F Mazza

M P Da

P Le Callet

Would you hire me? Selfie portrait images perception in a recruitment context

Keywords: image aesthetics, content perception, portrait images, social bias, social networks, crowdsourcing

Human content perception has been underlined to be important in multimedia quality evaluation. Recently aesthetic considerations have been subject of research in this field. First attempts in aesthetics took into account perceived low-level features, especially taken from photography theory. However they demonstrated to be insufficient to characterize human content perception. More recently image psychology started to be considered as higher cognitive feature impacting user perception. In this paper we follow this idea introducing social cognitive elements. Our experiments focus on the influence of different versions of portrait pictures in context where they are showed aside some completely unrelated informations; this can happen for example in social networks interactions between users, where profile pictures are present aside almost every user action. In particular, we tested this impact on resumes between professional portrait and self shot pictures. Moreover, as we run tests in crowdsourcing, we will discuss the use of this methodology for these tests. Our final aim is to analyse social biases' impact on multimedia aesthetics evaluation and how this bias influences messages that go along with pictures, as in public online platforms and social networks.

INTRODUCTION

During last ten years, multimedia quality evaluation evolved from the mere technical parameters analysis to the consideration of human factors in content perception. Later on, image aesthetic appeal has been introduced to deepen the analysis. Research in image aesthetics showed good results, allowing to build automatic aesthetic assessment systems 1 evaluating low-level features. These features were mainly taken from photography literature, like contrast, composition and colors. Many researches on color as factor on human behaviours have been carried out; a critical review on color psychology is present in Whitfield's review. [START_REF] Whitfield | Color psychology: a critical review[END_REF] Higher level features considering perceptual differences and technical details regarding photography -notably from camera settings -have also been proposed. [START_REF] Ke | The Design of High-Level Features for Photo Quality Assessment[END_REF] However, a gap is still present, as low-level computable features alone are not enough to express completely the impact of multimedia on users' experience. Moreover, there is a large variability between people in aesthetic canons.

High level human-oriented semantics are required. [START_REF] Datta | Algorithmic inferencing of aesthetics and emotion in natural images: An exposition[END_REF] These should take into account more complex mechanisms in human content perception. While content semantics are not new, as for example it has been used with content recognition in automatic image tagging [START_REF] Fu | Semantic Image Understanding : From Pixel to Word[END_REF] , in it's use there is more than the simple content perception. Content is not only perceived but processed by deeper mechanisms in human brain involving many factors, like memories, personal experiences, belief, and cultural background; we refer to this fact as "content cognition". First steps in taking into account this element have been done: image psychology has been suggested as a potential focus for further research by Fedorovskaya [START_REF] Fedorovskaya | Subjective matters: from image quality to image psychology[END_REF] and recently familiarity within image context 7 has been addressed.

In this paper we consider image psychology elements proposed by Fedorovskaya focusing on social factors as particular cognitive biases may be triggered. Cognitive biases are deeply investigated in psychology due to their impact on the decisional process. Their importance is underlined by the fact that they occur at an unconscious level, so that people are even not aware of being influenced. Between cognitive biases, an important category is regarding the social elements impacting our perception; these are called social biases. [START_REF] Wang | Social Bias in Online Product Ratings : A Quasi-Experimental Analysis[END_REF] We think that how an image is perceived is impacted by this bias by different social clues. In this work we start to explore how social clues conveyed inside an image impact the perception of the subject depicted in the image, as the message conveyed changes radically with elements not related to the objective image quality itself. This is especially true when people are present in the image, as more elements can be understood from the context regarding the person depicted. Many times these guessed elements impact in any case our perception of the person and change the message conveyed by the content itself and any other interaction with the person in the picture. This is the case for example of profile pictures on social networks where this image will be aside every comment or action the user does. In that case, people could evaluate his/her interactions influenced also by the picture aside. In case a person is depicted in the picture, they will associate a face to a message. Another example is regarding resumes, of course in case attaching pictures is not forbidden. In fact, candidate image may influence selection process as choice may be based not only on competencies but also on many other elements conveyed by the imagei.e. if it's clearly understandable sex, race, age, beauty. As we cannot change our face traits from shot to shot, mastering photo elements would be of great value: with this knowledge we can think of biasing hidden message to convey with the picture as desired. This for example can be useful to underline different personality traits of a person depending on the context of the image. These elements are related more to social interactions than image aesthetics.

Recently selfie portraits have become really popular, both between the mass but also between public figures and celebrities. These shots are self shot pictures, usually holding the camera in front of a mirror or more frequently pointing it to the subject holding it with one hand. [START_REF] Krause | Photo Idea Index[END_REF] Technically a selfie can also be shot via professional cameras with timers or remote controllers; however in this research we refer to normal selfies shot in consumer conditions: picture subject take a shot holding a consumer grade camera. Self shot pictures are not new in photography, but their use and production is recently growing hugely due to the spread of consumer cameras -now present also in most new mobile phones -and internet pervasiveness. More and more people are taking selfies in a wide range of contexts and upload them on social networks directly from hand-held devices. These pictures are often adopted as profile pictures, appearing in every interactions users do online. As this kind of pictures convey spontaneous highly variable situations, it becomes worth to see if and how these elements impacts on subject perception. This impact can be seen in the broader context of social biases. This study can be particularly important for social networks, as they can host different kind of interactions: with friends, for work or in public announcements. Different messages conveyed by the picture can affect also the message given aside it. In this work we adopted our previous example of resumes' pictures to evaluate the bias given by different picture portraits. Considered the growth of selfie pictures, we adopted this kind of portrait against professional portraits, commonly conceived more suitable in working contexts. Our research question is if a professional portraits gives more importance to a message, even unconsciously, respect a selfie one. We expect professional portraits to give more importance to message associated with them, as this kind of portraits are usually conceived as more valuable. To study this behaviour we will propose participants stimuli which message can be 'reinforced' by pictures, through our resume example previously said. Our analysis will also consider if this effect is affected by the content itself. Moreover we will investigate validity of crowdsourcing, a novel methodology already adopted in similar image aesthetic researches, for this kind of study. Next section is dedicated to experiment description, stimuli creation and crowdsourcing. Data section will follow this part, just before the conclusions and discussion of results.

METHODS

To evaluate picture bias on candidate choice, we set up our experiment as a resume selection process for a working position. We proposed the test as a game where we are an informatics company hiring developers. For this task participants have to select the best candidate for a proposed position, choosing between two resumes shown each time. Test adopts a pair comparison methodology. Proposed resumes are invented and have of course a picture attached, either a selfie portrait or a professional one.

To formalize the problem, three different factors are considered for our stimuli, as summarized in the table 2: the portrait typology, the resume informations and the model in the picture. Using this notation, each stimuli is noted as combination of these three. As example the stimuli having first portrait subject, professional typology and first version of resume informations is noted A P hD p . The same, with selfie typology would be noted as A P hD s . These three factors have been controlled during our test. Pairs showed to participants are made on possible stimuli combinations regarding these factors. A total of 6 * 2 * 2 = 24 stimuli originate from these. Some constraints have been enforced on pairs generation. We took care about which pairs to display each participant in order avoid people to get the real scope of the test, as this would have maybe biased the answers. In fact, providing to a participant different informations regarding a portrait subject, both in terms of resume or picture, would have made the participant more aware of the real purpose. To this extent, we followed these constraints:

-the same participant must not see different portrait typology for the same portrait subject; -the same participant must not see different resume informations for the same portrait subject.

Following notation adopted, the first constraint implies that a participant can observe either X P hD p or X P hD s , and the second one imposes either X P hD p or X M p . These constraints inevitably lead to much more participants needed, as we cannot propose to evaluate all our stimuli to each participant. It has to be noted that participants can be faced instead with two portraits having same typology in one pair, as there is no problem with this configuration. Pictures have been created ad-hoc as described in next section.

Stimuli creation 2.1.1 Portraits

As no database like this already exists at the best of our knowledge, we constructed a small database of stimuli ad-hoc. Eight male subjects from different countries (and face traits) and aged between 23 and 40 participated in the photo shooting as models. Female portraits have not been taken due to the lack of sufficient different models.

Professional portrait pictures have been shot with professional equipment. A high grade DSLR camera and objective have been adopted. Subjects have been shot in a photo studio with controlled diffused light. They were asked to take a natural posture but supervised to get a professional portrait. White balance has been controlled and then retouched digitally, as photos have been corrected in postprocess. Contrast has been enhanced, as well as unwanted shadows removed. Minimal retouches have been manually done on details, to enhance skin tone and softness, being careful to preserve face traits. Pictures have been taken at a resolution of 16 Mpx, then manually cropped to adjust the composition and cut empty space around subject.

A similar procedure has been adopted for the selfies shots, but in a spontaneous context and with only a consumer camera as equipment. Subject have been asked to take a self portrait with a mobile phone, without the help of the photo studio lighting, as they would do in a real case. Device is equipped with 2 Mpx front camera. Although subjects were free to take shots, they had a minimal supervision in the process to have correct portraits. Postprocess have been done to resize images as previously said. Minimal modifications on brightness and contrast have been done in order to conceal unwanted shadows effects. Unrecognizable and blurred shots have been discarded.

While on selfies -but also on some professional portraits -subjects depicted have an happy or smiling expression, we adopted here more serious portraits. This has been done in order to avoid biases from facial expressions. As we are not checking if a candidate is preferred to another in general we did not adopted a standard to follow regarding glasses or hairs. We suppose that other normal elements, as long hairs versus short hairs, or glasses, give no bias in this simulated selection process. Figure 2.1.1 shows some examples of portraits shot. In the end, regarding image aesthetics, most people will agree on the fact that professional shots look much sharper, brighter and more defined respect selfies shots. Moreover, as social clue, professional shots convey also the sense of a higher value photo where subject put more effort and took care of the details by purpose.

We kept only six from these selecting the best professional shots in terms of face expression and posture. We chose this value to limit the number of possible combinations to be evaluated while having enough different portraits.

Resumes

As said before, resumes excerpts have been proposed with created portraits. To simplify this part, we told participants that we were at the end of the selection process and informations on resumes were summarized. We did this in order to have minimal resumes informations, simple enough for us to deal with -create, modify, propose in comparisons -but also for participants to evaluate. Informations proposed in the resume are candidate age and instruction level. Informations are invented on the proposed context of an informatic company seeking employees. Each created portrait has been associated with two resume's versions, both with same specialty but different degrees: one is PhD and one Master Degree. Each participant saw either one version or the other, to avoid making him aware of our setup, as specified by our previously mentioned contraints. Ages are between 24 and 31 years old, to comply with picture models' ages, and coherent with the instruction degree in the resume. Studies courses names for the degree are taken from some known study courses and specializations related to computer science. Adopting a pair comparison methodology, participants are faced with a couple of resumes each time from which they have to select either the left or the right one. As said, we proposed this as the choice of a candidate for a particular position. However, differently from a normal pair comparison configuration, we had more constraints regarding which stimuli to show to a particular observer. In fact, we designed our experiment taking care to divert participants attention from the real purpose; experiment was presented as a different task then image assessment. Previously formalized constraints regarding our experiment setup were taken into account during pair comparison implementation; these inevitably led us to need more participants.

Lot of data from a large panel of heterogeneous participants can help mitigating the effect of personal opinions' biases on evaluations. As our task is small and well defined -chose the best candidate between the two proposed each time -we prepared a web interface to allow people to participate remotely, exploiting the power of crowdsourcing. This allowed us to gather relatively fast a large amount of evaluations as explained in next section.

Crowdsourcing the experiment

Crowdsourcing is a recent practice adopted in many fields to outsource to a crowd of people a task commonly done in a controlled context. In particular regarding multimedia quality research field, crowdsourcing is used to collect evaluations from a crowd of people through the internet. Outsource is done through an open call usually via online commercial platforms that collect small tasks provided by employers and gather huge crowds of people willing to participate. Examples of well known platforms are Microworkers * or Amazon Mechanical Turk † . Thanks to the web, crowdsourcing can quickly provide large number of workers -in our case tests participants -at a cost cheaper than the one to conduct laboratory experiments. This experiment could have been run in a controlled laboratory environment, however with this strategy we can have a much higher number of participants, as it is much less expensive and faster to run the test. Times and costs are cut by the fact that participants need no supervision and can participate remotely without moving from home or office. Moreover, crowdsourcing can provide heterogeneity between participants, as the crowd is spread all over the world. This demographic diversity of users, mostly in terms of geographical distributions but also of ages and education, would have been much more difficult to achieve with a normal laboratory setup. This element can be valuable in our research as social biases can be influenced by participants' social background. In our experiment, to gather data that can be considered later, we included a small anonymous questionnaire asking for participant nationality, job and education level.

Crowdsourcing has already been exploited in multimedia quality experiments many times, not only for still images 10 but also for video assessments. [START_REF] Gardlo | Quality of Experience Evaluation Methodology via Crowdsourcing[END_REF] However, this methodology still poses many challenges. [START_REF] Keimel | Challenges in crowd-based video quality assessment[END_REF] In fact, while in laboratory participants have a well defined environment and follow precise rules, remotely the crowd is anonymous and uncontrolled under many aspects: the context and hardware adopted to participate can vary greatly from user to user and some environments can be unsuitable to participate. This is the case for example of users participating with small screens unable to display our contents. Used devices are often out of control; some parameters can be detected and checked but for others we need to rely on other elements, as a posteriori controls on results useful to detect outliers. Moreover many subjects can provide incorrect results because they lack supervision or they do not understand the task to be done.

Our platform

To deal with all these problems, expanding our possibilities and propose our experiment, a new crowdsourcing software framework has been developed. This framework has the purpose of instructing users regarding the experiment, proposing the experiment itself and monitoring the users. While some platforms are already available for this purpose, like QualityCrowd 13 some features are missing and a modular platform as the one created allows greater flexibility. A wide range of features has been designed allowing future reuse for other tests and fast customizations. With this framework, we were able to have a greater control on many aspects, notably experiment work flow. In order to have a better understanding of our participants we proposed a small anonymous demographic questionnaire before the actual experiment. Information asked were the age, the Country of residence, the education level and if they previously already participated in similar test for research purposes. After the questionnaire we provided clear instructions in the first page, explaining to select a candidate each resume pair provided. Then, at the first pair provided, we provided an help screen highlighting interface buttons to chose a candidate. This screen disappears after clicking anywhere on the screen, as mentioned also in this help screen itself.

In our platform we implemented also a set of functions to allow the permutation of image metadata and captions. These are important for our experiment regarding resumes and pictures, as we need to handle metadata in profile shots. For example, we can track which elements were present in pictures proposed to a participant. As said, crowd is uncontrolled and unreliable; this is why functions to check participants reliability have also been added. Mainly this goal has been fulfilled adding content questions regarding stimuli proposed, sometimes called challenges or 'honey pots' [START_REF] Kazai | An analysis of human factors and label accuracy in crowdsourcing relevance judgments[END_REF] . These questions aim to check if users are really aware of what they are doing or they do proposed task as fast as possible just to earn money. In our case we proposed questions in the context of resume selection plot we designed; participants are told from time to time during the evaluations that the personnel chief is worried about some some informations about chosen candidate. Randomly, participant is asked if chosen subject was wearing glasses, or if he had long hair, or regarding his resume informations. Answers are stored with metadata functions previously told and shuffled with other stimuli answers, so that participants are asked randomly something different every time. Answers are checked on the spot and an error message is displayed to the user as feedback on his answer; again the answer is given taking advantage of proposed game context, saying that the answer 'did not convince' the chief personnel. Participants' reliability has been controlled also implicitly. Answers statistics and response times have been monitored to identify outliers; avoiding people selecting repeatedly too many times stimuli either right or left -just to speed up the experiment.

A problem detected with crowdsourcing regards the time limit participants are tolerating before quitting prematurely the experiment. Previous researches done in the field with similar methodology analyse participants' withdrawal behaviour, and their results suggested us a maximum limit of around five minutes. [START_REF] Keimel | Challenges in crowd-based video quality assessment[END_REF] We adopted this duration for designing our experiment; to achieve this with the honey pots provided in our configuration, we chose to limit to 15 the number of evaluations proposed each participant, considering a maximum of ten seconds needed for each choice. However this consideration does not guarantee that all participants complete the test; participants' withdrawal can make problems as some pairs are left unevaluated and at the end of the whole experiment have less quotes than the others. However, we took this problem into account while making our experiment and checked that every possible image pair in our setup has been evaluated by at least 20 people. With the considerations done, we decided to pay 0.50 each participation, looking also at current prices found in Microworkers for similar survey tasks and experiment durations. Before launching the experiment on a broad scale, we started a smaller one with fewer subjects to test our framework again. Crowdsourcing platform has been targeted to allow users from all over the world, taking care of limiting acceptance speed. In fact time zones difference must be taken into account in order to avoid accepting only people from a particular Country, active at the moment the experiment is launched. [START_REF] Hirth | Human Cloud as Emerging Internet Application-Anatomy of the Microworkers Crowdsourcing Platform[END_REF] Crowdsourcing the experiment worldwide imposes some challenges also regarding huge diversity of participants' devices and connections. Without taking care about these details, test can be impaired by different technical factors, i. e. wrong visualizations on some displays or network impairments due to poor connections. To mitigate these problems, all pictures have finally been resized to suit our online resume scenario; they have to fit a normal screen in a pair comparison methodology, that is to say two images must fit in screen side by side. To be sure that images would have not resizing on participants' browsers, we resized them to 400 x 533 px, considering internet users screen resolutions as done in. [START_REF] Gardlo | Quality of Experience Evaluation Methodology via Crowdsourcing[END_REF] At present more than half internet users have a screen resolution equal or bigger than 1024*768px. [START_REF] Netmarketshare | Internet users screen resolutions statistics[END_REF] Internet connection speed is another factor to consider. [START_REF] Hoß Feld | Modeling YouTube QoE based on Crowdsourcing and Laboratory User Studies[END_REF] The best solution is to reduce needed bandwidth as much as possible compatibly with our stimuli: files size must be kept as small as possible. To shrink file size we converted pictures to JPEG file format, setting quality to 85%. This quality setting was found as the best tradeoff allowing small filesize and minimal almost unnoticeable compression artifacts. However we can't be sure that stimuli will be presented completely unaffected by network delays or other network impairments; we will monitor these effects looking at answers times previously mentioned.

DATA ANALYSIS

Crowdsourcing methodology allowed us to gather data from 978 participants in 6 days, from 47 different Countries worldwide. Regarding their demographics, half of them are aged between 20 and 30 years old; majority of participants (74%) has a Bachelor or Master Degree and around 20% of them has a high school diploma. Data analysis on these results will be carried out in our future works regarding crowdsourcing. Here will focus on participants reliability.

Analysing participant answers to content questions data, we discovered that around half of participants answered wrong two or more "honey pots" on the five we proposed in total per participant. While the best scenario would be that no error is made on these content questions, we considered one error to be normal due to memory and fatigue influence. For this reason we removed from our first analysis users that made more than one error. Interestingly, from content questions asked it emerged that participants made more errors regarding resumes informations than resumes pictures -around 40% versus 60%. We underline that questions were prepared by our framework, randomly assigned and uniformly distributed on pairs informations, both the resume and the picture. As participants where unaware that test regarded portraits differences, we expected them to be more focused on resumes informations. This result may point to the fact that people are more likely to pay attention to or remember better profile pictures even in contexts where it should be of no importance -as in resumes selection.

Regarding participations, even simplifying test at maximum and making it last at maximum 5 minutes, around 17% of participants quit the experiment before the regular end (15 pairs to evaluate). Deeper analysis investigating this withdrawal behaviour can be carried out and it is part of our future works specific on crowdsourcing. To check evaluation reliability we analysed also evaluation timings. Measurements have been done with our crowdsourcing system, monitoring page loading times and evaluations timestamps. We found that 12% of evaluations have been given before stimuli page was fully loaded in participants' web browsers. This behaviour can be due to poor network connections, slowing stimuli download from our platform, or to unreliable participants that try to give evaluations as fast as possible just to finish earlier the test. However, as both cases cannot be considered reliable evaluations, we excluded these from successive data analysis.

Analysis of influent factors

Many analysis are possible with our proposed setup. Resume informations, portrait typology and demographic informations can be considered as factor of influence in candidate choice. In this work we focus on the influence of portrait typology, either selfie or professional portrait. To this extent we check if the choice between two different typologies is statistically significant, all the other conditions being equal, for every possible face-resume combination. In other words we will check if candidate choice "can be ascribed to chance" respect portrait typology: this can be done with a Barnard's exact test. [START_REF] Barnard | Significance Tests for 22 Tables[END_REF] This non-parametric test was claimed more powerful then Fisher's exact test on contingency tables 2x2. [START_REF] Barnard | A New Test for 2 2 Tables[END_REF] This statistical test checks the independence of rows and columns in contingency tables, returning a p-value under the null hypothesis of pure chance. On 95% confidence a p value< 0.05 implies significant difference between the two test scenarios. The only assumption required to be respected is that responses are independent between them; this hypothesis is not violated in our case as every evaluation is independent between different participants as well as between different comparisons.

Running Barnard test on all pairs between the two conditions, as said either professional portrait or selfie, we obtain in total a out of N significant differences. N in our case is given by the number of possible combinations after respecting previously mentioned constraint regarding stimuli -here equal to 10 * 24. To test if factor under test is a factor of influence on these results, we conducted a permutation test and checked if significance ratio a/N is sufficiently large. Algorithm followed is the same as in Li's work. [START_REF] Li | Subjective assessment methodology for preference of experience in 3DTV[END_REF] This methodology implies the random permutation of some participants quotes between the two conditions and recomputing Barnard tests for all pairs as said before. As in a Monte Carlo simulation, with a sufficiently large number of permutations this distribution can be estimated. Our simulation took into account 1000 iterations. Results shows that significant ratio before permutation (a = 23) belongs 95th percentile, pointing out that portrait typology is an influent factor even if not for all the possible combinations. As previously said, participants with more than one honey pot mistaken have been removed from first analysis as considered unreliable. To evaluate our strategy we reintroduced those in our dataset and repeated the analysis as before. The final distribution of significant comparisons reveals we are now slightly more than the percentile of 55, indicating no evidence of portrait typology influence. This fact tend to depict those evaluations as noise in our analysis.

RESULTS AND DISCUSSION

In this paper we started to analyze image psychology biases given by image contents. We analyzed the bias given by the difference of self shots and professional portraits through a simulated resume selection for a work profile. We conducted the experiment online through a crowdsourcing platform build ad hoc, proposing a pair comparison experiment showing invented resumes. Crowdsourcing methodology has been evaluated outlining some problems and adopting control strategies; outlier participants have been screened based on answer timings analysis and content questions during the experiment. Factors of influence have been outlined and controlled; in this work we focused on portrait typology. Barnard exact test has been adopted to check statistical significance of this factor for each pair. Permutation tests have been run to check the overall influence on all the stimuli proposed. Evidence of preference for professional portraits has been shown to be an influent factor for part of proposed stimuli. Our research also outlined that crowdsourcing is a suitable strategy for this kind of picture evaluation, although a careful planned experiment is needed as well as reliability measures. Many analysis are still possible with the data gathered; these concern demographic data collected with our pre-test questionnaire proposed to participants but also analysis regarding the impact of resume itself. These deeper analysis is part of our future works. However, only this data is not sufficient to derive a conclusion and deeper investigation is needed. All these elements underlined that researching social biases impact for multimedia quality evaluation is interesting from multiple perspectives, as if better understood it can be considered for building improved quality evaluation models. Moreover mastering those biases is important especially for evaluations done remotely via internet: nowadays social networks are a huge resource and their social engagement features -e.g. "Likes", "Share" or friends suggested elements -are always present. How this factor can be exploited and/or corrected has not been dealt at the moment in our knowledge. Furthermore from a practical point of view it can open the path to further research in product advertising as it can influence social impact.

Figure 1 .

 1 Figure 1. Some portraits created; from top to bottom professional shots and selfies.

Figure 2 .

 2 1.2 shows a proposed candidate selection with our resumes excerpts.

Figure 2 .

 2 Figure 2. A comparison proposed in the experiment. Invented curriculum excerpt are visible under the pictures.

Figure 3 .

 3 Figure 3. Permutation test results; significant ratio distribution considering data screening (a) and without data screening (b). Red line indicates 95th percentile and a star indicates significant ratio before permutations.

Table 1 .

 1 One of the two resume versions for each portrait Factors of influence in our experiment

	Name	Versions	Notation	Description
	Portrait subject	6	[A,B,...,F] The model in the portrait image
				attached to the resume
	Typology	2	[p,s]	The typology of the portrait image,
				either professional portrait (p) or selfie (s)
	Resume informations	2	[PhD / M]

  Data: Raw comparisons, influence factor to test, Loop num number of loops Result: Vector Sig ratio containing number of significant pairs every iteration Sig ratio ← initialization; Group 1 , Group 2 ← Divide pairs in two groups based on condition to study for n ← Loop num do foreach possible evaluated pair e do if n = 1 then randomly swap m quotes between the two conditions;

	end
	p(n) ←
	Barnard's test p-value;
	if p(n) <0.05 then
	Sig ratio(n) ← Sig ratio(n) + 1
	end
	end
	Sig ratio(n) ← Sig ratio(n)/N
	end
	Algorithm 1: Permutation test algorithm


Emmanuel Hugonnot

Marie-Hélène Delville

Jean-Pierre Delville
email: jp.delville@cpmoh.u-bordeaux1.fr

Influence of the Substrate/Photoactive Solution Interaction in Patterning and Adhesion of Photodeposited Films

Keywords: 81.15.Fg, 81.10.Dn, 42.40.Eq, 42.70.Gi photochemical deposition, surface patterning, adhesion, laser, chromate

come

Influence of the substrate/photo-active solution interaction in patterning and adhesion of photo-deposited films

Introduction

Laser writing has become the corner stone of numerous material processing technologies because surface patterning is performed in situ and in a single step. Among the different laser writing methods, such as photo-electrochemical etching [1], photo-doping [2], laser ablation [START_REF] Dieleman | Guest Editors[END_REF], laser machining [START_REF]Laser Microfabrication: Thin Film Processes and Lithography[END_REF], or chemical processing with lasers [START_REF] Bäuerle | Laser Processing and Chemistry[END_REF], the photochemical deposition of thin films in liquid solutions [START_REF] Peled | [END_REF] is especially attractive because it can be applied to a broad range of precursors, including molecular compounds. However, contrary to other techniques, the choice of substrate becomes crucial since the deposit nucleation must occur on the surface instead of bulk, and adhesion between dissimilar materials, e.g. the photodeposit and the substrate, strongly depends on the chemical, physical and morphological properties of the interface. While adhesion is important, it has surprisingly been very poorly discussed for photochemical deposition processes [7]. As precipitation of chromium hydroxide appears in numerous technological areas [8], we investigate its photodeposition characteristics on glass substrates. By varying the composition and the pH of the initial chromate solution, known to affect deposition [9], we compare here in each case the chromium hydroxide solubility, the substrate patterning and adhesion, and discuss the resulting correlation.

Experimental Section

Experiments are performed at room temperature using two starting acidic liquid mixtures I and II composed of potassium chromate

( )

Cr VI (9% wt), ethanol (8% wt), and water. The pH was adjusted using either 1N hydrochloric acid for mixture I or 1N acetic acid for mixture II. The presence of an organic compound, , is necessary as an organic quencher providing electrons towards activated ROH ( )

Cr
Λ =
on the substrate. The adhesion of the photodeposit was investigated by the scotch tape test [11].

Chromium Hydroxide Solubility

According to the reaction scheme given by Eq. ( 1), the ( ) Cr OH is highly soluble at low pH , as shown in the Inset of Figure 1 [START_REF] Jolivet | De la Solution à l'Oxyde[END_REF], and large beam powers are also required to reach the solubility.

Cr

Adhesion of the Induced Deposit

Besides the study of the ( ) 3 Cr OH solubility during the laser excitation, we investigated the patterning of the resulting deposit and analyzed its adhesion to the glass substrate. As illustrated in Figure 2, the surface patterns induced by two interfering beams can be different for mixtures with different compositions. The pH dependence of the morphology is also important since surface relief gratings are only deposited at low pH .

Surprisingly, the beam interference pattern cast on the substrate gives a rough coating at high pH . Results for a large variation in pH are summarized in Figure 3.

When hydrochloric acid is used (mixture I), the deposit is not adherent at low pH . In this case, the silica at the interface is of the form

Cr III
species is essentially in its neutral form ( ) ( )

2 3
Cr OH H O 3 . The condensation of this complex leads to the formation of hydrated hydroxide gels. On the other hand, the and groups at the silica surface participate in the reaction with the Cr leading to the creation of molecular bonds. Thus, deposits should adhere to the substrate at intermediate

O - OH OH Si O Cr --
pH , when the HCl concentration is decreased. We did not see evidence for this expected adhesion up to pH 4 = , whereas the coating partially remained on the substrate between pH 4 = and 7 . Finally, for higher pH , typically pH 7 > , the hydrated chromium hydroxide gel first dissolves and gives

( ) ( ) - ⎡ ⎣ 2 4 2 Cr OH H O ⎤ ⎦ species [ ].
As the interface is in this case also negatively charged, electrostatic repulsion prevents any adhesion. The same behavior is expected for mixture II with the acetic acid, but the absence of chloride increases the stability of the chemical bond and leads to a much better coating adhesion.

12

Si O Cr --

The same type of experiments was carried out on other substrates, such as silanized glass, PMMA and Indium tin oxide. If we define as Peled [START_REF] Peled | [END_REF] a relative adsorption affinity A χ towards the substrate, we find:

( )

A A A Silanized Glass, Indium Tin Glass . PMMA Oxide χ χ χ ⎛ ⎞ ⎛ < < ⎜ ⎟ ⎜ ⎝ ⎠ ⎝ ⎞ ⎟ ⎠ (2)

Morphology of the Induced Deposit

The pH dependent chemical nature of the induced

( )

Cr III species can be at the origin of the observed difference in the deposits morphology, i.e. wavy pattern versus rough coating. As shown in Figure 2, the

( ) 3
Cr OH film is modulated by the optical intensity distribution at low pH , where the

( )

Cr III corresponds to a hydrated hydroxide gel.

Moreover, the spatial modulation of the deposited film corresponds to the forced fringe spacing Λ . This suggests that the

( )

Cr III nucleation mainly occurred at, or close to, the substrate interface. Bulk nucleation is probably a minor process in this case. On the other hand, Figures 2b and2d show the formation of a rough coating for large values of the pH , where is of the form of

( Cr III ) ( ) ( ) - ⎡ ⎤ ⎣ ⎦ 2 4 2
Cr OH H O instead of a hydrated chromium hydroxide gel. Colloid particles are nucleated in this case. The deposits behave as if they have lost the memory of the laser optical pattern, suggesting a bulk nucleation process followed by a deposition on the substrate by diffusion. The mechanism of this surface-to-bulk transition during the nucleation is not well understood since there is also a large crossover regime at intermediate pH where the gel and colloid form of ( )

Cr III coexist, as illustrated in Figure 2c. Results are summarized in Figure 3.

Conclusion

We analyzed the adhesion and morphology of chromium hydroxide layers photodeposited on glass substrate versus the composition and the pH of the initial photoactive solution. For increasing pH the deposit morphology switches from a gel film to a compact colloid aggregate, with a crossover regime. The transition suggests that the nucleation of deposits varies from surface-to bulk-controlled for increasing pH . Good adhesion to the substrate occurs only at intermediate pH . Our investigation shows that maps like those in Figure 3 represent efficient tools to optimize surface patterning driven by photochemical reactions.

Figures Captions

  III concentration in the solution is an increasing function of the laser beam power and reaches a steady value during exposure. The nucleation of the ( ) Cr III precipitate occurs as soon as the concentration reaches the solubility of in the solution. The ( ) 3 Cr OH pH variations of the solubility threshold for the mixtures I and II are presented in Figure 1. We measure the solubility at a given pH using a dichotomy procedure in beam power and setting the maximum exposure time to one hour. Since Cr VI activated by the blue-green wavelength range of a cw Ar + laser, various forms of ( ) Cr VI can be found in aqueous solutions. As the concentration of 4 HCrO - decreases for > pH 7 , a significant increase in beam power is expected to produce and precipitate ( ) 3 Cr OH . On the other hand, ( ) 3

:

  Figure 1: Laser beam power required to reach solubility versus pH values for the

Figure 2 :Figure 3 :

 23 Figure 2: Influence of the pH and the mixture composition on the morphology of the

  Figure 1

  Figure 2


Pierrick Milhorat

Istrate Dan

Jérôme Boudy

Gérard Chollet

D Istrate

Hands-free speech-sound interactions at home

Keywords: speech recognition, sound processing, sound recognition, domotics

published or not. The documents may come

INTRODUCTION

The CompanionAble European project aims at combining smart home functionalities with mobile robot abilities for dependent people. The robot is the front-end of the domotic system (turning on/off the lights, shutting/opening the curtains, playing/stopping music, etc) as well as an everyday helper. Supported by external sensors in the house (infra red sensors, door opening detectors, etc) and internal data (camera, sonar, etc), it's an assistant reacting to predefined scenarios (homecoming, video call, etc) or defined by the user himself (task reminder, pill dispenser, etc). To achieve such variety of tasks, the device is equipped with a touch screen. A mobile tablet and a static screen on the kitchen wall are also available. These are the three means to access the common graphical user interface of the system. Esigetel and the Mines-Télécom institute gave the robot its vocal interaction ability. A list of domotic commands have been extracted from practical experiments with end users. Other applications, for instance the agenda, the cognitive training or the robot control are also accessed via vocal commands. In both cases, commands are not only words but full natural language sentences. Lots of projects were about speech recognition; current commercial systems show us how the vocal interaction may be widely available in a near future. However, our work tries to solve the issues related to the distance to the microphone. In our configuration, we use a single microphone on top of the robot which can drive anywhere in the one-floor house. The noise environment is also unrestricted and traditional. Noise subtraction methods with dedicated microphone recording hypothetical noise sources are difficult to be applied to this real time changing environment. The CompanionAble project is further detailed in the second part of this paper. Sections 3 and 4 are about the sound processing and classification process, then, in section 5, the speech recognition system is described. Section 6 presents the first evaluations. Conclusions and perspectives drawn from this work are presented in the final part. -To combine mobile companion robot ability with smart home functionalities -To support social connection for dependent people -To improve the quality of life and the autonomy of elderly people Esigetel and the Mines-Telecom institute are leaders, each, to develop a vocal interaction and a multimodal distress situation detector. They take part in the person localization within the house as well. This paper focuses on the acoustic work. Currently, the project is tested by end users in SmH Eindhoven (Netherlands) and LabinHam in Gits (Belgium). They are invited to try the whole system for several consecutive days.

COMPANIONABLE

CompanionAble stands for

SOUND PROCESSING ARCHITECTURE

The sound is acquired continuously through two parallel systems: a first one which is able to detect and classify sound events between existing sound classes; another one

F w c w c C s r T d h c T

Speech/sounds classification

A speech recognition engine such as Julius search for the closest sequence of words matching the input audio observations given the probabilities contained in the acoustic model and in the language model. One may add a garbage model which will be the default match for unknown observation sequences or sub-sequences. In this application, every input is matched with a sequence of words. Thus sounds are processed as they were speech and a word sequence is returned. The sound classification prevents this to happen by discarding speech recognition results that occur while the stream has been classified as sound. It's a real-time process in parallel of the speech recognition one.

Acoustic adaptation

Acoustic adaptation methods have been studied at the earliest stage of the project [START_REF] Caon | vAssist: The Virtual Interactive assistant for Daily Homecare[END_REF]. Two adaptation methods were compared, namely: Maximum A Posteriori (MAP) and Maximum Likelihood Linear Regression (MLLR). A language model was trained on a corpus of 57500 sentences derived from practical experiments and paraphrasing. The speaker is the same for the whole study, she has been previously recorded and the audio files are played through a loudspeaker. As expected, as only 10 phonetically balanced sentences are used, MLLR adaptation is the most suited technique. Without adaptation, 60% of the Julius' transcriptions are correct while this rate reach 70% with MAP adaptation and 73% with MLLR adaptation. Users go through MLLR adaptation before they use the system.

Language model combination

The first version of the speech recognition module was based on a single N-gram model trained on a 57658sentence corpus. The acoustic model was adapted to fit the voice characteristics of the users using the MLLR method. This first system presented too much false positives, i.e. unwanted commands, when put to practical tests. In order to improve both the recognition and rejection rates, a filter, described next, was implemented. The dialog is based on frames [START_REF] Müller | Aspects of user specific dialog adaptation[END_REF]. These frames contain sub-dialogue graphs and transitions between states are triggered by the robot internal state/variables and the user inputs (vocal commands, buttons or/and sensors). A frame is enabled when at least one of its activation conditions is fulfilled; these are the same kinds of variables than the intraframes ones. Thus one can build a dialogue hierarchy: the root frame which is initially enabled contains all the activation events to enable the sub frames and terminal states allow the sub frames to hand over the control to the main frame. The sub frames have been clustered within eight classes. Each class lists all the vocal commands which are allowed and can be interpreted in the compound frames. A language model is build from those lists. A 9 th language model is trained on the activation commands and is associated to the main frame. Even while the speech recognition module doesn't receive information about the state of the dialogue, nine instances of the recognition engine run at the same time and deliver transcriptions of the input audio stream. This language model selection process improves the good recognition rates for the application commands but on the other hand doesn't solve the rejection issues for out-ofapplication sentences.

Similarity test

Similarity between two recognizers' hypothesis is an extended Levenshtein distance. This is the total number of operation (substitution, deletion, insertion) to transform a sentence in another one. Furthermore it is normalized with the count of word in the sentences. Depending of the relative value of this distance, given a threshold, the hypothesis recognized by an engine fed with a specific language model is accepted or discarded. This test is used to:

-Confirm good recognition: a well recognized command according to both the general decoder and the specific decoder is validated. The exact specific decoder's hypothesis is sent -Reject wrong hypothesis: a command recognized only by the general decoder is rejected. -Correct partially correct hypothesis: a command recognized by a specific decoder while the general decoder outputs a close match is corrected: the specific hypothesis is sent

The general language model must, in this setup, recognize the sequences of word contained in the specific language models. One needs to add the whole set of commands in the training corpus of such a general model. We introduced a weight for these additional sentences which has been experimentally defined to be 1000: the commands were added 1000 times. Finally, the test is not effective between one hypothesis for each decoder. We found out that it is better to use the n-best ones; it improves the good recognition rate: -One hypothesis is outputted for specific decoder because of the size of their language model -Several hypothesis (3 in our application) are produced by the general decoder and then fed to the similarity test All this improvements were implemented. A first evaluation of those is presented next.

EVALUATIONS

  Integrated Cognitive Assistive & Domotic Companion Robotic Systems for Ability & Security. This project is funded by the European commission and is composed by 18 academic and industrial partners. Partners are from France, Germany, Spain, Austria, Belgium, the Netherlands and the United-Kingdom. The main objectives are:

  A test corpus has been recorded in SmH with 5 speakers.

	E Each one of f them spoke
	s sentences, 20		application c
	s sentences and d 6 modified
	a actually a del letion of one
	f from the appli ication.
	T The experime ent setup is sh
	s sequences are	played throug
	a a microphone e. The top
	e experiment se econd phase
	T The sound lev vel was of abo
	a an average sp	eaker standing
	l listener.
	T The first pha ase was inte
	c commands 'w weight in the g
	h hypothesis fr rom the gene
	s similarity mea asure.
	F For vocal co ommands all
	b baseline, whic ch is fed with
	t the commands s, recognizes 1
	Baseline + ada aptation
	Baseline + ada aptation + similari
	Baseline + ada aptation + similari
	Baseline + ada aptation + similari
			Tab
	Baseline + ada aptation
	Baseline + ada aptation + similari
	Baseline + ada aptation + similari
	Baseline + ada aptation + similari
	Baseline + ada
	Baseline + ada
	Baseline + ada
	Baseline + ada
	I In a second p
	r robustness wa
	s sounds.

Table aptation

 aptation

	e 58 sentenc
	commands, 22
	sentences. T
	or several wo
	hown on Figu
	gh a loudspeak
	loudspeaker
	and simulated
	out 60 dBA w
	g about one m
	ended to set
	general model
	eral recognitio
	lowed by th
	h a language m
	15% of them.
	Sys
	ity test (command
	ity test (command
	ity test (command
	ble 1. Recogni
	Sys
	ity test (command
	ity test (command
	ity test (command
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	aptation + similari ity test (command
	aptation + similari ity test (command
	aptation + similari ity test (command
	phase of the
	as tested. The
	Wash m
	Dutch s
	Music
	Crowd
	Tab
	Wash m
	Dutch s

Table 3 .

 3 Reco

	experimental
	e top loudspe
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	speaker
	ble 4. Recogni
	System
	machine
	speaker

20th European Signal Processing Conference (EUSIPCO 2012) Bucharest, Romania, August 27 -31, 2012 © EURASIP, 2012 -ISSN 2076-1465

ACKNOWLEDGMENTS

This work is supported by the FP7 European CompanionAble Project. We thank AKG in Vienna and SmartHome in Eindhoven for their assistance. We also thank Daniel Caon and Pierre Sendorek for their help in the first implementation of the speech recognition system.

CONCLUSIONS AND PESPECTIVES

The set up presented on this paper aims at providing spoken input for a companion robot within a smart home environment. As the robot is always on, so is the speech recognizer. Given these constraints, the most important characteristic to keep in mind is the robustness of the recognition. This combines both a good recognition rate but also accurate rejection criteria.

A trade-off between these two aspects has to be found. Is it acceptable to erroneously recognize a command? Can the user be asked to repeat utterances? During trials, it has been noticed that false positives could mean trouble and disturb the user. To solve this issue, the command/sentence set to be recognized has been restricted, this yields two other problems. Intended users are elderly and dependant people who get some trouble remembering specific commands. Furthermore, they could get quickly upset if the robot doesn't recognize their orders and think that this is useless, ignoring this functionality.

We proposed to experiment a combination of language models to improve the system accuracy.

A new general language model has been built from a read Dutch subset of the CGN corpus. Let's assume that it is able to recognize any Dutch utterances. Then another pass works on a restricted specific model with close vocabulary. The similarity between both resulting sentences, computed as a variation of the Levenshtein distance, behaves as a filter for acceptation/rejection. A closer collaboration with the dialog manager would also bring more ways of refinement and filtering. The dialog manager of the CompanionAble project implemented in the companion robot follows a finite state automaton clustered in frames. Except for the root/main state which activates sub-frames and so is always active, we can select a specific language model built from acceptable sentences given a frame. Thus 10 restricted models have been created, one for each frame and one for the "main" frame. The dialog manager listens to the recognition process outputs, filtering them with what the current state(s) allow(s). This more elaborated system proved to be robust enough to allow a good recognition rate as well as limited false positive cases. However, informal experiments showed its weakness when it comes to reject short commands, i.e. oneword sentences. The use of the robot's attention with the trigger word prevents this to happen.


C Garnier

B Lorrain

M.-L Pastor

Impact damage evolution under fatigue loading by InfraRed Thermography on composite structures

This study deals with cumulative damage and its evolution in already impact damage composite structure. In order to follow the growing damage and to compare it with cumulative model, tests are monitored with an InfraRed thermography system. A carbon-epoxy composite is first low-energy impacted and then fatigued under tensioncompression loading. This study also enables a very fast analysis of predicting the damage evolution coupling InfraRed Thermography as NDT method and InfraRed thermography as a following system.

Introduction

Even if the mechanical performance of composite materials give new perspectives for the aircraft and space design, the variability of their behaviour, linked to the presence of initial defects or led in service, constitute however a still important brake in their development. As regards particularly the response to fatigue loads or ageing, the behaviour of these materials is affected by several sources of uncertainties, which cause a large scatter in life time.

In aerospace industry, low energy impact phenomenon is not well known concerning composite materials and composite structures. These small impacts create some defects, on structure, that are not visible during general visual inspection (GVI). Under fatigue loading, they grow up and are propagated on the structure until the crack. In order to predict the crack of the structure, the damages and their evolution have to be detected. Non destructive tests are used. So, it is very important to develop qualitative and quantitative analysis and methodology in order to assess the safety and reliability of low energy impacted carbon fibre reinforced plastics under fatigue loading.

Many investigations were carried out from fatigue loading on composite structure and their behaviour [1][START_REF] Talreja | Transeverse cracking and stiffness reduction in cross-ply laminates of different matrix toughness[END_REF][START_REF] Gathercole | Life prediction for fatigue of T800/5245 carbonfibre composite : I. Constant-amplitude loading[END_REF][START_REF] Mao | Fatigue damage modelling of composite materials[END_REF][START_REF] Dzenis | Cycle-based analysis of damage and failure in advanced composites under fatigue: 1. Experimental observation of damage development within loading cycles[END_REF][START_REF] Gros | NDT data fusion at pixel level[END_REF][START_REF] Vary | Nondestructive testing of fiber reinforced plastics[END_REF]. Most of these investigations show that fatigue behaviour of composite structure is a complex phenomenon. Many factors act on this behaviour, such as the loading level, the frequency, etc. However, few studies take into account the worsening character of compression during fatigue loading. Most of the pre-cited works deal with tension-tension fatigue loading. But, when a fatigue cycle takes into account compression, local or global buckling shall appear [17] and initiate in a premature way damages. a e-mail: christian.garnier@enit.fr Concerning the damage development, many properties of the materials act on it. The inhomogeneous microstructure, where there are small disparate porosities or cavities on it, the stiffness or strength of the composite lead to complex damage development and to different modes of failure like delaminations, disbondings, fibre breakage, etc.

In order to detect all the defects and to analyse the failure facies, many different NDT methods were developed or adapted for composite structures (Ultrasonic Testing, IR Thermography, Spectroscopy, Speckle shearing interferometry, tomography) [START_REF] Luong | Infrared thermographic scanning of fatigue in metals[END_REF][START_REF] Toubal | Evaluation des déplacements et des déformations par photogrammétrie. 16ème Congrès Français de Mécanique[END_REF][START_REF] Subramanian | A cumulative damage model to predict the fatigue life of composite laminates including the effect of a fibre-matrix inter phase[END_REF][START_REF] Quaresimin | Damage Evolution in Woven Composite Laminates Under Fatigue Loading[END_REF][START_REF] Chrysochoos | Infrared thermography, a potential tool for analysing the material behaviour[END_REF]. IR thermography, coupling to fatigue loading is a simply and a good way to follow the damage evolution [START_REF] Toubal | Analytical and experimental approaches of damage by fatigue of a carbon/epoxy composite[END_REF][START_REF] Pastor | [END_REF][15][16]. Concerning low velocity impacted composite structure under fatigue loading, few studies are carried out. But some works were done on composite structure with hole [16] and its behaviour can be compared with impacted structure behaviour.

This paper presents fatigue tests on impacted carbon-epoxy composite under tensioncompression loading. All the tests were followed by infrared thermography to characterize the damage evolution.

Experiments

Material

The used material is a carbon epoxy produced by the Liquid Resin Infusion process. The carbon fabric is the high strength fibre 5H satin G926 coupled with the epoxy resin RTM6. The weight distribution of the carbon fabric is 50% on the warp direction and 50% on the weft direction. The nominal weight is 370 g/m². The lay-up of the specimens are [[45°/0°] 3 ] s . All the specimens were controlled after production. A control of the porosity rate was done and the average rate of porosity is under 2,5% in volume.

[±45°] n Glass/epoxy tabs made from glass prepreg were done and bonded to the samples in order to prevent matrix crushing or stress concentration due to pressure of the grips. All the mechanical properties of this composite were carried out from tensile tests realised from a previous study. The ultimate tensile strengths are 787 MPa and 749 MPa for the warp direction and for the perpendicular direction respectively.

Specimen

According to the standard specifications about fatigue and impact tests [START_REF]Plastiques renforcés de fibres --Détermination des propriétés de fatigue en conditions de chargement cycliques 19[END_REF]19], a new design of specimen was established. The useful part of the specimen allows the both tests (impact test and fatigue test). Specimen geometry is as shown on figure 1.

Impact test

Impact tests were performed with a MTT drop weight machine. A crosshead brake attached to the impactor is used in order to prevent multiple impacts. The used impactor has a hemispherical tap witch weights 3 kilograms. According to the standard specifications about fatigue and impact tests [START_REF]Plastiques renforcés de fibres --Détermination des propriétés de fatigue en conditions de chargement cycliques 19[END_REF]19], a new design of specimen was established. The useful part of the specimen allows the both tests (impact test and fatigue test).

The chosen impact energy is defined to be smaller than BVID (Barely Visible Impact Damage). So the samples are impacted at 10 J.

Impact tester is as shown on figure 2.

Fatigue test

In order to prevent a high elevation of temperature of the sample during fatigue loading, the frequency was decreased. For 2.5 Hz fatigue on air, the elevation of temperature does not exceed 10°C. The fatigue cycle is chosen in order to take into account the effect of compression loading on impacting composite. This loading must not cause buckling of the sample. The specimens were loaded in the Instron 1345 hydraulic fatigue machine having a 250 kN dynamic load cell. A load control of this tests was used. The tension-compression fatigue cycle is defined as following:

-R = -0.3 -Load level: 40% of the ultimate load -F = 2.5Hz Where R is the load ratio and F is the frequency of the test. The damage and temperature evolutions were monitored during the fatigue test using an Flir Titanium infrared camera with a sensitivity of 20 mk at 30°C. The thermal movies are recorded at 149 Hz in order to catch the maximum of data as possible. The test is carried out on a controlled temperature and hygrometry room. The protocol of the test is as follow on figure 3.

Impact damage produced

The 10J impact produced at the centre of the sample created some damages. Most common phenomena appearing during impact testing are matrix crack, delaminations, fibre breakage or fibre splitting at the back face of the specimen. In order to detect damages produced by impact, NDT method is used. For this case, Infrared thermography enables to detect the shape and the dimensions of the produced damage in a short time [START_REF] Pastor | [END_REF]. A thermal stress is sent to the sample by a halogen lamp. The thermal waves propagate on the material: it creates thermal gradient in it. Because of the difference of the two mediums (composite and defect) coefficient of emissivity, a thermal map is created by the IR sensor. During the heating time, the thermal movie reveals the damage, as shown on figure 4.

Fig. 4. Impact damage

The defect produced on the material is quite hemispherical, like the impactor shape and measurements are 19 mm and 17,5 mm on the direction 1 and 2 respectively.

Damage evolution

General Visual damage evolution

In this part, a sequence of all the visible mechanisms occurred during fatigue testing is presented. After impact, there is no visible indentation on the faces of the sample. After 100000 cycles, transverse cracks reached the front surface. The microcracks area grows hardly after 200000cycles and just before failure, fibre breakage appears. After examining of failure, delaminations appears and are oriented on the same directions as fibre directions.

Damage evolution by IR thermography

One of the main output data is the evolution of the defect. First, a classical method used in Toubal's work [16] consists in substracting two images caught at two different numbers of cycles. Then hot zones appear and reveal the damage evolution. In this work, the aim is to follow the damage evolution according to the fibre directions. A new method, consisting in coupling NDT and IR-fatigue enables to have two informations in one image: the initial defect and its evolution during fatigue. NDT methods, as shown in cf 3.1 [START_REF] Pastor | [END_REF], enables having a thermal map of the defect produced by impact. Following the defect during tensioncompression fatigue loading by Infrared thermography outputs a thermal map of the specimen at a known number of cycles. This new method consists in substracting the initial defect image, revealed by InfraRed NDT methods, to the image caught at the required cycle, as shown in figure 6. The damage evolution is followed by IR thermography. With the substracting method, impact damage evolution is performed as shown on figure 7. As showm of the figure 7, the damage mainly grows on the direction 2. In order to correlate with some other works [START_REF] Toubal | Analytical and experimental approaches of damage by fatigue of a carbon/epoxy composite[END_REF], a plot of the size of the damage, for the two directions, is performed. This trend correlates well with the cumulative damage of composite materials with 3 different stages [START_REF] Toubal | Analytical and experimental approaches of damage by fatigue of a carbon/epoxy composite[END_REF].

Conclusions

In this study, a tension-compression fatigue test on impacted composite was followed by IR Thermography. These conclusions are performed :

-Impact test affects the indeed integrity of the structure -The evolution of damage of a low-energy impacted composite correlate well with the cumulative damage trend of composite. -The damage grows following the fibre directions and propagates more perpendicularly to the load.

A new method to follow damage evolution is performed by IR thermography. It couples NDT method with a real-time following of the fatigue test.

The substraction of the impact damage to all the IR movie gives 2 informations in the same time:

-The size of the impact damage -The growing directions of the damage

This study has to be completed in comparing datas obtained by IR thermography to residual mechanical properties of the damage composite. Moreover, a cumulative damage model for impacted composite must be carried out.

Fig. 1 .

 1 Fig. 1. Specimen Geometry used for both tests

Fig. 2 .

 2 Fig. 2. Impact test machine used for this study

Fig. 3 .

 3 Fig. 3. Fatigue protocol

Fig. 5 .

 5 Fig. 5. Transverse microcracks on the front face

Fig. 6 .

 6 Fig. 6. Substracting method

Fig. 6 .

 6 Fig. 6. Evolution of the impact damage under fatigue loading by IR thermography

Fig. 7 .

 7 Fig. 7. Evolution of the size of the defect along directions

Table 1 .

 1 Elastic properties of composite G926/RTM6.

	E11 (GPa)	E22 (GPa)	G12 (GPa)	G21(GPa)	ν12	ν21
	63.3	62.5	30.2	29.7	0.049	0.051