EM International

News feeds are at the forefront of news forms that are close to the public's attention for their rapid news content in two directions:

1. its speed in summarizing events in one or two sentences easy to be understood and realized.
2. highlight the most important contents of screenings or news broadcast.

The researchers felt that the importance of these brief news compared to news broadcast, breaking news and news subtitle are still ambiguous, as well as their contents.

The researchers selected the city of Baghdad as a community to research and prepare a questionnaire form containing (11) questions.

The questionnaires were distributed to a non-relative stratified

Background: Hypertension is probably the most important public health problem around the world. People with periodontal disease may be at greater risk of hypertension. The inflammatory effects of periodontal disease help to promote endothelial dysfunction in arteries which may lead to changes in blood pressure. Salivary MMP-8 has been associated with both periodontal disease and prevalent hypertension. Aim of study: This study was conducted to measure salivary matrix metalloproteinase - 8, in relation to periodontal health condition among a group of patients with hypertension in comparison with control group. Materials and methods: Ninety subjects, aged 45-50 years old were included in this study, seeking treatment for chest pain in Ibn-A

In this research a new system identification algorithm is presented for obtaining an optimal set of mathematical models for system with perturbed coefficients, then this algorithm is applied practically by an “On Line System Identification Circuit”, based on real time speed response data of a permanent magnet DC motor. Such set of mathematical models represents the physical plant against all variation which may exist in its parameters, and forms a strong mathematical foundation for stability and performance analysis in control theory problems.

Abstract 

For sparse system identification,recent suggested algorithms are  -norm Least Mean Square (  -LMS), Zero-Attracting LMS (ZA-LMS), Reweighted Zero-Attracting LMS (RZA-LMS), and p-norm LMS (p-LMS) algorithms, that have modified the cost function of the conventional LMS algorithm by adding a constraint of coefficients sparsity. And so, the proposed algorithms are named  -ZA-LMS, 

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