Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

Background: Nasopharyngeal carcinoma (NPC) is one of the most challenging tumors because of their relative inaccessibility and that their spread can occur without significant symptoms with few signs, but Radiotherapy (RT) has a role in treatment of it.
Objectives: To show that RT is still the modality of choice in the treatment of NPC, to study modes of presentations, commonest histopathological types and their percentages, to show differences in the sensitivities of these types to RT and to find out a 5 year survival rate(5YSR) and its relation with lymph node involvement.
Methods: This is a retrospective study of 44 patients with NPC who were treated with routine RT from 1988-2007 at the institute of radiology and nuclear medicin

    In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A

Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea

The aim of this study is to screen the phytochemicals found in Populus euphratica leaves since this type of trees are used traditionally by many villagers as treatment for eczema and other skin disease and also this plant is poorly investigated for their phytochemicals especially in Iraq. Phytochemical screening of the extracts obtained from the n-hexane and chloroform fraction of leaves of Populus euphratica was done by Thin-layer chromatography and various spraying reagents to test if alkaloids, sterols and other compounds are present. UPLC-electrospray ionization –tandem mass spectroscopy along with GC-MS and HPTLC are used to identify the phytochemicals present in the plant leaves.UPLC-ESI-MS/MS method 20 compound

The present study aims to illuminate the assessment of the Turkish elite of the role of the Turkish media in forming the attitudes of public opinion vis a vis the attempted military coup of 15 July 2016. The authors utilized the survey method of a nominal sample of 315 individuals, equally distributed among the three foremost categories of the Turkish elite, namely: the political academic, and media elite. The foremost findings of the study are that the orientation of the coverage of the Turkish media of the events of the attempt military coup of 15 July, based on the perception and assessment of the Turkish elite, was positive to a high degree; it refuted the news and the inciting information given to foreign media revealed the bloodine

Objectives: With the advent of ongoing novel modalities toward the treatment of human epidermal growth factor receptor 2 (HER2)/NEU - positive malignancies, the serious side effects of chemoradiotherapy have been minimized. Hence, this study was conducted to identify the patterns of immunohistochemical expression of the promising therapeutic target (HER2/NEU) among Iraqi patients with medulloblastoma in an attempt to provide basic histological information’s that would help in future clinical researches.Materials and Methods: In this retrospective study, 42 formalin - fixed paraffin - embedded tissue blocks represent cases of surgically removed medulloblastomas were retrieved from the archived materials in a specialized surgical ho

The importance of kick tolerance in well operations has recently increased due to its implications in well design, in drilling and well control. To study a simple method for the application of kick tolerance concept in an effective way on the basis of field data, this research purpose is to improve knowledge about Kick Tolerance and represents a technical basis for the discussion on revision of standard procedure.

   The objective of this work is to review and to present a methodology of determination the kick tolerance parameters using the circulation kicks tolerance concepts.

   The proposed method allows to know, to evaluate and to analyze the kick tolerance problem in order to make the drilling exe

 An oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification