A la fin du XVIIIe siècle, les penseurs français dont Rousseau et Saint-Pierre, commencent à mettre en question la civilisation européenne. Dans leurs œuvres les plus importantes, ces deux auteurs parlent de la société européenne d'une façon très banale. Ils font, par contre, une invitation à la Solitude et l'isolement dans la nature afin d'éviter la corruption de l'âme par la société mondaine. Ces écrivains-penseurs croient que la société peut gâter l'humanité de l'individu. Ils suggèrent à travers les images innocentes de leurs principaux personnages vivant dans la campagne, un monde idéal où il n'y a que pureté et chasteté.  Dans les deux œuvres que nous avons choisies (Paul et Virginie de Bernardin de

Cutaneous leishmaniasis is one of endemic diseases in Iraq. It is considered as widely health problem and is an uncontrolled disease. The aim of the study is to identify of Leishmania species that cause skin lesions among patients in Thi-Qar Province, South of Iraq, also to detect some virulence factors of L. tropica. This study includes three local locations, Al-Hussein Teaching, Suq Al-Shyokh General and Al-Shatrah General Hospitals in Province for the period from the beginning of December 2018 to the end of September 2019. The samples were collected from 80 patients suffering from cutaneous leishmaniasis, both genders, different ages, various residence places and single and multiple lesions. Nested-PCR technique was

This research paper studies the use of an environmentally and not expensive method to degrade Orange G dye (OG) from the aqueous solution, where the extract of ficus leaves has been used to fabricate the green bimetallic iron/copper nanoparticles (G-Fe/Cu-NPs). The fabricated G‑Fe/Cu-NPs were characterized utilizing scanning electron microscopy, BET, atomic force microscopy, energy dispersive spectroscopy, Fourier-transform infrared spectroscopy and zeta potential. The rounded and shaped as like spherical nanoparticles were found for G-Fe/Cu‑NPs with the size ranged 32-59 nm and the surface area was 4.452 m²/g. Then the resultant nanoparticles were utilized as a Fenton-like oxidation catalyst. The degradation efficiency of

Sludge worm samples were collected from the Tigers River sediment during the period from November 2018 to June 2019 in Al Sarafiya District/ Baghdad- Iraq. Biometric morphological measurements focusing on the form of penis sheath and chaetal morphology were used for species identification, in addition to molecular analysis by amplification of conserved 18s rRNA encoding gene using ITS1 and ITS4 universal primers.According to the morphological measurement records, the results revealed the existence of Limnodrilus hoffmeisteri Claparede 1862, L. claparedeianus Ratzel, 1868 and L. cervix Brinkhurst 1963. Other two groups of specimens, with short penis sheath, were identified by molecular technology as L

ي لا ماق ثحبلا فادهأ قيقحتلو ثحبلا ةنيعل نايبتسا ءارجاو فراصملل ةيلاملا مئاوقلا ليلحتب ثحاب اهمهأ ناك تاجاتنتسا ىلإ ثحابلا لصوت دقو لإ صاخ معد دوجو مدع نم ةيفرصملا رطاخملا ةراد ةروصب اهدوجو مدعو فراصملل ةماعلا تارادلاا يف اهدوجو رصتقي ثيح ،ايلعلا تاهجلا لبق نم ديزي امم ،عورفلا يف ةلاعف مدع ةجيتن عورفلا نم ةدلوتملاو فراصملا اههجاوت يتلا رطاخملا اهمهأ ناك تايصوت ىلإ ثحابلا لصوت دقو امك ،ةيفرصملا تلاماعم

Deep learning techniques are applied in many different industries for a variety of purposes. Deep learning-based item detection from aerial or terrestrial photographs has become a significant research area in recent years. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed.  A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles and classification probabilities for an image. In layman's terms, it is a technique for instantly identifying and recognizing

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

Deep learning techniques are used across a wide range of fields for several applications. In recent years, deep learning-based object detection from aerial or terrestrial photos has gained popularity as a study topic. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed. A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles andclassification probabilities for an image. In layman's terms, it is a technique for instantly identifying and rec

 

    The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.

  In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.

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