Mechanical Expertise Management for the Information Management inScaling Systems with Deep Learning Process

Suresh Punnapu

doi:10.69996/jcai.2024023

Authors

Suresh Punnapu Assistant Professor, Department of ECE, Rajiv Gandhi University of Knowledge Technologies, Nuzvid (RGUKT-Nuzvid), Krishna District, Andhra Pradesh - 521201, India. Author

DOI:

https://doi.org/10.69996/jcai.2024023

Keywords:

Information Management, Deep Learning, Prediction, Dynamic Scaling, Information System Development Classification

Abstract

Dynamic scaling information management refers to the adaptive process of adjusting resources and managing data in real time to meet varying demands in computational and storage environments, particularly in cloud computing and data-intensive applications. This approach ensures optimal performance and resource utilization by automatically allocating or deallocating computing power,storage capacity, and network bandwidth based on current workloads and system performance metrics. Key components include monitoring tools that continuously assess resource usage, predictive analytics to anticipate future demands, and automated orchestration systems that execute scaling actions without human intervention. This paper introduces Predicted Dynamic Scaling in Information System Development (PDS-ISD) as a novel framework for talent cultivation within ISD education. By synthesizing empirical observations and theoretical models, PDS-ISD offers a predictive tool to forecast talent cultivation outcomes based on key educational factors. Through a comprehensive review of literature, the paper explores the theoretical foundations and practical applications of PDS-ISD in ISD education. Additionally, simulated results demonstrate the effectiveness of PDS-ISD in predicting talent outcomes across various scenarios. The findings highlight the importance of factors such as curriculum design, instructor expertise, student readiness, and project demands in shaping talent cultivation outcomes. The paper concludes with implications for practice and future research directions to further enhance the predictive capabilities and applicability of PDS-ISD in ISD education. Additionally, simulated results demonstrate the effectiveness of PDS-ISD in predicting talent outcomes across various scenarios, with an average accuracy of 85%. The findings highlight the importance of factors such as curriculum design, instructor expertise, student readiness, and project demand in shaping talent cultivation outcomes

References

[1] Z.Zheng, L.Jin and Y.Huang, “Distributed Education Talent Cultivation Model and Practice in Higher Vocational Colleges,” International Journal of Education and Humanities, vol.7, no.2,pp.49-59, 2023.

[2] H.Ao, H.Yan, H.Zhang and J.Zhang, “Teaching Reform and Practice of StrengtheningEngineering Education in Mechanical Engineering Specialty,” In 2022 International Conference on Engineering Education and Information Technology (EEIT), pp.45-48, IEEE, 2022.

[3] R.Liu, G.Chi, F.Wang, L.Yang, H.Yue and Y.Lu, “Talent cultivation method of aerospace manufacturing engineering incorporating new aerospace technology,” In SHS Web of Conferences,vol. 137, pp. 01016, 2022.

[4] Z.Yin, Z.Wu, D.Li, Y.Zhao and J.Liu, “Research on the talents education scheme based on integration of science and education for information and communication engineering,” International Journal of Information and Education Technology, vol.12, no.4, pp.359-364, 2022.

[5] D.Lv and Y.Zhang, “Teaching Reform and Practice of Sensor and Detection Technology Course Based on Specialty and Innovation Integration and Project-Based Education,” In International Conference on Computer Science, Engineering and Education Applications, pp. 1033-1045, 2023.

[6] X.Zhang, L.Meng, G.Cai, L.Geng, Q.Song and S.Liu, “Exploration of Innovation Points of Cultivating High-Quality Talents under the Background of New Engineering:--Taking Tangshan Colleges and Universities as an Example,” Journal of Education and Educational Research, vol.7, no.1, pp.16-22, 2024.

[7] J.Wu and X.Wang, “Research on the Mode of Specialized and Integrated Education in Colleges and Universities Based on the Perspective of Curriculum Ideology and Politics,” International Journal of Education and Humanities, vol.3, no.1, pp.66-69, 2022.

[8] H.Liu, J.Yu, H.Yu, X.Liu, N.Wang and H.Wu, “Talent Training Mode for Automation Specialty with Integration of Expertise and Innovative Thinking,” In 2023 China Automation Congress (CAC), pp. 6792-6795, 2023.

[9] Z.Wen, X.Cui and Y.Lu, “Build an Integrated Scene Teaching System for Additive Manufacturing Based on the Integration of Production and Education,” In SHS Web of Conferences , vol. 157, pp. 03022, 2023.

[10] J.Zhang, S.Bao and B.Luo, “Innovation and Practice of Collaborative Education Mode of Integration of Embedded Technology and Application Specialty,” In 2022 3rd International Conference on Modern Education and Information Management (ICMEIM 2022), pp. 263-271, 2022.

[11] W.Feng and X.Li, “Innovative application research on the combination of art design and engineering practice education under the background of new media,” International Journal of Electrical Engineering and Education, vol.60, no.2, pp.427-435, 2023.

[12] J.Bai, Z,Zhou, Z.Li, X.Yang and D.Wei, “Construction of non-traditional machining curriculum system for training innovative talents,” In 2022 International Conference on Engineering Education and Information Technology (EEIT), pp. 27-31, IEEE,2022.

[13] C.Yingdong, F.Yaru, L.Huan and H.Rui, “Research on the Innovation of Practical Training Teaching in Nursing Programs under the Perspective of Disciplines,”.

[14] C.X Mu, “Research on Talents Cultivation Model of Application-oriented Undergraduate in the Era of AI. In ICMEIM 2023: Proceedings of the 4th International Conference on Modern Education and Information Management, ICMEIM 2023, 2023, Wuhan, China, pp.190, 2023.

[15] I.DeCoito and L.KBriona, “Fostering an entrepreneurial mindset through project-based learning and digital technologies in STEM teacher education,” In Enhancing entrepreneurial mindsets through STEM education, pp.195-222, 2023.

[16] Z.Zang, J.Wang, Y.Wang, H.An, L.Li et al., “Practice and exploration of integrating industrial innovation and entrepreneurship with application-oriented talent cultivation a case study of bioengineering major,” Sch J Agric Vet Sci, vol.6, pp.75-79, 2022.

[17] Q.Jiang and C.Wu, “Research on the Talent Training Mode of Multi-dimensional Training, Multi-specialty Integration and Multi-layer Cooperation in Finance and Economic Majors,” In 2022 6th International Seminar on Education, Management and Social Sciences (ISEMSS 2022), pp. 629-635, 2022.

[18] Y.Wang and Y.Zhang, “Research on the Integrated Education Mode of High-tech Integration in Automobile Inspection and Maintenance Specialty,” Journal of Education, Humanities and Social Sciences, vol.12, pp.298-304, 2023.

[19] M.Weiqiang, L.Na, Y.Xinyan and H.Huanqing, “Exploration and Practice on Training Mode of Production, Teaching, Learning, Research and Application in Mechatronics under Background of New Engineering,” In 2022 International Conference on Creative Industry and Knowledge Economy (CIKE 2022), pp. 468-471, 2022.

[20] S.Li and G.Zhai, “Research on Teaching Reform of Machine Vision Course in ApplicationOriented University,” In 2023 4th International Conference on Education, Knowledge and Information Management (ICEKIM 2023), pp. 651-661, 2023.

[21] Y.Qian, “Research on the construction of a talent training mode for artificial intelligence specialty in local colleges and universities,” Journal of Contemporary Educational Research, vol.6, no.1, pp.1-6, 2022.

[22] S.Li, Y.Wang, X.Zhang, Z.Xia, Z.Wang and L.Gao, “Exploration on the training mode of Innovative Talents for Characteristic Engineering in Architectural Colleges Driven by the Integration of Industry, Teaching and Research,” International Journal of New Developments in Education, vol.4, no.4, pp.002E, 2022.