International Journal of Multidisciplinary Research and Explorer

This study presents a framework for managing technology transfer in India's wind energy sector, with a focus on supporting electric vehicle (EV) charging infrastructure. Using data from literature, interviews, Delphi studies, case studies, ISM modeling, and MICMAC analysis, the research offers strategies for fostering collaboration among stakeholders, expanding EV charging networks, and enhancing wind energy capacity...

This paper investigates the process of technology transfer within India’s renewable energy sector, focusing specifically on the wind and solar energy industries. Using a mixed-method approach, which includes case studies, site visits, and a Delphi study, the research highlights critical barriers, enablers, and strategic considerations for effective technology transfer. Findings emphasize the need for robust technolog...

Robots face many problems in identifying RGB colours in captured images, which affects their performance in many applications. These challenges include different lighting, colour matching, constraints, and environment. The same object will appear in assorted colours in different light, making it difficult for robots to identify and distinguish colours. differences, especially in complex scenes. For example, under cer...

Machine Learning (ML) models are becoming robust and more accurate nowadays as the rapid increase in the amount and quality of training data. Researchers are proposing complex models for real-life problems to achieve higher accuracy, which requires high computing and other resources. In the context of the healthcare disease diagnosis, detection and prediction is still a challenge. Early diagnosis of a disease or ailm...

The study investigates the relationship between psychological distress and purpose in life among older adults, along with gender differences in these variables. The sample consists of 80 older adults aged 65 to 79 years, selected from various parts of Kerala, primarily Palakkad, using a purposive sampling method to ensure equal representation of genders and minimize bias. The participants include 40 males and 40 fema...

The study explored teachers’ perceptions of parent-teacher partnerships for enhanced access to equitable education for learners with intellectual disabilities in mainstream primary schools. A qualitative case study was utilised to collect data from 8 teachers who taught in mainstream primary schools. Data was sourced through face-to-face semi-structured interviews. The findings reveal that while various challenges ha...

The India-UK Roadmap 2030 outlines a comprehensive strategic vision for deepening bilateral ties between India and the United Kingdom across key sectors, reinforcing both nations’ commitment to economic growth, sustainability, and global leadership.  As the global geopolitical and economic landscape undergoes rapid transformation—shaped by the UK's post-Brexit realignments and India’s emergence as a key global actor—...

The National Education Policy (NEP) 2020 aims to reform India's education system by introducing progressive changes. However, its success depends on stakeholder awareness and acceptance. This study investigates parental awareness and perception of NEP-2020, given that parents play a crucial role in their children's education. Using a quantitative approach, data was collected from 300 parents through a structured surv...

Effective inventory management is crucial for businesses dealing with perishable or deteriorating goods. This research article examines various inventory models that account for time-dependent demand, price fluctuations, and product deterioration. By synthesizing findings from multiple studies by Sharma and colleagues (2015–2024), this paper explores key strategies for optimizing stock levels, minimizing costs, and i...

The global COVID-19 pandemic, resulting from the infection by the SARS-CoV-2 virus, is emphasizing the urgent need for rapid and accurate diagnostic methods for the control of the infection spread. Lab-based testing methods can take time, leading to diagnostic delays and a high risk of transmission. Fuzzy Logic-Based Expert System in Early Detection of COVID-19 Symptoms and Risk Assessment in Real-Time. We provide a...

Nowadays, as technology is advancing to previously unheard-of levels, every company and organization is finding it difficult to balance inventory and customer expectations. Every organization relies heavily on sales, and being able to predict the future helps in making strategic and intelligent sales decisions. The majority of businesses still struggle with revenue forecasting because it is usually the first step in...

Background: Chronic low back pain (CLBP) with radiculopathy is a leading cause of disability worldwide. Conventional treatments generally have limited efficacy, high costs, and associated adverse effects. Objective: To evaluate the efficacy and safety of high-and low-frequency TENS (HLF-TENS) with paravertebral ozone therapy (POT)in chronic low back pain (CLBP) and radiculopathy. Methods: This non-randomized pilot st...

One of the main purposes of this work is to provide a path planning framework for IoT-enabled autonomous vehicles through the use of RRTs and A*. These were designed to maximize actual real-time navigation and decision-making in very dynamic and complex situations considering obstacles and uncertainties in the environment. In cases that have unknown or nonregular barriers, the RRT algorithm is employed to visualize t...

The increasing complexity of fraud strategies, combined with the rapid increase in transaction volumes, makes credit card fraud detection an important area of consideration in the banking sector. Due to the complexities of fraudulent behavior in the context of large transaction sizes, traditional techniques for fraud detection based on rules have become incapable of meeting the challenge. Cloud-based AI solutions bas...

E-commerce has highlighted the requirement to use advanced cloud technology and data analysis techniques to power customer experience and business efficiency. This paper is a detailed study of integrating cloud-based solutions and machine learning (ML) techniques in the analysis of e-commerce sales data. The research uses a customer credit card database to contrast and validate the performance of various ML models, i...

The very critical phase in SDLC is software testing, where application reliability, security, and efficiency are ensured. However, increasing complexity in software has made traditional test case prioritization (TCP) methods difficult, with regards to high execution time and computational overhead. The existing approaches such as Genetic Algorithms (GA) are highly computationally expensive, and the adaptability of te...

Software testing plays a critical role in ensuring software reliability, yet traditional test case generation approaches often suffer from high computational overhead and inefficiency. Traditional methods, including genetic algorithms, struggle with scalability and fail to optimize execution time while maintaining high test coverage. To address these limitations, this paper proposes a lightweight deep learning-based...

This work introduces a novel system incorporating Internet of Things (IoT) empowered drones, robotics, and deep learning methods, specifically Convolutional Neural Networks (CNN), to identify areas affected by landslides. The system uses modern sensors including cameras, LiDAR scanners, and environmental sensors, offering detailed information from distant and dangerous environments. The CNN model analyses this inform...

In this paper, a framework for optimizing cloud resource allocation using the Secretary Bird Optimization Algorithm and dynamic workload balancing has been presented. The presented method tackles inefficiency in cloud computing systems, such as inefficiency in task scheduling and resource overload, through dynamic task distribution among resources. With the introduction of SBOA, prompted by the innate behavior of sec...

This work discusses the evolution of a cloud platform for intelligent personalization and safe transactionmanagement in scalable e-commerce sites. With the growth of e-commerce, sites are compelled to provideindividualized user experience with transaction safety and privacy. On-premises solutions cannot processheavy loads of data and traffic and are therefore unsuitable for today's dynamic e-commerce environment. Clo...