International Journal of Multidisciplinary Global Research
type: channel
description: The International Journal of Multidisciplinary Global Research with Online ISSN 3107-4197 is a peer-reviewed, open-access academic journal dedicated to advancing innovative, cross-disciplinary research on global challenges. It provides a platform for scholars, practitioners, and thought leaders from diverse fields—social sciences, humanities, natural sciences, business, and technology—to exchange insights, foster collaboration, and contribute to sustainable solutions. This Journal encourages submissions that transcend traditional boundaries, promoting integrative approaches to complex issues such as climate change, global health, social equity, economic development, and digital transformation. The journal aims to address the interconnected nature of the problems and support a deeper understanding of emerging trends by publishing original research articles, case studies, and critical reviews. With a commitment to fostering inclusivity, this journal welcomes contributions from scholars worldwide, ensuring diverse perspectives that resonate across academia, policy-making, and industry. The three regular issues of the International Journal of Multidisciplinary Global Research could reflect thematic focuses or align with evolving global priorities yearly. Research and Emerging Trends This section focuses on groundbreaking research, new technologies, and innovative practices across disciplines that shape the future. Topics include digital transformation, artificial intelligence, biotech advancements, and novel interdisciplinary approaches. Global Challenges and Solutions This section addresses pressing global issues, including climate change, public health crises, geopolitical tensions, and sustainable development. It emphasizes actionable research and collaborative strategies to address societal, economic, and environmental challenges. Cultural Perspectives and Social Change This section highlights the role of culture, ethics, and social dynamics in a globalized world. I…
publisher: Intuitivo Gateway Ricerca Fatti Private Limited (IGRF Pvt. Ltd.)
language: en
publication name: International Journal of Multidisciplinary Global Research
issn: 3107-4197
copyright: IJMGR License
items: Modern Sports Analytics using Big Data
items: Object Detection Employing YOLOv8 in Conjunction with a Custom Dataset
items: Transforming Education through Cloud Technologies: A Review of Accessibility Challenges and Solutions
items: Automated Interview Scoring (AIS) by Integrating Wordnet with NLTK
items: Equity by Design: Harnessing AI TRiSM for Socially Responsible Innovation
items: Advanced In-Depth Literature Review on Intrusion Detection Systems
items: The Impact of Artificial Intelligence on Cultural Practices and Communication
items: Enhancing Digital Identity Verification and Content Rights Management with AI and Blockchain Using SVMs
items: https://ijmgr.igrf.co.in/index.php/ijmgr/article/view/14
items: The Campus Pay: Offline Payment System Using RFID Technology for Campus Transactions
items: Advancing Stock Price Forecasting: Exploring Methods, Models & Literature
items: YOLO-Based Framework for Detecting Suspicious Activities in ATMs
items: The Applications of AI in Smart Technologies and Manufacturing
items: The Hacker Eye
items: Chain Craft: Crafting the Future of Supply Chains with IoT and Blockchain Brilliance
items: DNA and KAMLA Approaches in Metamorphic Cryptography: An Evaluation
items: Supervised Learning used for Clinical Decision Support System
items: Bioengineered Neural Interfaces for Improved Brain-Computer Interactions
items: Global Environmental Imbalance: Gen Z Behavior and Social Responsibilities

Modern Sports Analytics using Big Data
type: item
description: The realm of sports is experiencing a dramatic transformation, driven by the assimilation of extensive data analysis. The enthusiasm from both scholars and industry professionals regarding the utilization of big data analytics (BDA) in athletics has surged significantly, leading to heightened demand for innovative research, development, and exploration of new methodologies. This review introduces a framework that encapsulates the current literature on the applications and impact of analytics within the sports sector. The studies evaluated in this paper utilize a variety of methods to assess and enhance athlete performance, including the creation of a player ranking system, visual assessments to pinpoint movement patterns, and the examination of numerical data during critical moments of the match. This review explores how big data analytics is revolutionizing player performance assessment, injury mitigation, training enhancement, and fan interaction. Key research publications are analyzed to offer a comprehensive perspective on the advantages and limitations of big data analytics in athletics. Additionally, potential future research directions are highlighted, emphasizing the significant opportunities within this field.
subject: Articles
  topic: section
subject: Apr - Jun 2025 (Vol.2, Iss.2, 2025)
  topic: category
subject: Analytics
  topic: keywords
subject: Big Data
  topic: keywords
subject: Data Analytics
  topic: keywords
subject: Data-Driven Decision-Making
  topic: keywords
subject: Sports Analytics
  topic: keywords
creator: Rais Abdul Hamid Khan
creator: YOGESH K. SHARMA
creator: MOHINI GURAV
creator: PRANALI JADHAV
rights: Copyright (c) 2025 International Journal of Multidisciplinary Global Research https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-06-29
publication date: 2025-06-29
starting page: 45
ending page: 51

Object Detection Employing YOLOv8 in Conjunction with a Custom Dataset
type: item
description: In a variety of applications, including surveillance and safety systems, object detection is a very important characteristic. The objective of this study is to apply the sophisticated object identification model known as YOLOv8 to a particular dataset that has been developed for emergency collision avoidance systems specifically. For the purpose of conforming to the format specifications of YOLOv8, the dataset was painstakingly hand-labeled and polished. It included components such as autos, pedestrians, and barriers in a variety of situations. In order to improve the efficiency of the model, supplementary data and transfer learning strategies were applied. According to the results of the experiments, the model achieves a mean average precision (mAP) of [0.43], which demonstrates both its accuracy and efficiency. The ability of the device to detect potential threats in real-time may make it possible for it to be included in complete safety systems. For the purpose of optimizing real-time processing, additional modifications will be investigated in subsequent research, and the concept will be applied to edge devices.
subject: Articles
  topic: section
subject: Apr - Jun 2025 (Vol.2, Iss.2, 2025)
  topic: category
subject: Bounding Box
  topic: keywords
subject: Data Augmentation
  topic: keywords
subject: Data Preprocessing
  topic: keywords
subject: Dataset Splitting (train/test/validation)
  topic: keywords
subject: Object classes
  topic: keywords
creator: Abdulkayyum fakirmohammad
creator: RAIS ABDUL HAMID KHAN
creator: YOGESH K. SHARMA
creator: MOHINI GURAV
creator: SAURABH PARDESHI
rights: Copyright (c) 2025 International Journal of Multidisciplinary Global Research https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-06-29
publication date: 2025-06-29
starting page: 52
ending page: 63

Transforming Education through Cloud Technologies: A Review of Accessibility Challenges and Solutions
type: item
description: Cloud-based solutions have emerged as key instruments for transforming education worldwide. As cloud computing technology keeps growing, more institutions offer courses through these means for their teaching and learning process. The scalability, flexibility, and affordability of this technology ensure that more people can access it to achieve education. This paper discusses how these cloud-based platforms are shaping the future of education, based on their advantages and challenges, and the implications on the development of an interactive, personalized, and collaborative learning environment. Further, it addresses the security, privacy, and infrastructure challenges related to the adoption of cloud solutions in education and talks about the future of education in a cloud-centric world. The introduction of cloud-based solutions is creating a revolution in education across the globe in newer and exciting ways. Increasingly, cloud computing technologies offer alternatives to the way in which businesses and students learn. Such technologies are providing increased education options through affordability, scalable operations, and flexibility. This research endeavors to explore the transformative essence of cloud platforms towards shaping the future of education, throwing light on their merits and demerits along with implications in making learning interactive, personalized and collaborative. Apart from that, it addresses creation of cloud services implementation in education in conjunction with security and privacy aspects. Finally, the impact of cloud computing may change the dimensions of education in terms of its wide adoption.
subject: Articles
  topic: section
subject: Apr - Jun 2025 (Vol.2, Iss.2, 2025)
  topic: category
subject: Cloud-based Solutions, Cloud Computing
  topic: keywords
subject: Cost-Effective Solution
  topic: keywords
subject: Flexible Solution
  topic: keywords
subject: Next-Generation Education
  topic: keywords
subject: Scalable
  topic: keywords
creator: Rais Abdul Hamid Khan
creator: YOGESH K. SHARMA
creator: MOHINI GURAV
creator: ABDULKAYYUM SHAIKH
rights: Copyright (c) 2025 International Journal of Multidisciplinary Global Research https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-06-29
publication date: 2025-06-29
starting page: 64
ending page: 77

Automated Interview Scoring (AIS) by Integrating Wordnet with NLTK
type: item
description: Manual rating of autobiographical interviews, the essence of the assessment of autobiographical memory in psychology, is a labour-intensive and time-consuming task. Here, narrative details have to be rated by human raters, that is, classified as internal (episodic) or external (non-episodic), which limits the scalability of such research efforts critically. This project looks at the application of NLP methods for automating the rating process. The objective of this research is to fine-tune a language model such as distilBERT toward the end of making its usage more efficient and relieving part of the burden from researchers without compromising the precision in content classification. The project further assesses the reliability of the automated system across various datasets and determines whether its general structure may present possible futures for advancing research in autobiographical memory. All these developments work towards focusing on efficient and scalable NLP tools development for mainstream psychological use.
subject: Articles
  topic: section
subject: Apr - Jun 2025 (Vol.2, Iss.2, 2025)
  topic: category
subject: Automated Interview Scoring
  topic: keywords
subject: Episodic Memory
  topic: keywords
subject: Interview Scoring
  topic: keywords
subject: NLTK
  topic: keywords
subject: Non Episodic Memory
  topic: keywords
subject: Wordnet
  topic: keywords
creator: Siddharth Machhindra Chavan
creator: RAIS ABDUL HAMID KHAN
creator: YOGESH K. SHARMA
creator: MOHINI GURAV
creator: ABDULKAYYUM SHAIKH
rights: Copyright (c) 2025 International Journal of Multidisciplinary Global Research https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-06-29
publication date: 2025-06-29
starting page: 01
ending page: 12

Equity by Design: Harnessing AI TRiSM for Socially Responsible Innovation
type: item
description: The rapid expansion of artificial intelligence (AI) into socially sensitive domains such as healthcare, education, energy, and finance has intensified calls for innovation that foregrounds equity, accountability, and public trust. This article advances the framework of "Equity by Design," demonstrating how AI TRiSM—Trust, Risk, and Security Management—can be strategically harnessed to centre social responsibility throughout the lifecycle of AI systems. Synthesizing findings across human-computer interaction, policy studies, and algorithmic ethics, we argue that achieving truly equitable AI requires more than technical post-processing or regulatory compliance; it demands intentional, participatory design processes that embed trustworthiness, stakeholder engagement, and risk mitigation from inception. Drawing from empirical research, we examine how dimensions of trust—spanning statistical reliability, explainability, and user-centred design—directly influence the acceptance, calibration, and societal impact of AI technologies. We further elaborate on the necessity of preemptively identifying and addressing ethical risks such as bias, discrimination, and technological uncertainty through comprehensive socio-technical assessments, highlighting mechanisms by which risk governance can avert social harms and amplify AI’s positive outcomes. The article presents cross-sectoral case analyses to illustrate actionable pathways for operationalizing AI TRiSM, including participatory auditing, transparent explanation interfaces, and adaptive governance strategies tailored to diverse social and regulatory contexts. Ultimately, we contend that "Equity by Design"—anchored in the rigorous application of AI TRiSM—constitutes a transformative paradigm for innovation, empowering organizations and policymakers to embed justice, inclusivity, and sustainable trustworthiness into the fabric of emerging AI systems. By bridging technical rigor with social responsibility, this approach offers a…
subject: Articles
  topic: section
subject: Apr - Jun 2025 (Vol.2, Iss.2, 2025)
  topic: category
subject: Explainability
  topic: keywords
subject: Risk
  topic: keywords
subject: Governance
  topic: keywords
subject: Trust
  topic: keywords
subject: Equity
  topic: keywords
creator: Sri Nandhini Sivaram
creator: SIVARAM PONNUSAMY
creator: HARSHITA CHOURASIA CHOURASIA
creator: SHILPA SACHIN BHOJNE
creator: ABDULKAYYUM SHAIKH
creator: ASHWINI DEELIP MAGAR
rights: Copyright (c) 2025 International Journal of Multidisciplinary Global Research https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-06-29
publication date: 2025-06-29
starting page: 13
ending page: 44

Advanced In-Depth Literature Review on Intrusion Detection Systems
type: item
description: As cyber protective systems become more advanced, they rely on constant intrusion monitoring and tackling access, attacks, and associated renewing dangers to disguise malicious activities within the network. Modern cybersecurity designs would not be complete without intrusion detection systems (IDS), which monitor networks for suspicious activity and new threats. Three groups are examined in this work regarding IDS transformation: signature-based detection, anomaly-based detection, and hybrid models involving AI and ML. Federalized learning, blockchain integration, and zero-trust architectures are some of the new areas of research that are being thoroughly discussed. Other topics covered include the underlying methodologies, the integration of advanced AI/ML techniques, technical challenges like scalability and encrypted traffic analysis, and emerging trends in the field. The review draws upon diverse sources from IEEE, ACM, Springer, IOPscience, and ScienceDirect.
subject: Articles
  topic: section
subject: Jan - Mar 2025 (Vol.2, Iss.1, 2025)
  topic: category
subject: Anomaly- Based Detection
  topic: keywords
subject: Blockchain
  topic: keywords
subject: Cybersecurity
  topic: keywords
subject: Federated Learning
  topic: keywords
subject: Hybrid IDS
  topic: keywords
subject: Intrusion Detection Systems
  topic: keywords
subject: Machine Learning
  topic: keywords
subject: Zero Trust
  topic: keywords
creator: Nasruddin Annapuri
creator: Karthikeya Annam
creator: MUJTABA ASHRAF QURESHI
rights: Copyright (c) 2025 International Journal of Multidisciplinary Global Research https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-03-31
publication date: 2025-03-31
starting page: 1
ending page: 9

The Impact of Artificial Intelligence on Cultural Practices and Communication
type: item
description: Artificial Intelligence has emerged as a transformational force that dramatically affects communication and cultural behaviors in modern society. This article analyzes the complex impact of AI on how individuals and groups communicate, share information, and construct cultural narratives. AI-driven technologies, including natural language processing, machine learning algorithms, and generative AI, have changed communication by enabling personalized content distribution, real-time language translation, and automated responses. These progressions boost accessibility yet modify how individuals communicate interpersonally and in huge numbers. The way it carries crucial cultural consequences, AI curation based on liking creates echo chambers that alter consumption patterns of culture and also encourage other biases. At the same time, AI-generated art, music, and literature challenge the nature of creativity and authorship and what constitutes authentic and valuable human versus machine-generated cultural artifacts. Therefore, this significantly influences reshaping cultural identities and practices as AI provides an opportunity to save endangered languages, digitize cultural heritage, and facilitate global cultural exchanges. This will raise ethical questions, such as the commodification of cultural heritage, erosion of privacy, and a possible loss of human agency in creative processes when AI becomes integrated into cultural domains. Therefore, this paper takes an interdisciplinary approach by incorporating communication theory, cultural studies, and AI ethics to critically assess the opportunities and challenges posed by AI. Based on case studies and empirical analysis, it has demonstrated how AI both empowers and disrupts communication and cultural spheres. Therefore, the outcome of this research underlines that AI should be taken up in such a way that technological advancement goes hand in hand with ethics and cultural preservation. It is through this trip that the c…
subject: Articles
  topic: section
subject: Jan - Mar 2025 (Vol.2, Iss.1, 2025)
  topic: category
subject: Artificial Intelligence
  topic: keywords
subject: Digitized Culture
  topic: keywords
subject: Emerging Technologies
  topic: keywords
subject: Evolution
  topic: keywords
subject: Impact on AI
  topic: keywords
creator: Dr. Rani
rights: Copyright (c) 2025 International Journal of Multidisciplinary Global Research https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-03-31
publication date: 2025-03-31
starting page: 60
ending page: 70

Enhancing Digital Identity Verification and Content Rights Management with AI and Blockchain Using SVMs
type: item
description: This research explores merging AI-driven identity confirmation with blockchain mechanisms for rights management in digitized media—the proposed framework leverages supervisor learning techniques to authenticate digitized content and ensure secure ownership confirmation. Utilizing blockchain offers a decentralized and tamper-proof framework for managing rights, enabling transparency and trust among stakeholders. Supervisor learning algorithms, such as Support Vectors Machines, are applied to improve content authentication accuracy, ensuring that digitized assets are protected against unauthorized use or duplication. The combination of AI and blockchain automates the confirmation process and provides a reliable framework for managing ownership rights and licensing in a secure, distributed environment. This strategy holds significant potential for addressing the challenges of digitized rights management while fostering innovation and trust in digitized content ecosystems.
subject: Articles
  topic: section
subject: Jan - Mar 2025 (Vol.2, Iss.1, 2025)
  topic: category
subject: AI-driven confirmation
  topic: keywords
subject: blockchain technology
  topic: keywords
subject: content authentication
  topic: keywords
subject: digitise content protection
  topic: keywords
subject: digitise rights management
  topic: keywords
subject: Support Vectors Machines
  topic: keywords
creator: K. SWAMINATHAN
creator: Sivaram Ponnusamy
creator: G. PRASANNA LAKSHMI
creator: Sri Nandhini Sivaram
creator: MANISH NYAYAPATI
creator: Rakesh Nyayapati
rights: Copyright (c) 2025 International Journal of Multidisciplinary Global Research https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-03-31
publication date: 2025-03-31
starting page: 22
ending page: 38

https://ijmgr.igrf.co.in/index.php/ijmgr/article/view/14
type: item
title: From the Consumers' Perspective: Plastic Free Consumer Products, based on a High Critical-Crisis-based Recommender System for the Manufacturers/Producers of Consumable Products packed with all types of containers based on Plastic Material
description: In recent years, the issues on the usage of plastic products from the consumer products industry and the generated plastic waste (PW) after use and PW management (PWM) from various domains of businesses and the human society caused the biological ecosystem (BES) and the green ecosystem (GES) to reach its imbalance state. This imbalance in the GES and BES causes various human hygiene problems, leading to and affecting the natural resources available to the next generation of living organisms from genuine accessibility. As humans, our foremost duty is to enjoy the natural resources from the available GES and BES, maintain them, and hand over the same for the next generation to utilize and train the successor generation to maintain fair practice. In such a scenario, the PW in human society is caused by the considerable percentage of business handlers of consumable products packed with all types of containers based on plastic material. The awareness and law enforcement for the usage of plastic exists in all nations, and the practice of the manufacturers of consumable products which reaches in massive volume, the common public is not provided with strict conditions to not to use such plastic on their products, which is the primary source of common public's PW generation. This article aims to provide a recommender system to the manufacturers/producers of consumable products (M/PCP) packed with all types of containers based on plastic material. In the name of a High Critical-Crisis-based Recommender System (HCCRS) for the Plastic Free Consumer Products (PFCP) to make the PW-free environment for the common public, where ordinary people are trained to handle the PW efficiently. This PFCP- HCCRS recommends clean and transparent procedures to manufacturers/producers to manage their consumer products for the market with solid and environment-friendly containers with green business promotion.
subject: Articles
  topic: section
subject: Jan - Mar 2025 (Vol.2, Iss.1, 2025)
  topic: category
subject: Consumer Products with Plastic Containers
  topic: keywords
subject: Ecosystems
  topic: keywords
subject: Go Green
  topic: keywords
subject: Green Business Model (GBM)
  topic: keywords
subject: Plastic Free Consumer Products (PFCP)
  topic: keywords
creator: Malathi Sivaram
creator: Sri Nandhini Sivaram
creator: Dr Sivaram Ponnusamy
creator: Madhusudan K.S.
rights: Copyright (c) 2025 International Journal of Multidisciplinary Global Research https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-03-31
publication date: 2025-03-31
starting page: 39
ending page: 59

The Campus Pay: Offline Payment System Using RFID Technology for Campus Transactions
type: item
description: The Campus Pay system integrates RFID-enabled ID cards to allow for cashless payments on campus. This approach meets the need for safe offline transactions in domains with unpredictable internet availability. After the RFID enabled cards save transactions, when connectivity is restored transactions are then synchronized with a cloud based system. The paper describes the architecture, design and implementation of Campus Pay, focusing on how RFID is integrated with current infrastructure and how cloud data analysis is used in transaction monitoring.
subject: Articles
  topic: section
subject: Oct - Dec 2024 (Vol.1, Iss.4, 2024)
  topic: category
subject: Campus Pay
  topic: keywords
subject: Cloud analytics
  topic: keywords
subject: RFID
  topic: keywords
subject: Offline Payment
  topic: keywords
subject: Payment Systems
  topic: keywords
creator: Syed Ibad Ali
creator: Kush Bhushanwar
creator: Bhavesh Atulbahi Vaghela
creator: Nilesh Khodifad
creator: Sumersing Dayaram Patil
creator: Akruti Pandwal
rights: Copyright (c) 2024 International Journal of Multidisciplinary Global Research https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-12-31
publication date: 2024-12-31
starting page: 75
ending page: 85

Advancing Stock Price Forecasting: Exploring Methods, Models & Literature
type: item
description: In stock market prediction, aim is to identify future values of different financial stocks of companies. This research paper delves into the dynamic and challenging domain of stock price forecasting, that aims to Participate to existing body of knowledge by introducing a comprehensive analysis of methods, model building flow, and pertinent literature. By introducing the situation, this section emphasizes the difficulties posed by the intrinsic variability of financial markets as well as the crucial role that precise stock price forecasts play in financial decision-making. A key component of financial market is stock price forecasting that offers experts in finance & investors able to take wise investment decisions. This research paper explores the latest advancements, methodologies, and challenges in stock price forecasting. The paper systematically explores various forecasting methods, ranging from traditional time series analysis to advanced machine learning techniques. Understanding each method's advantages and disadvantages is emphasized, providing readers with a nuanced perspective on the applicability of different approaches in different market conditions.
subject: Articles
  topic: section
subject: Oct - Dec 2024 (Vol.1, Iss.4, 2024)
  topic: category
subject: Financial Markets
  topic: keywords
subject: Predictive Modelling
  topic: keywords
subject: Sentiment Analysis
  topic: keywords
subject: Stock Price Forecasting
  topic: keywords
subject: Stock Price Models
  topic: keywords
creator: Priyanka Tikekar Chandrashekhar
creator: SANDHYA DAHAKE
creator: SARIKA S. RADE
creator: Suhashini Awadhesh Chaurasia
rights: Copyright (c) 2024 International Journal of Multidisciplinary Global Research https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-12-31
publication date: 2024-12-31
starting page: 1
ending page: 11

YOLO-Based Framework for Detecting Suspicious Activities in ATMs
type: item
description: The YOLO (You Only Look Once) algorithm is the basis of this research's novel approach to ATM security. After that, we suggest a deep learning model for real-time suspicious activity identification utilizing LO (Look Once) techniques. The proposed framework allows our system to detect and monitor security risks in an ATM environment using YOLOv5's sophisticated object detection. It has a detection accuracy of 94.3% and analyzes video in real-time for surveillance purposes. This suspicious activity includes cash trapping, card skimming, and strange human movements. Forty ATMs were used to showcase the technology. Executing at a rate of 30 frames per second with an average accuracy of 0.91. These findings show that conventional monitoring has made great strides forward. Better technique sensitivity is also provided by high detection, which has a false positive rate of just 0.4%.
subject: Articles
  topic: section
subject: Oct - Dec 2024 (Vol.1, Iss.4, 2024)
  topic: category
subject: CNN
  topic: keywords
subject: ConvLSTM
  topic: keywords
subject: Deep Learning
  topic: keywords
subject: LSTM
  topic: keywords
subject: YOLO
  topic: keywords
creator: Kush Bhushanwar Kush
creator: BHAVESH ATULBAHI VAGHELA
creator: NILESH KHODIFAD
creator: SUMERSING DAYARAM PATIL
creator: AKRUTI PANDWAL
creator: IBAD ALI SYED
rights: Copyright (c) 2024 International Journal of Multidisciplinary Global Research https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-12-31
publication date: 2024-12-31
starting page: 100
ending page: 109

The Applications of AI in Smart Technologies and Manufacturing
type: item
description: Smart manufacturing has been driven forward by intelligentization, a major industrial production trend over the last several decades, with the help of AI technology. The modernization of AI by various modern businesses has given birth to a novel concept known as Industrial Artificial Intelligence (IAI), which serves as the technological basis for smart manufacturing. Artificial intelligence (AI) driven manufacturing improves several parts of closed-loop production chains, from production processes to product delivery. Considerably, the field of production monitoring has profited from IAI's incorporation of domain expertise. Modern artificial intelligence techniques, including adversarial training, transfer learning, and deep neural networks, are widely used in manufacturing for diagnostic and predictive maintenance purposes. IAI is widely believed to be a crucial technology that will propel industrial production forward in the future. Artificial intelligence (AI) driven manufacturing and its monitoring applications are thoroughly reviewed in this study. More precisely, it summarizes the primary IAI technologies and discusses their everyday use cases concerning the three primary production monitoring facets of problem detection, residual useful life forecast, and quality inspection. The current issues and potential avenues for IAI research are also covered. By incorporating them into the overview, this study further presents the papers on Monitoring with AI in Smart Manufacturing in this targeted part.
subject: Articles
  topic: section
subject: Oct - Dec 2024 (Vol.1, Iss.4, 2024)
  topic: category
subject: Artificial Intelligence
  topic: keywords
subject: Deep Learning
  topic: keywords
subject: Diagnosis of Faults
  topic: keywords
subject: Machine Learning
  topic: keywords
subject: Smart Manufacturing
  topic: keywords
creator: BHAVESH VAGHELA
creator: Nilesh Khodifad
creator: Sumersing Dayaram Patil
creator: Akruti Pandwal
creator: Syed Ibad Ali
creator: Kush Bhushanwar
rights: Copyright (c) 2024 International Journal of Multidisciplinary Global Research https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-12-31
publication date: 2024-12-31
starting page: 56
ending page: 74

The Hacker Eye
type: item
description: As hacker eye is a concept of significant risk to internet safety, hacker eye tries to deprive gullible consumers of private information. Phishing websites are the threat that researchers are trying to fight and various techniques in detecting phishing websites have been developed such as machine learning algorithms. Many phishing and legitimate websites can be applied to machine learning algorithm training to learn patterns and characteristics of sites to identify which are phishing and which are not. Once identified and blocked, these algorithms can then be used to find and prey on phishing Web sites, while users are still unscathed. A machine learning approach to detecting Hacker Eye website phishing websites is feature extraction where, through a set of features regarding a website such as URL structure, domain age, content, the ideas around these features are used for identifying such websites. Using deep learning algorithms to automatically extract features and identify intricate patterns in the company's website data is the alternative strategy. Overall machine learning based phishing website detection techniques are promising since such techniques are able to obtain accuracies that rival or even surpass rule based methods. However, and with further research and development, these techniques could become a powerful weapon in the arsenal of anyone fighting against online phishing attacks.
subject: Articles
  topic: section
subject: Oct - Dec 2024 (Vol.1, Iss.4, 2024)
  topic: category
subject: AdaBoost
  topic: keywords
subject: Gradient Boosting
  topic: keywords
subject: Hybrid Module Evaluation
  topic: keywords
subject: Random Forest
  topic: keywords
subject: SVM
  topic: keywords
subject: Voting classifier
  topic: keywords
subject: XGBoost
  topic: keywords
creator: Nilesh Khodifad
creator: Akruti Pandwal
creator: Bhavesh Vaghela
creator: Syed Ibad Ali
creator: Sumersing Patil
creator: Kush Bhushanwar
rights: Copyright (c) 2024 International Journal of Multidisciplinary Global Research https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-12-31
publication date: 2024-12-31
starting page: 86
ending page: 99

Chain Craft: Crafting the Future of Supply Chains with IoT and Blockchain Brilliance
type: item
description: Blockchain technology and the Internet of Things (IoT) are coming together to bring about a new paradigm in supply chain management that is more transparent, efficient, and secure. It mulls over the revolutionary effects of integrating supply chain blockchain technology with data from Internet of Things sensors. Organizations may optimize their logistical operations, get end-to-end visibility, and use Blockchain for immutable records. IoT devices capture data in real-time. Their synergy powers automated smart contracts, reduces intermediaries, and neuters risks of fraud and counterfeiting. This integration makes demand forecasting more accurate and inventory management and quality control more effective. Yet, due to the growing complexity and globalization of supply chains, IoT and Blockchain solutions are becoming viable to transform supply chains into resilient, adaptive, and sustainable ones. This paper analyses the key advantages, issues, and potential for these advanced technologies in supply chain operations.
subject: Articles
  topic: section
subject: Oct - Dec 2024 (Vol.1, Iss.4, 2024)
  topic: category
subject: Data Integrity
  topic: keywords
subject: Demand Forecasting
  topic: keywords
subject: Fraud Prevention
  topic: keywords
subject: Interoperability
  topic: keywords
subject: Inventory Management
  topic: keywords
subject: Logistics Optimization
  topic: keywords
subject: Real-time Monitoring
  topic: keywords
subject: Smart Contracts
  topic: keywords
creator: Sumersing Patil
creator: Akruti Pandwal
creator: Syed Ibad Ali
creator: Kush Bhushanwar
creator: Bhavesh Atulbahi Vaghela
creator: Nilesh Khodifad
rights: Copyright (c) 2024 International Journal of Multidisciplinary Global Research https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-12-31
publication date: 2024-12-31
starting page: 12
ending page: 22

DNA and KAMLA Approaches in Metamorphic Cryptography: An Evaluation
type: item
description: Metamorphic cryptography, a shift in the paradigm of cryptographic techniques, is a programming paradigm in which transformations that maintain the semantic meaning of the data transform the syntactic representation of it. This paper delves into two prominent techniques within metamorphic cryptography: KAMLA and DNA based cryptography. DNA based cryptography depends on the inherent properties of DNA molecules to encrypt and decrypt the data, providing a promise for more secure information and less computationally demanding schemes. In contrast, KAMLA transforms the original data in a series of mathematical transformations thereby making it resistant to different attacks. This research attempts an indepth review of these two approaches, highlighting their strengths and weaknesses and their applicability in different cryptographic applications. We aim to gain insights into the potential impact of these primitives in the cryptography of tomorrow by analyzing their security properties and computational complexity, and their practical feasibility. We also discuss possible ways to further improve on these approaches via a hybrid combination of DNA based and KAMLA techniques to enable enhanced security and flexibility.
subject: Articles
  topic: section
subject: Oct - Dec 2024 (Vol.1, Iss.4, 2024)
  topic: category
subject: Computational Complexity
  topic: keywords
subject: Dynamic Key Generation
  topic: keywords
subject: Hierarchical Authentication
  topic: keywords
subject: Hybrid Cryptographic Framework
  topic: keywords
subject: Metamorphic Cryptography
  topic: keywords
subject: Quantum Resistance
  topic: keywords
creator: AKRUTI PANDWAL
creator: SYED IBAD ALI
creator: KUSH BHUSHANWAR
creator: BHAVESH ATULBAHI VAGHELA
creator: NILESH KHODIFAD
creator: SUMERSING DAYARAM PATIL
rights: Copyright (c) 2024 International Journal of Multidisciplinary Global Research https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-12-31
publication date: 2024-12-31
starting page: 23
ending page: 34

Supervised Learning used for Clinical Decision Support System
type: item
description: The process of privacy preserving data publishing addresses the problem of revealing the sensitive information when mining for useful information. In the existing approaches the anonymization techniques provides one of the strongest privacy guarantees. This paper addresses the problem of private data publishing, where different attributes for the same set of individuals are held by multi-parties. To achieve this, the highly secure provider anonymization protocol is proposed propose an algorithm to securely integrate person-specific sensitive data from multiple data providers, whereby the integrated data still retain the essential information for supporting data mining tasks. This protocol used as sub-protocol for the exponential mechanism in a distributed setting. Further, the proposed algorithm helps to releases the data in a secure way according to the definition of secure multi party computation. The proposed algorithm can effectively preserve information for a data mining task.
subject: Articles
  topic: section
subject: Oct - Dec 2024 (Vol.1, Iss.4, 2024)
  topic: category
subject: Elgamal encryption
  topic: keywords
subject: Homomorphic encryption
  topic: keywords
subject: SVM classification
  topic: keywords
subject: Anonymization methods
  topic: keywords
creator: KARTHIKEYAN R
creator: SATHIS KUMAR T
creator: BRITTO DENNIS J
rights: Copyright (c) 2024 International Journal of Multidisciplinary Global Research https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-12-31
publication date: 2024-12-31
starting page: 45
ending page: 55

Bioengineered Neural Interfaces for Improved Brain-Computer Interactions
type: item
description: Neural interfaces are bioengineered materials that provide improved bist between neural tissues and computers or other devices. This paper aims at discussing the advancement and use of these interfaces, in close consideration of the ways in which it may enhance the Accuracy and resilience of BCIs. These interfaces are designed to be incorporating with the neural tissue by using the novel biomaterials and fabrication approaches while keeping low immune reactions and high signal quality levels. These are the flexible and biocompatible surfaces for recording and stimulating the brain signals and high-density microelectrode arrays. The application of these two possibilities shows great potential in optimizing the functioning of BCIs and helping in better control of prosthetic limbs, new models of neuro prostheses, as well as in the improvement of therapeutic treatments for neurological disorders. As such, this study underlines the fundamental contribution of BE neural interfaces for the development of neuro technology and the nearer future BWI designs, which will elicit progressive improvement of the BCI systems’ efficacy in enhancing the patients’ quality and longevity of life.
subject: Articles
  topic: section
subject: Jan - Mar 2025 (Vol.2, Iss.1, 2025)
  topic: category
subject: BCI
  topic: keywords
subject: Neuro Devices
  topic: keywords
subject: Neural Electrodes
  topic: keywords
subject: Neuro Implants
  topic: keywords
subject: Neural Interfaces
  topic: keywords
creator: KARTHIKEYAN R
creator: Dr Swaminathan K
creator: Sivaram Ponnusamy
rights: Copyright (c) 2025 International Journal of Multidisciplinary Global Research https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-03-31
publication date: 2025-03-31
starting page: 10
ending page: 21

Global Environmental Imbalance: Gen Z Behavior and Social Responsibilities
type: item
description: The research paper explores the intricate relationship between global environmental imbalances and the behavioral tendencies of Generation Z, focusing specifically on their social obligation As the first generation to come of age in a world dominated by digital technology and heightened awareness of climate change, Gen Z displays distinct characteristics and viewpoints on environmental issues. The objective of this research is to comprehend how these young individuals perceive and react to the ecological crises that pose a threat to global stability. Through analyzing their attitudes, activism, and consumption patterns, we aim to pinpoint the driving forces behind their dedication to sustainability and environmental justice. The research employs a mixed-methods approach, incorporating surveys, interviews, and case studies to comprehensively capture Gen Z’s involvement with environmental concerns. The findings indicate that Gen Z's conduct is significantly shaped by their digital connectivity, educational background, and socio-political environment, which collectively influence their proactive approach to environmental stewardship. This paper underscores the potential of Gen Z to lead innovative solutions and cultivate a culture of environmental responsibility, underscoring the necessity for supportive policies and educational frameworks to effectively harness their potential. By understanding the motivations and actions of Gen Z, we can better tackle global environmental challenges and promote sustainable practices for future generations.
subject: Articles
  topic: section
subject: Oct - Dec 2024 (Vol.1, Iss.4, 2024)
  topic: category
subject: Culture
  topic: keywords
subject: Environmental Imbalance
  topic: keywords
subject: Gen Z
  topic: keywords
subject: Mix-method
  topic: keywords
subject: Potentials, Solution
  topic: keywords
creator: Dr. Rani Sarode
creator: PRASANNA LAKSHMI G
rights: Copyright (c) 2024 International Journal of Multidisciplinary Global Research https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-12-31
publication date: 2024-12-31
starting page: 35
ending page: 44