Spaces for agreement: a theory of time-stochastic dominance and an application to climate change

Many investments involve both a long time-horizon and risky returns. Making investment decisions thus requires assumptions about time and risk preferences. Such assumptions are frequently contested, particularly in the public sector, and there is no immediate prospect of universal agreement. Motivated by these observations, we develop a theory and method of finding ‘spaces for agreement’. These are combinations of classes of discount and utility function, for which one investment dominates another (or ‘almost’ does so), so that all decision-makers whose preferences can be represented by such combinations would agree on the option to be chosen. The theory is built on combining the insights of stochastic dominance on the one hand, and time dominance on the other, thus offering a nonparametric approach to inter-temporal, risky choice. We go on to apply the theory to the controversy over climate policy evaluation and show with the help of a popular simulation model that, in fact, even tough carbon emissions targets would be chosen by almost everyone, barring those with arguably ‘extreme’ preferences

Hierarchical topic structuring: from dense segmentation to topically focused fragments via burst analysis

International audienceTopic segmentation traditionally relies on lexical cohesion measured through word re-occurrences to output a dense segmen-tation, either linear or hierarchical. In this paper, a novel organization of the topical structure of textual content is proposed. Rather than searching for topic shifts to yield dense segmentation, we propose an algorithm to extract topically focused fragments organized in a hierarchical manner. This is achieved by leveraging the temporal distribution of word re-occurrences, searching for bursts, to skirt the limits imposed by a global counting of lexical re-occurrences within segments. Comparison to a reference dense segmentation on varied datasets indicates that we can achieve a better topic focus while retrieving all of the important aspects of a text

Investigating domain-independent NLP techniques for precise target selection in video hyperlinking

International audienceAutomatic generation of hyperlinks in multimedia video data is a subject with growing interest, as demonstrated by recent work undergone in the framework of the Search and Hyperlinking task within the Mediaeval benchmark initiative. In this paper, we compare NLP-based strategies for precise target selection in video hyperlinking exploiting speech material, with the goal of providing hyperlinks from a specified anchor to help information retrieval. We experimentally compare two approaches enabling to select short portions of videos which are relevant and possibly complementary with respect to the anchor. The first approach exploits a bipartite graph relating utterances and words to find the most relevant utterances. The second one uses explicit topic segmentation, whether hierarchical or not, to select the target segments. Experimental results are reported on the Mediaeval 2013 Search and Hyperlinking dataset which consists of BBC videos, demonstrating the interest of hierarchical topic segmentation for precise target selection

IRISA and KUL at MediaEval 2014: Search and Hyperlinking Task

International audienceThis paper presents our approach and results in the hyper-linking sub-task at MediaEval 2014. A two step approach is implemented: relying on a topic segmentation technique, the first step consists in generating potential target segments; then, for each anchor, the best 20 target segments are selected according to two distinct strategies: the first one focuses on the identification of very similar targets using n-grams and named entities; the second one makes use of an intermediate structure built from topic models, which offers the possibility to control serendipity and to explain the links created

Hierarchical Topic Models for Language-based Video Hyperlinking

International audienceWe investigate video hyperlinking based on speech transcripts , leveraging a hierarchical topical structure to address two essential aspects of hyperlinking, namely, serendipity control and link justification. We propose and compare different approaches exploiting a hierarchy of topic models as an intermediate representation to compare the transcripts of video segments. These hierarchical representations offer a basis to characterize the hyperlinks, thanks to the knowledge of the topics who contributed to the creation of the links, and to control serendipity by choosing to give more weights to either general or specific topics. Experiments are performed on BBC videos from the Search and Hyperlinking task at MediaEval. Link precisions similar to those of direct text comparison are achieved however exhibiting different targets along with a potential control of serendipity

Évaluation d'une nouvelle structuration thématique hiérarchique des textes dans un cadre de résumé automatique et de détection d'ancres au sein de vidéos

National audienceDans cet article, nous évaluons, à travers son intérêt pour le résumé automatique et la détection d'ancres dans des vidéos, le potentiel d'une nouvelle structure thématique extraite de données textuelles, composée d'une hiérarchie de fragments thématiquement focalisés. Cette structure est produite par un algorithme exploitant les distributions temporelles d'apparition des mots dans les textes en se fondant sur une analyse de salves lexicales. La hiérarchie obtenue a pour objet de filtrer le contenu non crucial et de ne conserver que l'information saillante des textes, à différents niveaux de détail. Nous montrons qu'elle permet d'améliorer la production de résumés ou au moins de maintenir les résultats de l'état de l'art, tandis que pour la détection d'ancres, elle nous conduit à la meilleure précision dans le contexte de la tâche Search and Anchoring in Video Archives à MediaEval. Les expériences sont réalisées sur du texte écrit et sur un corpus de transcriptions automatiques d'émissions de télévision. ABSTRACT Evaluation of a novel hierarchical thematic structuring of texts in the framework of text sum-marization and anchor detection for video hyperlinking This paper investigates the potential of a novel topical structure of text-like data in the context of summarization and anchor detection in video hyperlinking. This structure is produced by an algorithm that exploits temporal distributions of words through word burst analysis to generate a hierarchy of topically focused fragments. The obtained hierarchy aims at filtering out non-critical content, retaining only the salient information at various levels of detail. For the tasks we choose to evaluate the structure on, the lost of important information is highly damaging. We show that the structure can actually improve the results of summarization or at least maintain state-of-the-art results, while for anchor detection it leads us to the best precision in the context of the Search and Anchoring in Video Archives task at MediaEval. The experiments were carried on written text and a more challenging corpus containing automatic transcripts of TV shows. MOTS-CLÉS : analyse de salves lexicales, hiérarchie de fragments thématiques, résumé automa-tique, détection d'ancres. KEYWORDS: burst analysis, hierarchy of topical fragments, text summarization, anchor detection. (a) (b) (c) FIGURE 1 – Représentations génériques (a) d'une segmentation thématique linéaire, (b) d'une segmentation thématique hiérarchique dense classique, versus (c) celle d'une hiérarchie de fragments thématiquement focalisés. Les lignes verticales en pointillés illustrent les frontières des thèmes et sous-thèmes

Leveraging lexical cohesion and disruption for topic segmentation

International audienceTopic segmentation classically relies on one of two criteria, either finding areas with coherent vocabulary use or detecting discontinuities. In this paper, we propose a segmentation criterion combining both lexical cohesion and disruption, enabling a trade-off between the two. We provide the mathematical formulation of the criterion and an efficient graph based decoding algorithm for topic segmentation. Experimental results on standard textual data sets and on a more challenging corpus of automatically transcribed broadcast news shows demonstrate the benefit of such a combination. Gains were observed in all conditions, with segments of either regular or varying length and abrupt or smooth topic shifts. Long segments benefit more than short segments.However the algorithm has proven robust on automatic transcripts with short segments and limited vocabulary reoccurrences

Altering the tribological properties of Laser Powder Bed Fusion materials through various methods: a review

Additive Manufacturing has gained prominence in research due to its cost-effectiveness and design flexibility. However, the connection between tribology and Laser Powder Bed Fusion remains inadequately investigated despite its potential. This study examines various direct manufacturing methods (i.e., without post-processing), in order to identify the most effective technique for modifying tribological properties. The wear rate and coefficient of friction are influenced by densification, which is affected by the formation of melt pools and keyholes in the microstructure. Notably, there is conflicting evidence on the most influential processing parameter for wear. Some studies suggest that laser power holds the greatest significance, while others propose that scan angle has a more pronounced effect on wear behaviour. Additionally, texturing emerges as another tribology manipulation method, enabling the entrapment of lubricants and debris within the system. The study also explores the relationship between microhardness, volumetric energy density, wear, and friction

Geophysical prospections support the historical identification of the archaeological site at Lake Gala, Hebros/Maritsa/Meriç delta (Turkey)

Archaeological survey and combined geophysical measurements of magnetics were conducted. Geoelectrics and ground penetrating radar support the interpretation of a Roman station controlling a branch of the Via Egnatia leading to Ainos (modern Enez in Turkey). The site could be the first archaeological example of a road station in Thrace, constructed between the 1st and the 2nd century CE

Hygric properties of hemp bio-insulations with differing compositions

The paper presents the results of a laboratory investigation on the hygric properties of five hemp insulation materials commercially available in the UK. The hemp fibre content varies between 30% and 95% in the total fibre content of the insulation materials examined. The adsorption–desorption isotherm, moisture buffer value, vapour diffusion resistance factor and water absorption coefficient were determined for the insulation materials investigated. The results showed that the hygric properties of the hemp insulation materials could vary widely depending on the constituents and fibrous structure. The considerable differences noted in the hygric properties of the insulation materials examined could potentially influence their hygrothermal performance as part of a building thermal envelope