Proceedings of the National Academy of Sciences, India Section A: Physical Sciences最新文献

In this paper we study how the muscles in the human body move, electromyography (EMG Signal) is employed as a diagnostic technique for identifying various muscular activity. Noise from the SEMG signal is effectively minimized with a suitable wavelet selection. The root mean square values have been evaluated to determine which wavelet is the most efficient for signal denoising. Further, since a learning method of a neural structure with connections based on rules is necessary to be able to estimate the relationship, this paper also aims to analyse an approach that uses signals obtained by surface electrodes to characterize hand movements of the human arm for pattern recognition (i.e. ANFIS method is employed). The characteristics of seven hand gestures are categorized using the ANFIS-based learning, which is then assessed in order to predict the link between input and output.

Tropospheric delay play a critical role in satellite communication. Due to lack of measuring instruments, tropospheric wet delays are often estimated using empirical models. In this study, we investigated the performance of four (Saastamoinen, Callahan, Mendes, and Berman) models in four tropical locations within Nigeria. By comparing with GPS data, our results showed that the models generate errors on the same magnitude as the measurement data. The Saastamoinen and Mendes models were found to have the best performance amongst the four models at the monthly and annual scale. At the annual scale, RMSE values of 0.12–0.18 and 0.11–0.16 were obtained for Saastamoinen and Mendes models, respectively, compared to 0.19–0.29 for both Callahan and Berman models. In order to improve the performance of the wet delay models, calibration of their parameters was carried out. It was observed that the new parameters improved the performance of the models significantly. The results in this study will help reduce the uncertainties associated with estimating wet delays in tropical regions.

An analytical model has been developed to explore the structure of one-dimensional viscous shock waves in the presence of an axial magnetic field assuming the gaseous medium to follow the van der Waals equation of state. The exact solutions for pressure, temperature, fluid velocity and entropy are obtained taking into account the dissipative processes in the shock transition region. The detailed analysis of the structure of shock-front has been presented showing the dependence of the thickness of shock-front on the adiabatic index, the strength of magnetic field, coefficient of viscosity, shock strength and the non-idealness parameter of the gases. The findings are presented in graphical as well as in tabular forms which reveal that the shock-front thickness increases with increasing the strength of magnetic field and the viscous coefficient of gases, whereas it decreases with the increasing value of non-idealness parameter of the gases. Finally, a comparison has been done between the current findings following the van der Waals equation of state and the previously available data following the Anisomov and Spiner equation of state.

Moringa plants are now largely employed as a nutritional supplement, to enhance soil quality, and in water filtering systems. Moringa is a natural antioxidant and has antimicrobial property. They are also a rich supply of oil, which is a popular and significant revenue source. As a consequence, these plants have a diverse set of characteristics and uses on their own, and their activity is enhanced when coupled with other materials. In this article, the phytochemical analysis, antioxidant, and antimicrobial activity of moringa powder blended with the medicinally significant spices turmeric (Curcuma longa), pepper (Piper nigrum), dry ginger (Zingiber Officinale), and dry orange peel powder (Citrus Aurantium Dulcis). The moringa blends formed by mixing with above-mentioned spices were subjected to antioxidant activity by DPPH assay and antimicrobial activity by well diffusion method. Total phenolic contents and the flavonoid contents were determined using phytochemical analysis. Using FTIR spectroscopy, significant composition in all the four blends was determined. When Moringa powder is blended with other four remarkable spices, its phytochemical characteristics and biological characteristics like antioxidant antimicrobial activity are enhanced to high side.

Banking fraud is a problem that is becoming more and more serious, along with considerable monetary losses, damage to the bank's brand, loss of client and customer confidence. Fraud identification and prevention are major challenges for many financial organizations, retail firms, and e-commerce companies. Fraud detection is used to both identify and stop fraudsters from obtaining goods or bugs illegally. In the same vein, this research will conduct a feasibility study to determine the best fraud detection strategy. We provide a list of the tried-and-true methods for spotting fraud. To avoid fraud detection, many techniques like Deep Neural Network, Support Vector Machine, Multilayer Perceptron, K-Nearest Neighbors, Random Forest, XG Boost, LGBM, and Decision Tree were used. The dataset was built from 20,000 entries on Kaggle, each having 114 attributes. Before using machine learning and neural network approaches, the dataset is balanced using the Synthetic Minority Over-Sampling Method. Following the analysis of the dataset using a number of methods, it was determined that Random Forest, Decision Tree, XG Boost, and LGBM all had 100% accuracy. This demonstrates that the model outperformed other models by balancing the dataset.

In the present paper, we have analyzed the surface roughness influence on the dynamic performance of Rayleigh step bearing by taking the squeezing action. The non-Newtonian lubricant in the film region considered is a couplestress fluid. A stochastic random variable with a non-zero mean, variance and skewness characterizes the roughness. The improved averaged Reynolds type equation is obtained using constitutive Stoke’s equations for couple stress fluid and stochastic surface roughness theory. For volume flow rate, steady-state characteristics and dynamic characteristics are derived in closed-form expression and are solved numerically by Simpson rule using Mathematica software. The non-Newtonian couplestress fluid enhances (diminishes) the steady load carrying capacity, the dynamic stiffness, and the dynamic damping coefficients, also a decrease (increase) in the volume flow rate is required for negatively (positively) skewed surface roughness in accordance with the Newtonian case. The relative percentage increase in bearing characteristics is studied. The results are considered with that of the smooth case.

In the present paper, we have studied the local convergence of a three-step Newton-type method for solving nonlinear equations in Banach spaces under weak L-average. More precisely, we have derived the two existence theorems when the first-order Fréchet derivative of nonlinear operator satisfies the radius and center Lipschitz condition with a weak L-average; particularly, it is assumed that L is positive integrable function but not necessarily non-decreasing, which was assumed in the earlier discussion.

In the present paper, we set forth with the new notion of rough (mathcal {I})-deferred statistical convergence of order (alpha (0<alpha le 1)) in gradual normed linear spaces (GNLS). We prove some fundamental features and implication relations of this convergence method. Also, we put forward the notion of gradual rough (mathcal {I})-deferred statistical limit set of order (alpha ) and prove some of its properties such as closedness and convexity. We prove that the gradual rough (mathcal {I})-deferred statistical limit set also plays a crucial role in the gradually (mathcal {I})-deferred statistical boundedness of order (alpha ) of a sequence in a GNLS. We end up proving a necessary and sufficient condition for the rough (mathcal {I})-deferred statistical convergence of order (alpha (0<alpha le 1)) of a sequence in GNLS. Significance of the work in a broad context: Summability theory and convergence of sequences have many applications in mathematical analysis. The study of the convergence of sequences in GNLS has made little progress and is still in its early stages. In this paper, we introduce rough (mathcal {I}-)deferred statistical convergence of sequences in GNLS which provides a new direction to the researchers.

The de novo programming technique is used to design an optimal system when the objectives and constraints are linear. It was initially introduced with crisp parameters. Later, de novo programming with fuzzy parameters has been studied to make it more flexible. But the fuzzy set has its limitations too. On the other hand, type-2 fuzzy sets are capable of embracing even those uncertainties that have not been covered or addressed by fuzzy sets. So the general de novo programming problem with interval type-2 fuzzy parameters has been introduced and studied here to make the system more reliable by removing the shortcomings of the human thinking process. This makes de novo programming better for modelling real-life problems than a fuzzy (type-1 fuzzy) logic-based system. The solution procedures for the proposed problem have been illustrated by a solid transportation problem.