The aim of this paper is to approximate multidimensional functions f∈C(R^s) by developing a new type of Feedforward neural networks (FFNS) which we called it Greedy ridge function neural networks (GRGFNNS). Also, we introduce a modification to the greedy algorithm which is used to train the greedy ridge function neural networks. An error bound are introduced in Sobolov space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result in [1]).

In the spreading of the Internet, mobile smart devices, and interactive websites such as YouTube, the educational video becomes more widespread and deliberative among users. The reasons for its spread are the prevalence of technologies, cheap cost, and easy to use. However, these products often lack to the distinction in video production. By following videos of an educational channel on YouTube, some comments found to discuss the lack of the content presented to motivate the learners, which lead to reduce the viewers of the videos. Therefore, there is an important decision to find general standards for the design and production of educational videos. A list of standards has been drawn up to help those interested in producing educational

     The searching process using a binary codebook of combined Block Truncation Coding (BTC) method and Vector Quantization (VQ), i.e. a full codebook search for each input image vector to find the best matched code word in the codebook, requires a long time.   Therefore, in this paper, after designing a small binary codebook, we adopted a new method by rotating each binary code word in this codebook into 900 to 2700 step 900 directions. Then, we systematized each code word depending on its angle  to involve four types of binary code books (i.e. Pour when , Flat when  , Vertical when, or Zigzag). The proposed scheme was used for decreasing the time of the coding procedure, with very small distortion per block, by designing s

 Internet of Things (IoT) contributes to improve the quality of life as it supports many applications, especially healthcare systems. Data generated from IoT devices is sent to the Cloud Computing (CC) for processing and storage, despite the latency caused by the distance. Because of the revolution in IoT devices, data sent to CC has been increasing. As a result, another problem added to the latency was increasing congestion on the cloud network. Fog Computing (FC) was used to solve these problems because of its proximity to IoT devices, while filtering data is sent to the CC. FC is a middle layer located between IoT devices and the CC layer. Due to the massive data generated by IoT devices on FC, Dynamic Weighted Round Robin (DWRR)

The theory of Multi-Criteria Decision Making (MCDM) was introduced in the second half of the twentieth century and aids the decision maker to resolve problems when interacting criteria are involved and need to be evaluated.  In this paper, we apply MCDM on the problem of the best drug for rheumatoid arthritis disease. Then, we solve the MCDM problem via -Sugeno measure and the Choquet integral to provide realistic values in the process of selecting the most appropriate drug. The approach confirms the proper interpretation of multi-criteria decision making in the drug ranking for rheumatoid arthritis.

     The searching process using a binary codebook of combined Block Truncation Coding (BTC) method and Vector Quantization (VQ), i.e. a full codebook search for each input image vector to find the best matched code word in the codebook, requires a long time.   Therefore, in this paper, after designing a small binary codebook, we adopted a new method by rotating each binary code word in this codebook into 90⁰ to 270⁰ step 90⁰ directions. Then, we systematized each code word depending on its angle  to involve four types of binary code books (i.e. Pour when , Flat when  , Vertical when, or Zigzag). The proposed scheme was used for decreasing the time of the coding pro

      The Arabic Language is the native tongue of more than 400 million people around the world,  it is also a language that carries an important religious and international weight.  The Arabic language has taken its share of the huge technological explosion that has swept the world, and therefore it needs to be addressed with natural language processing applications and tasks.

This paper aims to survey and gather the most recent research related to Arabic Part of Speech (APoS), pointing to tagger methods used for the Arabic language, which ought to aim to constructing corpus for Arabic tongue. Many AI investigators and researchers have worked and performed POS utilizing various machine-learning methods, such as Hidden-Mark

The  role  of  free  radicals  generation  and  Lipid  Peroxidation

during the course of ischemic heart disease is well establshed as a basic for Pthogenesis and subsequent tissue damage consequenes . In an attempt to shed a light on the possible relationship between lipid peroxidation and some antioxidant.

The effect of vitamine E  (as a potent antioxidant free radical scavenger) . On the serum levels of the Lipoproteins, (HDLc) High Density Lipoprotein , (LDLc) Low Density Lipoprotein and (VLDLc) very Low Density Lipoprotein in healthy donors.

The  study  includes  (50) healthy  donors  from  males  and  females  ,

This study was conducted to determine the effect of vitamin A ( 10 mg/kg ) on avearage testis weight and sexual glands ( Prostate and Seminal Vesicle ) for albino male mice treated with Hexavalent chromium ( 1000 ppm ) .The current study 40 mice were divided into fife groups : 1st group treated with distilled water and considered an control group (C) / the 2nd group treated with sesame oil ( T1) / 3rd group was givin hexavalent chromium ( 1000 ppm ) (T2) / 4th group treated with vitamin A ( 10 mg / kg ) and exposed to hexavalent chromium ( 1000 ppm ) (T3) / 5th group treated with vitamin A ( 10 mg kg ) (T4) . The expermint lasted 35 day . the results showed a significant ( P ? 0.05 ) decrease in avearage testis weight and sexual glan

This study aims to analyze the messages of a number of global news outlets on Twitter. In order to clarify the news outlets tactics of reporting, the subjects and focus during the crisis related to the spread of the Covid-19 virus. The study sample was chosen in a deliberate manner to provide descriptive results. Three news sites were selected: two of the most followed, professional and famous international news sites: New York Times and the Guardian, and one Arab news site: Al-Arabiya channel.

A total of 18,085 tweets were analyzed for the three accounts during the period from (1/3/2020) to (8/4/2020). A content analysis form was used to analyze the content of the news coverage.   The results indicate an increase in th