Neutrosophic Sets and Systems, vol. 50/2022


Book Description

“Neutrosophic Sets and Systems” has been created for publications on advanced studies in neutrosophy, neutrosophic set, neutrosophic logic, neutrosophic probability, neutrosophic statistics that started in 1995 and their applications in any field, such as the neutrosophic structures developed in algebra, geometry, topology, etc. Neutrosophy is a new branch of philosophy that studies the origin, nature, and scope of neutralities, as well as their interactions with different ideational spectra. This theory considers every notion or idea together with its opposite or negation and with their spectrum of neutralities in between them (i.e. notions or ideas supporting neither nor ). The and ideas together are referred to as . Neutrosophy is a generalization of Hegel's dialectics (the last one is based on and only). According to this theory every idea tends to be neutralized and balanced by and ideas - as a state of equilibrium. In a classical way , , are disjoint two by two. But, since in many cases the borders between notions are vague, imprecise, Sorites, it is possible that , , (and of course) have common parts two by two, or even all three of them as well. Neutrosophic Set and Neutrosophic Logic are generalizations of the fuzzy set and respectively fuzzy logic (especially of intuitionistic fuzzy set and respectively intuitionistic fuzzy logic).




Neutrosophic Sets and Systems, Vol. 42, 2021


Book Description

“Neutrosophic Sets and Systems” has been created for publications on advanced studies in neutrosophy, neutrosophic set, neutrosophic logic, neutrosophic probability, neutrosophic statistics that started in 1995 and their applications in any field, such as the neutrosophic structures developed in algebra, geometry, topology, etc. In this issue: A hybrid Model Using MCDM Methods and Bipolar Neutrosophic Sets for Select Optimal Wind Turbine: Case Study in Egypt, Graphical Representation of Type-2 Neutrosophic sets, PESTEL Analysis to Identify Key Barriers to Smart Cities Development in India.




Brain Tumor Detection Based on Convolutional Neural Network with Neutrosophic Expert Maximum Fuzzy Sure Entropy


Book Description

Brain tumor classification is a challenging task in the field of medical image processing. The present study proposes a hybrid method using Neutrosophy and Convolutional Neural Network (NS-CNN). It aims to classify tumor region areas that are segmented from brain images as benign and malignant. In the first stage, MRI images were segmented using the neutrosophic set – expert maximum fuzzy-sure entropy (NS-EMFSE) approach.




Progress in Advanced Computing and Intelligent Engineering


Book Description

This book features high-quality research papers presented at the 4th International Conference on Advanced Computing and Intelligent Engineering (ICACIE 2019), Department of Computer Science, Rama Devi Women’s University, Bhubaneswar, Odisha, India. It includes sections describing technical advances and contemporary research in the fields of advanced computing and intelligent engineering, which are based on the presented articles. Intended for postgraduate students and researchers working in the discipline of computer science and engineering, the book also appeals to researchers in the domain of electronics as it covers hardware technologies and future communication technologies.




Biomedical Signal Processing


Book Description

This book reports on the latest advances in the study of biomedical signal processing, and discusses in detail a number of open problems concerning clinical, biomedical and neural signals. It methodically collects and presents in a unified form the research findings previously scattered throughout various scientific journals and conference proceedings. In addition, the chapters are self-contained and can be read independently. Accordingly, the book will be of interest to university researchers, R&D engineers and graduate students who wish to learn the core principles of biomedical signal analysis, algorithms, and applications, while also offering a valuable reference work for biomedical engineers and clinicians who wish to learn more about the theory and recent applications of neural engineering and biomedical signal processing.




A Survey Of Ultrasonography Breast Cancer Image Segmentation Techniques


Book Description

The most common cause of death among women globally is breast cancer. One of the key strategies to reduce mortality associated with breast cancer is to develop effective early detection techniques. The segmentation of breast ultrasound (BUS) image in Computer-Aided Diagnosis (CAD) systems is critical and challenging. Image segmentation aims to represent the image in a simplified and more meaningful way while retaining crucial features for easier analysis.




Algorithm Selection for Edge Detection in Satellite Images by Neutrosophic WASPAS Method


Book Description

Nowadays, integrated land management is generally governed by the principles of sustainability. Land use management usually is grounded in satellite image information. The detection and monitoring of areas of interest in satellite images is a difficult task. We propose a new methodology for the adaptive selection of edge detection algorithms using visual features of satellite images and the multi-criteria decision-making (MCDM) method. It is not trivial to select the most appropriate method for the chosen satellite images as there is no proper algorithm for all cases as it depends on many factors, like acquisition and content of the raster images, visual features of realworld images, and humans’ visual perception. The edge detection algorithms were ranked according to their suitability for the appropriate satellite images using the neutrosophic weighted aggregated sum product assessment (WASPAS) method. The results obtained using the created methodology were verified with results acquired in an alternative way—using the edge detection algorithms for specific images. This methodology facilitates the selection of a proper edge detector for the chosen image content.




SALT AND PEPPER NOISE REDUCTION AND EDGE DETECTION ALGORITHM BASED ON NEUTROSOPHIC LOGIC


Book Description

Noise reduction of images is a challenging task in image processing. Salt and pepper noise is one kind of noise that a ects a gray-scale image signi cantly. Generally, the median lter is used to reduce salt and pepper noise; it gives optimum results while compared to other image lters. Median lter works only up to a certain level of noise intensity.




A hybrid Fuzzy C-Means and Neutrosophic for jaw lesions segmentation


Book Description

It is really important to diagnose jaw tumor in its early stages to improve its prognosis. A differential diagnosis could be performed using X-ray images; therefore, accurate and fully automatic jaw lesions image segmentation is a challenging and essential task. The aim of this work was to develop a novel, fully automatic and effective method for jaw lesions in panoramic X-ray image segmentation.