BenardNMoreauE.Electrical and mechanical characteristics of surface AC dielectric barrier discharge plasma actuators applied to airflow control. Exp Fluids2014;
55: 1846.
2.
MishraBKPanigrahiPK. Design and characterization of a novel dielectric barrier discharge plasma actuator for flow control application. In: Mishra BK and Panigrahi PK (eds) Fluid mechanics and fluid power contemporary research. India: Springer, 2017, pp.346–378.
3.
ZhaoGJiaMSongHet al. Characteristics of plasma aerodynamic actuation generated by polyphase dielectric barrier discharge. In: International conference on electrical and control engineering. London: IEEE Computer Society, 2010, pp.3597–3600.
4.
PereiraRKotsonisMOliveiraGD, et al.
Analysis of local frequency response of flow to actuation: application to the dielectric barrier discharge plasma actuator. J Appl Phys2015;
118: 569–582.
5.
PesciniEFranciosoLGiorgiMGD, et al.
Investigation of a micro dielectric barrier discharge plasma actuator for regional aircraft active flow control. IEEE Trans Plasma Sci2015;
43: 3668–3680.
6.
ThomasFOCorkeTCIqbalM, et al.
Optimization of dielectric barrier discharge plasma actuators for active aerodynamic flow control. AIAA J2012;
47: 2169–2178.
7.
LiuXZhuZLiHet al.
Liquid spray dielectric barrier discharge induced plasma-chemical vapor generation for the determination of lead by ICP-MS. Anal Chem2017;
89: 16-25.
8.
KimBHWilliamsDREmoS, et al.
Modeling pulsed-blowing systems for flow control. AIAA J2015;
43: 314–325.
9.
WesGWJStemerdingSZuilichemDJV.Control of flow of cohesive powders by means of simultaneous aeration, and vibration. Powder Technol1990;
61: 39–49.
10.
AnghelSDSimonAFrentiuT.Spectroscopic investigations on a low power atmospheric pressure capacitively coupled helium plasma. Plasma Sources Sci Technol2008;
17: 045016.
11.
PaeseEGeierMHomrichRP, et al.
Simplified mathematical modeling for an electromagnetic forming system with flat spiral coil as actuator. J Braz Soc Mech Sci Eng2011;
33: 324–331.
12.
GargP.Study of photoluminescence from amorphous and crystalline silicon nanoparticles synthesized using a non-thermal plasma. Dissertations & Theses, Gradworks, Germany, 2015.
MohammedMAGhaniMKAArunkumarNet al. Genetic case-based reasoning for improved mobile phone faults diagnosis. Comput Electr Eng2018; 71: 212–222.
15.
MutlagAAGhaniMKAArunkumarN, et al.
Enabling technologies for fog computing in healthcare IoT systems. Future Generation Comput Syst2018; 90: 62–78. https://doi.org/10.1016/j.future.2018.07.049.
MohammedMAGhaniMKAArunkumarNet al.
Decision support system for nasopharyngeal carcinoma discrimination from endoscopic images using artificial neural network. J Supercomputing. Epub ahead of print 06 September 2018. https://doi.org/10.1007/s11227-018-2587-z
18.
MohammedMAGhaniMKAArunkumarNet al.
A real time computer aided object detection of nasopharyngeal carcinoma using genetic algorithm and artificial neural network based on Haar feature fear. Future Generation Comput Syst2018; 89: 539–547. https://doi.org/10.1016/j.future.2018.07.022
19.
AreenA-BMohammadA-AHalaAet al.
Computer-based cobb angle measurement using deflection points in adolescence idiopathic scoliosis from radiographic images. Neural Comput Appl. 2019; 31: 1547–1561
20.
KhannaAJainSAggarwalT, et al.
Optimized cuttlefish algorithm for diagnosis of Parkinson’s disease. Cogn Syst Res2018;
52: 36–48.
21.
HusseinAFArunKumarNRamirez-GonzalezG, et al.
A medical records managing and securing blockchain based system supported by a genetic algorithm and discrete wavelet transform. Cogn Syst Res2018;
52: 1–11.
22.
WeiJMengFArunkumarN.A personalized authoritative user-based recommendation for social tagging.Future Generation Comput Syst2018; 86: 355–361.
23.
AshokkumarPArunkumarNDonS.Intelligent optimal route recommendation among heterogeneous objects with keywords. Comput Electr Eng2018;
68: 526–535.
24.
MohamedEGustavoRGOsamaM, et al. Secure medical data transmission model for IoT-based healthcare systems, IEEE Access2018; 6: 20596–20608. https://doi.org/10.1109/ACCESS.2018.2817615
25.
VardhanaMArunkumarNAbdulhayE, et al.
Convolutional neural network for bio-medical image segmentation with hardware acceleration. Cogn Syst Res2018;
50: 10–14.