La contribución de los interventores españoles en el progreso de la arqueología del norte de Marruecos (1912-1956)

Il serait injuste d ’ attribuer le progrès de l ’ archéologie nord-marocaine durant la période du protectorat (1912- 1935) aux seuls grands archéologues. Outre César Luis de Montal - bán, le Père César Morán, Pelayo Quintero Atauri et Miguel Tarradell, on ne peut nier ou sous-estimer l ’ apport des “ Con - trôleurs ’’ dans l ’ amélioration des connaissances relatives à ce domaine. A travers la lecture de quelques ouvrages et articles publiés durant cette période et la consultation des documents conservés au Musée Archéologique de Tétouan, les noms de certains de ces fonctionnaires s ’ imposent. Bien qu ’ ils soient peu connus, T. García Figueras, C. Pereda Roig, R. Touceda Fontenla et d ’ autres “ Contrôleurs ’’ méritent une reconnais - sance à la hauteur des efforts qu ’ ils ont infatigablement dé - ployés et les résultats qu ’ ils ont obtenus et qui restent encore à exploiter.Sería injusto atribuir el progreso de la arqueolo - gía en el norte de Marruecos durante el periodo del Protecto - rado (1912-1935) solo a los grandes arqueólogos. Así, al lado de César Luis de Montalbán, del Padre César Morán, de Pe - layo Quintero Atauri y de Miguel Tarradell no podemos negar o subestimar la aportación de los Interventores en la mejora del conocimiento de esta disciplina. A través de la lectura de algunas obras y artículos publicados durante esta época y la consulta de documentos conservados en el Museo Arqueológico de Tetuán, se recuperan los nombres de algunos de estos funcionarios. Aunque sean poco conocidos, merece un reconocimiento, T. García Figueras, C. Pereda Roig, R. Touceda Fontenla, entre otros Interventores, para confirmar una realidad a la que no se le ha dado la importancia que merece. Debemos también ser conscientes de la calidad de los datos que nos han transmitido y que todavía no han sido completamente aprovechados

Tartessos, an overview of the Moroccan side of the Gibraltar strait

Del tema de Tartessos han surgido interesantes obras y artículos aclarando nuestros conocimientos sobre el desarrollo de las estructuras culturales, económicas y políticas de las sociedades locales en el sur de la península Ibérica. El presente ensayo que se interesa también por el norte de Marruecos, trata de plantear una perspectiva de análisis comparable a la que se efectúa en la zona conocida por todos como área geográfica de Tartessos. A partir de algunos elementos que hacen de la región del estrecho de Gibraltar una unidad donde los intercambios y las semejanzas son notables de forma brillante en el curso del periodo de las expansiones fenicia y griega, observamos que los componentes del concepto de Tartessos no son ausentes en la franja marroquí. En la misma dirección que apuntamos, el texto relatado en la Ora marítima (v. 331) nos sirve de indicio estimulante. Sobre todo, para abordar con mas detalles los aspectos de esta cuestión y comprobar la posibilidad o no de una época tartessica en el norte de Marruecos, es necesario emprender nuevas excavaciones especialmente concentrados en los sitios preromanos y a sus alrededores.Concerning Tartessos’s theme, many works and articles have appeared to enrich our kwnoledge about the progressing of cultural, economical and political structures among local societies in the south of the Iberian Peninsula. This essay which also takes into consideration the north of Morocco, aims at establishing an analytical comparable perspective of what exists in the area which is considered by all as a geographical zone of Tartessos. According to some elements which make the straits of Gibraltar region a unit in which exchanges and similarities are more noticeable during the Phoenician and Greek expansions period, we notice that the components of Tartessos concept are not absent in the Moroccan region. In the same direction, the text cited in the Ora maritima helps us as a stimulating point. Indeed, to approach this question in a more profound way, we believe in the necessity of undertaking new excavations especially in the pre-Roman sites and the areas around

ARMAS: Active Reconstruction of Missing Audio Segments

Digital audio signal reconstruction of a lost or corrupt segment using deep learning algorithms has been explored intensively in recent years. Nevertheless, prior traditional methods with linear interpolation, phase coding and tone insertion techniques are still in vogue. However, we found no research work on reconstructing audio signals with the fusion of dithering, steganography, and machine learning regressors. Therefore, this paper proposes the combination of steganography, halftoning (dithering), and state-of-the-art shallow (RF- Random Forest regression) and deep learning (LSTM- Long Short-Term Memory) methods. The results (including comparing the SPAIN, Autoregressive, deep learning-based, graph-based, and other methods) are evaluated with three different metrics. The observations from the results show that the proposed solution is effective and can enhance the reconstruction of audio signals performed by the side information (e.g., Latent representation and learning for audio inpainting) steganography provides. Moreover, this paper proposes a novel framework for reconstruction from heavily compressed embedded audio data using halftoning (i.e., dithering) and machine learning, which we termed the HCR (halftone-based compression and reconstruction). This work may trigger interest in optimising this approach and/or transferring it to different domains (i.e., image reconstruction). Compared to existing methods, we show improvement in the inpainting performance in terms of signal-to-noise (SNR), the objective difference grade (ODG) and the Hansen's audio quality metric.Comment: 9 pages, 2 Tables, 8 Figure

On Box-Cox Transformation for Image Normality and Pattern Classification

A unique member of the power transformation family is known as the Box-Cox transformation. The latter can be seen as a mathematical operation that leads to finding the optimum lambda ({\lambda}) value that maximizes the log-likelihood function to transform a data to a normal distribution and to reduce heteroscedasticity. In data analytics, a normality assumption underlies a variety of statistical test models. This technique, however, is best known in statistical analysis to handle one-dimensional data. Herein, this paper revolves around the utility of such a tool as a pre-processing step to transform two-dimensional data, namely, digital images and to study its effect. Moreover, to reduce time complexity, it suffices to estimate the parameter lambda in real-time for large two-dimensional matrices by merely considering their probability density function as a statistical inference of the underlying data distribution. We compare the effect of this light-weight Box-Cox transformation with well-established state-of-the-art low light image enhancement techniques. We also demonstrate the effectiveness of our approach through several test-bed data sets for generic improvement of visual appearance of images and for ameliorating the performance of a colour pattern classification algorithm as an example application. Results with and without the proposed approach, are compared using the AlexNet (transfer deep learning) pretrained model. To the best of our knowledge, this is the first time that the Box-Cox transformation is extended to digital images by exploiting histogram transformation.Comment: The paper has 4 Tables and 6 Figure

Contribution de l’écrit à l’enseignement/apprentissage du français dans le cycle primaire

L’écrit est une activité de production qui s’apprend grâce à la multiplication des occasions d’entraînement, à un enseignement/apprentissage progressif, à une pratique régulière et diversifiée basée sur des consignes claire, objectives et explicites qui orientent le scripteur. C’est ainsi que l’apprenant construit ses compétences scripturales, partant du principe que les aspects psychologiques de l’apprentissage jouent un rôle primordial dans la réussite ou l’échec des apprenants, ainsi que la maîtrise de la grammaire, du vocabulaire, de l’orthographe ont aussi un impact sur l’apprentissage de l’écrit

Estudi per la reutilització de contenidors marítims com a habitatge per a persones amb pocs recursos al Marroc

L’estudi tracta la viabilitat de convertir contenidors marítims en habitatges per gent amb pocs recursos al Marroc. En els últims anys, arran d’una major consciència global per la sostenibilitat del medi ambient i el reciclatge s’ha vist un clar increment en la reutilització d’aquests contenidors per finalitats relacionades amb la construcció. Aquesta transformació estudiada es basa en la utilització i aplicació de materials i tècniques sostenibles i renovables, fet que tot i presentar un major cost en un primer moment amb els anys s’amortitza tant econòmicament com en termes de sostenibilitat i empremta mediambiental. A part de fer l’estudi del tema principal que són els contenidors, la construcció i el disseny amb aquests, també s’estudia la instal·lació d’aigua calenta amb sistema tèrmic solar per proporcionar l’aigua calenta que manca a moltes llars en el país, tipus i aplicacions d’aïllaments tèrmics ecològics i sostenibles.Objectius de Desenvolupament Sostenible::11 - Ciutats i Comunitats Sostenibles::11.3 - Per a 2030, augmentar la urbanització inclusiva i sostenible, així com la capacitat de planificar i gestionar de manera participativa, integrada i sostenible els assentaments humans a tots els païso

Embed, Track and Authenticate Images Online with SDW-WebCrawler

The Internet is a widely open source to everyone to access Web pages. Using a web browser anyone can access websites. Because of this facility people can easily download images from websites without the owner's knowledge and use them in their own documents. Also image content may be modified for illegal purposes. Therefore a system is needed to authenticate images over the Web. Web image authentication is a challenging task that requires web crawlers to track and download images for authentication. Most of the known web image tracking engines such as TinEye and PicScout retrieve images according to the image infringement of the original image. However, these systems do not have the facility to authenticate the retrieved image, i.e. whether the retrieved image is similar to the original image or any image content alteration has occurred in the retrieved image and who is the copyrighted owner of the retrieved image.In order to solve the above mentioned drawbacks this paper presents a framework to protect image content, track it over the internet and authenticate the content. The proposed framework is based on self-embedding (i.e. where secret data and a binary version of the image are encrypted and embedded into the image), tracking (i.e. where a web crawler traverses over the internet to download images) and self-authentication (i.e. where the binary version of the hidden data is extracted to authenticate the image). Also another advantage of the proposed system is that it does not need the original image for the authentication process. </p

Prediction and classification of diabetic retinopathy using machine learning techniques

Diabetic retinopathy (DR) is a progressive and sight-threatening complication of diabetes mellitus, characterized by damage to the blood vessels in the retina. Early detection of DR is vital for timely intervention and effective management to prevent irreversible vision loss. This paper provides a comprehensive review of recent advancements in integrating machine learning (ML) and deep learning (DL) techniques for diagnosing DR, aiming to assist ophthalmologists in their manual diagnostic process. The paper presents a comprehensive definition of DR, elucidating the underlying pathological processes, clinical signs, and the various stages of DR classification, ranging from mild non-proliferative to severe proliferative DR. Integrating ML and DL in DR diagnosis has developed the field by offering automated and efficient methods and techniques to analyze retinal images. With high sensitivity and specificity, these techniques demonstrate their efficacy in accurately identifying DR-related lesions, such as microaneurysms, exudates, and hemorrhages. Furthermore, the paper examines diverse datasets employed in training and evaluating ML and DL models for DR diagnosis. These datasets range from publicly available repositories to specialized datasets curated by medical institutions. The role of large-scale and diverse datasets in enhancing model robustness and generalizability is emphasized