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

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

An Analytical Approach for Decision-Making

In this complex world, coping with daily problems is quite tedious. The more advancement in technology means more difficulties in decision-making process. Hence some analytical tools are needed to deal with improvement in decisions being made. A classic AHP model enables us to make efficient decision by reducing the complex issues. It takes multiple parameters into consideration. One of the area where decision-making is quite a tough job is Politics. Selection of the electoral party in any elections, be it Lok Sabha elections or Rajya Sabha elections, has been a matter of discussion for the voters as well as the media. The decisions are reflected when uncertainties are added in the opinions of the domain experts due to multiple parameters.  In this paper we have proposed a model for rectifying the uncertainties using multi criteria decision analysis and analytic hierarchy process (AHP)

Prediction of lung disease using machine and deep learning techniques: A review

Nowadays lung diseases are becoming a significant problem. In spite of this, Corona virus disease 2019 (COVID-19) has become a pandemic all over the world from last two years which effected lungs of few patients also. Many people are suffering from lungs diseases like Asthma, Allergies, lung cancer etc. The patients whose lung gets affected due to COVID-19 may face some lungs diseases in near future, so it very significant to early diagnosis of lungs diseases to save human life. Machine learning (ML) with feature selection techniques play significant role in the medical field by making diseases diagnoses accurate and early. The objective of this paper is to presents a review of recent ML algorithms and feature selection techniques used to predict lung diseases. As we cover the study between 2020 – 2021, some supervised (SVM, Logistic Regression, Random Forest, Logistic model tree, Bayesian Networks) machine learning techniques on 18,253 data instances and unsupervised (KNN,CNN) machine learning techniques on 8,761 data instances were used to detect accuracy, precision, recall, sensitivity and F1-score in order to predict lung diseases.&nbsp