A Strategy for Empowering Multi-Child Semantic Maps through Alpha C-Means Algorithm

Authors

  • Saritha Dasari Research Scholar, JNTUA, Ananthapuramu, Andhra Pradesh, India.
  • A. Rama Mohana Reddy Professor, Department of CSE, S.V. University, Tirupati, Andhra Pradesh, India.
  • B. Eswara Reddy Professor, Department of CSE, JNTU, Kalikiri, Andhra Pradesh, India

Keywords:

Clustering, Image, Semantic Maps, Spanning Trees

Abstract

Image technology is a developing field that involves harnessing the photovoltaic impact of each image and transforming it into data for segregation. The utilization of this imaging system holds significant importance across diverse industries. Computer science research about image processing has experienced significant growth and advancement, exhibiting a dynamic and progressive nature. The advancement of data in image processing is intricately linked to the image itself. Image analysis pertains to extracting concealed information and interpreting photographs that may lack explicit depiction of the depicted scenario. The image integrates several elements from machine learning, data management, application autonomy, and image processing. Semantic maps serve as visual representations that encapsulate stored image data in extensive databases. A prior investigation was dedicated to the utilization of the K-C Means Clustering Algorithm, specifically recognized as the MCSMK-C Algorithm. This algorithm was applied to facilitate a two-path clustering approach on Multi-Child Semantic Maps. This algorithm facilitates the formation of image clusters and enables the system to analyze the final section of the image. This work presents the Alpha-C Means Algorithm, which focuses on enhancing accuracy. The heightened aversion towards the image prompts the establishment of optimal criteria for visual comparison and repulsion. The Multi Child Semantic Maps algorithm enhances the precision of generating image outputs. The experimental results demonstrate the statistical importance of the expected and actual output.

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References

Vaidya, Jaideep, and Chris Clifton. "Privacy preserving association rule mining in vertically partitioned data." Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining. 2002.

Li, Lichun, et al. "Privacy-preserving-outsourced association rule mining on vertically partitioned databases." IEEE transactions on information forensics and security 11.8 (2016): 1847-1861.

Chen, Jingxiang, et al. "A distributed decision tree algorithm and its implementation on big data platforms." 2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA). IEEE, 2016.

Beloglazov, Anton, and Rajkumar Buyya. "Optimal online deterministic algorithms and adaptive heuristics for energy and performance efficient dynamic consolidation of virtual machines in cloud data centers." Concurrency and Computation: Practice and Experience 24.13 (2012): 1397-1420.

Bazarbayev, Sobir, et al. "Content-based scheduling of virtual machines (VMs) in the cloud." 2013 IEEE 33rd International Conference on Distributed Computing Systems. IEEE, 2013.

Ngenzi, Alexander, and Suchithra R. Nair. "Dynamic resource management in Cloud datacenters for Server consolidation." arXiv preprint arXiv:1505.00577 (2015).

Tran, Tony T., et al. "Resource-aware scheduling for data centers with heterogenous servers." (2015).

Dong, Ziqian, Ning Liu, and Roberto Rojas-Cessa. "Greedy scheduling of tasks with time constraints for energy-efficient cloud-computing data centers." Journal of Cloud Computing 4.1 (2015): 1-14.

Papalexakis, Evangelos E. "Automatic unsupervised tensor mining with quality assessment." Proceedings of the 2016 SIAM International Conference on Data Mining. Society for Industrial and Applied Mathematics, 2016

Thakar, Pooja, and Anil Mehta. "Performance analysis and prediction in educational data mining: A research travelogue." arXiv preprint arXiv:1509.05176 (2015).

Madapudi, Rudra Kumar, A. Ananda Rao, and Gopichand Merugu. "Change requests artifacts to assess the impact on the structural design of SDLC phases." Int’l J. Computer Applications 54.18 (2012): 21-26

Chalapathi, M. M., et al. "Ensemble Learning by High-Dimensional Acoustic Features for Emotion Recognition from Speech Audio Signal." Security and Communication Networks 2022 (2022)

Ramana, Kadiyala, et al. "Leaf disease classification in smart agriculture using deep neural network architecture and IoT." Journal of Circuits, Systems and Computers 31.15 (2022): 2240004.

Kumar, V., M. Rudra Kumar, N. Shribala, Ninni Singh, Vinit Kumar Gunjan, and Muhammad Arif. "Dynamic Wavelength Scheduling by Multiobjectives in OBS Networks." Journal of Mathematics 2022 (2022).

Goud, B. ., & Anitha, R. . (2023). Emerging Routing Method Using Path Arbitrator in Web Sensor Networks. International Journal on Recent and Innovation Trends in Computing and Communication, 11(4), 232–237. https://doi.org/10.17762/ijritcc.v11i4.6444

Merwe, M. van der, Petrova, M., Jovanović, A., Santos, M., & Rodríguez, M. Text Summarization using Transformer-based Models. Kuwait Journal of Machine Learning, 1(3). Retrieved from http://kuwaitjournals.com/index.php/kjml/article/view/141

Dhabliya, D. (2021). Delay-tolerant sensor network (DTN) implementation in cloud computing. Paper presented at the Journal of Physics: Conference Series, , 1979(1) doi:10.1088/1742-6596/1979/1/012031 Retrieved from www.scopus.com

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Published

30.08.2023

How to Cite

Dasari, S. ., Reddy, A. R. M. ., & Reddy , B. E. . (2023). A Strategy for Empowering Multi-Child Semantic Maps through Alpha C-Means Algorithm. International Journal of Intelligent Systems and Applications in Engineering, 11(11s), 329–335. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/3477

Issue

Vol. 11 No. 11s (2023)

Section

Research Article

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