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All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan INSPIREE: Indonesian Sport Innovation Review International Research Journal of Business Studies IJOT
Ajay Kumar
Raj Kumar Goel Engineering College, Ghaziabad
Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Health Professions Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation

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Patterns, Determinants and Challenges of Horticulture Diversification in India Meena, Akshay; Kumar, Ajay; Meena, Anita
International Research Journal of Business Studies Vol. 16 No. 1 (2023): April - July 2023
Publisher : Universitas Prasetiya Mulya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21632/irjbs.16.1.99-110

Abstract

This study attempts to analyze the trends and patterns of horticulture diversification in India, the differences between states in diversification toward highvalue crops, and identify the factors influencing horticulture diversification. Total horticulture crops have shown moderate diversification. Among horticulture crops, Fruits, plantation crops and spices have exhibited high diversification, whereas high and moderate diversification have been recorded for vegetables during the period under study.The states Assam, Andhra Pradesh, Arunachal Pradesh,Bihar,Gujrat, Kerala, Karnataka, Chhattisgarh, Meghalaya,Madhya Pradesh, Mizoram, Maharashtra, Manipur, Nagaland, Rajasthan, Odisha, Sikkim, Tripura, Telangana, Tamil Nadu,Uttar Pradesh have shown high diversification whereas Jammu & Kashmir, Himachal Pradesh, Haryana, Punjab, Jharkhand, West Bengal, Uttarakhand have displayed moderate diversification in the year 2020-21. Per capita income, annual rainfall, and lagged SID for total horticulture crops all have positive effects on horticulture diversification, whereas fertilizer consumption has a negative effect.
Research on Strength and Durability of Concrete Manufactured with Artificial Sand Kumar, Ajay; Kadian, Dr. Amarender
International Journal on Orange Technologies Vol. 4 No. 11 (2022): IJOT
Publisher : Research Parks Publishing LLC

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Abstract

The use of synthetic sand in concrete has attracted the interest of numerous academics all over the world. The growing demand for fine aggregate for the needs of building is greater than the supply of limited natural sand that is currently available. The physical properties of naturally occurring river sand and man-made sand should be compared (M-sand). The current study focused on the M30, M40, and M50 mixtures. The modulus of elasticity (MOE) was calculated by altering the proportion of M-sand from 0 to 100%. To determine the optimal percentage of manufactured sand, the aforementioned mixes were also evaluated for sorptivity and impact resistance. Moreover, microscopic studies were performed using scanning electron microscopy (SEM) and electron dispersive spectroscopy (EDS). Yet, as concrete grade and M-sand content increased, sorptivity was found to decrease. Also, a comparison between experimental MOE values and IS code results was done. According to microscopic investigations, M-sand has an angular and rough surface in comparison to natural sand, which is thought to be the cause of the material's improved MOE and impact resistance as well as its decreased sorptivity.
WAVELET-BASED COMPUTATIONAL FRAMEWORK FOR THE SOLOW-SWAN ECONOMIC MODEL Sahani, Jay Kishore; Sharma, Pankaj; Khanna, Nikhil; Kumar, Ajay
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 2 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss2pp1557-1568

Abstract

In this paper, we introduce an innovative numerical technique for addressing the classical Solow-Swan economic growth model through the application of the Haar wavelet approach. The Solow-Swan model, a cornerstone of neoclassical economics, elucidates long-run economic growth influenced by capital accumulation, labor, and technological advancements. Although various computational methods have been utilized to study its behavior, the use of wavelet-based techniques, specifically Haar wavelets, has been largely overlooked. The Haar wavelet method provides distinct benefits, such as computational simplicity and adaptability to piecewise continuous functions. By transforming the Solow-Swan model into a set of algebraic equations using Haar wavelet expansion, we showcase the method’s ability to accurately capture growth dynamics. We present numerical results to substantiate the efficacy of this approach and compare it with conventional numerical techniques, underscoring the advantages of wavelet-based solutions. This study offers a fresh perspective on economic modeling, emphasizing the potential of wavelet theory in the numerical analysis of growth equations.
A Performance Metrics–Based Model for Predicting Match Outcomes in the 2023 ICC Cricket World Cup Kumar, Ajay; Sisodia, Anurodh; Takhur, Yogesh Chander
INSPIREE: Indonesian Sport Innovation Review Vol. 7 No. 02 (2026): Articles May in Press (Accepted Manuscripts) – INSPIREE
Publisher : INSPIRETECH GLOBAL INSIGHT & DPE Universitas Pahlawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53905/inspiree.v7i02.172

Abstract

The  purpose  of  the study. To develop and validate a logistic regression model for predicting match outcomes in the 2023 ICC Cricket World Cup using selected in-game performance indicators and to determine the relative contribution of each variable. Materials and methods. Data from 47 matches of the 2023 ICC Men’s Cricket World Cup were analysed (one match decided by the Duckworth-Lewis-Stern method was excluded). Independent variables included Toss outcome, Opening Partnership Score, Runs and Wickets Lost in Powerplay, Total Number of Fours and Sixes, and Total Wickets Lost in an Inning. Binary logistic regression was applied to predict match outcomes (win/loss). Model goodness-of-fit was evaluated using the Hosmer-Lemeshow test. Results. Wickets Lost in an Inning was the strongest predictor (OR = 2.324, p < 0.05); each additional wicket lost increased the odds of losing by 132.4%. Each additional four reduced the odds of losing by 13.7% (OR = 0.863). Total sixes and other variables showed weaker or non-significant effects. Toss outcome and Opening Partnership Score were not statistically significant predictors. The final model demonstrated good fit (Hosmer-Lemeshow test, p > 0.05) and acceptable predictive accuracy. Conclusions. Preserving wickets throughout the innings and maximising boundary scoring (especially fours) are the most critical factors influencing match outcomes in the 2023 ICC Cricket World Cup. The developed logistic regression model offers a reliable tool for performance analysis and strategic decision-making in limited-overs cricket.
Co-Authors Kadian, Dr. Amarender Khanna, Nikhil Meena, Akshay Meena, Anita Sahani, Jay Kishore Sharma, Pankaj Sisodia, Anurodh Takhur, Yogesh Chander