AHP–neutrosophic decision model for selection of relay node in wireless body area network

Bilandi, Naveen; Verma, Harsh Kumar; Dhir, Renu

doi:10.1049/trit.2020.0059

Cited by 27 publications

(7 citation statements)

References 33 publications

(25 reference statements)

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“…Also, by employing pair-wise comparison, the significance of weight was determined for dealing with fuzzy neutrosophic sets, therefore contributing to higher sensitivity with accuracy. Yet another data analysis method employing an analytic hierarchy process was designed in [12] with the objective of reducing energy consumption while selecting relay nodes for data transmission. However, both the methods lacked the time involved along with the focus on accuracy.…”

Section: Related Workmentioning

confidence: 99%

Blinder Oaxaca and Wilk Neutrosophic Fuzzy Set-based IoT Sensor Communication for Remote Healthcare Analysis

Khalaf

Natarajan

Mahadev³

et al. 2024

IEEE Access

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In the remote healthcare industry data analytics denotes the computerization of collection, processing, and exploring complicated data to acquire finer perceptions and validate healthcare practitioners to produce familiar decisions. Healthcare basics in the modern age are vital challenges specifically in developing countries owing to the shortfall of difficult hospitals and medical professionals. As fuzzy systems have reformed several areas of work, health has also made the most of it. In this paper, the purpose of the study is to introduce a novel and intelligent remote healthcare system based on modern technologies like the Internet of things (IoT) and Neutrosophic fuzzy systems to ensure precise data analysis with lesser time and energy consumption. In this study, a novel method called, Blinder Oaxaca-based Shapiro Wilk Neutrosophic Fuzzy (BO-SWNF) data analytics for remote healthcare is designed. Data collection is performed with the WESAD dataset. Duplicated data are eliminated by Blinder Oaxaca Linear Regressionbased Preprocessing model. With the application of the Blinder Oaxaca function, energy efficiency is enhanced. Finally, the Shapiro Wilk Neutrosophic Fuzzy algorithm is applied for ensuring robust data analysis. The experimental results of the proposed BO-SWNF envisage the data for finer comprehension of attribute distribution. The result is conducted by using PYHTON application to analyze stress detection with the WESAD dataset. The proposed BO-SWNF method achieved an overall accurate data analysis of 12% with minimum time ensuring 56%improvement and minimizing energy consumption by 54%.

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Section: Related Workmentioning

confidence: 99%

Blinder Oaxaca and Wilk Neutrosophic Fuzzy Set-based IoT Sensor Communication for Remote Healthcare Analysis

Khalaf

Natarajan

Mahadev³

et al. 2024

IEEE Access

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“…In this step, the preprocessed image is given as an input and then a wireframe model of the image is constructed using the CLAP-based model for 3D images [39][40][41]. e proposed approach works on the abrupt change in the gray level value of the neighborhood pixels.…”

Section: Wireframe Of the Imagementioning

confidence: 99%

Efficient 3D AlexNet Architecture for Object Recognition Using Syntactic Patterns from Medical Images

Rani

Ghai

Kumar

et al. 2022

Computational Intelligence and Neuroscience

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In computer vision and medical image processing, object recognition is the primary concern today. Humans require only a few milliseconds for object recognition and visual stimulation. This led to the development of a computer-specific pattern recognition method in this study for identifying objects in medical images such as brain tumors. Initially, an adaptive median filter is used to remove the noise from MRI images. Thereafter, the contrast image enhancement technique is used to improve the quality of the image. To evaluate the wireframe model, the cellular logic array processing (CLAP)-based algorithm is then applied to images. The basic patterns of three-dimensional (3D) images are then identified from the input image by scanning the whole image. The frequency of these patterns is also used for object classification. A deep neural network is then utilized for the classification of brain tumor. In the proposed model, the syntactic pattern recognition technique is used to find the feature vector and 3D AlexNet is used for brain tumor classification. To evaluate the performance of the proposed work, three benchmark brain tumor datasets are used, i.e., Figshare, Brain MRI Kaggle, and Medical MRI datasets and BraTS 2019 dataset. The comparative analyses reveal that the proposed brain tumor classification model achieves significantly better performance than the existing models.

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“…SSC mitigates uncertainties and threats, such as environmental damage and labor constraints, enhancing market continuity, limiting manufacturing and delivery delays and prices [15]. But many developing economies do not currently have the skills to adapt and incorporate sustainable activities successfully; this is mainly because sustainability science remains underdefined, implemented, and implemented.The above remarks explicitly illustrate the need to address sustainability in the supply chain (SC)s to ensure equity and create opportunities for resilience in developing countries [16]. Growing instability and SSC-related uncertainties have focused on the economy in numerous developed countries, given its competitive markets.…”

Section: Sustainable Supply Chain (Ssc) and Epidemicmentioning

confidence: 99%

Sustainable Policies for Supply Chain During the Digital Economic Crisis Due to Epidemics

Sharma

et al. 2021

Preprint

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One of the most exciting issues in the digital economy has been sustainability supply chain management. There are many articles on this area and several different viewpoints. This work focuses on assessing the sustainability of supply chain management based on two main measurements. Firstly, the value of ecological, environmental, and social measurement indicators and the extent of the challenge in collecting information. The objective of this article is to improve the precision of the assessment. A Sustainable Policies for Supply Chain Management (SP-SCM)is proposed in this article. The suggested framework is a synthesis of quality function deployment (QFD) with plithogenic set grouping processes.A summation function is applied: the perception of the decision-maker of criteria required to assess the viability of the supply chain, the measurement criteria dependent on the specifications, and the difficulties in collecting details. This research submitted a real-world test case on the sugar industry to test the proposed framework. In evaluating the sustainability of the supply chain policy, the findings revealed the performance efficiency of the proposed system.

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AHP–neutrosophic decision model for selection of relay node in wireless body area network

Cited by 27 publications

References 33 publications

Blinder Oaxaca and Wilk Neutrosophic Fuzzy Set-based IoT Sensor Communication for Remote Healthcare Analysis

Blinder Oaxaca and Wilk Neutrosophic Fuzzy Set-based IoT Sensor Communication for Remote Healthcare Analysis

Efficient 3D AlexNet Architecture for Object Recognition Using Syntactic Patterns from Medical Images

Sustainable Policies for Supply Chain During the Digital Economic Crisis Due to Epidemics

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