36 research outputs found
An Analytical study to Identify Serum Arginase 1 as an Early Biomarker for Vascular Complications in Type 2 Diabetes Mellitus
No full text
Neutrosophic Labeling Graph
No full textIn this paper, some new connectivity concepts in neutrosophic labeling graphs are portrayed. Definition of neutrosophic strong arc, neutrosophic partial cut node, Neutrosophic Bridge and block are introduced with examples. Also, neutrosophic labeling tree and partial intuitionistic fuzzy labeling tree is explored with interesting properties
Integrating Electroencephalography with Motophysic training: Assessing the shift in fitness and cognitive functions in elite youth soccer players
No full textMotor and physical fitness play a crucial role to optimize the player performance in the soccer game. Implementing a customized workout schedule targeting Motophysic Fitness (MPF) helps to elevate their on-field performance. The present study was aimed to assess the impact of a 12-week MPF Training program targeted to have improvements in physical fitness for elite soccer players. MPF training program was implemented during the off-season for youth soccer players with average age (20 ± 1 years), height (1.75 ± 0.5 m) weight (64.3 ± 5.7 kg). Soccer-related fitness traits were assessed to evaluate performance levels, while Electroencephalography (EEG) was utilized for cognitive assessment. Statistical analysis was performed to evaluate the outcome of the fitness traits. Significant improvements were observed across diverse fitness traits, with mean values increasing by a minimum of 2 % and a maximum of 5 %. Speed emerged as a predominant contributor, showing a robust correlation (Adjusted R2 = 0.84), while agility, strength, power, endurance, balance, coordination, and reaction time also displayed substantial improvements. Despite observable gains in flexibility, its impact on overall fitness appeared comparatively modest (Adjusted R2 = 0.23). Z-test confirmed the statistical significance of all fitness assessments post-MPF, with p-values less than 0.05 for each test. Features extracted from EEG highlighted the improvement in cognitive ability before and after training
Neutrosophic Fuzzy Threshold Graph
No full textThe aim of this paper is to introduce the extension of intuitionistic fuzzy threshold graph to Neutrosophic field of approach. A new structure called Neutrosophic fuzzy threshold graph (NFTG) have been portrayed and the Neutrosophic fuzzy alternating 4-cycle have been explained using suitable examples. Two parameters namely, Neutrosophic fuzzy threshold dimension and Neutrosophic fuzzy threshold partition number have been illustrated with examples. Theorems based on proposed concepts were proved and one application has been discussed to insist the utility of Neutrosophic fuzzy threshold graph in resource management technique
Modelling an Efficient Hybrid Optimizer for Handling Vehicle Routing Problem
No full text651-662Vehicle Routing Problem (VRP) like total routing distance, number of serve provisioning vehicles, and vehicles'
waiting time are determined as the multi-objective constraints. Investigators pretend to handle these multi-constraint issues
with the time window and fail to attain a prominent solution. Thus, there is a need for a global multi-objective vehicle
routing solution. Here, a novel Particle Positioning Particle Swarm Optimization () approach is designed to predict the
robust route with the elimination of non-linearity measures. The linearity measure includes the movement of the vehicles,
service time, and status of the move towards a particular direction. The lack of exploration and exploitation conditions
during optimization is addressed with the inclusion of Grey Wolf Optimization (GWO). Therefore, the models attain a
global solution with the least error rate. Simulation is done in MATLAB 2016b environment, and the experimental
outcomes are compared with various approaches in large-scale and small-scale instances. The model intends to attain
robustness and stability towards the measure in a linear manner. The model's time consumption and computational
complexity are reduced with the adoption of a global routing-based optimization approach
