Discrimination of Research Object in Academic Papers
DOI:
https://doi.org/10.71222/v57fhs97Keywords:
academic papers, research object, unit of analysis, research contentAbstract
By mainly employing the literature review method, this study analyzes the research objects in academic papers. The results indicate that, unlike the meanings in academic disciplines (or courses) or in the process of solving physics problems, the use of the term “research object” in academic papers exhibits the following characteristics: (1) Except in medical papers — where the term is clearly defined (primarily referring to humans and animals) — in general academic papers and in some research methods textbooks the term is commonly used without a strict definition, seemingly established by convention. (2) Although there is occasional mixing with terms related to samples (such as sampling groups and observation objects), the research object is generally considered relative to the overall population. (3) Differences in the limitations or focal points of the research content may lead to changes in the research object. (4) In social research methods, the unit of analysis replaces the research object and can express the complex meaning of the research object more accurately. (5) A lack of clear understanding of the research object may lead to “elevation errors” and “degradation errors” in research.
References
1. K. S. Fu, "Syntactic pattern recognition," in Applications of Pattern Recognition, CRC Press, 1982. ISBN: 9781351069809
2. E. Pavlick, "Semantic Structure in Deep Learning," Annual Review of Linguistics, vol. 8, no. 1, pp. 447-471, 2022, doi: 10.1146/annurev-linguistics-031120-122924.
3. Y. Wei, Y. Cheng, and H. T. Liao, "Fleet Service Reliability Analysis of Self-Service Systems Subject to Failure-Induced De-mand Switching and a Two-Dimensional Inspection and Maintenance Policy," IEEE Transactions on Automation Science and Engineering, 2024 Dec 2024, doi: 10.1109/tase.2024.3516049.
4. Y. Wei, Y. Cheng, and H. Liao, "A Quantitative Maintenance Policy Development Framework for a Fleet of Self-Service Systems," Naval Research Logistics (NRL), vol. n/a, no. n/a, 2025, doi: 10.1002/nav.22252.
5. Y. Wei, A. Li, Y. Cheng, and Y. Li, "An Optimal Multi-Level Inspection and Maintenance Policy for a Multi-Component System with a Protection Component," Computers & Industrial Engineering, p. 110898, 2025, doi: 10.1016/j.cie.2025.110898.
6. C. Y. Zou, J. W. Wang, and Y. Cheng, "The Impact of the Variability of Patient Flow and Service Time on the Efficiency of Large-Scale Outpatient Systems," IEEE Transactions on Computational Social Systems, vol. 10, no. 3, pp. 1230-1240, Jun 2023, doi: 10.1109/tcss.2021.3137930.
7. J. W. Wang, Y. Gao, and Y. Cheng, "On Time-Dependent Critical Platforms and Tracks in Metro Systems," Transportation Science, vol. 56, no. 4, pp. 953-971, Jul-Aug 2022, doi: 10.1287/trsc.2022.1124.
8. C. Y. Zou, J. W. Wang, and Y. Cheng, "Critical Department Analysis for Large-Scale Outpatient Systems," IEEE Transactions on Computational Social Systems, vol. 10, no. 6, pp. 3194-3203, Dec 2023, doi: 10.1109/tcss.2022.3212121.
9. Y. Gao, J. W. Wang, S. Gao, and Y. Cheng, "An Integrated Robust Design and Robust Control Strategy Using the Genetic Algorithm," IEEE Transactions on Industrial Informatics, vol. 17, no. 12, pp. 8378-8386, Dec 2021, doi: 10.1109/tii.2021.3056417.
10. X. Wang, X. Zhang, Y. Cao, W. Wang, C. Shen, and T. Huang, "Seggpt: Towards segmenting everything in context," in Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023, pp. 1130-1140, doi: 10.48550/arXiv.2304.03284.
11. Y. Cheng, H. T. Liao, and Z. Y. Huang, "Optimal Degradation-Based Hybrid Double-Stage Acceptance Sampling Plan for a Heterogeneous Product," Reliability Engineering & System Safety, vol. 210, Jun 2021, Art no. 107544, doi: 10.1016/j.ress.2021.107544.
12. Y. Cheng and E. A. Elsayed, "Optimal Sequential ALT Plans for Systems With Mixture of One-Shot Units," IEEE Transactions on Reliability, vol. 66, no. 4, pp. 997-1011, Dec 2017, doi: 10.1109/tr.2017.2728625.
13. S. S. Naik and M. N. Gaonkar, "Extractive Text Summarization by Feature-Based Sentence Extraction using Rule-Based Concept," in 2017 2nd IEEE international conference on recent trends in electronics, Information & Communication Technology (RTEICT), 2017: IEEE, pp. 1364-1368, doi: 10.1109/RTEICT.2017.8256821.
14. Y. Cheng and E. A. Elsayed, "Design of Optimal Sequential Hybrid Testing Plans," IISE Transactions, vol. 53, no. 7, pp. 830-841, Apr 2021, doi: 10.1080/24725854.2020.1805828.
15. Y. Cheng and E. A. Elsayed, "Reliability Modeling and Prediction of Systems With Mixture of Units," IEEE Transactions on Reliability, vol. 65, no. 2, pp. 914-928, Jun 2016, doi: 10.1109/tr.2015.2503340.
16. S. Dargan, M. Kumar, M. R. Ayyagari, and G. Kumar, "A survey of Deep Learning and its Applications: A New Paradigm to Machine Learning," Archives of Computational Methods in Engineering, vol. 27, pp. 1071-1092, 2020, doi: 10.1007/s11831-019-09344-w.
17. Y. Wei, Y. Cheng, and H. T. Liao, "Optimal Resilience-Based Restoration of a System Subject to Recurrent Dependent Haz-ards," Reliability Engineering & System Safety, vol. 247, Jul 2024, Art no. 110137, doi: 10.1016/j.ress.2024.110137.
18. Y. Cheng, E. A. Elsayed, and X. Chen, "Random Multi Hazard Resilience Modeling of Engineered Systems and Critical Infrastructure," Reliability Engineering & System Safety, vol. 209, May 2021, Art no. 107453, doi: 10.1016/j.ress.2021.107453.
19. Y. Cheng, Y. Wei, and H. T. Liao, "Optimal Sampling-Based Sequential Inspection and Maintenance Plans for a Heteroge-neous Product with Competing Failure Modes," Reliability Engineering & System Safety, vol. 218, Feb 2022, Art no. 108181, doi: 10.1016/j.ress.2021.108181.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Wenyue Xia (Author)

This work is licensed under a Creative Commons Attribution 4.0 International License.