El estudio se clasifica dentro los estudios teóricos sobre literatura que se ocupa del estudio de los métodos de la crítica literaria: El Estructralismo literario francés y el Formalismo ruso del siglo XX que se utilizan en la interpretación literaría. Las dos corrientes literarias estudian la literatura como ciencia que busca aplicar un método científico al estudio de la literatura. Dicho estudio trata de exponer las teorías críticas que surgen en el debate de la interpretación de los textos literarios como el de Susan Sontag, Ricoeur Paul y Mijail Bajitin, etc. Además se incluye algunos ejemplos implican el análisis estructuralista y formalista como Kafka y la tragedia Judía. y Sur Racine.

ABSTRACT:

Schiff base (methyl 6-(2- (4-hydroxyphenyl) -2- (1-phenyl ethyl ideneamino) acetamido) -3, 3-dimethyl-7-oxo-4-thia-1-azabicyclo[3.2.0] heptane-2-carboxylate)Co(II), Ni(II), Cu (II), Zn (II), and Hg(II)] ions were employed to make certain complexes. Metal analysis M percent, elemental chemical analysis (C.H.N.S), and other standard physico-chemical methods were used. Magnetic susceptibility, conductometric measurements, FT-IR and UV-visible Spectra were used to identified. Theoretical treatment of the generated complexes in the gas phase was performed using the (hyperchem-8.07) program for molecular mechanics and semi-empirical computations. The (PM3) approach was used to determine the heat of formation (ΔH˚f), binding energy (ΔEb), an

The preparation and spectral characterization of complexes for Co(II), Ni(II), Cu(II), Cd(II), Zn(II) and Hg(II) ions with new organic heterocyclic azo imidazole dye as ligand 2-[(2`-cyano phenyl) azo ]-4,5-diphenyl imidazole ) (2-CyBAI) were prepared by reacting a dizonium salt solution of 2-cyano aniline with 4,5-diphenyl imidazole in alkaline ethanolic solution .These complexes were characterized spectroscopically by infrared and electronic spectra along with elemental analysis‚ molar conductance and magnetic susceptibility measurements. The data show that the ligand behaves a bidantate and coordinates to the metal ion via nitrogen atom of azo and with imidazole N3 atom. Octahedral environment is suggested for all metal complex

المستودع الرقمي العراقي. مركز المعلومات الرقمية التابع لمكتبة العتبة العباسية المقدسة

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

Audio classification is the process to classify different audio types according to contents. It is implemented in a large variety of real world problems, all classification applications allowed the target subjects to be viewed as a specific type of audio and hence, there is a variety in the audio types and every type has to be treatedcarefully according to its significant properties.Feature extraction is an important process for audio classification. This workintroduces several sets of features according to the type, two types of audio (datasets) were studied. Two different features sets are proposed: (i) firstorder gradient feature vector, and (ii) Local roughness feature vector, the experimentsshowed that the results are competitive to

Aspect categorisation and its utmost importance in the eld of Aspectbased Sentiment Analysis (ABSA) has encouraged researchers to improve topic model performance for modelling the aspects into categories. In general, a majority of its current methods implement parametric models requiring a pre-determined number of topics beforehand. However, this is not e ciently undertaken with unannotated text data as they lack any class label. Therefore, the current work presented a novel non-parametric model drawing a number of topics based on the semantic association present between opinion-targets (i.e., aspects) and their respective expressed sentiments. The model incorporated the Semantic Association Rules (SAR) into the Hierarchical Dirichlet Proce

The increasing complexity of assaults necessitates the use of innovative intrusion detection systems (IDS) to safeguard critical assets and data. There is a higher risk of cyberattacks like data breaches and unauthorised access since cloud services have been used more frequently. The project's goal is to find out how Artificial Intelligence (AI) could enhance the IDS's ability to identify and classify network traffic and identify anomalous activities. Online dangers could be identified with IDS. An intrusion detection system, or IDS, is required to keep networks secure. We must create efficient IDS for the cloud platform as well, since it is constantly growing and permeating more aspects of our daily life. However, using standard intrusion