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Publications associées (30)

Systematic Method for the Energy-Saving Potential Calculation of Air Conditioning Systems via Data Mining. Part II: A Detailed Case Study

Shen Yang, Xianlin Wang

Increased data monitoring enables the energy-efficient operation of air-conditioning systems via data-mining. The latter is projected to have lesser consumption but more comprehensive diagnosis than traditional methods. Following the companion paper that p ...

2021

Data & Figures on the Multiscale Spatiotemporal Characterization of Embodied Environmental Efficiency of Building Structures in Geneva from 1850 to 2018

Corentin Jean Dominique Fivet, Catherine Elvire L. De Wolf

Process data, figures, and figure data resulting from the study on Multiscale Spatiotemporal Characterization of Embodied Environmental Efficiency of Building Structures in Geneva from 1850 to 2018. ...

2021

Smaller, Faster & Lighter KNN Graph Constructions

Rachid Guerraoui, Anne-Marie Kermarrec

We propose GoldFinger, a new compact and fast-to-compute binary representation of datasets to approximate Jaccard’s index. We illustrate the effectiveness of GoldFinger on the emblematic big data problem of K-Nearest-Neighbor (KNN) graph construction and s ...

2020

Adaptive partitioning and indexing for in situ query processing

Anastasia Ailamaki, Ioannis Alagiannis, Manolis Karpathiotakis, Manoussos Gavriil Athanassoulis, Matthaios Alexandros Olma

The constant flux of data and queries alike has been pushing the boundaries of data analysis systems. The increasing size of raw data files has made data loading an expensive operation that delays the data-to-insight time. To alleviate the loading cost, in ...

SPRINGER2020

Progress Toward Interpretable Machine Learning-Based Disruption Predictors Across Tokamaks

Olivier Sauter, Alessandro Pau

In this paper we lay the groundwork for a robust cross-device comparison of data-driven disruption prediction algorithms on DIII-D and JET tokamaks. In order to consistently carry on a comparative analysis, we define physics-based indicators of disruption ...

TAYLOR & FRANCIS INC2020

Fingerprinting Big Data: The Case of KNN Graph Construction

Rachid Guerraoui, Anne-Marie Kermarrec

We propose fingerprinting, a new technique that consists in constructing compact, fast-to-compute and privacy-preserving binary representations of datasets. We illustrate the effectiveness of our approach on the emblematic big data problem of K-Nearest-Nei ...

2019

Efficient User Guidance for Validating Participatory Sensing Data

Quoc Viet Hung Nguyen, Thành Tâm Nguyên

Participatory sensing has become a new data collection paradigm that leverages the wisdom of the crowd for big data applications without spending cost to buy dedicated sensors. It collects data from human sensors by using their own devices such as cell pho ...

ASSOC COMPUTING MACHINERY2019

Necessity entrepreneurship and industry choice in new firm creation

Marc Gruber

Research Summary Research on necessity entrepreneurship has generated important insights, yet it views necessity entrepreneurs in developed countries as one encompassing group of unemployed individuals-ignoring that the level of need is not uniform but ins ...

2019

Physiological Responses in Humans Acutely Exposed to High Altitude (3480 m): Minute Ventilation and Oxygenation Are Predictive for the Development of Acute Mountain Sickness

Johannes Burtscher

Burtscher, Martin, Michael Philadelphy, Hannes Gatterer, Johannes Burtscher, Martin Faulhaber, Werner Nachbauer, and Rudolf Likar. Physiological responses in humans acutely exposed to high altitude (3480 m): Minute ventilation and oxygenation are predictiv ...

MARY ANN LIEBERT, INC2019

Adaptive Cache Mode Selection for Queries over Raw Data

Anastasia Ailamaki, Tahir Azim

Caching the results of intermediate query results for future re-use is a common technique for improving the performance of analytics over raw data sources. An important design choice in this regard is whether to lazily cache only the offsets of satisfying ...

2018