives, inspects a novel approach to representing intangible knowledge in traditional martial arts. The methodology presents a unity of ontological modeling, semantic annotation, and feature-based mach ...

Zenodo2023

Examining European Press Coverage of the Covid-19 No-Vax Movement: An NLP Framework

Daniel Gatica-Perez

This paper examines how the European press dealt with the no-vax reactions against the Covid-19 vaccine and the dis- and misinformation associated with this movement. Using a curated dataset of 1786 articles from 19 European newspapers on the anti-vaccine ...

ASSOC COMPUTING MACHINERY2023

Blue Brain Nexus: An open, secure, scalable system for knowledge graph management and data-driven science

Henry Markram, Henry Genet, Alejandra Garcia Rojas Martinez, Sean Lewis Hill, Huanxiang Lu, Mohameth François Sy, Samuel Claude Kerrien, Michaël Fernand Paul Dupont, Silvia Rosario Jimenez Tejeda, Bogdan Roman, Ian Lavriushev, Anna-Kristin Kaufmann, Didac Montero Mendez, Wojciech Adam Wajerowicz, Pierre-Alexandre Fonta, Kenneth William Pirman, Julien Antonin Machon, Jonathan Raël Lurie, Dhanesh Neela Mana, Natalia Stafeeva, Alexander Désiré Ulbrich, Carolina Johanna Elisabeth Lindqvist

Modern data-driven science often consists of iterative cycles of data discovery, acquisition, preparation, analysis, model building and validation leading to knowledge discovery as well as dissemination at scale. The unique challenges of building and simul ...

2023

A semi-supervised algorithm for improving the consistency of crowdsourced datasets: The COVID-19 case study on respiratory disorder classification

David Atienza Alonso, Lara Orlandic, Tomas Teijeiro Campo

Background and Objective: Cough audio signal classification is a potentially useful tool in screening for respiratory disorders, such as COVID-19. Since it is dangerous to collect data from patients with contagious diseases, many research teams have turned ...

2023

Computationally Efficient Reinforcement Learning: Targeted Exploration leveraging Simple Rules

Colin Neil Jones, Loris Di Natale

Model-free Reinforcement Learning (RL) generally suffers from poor sample complexity, mostly due to the need to exhaustively explore the state-action space to find well-performing policies. On the other hand, we postulate that expert knowledge of the syste ...

2023

Data-driven Methods for Control: from Linear to Lifting

Yingzhao Lian

The progress towards intelligent systems and digitalization relies heavily on the use of automation technology. However, the growing diversity of control objects presents significant challenges for traditional control approaches, as they are highly depende ...

EPFL2023

Cognitive twin construction for system of systems operation based on semantic integration and high-level architecture

Dimitrios Kyritsis, Jinzhi Lu

With the increasing complexity of engineered systems, digital twins (DTs) have been widely used to support integrated modeling, simulation, and decision-making of the system of systems (SoS). However, when integrating DTs of each constituent system, it is ...

IOS PRESS2022