Notice Board :

Call for Paper
Vol. 5 Issue 2

Submission Start Date:
Feb 01, 2024

Acceptence Notification Start:
Feb 10, 2024

Submission End:
Feb 25, 2024

Final MenuScript Due:
Feb 28, 2024

Publication Date:
Feb 28, 2024
                         Notice Board: Call for PaperVol. 5 Issue 2      Submission Start Date: Feb 01, 2024      Acceptence Notification Start: Feb 10, 2024      Submission End: Feb 25, 2024      Final MenuScript Due: Feb 28, 2024      Publication Date: Feb 28, 2024




Volume III Issue XII

Author Name
Mahalya Chopra, Gajendra Singh
Year Of Publication
2022
Volume and Issue
Volume 3 Issue 12
Abstract
For higher education, it is crucial for the institution to forecast early student academic performance in order to give students appropriate facilities for improving their academic records and make it simple for the instructor to detect them. Numerous machine learning approaches, including knearest neighbour, support vector machines, Naive Bayes classifiers, logistic regression, etc., have been created to enhance student academic performance. In this paper, we propose a method for predicting student performance using a machine learning neural network. The MATLAB toolbox is used to develop this model, and comparison analysis is carried out utilising a variety of measurement factors, including precision, recall, f-measure, and execution time
PaperID
2022/IJEASM/3/2022/1780

Author Name
Kirti Tiwari, Arihant Jain
Year Of Publication
2022
Volume and Issue
Volume 3 Issue 12
Abstract
By taking into account the effects of Brownian diffusion and thermophoresis, the start of convective instability in a layer of porous material saturated by the Oldroyd-B viscoelastic nanofluid heated from below is explored. On the boundary, it is assumed that the flux of the nanoparticle volume fraction is zero. The Galerkin method is used to numerically solve the resulting eigenvalue problem. When the strain retardation parameter does not surpass a threshold value that in turn depends on other physical parameters, the start of convective instability is only oscillatory if the strain retardation parameter is less than the stress relaxation parameter. When the strain retardation parameter is increased, the oscillatory beginning is delayed; however, when the stress relaxation parameter is increased, the opposite trend is seen. The onset of stationary and oscillatory convection is accelerated by increasing the modified diffusivity ratio, concentration Darcy-Rayleigh numb
PaperID
2022/IJEASM/3/2022/1780a

Author Name
Ambikesh Kumar Soni, Durgesh Vishwakarma
Year Of Publication
2022
Volume and Issue
Volume 3 Issue 12
Abstract
In this report a space vector PWM technique-controlled series connected distribution generation units are controlled with stable power sharing. In cascaded-type micro grid, the synchronization and power balance of distributed generators become two new issues that need to be addressed urgently. To that end, an f-P/Q droop control is proposed in this letter, and its stability is analyzed as well. This proposed droop control is capable to achieve power balance under both resistive-inductive and resistive-capacitive loads autonomously. Compared with the inverse power factor droop control, an obvious advantage consists in extending the scope of application. Finally, the feasibility of the proposed method is verified by simulation results. The method will ensure in accurate power sharing even if the communication is interrupted. If the load changes while the communication is interrupted, the accuracy of power sharing is reduced but the proposed method is better than the conventional droop con
PaperID
2022/IJEASM/3/2022/1781

Author Name
Kamlesh Patil, Arihant Jain
Year Of Publication
2022
Volume and Issue
Volume 3 Issue 12
Abstract
In this study, a two-warehouse inventory model with exponentially increasing trend in demand involving different deterioration rates under permissible delay in payment has been studied. Here, the scheduling period is assumed to be a variable. The objective of this study is to obtain the condition when to rent a warehouse and the retailer’s optimal replenishment policy that minimizes the total relevant cost. An effective algorithm is designed to obtain the optimal solution of the proposed model. Numerical examples are provided to illustrate the application of the model. Based on the numerical examples, we have concluded that the single warehouse model is less expensive to operate than that of two warehouse model. Sensitivity analysis has been provided and managerial implications are discussed
PaperID
2022/IJEASM/3/2022/1781a