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Luxembourg Institute of Science and Technology, Luxembourg

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16 Papers

Automated Machine Learning for Wind Farms Location

Topics: Advanced Learning Methods; Industry Related Applications; Machine Learning Methods; Classification and Clustering

Authors: Olivier Parisot and Thomas Tamisier

Affiliation: Luxembourg Institute of Science and Technology (LIST), Luxembourg

Digital Object Identifier: 10.5220/0010232102220227

Proceedings of ICPRAM 2021, ISBN: 978-989-758-486-2

Quick Abstract

Automated Machine Learning aims at preparing effective Machine Learning models with little or no data science expertise. Tedious tasks like preprocessing, algorithm selection and hyper-parameters optimization are then automatized: end-users just have to apply and deploy the model that best suits the real world problem. In this paper, we experiment Automated Machine Learning to leverage open data sources for predicting potential next wind farms location in Luxembourg, France, Belgium and Germany.

A Novel 2.5D Shadow Calculation Algorithm for Urban Environment

Topics: Computational Geometry; Spatio-Temporal Data Acquisition; Spatial Modeling and Reasoning; Geospatial Information and Technologies; Geocomputation; Urban and Regional Planning; Spatial Information Management

Authors: Sukriti Bhattacharya , Christian Braun and Ulrich Leopold

Affiliation: Department for Environmental Research and Innovation (ERIN), Luxembourg Luxembourg Institute of Science and Technology (LIST) and Luxembourg

Digital Object Identifier: 10.5220/0007748602740281

Proceedings of GISTAM 2019, ISBN: 978-989-758-371-1

Quick Abstract

This paper proposes a novel efficient algorithm to calculate a 2.5D shadow map based on a coherent mathematic formula concerning the sun’s position in a specific location, date and time. This work attempts to improve the understanding of the underlying equations and data structures from an analytical, a geometric and a dynamical systems perspective. By using scalable tensor data structure and inherent parallelism offered by data-flow based implementation the proof of concept is developed to test the technical feasibility of the proposed algorithm. Results show noticeable and significant improvements in overall performance keeping accuracy at negligible differences.

Related Ontology Subjects/Areas/Topics (3)

Computational Geometry

Computer Vision, Visualization and Computer Graphics

Image Formation and Preprocessing

Storing and Processing Personal Narratives in the Context of Cultural Legacy Preservation

Topics: Data Modeling and Visualization; Data Structures and Data Management Algorithms; Nosql Databases

Authors: Pierrick Bruneau , Olivier Parisot and Thomas Tamisier

Affiliation: Luxembourg Institute of Science and Technology, Luxembourg

Digital Object Identifier: 10.5220/0006422800480055

Proceedings of DATA 2017, ISBN: 978-989-758-255-4

Quick Abstract

An important, yet underestimated, aspect of cultural heritage preservation is the analysis of personal narratives told by citizens. In this paper, we present a data model and implementation towards facilitating narratives storage and sharing. The proposed solution aims at collecting textual narratives in raw form, processing them to extract and store structured content, and then exposing results through a RESTful interface. We apply it to a corpus related to the time of the European construction in Luxembourg. We disclose details about our conceptual model and implementation, as well as evidence supporting the interest of our approach.

Related Ontology Subjects/Areas/Topics (6)

Data Engineering		Data Modeling and Visualization		Databases and Data Security
Data Management and Quality		Data Structures and Data Management Algorithms		Nosql Databases

Subspace Clustering and Visualization of Data Streams

Topics: Visual Data Analysis and Knowledge Discovery; Visual Representation and Interaction; Interactive Visual Interfaces for Visualization; Interface and Interaction Techniques for Visualization; Information and Scientific Visualization

Authors: Ibrahim Louhi ¹ , Lydia Boudjeloud-Assala ² and Thomas Tamisier ³

Affiliations: ¹ Université de Lorraine and Luxembourg Institute of Science and Technology, France , ² Université de Lorraine, France , ³ Luxembourg Institute of Science and Technology, Luxembourg

Digital Object Identifier: 10.5220/0006169702590265

Proceedings of IVAPP 2017/VISIGRAPP, ISBN: 978-989-758-228-8

Quick Abstract

In this paper, we propose a visual subspace clustering approach for data streams, allowing the user to visually track data stream behavior. Instead of detecting elements changes, the approach shows visually the variables impact on the stream evolution, by visualizing the subspace clustering at different levels in real time. First we apply a clustering on the variables set to obtain subspaces, each subspace consists of homogenous variables subset. Then we cluster the elements within each subspace. The visualization helps to show the approach originality and its usefulness in data streams processing.

Related Ontology Subjects/Areas/Topics (8)

Abstract Data Visualization	Information and Scientific Visualization	Visual Data Analysis and Knowledge Discovery
Computer Vision, Visualization and Computer Graphics	Interactive Visual Interfaces for Visualization	Visual Representation and Interaction
General Data Visualization	Interface and Interaction Techniques for Visualization

Using Visualisation Techniques to Acquire a Better Understanding of Storytelling for Cultural Heritage

Topics: Data Analytics; Information and Scientific Visualization; Data Science

Authors: Paulo Carvalho , Olivier Parisot and Thomas Tamisier

Affiliation: Luxembourg Institute of Science and Technology, Luxembourg

Digital Object Identifier: 10.5220/0006415801570164

Proceedings of DATA 2017, ISBN: 978-989-758-255-4

Quick Abstract

Historical information has an important role regarding cultural heritage. It is used to interpret facts occurred in the past and also to understand the present. Storytelling, when applied in the narrative of true events and resulting from different personal views and anecdotal stories, act as an important source of historical information. In this paper, we discuss the problems we encounter in the field of historical information storytelling and we present a software architecture to facilitate the comprehension of stories. More precisely, the proposed solution helps to analyse a story, examine its composition identifying existing entity classes and computing possible relations with other stories, to finally build a visual representation of these stories.

Related Ontology Subjects/Areas/Topics (10)

Artificial Intelligence	Data Engineering	Knowledge Discovery and Information Retrieval
Business Analytics	General Data Visualization	Knowledge-Based Systems
Computer Vision, Visualization and Computer Graphics	Information and Scientific Visualization	Symbolic Systems
Data Analytics

A Geospatial Tangible User Interface to Support Stakeholder Participation in Urban Planning

Topics: Decision Support Systems; Human Computer Interaction and Visualization

Authors: Valérie Maquil , Luís De Sousa , Ulrich Leopold and Eric Tobias

Affiliation: Luxembourg Institute of Science and Technology, Luxembourg

Digital Object Identifier: 10.5220/0005370801130120

Proceedings of GISTAM 2015, ISBN: 978-989-758-099-4

Quick Abstract

The complexity of urban projects today requires new approaches to integrate stakeholders with different professional backgrounds. Traditional tools used in urban planning are designed for experts and offer little opportunity for participation and collaborative design. This paper introduces the concept of Geospatial Tangible User Interfaces (GTUI), and reports on the design and implementation of such a GTUI to support stakeholder participation in collaborative urban planning. The proposed system uses physical objects to interact with large digital maps and geospatial data projected onto a tabletop. It is implemented using a PostGIS database, a web map server, the computer vision framework reacTIVision, a Java based TUIO client, and GeoTools. Based on a series of comments collected during an evaluation workshop with stakeholders in the fields of urban and energy planning, we discuss how maps projected on a table and physical objects can be an new approach to participatory bottom-up urban planning.

A Visual Technique to Assess the Quality of Datasets - Understanding the Structure and Detecting Errors and Missing Values in Open Data CSV Files

Topics: Information Quality; Data Modeling and Visualization; Data Structures and Data Management Algorithms; Open Data

Authors: Paulo Da Silva Carvalho ¹ , Patrik Hitzelberger ¹ , Fatma Bouali ² and Gilles Venturini ²

Affiliations: ¹ Luxembourg Institute of Science and Technology, Luxembourg , ² University François Rabelais of Tours, France

Digital Object Identifier: 10.5220/0005496601340141

Proceedings of DATA 2015, ISBN: 978-989-758-103-8

Quick Abstract

Nowadays, more and more information is flowing in and is provided on the Web. Large datasets are made available covering many fields and sectors. Open Data (OD) plays an important role in this field. Thanks to the volumes and the variety of the released datasets, OD brings high societal and business potential. In order to realize this potential, the reuse of the datasets (e.g. in internal business processes) becomes primordial. However, if the aim is to reuse OD, it is also necessary to be able of assessing its quality. This paper demonstrates how Information Visualization may help on this task and presents Stacktab chart - a new chart to analyse and assess CSV files in order to understand their structure, identify the location of relevant information and detect possible problems in the datasets.

Related Ontology Subjects/Areas/Topics (6)

Data Engineering		Data Modeling and Visualization		Information Quality
Data Management and Quality		Data Structures and Data Management Algorithms		Open Data

Adopting an Agent and Event Driven Approach for Enabling Mutual Auditability and Security Transparency in Cloud based Services

Topics: Monitoring of Services, Quality of Service, Service Level Agreements; Security, Privacy, and Compliance Management; Privacy, Security and Trust

Authors: Moussa Ouedraogo ¹ , Eric Dubois ¹ , Djamel Khadraoui ¹ , Sebastien Poggi ² and Benoit Chenal ²

Affiliations: ¹ Luxembourg Institute of Science and Technology, Luxembourg , ² Victor Buck Services S.A, Luxembourg

Digital Object Identifier: 10.5220/0005496205650572

Proceedings of CLOSER 2015, ISBN: 978-989-758-104-5

Quick Abstract

We propose an event-driven approach for the automated audit of cloud based services security. The proposed approach is a solution to two of the intrinsic security issues of cloud based services, notably the need of security transparency and mutual auditability amongst the stakeholders. We leverage a logic based event specification language to represent patterns of events which occurrence can be evidence of security anomaly or breach or simply a sign of a nefarious use of the cloud infrastructure by some of its users. The use of dedicated algorithms for the detection of composite events coalesced with the definition of primitive events structure based on XCCDF format ensures the reuse and interoperability with security audit tools based on the Security Content and Automation Protocol-SCAP. The implementation and application of the approach on a cloud service dealing with electronic archiving have demonstrated its feasibility and viability.

Related Ontology Subjects/Areas/Topics (4)

Cloud Computing		Monitoring of Services, Quality of Service, Service Level Agreements		Security, Privacy, and Compliance Management
Cloud Computing Enabling Technology

Preserving Prediction Accuracy on Incomplete Data Streams

Topics: Datamining; Data Analytics; Data Curation; Predictive Modeling

Authors: Olivier Parisot , Yoanne Didry , Thomas Tamisier and Benoît Otjacques

Affiliation: Luxembourg Institute of Science and Technology (LIST), Luxembourg

Digital Object Identifier: 10.5220/0005553500910096

Proceedings of DATA 2015, ISBN: 978-989-758-103-8

Quick Abstract

Model tree is a useful and convenient method for predictive analytics in data streams, combining the interpretability of decision trees with the efficiency of multiple linear regressions. However, missing values within the data streams is a crucial issue in many real world applications. Often, this issue is solved by pre-processing techniques applied prior to the training phase of the model. In this article we propose a new method that proceeds by estimating and adjusting missing values before the model tree creation. A prototype has been developed and experimental results on several benchmarks show that the method improves the accuracy of the resulting model tree.

Related Ontology Subjects/Areas/Topics (19)

Artificial Intelligence	Data Mining	Knowledge-Based Systems
Biomedical Engineering	Databases and Information Systems Integration	Predictive Modeling
Business Analytics	Datamining	Sensor Networks
Data Analytics	Enterprise Information Systems	Signal Processing
Data Curation	Health Information Systems	Soft Computing
Data Engineering	Knowledge Discovery and Information Retrieval	Symbolic Systems
Data Management and Quality

Twist, Shift, or Stack? - Usability Analysis of Geospatial Interactions on a Tangible Tabletop

Topics: Decision Support Systems; Human Computer Interaction and Visualization

Authors: Catherine Emma Jones ¹ and Valérie Maquil ²

Affiliations: ¹ CVCE, Luxembourg , ² Luxembourg Institute of Science and Technology (LIST), Luxembourg

Digital Object Identifier: 10.5220/0005377601700177

Proceedings of GISTAM 2015, ISBN: 978-989-758-099-4

Quick Abstract

Maps as learning, exploration and analysis tools have great power to aid understanding of complex phenomena and to instigate and engage discussion. To date, web-mapping platforms have largely contributed to the public availability of geospatial information. Tangible user interfaces (TUI) as an emerging class of interfaces, have a clear potential for improving collaboration around geospatial data, as well as increase geospatial understanding, but to realise this potential they must be easy and straightforward to learn and use. To date, there is a lack of research centred on human interactions with geospatial tangible applications. This paper reports on the results of an initial qualitative usability study carried with novice users on a geospatial tangible table. It discusses aspects related to cartographic elements, object manipulations, and offline interactions, to create an initial set of usability guidelines for geo-tangible tables.