Literature Review on Artificial Neural Network and Support Vector Machine anchored in Face Recognition System
Rakesh Kumar Yadav, A.K Sachan
Sch J Eng Tech | 95-102
DOI : 10.36347/sjet
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In view of two fundamental reasons, face recognition system has gotten consideration in the research. The
primary reason is the extensive variety of business and law enforcement applications and second reason is concerned
with the accessibility of the attainable advancements. The combination of PCA-SVM (Principal Component Analysis and
Support Vector Machine) and PCA-ANN (Principal Component analysis and Artificial Neural Network) techniques for
face recognition system have been easily found in recent years. Some researchers came up to improve PCA-SVM and
PCA-ANN combinations. This paper gives state-of-the-art audits of these blends and tries to clarify the reason that why
PCA is utilized with numerous classifiers and which one combination is ideal to use in future.
Optimization of injection parameters for air foam profile control in low permeability oil field
Zhou Fu, Wang Li-ya
Sch J Eng Tech | 103-106
DOI : 10.36347/sjet
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In view of the high water cut, effect of strong anisotropy, low water drive spread coefficient and injected water
channeling of M block in A oil field, some research on the technology of M block air foam profile control was done. On
the basis of 3D geological model, method of numerical simulation and controlling variate method and input-output ratio
used as an economic evaluation index were chosen to optimize the injection parameters affecting the effect of profile
control. The research showed that, air foam profile control technology can significantly improve the output of M block.
On the same time, to M block in A oil field, the optimal injection parameters for injection were: the foaming agent
volume was 0.5PV, the foaming agent injection rate was 13m3/d, foaming agent concentration was 0.3%, the foaming
agent injection cycle was 25d, gas injection rate was 40m3/d, gas-liquid ratio was 3:1.
Analysis of Corrosion Properties caused by Zn Fume in Ni Alloy
Min-Sook Baek, Man-Bok Park, Kyeong-Cheol Baek, Pub-Sung Kang, Ki-Bok Heo, Dong-Joo Yoon, Joon-Seop Kwak
Sch J Eng Tech | 107-112
DOI : 10.36347/sjet
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In this study, the manufactured Ni alloy was tested on how much it had corrosion resistance against Zn fume
when it was used in the hot dip galvanizing equipment in the steel plant. Two kinds of materials currently used in the
equipment, SM45C(steel for mechanical structure, KS) and Inconel(typical corrosion-resistant Ni alloy), were selected as
the reference groups. Two alloys of Ni-28Cr-4Mo-2Ti and Ni-20Cr-10Mo-1Ti were designed and the same heat
treatment as Inconel 625 was conducted for a proper comparison. Zn fume was generated by bubbling Ar gas from
molten Zn in the furnace and the samples were analyzed after 10, 20 and 30 days. According to the result of XRD and
Potentiodynamic polarization test, it was confirmed that ZnO was formed on the entire metal surface, which resulted in
the change of corrosion resistance on the samples. Especially the newly designed alloy out of samples showed the most
excellent corrosion resistance for the high temperature in the trial for 30 days.
Application of ionic liquid-based microwave-assisted extraction of anthocynin from lycium ruthenicum
Juan Zhang, Ting Fan, Jiangbin Xu, Shaoying Zhang, Min Jiang, Qing Liu, Yunsong Zhao
Sch J Eng Tech | 113-117
DOI : 10.36347/sjet
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The anthocyanin of lycium ruthenicum was extracted using ionic liquid combined with microwave. The
effects of ionic liquid species, ionic liquid concentration, microwave power and extraction time on the anthocyanin yield
of lycium ruthenicum were investigated. The results showed that the application of ionic liquid-based microwave-assisted
extraction might effectively increase the extraction rate of anthocyanin of lycium ruthenicum. The most suitable
conditions were 1.0 mol∕L of [Bmim]Br and 210 W of microwave power for 12 seconds with the sample to solvent ratio
of 1:30. Under the best condition, the anthocyanin yield of lycium ruthenicum was 2.92mg/g.