1.       

Devi P, Kizielewicz B, Guleria A,Shekhovtsov A, WątróbskiJ, Królikowski T,Więckowski J and Sałabun W. 2022. Decision Support in Selecting a Reliable Strategy for Sustainable Urban Transport Based on Laplacian Energy of T-Spherical Fuzzy Graphs. Energies, 15(14), 4970. https://doi.org/10.3390/en15144970. NAAS:9.2

2.       

Devi P, Kizielewicz B, Guleria A,Shekhovtsov A, WątróbskiJ, Królikowski T,Więckowski J and Sałabun W. 2022. Decision Support in Selecting a Reliable Strategy for Sustainable Urban Transport Based on Laplacian Energy of T-Spherical Fuzzy Graphs. Energies, 15(14), 4970. https://doi.org/10.3390/en15144970. NAAS:9.2

3.       

Bajaj R. K., Srivastava S and Abhishek Guleria. 2023. Solving Multi-objective Linear Fractional Programming Problem Utilizing (α, β)- cut Triangular Intuitionistic Fuzzy setup: In: L. Sahoo, T. Senapati, R.R. Yager (eds), Real Life Applications of Multiple Criteria Decision-Making Techniques in Fuzzy Domains. Studies in Fuzziness and Soft Computing, Vol 420,  Springer, Singapore. [Scopus Indexed]

4.       

Bhardwaj S and Banti Kumar. 2022. Forecasting of Potato Production in Himachal Pradesh using ARIMA model. Potato Journal, 49(2): 167-173. NAAS Rating: 4.94

5.       

Hussain S, Sharma M, Banti Kumar and Bhat VA. 2022. Almost unbiased dual exponential type estimators of population mean using auxiliary information. Statistics and Application, 20(2), 147-156. NAAS RATING:  5.76 

6.       

Kumar A, Goyal M and Kumar N. 2021. A Class of Tests Based Jointly on Sub-Sample Minimum and Median. Journal of the Kerala Statistical Association. 32:1-17.

7.       

Sharma M, Singh AK, Salgotra RK, Sharma BK, Gangurde SS, Bakshi P, Raina, M and Kumar B. 2021. Assessment of genetic advance and correlation coefficient for yield and yield attributed traits of RIL population in Basmati Rice (Oryzae sativa L.). Journal of Pharmacognosy and Photochemistry. 10(1):328-330.

8.       

Kumar B, Sharma M, Bhat A& Sharma P. (2021). An analysis of Indian agricultural workers: A ridge regression approach. Agricultural Economics Research Review. 34. 121-127.

9.       

Guleria A and Bajaj RK. 2021. T-spherical fuzzy soft sets and its aggregation operators with application in decision making. ScientiaIranica. 28(2), 1014-1029.

10.   

Guleria A and Bajaj RK. 2021. Eigen spherical fuzzy set and its application in decision making problem. ScientiaIranica. 28(1):516-531.

11.   

Guleria A and Bajaj RK. 2021.On some new statistical correlation measures for t-spherical fuzzy sets and applications in soft computing. Journal of Information Science and Engineering. 37(2):323-336.

12.   

Kumar I, Gupta RK and Kumar A.  2020.  Construction of Two-Way Volume Table of Eucalyptus Tereticornis for Mid-Himalayan Region of Himachal Pradesh, International Journal of Bio Resource and Stress management.11(1):046-050.

13.   

Kumar N and Kumar A. 2020. Two Sample Statistical Test for Location Parameters. Journal of Modern Applied Statistical Methods.

14.   

Kumar B and Sharma M.2020. General class of improved product type estimator. European Journal of Molecular and clinical medicine. 07(07):4349-435.5

15.   

Guleria A and Bajaj RK. 2020. A robust decision-making approach for hydrogen power plant site selection utilizing (R, S)-norm Pythagorean fuzzy information measures based on VIKOR and TOPSIS method. International Journal of Hydrogen Energy. 45(38):18802–18816.

16.   

Guleria A and Bajaj RK. 2020. T-spherical fuzzy graphs: Operations and applications in various selection processes. Arabian Journal for Science and Engineering.45:2177–2193.

17.   

Guleria A and Bajaj RK. 2020. Pythagorean fuzzy (R, S)-norm discriminant measure in various decision-making processes. Journal of Intelligent Fuzzy Systems. 38(1):761–777.

18.   

Bajaj RK and Guleria A .2020. Dimensionality reduction technique in decision making using Pythagorean fuzzy soft matrices. Recent Patents on Computer Science.13 (3):406–413.

19.   

Kumar B. and SharmaM.2019.Forecasting of Cotton Production In India- An ARIMA Modelling Approach. Think India Journal, 22(16):3255-3263.

20.   

Kumar B, Monika, Bhanot RP and Sharma M. 2019.Forecasting of Oilseed Crop Production through Time Series Modelling. Think India Journal.22 (37):321-329.

21.   

Guleria A and Bajaj RK. 2019. On Pythagorean fuzzy soft matrices, operations and their applications in decision making and medical diagnosis. Soft Computing, 21(17), 7889–7900.

22.   

Guleria A, Srivastava S. & Bajaj RK. 2019. On parametric divergence measure of neutrosophic sets with its application in decision making models. Neutrosophic Sets and Systems. 29:101–120.

23.   

Guleria A and Bajaj RK. 2019. Technique for reducing dimensionality of data in decision making utilizing neutrosophic soft matrices. Neutrosophic Sets and Systems, 29, 129–141,

24.   

Sharma M, Jasrotia N, Kumar B and Singh SP. 2019.Marketing and Statistical Assessment of Income of Fish Retailers in Jammu Region of Jammu & Kashmir State. India. International Journal of Bio-resource and Stress Management. 10(6):645-650.

25.   

Sharma M, Jasrotia N, Kumar B, Bhat A and Mahajan S. 2018. Modeling of Monthly Arrival of Rohu Fish using ARIMA in Jammu Region of J&K State. Journal of animal research. 8(2):259-262.

26.   

Mahajan S, Sharma M and Kumar B .2018.Robust modeling in the presence of outliers for food grain production in India. International Research Journal of Agricultural Economics and Statistics. 9(1):25-30.

27.   

Guleria A and Bajaj RK. 2018. Pythagorean fuzzy (R, S)-norm information measure for multicriteria decision-making problem. Advances in Fuzzy Systems. 1–11.

28.   

Angotra J, Bali RK, Mazal B and Kumar B.2018. Expression of heterosis in silkworm hybrids with popular commercial hybrid CSR2 x CSR4 as control. Journal of Pharmacognosy and Photochemistry. 7(4):2219-2223.

29.   

Iqbal MIJ, Nazir N, Sharma M, Bhat A, Gul M and Kumar B. 2018. R codes for Randomized complete Block Design. International Journal of Information Science and System. 6(1):1-8.

30.   

Kumar M, Chandra H, Kumar B and Saxena KK. 2018. A Class of dual type estimators for estimating the population mean. Paper accepted for publication in the proceeding of the Annual Statistics Conference during the 3^rd Statistical Conference of Department of Statistics, University of Dodoma, Dodoma, Tanzania. ISBN 978-9987-04-062-9.

31.   

Kumar B, and Mahajan, S. (2018). Use of Auxiliary information in improving Ratio type estimators for estimation of Population mean. SIDAVES Journal of Safe Agriculture,02(1):05-09.

32.   

Mahajan S, Sharma M, Peshin R, Arya VM and Kumar B. 2018. Production performance of Maize in India: An ARIMA Approach. SIDAVES Journal of Safe Agriculture, 02(1):24-27.

33.   

Kumar B, Sharma M, Bhat, MIJ and Danish F. 2018. Modified product type estimator. International Journal of Agricultural and Statistical Sciences. 14(1):371-376.

34.   

Kumar B, Sharma M, Rizvi SEH and Bhat, MIJ. 2018.  Estimation of Population Mean through Improved Class Ratio Type Estimators using Auxiliary Information. Journal of Reliability and Statistical Studies. 11(1):01-07.

35.   

Sharma M, Sharma P, Kumar B, Mahajan S and Archana. 2017. Testing statistical Models for forecasting malaria cases in India. International Research Journal of Agricultural Economics and Statistics.8 (1): 8-14.

36.   

Mujahid K, Hasija, RC, Hooda BK, Tanwar, N and Kumar, B. 2017. Relative efficiency of experimental designs in relation to various size and shape of plots and blocks in Indian mustard (Brassica juncea l.) crop. International Journal of Agricultural and Statistical Sciences, 13(1): 253-258.

37.   

Kumar B, Sharma M, Rizvi SEH, Mahajan S. 2017. Improved General Class of Ratio Type Estimators. International Journal of Mathematics and Computer Research. 5(8): 1790-1796.

38.   

Sharma M and Sharma V. 2017.Effect of carbon nanotubeadition on the thermite reaction in the Al/CuO energetic nanocomposites. Philosophical Magazine. 97(22): 1921-1938,

39.   

Mahajan S, Sharma M, Peshin R, Bhat, A and Kumar B. 2017. Production of Rice in India: A robust statistical approach. Maharashtra Journal of Agricultural Economics. 20(2):137-140.

40.   

Sharma M and Sharma V. 2016. Chemical, Mechanical and Thermal Expansion Properties of Carbon Nanotube Reinforced Aluminum Nanocomposite. International Journal of Minerals, Metallurgy and Materials. 23(2): 222-233.

41.   

Sharma M and Sharma V. 2016.Thermal and Electrical Properties of Functionalized Multiwall Carbon Nanotube Reinforced Nanocrystalline Aluminium Matrix Composite. Z Naturforsch A. 71(2):165-174.

42.   

Sharma M and Sharma V. 2016. Tailoring Oxidation of Aluminum Nanoparticles Reinforced with Carbon Nanotubes, AIP Conference Proceedings1731, 050086.

43.   

Sharma M, Kumar B, Bhat A, Jeelani MIJ & Mahajan S. 2016. Robust Regression Model to Study the Number of Indian Agricultural Workers. Indian Journal of Ecology. 43(1):599-601.

44.   

Kumar B, Sharma M, Rizvi SEH and Singh SP. 2015. Impact of influential and outlier observations on the ordinary least square model for Indian agriculture workers. Ecology, Environment and Conservation. 21 (2):955-962.

45.   

Sharma M, Pal H, and Sharma V. 2015.The Mechanical Properties Measurement of Multiwall Carbon Nanotube Reinforced Nanocrystalline Aluminum Matrix Composite. AIP Conference Proceedings.1661:080025.

46.

Sharma M, Pal H, and Sharma V. 2014.Thermal expansion of multiwall carbon nanotube reinforced nanocrystalline silver matrix composite. AIP Conference Proceedings.1591, 374-376.

47.

Sharma M, Pal H, and Sharma V. 2014.Electrical Conductivity and Thermal Expansion Measurement of Nanocrystalline Aluminum Reinforced with Functionalized Multiwall Carbon Nanotubes. International Journal of Chemtech Research. 6(3):2057-2059.

48

Pal H, Sharma V and Sharma M. 2014.Influence of functionalization on mechanical and electrical properties of carbon nanotube-based silver composites. Philosphical Magazine.94 (13): 1478 -1492.

49.

Pal H, Sharma V and Sharma M. 2014. Thermal expansion behavior of CNT/Ag nanocomposite. International Journal of Materials Research. 105E:1-5.

50.

Thakur A, Kumar S, Sharma M and Rangra VS. 2016. Optical, electrical and antimicrobial studies of chemically synthesized graphite oxide and reduced graphene oxide. Advanced Materials Letters.7 (12), 1029-1034.

Books/Book Chapters:

1.

Sharma M, Kumar B and Rizvi SEH.  2016. Statistical Techniques for Insect Pest Management. Integrated Pest Management Part-II: Edited by D.P. Abrol, Chapter 25^th, New India Publishing Agency, New Delhi (India). Pp.751-763.(ISBN: 978-93-85516-11-5)

2.

Sharma M, Sharma P, Kumar B and Jeelani MIJ. 2016. Survey Sampling for Assessing Externalities in Agriculture and Policy Planning. Agricultural marketing Perspectives and Potentials: Edited By Anil Bhat and S.P. Singh, Chapter 27^th, New India Publishing Agency, New Delhi (India). Pp.403-419. (ISBN: 978-93-85516-15-3)

3.

Sharma M, Mahajan S and Kumar B.2016. Statistical Techniques in Social Sciences for perspective. Research in Social Sciences: Interdisciplinary Perspective. Edited by Priyanka Sharma, Social research Foundation, Kanpur, 123-133.(ISBN:978-81-921665-8-2)

4.

Sharma M and Kumar B. 2017. Statistical Methods for Data Analysis using SPSS.  Book published on Essential Bioinformatics and Data Mining by the Society for Bioinformatics and Biological Sciences (SBBS) during the international conference of SBBS on Recent trends in Bioinformatics and Biotechnology for Sustainable Development during October 12 - 13, 2017. Chapter 3, pp. 21-50.(ISBN: 978-93-86200-45-7)

5.

Sharma M, Kumar B, Mahajan V and Bhat MIJ. (2020) Ridge Regression Model for the Estimation of Total Carbon Sequestered by Forest Species. In: Chandra G., Nautiyal R., Chandra H. (eds) Statistical Methods and Applications in Forestry and Environmental Sciences. Forum for Interdisciplinary Mathematics. Springer, Singapore. (ISBN: 978-981-15-1475-3)

6.

Bajaj RK and Guleria A. 2021.  Spherical Fuzzy Information and Graphs with soft Computing Applications. ISBN: 978-81-8487-720-5.