dataesr/scientific-paragraphs-categorization huggingface dataset:
A. Parameter setting In all tests, the size of an image patch is set to 3 × 3 and the overlap between two adjacent patches is 2 pixels. In cases of binary and natural images, the Kodak PhotoCD Dataset (shown in Fig. 4 ) is used as standard images. For the stage of estimation of p(α) as described in section II-A, we use N = 500000 patches randomly extracted from standard images to form the database of patches. In our empirical work, each axis in the α-space is divided into 2 5 = 32 intervals. Moreover, the noisy images are generated from the corresponding noise-free versions by adding Gaussian noise with different levels σ = 10, 20, 30. In regard to binary tests, all images are converted into binary ones using a threshold method. To evaluate the objective quality of denoising of vertical structure and natural images, two widely used metrics peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) are employed.
C. Denoising of binary images In this part, we will not only compare the performance of proposed method with the sparse patch-based algorithms OMP and LARS, but also with others denoising methods developed for binary images, called Iterated Conditional Mode (ICM)  [19]  and Graph Cuts  [20]. The ICM method is based on the maximization of local conditional probabilities, while the latter optimizes the flow through an associated network constructed from image. Please refer to  [19]  and  [20]  for more details. In the experiment, all images are converted into binary form using a threshold method as a pre-processing step. We used all the images (24) in the Kodak PhotoCD Dataset (Fig. 4 ) as standard images and some other widely used test images (shown in Fig. 7 ) for the evaluation. The dictionary is chosen as the same as Fig.
D. Denoising of natural images In the rest of our work, we compare the performance of the proposed method with two sparsity-based algorithms OMP and LARS for natural images. As in section III-C, we use all 24 images in the Kodak dataset (Fig. 4 ) as standard images. Moreover, we carry out the experiments by adopting the same dictionary for all methods, which is directly trained from each noisy image, using the K-SVD method  [10]. In reality, with a simple dictionary of three atoms, the denoising results will not be good enough for visual quality requirement. But we have to emphasize again that the objective of our research is to demonstrate that using the estimated probability distribution as the image prior is more efficient than a sparsity model for noise removal. As illustrated in table III, the proposed method yields better values of PSNR and SSIM than the others in most of cases of high noise levels (σ = 20, 30).
IV. DISCUSSION In this paper, we proposed a novel idea for patch-based denoising where the prior of patches distribution is learned from the external database. More precisely, we proposed a method for the estimation of probability distribution function by spatial division and demonstrated how to employ it in an optimization-based denoising process. The experimental results indicate that the approach improves considerably the results of denoising for some simple models of image when compared to the classical sparsity methods. The objective of our work is to make in evidence that the idea of embedding the probability distribution learned from external database is efficient and is a promising approach for image denoising. However, a drawback of the proposed method is the implementation for high dimensional (K > 3) α-space due to the curse of dimensionality.
This paper describes the properties and functionalities of the application we have created to retrace the story and evolution of international competitions organised by the Bourges's Institute of Electroacoustic Music (IMEB) from 1973 to 2009 using a set of interactive data visualisations. This set of interactive data visualisations serve different purposes: it provides multiple views of the database it allows to browse but also gives insights about navigation paths that have been previously taken to assist their users in their browsing experience. This set of interactive data visualisations represent an attempt to give access to the content of a digital archive, not only by considering its main properties, but also by gathering information about its past exploration using multi-agent systems.
According to Christian Clozier, 274 artists from 43 countries have worked in their studios on 765 different audio compositions and 4,836 composers from 82 countries have presented their work during the competitions and music festivals they have organised starting from 1971. From 2005 to 2011, the IMEB has donated all of its archives to the Bibliothèque nationale de France (BnF) that is to say a complete set of multimedia data about the history of electroacoustic music and its worldwide diffusion. In this paper, I will be describing part of the work that has been done to explore these archives as part of a research project directed by Geneviève Mathon and that has been financially supported by the Arts-H2H Labex. This paper focuses on the application that has been specially designed to retrace the story of the international electroacoustic music competitions organised by the IMEB from 1973 to 2009.
The application is presented as a prototype that can be accessed online (https://goo. gl/dlv07L). It includes a set of interactive data visualisations that provide information about the participants of the competitions organised by the IMEB and their works. To respect copyright laws, this online version doesn't give access to any audio records available at the National Library of France. Only the version of the application meant to be available at the BnF will grant such access. Despite these restrictions, we hope that the functionalities attached to the interactive data visualisations accessible online will be enough to understand how these audio compositions can be easily retrieved using the same set of functionalities and graphical interfaces.
VISUALISING MULTIMEDIA ARCHIVES To collect data about the international electroacoustic music competitions organised by the IMEB, multiple documents available at the BnF have been consulted including administrative forms and the minutes of each competition. Administrative forms provide information about the structure of the competitions itself and the evolving set of categories used to organise them. Minutes, on the other hand, contain information about each participant allowing us to know their name but also their current address and the number (or category) of each of their submissions. Some minutes contain also the titles of the audio works that have obtained a price allowing us to gather information about electroacoustic compositions whose quality has been publicly rewarded. All this information has been entered in a database in order to be able to retrieve it using queries but also to be able to explore it using interactive data visualisations that provide overviews and allow its users to filter data (and retrieve more detailed information) based on user input.
The data contained in this new database can also be used to create listings of award-winning pieces or statistics about the provenance of the competitions participants as those provided by Christian and Clozier Françoise Barrière. But these listings have the advantage to be dynamic. They respond to any change made to the relational database and can be linked, on different scales, to the data that have been used to generate them. The interactive visualisations presented below have been specially designed to look at the same data from different points of view. Each of them focuses on one property of the information that has been collected in order to be able to compare multiple views of the same data set and be able to perceive more easily its main properties and elements. To emphasise the multiplicity of points of view, each visualisation doesn't use the same type of structure nor provide the same functionalities.
Flow Diagram A Sankey diagram has been used to represent the set of categories chosen by Françoise Barrière and Christian Clozier to structure the IMEB international competitions and sort out submissions (see Figure  1 ). It reveals the evolution of the competitions main categories from one edition to another. It permits its users to identify the number of categories used for each edition and their weight based on their longevity. It lets detect their reorganisation too with the appearance for example in 1988 of new categories called "Magister," "Residency" and "Quadrivium" that regroup subcategories that have been previously used to separate different types of submissions. The Sankey diagram provides an overview of the structure of the competitions but it can also be used to dive into the database that has been built.
Each category can be selected in order to expand the diagram revealing new curves that link each category to a collection of electroacoustic compositions that have received a prize during the competitions and are part, for many of them, of the IMEB archives. The flow diagram filters automatically the awardwinning works' collection based on the user inputs: only the information about the electroacoustic compositions whose category has been selected is displayed. This information includes the title of the composition and the name of its author. It can be used to access a more complete data set stored in the database that indicates for example its date of creation, its duration or its number of tracks. The main purpose of these titles collections is to give access to the electroacoustic compositions themselves to be able to listen to the IMEB archives even if this access will only be granted inside the BnF premises.
Interactive Index and Line Charts To give an insightful representation of the IMEB competitions more than one data visualisation has been created. This plurality permits us to focus on different properties of Bourges's international competitions. The next data visualisation represents an interactive index. Unlike the flow diagram, this index doesn't highlight the competitions categories. It reveals the large number of competitions participants by referencing all the composers whose name has been found in the minutes archived at the BnF. For the time being, only minutes from 1973 to 1994 have been completely processed. But data has also been gathered for the editions that took place between 1996 and 2009 using the content of the 6292 capsules to identify new participation. To sum up, 2,590 different participants have already been identified and 1,202 of them have at least one of their electroacoustic compositions stored in the IMEB capsules.
The colours go from red to purple passing by orange, yellow, green and blue. They allow to quickly identify composers that have participated in more than one competition but also the ones that have contributed repeatedly to the activities of the IMEB between 1973 and 2009. The interactive index invites by default to access data about composers that have participated multiple times to international competitions and have at least one of their electroacoustic pieces stored in the IMEB capsules. These composers are represented by several coloured squares that creates linear colour gradients that can be rapidly identified. The longer these gradients are, the more chance they have to pinpoint to composers whose works have been particularly well preserved. Among these composers we find Eugeniusz Rudnik, Åke Parmerud, Francis Dhomont, Jonty Harrison and Maggi Payne.
Visualising the Multimedia Archives of Bourges's Institute of Electroacoustic Music Florent Di Bartolo 141 The menu of the interactive index can also be used to filter the index in order to display for example only information about composers that have participated in one or more editions chosen by a user. The interactive index lets its users retrieve data about a specific composer using advanced search criteria but it also permits its users to explore the content of the IMEB archives by selecting several of its graphical elements based on their position and colour without having to know necessarily any composer's name. The interfaces presented in this paper are designed to highlight by default the main actors of the IMEB competitions and reference the documents that are available at the BnF.
Another type of interactive visualisations has been designed to continue to explore the IMEB archives without having to know in detail the history of electroacoustic music. These interactive visualisations are line charts that let their users access the information stored in the database by country. The line charts show the total number of participants by countries for each edition based on the information contained in the competition's minutes. They give a clear picture of the increasing participants number, edition after edition, from 1973 to 1994. The minutes of the editions that took place between 1996 and 2009 haven't fully been processed yet but demonstrates the competitions' success by reporting each year more than 500 candidates' applications on average. Compared to the minutes, the line charts don't indicate the amount of candidate's applications but the total number of participants (who sometimes submit more than one electroacoustic composition) in order to be able to follow more easily the evolution of their number but also to know how many composers are from a specific country.
Visualising the Multimedia Archives of Bourges's Institute of Electroacoustic Music Florent Di Bartolo 142 capsules who give access to 361 of their electroacoustic compositions. The interactive visualisations that have been previously described don't pretend to grant access to all the information related to the IMEB competitions that have been archived at the BnF. On the contrary, they try to give an image of the archives where the information still missing is represented as such. Like the database they are using, the interactive visualisations can always be edited and enriched. They represent navigation tools that allow their users to browse the IMEB capsules while providing overviews and references to the BnF general catalogue. Theses overviews focus on different properties of the electroacoustic competitions in an attempt to facilitate access to the records of the electroacoustic compositions while linking to other resources that are available and share some of their attributes.
VISUALISING NAVIGATION PATHS In order to extend the accessibility of the IMEB archives a multi-agent system has been designed (MAS). This system is used to draw maps that represent the data has been retrieved from the database by a unique user while using the interactive index presented previously. Each agent of the MAS is created from an information node related to a composer or an electroacoustic piece. The information node represents its genetic string. It determines its appearance (colour, shape) and behaviour (movement speed, actions). It allows them to appear with different colours and behave differently. Like fireflies, each agent has the ability to interact with other agents that are spatially closed to him. These interactions serve to create group dynamics. They are used to automatically compare information nodes and reveal the properties they have in common.
The yellow ellipses are parent nodes that have been opened to access their child nodes. While being associated with the interactive index, each system's agent can represent either a composer, a country or an audio composition and can be grouped accordingly. But the nature of each element is only one of many variables that can be used as a common denominator to gather several agents. The MAS can also be used to order awardwinning composition by categories (abstract music, program music, electroacoustic music with instruments, sonic art work, etc. ). This possibility appears automatically once the information about several electroacoustic compositions belonging to the same category has been accessed. By generating multiple groupings between agents based on a common attribute chosen to display them, this kind of interactive visualisation allows a user to acquire knowledge about its click stream.
CONCLUSION The different data visualisations presented in this paper aim to facilitate access to the IMEB archives located at the National Library of France. They focus on the electroacoustic international competitions organised by the IMEB from 1973 to 2009 and provide different ways to access information about their participants and audio compositions that have been submitted to enter the competitions. The information that can be retrieved comes from different documents available at the BnF like the competitions minutes or data collections like the 6292 digital folders made by Christian Clozier and Françoise Barrière to represent the diversity and richness of electroacoustic music presented during the IMEB festivals and competitions. Together, these interactive visualisations represent an attempt to create interfaces that can display some of the specificities of the IMEB archives but also connect its content to other resources like the BnF general catalogue using a database that references its entries about electroacoustic composers.
ACKNOWLEDGMENTS We would like to thank Françoise Barrière and Christian Clozier for their entire lifework and insights about the IMEB activities. We are thankful to the Audiovisual Department of the Bibliothèque nationale de France represented by Audrey Viault and Pascal Cordereix, as well as the Department of Music and its Conservation and Communication service represented by Catherine Vallet-Collot. We would also like to extend our thanks to Associate Professor Geneviève Mathon and research assistant Azadeh Nilchiani for their feedback and support.
Dictionary Refining and Sparse Coding Stage The second step of the algorithm (see figure  1 ) firstly aims at refining the pre-trained dictionary to sparsify the images via K-Singular Value Decomposition (K-SVD) algorithm  (Rubinstein et al. , 2008). Secondly it aims at deriving the sparse code associated to each signal by solving l 0 -norm regularization to enforce sparsity by using an approximate sparse reconstruction algorithm, Orthogonal Matching Pursuit (OMP)  (Tropp, 2004). Given a dataset Y ∈ R n×N and a target sparsity level L (maximum number of atoms allowed in each representation) the problem is to build the dictionary D ∈ R n×K and the sparse matrix X ∈ R K×N such that Y ≈ DX. The problem can be formulated as: < D, X >= argmin D,X ||Y -DX|| 2 F such that (2) ∀ i , i ∈ [1, N], ||x i || 0 ≤ L ∀ j , j ∈ [1, K], ||d j || 2 = 1 where: • ||x i || 0 is ||l|| 0 pseudo norm, defined by the number of non-zero coefficients in column x i.
EXPERIMENTAL SETUP AND ANALYSIS A critical experimental evaluation of the proposed approach is presented. Two public data sets that exhibit various emotions in different conditions, starting from acted facial expressions: the JAFFE database  (Lyons et al. , 1998) , to everyday natural and spontaneous facial expressions: the DynEmo database  (Tcherkassof et al. , 2013) , are used. The effectiveness of the proposed random face feature descriptor as a dimension reduction technique and dictionary pre-training method is analyzed by considering first the acted and controlled JAFFE database. This database is also used for fair comparison with the state of the art methods. Then experiments on the DynEmo database are reported since spontaneous facial expressions recognition is our main goal.
Experimental Setup and Analysis: The efficiency of our approach and its capability to recognize acted facial expressions beforehand testing it on spontaneous facial expressions is evaluated and demonstrated as a control experiment. Firstly, the dataset is divided into two portions based on the number of images per class as defined in the previous JAFFE dataset protocol. Figure 4 represents the evaluation of the random face feature descriptor. The x-axis represents the generation of different random matrix R for the same desired dimension m. The y-axis represents the final average classification rate over the projected data. To evaluate the performance of RFFD over the JAFFE database, we define a list of desired lower dimensions, m: 600, 650, 700, 750, 800, 900, and1000. For each dimension, different random matrices R i are generated.
Model Evaluation Over the DynEmo Database The DynEmo Database: DynEmo is a database containing dynamic and natural emotional facial expressions (EFEs). It is made of six spontaneous expressions which are: "irritation", "curiosity", "happiness", "worried", "astonishment", and "fear" (see figure  8 ). Those expressions have been elicited by showing some emotive short clips to volunteer subjects. The database contains a set of 125 recordings of EFE of ordinary Caucasian people (ages 25 to 65, 182 females and 176 males) filmed in natural but standardized conditions. In this set, EFE recordings are both associated with the affective state of the expresser itself and with continuous annotations of observers' ratings of the emotions displayed throughout the recording (see figure  9 ). The x-axis of figure  9  represents the time line, while the y-axis represents the probability of judgment for each frame.
We built a labelled spontaneous database in which the frames are extracted based on the previous defined ground truth. 480 images of female and male facial expressions of 65 different identities form the database. Each image has a resolution of 239 × 200 pixels after face detection and cropping. The head is not totally in frontal pose. The number of images corresponding to each of the six categories of expressions is roughly the same (80 images per class). The dataset is challenging since it is closer to natural human behaviour and figure  10  shows that even for the same emotion, people can perform it in different ways. 3. test set: 20 images per class are picked out as test set. In total we have 120 facial expression images, randomly shuffled, to test the performance of our algorithm.
Experimental Setup and Analysis: Same experimental setup as in the control experiment has been followed. Firstly, the dataset is divided into two portions based on the number of images per class as defined in the previous DynEmo dataset protocol. Then, RFFD is applied in which the optimal random matrix that generates good discriminative features and the optimal dimensionality size (n-features = 250 feature points) are derived. Therefore, passing through the first stage of SFER algorithm, we get a training set with 360 images and 250  feature points (n) in addition to a testing set of 120 images and 250 feature points. The average recognition rate over the projected data prior to the second stage of SFER algorithm is 68. 4%. The performance of RFFD is compared with PCA which achieves an average recognition rate of 24% only.
Approach Average Recognition Rate % SFER (ours) 91. 68 LC-KSVD-1 20. 1 LC-KSVD-2 85. 4 est number of misclassifications is obtained for "irritation" (IRR) and "worried" (WO). Figure  8  shows that WO and expressions are visually close to each other. For the rest of the classes like "curious" (CU), "astonishment" (AST) and "fear" (FE), the obtained recognition rate is above 95%. The class "disgust" (DI) got a 93% recognition rate. The average recognition rate is 91. 67%. Table  5  shows the recognition rate on the DynEmo dataset compared to the other sparse approaches. It can be seen that our approach performs much better than LC-K-SVD1 and LC-K-SVD2.