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

Big data of different types, such as texts and images, are rapidly generated from the internet and other applications. Dealing with this data using traditional methods is not practical since it is available in various sizes, types, and processing speed requirements. Therefore, data analytics has become an important tool because only meaningful information is analyzed and extracted, which makes it essential for big data applications to analyze and extract useful information. This paper presents several innovative methods that use data analytics techniques to improve the analysis process and data management. Furthermore, this paper discusses how the revolution of data analytics based on artificial intelligence algorithms might provide

Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an

     The objective of this paper is, first, study a new collection of sets such as field and we discuss the properties of this collection. Second, introduce a new concepts related to the field such as measure on field, outer measure on field and we obtain some important results deals with these concepts. Third, introduce the concept of null-additive on field as a generalization of the concept of measure on field. Furthermore, we establish new concept related to - field noted by weakly null-additive on field as a generalizations of the concepts of measure on and null-additive. Finally, we introduce the restriction of a set function  on field and many of its properties and characterizations are given.

The present study is concern with the interaction between the naidid worms diversity and the species of aquatic plant within which the worms found . For this purpose, two species of aquatic plant were used, Ceratophyllum demersum and Eichhornia crassipes. 12 samples of aquatic plants were collected , as one sample monthly for a period from September 2012 to September 2013 from different site on Tigris river within Baghdad City. From C. demersum, 1428 individuals, were sorted during the study period, related to 17 species. 12 species of subfamily Naidinae which are Chaetogaster limnaei , C. diastrophus , Ophidonais serpentine , Dero ( Dero) digitata. , D.(D.) evelinae , Nais pseudobtosa , N.simplex, N.stolci , N.Paradalis , N.elingiu

Twitter data analysis is an emerging field of research that utilizes data collected from Twitter to address many issues such as disaster response, sentiment analysis, and demographic studies. The success of data analysis relies on collecting accurate and representative data of the studied group or phenomena to get the best results. Various twitter analysis applications rely on collecting the locations of the users sending the tweets, but this information is not always available. There are several attempts at estimating location based aspects of a tweet. However, there is a lack of attempts on investigating the data collection methods that are focused on location. In this paper, we investigate the two methods for obtaining location-based dat

In present study, the technique was used, including nuclear track detector type (CR-39), for appreciative concentrations uranium and radon in soil samples from Baghdad University Campus-AL-Jadiriyah utilizing a prolonged -term with a solid-state nuclear path sensor, a technique for charged particles has been developed., the radon concentrations, effective dose rate and uranium concentrations have measured in soil samples. Eight various venues from soil Baghdad University Campus have appointed. The results indicated variant values about uranium and radon concentrations, the average value for radon gas, effective dose rate and uranium concentrations was found to be 281.59 Bq/cm3, 7.09 mSv/y and 0.01 Bq/mm-2 respectively. All results a