Damage Assessment of civil engineering structures and bridges using nonlinear dynamic characteristics

Doctoral thesis (2009)

Data driven discovery of cyber physical systems

in Nature Communications (2019)

Cyber-physical systems embed software into the physical world. They appear in a wide range of applications such as smart grids, robotics, and intelligent manufacturing. Cyber-physical systems have proved ... [more ▼]

Cyber-physical systems embed software into the physical world. They appear in a wide range of applications such as smart grids, robotics, and intelligent manufacturing. Cyber-physical systems have proved resistant to modeling due to their intrinsic complexity arising from the combination of physical and cyber components and the interaction between them. This study proposes a general framework for discovering cyber-physical systems directly from data. The framework involves the identification of physical systems as well as the inference of transition logics. It has been applied successfully to a number of real-world examples. The novel framework seeks to understand the underlying mechanism of cyber-physical systems as well as make predictions concerning their state trajectories based on the discovered models. Such information has been proven essential for the assessment of the performance of cyber- physical systems; it can potentially help debug in the implementation procedure and guide the redesign to achieve the required performance. [less ▲]

Data mining in geographical contexts and texts

Presentation (2010)

An increasing number of institutions, acting at different scales and within different sectors, create in-house geographical information systems, e.g. for regional statistics, for land and transport ... [more ▼]

An increasing number of institutions, acting at different scales and within different sectors, create in-house geographical information systems, e.g. for regional statistics, for land and transport management, for local urban planning, etc. In addition, with the advent of new technologies, such as GPS's or web-mapping facilities, the use of such geographical data is being more and more popular and data is made more easily accessible (sometimes even contributed by the end-users). Geographers find themselves in rather data rich environments today (irrespective of homogeneity and quality). Also geographical objects require specific visualization and statistical methods. The application and adaptation of data mining approaches in geographical contexts is an increasingly important research topic. In this lecture we will start from theoretical considerations on data mining in geography, particularly emphasizing what is special with exploratory spatial data analysis. We will then refer to ongoing research related to geographical data mining undertaken at the University of Luxembourg in collaboration with colleagues from other institutions. A first example will refer to a large and homogeneous dataset of all dwellings within a Belgian province. Using graph theory and local spatial statistics, the data is used to identify and categorize urbanisation patterns across scales in an iterative way. A second example will depict an application of 'self-organizing maps' to understand patterns of 'territorial cohesion' in Europe using a rather small and lacunary dataset. The third example will be dedicated to a text-mining application to a rather large corpus of documents related to spatial development in Europe. This work funded under the ESPON (European Spatial Observatory Network) aims at producing a relevant thematic structure to the online regional statistics database of the ESPON network. [less ▲]

Data Science and Environmental Cheminformatics (SanDAL Workshop, Uni Lu)

Presentation (2020, October 13)

Data science meets computational mechanics

Report (2021)

Data-driven constitutive laws for hyperelasticity in principal space using symbolic representations of Pytorch ANNs in FEniCS

Poster (2021, May 21)

Data-driven preventive maintenance for a heterogeneous machine portfolio

in Operations Research Letters (2023)

DBSegment: Fast and robust segmentation of deep brain structures considering domain generalisation

in Human Brain Mapping (2022)

Segmenting deep brain structures from magnetic resonance images is important for patient diagnosis, surgical planning, and research. Most current state-of-the-art solutions follow a segmentation-by ... [more ▼]

Segmenting deep brain structures from magnetic resonance images is important for patient diagnosis, surgical planning, and research. Most current state-of-the-art solutions follow a segmentation-by-registration approach, where subject magnetic resonance imaging (MRIs) are mapped to a template with well-defined segmentations. However, registration-based pipelines are time-consuming, thus, limiting their clinical use. This paper uses deep learning to provide a one-step, robust, and efficient deep brain segmentation solution directly in the native space. The method consists of a preprocessing step to conform all MRI images to the same orientation, followed by a convolutional neural network using the nnU-Net framework. We use a total of 14 datasets from both research and clinical collections. Of these, seven were used for training and validation and seven were retained for testing. We trained the network to segment 30 deep brain structures, as well as a brain mask, using labels generated from a registration-based approach. We evaluated the generalizability of the network by performing a leave-one-dataset-out cross-validation, and independent testing on unseen datasets. Furthermore, we assessed cross-domain transportability by evaluating the results separately on different domains. We achieved an average dice score similarity of 0.89 ± 0.04 on the test datasets when compared to the registration-based gold standard. On our test system, the computation time decreased from 43 min for a reference registration-based pipeline to 1.3 min. Our proposed method is fast, robust, and generalizes with high reliability. It can be extended to the segmentation of other brain structures. It is publicly available on GitHub, and as a pip package for convenient usage. [less ▲]

Deadzone-Quadratic Penalty Function for Predictive Extended Cruise Control with Experimental Validation

in ROBOT 2017: Third Iberian Robotics Conference, Sevilla, Spain 22-24 November 2017 (2017, November)

Battery Electric Vehicles have high potentials for the modern transportations, however, they are facing limited cruising range. To address this limitation, we present a semi-autonomous ecological driver ... [more ▼]

Battery Electric Vehicles have high potentials for the modern transportations, however, they are facing limited cruising range. To address this limitation, we present a semi-autonomous ecological driver assistance system to regulate the velocity with energy-efficient techniques. The main contribution of this paper is the design of a real-time nonlinear receding horizon optimal controller to plan the online cost-effective cruising velocity. Instead of conventional L2-norms, a deadzone-quadratic penalty function for the nonlinear model predictive controller is proposed. Obtained field experimental results demonstrate the effectiveness of the proposed method for a semi-autonomous electric vehicle in terms of real-time energy-efficient velocity regulation and constraints satisfaction. [less ▲]

Dealing with requirements: Influences on Idea Generation in the Early Stages of Product Development

in Proceedings of DTRS7: Design Meeting Protocols (2007)

This paper aims at identifying factors which influence the number of ideas generated during a brainstorming meeting as part of an industrial mechanical engineering design project. A framework for ... [more ▼]

This paper aims at identifying factors which influence the number of ideas generated during a brainstorming meeting as part of an industrial mechanical engineering design project. A framework for describing groups of influencing factors and their relationships is used. As a result of an explorative, comparative protocol analysis of two design meetings the influence of some factors is described e.g. the formulation of the design task description and the sequence of the process steps. [less ▲]