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All issues Volume 507 (2024) E3S Web of Conf., 507 (2024) 01015 References
Open Access
Issue
E3S Web of Conf.
Volume 507, 2024
International Conference on Futuristic Trends in Engineering, Science & Technology (ICFTEST-2024)
Article Number 01015
Number of page(s) 9
DOI https://doi.org/10.1051/e3sconf/202450701015
Published online 29 March 2024
  1. Prathik, Anandhan, K. Uma, and J. Anuradha. “An Overview of application of Graph theory.” International Journal of ChemTech Research 9.2 (2016): 242–248. [Google Scholar]
  2. Sadavare, A. B., and R. V. Kulkarni. “A review of application of graph theory for network.” International Journal of Computer Science and Information Technologies 3.6 (2012): 5296–5300. [Google Scholar]
  3. Majeed, Abdul, and Ibtisam Rauf. “Graph theory: A comprehensive survey about graph theory applications in computer science and social networks.” Inventions 5.1 (2020): 10. [CrossRef] [Google Scholar]
  4. Ismail, Lina Elsherif, and Waldemar Karwowski. “A graph theory-based modeling of functional brain connectivity based on eeg: A systematic review in the context of neuroergonomics.” IEEE Access 8 (2020): 155103–155135. [CrossRef] [Google Scholar]
  5. Hubert, Lawrence J. “Some applications of graph theory to clustering.” Psychometrika 39.3 (1974): 283–309. [CrossRef] [Google Scholar]
  6. Heckmann, Tobias, Wolfgang Schwanghart, and Jonathan D. Phillips. “Graph theory—Recent developments of its application in geomorphology.” Geomorphology 243 (2015): 130–146. [CrossRef] [Google Scholar]
  7. Swarna, K. S. V., Vinayagam, A., Ananth, M. B. J., Kumar, P. V., Veerasamy, V., & Radhakrishnan, P. (2022). A KNN based random subspace ensemble classifier for detection and discrimination of high impedance fault in PV integrated power network. Measurement, 187, 110333. [CrossRef] [Google Scholar]
  8. Mondal, Basudeb, and Kajal De. “An overview applications of graph theory in real field.” International Journal of Scientific Research in Computer Science, Engineering and Information Technology 2.5 (2017): 751–759. [Google Scholar]
  9. Chakraborty, A., Dutta, T., Mondal, S., & Nath, A. “Application of graph theory in social media.” International Journal of Computer Sciences and Engineering 6.10 (2018): 722–729. [CrossRef] [Google Scholar]
  10. Awasthi, A., Saxena, K. K., & Arun, V. (2021). Sustainable and smart metal forming manufacturing process. Materials Today: Proceedings, 44, 2069–2079. [Google Scholar]
  11. Manohar, T., Prashantha, S. C., Nagaswarupa, H. P., Naik, R., Nagabhushana, H., Anantharaju, K. S., … & Premkumar, H. B. (2017). White light emitting lanthanum aluminate nanophosphor: near ultra violet excited photoluminescence and photometric characteristics. Journal of Luminescence, 190, 279–288. [CrossRef] [Google Scholar]
  12. Derrible, Sybil, and Christopher Kennedy. “Applications of graph theory and network science to transit network design.” Transport reviews 31.4 (2011): 495–519. [CrossRef] [Google Scholar]
  13. Singh, Rishi Pal. “Application of graph theory in computer science and engineering.” International Journal of Computer Applications 104.1 (2014). [Google Scholar]
  14. Kumar, C. P., Raghu, M. S., Prathibha, B. S., Prashanth, M. K., Kanthimathi, G., Kumar, K. Y., … & Alharthi, F. A. (2021). Discovery of a novel series of substituted quinolines acting as anticancer agents and selective EGFR blocker: Molecular docking study. Bioorganic & Medicinal Chemistry Letters, 44, 128118. [CrossRef] [PubMed] [Google Scholar]
  15. Likaj, R., Shala, A., Mehmetaj, M., Hyseni, P., & Bajrami, X. “Application of graph theory to find optimal paths for the transportation problem.” IFAC Proceedings Volumes 46.8 (2013): 235–240. [Google Scholar]
  16. chary, Thipparthi Raja gopala, Srikar potnuru, R. Jose Immanuel, Kuldeep K. Saxena, Dharam Buddhi, and Ajit Behera. “Dissimilar metal welding on Mg AZ31 and AA 6061 alloys by using friction stir welding.” International Journal on Interactive Design and Manufacturing (IJIDeM) 17, 6 (2023): 2913–2918. [CrossRef] [Google Scholar]
  17. Ruiz-Frau, A., Ospina-Alvarez, A., Villasante, S., Pita, P., Maya-Jariego, I., & de Juan, S. “Using graph theory and social media data to assess cultural ecosystem services in coastal areas: Method development and application.” Ecosystem Services 45 (2020): 101176. [CrossRef] [Google Scholar]
  18. Alkorbi, A. S., Kumar, K. Y., Prashanth, M. K., Parashuram, L., Abate, A., Alharti, F. A., … & Raghu, M. S. (2022). Samarium vanadate affixed sulfur self doped g-C3N4 heterojunction; photocatalytic, photoelectrocatalytic hydrogen evolution and dye degradation. International Journal of Hydrogen Energy, 47(26), 12988–13003. [CrossRef] [Google Scholar]
  19. Yi, Zhiyan, Xiaoyue Cathy Liu, Nikola Markovic, and Jeff Phillips. “Inferencing hourly traffic volume using datadriven machine learning and graph theory.” Computers, Environment and Urban Systems 85 (2021): 101548. [CrossRef] [Google Scholar]
  20. Vecchio, F., Miraglia, F., Judica, E., Cotelli, M., Alù, F., & Rossini, P. M. “Human brain networks: A graph theoretical analysis of cortical connectivity normative database from EEG data in healthy elderly subjects.” GeroScience 42 (2020): 575–584. [CrossRef] [PubMed] [Google Scholar]
  21. Erb, Wolfgang. “Shapes of uncertainty in spectral graph theory.” IEEE Transactions on Information Theory 67, no. 2 (2020): 1291–1307. [Google Scholar]
  22. Tripathi, G. P., Agarwal, S., Awasthi, A., & Arun, V. (2022, August). Artificial Hip Prostheses Design and Its Evaluation by Using Ansys Under Static Loading Condition. In Biennial International Conference on Future Learning Aspects of Mechanical Engineering (pp. 815–828). Singapore: Springer Nature Singapore. [Google Scholar]
  23. Raj, Ashish, Chang Cai, Xihe Xie, Eva Palacios, Julia Owen, Pratik Mukherjee, and Srikantan Nagarajan. “Spectral graph theory of brain oscillations.” Human brain mapping 41, 11 (2020): 2980–2998. [CrossRef] [PubMed] [Google Scholar]
  24. Srinivasan, K., Porkumaran, K., & Sainarayanan, G. (2009, August). Improved background subtraction techniques for security in video applications. In 2009 3rd International Conference on Anti-counterfeiting, Security, and Identification in Communication (pp. 114–117). IEEE. [Google Scholar]
  25. Koutrouli, M., Karatzas, E., Paez-Espino, D., & Pavlopoulos, G. A. (2020). A guide to conquer the biological network era using graph theory. Frontiers in bioengineering and biotechnology, 8, 34. [CrossRef] [PubMed] [Google Scholar]
  26. Hashmi, Abdul Wahab, Harlal Singh Mali, Anoj Meena, Nakul Gupta, Shadab Ahmad, Kuldeep K. Saxena, and Vinayak Malik. “Abrasive Flow Finishing of Fdm Printed Extrusion Die Insert Pattern Using Novel Afm Fixture with Mandrel Guide.” Surface Review and Letters 30, 06 (2023): 2350034. [CrossRef] [Google Scholar]
  27. Indira, D. N. V. S. L. S., Rajendra Kumar Ganiya, P. Ashok Babu, A. Xavier, L. Kavisankar, S. Hemalatha, V. Senthilkumar et al. “Improved artificial neural network with state order dataset estimation for brain cancer cell diagnosis.” BioMed Research International 2022 (2022). [Google Scholar]
  28. Padmaja, B., VV Rama Prasad, and K. V. N. Sunitha. “A machine learning approach for stress detection using a wireless physical activity tracker.” International Journal of Machine Learning and Computing 8, no. 1 (2018): 33–38. [CrossRef] [Google Scholar]
  29. Hashmi, Abdul Wahab, Harlal Singh Mali, Anoj Meena, Nakul Gupta, Shadab Ahmad, Kuldeep K. Saxena, and Vinayak Malik. “Abrasive Flow Finishing of Fdm Printed Extrusion Die Insert Pattern Using Novel Afm Fixture with Mandrel Guide.” Surface Review and Letters 30, 06 (2023): 2350034. [CrossRef] [Google Scholar]
  30. Löffler, Matthias, Anderson Y. Zhang, and Harrison H. Zhou. “Optimality of spectral clustering in the Gaussian mixture model.” The Annals of Statistics 49, 5 (2021): 2506–2530. [Google Scholar]
  31. Zhu, Xiaofeng, Yonghua Zhu, and Wei Zheng. “Spectral rotation for deep one-step clustering.” Pattern Recognition 105 (2020): 107175. [CrossRef] [Google Scholar]
  32. Tanaka, Yuichi, Yonina C. Eldar, Antonio Ortega, and Gene Cheung. “Sampling signals on graphs: From theory to applications.” IEEE Signal Processing Magazine 37, 6 (2020): 14–30. [CrossRef] [Google Scholar]
  33. Gama, Fernando, Elvin Isufi, Geert Leus, and Alejandro Ribeiro. “Graphs, convolutions, and neural networks: From graph filters to graph neural networks.” IEEE Signal Processing Magazine 37, 6 (2020): 128–138. [CrossRef] [PubMed] [Google Scholar]
  34. Mateos, Gonzalo, Santiago Segarra, Antonio G. Marques, and Alejandro Ribeiro. “Connecting the dots: Identifying network structure via graph signal processing.” IEEE Signal Processing Magazine 36, 3 (2019): 16–43. [CrossRef] [Google Scholar]
  35. Li, Rui, Xin Yuan, Mohsen Radfar, Peter Marendy, Wei Ni, Terrence J. O’Brien, and Pablo M. Casillas-Espinosa. “Graph signal processing, graph neural network and graph learning on biological data: a systematic review.” IEEE Reviews in Biomedical Engineering 16 (2021): 109–135. [Google Scholar]
  36. Stanković, Ljubiša, Miloš Daković, and Ervin Sejdić. “Introduction to graph signal processing.” Vertex-Frequency Analysis of Graph Signals (2019): 3–108. [Google Scholar]
  37. Sporns, Olaf. “Graph theory methods: applications in brain networks.” Dialogues in clinical neuroscience 20, no. 2 (2018): 111–121. [CrossRef] [PubMed] [Google Scholar]
  38. Upadhyay, K. K., Srivastava, S., Arun, V., & Shukla, N. K. (2020). Design and performance analysis of all-optical reversible full adder, as ALU. Proceedings of the National Academy of Sciences, India Section A: Physical Sciences, 90, 899–909. [Google Scholar]
  39. Heckmann, Tobias, Wolfgang Schwanghart, and Jonathan D. Phillips. “Graph theory—Recent developments of its application in geomorphology.” Geomorphology 243 (2015): 130–146. [CrossRef] [Google Scholar]
  40. Radhakrishna, Vangipuram, P. V. Kumar, V. Janaki, and N. Rajasekhar. “Estimating prevalence bounds of temporal association patterns to discover temporally similar patterns.” In International Conference on Soft Computing- MENDEL, pp. 209–220. Cham: Springer International Publishing, 2016. [Google Scholar]
  41. Mohammed, Kahtan A., Hussein A. Alshamarti, Hadeel A. Jameel, Zahraa Falah Khudair, Rahman S. Zabibah, and Kuldeep K. Saxena. “Enhancing the parameters of ZnO/CdZnS thin film photodetector by thermal annealing.” Optical and Quantum Electronics 55, 4 (2023): 366. [CrossRef] [Google Scholar]
  42. Jaimin, Aarjoo, Nitin Kotkunde, Swadesh Kumar Singh, and Kuldeep Kumar Saxena. “Studies on flow stress behaviour prediction of AZ31B alloy: Microstructural evolution and fracture mechanism.” Journal of Materials Research and Technology 27 (2023): 5541–5558. [CrossRef] [Google Scholar]

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