Abstract

Characterized by the Ordinary Least Squares (OLS) on Maximum Likelihood for the greatest possible way that the exact moments are known , which means that it can be found, while the other method they are unknown, but approximations to their biases correct to 0(n^-1) can be obtained by standard methods. In our research expressions for approximations to the biases of the ML estimators (the regression coefficients and scale parameter) for linear (type 1) Extreme Value Regression Model for Largest Values are presented by using the advanced approach depends on finding the first derivative, second and third.

The research problem revolves around the Iraqi public's use of digital television and cinematic websites، and their importance to the academic study and society، as it examines the public's relationship with these websites، usage habits، and the reasons for their interaction with them. And for the prevalence of this phenomenon of use، it was necessary to address the intensity، intentionality، and timing of use to theoretically root the subject of the study، which is one of the modern studies in Iraq and the Arab world. The survey approach، where the research was based on the theory of uses and gratifications that confer positivity and activity on the mass media audience.

     The researchers designed

Deixes belong to the field of both semantics and  pragmatics as they lie in the edge of these two fields. Pragmatically, they are concerned with the relationship between the structure of a language and the contexts. The present work aims at analyzing the use of deixes using Levinson’s (1983) and Yule's (1996) concept of deixes, where the latter maintained that the referents of the deixes cannot be realized apart from the context where they are used. He added that the contextual information of certain utterances involves information about the participants (the speaker and the addressee), the time and the place. Consequently, a qualitative- descriptive approach has been adopted to meet the objective of the study which reads, “exam

ABSTRACT: Polypyrrole and polypyrrole / silver nanocomposites were fabricated by in-situ polymerization employing Ammonium Persulphate as an oxidizing agent. Nanocomposites were synthesized by combining polypyrrole and silver nanoparticles in various weight percentages (0.1%, 0.5%, 3%, 5% and 7% wt.). Crystallographic data were collected using X-ray diffraction.  PPy particles were found to have an orthorhombic symmetry. In contrast, PPy/Ag nanocomposites were reported to have monoclinic structure. The crystallite size was determined by XRD using Scherrer equation and considered to be within 49 nm range. DC conductivity of pelletized samples was evaluated in the temperature range of 323.15k to 453.15k. The conductivity displayed an

ABSTRACT: Polypyrrole and polypyrrole / silver nanocomposites were fabricated by in-situ polymerization employing Ammonium Persulphate as an oxidizing agent. Nanocomposites were synthesized by combining polypyrrole and silver nanoparticles in various weight percentages (0.1%, 0.5%, 3%, 5% and 7% wt.). Crystallographic data were collected using X-ray diffraction.  PPy particles were found to have an orthorhombic symmetry. In contrast, PPy/Ag nanocomposites were reported to have monoclinic structure. The crystallite size was determined by XRD using Scherrer equation and considered to be within 49 nm range. DC conductivity of pelletized samples was evaluated in the temperature range of 323.15k to 453.15k. The conductiv

    Ni2O3 nanomaterial, a phase of nickel oxide, is synthesized by a simple chemical process. The pure raw materials used in the present process were nickel chloride hexahydrate NiCl2.6H2O and potassium hydroxide KOH by utilizing temperature at 250 oC for 2 hour.  The structural, morphological and optical properties of the synthesized specimens of Ni2O3 were investigated employing diverse techniques such as XRD, AFM, SEM and UV-Vis, respectively. The XRD technique confirms the presence of Ni2O3 nanomaterial with crystal size of 57.083 nm which indexing to the (2θ) of 31.82; this results revealed the Ni2O3 was a phase of nickel oxide with Nano structure. The synthesized Ni2O3 will be useful in manufacturng electrodes materials f

Purpose A diagnosis of tuberculosis (TB) of the head and neck has been a dilemma for clinicians, because the clinical and pathologic features tend to mimic different pathologies. Our study aimed to identify the demographic, clinical, and pathologic features of head and neck TB to help healthcare providers in the early detection of the disease. Materials and Methods We performed a retrospective analysis using the medical archives at the pathology laboratory. Twenty-one patients with a clinical and pathologic diagnosis of head and neck TB were identified from 2010 to 2019. Results The age distribution was broad, with 28.5% of the patients younger than 15 years old. Seven patients had oral TB, with the most common sites affected the labial ves

Artificial intelligence techniques are reaching us in several forms, some of which are useful but can be exploited in a way that harms us. One of these forms is called deepfakes. Deepfakes is used to completely modify video (or image) content to display something that was not in it originally. The danger of deepfake technology impact on society through the loss of confidence in everything is published. Therefore, in this paper, we focus on deepfakedetection technology from the view of two concepts which are deep learning and forensic tools. The purpose of this survey is to give the reader a deeper overview of i) the environment of deepfake creation and detection, ii) how deep learning and forensic tools contributed to the detection

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod