Cognitive Computing for Multimodal Sentiment Sensing and Emotion Recognition Fusion Based on Machine Learning Techniques Implemented by Computer Interface System

Authors

  • Arun Kumar Marandi Associate Professor, Department of Computer Science, ARKA JAIN University, Jamshedpur, Jharkhand, India.
  • Gordhan Jethava Assistant Professor, Department of Computer Science and Engineering, Parul Institute of Technology, Parul University, Vadodara, Gujarat, India.
  • A Rajesh Professor, Department of Computer Science and Engineering, Jain (Deemed-to-be University), Bangalore, India.
  • Sachin Gupta Chancellor, Department of Management, Sanskriti University, Mathura, Uttar Pradesh, India.
  • Shrddha Sagar Professor, School of Computing Science and Engineering, Galgotias University, Greater Noida, Uttar Pradesh, India.
  • Sonia Sharma Assistant Professor, Department of Computer Science Engineering, Chandigarh Engineering College, Jhanjeri, India.

DOI:

https://doi.org/10.17762/ijcnis.v14i2.5462

Keywords:

BCI, multimodal emotion recognition, sentimental sensing, FFT-CNN, TL-SVM

Abstract

A multiple slot fractal antenna design has been determined communication efficiency and its multi-function activities.  High-speed small communication devices have been required for future smart chip applications, so that researchers have been employed new and creative antenna design. Antennas are key part in communication systems, those are used to improve communication parameters like gain, efficiency, and bandwidth. Consistently, modern antennas design with high bandwidth and gain balancing is very difficult, therefore an adaptive antenna array chip design is required. In this research work a coaxial fed antenna with fractal geometry design has been implemented for Wi-Fi and Radio altimeter application. The fractal geometry has been taken with multiple numbers of slots in the radiating structure for uncertain applications. The coaxial feeding location has been selected based on the good impedance matching condition (50 Ohms). The overall dimension mentioned for antenna are approximately 50X50X1.6 mm on FR4 substrate and performance characteristic analysis is performed with change in substrate material presented in this work. Dual-band resonant frequency is being emitted by the antenna with resonance at 3.1 and 4.3 GHz for FR4 substrate material and change in the resonant bands is obtained with change in substrate. The proposed Antenna is prototyped on Anritsu VNA tool and presented the comparative analysis like VSWR 12%, reflection coefficient 9.4%,3D-Gain 6.2% and surface current 9.3% had been improved.

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Published

2022-08-31

How to Cite

Marandi, A. K. ., Jethava, G. ., Rajesh, A. ., Gupta, S. ., Sagar, S. ., & Sharma, S. . (2022). Cognitive Computing for Multimodal Sentiment Sensing and Emotion Recognition Fusion Based on Machine Learning Techniques Implemented by Computer Interface System. International Journal of Communication Networks and Information Security (IJCNIS), 14(2), 15–32. https://doi.org/10.17762/ijcnis.v14i2.5462

Issue

Section

Research Articles