Julien Subercaze
email: julien.subercaze@univ-st-etienne.fr

Christophe Gravier
email: christophe.gravier@univ-st-etienne.fr

FoP: Never-ending learner for multimedia knowledge extraction

In this paper we present our system Faces of Politics (henceforth FoP), that is able to continuously learn multimedia knowledge of Web multimedia resources about the presence of person(s) in a pictures and to leverage this knowledge to the Linked Open Data cloud (LOD-cloud). FoP promotes both scalability of the data lift process for this domain and a structured knowledge representation for complex queries. The system was bootstraped using Freebase data about politicians and their pictures, and we show that the model provides a good generalization with an error rate below 7%. Meantime, FoP not only relates a person to a multimedia resource, but it also detects and publishes metadata on the position of the person in the picture. Moreover, it supports the presence of several persons in the picture. At this step, FoP is also giving data in return to the LoD cloud that fed him in the first place: it leverages Linked Data on people recognized in these pictures, and on which rectangle area. This allows fine-grained queries like creating a curation of documents in which a person is depicted relatively to another for instance. On a technical point-of-view, we also provide a Website for browsing FoP knowledge base as Web users, and we also offer a public SPARQL endpoint for robots or other Web applications.

I. INTRODUCTION

The LOD-Cloud was first initiated using manually generated ontologies, such as OpenCyc [1] or Freebase [START_REF] Bollacker | Freebase: a collaboratively created graph database for structuring human knowledge[END_REF]. This approach, while providing a good quality of data, fails to scale for the Web. One of the main difficulty is the requirements on the user to contribute to the knowledge modeling tasks. Another limitation is the incomplete domain coverage of the underlying ontologies. Meanwhile, wikis offered a very convenient framework for sharing general knowledge in an unstructured manner. Social web users therefore massively contributed to these platforms and classification tasks, especially Wikipedia [START_REF] Nov | What motivates wikipedians?[END_REF]. As a consequence, many projects focused on the automated leverage of knowledge from these unstructured data. For example, Wikipedia being the most popular wiki, several projects used it for enriching the LOD-Cloud with new structured knowledge (e.g. [START_REF] Wu | Autonomously semantifying wikipedia[END_REF], [START_REF] Milne | An open-source toolkit for mining wikipedia[END_REF], [START_REF] Strube | Wikirelate! computing semantic relatedness using wikipedia[END_REF]). Such approaches mainly suffers from two limitations. First, they are prone to human mistakes when editing wikis, or spam (because of free-riding). Secondly, they does not take into account the large amount of knowledge that is already present on the Web, and may not intend to model all existing or future domain knowledge.

As a consequence, other works explore the possibility to tackle these problems by walking the entire Web corpus and therefore learning knowledge at web scale. The size of the Web makes it difficult to leverage knowledge from a significant part of the Web corpus in a single shot. To overcome this issue, incremental learning approaches have demonstrated significant improvement for the task of automated integration of textual data. This principle was popularized by NELL, the neverending learner [START_REF] Carlson | Toward an architecture for never-ending language learning[END_REF], that has been running continuously, and has learnt more than 50 millions of facts by itself. Recently, we also contributed to this task by making NELL compliant with semantic Web standards [START_REF] Zimmermann | Nell2rdf: Read the web, and turn it into rdf[END_REF].

These approaches primarily leverage textual data to the LOD-Cloud. Less efforts were provided for multimedia data with respect to those brought on textual data. Nonetheless, pictures and videos are a first-class citizen on the Web, which drove several works towards leveraging multimedia data for the LOD-Cloud [START_REF] Stamou | Multimedia annotations on the semantic web[END_REF], [START_REF] Arndt | Comm: designing a well-founded multimedia ontology for the web[END_REF] (See Section II for a more detailled state-of-the-art). The first issue with multimedia data is that currently only a high-level of information is leveraged to the LOD-cloud. This mainly means that multimedia data in the LOD-Cloud appears in the form of link from an URI associated from a Person to an URI associated to a picture. When these information comes from Wikis, there are prone to the same weaknesses than their textual equivalents (errors, spam, scalability, broad range of high level taxonomies versus narrow domain to model). There is also a concern of level of details in the knowledge modeling task of multimedia data, that are the leverage of multimedia fragment. For instance a picture may depict three sports car of different brands. One may want to query the data about the relative positions of these cars or about the brands of the cars, whether they are in the foreground or not, etc. Although the standards do exist in the LOD-cloud [START_REF] Troncy | Media fragments uri 1.0[END_REF], there are yet to be a learner that will both improve the scalability of learnt multimedia knowledge, while proposing a fine-grained representation of multimedia knowledge.

In this paper we present our system FoP that is able to continuously learn from the Web new multimedia knowledge about the presence of person(s) in a pictures and to leverage this knowledge to the LOD-cloud. This allows queries on structured content, therefore providing a richer expressivity of the query. In a first part FoP has to be bootstrapped using labelled data. For this, FoP needs a dataset with structured data already linking people resources and images in which this resource is present. The LoD-cloud provides such datasets, and using them to bootstrap FoP allows to circumvent the usual pitfall that only he who has the data can learn the model. In a second part, FoP learns new visual knowledge from the Web and makes its result available into the LoD-Cloud.

The main contributions of the paper are the following :

• we propose a never-ending learner that is able to assess the presence of a person in a picture and to specify where the person is in the picture.

• We show that a very low error rate is possible : FoP achieves an error rate under 7%

• FoP can be queried online by both machines and humans. We provide a new data source of multimedia fragments into the LoD-Cloud, available through a SPARQL endpoint.

• We demonstrate the virtuous circle between the LoD cloud and a visual knowledge learner: the more the visual knowledge learner is fed by LoD data, the more it is accurate hence the more it gives data back to the LoD cloud.

On a technical point-of-view, we also provide a publicly available service compliant with semantic Web standards. The paper is organized as follows : Section II related works relevant to FoP. Section IV presents the bootstrapping part of our system. Section V describes the general architecture and the behaviour of the learner. Section VI describes usage of the public online service and provides some illustrations. Section VII concludes.

II. RELATED WORK

FoP aims at providing a fine-grained knowledge representation in the Semantic Web informational space about the presence of people in pictures. Given the tremendous amount of photos on the Web due to the ever-increasing multimedia consumption in our society, this is a problem that has gained interest over the recent years. We classified related works into two major categories. The first one encompasses approaches in which the knowledge representation is provided by a crowdsourcing mechanisms, which is not uncommon in linked data management tasks [START_REF]Crowdsourcing tasks in Linked Data management[END_REF]. At the opposite, FoP falls into the second categories that is automatic person recognition. Both categories exhibit complementary strengths and shortcomings. A manual process, even crowdsourced, may not scale as well as an autonomic approach. Nonetheless, humans may encode knowledge that is difficult for the machine to learn, such as the relative position of persons in the picture, the fact that a person is a sunglass bearer, etc. That is the reason why this category is interesting as related works in order to have an idea on how FoP performs in terms of knowledge representation.

At the opposite to crowdsourced solutions, an automatic process may not be able to grasp all the latent knowledge in the picture about people -or to grasp it with precision -yet it may well tend to address Web scale. Crowdsourced and automatic processes are a trade-off between precision and recall. In this section, we will review related works that falls into these two categories as follows. On one hand, crowdsourcing approaches will be reported and analyzed with a prority given to how finegrained is the knowledge representation. On the other hand, we will be primarily interested in the scalability and precision of automatic person recognition processes. Both will be discussed in term of data lift abilities. In Table I, we provide a synoptic view on the related works reported in this section.

Crowdsourcing person recognition and data lift for multimedia Web resources. The Flickr wrapper [START_REF] Berlin | Flickr wrappr, precise photo association[END_REF] intends to extend Wikipedia with RDF annotations on Flickr pictures. Any Web user is invited to declare links between a Flickr photo and a Wikipedia page. The linkage possibilities are only available at a coarse grain: a user only declares that a picture is "related" to a Wikipedia page (related can be pretty vague), and it is not possible to link only a subpart of the picture (e.g. faces). No control is applied on the crowsourced data, while free-riding is prone to error, and no metric aside human validation on such a large corpus is made available. With the assumption that video objects are an opaque information nutshell for crawlers, [START_REF] Steiner | Crowdsourcing event detection in youtube video[END_REF] presents a generic crowd-sourcing framework for automatic and scalable event detection framework for HTML 5 videos, especially for YouTube. This framework is easing the leveraging of Linked Data based on the Event Ontology1 , which includes the Agent class whose instances can be persons. It partially relies on the end-user behaviour when reading the video in order to detect events. The authors state that the precision of the inferred knowledge from these observations improve because of the wisdom of the crowd. However, no evaluation of this improvement, neither its absolute performance to a ground truth is provided to support this claim. In [START_REF] Maji | Large scale image annotations on amazon mechanical turk[END_REF], the authors explore the utility of tasks marketplaces like Amazon Mechanical Turk [START_REF] Paolacci | Running experiments on amazon mechanical turk[END_REF] (AMT). In this project, the Human Intelligence Task (HIT as denoted in AMT) is to identify figure ground masks for different object categories on the PASCAL VOC 2010 dataset [START_REF] Everingham | The pascal visual object classes (voc) challenge[END_REF]. The interface of the task allows to outline polygons in images in order to draw the outline of recognized object by the human performing the HIT. Among all objects in the PASCAL dataset, 7296 are persons (31.2%). The validation is performed against the PASCAL 2010 dataset ground truth. While the model does not evolve with time and does not provide a data lift mechanism, it however provides a leveraging of fine-grained information on people in a picture, especially gender, race, age, hair-type, glasses, shoes, lower-clothes, . . . This work is also interesting because it enforces the assumption stated at the begining of this section: the recognition task performed by humans are pretty good since only 10% of submitted boundaries were rejected, under tight validation constraints. Photocopain [START_REF] Tuffield | Proceedings of the First International Workshop on Semantic Web Annotations for Multimedia (SWAMM)[END_REF] is a semi-automatic annotation system. It tries to ease the burden of photo annotation from its end-users, while using human annotation as a very high confidence datasource. The main application is archiving the personal experience of its user. Among several features, it provides a person detection, recognition and annotation service. The face detection model is built using a hue, intensity, and texture map, whose precision is tuned by correlating its output with the EXIF data of the photo. The result is stored in a RDF triplestore, and proposed to the end user for validation and metadata expansion (including person tagging and recognition). Tested on a limited dataset of 150 images including a 30 images tests set, Photocopain exhibits promising result for photo annotation.

Automatic person recognition and data lift. In [START_REF] Smith | Visualising the past: Annotating a life with linked open data[END_REF], the authors present a life-logging system that combines users' private log on their smartphone and data obtained automatically from the Web. The face recognition system is mainly performed using Bluetooth scans of nearby devices, whose owner had been previously declared in the system database. The user's picture are then lifted to the LoD-cloud mainly using the foaf ontology which is limited vocabuluary if solely used, and does not allow an excellent precision. Nonetheless, this can be explained by the fact that the application not only address person recognition, but also other personal events that the end user wants to reccord in his personal life-blogging system. In [START_REF] Bozzon | Integration of a human face annotation technology in an audio-visual search engine platform[END_REF], the authors present Pharos, an European initiative to index and search audiovisual contents. In Pharos, a Face Annotation service submodule is responsible for indexing persons which are depicted in a picture. It relies on a previously learned model, on an unknown dataset. This submodule is not reported to embed online learning mechanisms. This module is not exploiting neither publishing Linked Data, but instead focused on publishing MPEG7 compliant metadata. Last year [START_REF] Hoi | Fans: face annotation by searching large-scale web facial images[END_REF] presented FANS, a face annotation framework. The FANS inner model is first trained using a manually constructed dataset resulting from google queries on 6,025 persons. By applying a Locality-Sensitive Hash function to the natural feature points of detected faces, the authors demonstrated a scalable Web image retrieval engine. However, FANS do not interact with the Web of Data, and the model is not evolving with time. Another work provided by [START_REF] Verborgh | Enabling context-aware multimedia annotation by a novel generic semantic problem-solving platform[END_REF] stresses the usage of sponging multimedia information, as intended in FoP. Sponging is the task to leverage new triples from Web crawls and large textual corpus. The authors propose to search dbpedia for the persons depicted in a resource (a foaf:image). The authors assume that two or more persons are present in the picture, and that face detection and face recognition algorithms can fail to identify all persons in a given picture. If at least one person is devised, the sponging process is started : the system looks up for related persons in dbpedia for the recognized persons. A new iteration of face recognition is then started, limited to the foaf:depicts

properties matching related persons. The shortcomings of this approach is that the picture must contain at least two persons, and that all these persons can be recognized and linked in DBPedia.

Lately [START_REF] Chen | Neil: Extracting visual knowledge from web data[END_REF] proposed NEIL, a Never Ending Image Learner. Like FoP, NEIL is a never-ending learner that aims at extracting visual knowledge from various images. NEIL discovers terminology and instance classification information. It is a large scale initiative in term of CPU consumption (more than 350K CPU hours) for processing the 2 millions images downloaded by NEIL (and counting). NEIL is bootstraped using textbased indexing tools, primarily Google Image Search. Among the 1152 manually entered or discovered object categories in NEIL, some include visual knowledge for people. This includes learning that eye is a part of Baby, for instance. However, it does not provide instance labelling to existing person. Instead, NEIL is interested in discovering the visual descriptor of a given concept. For instance, NEIL discovered the Actor object class2 . Among classified photo in this object class, there are indeed mainly actors that have been correctly classified as such by NEIL. There is no possibility however to link the image with an actor, neither to know which actor is depicted in the image. NEIL does not support multiple person in an image, neither does it provides a sponging process from its database to the LOD cloud.

III. FOP OVERVIEW

Our system, called FacesOfPolitics is made of two steps. In a first part, detailed in the next section, we bootstrap the face recognition model using data from Freebase3 . The aim of this step is to leverage existing LOD-Cloud data to avoid as most as possible classical cold start issues.

Related works

System name

Flickrwrappr N/A N/A Photocopain Imouto Pharos FANS N/A NEIL In a second step, which is the steady state of FoP, our system crawls RSS feeds of major news websites, looking for new pictures. Whenever a face is detected and matched to a known person, the internal triplestore stores this information (See Figure 1). Following the idea of never-ending learner that has been succesfully applied to language learning [START_REF] Carlson | Toward an architecture for never-ending language learning[END_REF], our model is being updated and improved whenever a person has been recognized in a new picture. This step is detailled in section V. An overview of this global architecture is depicted in figure 1.

IV. BOOTSTRAPPING (TRANSIENT STATE))

FoP's central component is the face recognition model that is used both to identify persons in images and to be updated throughout the never ending learning process. The problem of initiating the model is twofold. In the first place, the algorithm powering the face recognition module must be efficient, i.e. in our case provide a low false positive rate and it must also be rapidly updated whenever new pictures arise. In the second place, the model has to be initiated with reliable data in a sufficient volume.

There are several approaches to perform face recognition. It is however out of the scope of this paper to provide an extensive review of existing literature. The interested reader may referto the following surveys : [START_REF] Abate | 2d and 3d face recognition: A survey[END_REF], [START_REF] Zou | Illumination invariant face recognition: A survey[END_REF], [START_REF] Jafri | A survey of face recognition techniques[END_REF], [START_REF] Zhao | Face recognition: A literature survey[END_REF].

Nonetheless, the Local Binary Patterns algorithm [START_REF] Ahonen | Face description with local binary patterns: Application to face recognition[END_REF] is a very robust face recognition algorithm that is less sensitive to lighting conditions than other standard algorithms. Moreover it is not computationally expensive to perform an update of the model, which is a unique feature among holistic methods [START_REF] Zhao | Face recognition: A literature survey[END_REF]. It is therefore our algorithm of choice for FoP.

Face recognition algorithms are very sensitive to paramaters settings. For this purpose, we conducted several tests to determine the best parameter set. Experiments conducted on a sample dataset showed that it is not possible to maintain high values for both precision and recall, as depicted in Figure 3. This is due to the fact that the task of face recognition is complex and is still a hard research issue. As our system will handle a large volume of pictures, and that our goal 5 Ranging from --, -, +, ++ for respectively no person identification, linkage of person "related to" a resource, linkage of region of picture with a resource, fine-grained information such as person position, hair colour, etc. 6 The baseline in this case was a learnt model using a face recognition algorithm. 7 Relates to the ability of the system to reinfine its person recognition mechanisms beyond the learnt model. is to offer correctly labeled data, we decided to trade recall for precision. For this first model, as depicted in Figure 6 on the iteration zero, we chose a threshold of 57 (which is the maximum authorized distance between two pictures to be considered neighbours), that maximizes the recall for a perfect precision. However the recall still remains low and very few pictures would be handled. We show in section V-B, how the continuous update of the model allows to overcome this low recall issue.

In FoP we demonstrate our approach on recognizing French politicians in national news. To boostrap our model, we therefore required an initial dataset with correctly labeled pictures. umerous celebrities are identified in the LOD-Cloud, mainly in DBPedia and Freebase. Regarding persons, both databases are linked together, not through the LOD-Cloud, but through the use of Wikipedia identifier.

For our needs, Freebase presented two main advantages. Firstly, the database has been manually generated and is therefore less error prone than the automatic generation of DBPedia. Secondly, for persons, Freebase usually provides links to several pictures which is not the case for DBPedia. We used the following approach to overcome potential issues in DBPedia.

We first extracted the list of living politicians in France along to their pictures from Freebase using the MQL query shown in figure 4. For each person, the number of pictures [{ "mid": null, "name": null, "id": null, "type": "/government/politician", "/common/topic/image": [{ "id": null }], "wiki_en:key": { "/type/key/namespace":"/wikipedia/en_id", "value": null }, "ns0:type": { "id": "/people/deceased_person", "optional": "forbidden" }, "/people/person/nationality": "France" }] Fig. 4. MQL Query to retrieve living french politicians along to their pictures and Wikipedia ID from Freebase ranges from one to three. We then use these pictures and their associated label (i.e. the person identifier) to train a first version of the face recognition model. Then we retrieved for each person a second set of pictures from DBPedia using the Wikipedia identifier as previously stated. We used the previously trained model to assess the presence of the person and if validated, we updated the previous model.

V. NEVER-ENDING LEARNING (STEADY STATE)

The never-ending learning part of FoP is made of two successive steps. In the first one FoP is querying the LoD-Cloud for new data and in the second one, it is providing new data to this latter. The exchange of data between FoP and the LoD-cloud is giving rise to raising edges of data called "ticks", while the falling edges (from the LoD-cloud to FoP) are respectively called "tocks". The FoP system data leveraging flow is illustrated in Figure 2. These two distinct percolations of data are of uneven complexity. In what follows we first depict tocks phases, as being a more straightforward process and which initiate the FoP never-ending learner.

We then present ticks occurring in FoP.

A. Tocks

Tocks are data queried from the LoD-cloud that enrich the FoP learner. A first tock occurred when we initialized FoPas described in the previous section. However data from the LOD-Cloud are not static and are subject to change over time. For instance, new politicians may be added to Freebase or DBPedia, or new pictures may be added for a person. That is the reason why other tocks occur at regular interval of time. At further tocks, FoP queries against Freebase and DBPedia for new Picture-Person links, following the same process as described previously for newly added persons. For each of the new pictures that were introduced in Freebase or DBPedia since the last query, FoP updates the learnt model. FoP then updates its internal triple store by introducing a new person along the image(s) in which he/she appears in. At each tock, the FoP face recognition model is therefore enhanced using LoD-based data. Conversely, the LoD based data are enhanced at each tick.

B. Ticks

A tick is initiated by receiving an update of one of the RSS feeds to which FoP has subscribed. For each article FoP extracts pictures, detects faces, and matches them against the previously trained model. If a person is detected using the face recognition model, we validate its presence by searching the article text for his/her name. If validated, annotated feeds articles are added to the internal database, and the model is updated using the newly detected face. A tick can therefore also generate model updates of the FoP recognition model. Updating the model allows us to overcome the initial low recall issue. As shown in Figure 6, for a threshold of 57, we maintain a very high precision (above .93).

In the mean time, recall greatly improved from .10 to .35. For greater values of the threshold the recall improvement is far greater but it implies serious degradation of the precision to unacceptable values, that would result in numerous falsely labeled pictures. Aside from updating the model and storing annotated feeds articles for later consultation by FoP users, FoP leverages Linked Data at ticks.

C. Providing linked data

The ontology for media resources (ma-ont 10 ) defines media fragment as sub-parts of a media. In our purpose we use the relationship hasFragment to identify relationship between the original images and the faces it contains. Mediafragments 11 makes it possible to specify rectangular clipping of images by appending its coordinates to the original URI. This is particularly useful for identifying several persons in a picture, since one can specify the region where the face of a person is located. Due to domain coverage shortcomings of ma-ont, we extended the ontology to be able to identify persons within an image. ma-ont has a property called features that is to be used for actor in movies. In our case, we intend to define that a person is present in picture, not acting. We therefore defined an object property IsInPicture whose domain is a foaf:Person and whose range is the intersection of ma-ont#Image and ma-ont#MediaFragment.

An depiction of the Ontology in use is given in Figure 5. This enables, among other, to search for pictures containing multiple people, as we demonstrate in the next section.

VI. USING FOP

Our FoP never ending learner is available online at http: //demo-satin.univ-st-etienne.fr/facesofpolitics/. Figure 7 shows the current trained face recognition model fueling FoP. FoP is currently subscribing to the politicians news feeds of the New York Times, the BBC, Le Monde, Liberation, and El País. Using these settings, we want to demonstrate the benefits of never-ending learning from Linked Data and never-ending lifting new Linked Data in return, plus the fine-grained representation that is then made possible.

On FoP Website, it is possible to browse latest annotated feeds. It offers a list of discovered persons along the part of the multimedia in which they were found, and the context of the original feed article. This is the primary task for a new FoP user in order to get familiar with the system.

A more advanced task is to make article curations on single or multiple person presence selection. By switching to another GUI area, one can query FoP data using SPARQL. This encompasses article retrieval based on the presence of one known person in the FoP triplestore. It is also possible to create a curation of articles from different RSS feeds by specifying several persons that must be present in the illustration of the article. Let us illustrate an example of a fine-grained query that FoP offers. One can query FoP for all pictures and associated articles in which one person is placed left to another in the picture.

For example, let us query FoP for any picture in which Jean-Marc Ayrault, French prime minister at the time of writing, is depicted left to Franc ¸ois Hollande, French President, in all pictures in which FoP recognized both of them. This can be achieved using the SPARQL query 12 provided at Figure 8. The first article matching this query is given at Figure 9 as taken from one major French media website 13 .

Full RDF Dumps are also available from the previously specified URL 14 .

VII. CONCLUSION

In this paper we presented FoP, a never-ending face recognition learner that leverages annotated faces from RSS feeds through a continuous virtuous circle between the LoDcloud and FoP recognition model. Subscribing to several RSS feeds, it is able to recognize famous politicians, to auto-enhance its model and to serve the data as linked open data.

By using a face recognition model, bootstraped with LOD-Cloud data, we are able to ensure a high precision for the presence of a person in a picture. The never-ending learning 12 The following prefixes were ommitted for formating considerations: PREFIX dbpedia:<http://dbpedia.org/resource/>, PREFIX fop:<http://demo-satin.telecom-st-etienne.fr/facesof politics/public/ontologies/pplinpic#>, and PREFIX maont: <http://www.w3.org/ns/ma-ont#> 13 http://www.europe1.fr/Politique/Chomage-la-methode-Coue-de-Hollandeet-Ayrault-1686655/ 14 http://demo-satin.telecom-st-etienne.fr/facesofpolitics/rdf SELECT ?media WHERE { dbpedia:Jean-Marc_Ayrault fop:isInPictu re ?medfragJMA . dbpedia:Fran%C3%A7ois_Hollande fop:isIn Picture ?medfragFH . ?media maont:hasFragment ?medfragJMA . ?media maont:hasFragment ?medfragFH . BIND(str(?medfragJMA) as ?newJMAmedia). BIND(str(?medfragFH) as ?newFHmedia) . BIND(STRBEFORE(STRAFTER(?newJMAmedia, '?xywh=pixel:'), ",") AS ?JMAabs) BIND(STRBEFORE(STRAFTER(?newFHmedia, '?xywh=pixel:'), ",") AS ?FHabs) FILTER (xsd:decimal(?JMAabs) < xsd:decimal(?FHabs)) } approach allows us to overcome the initial low recall issue. Finally, we provide a publicly available dataset of politicians pictures that is constantly growing and being enhanced.

In the future, we plan to study the evolution of FoP over time, especially the evolution of its precision and recall as it scales for more faces.We will aim at generalizing our system to foreign politician but also other applications like sport as well and larger categories of persons.

Fig. 1 .

 1 Fig. 1. FoP overview. Left part presents the bootstrapping step (i.e transient state) while the right part shows the steady state step of the system.

Fig. 3 .

 3 Fig. 3. Face recognition : influence of Binary Local Pattern parameter on precision and recall

theFig. 2 .

 2 Fig. 2. Never-ending face recognizing and semantizing tick/tock model.

Fig. 5 .

 5 Fig.5. People In Picture Ontology in use, for a picture having two people depicted. See Figure8for the SPARQL Query and Figure9for the resulting picture.

Fig. 6 .

 6 Fig.6. Influence of updates on precision and recall. Note that for readibility, scale of threshold has been inverted between the two pictures.

Fig. 7 .

 7 Fig. 7. Primary user interface for reading enriched RSS articles from subscribed feeds.

Fig. 8 .

 8 Fig. 8. SPARQL query for all pictures with Jean-Marc Ayrault positionned left to Franc ¸ois Hollande.

Fig. 9 .

 9 Fig. 9. Media retrieved by FoP using query provided by Figure 8

http://motools.sourceforge.net/event/event.html

http://ladoga.graphics.cs.cmu.edu/xinleic/NEILWeb/content.php?category= Objects\&class=actor

http://www.freebase.com

Ranging from --, -, +, ++ for respectively personal data, small datasets (in hundred or thousands), large dataset (hundred of thousaunds), Web scale). N.S. stands for "not specified".


Meropi Topalidou
email: meropi.topalidou@inria.fr

Daisuke Kase
email: daisuke.kase@u-bordeaux.fr

Thomas Boraud
email: thomas.boraud@u-bordeaux.fr

Nicolas Rougier
email: nicolas.rougier@inria.fr

The formation of habits: a computational model mixing reinforcement and Hebbian learning

Keywords: basal ganglia, decision making, habits, Hebbian learning, reinforcement learning

If basal ganglia are widely accepted to participate in the high-level cognitive function of decision-making, their role is less clear regarding the formation of habits. One of the biggest problem is to understand how goal-directed actions are transformed into habitual responses, or, said differently, how an animal can shift from an action-outcome (A-O) system to a stimulus-response (S-R) one while keeping a consistent behaviour.

)). Hebbian learning has been added at the cortical level such that the model learns each time a move is issued, rewarded or not. Then, by inhibiting the output nuclei of the model (GPi), we show how learning has been transferred from the basal ganglia to the cortex, simply as a consequence of the statistics of the choice. Because best (in the sense of most rewarded) actions are chosen more often, this directly impacts the amount of Hebbian learning and lead to the formation of habits within the cortex.

These results have been confirmed in monkeys (unpublished data at the time of writing) doing the same tasks where the BG has been inactivated using muscimol. This tends to show that the basal ganglia implicitely teach the cortex in order for it to learn the values of new options. In the end, the cortex is able to solve the task perfectly, even if it exhibits slower reaction times.

Introduction

According to [START_REF] Schneider | Controlled and automatic human information processing: I. detection, search, and attention[END_REF], a behaviour is automatic (i.e. becomes an habit) if a sensory events always elicit the same behaviour, even if the subject is doing something else. Think, for example, of someone entering a dark room while talking on the phone and switching on the light without ever really thinking about it. How this behaviour is acquired in the first place? How do we learn such habits? [START_REF] Seger | A critical review of habit learning and the basal ganglia[END_REF], characterized habit learning using five definitional features: inflexible, incremental, unconscious, automatic, and insensitive to reinforcer devaluation. This tentative definition seems to be clearly in opposition with decision making that we could think of as flexible and highly sensitive to reinforcer devaluation. However, there are more and more evidences these two types of learning are somehow linked together [START_REF] Yin | The role of the basal ganglia in habit formation[END_REF]), the question being how?

In a recent (unpublished) study, monkeys have been tested on a two-armed bandit task using a pharmacological approach, combining both decision making and procedural learning. Primates have been daily accustomed with the setup which is composed of four buttons placed on different directions (0, 90, 180 and 270) and another one on central position which detects the contact with monkeys hands. These buttons correspond to the four possible appearance directions of a cursor on a perpendicular screen. The monkeys initiated a trial keeping their hand on the central button, which induced the appearance of the cursor in the central position of the screen. After a random delay (0.5-1.5 s), two cues appeared in two (out of four) different positions determined randomly for each trial. Two experimental conditions were alternated by blocks of ten trials. On Habitual Condition (HC), the two cues (HC1 and HC2) are the ones with which the animals have been trained. Each cue had a fixed probability for monkeys to be rewarded (PHC1=0.75 and PHC2=0.25). The nature and the probability of each cue remained the same during each working session and between each working session. On Novelty Condition (NC), the two cues presented are new (NC1 and NC2). Each cue had a fixed probability for monkeys to be rewarded (PNC1=0.75 and PNC2=0.25). Once the cues are shown, the monkeys had a delay period (0.5-1.5s) to press the button according to one cue during a random time (0.5-1.5s). The cursor appeared on the chosen cue. An "end-of-trial" signal corresponding to the disappearance of the cursor indicated to the monkeys that the trial is actually finished. Monkeys were rewarded (0.3 ml of water) or not according to the reward probability of the chosen target. They could then start a new trial after an inter-trial interval included between 500ms and 1.5 ms. The procedure is summarised in 1 In one condition, the internal part of the Globus Pallidus (the main output structure of the BG) is injected with a saline solution (no effect) and in the other condition, it is injected with muscimol (inactivation). Results tend to show that performances related to familiar cues stay unchanged, independently of GPi inactivation, while learning of new cues is deeply impacted when GPi has been inactivated. This tends to suggest BG might be critical in learning decision and this learning can be later transferred to the cortex. In accordance with this hypothesis, we build a computational model whose architecture is described in the next section.

Methods

The architectural basis of the model has been originally described in [START_REF] Guthrie | Interaction between cognitive and motor cortico-basal ganglia loops during decision making: a computational study[END_REF] where authors introduced a biophysical model of action selection that can solve a two-arm bandit task, such as the one describe above. Two parallel action selection pathways compose the model with inputs from distinct areas of the cortex: one for handling the cognitive action selection, and the other for the motor selection. The model includes the cortex (Cx), the thalamus (Th) and several nuclei of the BG: striatum (Str), the subthalamic nuclei (STN) and the globus pallidus internal and external (GPi, GPe). Each module is made of a closed-loop positive feedback direct pathway (Cx-Str-GPi-Th-Cx) and two closedloop negative feedbacks, indirect pathway (Cx-Str-GPe-STN-GPi-Th-Cx) and hyperdirect pathway (Cx-STN-GPi-Th-Cx), and is based on the center-surround architecture of [START_REF] Mink | The basal ganglia: focused selection and inhibition of competing motor programs[END_REF]. The interactions between these three pathways are able to induce an action selection at the motor level. However, the task requires first the actual selection of the best cue before performing the corresponding motor action. In the [START_REF] Guthrie | Interaction between cognitive and motor cortico-basal ganglia loops during decision making: a computational study[END_REF] model, this is implemented at the striatal level where a dopamine reward signal is used to implement a simple value-based learning. The general architectural of the model is illustrated on Figure 2.

In the original model, the inactivation of the basal ganglia output (GPi) results in the inability of the model to make a decision since there is no competitive mechanism at the cortical level. We thus added lateral connections in each cortical modules (self-excitation and surround inhibition) such that a unique cognitive and motor decision can be made. At this point, there is no guarantee that the motor decision corresponds to the cognitive ones. The model can choose a cue A but moves toward the location of a cue B. To overcome this problem, we also need to establish a cross-talking between the different cortical modules, independently of the BG pathways. This has been made using excitatory connections from and to the associative cortical module. Hebbian learning in cortical level allows the cortex to make a consistent decision in the absence of GPi, even if it does not guarantee to make the optimal decision. One important property of the cortical decision is that it is significantly slower than the BG decision. This can be shown by measuring the time of motor decision; defined as the time required for the difference between the two most activated units in the motor cortex to become greater than a given threshold (40Hz). Before learning, the BG decision time (GPi is intact) is around 250ms while the cortical decision time (GPi is disabled) is around 800 ms. This difference in timing is actually critical for the BG to teach the cortex as explained in the results section.

Results

We tested the model using 4 different paradigms:

• HC/GPi: Habitual condition using already learned stimuli with intact GPi.

• HC/NoGPi: Habitual condition using already learned stimuli with lesioned GPi.

• NC/GPi: Novel condition using non familiar stimuli with intact GPi.

• NC/NoGPi: Novel condition using non familiar stimuli with lesioned GPi.

Each condition has been tested for 250 experiments where each experiment consists in 120 consecutive trials (presentation of the cues, decision, potential reward and reset). Before starting an new experiment, the model is trained on the familiar stimuli until the performance is over 0.95. Performances were measured as the ratio of optimal choices compared to the number of trials. Response time has been recorded as the time of the motor decision. This time is relative to the stimulus onset (t=500ms).

As shown in 3a, our results are equivalent to the experiments in monkeys (3b). In the habitual condition, performances are optimal with or without lesion, indicating the cortex is able to make the optimal decision without the help of the basal ganglia. However, in the novel condition, things are quite different. For the intact model, the model starts a trial at chance level, giving random choices. Nevertheless, after a few trials (around 15), it reaches a near-optimal performance, indicating the model has learned the respective reward probability associated with each cue. For the lesioned model, the performances stay at the level of chance, indicating the cortex is unable to learn the task "on its own". It is to be noted that due to Hebbian learning, the lesioned model tend to first choose a given random cue and stick to this choice until the end of the experiment. If this is the right cue, the performance can reach 1 for a single experiment, but over the course of the 250 experiments, the mean performance is around 0.5.

Conclusion

The aim of this model is to gain a better understanding of the role of the basal ganglia in the formation of habits. It is based on a previous model by [START_REF] Guthrie | Interaction between cognitive and motor cortico-basal ganglia loops during decision making: a computational study[END_REF] that explain the dynamic of action selection in the BG. The model has been further refined with connections at the cortical level which are consistent with neuro-anatomy. We also implemented Hebbian learning at the cortical level, independently of reward. However, since BG helped to choose the best action anytime, this results in having cortical learning to be naturally modulated according to the value of the different cue, simply because the best cue is chosen more often. After learning, the cortex is able to choose the best cue without help of the BG, hence forming a new habit.

 1), with or without GPi (the dashed line is not shown, because it coexists with the straight one). In NC, only the intact model (with GPi) is able to learn the new stimuli while lesioned model performances stay at the level of chance. 3b) Monkeys' performances are analogous to the models.


Raphael Falco
email: raphael.falco@mines-paristech.fr

The contribution of "human" and "non-human" actors to a collaborative health and safety inspection process for civilian nuclear power

Keywords:

As the international standards OHSAS 18001 and ISO 31000 bear witness, interest in safety management is growing worldwide. At the same time, it is becoming more and more complex, which has led to increasing reliance on procedures. On the one hand, control procedures are embodied in inspection services, who are gaining in knowledge and experience and creating frameworks and tools. These changes have provided a better understanding and definition of the role and responsibilities of inspectors in compliance control. On the other hand, industries need to adapt to cultural and technical changes resulting from economic needs. The complexity of the situation has led industries to adopt management tools; amongst them new, but promising software packages. Decision support systems are growing in popularity with safety stakeholders. Feedback, indicators, monitoring: the toolbox continues to expand. At the same time, the information that is shared is expanding. Our work relates to the regulation process: do enhanced legal powers lead to improved control? Improvements in safety require a virtuous relationship between stakeholders and improved communication. This article looks in detail at the role of occupational health and safety inspectors in France and their relationships with industrial partners.

Introduction

On 21 September 2001 a disaster occurred at the AZF fertiliser factory in Toulouse, France. Inspection reports 1 stated that the hangar in which the explosion occurred did not comply with chemical industry regulations in force at the time. In its judgment of 24 January 2013, the Administrative Court of Appeal of Bordeaux acknowledged, for the first time in France, that the State was partially responsible. Over and above the legal implications, this ruling raised questions about the limitations of the control model of safety. Classically, safety is guaranteed by safety management systems [START_REF] Cambon | Towards a new tool for measuring Safety Management Systems Performance[END_REF] that are developed by businesses, and legal provisions that are enforced by State entities. Typically, this relationship manifests in various processes (such as regulatory monitoring and legal compliance) and inspections.

Inspections, which are one of the founding principles for the control of industrial installations, mobilize various human and non-human actors [START_REF] Law | Notes on the theory of the Actor-network: ordering, strategy and heterogeneity[END_REF]. The considerable progress made in information technology and communication has led to the emergence of "non-human" actors in the form of databases, decision support software, and more recently, communication and collaborative solutions with high added value.

The "system of actors" has therefore become both more extensive and more complicated. Consequently, a characterization of the relationships and interactions between human actors, non-human actors, and human and non-human actors merits close analysis.

In this study we focus on the French Atomic Energy Commission (Commissariat à l'énergie atomique et aux énergies alternatives, CEA) to characterize this complexity. The CEA is a longstanding member of the French nuclear community. In addition to its inspection responsibilities (nuclear security, occupational health and safety, and environment), it lies at the crossroads between central government, which is driven by political and industrial imperatives [START_REF] Foasso | Du service à l'autorité : les ingénieurs des Mines et la sûreté nucléaire[END_REF] and local facilities that must respond to technical and scientific requirements, and human and organizational needs (workers, suppliers, local residents), which are distributed across the country. In practice the CEA has two hats: it is both "controlled" and it is the "controller". The latter role is equally important in terms of internal (the State and accredited bodies) and external (IGN, CSNSQ 2 ) controls.

This paper begins with a general typology of stakeholders and their organization. Next, the theoretical framework is described in detail in order to integrate it into the framework of our work and with the aim of modelling collaboration between actors. Finally we analyse our initial, exploratory field interviews, which demonstrate how a collaborative management software platform is used in the actor network.

The controller/ controlled relationship: current practice

Classically, the actors involved in nuclear control activities are divided into internal and external stakeholders. In this section, In order to organize and classify the actors, we rely on the [START_REF] Chiapello | Les typologies des modes de contrôle et leurs facteurs de contingence: un essai d'organisation de la littérature[END_REF] typology of control process. It permits to categorize the principal actors involved in control into four subsystems: self-regulation, internal inspection, external agencies and State inspectors.

The CEA

French risk prevention regulations define the obligations of employers and operators. These obligations, which relate to the fields of Occupational Health and Safety (OHS), the environment, and nuclear safety, require operators to have a good understanding of the regulatory framework. They must both meet regulatory requirements3 and ensure that they are followed in the field.

Most CEA centres have been awarded triple certification: ISO 9001 (quality management), OHSAS 18001 (occupational health and safety) and ISO 14001 (environmental management). In order to meet the requirements of the French government and international standards, the CEA's central administration has developed a Quality, Safety and Environment policy, which is supported by an internal Risk Management Department (Pôle de Maîtrise des Risques). The policy is based on the following safety standards:

 Design of facilities must adhere to strict rules.  Construction must meet the highest quality standards and include multiple control checks.  Rigorous, programmed maintenance schedules that incorporate significant safety margins with respect to the failure of materials.  A prudent approach to operations, framed by clearly specified rules,  Periodic re-evaluations of safety, leading to action plans that reflect the most recent safety standards.

The CEA must be able to respond to a wide variety of risks. This high level of vulnerability has prompted the deployment of a complex safety management system (SMS) that comprises internal experts and external service providers. The semi-exploratory interviews that we carried out with members of the various inspection services made it possible to establish an overview of the actors involved in nuclear control (Figure 1). 2013) characterized the internal actors involved in the SMS: the "prevention specialists". Despite the diversity of job titles (e.g. "safety officer", "safety manager" or even "QSE officer"), a clear typology emerged (Table 1). The CEA shares the commitment to safety culture that is typically found in the nuclear sector. Each worker is a "ground-level" actor. OHS "fieldworkers" work in the safety and security services at facilities and are responsible for internal self-regulation. OHS "managers" are responsible for internal audits and inspections; they work at managerial level at sites and in the CEA's Risk Management Department, which is under the control of the central administration.

Self-regulation

The head of a facility (the facility director) holds delegated authority from the site director; this delegation confers authority to decide and execute the actions needed to ensure risk management at the facility and all other areas of safety.

Support is provided by the facility's OHS unit. This is composed of engineers (OHS fieldworkers, as described in [START_REF]  Audiffren | A quantitative analysis of health, safety and environment policy in France[END_REF], who are responsible for local controls.

The main responsibility of the facility director is to provide Level 1 controls, which involves verification that the facility complies with regulations, and the management of safety and security. The service is guided by recommendations provided by OHS managers and CEA best practice4 . It represents the front line of safety, and is subject to both internal (IGN, CSNSQ) and external (ASN5 , DREAL6 , control agency) inspections.

In order to meet these internal and external requirements, the OHS unit is responsible for local self-regulation. This involves the following processes:

 Regulatory monitoring (internal, international and legal standards).

 Local compliance assessments.  Planning of remedial actions.

 Management of priorities.

The distinctive feature of the unit is that it is close to the situation on ground and has considerable expertise. As it is centralizes the facility's technical, human and organizational knowledge, it is also an asset in dealing with the various State inspectors and auditors. It constitutes the initial point of contact with external agencies and is able to respond in many different ways. For example, one facility has designed and developed a computerized system for monitoring actions to be taken in cases of non-compliance with regulatory requirements.

However, the effectiveness of self-regulation often depends on the quality of the relationship between OHS professionals and the operator on the one hand, and between OHS professionals and the facility's inspector on the other.

Figure 3 shows how self-regulation can be organized within a facility.  Level 1: a physical inspection of facilities and activities (IGN).

 Level 2: an evaluation of the SMS (verification of processes and documentation).

Interlocutors include the site director, the facility manager and its OHS mangers and units.

The exercise consists of an inspection and audits prepared by the central administration carried out by the actors listed above, and internal audits prepared by OHS managers. In both cases, they are based on feedback from the field (local expressions of needs) and the broad headings found in international standards (measurement, continuous improvement, etc.). This makes it possible to verify compliance with the facility's safety and security policy and suggest improvements in response to feedback that is shared with other sites.

However, the actors involved in these internal controls report that not all information is shared. While the audits that are carried out by OHS managers are welcomed and enable open and honest discussion, the stakes are high in PMR inspections (which are viewed in the same way as State inspections), and discussion is strictly limited to meeting the demands of inspectors.

Figure 4 The organization of internal controls

Non-State control agencies

Inspection services can share their workload with accredited organizations such as control, consultancy and advisory agencies. These agencies provide corporate clients with expertise that is deployed directly on-site by specialized professionals in order to carry out various checks (fire extinguishers, equipment compliance, etc.). This "audit" is carried out by an external expert who is accredited by the French Accreditation Committee (Comité Français d'Accréditation, COFRAC) and it is another key process. It consists of the "verification and assessment of all aspects of a structure, an organization or a system" (Dictionary of the Environment). Its objective is to highlight "non-compliance with standards or regulatory requirements" and "the strengths and weaknesses of the company's approach to occupational risk prevention" (Esen Education7 ).

These control agency auditors contribute significant expertise in the investigative techniques (field visits, interviews, reviews of documentation) deployed in an audit [START_REF] Innes | Health and Safety Auditing[END_REF]. They are involved in both regulatory compliance assessments (e.g. for classified installations) and normative audits (e.g. compliance with ISO 140018 ). Consequently, they are seen as external experts whose opinion on the operation of the facility is both valued and respected. Nevertheless, OHS units and facility directors do not share any more information with them than with internal auditors.

There is one more external participant whose opinion can create problems for the facility.

State inspectors

Current State inspections

Safety controls are the primordial responsibility of State inspection services. These entities work with accredited organizations that provide complementary services or have other responsibilities delegated to them by the State; they can also carry out internal controls.

Our study looks at three specific inspections that apply to the nuclear industry:

 Inspectors of Classified Installations;  Labour Inspectors; and  Nuclear Inspectors.

Figure 5 shows how these three services are organized, from national to local level: Inspections are carried out nationwide and are the responsibility of both the central administration and decentralized services. Policies are defined at national level and integrate local-level feedback that contributes to centralized procedures which are deployed according to local needs. They are framed by a multi-year national strategic plan, which is divided into yearly national actions applied to regions. These inspections share several responsibilities:

 specification of the regulatory framework;  monitoring of companies; and  public information.

These principal responsibilities of each inspectorate are complemented by specific responsibilities that apply to individual inspection services:

 Labour Inspectorate: provision of advice to business, the fight against black-market work, accident inquiries.  Inspectorate of Classified Installations: accident inquiries, complaint management.  Nuclear Inspectorate: monitoring of significant events involving radiation.

Nuclear inspectors in particular benefit from a number of prerogatives:

 Unannounced and unimpeded visits at any time 9 .  The right of immediate access to all mandatory documentation.  The right to interview any employee/ manager/ director with respect to any legal provision.

As for the Labour Inspectorate, it has an arsenal of punitive measures to facilitate its work:

 Procès-verbaux (official reports of observed offences)  Mises en demeure (time-limited enforcement notices that are issued by the inspector or the regional director as provided for by the French Labour Code)

Changes in inspection practice

The current form of inspections in the civilian nuclear sector finds its origins in a Napoleonic decree of 1810 on polluting sites 10 . The regulation of industrial facilities came about through a "combination of competing interests" (Bonnaud 2002, p.177), at a time when it did not make sense to distinguish between industrial development and inspection. This combination of liberalism and State intervention has guided regulation, which supports development through the implementation of best practices (Bonnaud, 2002, p.178). Initially, the role of the inspector was entrusted to the municipal police force and concerned the maintenance of public order under the supervision of the préfet (the appointed local representative of the State).

During the nineteenth century, safety at classified installations was perceived primarily in terms of public health. The responsibilities of inspectors tended to focus on hygiene 11 . At this time, inspectors were mainly recruited from the medical world (doctors, pharmacists, etc.) and there were few technical experts (e.g. from the Ministries of Industry, Bridges and Highways) (Bonnaud 2002, p.186).

Inspection procedures for classified installations were formalized at the beginning of the twentieth century. The principle of the inspection visit was established, and a body of professional experts responsible for their inspection appeared. This came under the responsibility of the Labour Inspectorate (Act of 2 November 1892) immediately after the First World War (Act of 19 December 1917). This change made it possible for the State to take full control of industrial practices and to homogenize them at the national level.

In 1966, a catastrophe at the Feyzin refinery near Lyon in France highlighted two weaknesses of the system: the lack of technical knowledge of labour inspectors and regulations that had not kept pace with industrial practice (Bonnaud, 2002, p 255.). Consequently, responsibility for the inspection of classified installations was handed to the Ministry of Industry. This transfer led to the embodiment of responsibility for technical, administrative and legal issues in a single person: the inspector. It also enhanced the legitimacy of the actions of inspectors of classified installations and left labour inspectors to focus on their priority, the health and safety of workers.

At the same time, the emergence of military and civilian nuclear energy led to the creation of a new profession: the inspector of nuclear installations. It should be noted that given the specificities of the nuclear sector, some occupational health and safety obligations were transferred from the labour inspectorate to the nuclear inspectorate, resulting in joint inspections and the transfer of skills and knowledge.

Although the three inspection services share a common origin, it is important to note the significant cultural difference between labour inspectors and inspectors of classified and nuclear installations. In the latter services "technical" inspectors share the same industrial engineering background, which means that personnel often move between them. This similarity was highlighted by the Feyzin disaster. The "new" inspectors of classified facilities based their relationship with the industry on technical issues, unlike the legal approach taken by the Labour Inspectorate (Bonnaud, 2002, p. 255).

Framework

We based our work on a theoretical base and the use of a society platform. We selected two major sociological theories in order to analyse and understand the interactions between the actors involved in control activities: actor-network theory (ANT) and social regulation theory (SRT). The former makes it possible to analyse the broader organization in terms of technical objects (human or non-human actors). The latter makes it possible to better understand the relationship between external and self-regulation. The management tool choose has improve a ten years assessment in various industrial fields (Energy, transport, aeronautic, petroleum, etc…) and propose an adaptable framework which permit the creation of a specific tool for the experimentation.

Theoretical base

Actor-network theory

Various authors (Latour, 1991;[START_REF] Callon | Techno-economic networks and irreversibility[END_REF][START_REF] Law | Notes on the theory of the Actor-network: ordering, strategy and heterogeneity[END_REF] have investigated the influence of the technical object on its environment (geographical, political, social, etc.). Madeleine [START_REF] Akrich | La gestion de la recherche[END_REF] studied the influence of human and non-human actors on each other. From this perspective the technical object is not passive, but instead participates in the creation of the socio-economic-technical system [START_REF] Law | Notes on the theory of the Actor-network: ordering, strategy and heterogeneity[END_REF]. The distinguishing feature of ANT is that it sees both human and non-human stakeholders as equal, and actors communicate via a "translation centre".

The relationship between controllers and the controlled, which combines physical characteristics and forms of usage [START_REF] Akrich | Le médicament comme objet technique[END_REF] is rooted in this framework. As [START_REF] Lascoumes | Gouverner par les instruments[END_REF] points out, the focus is not on theories, but the instruments and devices that they give rise to. In other words, it is tools ("technical objects") that enable the management of nuclear safety, notably with respect to radiation protection.

The concept of "Punctualization" [START_REF] Law | Notes on the theory of the Actor-network: ordering, strategy and heterogeneity[END_REF] is useful in clarifying the system of actors. Actors are defined as local networks that are transformed into "black boxes" in the form of irreducible resources in order to improve the creation of the network in question. For example, increasing reliance on procedures leads to greater weight being given to legal, technical and accounting provisions and a generalization of norms and standards, which can be grouped under the heading "regulation".

The heterogeneity of actors creates a need for translation [START_REF] Callon | Éléments pour une sociologie de la traduction : la domestication des coquilles St-Jacques et des marins pêcheurs dans la baie de St. Brieuc. L'Année Sociologique[END_REF]. Translation centres undertake the work of making the network intelligible. For example, the profusion of regulations has led to the development of management tools (Moisdon, 2005) that represent "arrangements" for people and "objects". These tools make it possible to highlight the different dynamics at work in "orienting" the network [START_REF] Law | Notes on the theory of the Actor-network: ordering, strategy and heterogeneity[END_REF]. Actors and organizations "translate" parts of the network in order to orient it towards their "aspirations". Translation is also therefore a way to exercise power and is seen, for example, in the interpretation of regulatory texts by inspectors according to the situation.

ANT highlights three safety actor profiles:

 People: meaning both physical human beings and their skills and ability to adapt (Sonntag, 2007). Consequently, an engineer who is an OHS manager is both an facility auditor and an IGN controller.  Materials: represented by measuring instruments, regulatory texts, etc. Materials can direct the way in which people behave [START_REF] Akrich | Comment décrire les objets techniques[END_REF]. At the CEA for example, legislation is translated by a dedicated service which aims to provide operational guidance to OHS professionals. However, this translation centre lacks resources, and it has become necessary to have a further translation of the actors involved in "legal regulation" and "normative regulation" in order to keep up to date.  Management tools: these are innovative technical objects used to analyse the requirements of authorities that are phrased in terms of controls.

Information technology is widely used by stakeholders who use it rationalize and justify their actions. These "mental prosthesis" (as they were termed by Moisdon, 2005), are targeted at the level of the system and form an integral part of an ongoing process of "governmentality". For example, the CEA has developed a nationwide management tool in the form of an intranet that brings together and centralizes information about each site and each of its facilities.

These tools can also improve collaboration between controllers and controlled. [START_REF] Bollecker | La dimension sociologique du contrôle de gestion par l'analyse des relations de coopération entre contrôleurs de gestion et responsables opérationnels[END_REF] argues that the outcome of controls depends first and foremost on a mutual understanding of the benefits. When performance is linked to objectives that include control criteria, efficiency is guaranteed. The design, development and use of these technical objects is therefore paramount in order to ensure effective controls and enhance interactions between actors.

The correct translation of the aspirations of people via management tools operates through four fundaments:

 Sustainable: the need for sustainable actors (e.g. regulations).

 Mobile: the need for mobile actors (e.g. inspectors or OHS specialists).

 Anticipation: the need for responsive translation centres and alert actors (e.g. through regulatory monitoring processes).  Strategy: the need for "visionary" and well-organized actors (e.g. SMS).

In the nuclear context, a number of specialized management tools with varying capabilities have emerged in the areas of OHS, the environment and nuclear safety (Vigneron et al., 2013).

 Simple regulatory monitoring (public structures, publishers of legal information).  Consulting (control or advisory agencies).  In-house solutions (internal information systems).  Specialised publishers (integrated health, safety and environment performance management tools including assessment and reporting tools, action plans and performance indicators).

Social regulation theory

If ANT laid the groundwork for the system of actors, social regulation theory (SRT) provides a better understanding of the interactions between them. It argues that any organization is governed by regulations (de Terssac, 2003, p.10): regulatory controls on the one hand and self-regulation on the other, which cohabit via negotiations that lead to joint regulation (Figure 6). Regulation is mainly used as a normative concept [START_REF] De Terssac | La théorie de la régulation sociale de Jean-Daniel Reynaud[END_REF]: in other words, adjustments to rules (injunctions, prohibitions) act as an organizing principle (Reynaud, 2005) This approach to safety management is partially based on the argument put forward by March and Simon (1958) that actions do not flow naturally from rules. Similarly, organizations are not regulated by a single optimal rationality. Instead, there is an ongoing process of adaptation centred on interactions between regulatory controls on the one hand (the State, central administration, management) and autonomous regulation (decentralized State services, executive agencies, subsidiaries, etc.) on the other.

Here, we focus specifically on regulations that are designed to manage interactions between control organizations (internal or external) and those they control (who may themselves be controllers).

Control begins with legal provisions put in place by the State and self-regulation. Consequently, as [START_REF] Jammaud | Théorie de la régulation sociale et intelligence du droit[END_REF] underlines, there is a plurality of sources of rules that are not only legal or statutory. For example, the CEA must comply with both external regulations, and its own General Operating Rules. During an inspection the two sets of regulations (external and internal) are harmonised through a mutual adjustment process (letters detailing corrective actions to be undertaken known as lettres de suite) leading to a negotiated compromise (Reynaud, 2005) and joint regulation (the operating license).

Rules are adjusted by each party via adaptation mechanisms, notably through demonstrated respect for effective compliance [START_REF] De Terssac | De la sécurité affichée à la sécurité effective: l'invention de la règles d'usage[END_REF]. The process takes into account how regulations are actually applied in the field (Alter, 2003), for example during site visits by State entities, and the implementation of their recommendations. Effective respect requires the implementation of the usage rules proposed by de Terssac ( 2013). It reflects the ability of managers [START_REF] Amblard | Les nouvelles approches sociologiques des organisations[END_REF] to mobilize stakeholders, notably through reciprocal requirements, in order to legitimize their actions (the rule of engagement). Then they must convert passive stakeholders into proactive actors (Morel et al., 2008) (the rule of ownership). This step requires adaptation to safety rules: it is the outcome of negotiations (control and safety rules) and relevant know-how (self-regulation). The third step concerns learning by doing (the rule of understanding). An example of this is feedback processes (Morel, 2009) that are free from sanction. The last step focuses on increasing the maturity of the system. It concerns the ability of each actor to support the development of regulations (the rule of confrontation), for example through roundtable discussions, or internal practices such as "safety Tuesdays" suggested by some inspection services. This brings us to the question of the integration of an ongoing, endemic improvement process [START_REF] Blazsin | Safety at the Sharp-End: A Case Study in the Gas Sector[END_REF], which could perhaps be called a safety culture [START_REF] Lefranc | Does the management of regulatory compliance and occupational risk have an impact on safety culture?[END_REF]. Complex systems such as the CEA consist of multiple sets of regulations that interact and provide a shared system of negotiated rulesa process that promotes more effective safety management.

ANT provides an insight into the mutual influence of human and non-human actors in a complex socio-technical system such as the CEA. Coupled with SRT, it offers a way to describe and analyse the network of actors that are stakeholders in the control process. Figure 7 provides an initial overview of their respective contributions.

Implementation and modelling

The work carried out by Audiffren et al. ( 2013) on safety compliance and that of [START_REF] Lefranc | Does the management of regulatory compliance and occupational risk have an impact on safety culture?[END_REF] on safety culture contribute to our modelling approach. As the control relationship is intimately linked to the question of compliance, the normative compliance models developed by Audiffren and Lefranc provide a starting point for our model. The quantitative survey conducted by Audiffren et al. ( 2013) highlighted a number of issues related to corporate management systems; in particular the importance of compliance to the optimization of safety.

The model is based on the typology of models developed by Le Moigne (1987). Specifically, we selected a prescriptive normative model, which provides an ideal representation of the system of actors. Following Walliser (1977), general expectations are based on the objectives to be achieved: here, radiation protection management and the use of a collaborative platform between actors needed to achieve this goal.

The role of inspectors is to identify divergences from a given repository and the company's SMS is used to implement the measures necessary for compliance management.

In the following sections, we present the key compliance processes suggested by [START_REF]  Audiffren | The contribution of case law to compliance management in Occupational Health and Safety (OHS) in France[END_REF]. We model exchanges between actors involved in radiation protection control (inspectors, the CEA and the collaborative platform). The two main human actors in this process were identified by Audiffren et al. ( 2012) as the "prevention manager" and the "prevention fieldworker". Figure 9 suggests the links between the human and non-human actors. The software tool acts as a relay and a central point to store information. Thus, the two human actors involved in control (the prevention manager and the fieldworker) can use it to communicate.

However, Audiffren and Lefranc's work was limited to internal management systems and focuses on a single control process (compliance). Our study includes external control actors and an objective (radiation protection safety management), i.e. the effectiveness of compliance regulations controlled by the inspection process.

Classically, the inspection and control process is based on an assessment of compliance with regulations. Here we focus on the support that can be provided by collaborative software. Specifically, we look at software solutions from specialized publishers such as the company Preventeo (a partner in this research). The following sub-processes can be identified [START_REF]  Audiffren | A quantitative analysis of health, safety and environment policy in France[END_REF], Lefranc et al., 2013):

1) Company configuration 2) legal measurement 3) practice measurement 4) Management, 5) publication of data and knowledge bases Each of these sub-processes corresponds to a module in the Preventeo platform.

The first module, "organization" (1) concerns how the business is organized.. The "organization" module centralizes all the information generated by the software package.

Each part of the organization is able to monitor applicable regulatory texts via the "regulatory monitoring" module (2). The regulatory scope applicable to each business unit is divided into three areas: OHS, Environment and Nuclear.

Once the scope has been determined (with the help of the regulatory monitoring module), it can be evaluated in detail via the "compliance assessment" (2) module. This aims to create a detailed assessment of compliance based on classical audit techniques [START_REF] Innes | Health and Safety Auditing[END_REF] and improve the quality of associated reporting (compliance reports).

On the other hand, the "feedback" and "risk assessment" modules (3) allow taking a closer look to the real deal inside the organization. These "company practice measurement" tools provide internal information about the safety management.

The results of the compliance assessment are centralized in a fourth module dedicated to the daily monitoring and management of action plans (4). OHS managers and the IGN can use this module to manage internal CEA action plans and suggest additions resulting from requests from inspection services and comments from accredited bodies.

The knowledge bases and assessment questionnaires that make up the monitoring and compliance assessment (2) modules are created using a fifth module called the "knowledge base editor" (5). This module enables the creation of legal, normative or internal databases.

The editor makes it possible to divide texts into requirements, which then take the form of audit questions.

The previous elements allow us to gave a more accurate view of the interactions between the safety stakeholders and the place of a collaborative platform as a management tool in the control relation.

Results and discussion

In order to organize and classify the interactions between the stakeholders by the collaborative platform, we categorize the flow of their interaction with the management tool.

Initial results

The value of our work lies in the ability to understand the interactions and aspirations of each actor. It provides a neutral space for discussion leading to mutual support in order to fulfil shared safety goals and meet each actor's objectives. The typology of actors provides an initial representation of a control process that integrates a collaborative dimension. We illustrate the process through the role played by a collaborative software tool implemented at a facility.

The first step was to define the system of actors likely to contribute to the inputs of the software platform. Figure 10 shows these contributors. This representation highlights the contributors of management tools in all stakeholders. There is two kinds of them: direct and indirect ones. The first ones upload directly the input in the platform, instead of the other ones whom gave information but don't upload them to the platform (as a free download platform who provide information but don't analyse them). As we can observe, the direct contributors are internal (company OHS managers and fieldworkers) and the indirect ones are mostly external (inspectors and the testing companies) but also internal (HSE officer). It is completed by an analysis of the stakeholders' users of the outputs (Figure 11). Theses two schemes provide a lot of information about HOW information around the platform are used. The next figure will provide information about WHICH information are uploaded/downloaded on the management tool (figure 12): This scheme figure out information provide to the platform (inputs) and ones get in return (outputs). It is completed by a categorization between information shared or unshared by the stakeholders. As we can see shared information relies on legal information. Others information aren't shared.

Discussion

As say in the introduction, these results are based on initial, exploratory field interviews. They focus on two data: contributors/ users stakeholders and inputs/outputs. They allow to see the network organization with the management tool as a centre.

Of course, we have to stay cautious with the results. The actual actor network doesn't represent the platform builders and their role in the indirect data inputs collect. Even if it take in account the formal human stakeholders of the control process, new perspectives open the door of a stakeholders extension with associations and population involvement [START_REF] Granier | Le rôle des contrôleurs -inspecteurs : du censeur au co-producteur de normes[END_REF]. The qualitative analysis use in this work is a bias as well. Because we only did a few interviews and test one software solution, results are threaten by subjectivity and have to be taken as a concept proof and not a globalization. Finally the actual vision stay a macroscopic view of the situation and a more precise case study should be conducted about a significant event to analyse precisely the actor network.

Results show that the use of a management tool increases the legal requirements understanding (watch, compliance) and the ways of deal with it (framework and formalization, self-regulation). As a mainly company used tool, the platform develop the capacity of the OHS managers and fieldworkers to respond to the inspections demands (compliance). In this purpose, they use watch tools which give them an overview of present legal rules (laws, acts, guidelines, etc…) and futures ones (law projects, state studies, etc…). It lead to a better monitoring of safety management. These evolutions increase the legal compliance of the company and the understanding between inspectors and OHS managers and fieldworkers. However, as De Terssac ( 2003) say, we have to stay cautious about the effectiveness of the measures took. Focus on legal compliance can lead to a superficial safety management which rely on the indicators more than field reality. In the other hand, the platform proposes a framework which help the company to formalize its methods (methodologies, analysis, and organization) and insure a correct safety culture (selfregulation initiatives, internal rules OHS organization). Despite the enthusiasm of OHS and corporate managers about these solutions, there are risks to overestimate their potential and lead to a standardization of the safety process and methods which don't take in account differences between facilities. Also there is the question of the flexibility of the platform solution: could it adapt easily to a new legal context as current hardness legal (Pénibilité) questions in France? Anyway, even if there are lots of question about how collaborative platform can challenge the safety performance. The interest and will of the OHS managers and fieldworkers to come to a collaborative platform solution is a good reason to take a closer look to these solutions and the way to improve their efficiency. Finally, the current biggest question is about the involvement of inspectors in this collaborative platform use.

Conclusion

It is clear that while the management tool is mainly useful internally, it provides a better understanding of the demands of the various inspection services and therefore, initially, can help in compliance management. In addition, it can improve monitoring of occupational health and safety with respect to radiation protection management, as it offers an overview of both compliance and preventive actions that have been implemented (e.g. management of protection barriers and responses to a significant event). The limitations of the tool relate to excessive formalisation, which rigidifies procedures and does not take account of changes in the business. It is clear that an innovative and powerful tool must, above all, adapt to changing circumstances while remaining objective and scalable. This demonstrates the importance of the selection and use of management tools in nuclear safety. An avenue of research for future work will be to integrate State inspectors into the collaborative process. Another one will be to analyse through an accident case study how to improve these management tools and how they provide better safety prevention.

Figure 1

 1 Figure 1 Overall organization of CEA controls The overall system is divided into two subsystems: internal controls (consisting of selfregulation and inspection/ internal audit procedures), and external accredited bodies (consisting of control agencies). The work of Audiffren et al. (2012) and in particular a survey conducted in 2009 and 2010 by Audiffren et al. (2013) characterized the internal actors involved in the SMS: the "prevention specialists". Despite the diversity of job titles (e.g. "safety officer", "safety manager" or even "QSE officer"), a clear typology emerged (Table1).

Figure 2

 2 Figure 2 makes it possible to compare this typology with the CEA's mode of operation.

Figure 2 A

 2 Figure 2 A typology of internal CEA OHS actors

Figure 3

 3 Figure 3 Self-regulation within a facility 1.1.2 Internal inspection Internal inspections are carried out by the CEA's central administration represented by the PMR (in particular the IGN) and OHS managers at the facility. It operates at two levels of control:

Figure 5 :

 5 Figure 5: The organization of State inspections in France

9

  Inspections of classified and nuclear installations: Article L.514-5 of the Environmental Code. 10 Decree on troublesome or dangerous factories and sweatshops, 15 October 1810 11 Letter from the Parisian Préfet of Police to the Préfet of the Rhone, 20 November 1821

Figure 6

 6 Figure 6 Model of joint regulation (Revue française de gestion, 2008/3 n° 183)

Figure 7

 7 Figure 7 SRT -ANT model

Figure 89

 89 Figure89Legal compliance management[START_REF]  Audiffren | The contribution of case law to compliance management in Occupational Health and Safety (OHS) in France[END_REF]

Figure 98

 98 Figure98Compliance management sub-processes[START_REF]  Audiffren | The contribution of case law to compliance management in Occupational Health and Safety (OHS) in France[END_REF]

Figure 10

 10 Figure 10 Collaborative control platform, contributors

Figure 11

 11 Figure 11 platform usersAs for the contributors, this figure proposes two categories of users: direct and indirect. First ones take the outputs directly from the platform, instead of the indirect users which rely on the direct users to get information. As we can observe, the direct users internal (company OHS managers and fieldworkers) and the indirect ones are the mostly external (inspectors and the testing companies) but also internal (HSE officer).

Figure

  Figure 12 inputs/outputs sharing

Table 1 Typology

 1

of OHS professionals (Audiffren et al., 2012)

Act No. 2003-699 of 30/07/03 relating to the prevention of technological and natural risks and compensation for any damage.

General Rules of Operation (Règles Générales d'Exploitation): the CEA's internal guide to operations and best practice.

The Nuclear Security Authority (Autorité de Sureté Nucléaire) is an inspection agency responsible for nuclear security.

The Regional Directorate of Environment, Planning and Housing (Direction Régionale de l'Environnement, de l'Aménagement et du Logement) is a decentralized state service responsible for the inspection of classified installations.

Source: Ministry of National Education (Ministère de l'éducation nationale) website.

http://www.boutique-certification.afnor.org/

Acknowledgments

The author would like to thank the company Preventeo for their support in this research project.

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