One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

    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

The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

The use of ultraviolet rays is one of the methods of treating surface contamination of many foods especially pickles. however, there are some side effects to its use, especially in high percentage oil food products, it is necessary to determine the appropriate doses and time periods to avoid deterioration of its oil physicochemical characteristics. this study was conducted to see the effect of ultraviolet rays 15W on some chemical properties of olive oil when using it to preserve green olive pickles, treated for 5, 10 and 15 min daily. green olive fruits Iraqi variety (al-ashrasi), in season (2020-2021) were pickled using Spanish style, the best time period to pr

The bile salt hydrolase gene (bshA), encoding bile salt hydrolase enzyme (EC 3.5.1.24) from probiotic isolate Lactobacillus acidophilus Ar strain which is responsible for assimilation cholesterol were studied in the present work. About 801 bp in length DNA fragment of Lb. acidophilus Ar strain was amplified by PCR techniques. Two restriction sites (PstI/SacI) were added to each end of that fragment for manipulation of DNA during cloning. Amplified fragment inserted into pJET1.2\blunt end vector and pMG36e vector respectively. pJET1.2\blunt end vector is overexpression plasmid for E. coli MC1022, and pMG36e vector is a shuttle vector which is able to replicate in both E. coli and lactic acid bacteria. The resulted constructs were named as pJ

objective of this research is to identify some of the obstacles that face secondary school teachers of the Arabic language courses in using modern teaching methods in class.

The research focuses on secondary school teachers of the Arabic language courses at the central region of Nineveh Governorate for the school year (2008-2009). 30 teachers out of 792, were randomly chosen to apply the research tool upon.

To fulfill the objective of this research, the researcher first surveyed a number of teachers , he then identified four categories of obstacles; obstacles related to school administrative system and environment, the teacher, courses and pupils, and the nature of teaching method

Bac kground:
Failure is the state or condition of not meeting a desirable or intended objective, and may be viewed as the opposite of success; students always have a question "Why did I get this grade. On the contrary success leads towards new sources of earning, in fact there are a lot of interacting factors play such extrinsic and extrinsic to reach success.
Objec t i ves :
To explore internal and external factors causing students failure in medical college and to reconnoiter factors improve academic performance.
Methods: A cross-sectional study, conducted in Al Kindy College of Medicine, for the period from November 8th 2012 to May 1st 2013. Formal ethical considerations were obtained about participation and methodology. A