Teikyo Medical and medicine Journal (ISSN:03875547) is a monthly peer reviewed fast publishing international medical and medicine journal that aims to publish good quality of Medical and pharmaceutical, medicine and health science Journal.

In this paper, a study was made to determine the properties of Jovian radio bursts emitted at frequency 20.1MHZ. The data were provided from the Radio Jove archive for twelve years (2000-2012) for multi stations. The duration time for Long bursts (L) was (10-30) seconds and for Short bursts (S) was (10-20) seconds. The effect of radio bursts from the Sun and the galactic background were calculated at the same frequency and were found that radio bursts from the Sun will reduce the occurrence probability of Jovian radio bursts much more than radio bursts from the galactic background. The distribution of Jovian radio bursts was different; the occurrence probability with respect to the northern latitudes was more than the southern latitudes.

The traditional centralized network management approach presents severe efficiency and scalability limitations in large scale networks. The process of data collection and analysis typically involves huge transfers of management data to the manager which cause considerable network throughput and bottlenecks at the manager side. All these problems processed using the Agent technology as a solution to distribute the management functionality over the network elements. The proposed system consists of the server agent that is working together with clients agents to monitor the logging (off, on) of the clients computers and which user is working on it. file system watcher mechanism is used to indicate any change in files. The results were presente

With the continuous progress of image retrieval technology, the speed of searching for the required image from a large amount of image data has become an important issue. Convolutional neural networks (CNNs) have been used in image retrieval. However, many image retrieval systems based on CNNs have poor ability to express image features. Content-based Image Retrieval (CBIR) is a method of finding desired images from image databases. However, CBIR suffers from lower accuracy in retrieving images from large-scale image databases. In this paper, the proposed system is an improvement of the convolutional neural network for greater accuracy and a machine learning tool that can be used for automatic image retrieval. It includes two phases

Abstract:
Al-Marba'aniyah, which is a long cold wave, was defined by ancient
Iraqis. It represents the coldest days in Iraq. In this research paper, a new
scale was put to define it. It shows that the period between the minimum
temperature degree recoded in December and the minimum temperature
degree recorded in January is considered to be the period of Al-Marba'aniyah.
The research concluded that Al-Marba'aniyah is unsteady and it changes in
the days of its occurrence. It was also concluded that the dates of the
beginning and the end of Al-Marba'aniyah are unsteady, too. Moreover, it was
found out that each of the Siberian high, European high, and finally the
subtropical high are the responsible systems for

  The phenomenon of child labor, any activity performed by a child and represents a contribution to the production, this phenomenon had been rife in Iraqi society, after that the proportion of child labor for the age group (6-14 years) amounting to 3% in 2006, became for  the same age group of 8% in 2008*.                                                      

It is recognized that each phenomenon reasons, the phenomenon which our atten

Due to the huge variety of 5G services, Network slicing is promising mechanism for dividing the physical network resources in to multiple logical network slices according to the requirements of each user. Highly accurate and fast traffic classification algorithm is required to ensure better Quality of Service (QoS) and effective network slicing. Fine-grained resource allocation can be realized by Software Defined Networking (SDN) with centralized controlling of network resources. However, the relevant research activities have concentrated on the deep learning systems which consume enormous computation and storage requirements of SDN controller that results in limitations of speed and accuracy of traffic classification mechanism. To fill thi