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 current study used extracts from the aloe vera (AV) plant and the hibiscus sabdariffa flower to make Ag-ZnO nanoparticles (NPs) and Ag-ZnO nanocomposites (NCs). Ag/ZnO NCs were compared to Ag NPs and ZnO NPs. They exhibited unique properties against bacteria and fungi that aren't present in either of the individual parts. The Ag-ZnO NCs from AV showed the best performance against E. coli, with an inhibition zone of up to 27 mm, compared to the other samples. The maximum absorbance peaks were observed at 431 nm and 410 nm for Ag NPs, at 374 nm and 377 nm for ZnO NPs and at 384 nm and 391 nm for Ag-ZnO NCs using AV leaf extract and hibiscus sabdariffa flower extract, respectively. Using field emission-scanning electron microscopes (FE-
... Show MorePreparation of Carboxy Methylated mPEG-Block-(4-Dodecyl Anilide) Copolymers and Their Visco Metric and Surface Tension Properties in THF
Mixed Kirkuk and Sharki-Baghdad crude oils were distilled into narrow fractions. The range of these narrow fractions were 10oC, starting from IBP to 350oC. The total distillates from mixed Kirkuk and Sharki-Baghdad crude oils were 58.25 vol % and 44.65 vol %, respectively.The hydrocarbons compositions (paraffin, naphthene, aromatic) in light fractions starting from IBP to 250oC were determined by using PONA analysis method. The results show that the paraffin content decreases with increasing mid percent boiling point of the fraction, while the naphthene, and aromatic increase with the increase of mid percent boiling point of mixed Kirkuk and Sharki-Baghdad crude oils. Three groups of empirical equations were developed for the prediction
... Show MoreTwo field experiments were conducted during the spring season 2020 in Karbala governorate to study the effect of irrigation systems, irrigation intervals, biofertilizers and polymers on some characteristics of vegetative growth and potato production. The results showed that there were significant differences in the values of the average plant height due to the effect of the double interference between the irrigation system and the improvers, The height of potato plant under any irrigation system was superior when adding conditioners compared to the control treatment, as it reached 48.56, 58.00 and 64.33cm when adding polymer, biofertilizer, and polymers+ biofertilizers, respectively compared with the control treatment of 44.64cm in the surf
... Show MoreGFRP was employed in constructions as an alternative to steel, which has many advantages like lightweight, large tensile strength and resist corrosion. Existing researches are insufficient in studying the influence of hybrid reinforced concrete composite columns encased by GFRP I-section (RCCCEG) and I-section steel (RCCCES). In this study twenty one (RC) specimens of a cross-section of 130 mm × 160 mm, with different length (long 1600 mm and short 750 mm) were encased by using I-section (steel and GFRP) and tested under various loading (concentric, eccentric and flexural loads). The test was focused on the influence of many parameters; load-carrying capacity, mode of failure, deformation and drawing an interaction diagram (N-
... Show MoreThe aim of the current research is to identify the level of organizational culture among the headmasters and teachers of intermediate and secondary schools in Arar city. It also aims to identify the effect of job variables, qualifications, educational stage, and years of experience on the level of organizational culture and its domains. The research sample consisted of 62 participants divided into 7 headmasters and 55 teachers. The researcher used the questionnaire of the organizational culture. The researcher used also statistical methods such as mean, standard deviation, t-test, and One way ANOVA. The results revealed that the level of organizational culture and its four domains were high, and there was no effect of the variables (teac
... Show MoreTo evaluate the shear bond strength and interfacial morphology of sound and caries-affected dentin (CAD) bonded to two resin-modified glass ionomer cements (RMGICs) after 24 hours and two months of storage in simulated body fluid at 37°C.
Sixty-four permanent human mandibular first molars (32 sound and 32 with occlusal caries, following the International Caries Detection and Assessment System) were selected. Each prepared substrate (sound and CAD) was co
Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m
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