Co(II) ion was determined by a new, accurate, sensitive and rapid method via a
continuous flow injection analysis (CFIA) with a chemiluminescence reaction based on
the oxidation of Luminol which is loaded on poly acrylic acid gel beads by hydrogen
peroxide in presence of Cobalt (II) ion as a chemiluminescence catalyst. Chemical and
physical parameters were investigated to obtain the best conditions. Linear dynamic
range of Cobalt (II) ion was from 0.1-20.0 μg.ml-1 with a correlation coefficient r =
0.9758, limit of detection (L.O.D) 0.2 ng/sample from the step wise dilution of lowest
concentration in the calibration graph with the percentage relative standard deviation for
3 μg.ml-1 Co(ll) solution is 0.8537% (n=5). The method was applied successfully for the
determination of Co (II) ion in CoMo catalyst type ( K F124- 3E).
Chemiluminometric- CFIA for the Determination of Cobalt (ll) Ion in Commercial Cobalt-Molybdenum Catalyst (K F124-3E) Used in Desulphurization Processes of Petroleum Products via Multi Gel Beads Reactor.
Chemiluminescence
Flow injection analysis
gel beads
Cobalt (ll) Ion
CoMo Catalyst (K F124- 3E)
Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
Arabic Sentiment Analysis (ASA) Using Deep Learning Approach
Deep Learning (DL)
Machine Learning (ML)
Arabic Sentiment Analysis (ASA)
word embedding
Long-Short Term Memory (LSTM)
features
Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l
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