مطالب

Recently, Massive Open Online Courses have become sensational in the field of distance learning. There is a plethora of advantages being listed in learning through MOOCs but this pedagogy lacks in few areas when compared with traditional classes. One of those inabilities of MOOC is its support to prepare the students for laboratory-based courses. The authors of this study chose a MOOC course that teaches Digital Photography and created an Augmented Reality (AR) experience for a module that explains the different parts of a digital camera. The 2 nd year Multimedia students of Vellore Institute of Technology have been asked to experience the MOOC video followed by the AR experience. Their feedbacks before and after the AR experience has been statistically tested and reported. The results revealed that the students feel more confident and concentrate more when the instructional video was given as an AR experience. This study suggests that AR integrated MOOC modules might help in training students better for practice-based courses.

Deep learning techniques have become very popular among Artificial Intelligence (AI) techniques in many areas of life. Among many types of deep learning techniques, Convolutional Neural Networks (CNN) can be useful in image classification applications. In this work, a hybridized approach has been followed to classify lung nodule as benign or malignant. This will help in early detection of lung cancer and help in the life expectancy of lung cancer patients thereby reducing the mortality rate by this deadly disease scourging the world. The hybridization has been carried out between handcrafted features and deep features. The machine learning algorithms such as SVM and Logistic Regression have been used to classify the nodules based on the features. The dimensionality reduction technique, Principle Component Analysis (PCA) has been introduced to improve the performance of hybridized features with SVM. The experiments have been carried out with 14 different methods. It has been found that GLCM + VGG19 + PCA + SVM outperformed all other models with an accuracy of 94.93%, sensitivity of 90.9%, specificity of 97.36% and precision of 95.44%. The F1 score was found to be 0.93 and the AUC was 0.9843. The False Positive Rate was found to be 2.637% and False Negative Rate was 9.09%.

Le personnage fait partie des principaux composants de tout produit littéraire et s’introduit donc dans le domaine des théories et recherches littéraires. La sémiotique analysant la formation du sens, considère le personnage comme un signe motivé dont le signifiant est composé de plusieurs caractéristiques physiologiques et psychologiques, y compris le nom propre. Mahmoud Dowlatâbâdi est un écrivain réaliste iranien dont certaines particularités littéraires comme la construction du personnage, sont comparables aux grands réalistes tels que Balzac. En plus, malgré un langage poétique et une prose emphatique, le silence chez lui, dispose d'un statut remarquable. La plupart des personnages dowlatâbâdiens sont silencieux, voire muets, de par l’impossibilité à parler, le refus de la communication, la souffrance, la panique, etc. Basée sur les principes de la sémiotique du personnage, cette recherche vise à étudier le silence chez les personnages de Solouk, le roman dowlatâbâdien. Pour ce faire, on est obligé de recourir aux principes de la sémiotique tensive, ainsi qu'aux théories considérant le personnage comme un signe. Cette étude montrera donc comment le personnage/signe contribue à la formation du silence/signe chez Dowlatâbâdi. En conséquence, on verra comment le silence dowlatâbâdien se lie aux affects dysphoriques et aux sèmes divers, et dans les profondeurs du parcours génératif, à l'isotopie fondamentale de la vie/mort.

The South Caucasus region is experiencing crises that have continued for many years. Russia's war with Georgia in 2008 and the Armenian-Azerbaijani conflict over the Nagorno-Karabakh region after the collapse of the Soviet Union (1991) changed the security order in the South Caucasus. Russia has interests as a global player in the South Caucasus region and Kremlin considers it's near abroad as its backyard and exclusive sphere of influence. This article uses a descriptive-analytical method as well as the theory of regional security of Barry Buzan to answer the question of what is Russia's security strategy towards the South Caucasus region. The main hypothesis emphasizes that Russia's strategy in the South Caucasus region is to prevent securitization of the region against its economic and political interests, as well as prevent the influence and presence of NATO, in the region. The results show that in tensions with Georgia, Russia seeks to prevent Western interference and urges them to recognize the separation of Abkhazia and South Ossetia from Georgia. On the other hand, Russia's foreign policy in the face of the Nagorno-Karabakh crisis is to maintain a balance between the two parties involved, Armenia and Azerbaijan, to cooperate with both countries, and to resolve the Nagorno-Karabakh conflict by a political solution, not a military one. The purpose of this article is to examine Russia's security strategy in the South Caucasus, with a particular focus on Georgia and the Nagorno-Karabakh crisis from the beginning of the crisis until 2020. And then it offers specific reasons for the confrontation between Russia and the West, as well as Iran's role in regional security issues.