A Suggested Diagnostic System of Corona Virus based on the Neutrosophic Systems and Deep Learning

A.A.; Mohamed; Mohamed; M.

doi:https://doi.org/10.54216/IJNS.090105

Fusion: Practice and Applications | 2020

Improving Cloud-based ECG Monitoring, Detection and Classification using GAN

Internet of Things (IoT) based healthcare applications have grown exponentially over the past decade. With the increasing number of fatalities due to cardiovascular diseases (CVD), it is the need of the hour to detect any signs of cardiac abnormalities as early as possible. This calls for automation in the detection and classification of said cardiac abnormalities by physicians. The problem here is that there is not enough data to train Deep Learning models to classify ECG signals accurately because of the sensitive nature of data and the rarity of certain cases involved in CVDs. In this paper, we propose a framework that involves Generative Adversarial Networks (GAN) to create synthetic training data for the classes with fewer data points to improve the performance of Deep Learning models trained with the dataset. With data being input from sensors via the cloud and this model to classify the ECG signals, we expect the framework to be functional, accurate, and efficient.

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S Hariharan mail -

Monika Gupta mail

link https://doi.org/10.54216/FPA.020201

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Vol. Volume 2 / Iss. Issue 2

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Fusion: Practice and Applications | 2020

ARZARA: Augmented reality app to try watch on your wrist

Whenever we visit a showroom to buy a watch, we are unable to try all color variants of watches due to unavailability, and also, if a watch is tried by too many customers, it loses its shine and finishing. We tried to overcome this problem with our Augmented reality app called “Arzara ."This Augmented reality app lets customers see how a particular watch model looks on their hand without physically trying the Watch. It will not only prevent the degradation of the polish of watches due to repeated wear by different customers at offline stores but also this new Augmented Reality watch app will take off online watch shopping. It will make it easier for customers to make decisions and purchase watches.

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Sarthak Gupta mail -

Monil Pahwa mail -

Prayant Gupta mail -

Surinder Kaur mail

link https://doi.org/10.54216/FPA.020202

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Vol. Volume 2 / Iss. Issue 2

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Fusion: Practice and Applications | 2020

Facial Expression Recognition with Gender Identification

Human facial emotion recognition has attracted interest in the field of Artificial Intelligence. The emotions on a human face depict what's going on inside the mind. Facial expression recognition is the part of Facial recognition which is gaining more importance, and the need for it has increased tremendously. Though there are methods to identify expressions using machine learning and Artificial Intelligence techniques, this work attempts to use convolution neural networks to recognize expressions and classify the expressions into 6 emotional categories. Various datasets are investigated and explored for training expression recognition models are explained in this paper, and the models which are used in this paper are VGG 19 and RESNET 18. We included facial emotional recognition with gender identification also. In this project, we have used the fer2013 and ck+ datasets and ultimately achieved 73% and 94% around accuracies, respectively.

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Shubham Gupta mail -

Aarushi Dhawan mail -

Arpit Gupta mail -

A. Kumar Dubey mail

link https://doi.org/10.54216/FPA.020203

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Vol. Volume 2 / Iss. Issue 2

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Fusion: Practice and Applications | 2020

Egocentric Performance Capture: A Review

Performance capture of human beings has been used to animate 3D characters for movies and games for several decades now. Traditional performance capture methods require a costly dedicated setup which usually consists of more than one sensor placed at a distance from the subject, hence requiring a large amount of budget and space to accommodate. This lowers its feasibility and portability by a huge amount. Egocentric (first-person/wearable) cameras, however, are attached to the body and hence are mobile. With the rise of acceptance of wearable technology by the general public, wearable cameras have gotten cheaper too. We can make use of their excessive portability in the performance capture domain. However, working with egocentric images is a mammoth task as the views are severely distorted due to the first-person perspective, and the body parts farther from the camera are highly prone to be occluded. In this paper, we review the existing state-of-the-art methods of performance capture using egocentric-based views.

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Shivam Grover mail -

Kshitij Sidana mail -

Vanita Jain mail

link https://doi.org/10.54216/FPA.020204

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Vol. Volume 2 / Iss. Issue 2

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American Journal of Business and Operations Research | 2020

Pythagorean Neutrosophic [PN] P-Spaces (with T and F are dependent neutrosophic components

In this paper, we study the Pythagorean Neutrosophic Sets with T and F are dependent neutrosophic components [PN] topological spaces. We also study the Pythagorean Neutrosophic [PN] P-spaces (with T and F are dependent neutrosophic components) , weak P-spaces and almost P-spaces.Also we study the inter-relations between the spaces are introduced.

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International Journal of Neutrosophic Science | 2020

NEUTROSOPHIC RATIO TYPE ESTIMATORS FOR ESTIMATING THE POPULATION MEAN

In previous studies, many researchers have estimated the mean of the finite population in the presence of auxiliary information under classical statistics when data is stable and determined but the problem arises when the data is uncertain, data may be imprecise, ambiguous, incomplete and vague. In these situations, Neutrosophic Statistics can be applied. In this article, we developed the neutrosophic ratio type estimators for estimating the mean of the finite population using an auxiliary variable under Neutrosophic data. Unbiasedness at order one was proved and the efficiencies of the proposed neutrosophic ratio type estimators using mean square errors are also discussed by neutrosophic interval data of temperature. These proposed ratio type estimators are very helpful for obtaining estimates of the mean as in SRSWOR when our sample has some indeterminacy.

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ZaighamTahir mail -

HinaKhan mail

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International Journal of Neutrosophic Science | 2020

On Refined Neutrosophic Vector Spaces II

The concept of refined neutrosophic vector spaces was introduced by Ibrahim et al. in [20] and the present paper is the continuation of the work. In the present paper, further studies on neutrosophic vector spaces are presented. Specifically, linear dependence, independence, bases and dimensions of refined neutrosophic vector spaces are studied with several results and examples presented. Also, refined neutrosophic homomorphisms of refined neutrosophic vector spaces are studied and existence of linear maps between weak refined Neutrosophic vector spaces and weak neutrosophic vector spaces are established.

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M.A. Ibrahim mail -

A.A.A. Agboola mail -

B.S. Badmus mail -

S.A. Akinleye mail

link https://doi.org/10.54216/IJNS.090102

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Vol. Volume 9 / Iss. Issue 1

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International Journal of Neutrosophic Science | 2020

Aggregation Operators of Bipolar Neutrosophic Soft Sets and It’s Applications In Auto Car Selection

In this paper, it is intended to study the concept of bipolar eutrosophic soft set ( . It is aimed to defined bipolar eutrosophic soft set. Definitions and perations have been presented the BNSS. Then we present an aggregation BNSS operator and decision aking algorithm depend on the BNSS. Number-based examples discussed to show (ability to be done) and efficiency of the advanced method.

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Muhammad Naveed Jafar mail -

Mushal Zia mail -

Ayisha Saeed mail -

Maryam Yaqoob mail -

Samreen Habib mail

link https://doi.org/10.54216/IJNS.090103

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Vol. Volume 9 / Iss. Issue 1

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International Journal of Neutrosophic Science | 2020

Neutrosophic Environment for Traffic Control Management

Neutrosophic along with its environment development over the past decades. Neutrosophic environment is apply to various applications in logic,statstics,albebra, neural networks and several other fields. Neutrosophic sets has been presented to handle the indeterminacy in real-world decision-making problem. Real world problems have some kind of uncertainty in nature and one of the influential problem in environment. Neutrosophic environment results are apply  to  a new dimension in traffic control. Neutrosophic is the vital role on traffic flow control . It is deal with  membership , non membership  and also indeterminacy of the data as well.  The advantage of the neutrosophic environment is to  find the optimized result of the system choosing the best alternative.In this paper, traffic flow control is analyzed under neutrosophic environment using  MATLAB. 

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D. Nagarajan mail -

Said Broumi mail -

J. Kavikumar mail

link https://doi.org/10.54216/IJNS.090104

Volume & Issue

Vol. Volume 9 / Iss. Issue 1

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International Journal of Neutrosophic Science | 2020

A Suggested Diagnostic System of Corona Virus based on the Neutrosophic Systems and Deep Learning

The idea for this paper is based on the use of a computer-connected microscope associated with Deep Learning, using Convolutional Neural Network (CNN). CNN is a mathematical type of Deep Learning used to recognize and diagnose images.  After that, we photograph blood samples, as well as samples, were taken from the mouth and nose, as well as it is possible to photograph the throat from the inside of a large number of injured and uninfected people as well as suspected of infection and provide a large number of references for this program for each type of those different samples. It is possible to perform this process in few minutes, save time and money, make analyzes for the largest possible number of people, and provide results in an accurate and documented manner, which is through the Neutrosophic time series. The basis and analysis of dealing with all data, whether specific or not, that can be taken by time series values, then we present the linear model for the neutrosophic time series, and we test the significance of its coefficient based on patients distribution. Finally, from the above, we can provide a patient neutrosophic time series according to the linear model through which we can accurately predict the program will give degrees of verification and degrees of the uncertainty of the data.

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A.A. Salama mail -

Mohamed Fazaa mail -

Mohamed Yahya mail -

M. Kazim mail

link https://doi.org/10.54216/IJNS.090105

Volume & Issue

Vol. Volume 9 / Iss. Issue 1

Details open_in_new