Empowering Knowledge: Design and Development of Expert Systems with Shell Programs

Year : 2024 | Volume : 11 | Issue : 02 | Page : 1 4
    By

    Manmeet Kaur Arora,

  • Sahil Lal,

  • Bhupinder Singh,

  1. Research Scholar, School of Law, Sharda University, Greater Noida, Uttar Pradesh, India
  2. Research Scholar, School of Law, Sharda University, Greater Noida, Uttar Pradesh, India
  3. Professor, School of Law, Sharda University, Greater Noida, Uttar Pradesh, India

Abstract

Even if one never intends to write scripts, mastery of shell scripting is an essential skill for anybody hoping to advance in system administration. For instance, a Linux computer uses the shell scripts to start services and restore system settings when it first boots up. Gaining an in-depth understanding of these starting scripts facilitates the analysis and possible optimization of system behavior. Because scripts may be written in short bursts and there are not many shell-specific operators and choices to learn, learning shell scripting is not too difficult. With only a few criteria to go by, the syntax is simple and evocative of chaining commands at the command line. Most simple programs launch immediately, and debugging lengthier scripts is not too hard. Early microcomputers could be programmed with basic computing abilities thanks to the BASIC language. This was the era of personal computing. These days, anyone with a little knowledge of Linux or UNIX can accomplish the same on contemporary systems thanks to the bash scripting language.

Keywords: Shell, bash scripting language, UNIX, technological trends, cloud computing, big data

[This article belongs to Journal of Advances in Shell Programming ]

How to cite this article:
Manmeet Kaur Arora, Sahil Lal, Bhupinder Singh. Empowering Knowledge: Design and Development of Expert Systems with Shell Programs. Journal of Advances in Shell Programming. 2024; 11(02):1-4.
How to cite this URL:
Manmeet Kaur Arora, Sahil Lal, Bhupinder Singh. Empowering Knowledge: Design and Development of Expert Systems with Shell Programs. Journal of Advances in Shell Programming. 2024; 11(02):1-4. Available from: https://journals.stmjournals.com/joasp/article=2024/view=153012


References

  1. Singh B, Kaunert C. Future of digital marketing: hyper-personalized customer dynamic experience with ai-based predictive models. In: Khang A, Dutta PK, Gupta S, Ayedee N, Chatterjee S, editors. Revolutionizing the AI-Digital Landscape: A Guide to Sustainable Emerging Technologies for Marketing Professionals. New York, NY, USA: Routledge; 2024. pp. 189–203.
  2. Gierlich-Joas M, Baiyere A, Hess T. Inverse transparency and the quest for empowerment through the design of digital workplace technologies. J Assoc Inform Syst. 2024. Preprint 131. doi: 10.17705/1jais.00879.
  3. Singh B, Kaunert C, Vig K. Reinventing influence of artificial intelligence (AI) on digital consumer lensing transforming consumer recommendation model: exploring stimulus artificial intelligence on consumer shopping decisions. In: Musiolik T, Rodriguez R, Kannan H, editors. AI Impacts in Digital Consumer Behavior. Hershey, PA, USA: IGI Global; 2024. pp. 141–169. doi: 10.4018/979-8-3693-1918-5.ch006.
  4. Bisessar R, Reid D. Designing Futures by Empowering Novice Designers. Master’s Thesis. Toronto, Ontario, Canada: OCAD University; 2024.
  5. Singh B, Kaunert C. Salvaging responsible consumption and production of food in the hospitality industry: harnessing machine learning and deep learning for zero food waste. In: Singh A, Tyagi PK, Garg A, editors. Sustainable Disposal Methods of Food Wastes in Hospitality Operations. Hersher, PA, USA: IGI Global; 2024. pp. 176–192.
  6. Yang B, Jiang S, Xu L, Liu K, Li H, Xing G, Chen H, Jiang X, Yan Z. DrHouse: an LLM-empowered diagnostic reasoning system through harnessing outcomes from sensor data and expert knowledge. arXiv preprint arXiv:2405.12541. Available at https://arxiv.org/abs/2405.12541.
  7. Guo L, Li X, Yan F, Lu Y, Shen W. A method for constructing a machining knowledge graph using an improved transformer. Expert Syst Appl. 2024; 237: 121448.
  8. Rani S, Srivastava G. Secure hierarchical fog computing-based architecture for industry 5.0 using an attribute-based encryption scheme. Expert Syst Appl. 2024; 235: 121180.
  9. Ali KA, Mohin SK, Mondal P, Goswami S, Ghosh S, Choudhuri S. Influence of artificial intelligence in modern pharmaceutical formulation and drug development. Future J Pharm Sci. 2024; 10 (1): Article 53.
  10. Dirik HF, Seren Intepeler S. An authentic leadership training programme to increase nurse empowerment and patient safety: a quasi‐experimental study. J Adv Nurs. 2024; 80 (4): 1417–1428.
  11. Alshahrani R, Yenugula M, Algethami H, Alharbi F, Goswami SS, Naveed QN, Lasisi A, Islam S, Khan NA, Zahmatkesh S. Establishing the fuzzy integrated hybrid MCDM framework to identify the key barriers to implementing artificial intelligence-enabled sustainable cloud system in an IT industry. Expert Syst Appl. 2024; 238: 121732.
  12. Froes P. Software Diagnosis as Intelligent Technologies in Industrial System Maintenance. TechRxiv. March 29, 2024. doi: 10.36227/techrxiv.171173911.11355438/v1.
  13. Mirchandani R. Empower to Enslave: Decoding Intentions for Product Design and Demand Forecasting. Partridge Publishing; 2024.
  14. Carpentras D, Hänggli R, Helbing D. Collective intelligence for democracy: empowering minorities and everyone in participatory budgeting. Preprint. May 18, 2024. doi: 10.2139/ssrn.4832498.
  15. Tonle FB, Niassy S, Ndadji MM, Tchendji MT, Nzeukou A, Mudereri BT, Senagi K, Tonnang HE. A road map for developing novel decision support system (DSS) for disseminating integrated pest management (IPM) technologies. Computers Electron Agric. 2024; 217: 108526.
  16. Yang Z, Zeng W, Jin S, Qian C, Luo P, Liu W. AutoMMLab: automatically generating deployable models from language instructions for computer vision tasks. arXiv preprint arXiv:2402.15351. Available at https://arxiv.org/abs/2402.15351
  17. Ma S, Chen Q, Wang X, Zheng C, Peng Z, Yin M, Ma X. Towards human-AI deliberation: design and evaluation of LLM-empowered deliberative AI for AI-assisted decision-making. arXiv preprint arXiv:2403.16812. Available at https://arxiv.org/abs/2403.16812
  18. Almatrafi O, Johri A, Lee H. A systematic review of AI literacy conceptualization, constructs, and implementation and assessment efforts (2019-2023). Computers Educ Open. 2024; 6: 100173.
  19. Abaku EA, Edunjobi TE, Odimarha AC. Theoretical approaches to AI in supply chain optimization: pathways to efficiency and resilience. Int J Sci Technol Res Arch. 2024; 6 (1): 92–107.
  20. Luu RK, Arevalo S, Lu W, Ni B, Yang Z, Shen SC, Berkovich J, Hsu YC, Zan S, Buehler MJ. Learning from nature to achieve material sustainability: generative AI for rigorous bio-inspired materials design. An MIT Exploration of Generative AI. March 27, 2024. doi: 10.21428/e4baedd9.33bd7449.
  21. Holst J, Grund J, Brock A. Whole institution approach: measurable and highly effective in empowering learners and educators for sustainability. Sustain Sci. 2024; 19: 1359–1376.
  22. Carminati JYJ, Holth K, Ponsford JL, Gould KR. Co-designing positive behaviour support (PBS + PLUS) training resources: a qualitative study of people with ABI, close-others, and clinicians’ experiences. Brain Impair. 2024; 25 (2): IB23060.
  23. Rowan W, McCarthy S, Mebrahtu S, Ertiö T, Dimova A, Asenova D, Moraitis N, Revez A. Promoting active citizen engagement in sustainable energy transitions: a co-creation approach. J Decis Syst. 2024: 1–12. doi: 10.1080/12460125.2024.2344872.
  24. Cantarero-Arevalo L, Kaae S, Jacobsen R, Nielsen A, Slyngborg L, Smistrup N, Kastrup LM, Hämeen-Anttila K, Strömberg A, Nørgaard LS. Empowering patients as co-researchers in social pharmacy: lessons learned and practical tips for meaningful partnership and impact. Res Soc Admin Pharm. 2024; 20 (3): 372–376.
  25. Bai Z, Fang Y, Chen H, Chen X, An N, Zhang M, Rui G, Jin J. Development of an evaluation tool for age-appropriate software in aging environments: a Delphi study. arXiv preprint arXiv:2402.03933. Available at https://arxiv.org/abs/2402.03933
  26. Hassan AE, Lin D, Rajbahadur GK, Gallaba K, Cogo FR, Chen B, Zhang H, Thangarajah K, Oliva GA, Lin J, Abdullah WM, Jiang ZM. Rethinking software engineering in the era of foundation models: a curated catalogue of challenges in the development of trustworthy FMware. arXiv preprint arXiv:2402.15943. Available at https://arxiv.org/abs/2402.15943
  27. Salimi-Bani M, Pandian V, Vahedian-Azimi A, Moradian ST, Bahramifar A. A respiratory critical care nurse training program for settings without a registered respiratory therapists: a protocol for a multimethod study. Intensive Crit Care Nurs. 2024; 82: 103662.
  28. Liu C, González VA, Lee G, Cabrera-Guerrero G, Zou Y, Davies R. Integrating the last planner system and immersive virtual reality: exploring the social mechanisms produced by using LPS in projects. J Construct Eng Manage. 2024; 150 (7): 04024070.
  29. Lachney M, Green B, Yadav A, Drazin M, Allen Kuyenga MC, Harris A. Sparring with technology: collaborating with coaches, mentors, and academic staff to develop culturally responsive computing education for a youth boxing program. Educ Technol Res Dev. 2024; 72: 1563–1595.
  30. Zhao T, Gasiba T, Lechner U, Pinto-Albuquerque M. Thriving in the era of hybrid work: raising cybersecurity awareness using serious games in industry trainings. J Syst Softw. 2024; 210: 111946.
  31. Indira R. Educational Design Recommendations to Improve the Training Programme for New Operators of Pyrolysis Plants. Master’s Thesis. Enschede, Netherlands: University of Twente; 2024. Available from https://essay.utwente.nl/98495/
  32. Huang R, Lin H, Chen C, Zhang K, Zeng W. PlantoGraphy: incorporating iterative design process into generative artificial intelligence for landscape rendering. In: Proceedings of the CHI Conference on Human Factors in Computing Systems, Honolulu, HI, USA, May 11–6, 2024. pp. 1–19.
  33. Liu WSK. Global leadership dynamics: refining executive selection in multinational corporations. J Knowledge Econ. 2024; 1–45. doi: 10.1007/s13132-024-01794-3.
Regular Issue Subscription Review Article
Volume 11
Issue 02
Received 30/04/2024
Accepted 15/05/2024
Published 04/07/2024
334

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