Global Journal of Multidisciplinary Sciences and Arts
type: channel
description: The Global Journal of Multidisciplinary Sciences and Arts is an internationally recognized Pakistan-based journal that is published by a well-known publisher of Pakistan GLOBAL ALLIANCE FOR SCIENTIFIC STUDIES. Global Journal of Multidisciplinary Sciences and Arts operates under a Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) It welcomes submissions from various disciplines. It is a peer-reviewed and open-access publication that aims to showcase high-quality original research, reviews, letters, and case reports in natural sciences, social sciences, applied sciences, formal sciences, arts, and related areas. Our goal is to improve the efficient dissemination of new research ideas and findings, enabling researchers to generate new knowledge, studies, and inventions that will serve as a valuable reference for the future. The Journal is affiliated with Global Alliance for Scientific Studies (SMC-Private) Limited Multan, Pakistan. Journal Description Journal Name Global Journal of Multidisciplinary Sciences and Arts ISSN Number 3078-2724 Editor in Chief Abdul Samad | Department of Animal Science Gyeongsang National University 501, Jinju-daero, Jinju-si, Gyeongsangnam-do Frequency a Half Year| June and Decemeber Research Scope Computer Science | Management | Veterinary | Mathematics | Agriculture | Engineering | Health
language: en
publication name: Global Journal of Multidisciplinary Sciences and Arts
items: From Raw Data to Actionable Insight: Innovations in Machine Learning and Predictive Modeling
items: Optimization of Power Systems Using AI: A Review of Modern Approaches
items: Automation and Smart Manufacturing in Medical Device Production
items: Intelligent Data Analytics: A Review of AI-Based Approaches
items: Recent Advances in Artificial Intelligence for Data Science: A Review
items: From Data to Decisions: AI-Driven Machine Learning in Modern Healthcare
items: Next-Generation Healthcare Informatics: The Role of Artificial Intelligence, Predictive Analytics, Block chain, and Secure Data Systems
items: Convergence of Artificial Intelligence, Block chain, and Predictive Analytics in Healthcare Informatics: Opportunities and Challenges
items: AI-Enabled Digital Healthcare Informatics: Cybersecurity, Block chain Technologies, Supply Chain Analytics, and Predictive Healthcare Intelligence
items: Future of Organic Chemistry in the Age of Artificial Intelligence
items: Quality and Efficiency in the Age of AI: A Review of Healthcare Informatics, Computer Science Innovations, Nanocarrier Drug Delivery, Cybersecurity, Food Production, and Lean Six Sigma
items: From Algorithms to AI: A Comprehensive Review of Core Concepts in Computer Science
items: Privacy, Policy, and Progress: Reviewing the Regulatory Landscape in Health Informatics
items: Digital Health Revolution: Wearables in Health Informatics
items: Harnessing AI for Product Design and Processing
items: Next-Generation Healthcare: How AI is shaping the Future of Healthcare Informatics
items: Advancing Healthcare through Artificial Intelligence: A Comprehensive Review of Machine Learning Applications in Health Informatics
items: Advancements and Integrative Approaches in Modern Healthcare: AI-Driven Health Informatics, Nanocarrier-Based Drug Delivery, Cybersecurity, and Lean Six Sigma Applications
items: Integrating AI in Healthcare, Health Informatics, and Food Production: Advances in Machine Learning, Nanocarrier Drug Delivery, Computational Methods, Cybersecurity, and Quality Assurance
items: Harnessing C–H Activation and Photoredox Catalysis in Organic Synthesis: A Contemporary Review
items: AI in Lean Six Sigma: A Review of Industrial Implementations, Benefits, and Barriers
items: Synergizing AI and Lean Six Sigma: A Comprehensive Review of Smart Quality Assurance Systems
items: Artificial Intelligence in Product Management: Driving Innovation and Market Success
items: Artificial Intelligence as a Catalyst for the Next Generation of Healthcare Innovation
items: AI in Manufacturing Quality Management: A Review of Techniques, Tools, and Industrial Adoption
items: Transforming Supply Chains: Innovations, Sustainability, and Resilience in the Modern Era
items: Modern Trends in Urdu Literature: A Brief Overview
items: Design and Control of a Ball and Beam Balancing Mechanism Using MATLAB/Simulink
items: Ethical Implications and Practical Applications of AI in Modern Healthcare
items: Cybercrime and Cybersecurity in the Age of AI: Exploring the Challenges and Opportunities Presented by ChatGPT

From Raw Data to Actionable Insight: Innovations in Machine Learning and Predictive Modeling
type: item
description: This review will examine how machine learning and predictive modeling can transform raw data into actionable insights. It outlines the main steps such as data preprocessing, feature engineering, algorithm development, and model evaluation. The paper analyzes fundamental and developed algorithms like regression, classification, deep learning, time series predictions, and ensemble algorithms. The practical implications of predictive analytics can be seen in numerous real-life applications across the healthcare, financial, marketing, and industry sectors. Issues like data quality, interpretability, scalability, and ethical issues are addressed. The emerging trends such as explainable AI, AutoML and real-time analytics are introduced with the focus on the increased significance of intelligent and data-driven decision-making systems.
subject: Articles
  topic: section
subject: Machine learning
  topic: keywords
subject: predictive modeling
  topic: keywords
subject: data preprocessing
  topic: keywords
subject: feature engineering
  topic: keywords
subject: deep learning
  topic: keywords
subject: predictive analytics
  topic: keywords
creator: A Singh
rights: Copyright (c) 2025 A Singh (Author) https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-04
publication date: 2026-05-04
starting page: 225
ending page: 252
doi: 10.70445/gjmdsa.2.2.2025.225-252

Optimization of Power Systems Using AI: A Review of Modern Approaches
type: item
description: This review paper reviews recent Artificial Intelligence (AI) techniques for power system optimization. It underscores the shortcomings of conventional approaches and stresses the importance of AI approaches such as machine learning, evolutionary algorithms, swarm intelligence and deep learning in addressing complex problems such as economic dispatch, unit commitment and optimal power flow. The research also explores applications for renewable energy, smart grids, and demand response. Challenges such as data quality, computational efficiency and interpretability are discussed. Emerging challenges include explainable AI, real-time operation, and hybrid approaches. In conclusion, AI improves efficiency, reliability, and sustainability of power systems.
subject: Articles
  topic: section
subject: AI
  topic: keywords
subject: Power system optimization
  topic: keywords
subject: Machine learning
  topic: keywords
subject: Renewable Energy
  topic: keywords
subject: Swarm Intelligence
  topic: keywords
subject: Deep learning
  topic: keywords
creator: Fawad Khan
rights: Copyright (c) 2025 Fawad Khan (Author) https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-01
publication date: 2026-05-01
starting page: 203
ending page: 224
doi: 10.70445/gjmdsa.2.2.2025.203-224

Automation and Smart Manufacturing in Medical Device Production
type: item
description: By improving precision, efficiency, and regulatory compliance, automation and smart manufacturing are changing the medical device production process. The review is based on the idea of the transformation of manual operations to Industry 4.0 systems featuring robotics, IoT, AI, and digital technologies. These enhancements enhance quality management, real-time monitoring, and support predictive maintenance and traceability. The advantages are increased productivity, cost reduction, increased safety and accelerated innovation. But there are still obstacles to overcome, including the cost of investments, cybersecurity concerns, and integration concerns. The upcoming tendencies such as AI-based automation, digital twins, and customized production are expected to bring additional innovations. These technologies are reshaping medical device manufacturing into a more intelligent and efficient system.
subject: Articles
  topic: section
subject: Automation
  topic: keywords
subject: Smart Manufacturing
  topic: keywords
subject: Medical Device Production
  topic: keywords
subject: Industry 4.0
  topic: keywords
subject: IoT
  topic: keywords
subject: AI
  topic: keywords
subject: Quality Control
  topic: keywords
creator: Mannan Mohammed
creator: Salman Kunnipurayil
rights: Copyright (c) 2025 Mannan Mohammed, Salman Kunnipurayil (Author) https://creativecommons.org/licenses/by-nc/4.0
date: 2026-04-18
publication date: 2026-04-18
starting page: 176
ending page: 202
doi: 10.70445/gjmdsa.2.2.2025.176-202

Intelligent Data Analytics: A Review of AI-Based Approaches
type: item
description: Intelligent Data Analytics (IDA) combines artificial intelligence with recent data processing algorithms to discover valuable insights out of big and complex data. The current review of the history of data analytics as the development of traditional statistical tools into modern AI-powered systems reveals the main concepts of machine learning, deep learning, data mining, and big data processing. It talks about major AI-based strategies, applications, tools, across industries, challenges, recent developments, comparative analysis and future trends. IDA enhances decision-making in healthcare, finance, business, cybersecurity, and IoT. With such obstacles as data quality, privacy, and interpretability, new developments keep enhancing efficiency, accuracy, and automation in analytics systems.
subject: Articles
  topic: section
subject: Intelligent Data Analytics
  topic: keywords
subject: AI
  topic: keywords
subject: Machine learning
  topic: keywords
subject: Deep learning
  topic: keywords
subject: Big data
  topic: keywords
subject: Predictive Analytics
  topic: keywords
subject: Data Mining
  topic: keywords
creator: Vidya Devi Oad
rights: Copyright (c) 2025 Vidya Devi Oad (Author) https://creativecommons.org/licenses/by-nc/4.0
date: 2026-04-16
publication date: 2026-04-16
starting page: 153
ending page: 175
doi: 10.70445/gjmdsa.2.2.2025.153-175

Recent Advances in Artificial Intelligence for Data Science: A Review
type: item
description: Artificial Intelligence (AI) has significantly changed the face of Data Science to the extent that analysis, prediction, and automation of various fields can occur at an advanced level. This review examines the fundamental concepts of AI, such as machine learning, deep learning, and natural language processing and its use in combination with data preprocessing, feature engineering, and model validation. The recent developments AutoML, big data analytics, generative AI and transformer-based models have expanded the capabilities of AI and have enhanced its efficiency, scalability, and usability. Healthcare, financial, marketing, and scientific applications create specific domains that can be seen to have tangible benefits, whereas the issues of data quality, interpretability, computational needs, and ethical issues have become critical. The directions of future research include transparency, flexibility, ethically friendly AI and incorporation with the latest technologies. On the whole, AI keeps reinventing Data Science and provides disruptive insights and solutions in any industry.
subject: Articles
  topic: section
subject: AI
  topic: keywords
subject: Data Science
  topic: keywords
subject: Machine learning
  topic: keywords
subject: Deep learning
  topic: keywords
subject: AutoML
  topic: keywords
subject: Big data
  topic: keywords
subject: Predictive Analytics
  topic: keywords
creator: Surdesh Kumar Oad
rights: Copyright (c) 2025 Global Journal of Multidisciplinary Sciences and Arts
date: 2026-04-01
publication date: 2026-04-01
starting page: 133
ending page: 152
doi: 10.70445/gjmdsa.2.2.2025.133-152

From Data to Decisions: AI-Driven Machine Learning in Modern Healthcare
type: item
description: Data-driven health care is being revolutionized by artificial intelligence (AI) and machine learning (ML). To inform clinical practice, AI uses electronic medical records, imaging and wearable’s to improve prediction, diagnosis, treatment and disease monitoring. ML (supervised, unsupervised, reinforcement and deep learning) enhances diagnosis, treatment and workflows. However, AI and ML in health care face issues such as privacy, bias, explain ability, regulatory and clinical practice. Explain ability, multimodal data integration and human-in-the-loop approaches can overcome these challenges to achieve safe, explainable and efficient AI-based medical care. Predictive, diagnostic and personalized medicine AI can transform care, outcomes and efficiency. Further research and ethical deployment will be crucial to unlocking the full potential of AI and ML in health care.
subject: Articles
  topic: section
subject: AI
  topic: keywords
subject: Machine learning
  topic: keywords
subject: Healthcare Data
  topic: keywords
subject: Predictive Analytics
  topic: keywords
subject: Personalized medicine
  topic: keywords
subject: clinical decision support
  topic: keywords
subject: ethical challenges
  topic: keywords
creator: Mehtab Jamal
creator: Muhammad Shahrukh Aslam
rights: Copyright (c) 2025 Global Journal of Multidisciplinary Sciences and Arts
date: 2026-03-28
publication date: 2026-03-28
starting page: 115
ending page: 132
doi: 10.70445/gjmdsa.2.2.2025.115-132

Next-Generation Healthcare Informatics: The Role of Artificial Intelligence, Predictive Analytics, Block chain, and Secure Data Systems
type: item
description: The blistering development of digital technologies has revolutionized healthcare informatics and permitted intelligent, safe, and data-driven systems. This review will examine how Artificial Intelligence (AI), Machine Learning, Predictive Analytics, Block chain, and secure data system have been integrated in the modern healthcare. The health care AI and Machine Learning enhance clinical decision-making, medical imaging analysis, and personalized treatment that determines patterns and predicts outcomes using extensive datasets. Predictive analytics help in proactive care of patients, risk management, and resource utilization. Tamper-proof management of data and interoperability are achieved with the help of block chain, whereas sensitive health information is secured by cybersecurity frameworks. These technologies, albeit with challenges including information quality, standards incompatibility, ethics, and the cost of implementation, all can be used to facilitate next generation, patient-centered, and efficient healthcare systems. The review identifies the existing applications, challenges and future trends and stresses on the opportunities offered by integrated electronic solutions to transform healthcare delivery, optimize patient outcomes, and operational efficiency.
subject: Articles
  topic: section
subject: AI
  topic: keywords
subject: Machine learning
  topic: keywords
subject: Predictive Analytics
  topic: keywords
subject: Healthcare Informatics
  topic: keywords
subject: Block chain technology
  topic: keywords
subject: Cybersecurity
  topic: keywords
subject: EHR
  topic: keywords
subject: Data analytics
  topic: keywords
creator: Mohammad Ali
rights: Copyright (c) 2025 Global Journal of Multidisciplinary Sciences and Arts
date: 2026-03-07
publication date: 2026-03-07
starting page: 84
ending page: 114
doi: 10.70445/gjmdsa.2.2.2025.84-114

Convergence of Artificial Intelligence, Block chain, and Predictive Analytics in Healthcare Informatics: Opportunities and Challenges
type: item
description: The integration of Artificial Intelligence (AI), block chain, and predictive analytics is revolutionizing healthcare informatics because these systems allow intelligent, secure, and data-driven systems. With the help of the AI, one can detect the correct diagnosis, clinical decision support, and make a specific treatment with the help of specific data analysis. Predictive analytics enable an active intervention, risk evaluation, and the efficient deployment of resources, whereas block chain can guarantee transparent, safe, and data exchange. The adoption of these technologies will result in improved patient care, efficiency, and the trust of the healthcare system. Their joint implementation has enormous possibilities of intelligent, patient-centered, and efficient healthcare systems despite their issues like data privacy, interoperability, and computational requirements as well as regulatory compliance that will define the future of digital health.
subject: Articles
  topic: section
subject: AI
  topic: keywords
subject: Block chain technology
  topic: keywords
subject: predictive analytics
  topic: keywords
subject: Healthcare
  topic: keywords
subject: Informatics
  topic: keywords
subject: data security
  topic: keywords
subject: Privacy
  topic: keywords
subject: Machine learning
  topic: keywords
subject: Healthcare data analytics
  topic: keywords
creator: Alexandra Harry
rights: Copyright (c) 2025 Global Journal of Multidisciplinary Sciences and Arts
date: 2026-03-04
publication date: 2026-03-04
starting page: 54
ending page: 83
doi: 10.70445/gjmdsa.2.2.2025.54-83

AI-Enabled Digital Healthcare Informatics: Cybersecurity, Block chain Technologies, Supply Chain Analytics, and Predictive Healthcare Intelligence
type: item
description: The fast digitalization of healthcare has provided enormous possibilities on how AI-enabled healthcare informatics can transform the care of patients, the efficiency of its operations, and decision-making. This review discusses the use of Artificial Intelligence, machine learning, block chain, cybersecurity, predictive analytics, and supply chain management in the contemporary healthcare systems. The use of AI and machine learning allows processing data intelligently, predicting diseases and treating patients individually, block chain and cybersecurity provide healthcare data management that is secure, transparent, and free from any manipulations. Proactive provision of healthcare and allocation of resources are improved with the help of predictive analytics and supply chain optimization. The review shows the following obstacles as data privacy, interoperability, ethical issues, and regulatory compliance, where responsible implementation is needed to develop secure, data-driven, and patient-centered healthcare ecosystems.
subject: Articles
  topic: section
subject: AI
  topic: keywords
subject: Machine learning
  topic: keywords
subject: Healthcare Informatics
  topic: keywords
subject: Cybersecurity
  topic: keywords
subject: Block chain
  topic: keywords
subject: Predictive Analytics
  topic: keywords
subject: Supply Chain Management
  topic: keywords
creator: George Edison
rights: Copyright (c) 2025 Global Journal of Multidisciplinary Sciences and Arts
date: 2026-03-01
publication date: 2026-03-01
starting page: 27
ending page: 53
doi: 10.70445/gjmdsa.2.2.2025.27-53

Future of Organic Chemistry in the Age of Artificial Intelligence
type: item
description: Organic chemistry is being reshaped by artificial intelligence (AI), which can be used to implement data-driven methods in the process of reaction prediction, retrosynthesis, molecular design, and process optimization. The patterns found by machine learning and deep learning models are used to accelerate chemical discovery, direct reaction conditions, and explore chemical space, based on large chemical datasets. Closed-loop experimentation can be provided by integrating with automation and self-driving laboratories, which enhances efficiency, reproducibility, and sustainability. Green chemistry is also aided by AI in reduction of waste and maximization of resources. In spite of these obstacles to information quality, meaning, and responsible application, AI is viewed as a complement to human knowledge and potentially transformative within the field of organic chemistry, which will become faster, more innovative, and greener in the next several decades.
subject: Articles
  topic: section
subject: AI
  topic: keywords
subject: Organic Chemistry
  topic: keywords
subject: reaction prediction
  topic: keywords
subject: retrosynthesis
  topic: keywords
subject: molecular design
  topic: keywords
subject: machine learning
  topic: keywords
subject: sustainability
  topic: keywords
creator: Javeriya Sayed
rights: Copyright (c) 2025 Global Journal of Multidisciplinary Sciences and Arts
date: 2025-12-01
publication date: 2025-12-01
starting page: 1
ending page: 26
doi: 10.70445/gjmdsa.2.2.2025.1-26

Quality and Efficiency in the Age of AI: A Review of Healthcare Informatics, Computer Science Innovations, Nanocarrier Drug Delivery, Cybersecurity, Food Production, and Lean Six Sigma
type: item
description: Computational technologies and artificial intelligence (AI) are revolutionizing the healthcare, food production, and biomedical research spheres through the increase of efficiency, quality, and optimization. This review discusses AI-controlled healthcare systems, health informatics, nanocarrier drug delivery, computational modeling, and cybersecurity and their role in diagnostics, patient care, and optimization of operations. Simultaneously, AI-based solutions in the agricultural sector, food production, and supply chain management enhance resource use and sustainability. The combination of the Lean Six Sigma and AI indicates quantifiable improvements in the efficiency of processes in the domains. Ethical, technical and regulatory issues are presented, focusing on the interdisciplinary cooperation and future research strategies on the way to the sustainable, intelligent, and high-quality systems.
subject: Articles
  topic: section
subject: AI
  topic: keywords
subject: Healthcare Informatics
  topic: keywords
subject: Nanocarrier
  topic: keywords
subject: drug delivery
  topic: keywords
subject: Cybersecurity
  topic: keywords
subject: lean six sigma
  topic: keywords
subject: predictive analytics
  topic: keywords
subject: process optimization
  topic: keywords
subject: sustainability
  topic: keywords
creator: Ali Husnain
rights: Copyright (c) 2025 Global Journal of Multidisciplinary Sciences and Arts
date: 2025-11-16
publication date: 2025-11-16
starting page: 84
ending page: 108
doi: 10.70445/gjmdsa.2.1.2025.84-108

From Algorithms to AI: A Comprehensive Review of Core Concepts in Computer Science
type: item
description: The review delves into the very ideas of Computer Science and constantly-developing fields, thoroughly reviewing the theoretical basis and the most modern technologies. The theory is started with basic concepts like algorithms, data structures and models of computation then moves to programming paradigms, architecture of computation, and operating systems. The explanations are carried out to its practical fields such as databases, networking, software engineering and artificial intelligence. Emerging fields like quantum computing, human-computer interaction, cloud and edge computing and ethical considerations are also outlined. Through the combination of fundamental knowledge and its application in the real world, the review highlights the cross-disciplinary purpose of Computer Science and its central role in innovation of the present times. The goal of this synthesis is to help learners, educators, and professionals learn the depth and relevance, as well as the future development direction of the field.
subject: Articles
  topic: section
subject: Algorithms
  topic: keywords
subject: AI
  topic: keywords
subject: Computer architecture
  topic: keywords
subject: Operating systems
  topic: keywords
subject: Programming paradigms
  topic: keywords
subject: quantum computing
  topic: keywords
subject: software engineering
  topic: keywords
creator: A singh
rights: Copyright (c) 2025 Global Journal of Multidisciplinary Sciences and Arts
date: 2025-07-29
publication date: 2025-07-29
starting page: 60
ending page: 83
doi: 10.70445/gjmdsa.2.1.2025.60-83

Privacy, Policy, and Progress: Reviewing the Regulatory Landscape in Health Informatics
type: item
description: Because of health informatics, digital systems can now gather, analyze and trade health information. Nevertheless, using new technologies such as electronic health records, artificial intelligence and telehealth brings up important issues related to data privacy, proper use and being controlled by rules. It reviews basic health informatics principles and studies international rules, like HIPAA and GDPR, pointing out the difficulties in fulfilling these rules and the need for similar regulations. It also deals with ethical issues about consent, who owns data and the bias found in algorithms, as well as rules that ensure both progress and responsibility. AI, block chain and remote monitoring have huge potential, but to avoid problems, strong guidelines should be adopted. The review underlines how adaptive and inclusive governance guarantees progress in health informatics by focusing on patients’ rights and technology at the same time.
subject: Articles
  topic: section
subject: Health Informatics
  topic: keywords
subject: Digital health governance
  topic: keywords
subject: HIPAA
  topic: keywords
subject: GDPR
  topic: keywords
subject: AI
  topic: keywords
subject: telehealth
  topic: keywords
subject: data security
  topic: keywords
creator: Mohammed Javeedullah
creator: Shah Zeb
rights: Copyright (c) 2025 Global Journal of Multidisciplinary Sciences and Arts
date: 2025-06-21
publication date: 2025-06-21
starting page: 44
ending page: 59
doi: 10.70445/gjmdsa.2.1.2025.44-59

Digital Health Revolution: Wearables in Health Informatics
type: item
description: Advancements in wearable technology have enabled health informatics to continuously monitor an individual’s health and behavior.The review looks at various wearables for consumers and medical use and how they support chronic disease management, monitoring patients from a distance, spotting diseases early, and personalized care. Wearable data can be added to health information systems so that healthcare professionals can improve decisions and offer preventive healthcare. Still, issues such as data accuracy, privacy, challenges with sharing information, and following regulations are making it difficult for more people to use Block chain. Innovations in sensors, AI, smart clothes, and handling data are expected to remove these problems and improve the accuracy, confidentiality, and user experience of wearables. Because of their continual advancements, wearables will have a greater impact on health informatics to help patients and support public health. It brings out how wearable technology can have a significant impact on healthcare and points out the main obstacles to using them successfully.
subject: Articles
  topic: section
subject: Wearable technology
  topic: keywords
subject: Health Informatics
  topic: keywords
subject: Remote Patient Monitoring
  topic: keywords
subject: AI
  topic: keywords
subject: Privacy and security
  topic: keywords
subject: Digital Health Revolution
  topic: keywords
creator: Mohammed Javeedullah
rights: Copyright (c) 2025 Global Journal of Multidisciplinary Sciences and Arts
date: 2025-06-08
publication date: 2025-06-08
starting page: 19
ending page: 43
doi: 10.70445/gjmdsa.2.1.2025.19-43

Harnessing AI for Product Design and Processing
type: item
description: This review brings forth the major changes that Artificial Intelligence is bringing to product design and manufacturing. Thanks to generative design, machine learning and computer vision, AI makes creativity, optimization and automation much easier in product development. In designing products, AI speeds up coming up with new ideas, testing ideas and meeting customer needs and in processing products, it raises the quality, helps prevent problems and automates several tasks in smart facilities. The writing covers the key aspects of artificial intelligence, important tools involved and recent advancements. While AI greatly helps, still, some obstacles, for instance, problems with data quality, mixing multiple systems, transparent explanations and ethical questions persist. After that, considerations are given to areas such as sustainable design, working together with AI and explainable AI, revealing how AI could lead to more advanced, efficient and ethical development of products. This overview proves useful for researchers, engineers and industry leaders who want to apply AI to succeed against competition.
subject: Articles
  topic: section
subject: AI
  topic: keywords
subject: Product design
  topic: keywords
subject: Product processing
  topic: keywords
subject: generative design
  topic: keywords
subject: Machine learning
  topic: keywords
subject: Smart manufacturing
  topic: keywords
creator: Muhammad Mohsin Kabeer
rights: Copyright (c) 2025 Global Journal of Multidisciplinary Sciences and Arts
date: 2025-06-06
publication date: 2025-06-06
starting page: 1
ending page: 18
doi: 10.70445/gjmdsa.2.1.2025.1-18

Next-Generation Healthcare: How AI is shaping the Future of Healthcare Informatics
type: item
description: The field of healthcare informatics is also being transformed by artificial Intelligence (AI), which allows conducting intelligent data analysis, predictive modeling, and automating clinical and administrative processes. This review discusses the underlying technologies in AI, such as machine learning and deep learning and natural language processing and computer vision, and their current applications in electronic health records, diagnostics, clinical decision support, and population health management. The combination of AI and healthcare infrastructure is associated with the opportunities of the personalized care, workflow optimization, and proactive approaches to the population health, as well as with ethical, legal, and operational issues. New developments in generative AI, digital twins, and autonomous systems point to a more efficient future being easier to achieve, patient-focused.
subject: Articles
  topic: section
subject: AI
  topic: keywords
subject: Healthcare Informatics
  topic: keywords
subject: Machine learning
  topic: keywords
subject: Clinical Decision
  topic: keywords
subject: Support
  topic: keywords
subject: Predictive Analytics
  topic: keywords
creator: Bimalendu Pendy
rights: Copyright (c) 2024 Global Journal of Multidisciplinary Sciences and Arts
date: 2024-12-15
publication date: 2024-12-15
starting page: 236
ending page: 254
doi: 10.70445/gjmdsa.1.2.2024.236-254

Advancing Healthcare through Artificial Intelligence: A Comprehensive Review of Machine Learning Applications in Health Informatics
type: item
description: Deep learning and other types of Artificial Intelligence (AI) are quickly changing the healthcare and health informatics landscape to allow deeper data analysis, predictive modeling, and customized care of patients. Convolutional and recurrent neural networks are examples of deep learning architecture that have demonstrated spectacular performance in medical imaging, disease prediction, drug discovery and telemedicine applications. Health informatics will ensure the required data collection, data storage, and integration structures that will ensure efficient and safe operation of AI models. The emerging techniques are mitigating these drawbacks despite the various problems posed by data quality, interpretability, ethical issues, and infrastructure needs. The review presents the existing innovations, uses, challenges, and prospects, focusing on the synergistic opportunities of AI and deep learning to transform the modern healthcare.
subject: Articles
  topic: section
subject: AI
  topic: keywords
subject: Deep learning
  topic: keywords
subject: Healthcare
  topic: keywords
subject: Health Informatics
  topic: keywords
subject: Medical Imaging
  topic: keywords
subject: Predictive Analytics
  topic: keywords
subject: Personalized Medicine
  topic: keywords
subject: Telemedicine
  topic: keywords
creator: Mohammad Ali
rights: Copyright (c) 2024 Global Journal of Multidisciplinary Sciences and Arts
date: 2024-12-15
publication date: 2024-12-15
starting page: 219
ending page: 235
doi: 10.70445/gjmdsa.1.2.2024.219-235

Advancements and Integrative Approaches in Modern Healthcare: AI-Driven Health Informatics, Nanocarrier-Based Drug Delivery, Cybersecurity, and Lean Six Sigma Applications
type: item
description: Healthcare industry has been experiencing revolutionary developments in the fields of artificial intelligence (AI), drug delivery using nanocarriers, cybersecurity, and Lean Six Sigma. The artificial intelligence-based health informatics improves the quality of diagnostics, predictive analytics, and individual therapy, and nanocarriers provide the delivery of drugs to specific tissue sites in a targeted and controlled manner, improving therapy effectiveness and minimizing side effects. At the same time, effective cybersecurity allows protecting sensitive patient data and medical systems, which promotes safe online healthcare activities. Lean Six Sigma streamlines operations, diminishes mistakes, and improves the efficiency of operations. This review identifies the synergistic prospects of these areas, current applications, challenges, and future prospects, and the overall thrust of these areas in delivering precise, efficient, and secure healthcare delivery.
subject: Articles
  topic: section
subject: AI
  topic: keywords
subject: Health Informatics
  topic: keywords
subject: Nanocarrier drug delivery
  topic: keywords
subject: Cybersecurity
  topic: keywords
subject: Lean Six Sigma
  topic: keywords
subject: Precision medicine
  topic: keywords
creator: Alexandra Harry
rights: Copyright (c) 2024 Global Journal of Multidisciplinary Sciences and Arts
date: 2024-12-14
publication date: 2024-12-14
starting page: 201
ending page: 218
doi: 10.70445/gjmdsa.1.2.2024.201-218

Integrating AI in Healthcare, Health Informatics, and Food Production: Advances in Machine Learning, Nanocarrier Drug Delivery, Computational Methods, Cybersecurity, and Quality Assurance
type: item
description: Artificial Intelligence (AI) is transforming the healthcare system, health informatics, drug delivery, and food production as it allows making predictions, tailored treatment and streamlining processes. This review discusses the combination of AI and machine learning, nanocarrier-based drug delivery, computational solution, cybersecurity, and quality assurance in these fields. In the healthcare sector, AI has improved diagnostics, treatment planning, and patient monitoring, whereas in the food production industry it is applied in precision agriculture, optimization of the supply chain, and safety monitoring. Data privacy, bias in algorithms, and compliance with regulations are the other issues that were discussed in the paper. Future looks indicate interdisciplinary innovations that may offer safer, effective and sustainable solutions in the health and nutrition.
subject: Articles
  topic: section
subject: AI
  topic: keywords
subject: Machine learning
  topic: keywords
subject: Nanocarrier drug delivery
  topic: keywords
subject: Health Informatics
  topic: keywords
subject: Food Production
  topic: keywords
creator: George Edison
rights: Copyright (c) 2024 Global Journal of Multidisciplinary Sciences and Arts
date: 2024-12-14
publication date: 2024-12-14
starting page: 178
ending page: 200
doi: 10.70445/gjmdsa.1.2.2024.178-200

Harnessing C–H Activation and Photoredox Catalysis in Organic Synthesis: A Contemporary Review
type: item
description: C–H activation and photoredox catalysis have become complementary and are leading to the synergistic integration into a new potent approach to modern organic synthesis that is highly selective, efficient, and sustainable in its ability to transform molecules. Site-selective functionalization of inert C-H bonds is achieved through C-H activation, and the formation of reactive radical intermediates in mild conditions under visible light is achieved through photoredox catalysis. Their combination enables two-catalytic processes, which provides the possibility to build new bonds and functionalize functional groups late, as well as bring complex molecules, such as natural products, pharmaceuticals, and heterocycles, into easy reach. Recent developments include the emphasis on environmentally friendly procedures, widening the range of substrates, and reaction design that is guided by calculations. This review has outlined key principles, mechanistic understanding, applications, challenges and emerging trends in this field of synthetic chemistry with particular focus on its transformative nature through this dual approach.
subject: Articles
  topic: section
subject: C-H activation
  topic: keywords
subject: Photoredox Catalysis
  topic: keywords
subject: Dual Catalysis
  topic: keywords
subject: visible light reactions
  topic: keywords
subject: late-stage functionalization
  topic: keywords
creator: Javeriya Sayed
rights: Copyright (c) 2024 Global Journal of Multidisciplinary Sciences and Arts
date: 2024-12-14
publication date: 2024-12-14
starting page: 159
ending page: 177
doi: 10.70445/gjmdsa.1.2.2024.159-177

AI in Lean Six Sigma: A Review of Industrial Implementations, Benefits, and Barriers
type: item
description: The present review addresses the concept of Artificial Intelligence (AI) integration in the methods of Lean Six Sigma (LSS), its industrial applications, advantages, and obstacles. The AI technologies like machine learning, predictive analytics, and computer vision can support LSS by facilitating real-time processing of data, forecasting decision-making, and optimization of processes. The paper presents the examples of successful applications in manufacturing, healthcare, services and logistics showing that the efficiency, quality and innovation are strongly improved. Nevertheless, the problems of data quality, cultural resistance, and lack of skills remain. The review concludes that AI-based LSS promotes smart and flexible and sustainable continuous improvement in line with Industry 4.0 and beyond.
subject: Articles
  topic: section
subject: AI
  topic: keywords
subject: Lean Six Sigma
  topic: keywords
subject: process optimization
  topic: keywords
subject: predictive analytics
  topic: keywords
subject: Industry 4.0
  topic: keywords
subject: Continuous improvement
  topic: keywords
creator: Muhammad Mohsin Kabeer
rights: Copyright (c) 2024 Global Journal of Multidisciplinary Sciences and Arts
date: 2024-12-13
publication date: 2024-12-13
starting page: 134
ending page: 158
doi: 10.70445/gjmdsa.1.2.2024.134-158

Synergizing AI and Lean Six Sigma: A Comprehensive Review of Smart Quality Assurance Systems
type: item
description: This review examines how Artificial Intelligence (AI) can be integrated with Lean Six Sigma (LSS) in making intelligent and data-driven Quality Assurance (QA) systems. The new AI technology can complement the old LSS techniques by adding predictive analytics, automation, and optimization of processes at any moment, allowing to control the quality pro-actively and constantly improve the processes. The article discusses the important uses, advantages, issues and future of AI-driven Lean Six Sigma within the contemporary industries. The results indicate that AI is highly useful in enhancing the accuracy, efficiency, and decision-making in the DMAIC framework; in addition, it corresponds to the Industry 4.0 and 5.0 paradigms. The paper concludes that AI-enhanced LSS can be taken as a radical change to smarter, adaptive, and sustainable quality management systems.
subject: Articles
  topic: section
subject: AI
  topic: keywords
subject: Lean Six sigma
  topic: keywords
subject: Quality assurance
  topic: keywords
subject: Predictive Analytics
  topic: keywords
subject: Automation
  topic: keywords
subject: Continuous Improvement
  topic: keywords
subject: Industry 4.0
  topic: keywords
subject: Smart Manufacturing
  topic: keywords
creator: Muhammad Mohsin Kabeer
rights: Copyright (c) 2024 Global Journal of Multidisciplinary Sciences and Arts
date: 2024-12-12
publication date: 2024-12-12
starting page: 113
ending page: 133
doi: 10.70445/gjmdsa.1.2.2024.113-133

Artificial Intelligence in Product Management: Driving Innovation and Market Success
type: item
description: The use of Artificial Intelligence (AI) in product management is changing very fast, as it allows making decisions based on data, optimizing processes, and introducing novel solutions. This review examines how AI can be used throughout the product lifecycle including market research, product strategy, development and project management. Using AI, predictive analytics, customer insights, allocation of resources, and risk assessment are increased, making AI more efficient, personalized, and time-to-market. Although it has considerable benefits, the issues that may arise when adopting AI include problems with data quality, ethical aspects, and complexities with integrations, as well as adapting the workforce. The review shows industry case studies and trends, with an accent on the possibility of strategic, responsible AI implementation to drive innovation, improve performance of the products and provide market success with the time of growing competition of the business world.
subject: Articles
  topic: section
subject: AI
  topic: keywords
subject: Product management
  topic: keywords
subject: Innovation
  topic: keywords
subject: Predictive analytics
  topic: keywords
subject: customer insights
  topic: keywords
subject: project management
  topic: keywords
subject: decison-making
  topic: keywords
subject: market sucess
  topic: keywords
creator: Muhammad Shahrukh Aslam
rights: Copyright (c) 2024 Global Journal of Multidisciplinary Sciences and Arts
date: 2024-12-12
publication date: 2024-12-12
starting page: 88
ending page: 112
doi: 10.70445/gjmdsa.1.2.2024.88-112

Artificial Intelligence as a Catalyst for the Next Generation of Healthcare Innovation
type: item
description: The application of Artificial Intelligence (AI) in healthcare is changing the industry, making it more precise, efficient, and personalized in the care of patients. This review examines the history, underlying technologies, and various uses of AI in diagnostics, treatment plan, and healthcare management. It emphasizes the significant advantages, which are better diagnostic accuracy, predictive medicine, and the efficiency of its operation, and problems in ethics, law, and social issues, which include data privacy, biases, and responsibility. The paper is also focused on the existing constraints and opportunities with a particular emphasis on the transition to explainable, equitable, and human-centered AI systems. AI is an effective innovation driver that can influence a smarter, more equitable and compassionate future of healthcare.
subject: Articles
  topic: section
subject: Machine learning
  topic: keywords
subject: healthcare innovation
  topic: keywords
subject: AI
  topic: keywords
subject: Predictive analytics
  topic: keywords
subject: Deep learning
  topic: keywords
subject: Ethical Issues
  topic: keywords
subject: Digital health
  topic: keywords
creator: Muhammad Fahad
creator: Mazhar Farooq
creator: Shah Zeb
rights: Copyright (c) 2024 Global Journal of Multidisciplinary Sciences and Arts
date: 2024-12-12
publication date: 2024-12-12
starting page: 65
ending page: 87
doi: 10.70445/gjmdsa.1.2.2024.65-87

AI in Manufacturing Quality Management: A Review of Techniques, Tools, and Industrial Adoption
type: item
description: It is true that Artificial Intelligence (AI) is fast transforming the quality management of manufacturing services by providing smarter, data-driven solutions to detect defects in manufacturing processes, optimize processes and provide predictive maintenance. Conventional approaches to quality assurance are easily surpassed by complex data and dynamic production contexts, whereas AI-based technologies, including machine learning, deep learning, computer vision, and reinforcement learning, demonstrate increased accuracy, scale and flexibility. This review discusses the principles of AI in quality management, its major technologies, tools, and implementation in Industry 4.0 ecosystems. It also emphasizes industry adoption in the automotive, electronic, pharmaceutical and aerospace sectors and discusses the issues of data quality, implementation cost, employee preparation and readiness and interpretability. The trends of the future focus on explainable AI, sustainable manufacturing and human-AI cooperation. In contemporary manufacturing AI is offering radical possibilities of attaining better quality management that is efficient, reliable, and sustainable.
subject: Articles
  topic: section
subject: AI
  topic: keywords
subject: Quality management
  topic: keywords
subject: Manufacturing
  topic: keywords
subject: ML
  topic: keywords
subject: Deep learning
  topic: keywords
subject: Computer Vision
  topic: keywords
subject: Industry 4.0
  topic: keywords
subject: Predictive maintenance
  topic: keywords
subject: Digital twins
  topic: keywords
creator: Muhammad Mohsin Kabeer
rights: Copyright (c) 2024 Global Journal of Multidisciplinary Sciences and Arts
date: 2024-12-11
publication date: 2024-12-11
starting page: 46
ending page: 64
doi: 10.70445/gjmdsa.1.2.2024.46-64

Transforming Supply Chains: Innovations, Sustainability, and Resilience in the Modern Era
type: item
description: Supply chain management continues to transform at present because of technological innovations together with environmental sustainability goals and market demands for operational stability in an unstable worldwide system. Supply chain operations experience revolutionary changes through key trends which include automation with artificial intelligence (AI) and machine learning and the Internet of Things (IoT) that improve efficiency and help make better decisions and provide enhanced visibility. Both Block chain technology improves system transparency and security while digital twins achieve real-time monitoring operations which optimize supply chain process functions. Sustainability stands as the new core priority alongside which companies now devote their resources to establishing sustainable sourcing methods and reducing waste and increasing energy operational efficiency. Business operations focus on resilience together with risk management because companies implement adaptable supply chains that can withstand multiple types of disruptions including geopolitical tensions and natural disasters and unexpected threats. Supply chains of the future will evolve under current scientific innovations while maintaining their emphasis on agile structures and circular economy practices. Firms adopting these trends will better satisfy shifting customer needs and operate with improved efficiency through a global market that requires competitiveness. The abstract details crucial supply chain-transforming trends and disruptive innovations alongside their effects on businesses that plan to succeed in developing complicated market conditions.
subject: Articles
  topic: section
subject: Automation
  topic: keywords
subject: Robotics
  topic: keywords
subject: AI
  topic: keywords
subject: ML
  topic: keywords
subject: IoT
  topic: keywords
subject: Block chain
  topic: keywords
subject: Circular economy
  topic: keywords
subject: Agile supply chains
  topic: keywords
creator: Abdul Ahad
creator: Muhammad Rehan Ashraf
creator: Khizar Ilyas
creator: Benish Sarfraz
rights: Copyright (c) 2024 Global Journal of Multidisciplinary Sciences and Arts
date: 2024-12-10
publication date: 2024-12-10
starting page: 46
ending page: 74
doi: 10.70445/gjmdsa.1.2.2024.46-74

Modern Trends in Urdu Literature: A Brief Overview
type: item
description: The contemporary Urdu literary world unites classic heritage with novel emotional content through innovative structural forms. This research project checks vital shifts within contemporary Urdu literature while assessing how progressive writers embraced social justice discussion through protests against repressive practices. Following independence Urdu writers conducted significant investigations into partition trauma through the study of dislocation effects and culture separation together with identity matters. New counting patterns and literary building approaches emerged as fundamental elements in contemporary Urdu literature because authors utilize these elements to express the realities of current times. Publisher and artist women use feminist works to confront patriarchal social structures and express themselves forcefully across poetry and prose forms. Through their literary contributions Ismat Chughtai joined by Qurratulain Hyder and Faiz Ahmed Faiz shaped novel trends in Urdu literature that delved into political events and gender analyses with human experiential study. The combination of worldwide integration and digital platforms has widened Urdu literature's reading audience base while maintaining original language roots to allow writers global literary exposure. Leaving behind social critique and political examination Urdu literature maintains both its academic relevance and cultural depth.
subject: Articles
  topic: section
subject: Urdu literature
  topic: keywords
subject: Post-independence
  topic: keywords
subject: identity
  topic: keywords
subject: experimentation
  topic: keywords
subject: Feminist literature
  topic: keywords
subject: social realism
  topic: keywords
subject: Urdu poetry
  topic: keywords
creator: Jamal Khan
creator: Zeenat Bibi
rights: Copyright (c) 2024 Global Journal of Multidisciplinary Sciences and Arts
date: 2024-12-10
publication date: 2024-12-10
starting page: 35
ending page: 45
doi: 10.70445/gjmdsa.1.2.2024.35-45

Design and Control of a Ball and Beam Balancing Mechanism Using MATLAB/Simulink
type: item
description: This report begins with an introduction to a ball and beam balancing mechanism. Basic electronic components and transmission mechanisms are also discussed which is then linked to mathematical calculations. An in-depth dynamic model of ball is presented which includes basic dynamic equations derived from newton’s laws of motions and lagrangian approach. However, lagrangian approach is used throughout to model system on a computer. Matlab/simulink was used to generate system output by employing a pid controller and a lead compensator. Root locus method was used to design a lead compensator. Lead compensator designed was also used with simulink model of the system to achieve desired system output. Output generated from each control strategy successfully satisfied the design criteria i.e. Percentage overshoot to be less than 5% and settling time to be less than 3 seconds.
subject: Articles
  topic: section
subject: Ball and beam balancing mechanism
  topic: keywords
subject: dynamic modeling
  topic: keywords
subject: lagrangian approach
  topic: keywords
subject: newtons's law of motion
  topic: keywords
subject: PID controller
  topic: keywords
subject: Lead compensator
  topic: keywords
subject: root locus method
  topic: keywords
subject: MATLAB
  topic: keywords
subject: Control strategies
  topic: keywords
subject: system output
  topic: keywords
subject: percentage overshoot
  topic: keywords
subject: setting time
  topic: keywords
creator: Syed Muhammad Asif
rights: Copyright (c) 2024 Global Journal of Multidisciplinary Sciences and Arts
date: 2024-12-01
publication date: 2024-12-01
starting page: 1
ending page: 34
doi: 10.70445/gjmdsa.1.2.2024.1-34

Ethical Implications and Practical Applications of AI in Modern Healthcare
type: item
description: AI is capable of solving many problems in the contemporary healthcare systems, and its application is likely to enhance the diagnostic process, choose individual treatment plans, enhance the level of patient satisfaction and enhance the organization of the delivery of healthcare. Techniques of machine learning and natural language processing based on AI have revealed their efficiency for diagnosing the illness, getting the positive results and client’s oriented recommendations concerning treatment of diseases. Nonetheless, the advancement and use of AI technologies in healthcare brings to the table several innuendos: privacy; security; data control and dissemination; responsibility and prejudice. Luckily however, addressing these challenges needs not only good and advisable policies and guidelines but also cooperation among policy makers, ethicists, technology and health care providers /researchers etc. The purpose of this review is to identify the most common ethical concern regarding the application of AI in health care and the results of practical efforts. It escalates how AI could vary from altering diagnosis approaches, enhancing therapies, controlling documents to raising stress on consumer’s details and securing that those leveraging artificial intelligence act morally and brightly. But the process of getting there into the era of benefit realization from this new technology will open more ideas and details into risks such as bias inference in AI models, patient’s consent and agency, and accessibility of AI technologies in developing countries and remote areas. In conclusion it will be necessary to be purposely reasonable, to be conscious and very communicative in order to introduce AI into better and convenient and humane healthcare.
subject: Articles
  topic: section
subject: AI in healthcare
  topic: keywords
subject: Diagnostic improvements
  topic: keywords
subject: treatment customization
  topic: keywords
subject: data issues as storage
  topic: keywords
subject: security
  topic: keywords
subject: analysis
  topic: keywords
subject: ethical concerns
  topic: keywords
subject: employing AI for prediction
  topic: keywords
subject: healthcare factors
  topic: keywords
subject: staff training
  topic: keywords
subject: precision healthcare
  topic: keywords
subject: accountability
  topic: keywords
subject: Healthcare
  topic: keywords
subject: Disparties
  topic: keywords
subject: Robotic function
  topic: keywords
subject: AI transparency
  topic: keywords
subject: legal implications
  topic: keywords
creator: Abdul Mannan Khan Sherani
creator: Murad Khan
rights: Copyright (c) 2024 Global Journal of Multidisciplinary Sciences and Arts
date: 2024-08-01
publication date: 2024-08-01
starting page: 142
ending page: 164
doi: 10.70445/gjmdsa.1.1.2024.142-164

Cybercrime and Cybersecurity in the Age of AI: Exploring the Challenges and Opportunities Presented by ChatGPT
type: item
description: One of the most hopeful trends in cybersecurity specialization is the utilization of artificial intelligence (AI) in the anti-cybersecurity movement, which provides specialists with rather elaborate tools to identify, thwart, and respond to newer, and more diverse, digital threats. While AI programs compliment traditional approaches of the identification of cyber threat and other measures, the former stands advantages in the way it can pin-point future threats and act on them. Nevertheless, as the usage of AI grows so does new threats emerge; first of all, AI is hackable which means that it can be used by offenders, thus the threats are consistently evolving exist. In this work the author also described more important role of AI in cyber space for both defense and offense. The FCA has indeed eyed the regulations and governance aspect as being at the heart of the ethical AI, privacy issue and reporting. In order to avoid the situation when security is dominated by technology, and within cyberspace threats are solved cooperatively at the international level, there is an appeal to open, non-discriminatory, and constantly developing architecture. It is anticipated that new trends, such as self-managing systems, computational prognostication, self-healing models, will emerge in the sphere of cybersecurity using AI, however, it is necessary to mention that this field has to be applied at the right level due to potential unfavorable outcomes. Finally, the achievement of a synergy in artificial intelligence alongside human decision-making will create robust digital environments that this author shall use towards the safe development of the new technology alongside the fight against emergent cybercrime challenges.
subject: Articles
  topic: section
subject: AI
  topic: keywords
subject: Cybersecurity
  topic: keywords
subject: Cyber threats
  topic: keywords
subject: Big data
  topic: keywords
subject: Policy
  topic: keywords
subject: ethic AI
  topic: keywords
subject: Data privacy
  topic: keywords
subject: responsibility
  topic: keywords
subject: Probabilistic approaches
  topic: keywords
subject: autonomous system
  topic: keywords
subject: threat
  topic: keywords
subject: cooperation
  topic: keywords
subject: international
  topic: keywords
subject: self-correcting system
  topic: keywords
subject: protection
  topic: keywords
subject: AI military
  topic: keywords
subject: Ai warfare
  topic: keywords
subject: ethic
  topic: keywords
subject: openness
  topic: keywords
subject: regulation
  topic: keywords
subject: digital
  topic: keywords
creator: Noman Abid
rights: Copyright (c) 2024 Global Journal of Multidisciplinary Sciences and Arts
date: 2024-08-01
publication date: 2024-08-01
starting page: 111
ending page: 141
doi: 10.70445/gjmdsa.1.1.2024.111-141