Everybody is connected with social media like (Facebook, Twitter, LinkedIn, Instagram…etc.) that generate a large quantity of data and which traditional applications are inadequate to process. Social media are regarded as an important platform for sharing information, opinion, and knowledge of many subscribers. These basic media attribute Big data also to many issues, such as data collection, storage, moving, updating, reviewing, posting, scanning, visualization, Data protection, etc. To deal with all these problems, this is a need for an adequate system that not just prepares the details, but also provides meaningful analysis to take advantage of the difficult situations, relevant to business, proper decision, Health, social media, science, telecommunications, the environment, etc. Authors notice through reading of previous studies that there are different analyzes through HADOOP and its various tools such as the sentiment in real-time and others. However, dealing with this Big data is a challenging task. Therefore, such type of analysis is more efficiently possible only through the Hadoop Ecosystem. The purpose of this paper is to analyze literature related analysis of big data of social media using the Hadoop framework for knowing almost analysis tools existing in the world under the Hadoop umbrella and its orientations in addition to difficulties and modern methods of them to overcome challenges of big data in offline and real –time processing. Real-time Analytics accelerates decision-making along with providing access to business metrics and reporting. Comparison between Hadoop and spark has been also illustrated.
the banks are one of the public services that must be available in the city to ensure easy financial dealings between citizens and state departments and between the state departments with each other and between the citizens themselves and to ensure easy access to it, so it is very important to choose the best location for the bank, which can serve the largest number of The population achieves easy access. Due to the difficulty of obtaining accurate information dealing with the exact coordinates and according to the country's specific projection, the researcher will resort to the default work using some of the files available in the arcview program
The focus of this article is to add a new class of rank one of modified Quasi-Newton techniques to solve the problem of unconstrained optimization by updating the inverse Hessian matrix with an update of rank 1, where a diagonal matrix is the first component of the next inverse Hessian approximation, The inverse Hessian matrix is generated by the method proposed which is symmetric and it satisfies the condition of modified quasi-Newton, so the global convergence is retained. In addition, it is positive definite that guarantees the existence of the minimizer at every iteration of the objective function. We use the program MATLAB to solve an algorithm function to introduce the feasibility of
... Show MoreA new Species of the Cerambycinae belonging to the genus Hesperophanes was found new to the fauna of Iraq and Science. H. testaceus was studied in details and the male genitalia were illustrated. Type's paratypes and the locality of this newly described Species were mentioned.
The process of soil classification in Iraq for industrial purposes is important topics that need to be extensive and specialized studies. In order for the advancement of reality service and industrial in our dear country, that a lot of scientific research touched upon the soil classification in the agricultural, commercial and other fields. No source and research can be found that touched upon the classification of land for industrial purposes directly. In this research specialized programs have been used such as geographic information system software The geographical information system permits the study of local distribution of phenomena, activities and the aims that can be determined in the loca
Wireless sensor applications are susceptible to energy constraints. Most of the energy is consumed in communication between wireless nodes. Clustering and data aggregation are the two widely used strategies for reducing energy usage and increasing the lifetime of wireless sensor networks. In target tracking applications, large amount of redundant data is produced regularly. Hence, deployment of effective data aggregation schemes is vital to eliminate data redundancy. This work aims to conduct a comparative study of various research approaches that employ clustering techniques for efficiently aggregating data in target tracking applications as selection of an appropriate clustering algorithm may reflect positive results in the data aggregati
... Show MoreOur recent work displays the successful preparation of Schiff_bases that carried out between hexane-2,5-dione and 2 moles of (Z)-3-hydrazineylideneindolin-2-one forming in Schiff-bases-(L), Which in turn allowed combining with each of the next metal ions: (M2+) = Ni, Mn, Zn, Cu and Co forming complexes_ in high stability. The formation of resulting Schiff_ bases (L) is detected spectrally using LC_Mss which gave approximately matching results with theoretical incomes, 1HNMR proves the founding of doublet signal of (2H) for 2NH, FTIR indicates the occurrence of two interfered imine bands and UV-VIS mean is also indecates the formation of ligand. On the other hand, complexes-based-Schiff were characterized using the s
... Show MoreThe sequence in the upper part of the Balambo Formation is composed mainly of limestone alternating with marly limestones and dark grey shale in the Bosheen section (eastern Sulaymaniyah, northeastern Iraq) and has been studied in terms of its rare earth element (REE) content. The REEs are very low compared to modern marine sediments. They are depletion in LREEs, and enrichment in HREEs and (La/Yb)N in the studied rocks, indicating that these sediments retained the REEs pattern of marine waters. The negative Ce anomaly reflects direct sedimentation from marine waters under anoxic conditions with the contribution of terrigenous clays. The positive correlation of ∑REEs with Al, Ti, and Y, and the negative correlation of ∑REE
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Shear and compressional wave velocities, coupled with other petrophysical data, are vital in determining the dynamic modules magnitude in geomechanical studies and hydrocarbon reservoir characterization. But, due to field practices and high running cost, shear wave velocity may not available in all wells. In this paper, a statistical multivariate regression method is presented to predict the shear wave velocity for Khasib formation - Amara oil fields located in South- East of Iraq using well log compressional wave velocity, neutron porosity and density. The accuracy of the proposed correlation have been compared to other correlations. The results show that, the presented model provides accurate
... Show MoreMany approaches of different complexity already exist to edge detection in
color images. Nevertheless, the question remains of how different are the results
when employing computational costly techniques instead of simple ones. This
paper presents a comparative study on two approaches to color edge detection to
reduce noise in image. The approaches are based on the Sobel operator and the
Laplace operator. Furthermore, an efficient algorithm for implementing the two
operators is presented. The operators have been applied to real images. The results
are presented in this paper. It is shown that the quality of the results increases by
using second derivative operator (Laplace operator). And noise reduced in a good
Some of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems. Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic. Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance. In this study, two different sets of select
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