International Journal of Multidisciplinary Research and Explorer
The International Journal of Multidisciplinary Research and Explorer (IJMRE) is an esteemed international peer-reviewed academic journal that publishes 4 issues per year, quarterly. Its primary objective is to deliver authentic and reliable contributions to the global research community. Supported by a strong editorial board of subject experts, IJMRE ensures a rigorous peer-review process while maintaining efficiency and quality. Renowned for its academic prominence, the journal covers a wide spectrum of fundamental and emerging research topics across multiple disciplines. By offering valuable publishing opportunities, IJMRE strengthens research competencies and fosters the growth of academic trends worldwide. With its active presence on academic journal sites and journal article platforms, IJMRE has established itself as a trusted resource for scholars, researchers, and professionals seeking credible and high-quality research publications. International Journal of Multidisciplinary Research and Explorer (IJMRE) Publisher: Academics Achievers Education and Research Foundation Editor-In-Chief: Dr. Jaydip Kumar Address: Umrapur, Ibrahimpur, District Raebareli, Pin-229212 Email: admin@academicsachievers.in No. of Issues Per Year: 4 | Frequency: Quarterly ISSN (Online): 2833-7298 ISSN (Print): 2833-7301 Publication Fee: IJMRE has no publication fee up to 10 pages, and for extra pages, authors need to pay 5 USD per page. For details on article withdrawal, please see our Article Withdrawal Policy Article Template: click here
Academics Achievers Education And Research Foundation
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Pottery Industry and Value Chain Model: A Conceptual Study
Decrease market demand, low profitability, labour turnover and unsound financial situation is what characterise pottery industry in today`s scenario. Value chain model primary activities of inbound logistic, operations, outbound logistic, marketing & sales and service activities are needed systematically to be executed with support activities of procurement; human resource management, technological development and infrastructure, in case of pottery industry, these activities to be performed systematically require organising of artisans, government assistance and social as well as psychological motivation. Thus, a new framework is framed keeping these points in view. The study using literatures of various authors attempts to study pottery industry using value chain model and suggest a viable solution in the form of new framework to improve the situation of pottery industry.
Copyright (c) 2025 Vaishali Silakari, Dr Priti Goswami (Author) https://creativecommons.org/licenses/by/4.0
Comparative Insights into State-of-the-Art Cryptographic Techniques and Design Approaches
The modern communication technology has experienced huge changes with the rapid growth of the Internet. This expansion has made human beings more dependent on it, but has also raised security issues during information exchange. While being transferred over a public network, attackers may monitor and capture the data packets if they are unencrypted. Consequently, the communication process may be interrupted and intercepted. Attackers can combine multiple methods to grab the transmitted data. Therefore, security of information is imperative prior transmission. Cryptography is a security measure to make data unintelligible to intruders. Numerous research studies have been conducted over the decades to introduce a variety of cryptography methods. Additionally, a number of analyses have been carried out to determine the optimal encryption technique based on specific characteristics, each with its own shortcomings. This prompts individuals to implement robust security measures. This paper provides a comprehensive analysis of contemporary cryptography methods, while also reviewing several existing related research efforts.
Copyright (c) 2025 Most. Mazriha Akter Mohua (Author) https://creativecommons.org/licenses/by/4.0
A Comparative Study of ECG Sampling Rates in Predicting Cardiac Arrhythmias Using a Deep Learning Approach
Cardiac arrhythmias are a group of conditions that have caused great concern among healthcare professionals because they have a high incidence and prevalence worldwide, and their early diagnosis and effective treatment are essential to alleviate the negative impacts they can have on people’s quality of life. In recent years, many studies have suggested Deep Learning models for diagnosing cardiac arrhythmias by analysing data from electrocardiograms (ECG). The heart’s electrical activity can be measured using different ECG sampling rates, and the chosen rate can impact the model’s prediction accuracy and associated computational costs. This study presents a comparative analysis of various sampling rates for predicting cardiac arrhythmias using a Deep Learning model and a large public dataset. The findings can serve as a guideline for doctors and researchers to select the most appropriate sampling rates to achieve greater efficiency when using the ECG and better outcomes in predicting cardiac arrhythmias.
Copyright (c) 2025 Rodrigo Alexandre Dos Santos (Author) https://creativecommons.org/licenses/by/4.0
Enhancing Melanoma Skin Cancer Detection and Classification: U-Net segmentation and feature fusion of Deep Learning Algorithms
Human skin cancer is the most prevalent type of cancer and poses a significant threat to life, particularly, melanoma skin cancer, which exhibits a high mortality rate. Accurate detection and classification of melanoma skin cancer continue to be essential for timely treatment and improving patient diagnosis. Traditionally, painful, invasive and time-consuming biopsies are used to detect melanoma skin cancer. However, recently, computer-aided diagnosis of melanoma has become crucial. Thus, in this study, the researcher proposes a novel approach combining the feature extraction capability of the VGG16 and ResNet-50 deep learning algorithms with the precise segmentation power of the U-Net architecture. By combining these methodologies, the study aimed to achieve enhanced accuracy in distinguishing melanoma skin cancer as benign or malignant. The proposed method leverages the U-net segmentation algorithm to accurately delineate lesion boundaries and highlight crucial diagnostic areas, and the VGG16 and ResNet-50 models to extract high-level features from melanoma images, capturing textures and intricate patterns indicative of melanoma skin cancer. With a precise segmentation algorithm and the fusion of rich features from deep learning models enable a comprehensive analysis of melanoma characteristics, facilitating more reliable classification. The study used a total of 10606 images of melanoma skin cancer, and the experimental result demonstrates promising results, achieving a classification accuracy of 93% in distinguishing benign and malignant cases. As the experimental result shows, it validates the effectiveness of the proposed method in accurate classification of melanoma skin cancer. This study contributes to advancing melanoma detection capability and paving the way for more accurate dermatological diagnostic tools
Copyright (c) 2025 Getnet Tigabie Askale, Belayneh Matebie Taye, Achenef Behulu Yibel, Misganaw Abeje Debasu (Author) https://creativecommons.org/licenses/by/4.0
OVERVIEW OF INTESTINAL HELMINTHIASIS IN NIGERIA: REGIONAL PATTERNS, CONTRIBUTING FACTORS, AND THE PARADOX OF PROLONGED WASH INTERVENTIONS
This study reviewed the current report helminthiasis in Nigeria. This study revealed that prevalence of intestinal helminth in the country has not declined since the1970s. Ascarislumbricoides was the most prevalent helminth in the Southwestern and South-southern parts of Nigeria. Hookworm was the most prevalent helminth infection in the Southeastern while multiple infections were highly prevalent in Northern Nigeria. Nigeria has benefited from the Water, Sanitation and Hygiene (WASH) programme for over thirty years in the aspects of enhanced capacity building for applying personal hygiene and sanitation, improved water sources and provision of sanitation facilities and the National Emergency Group for coordination of emergency preparedness and response for WASH-related diseases. Despite the prevalence of helminth infections in Nigeria is still very high and alarming. The factors identified for the high prevalence include socio-economic status, culture and ignorance; attitudes and behaviours toward hygiene and sanitation are also critical.
Copyright (c) 2025 Chukwuma Ogechi D, andUmoren, Otoh D. (Author) https://creativecommons.org/licenses/by/4.0
Philosophical Reflection on the Changing Face of Economic Development in the Context of Sustainability
This article examines the changing nature of economic development through the lens of sustainability. It explores agriculture’s evolving role within the economy—not only as a productive sector but also as a provider of public goods such as biodiversity, landscape preservation, and food security. The analysis draws on classical and modern theories, including Friedrich List’s stages of national development and A. Fisher’s three-sector model, which outlines the structural shift from agriculture to industry and services. Keynesian interventionism is revisited to highlight the state’s role in stabilizing economies and supporting vulnerable sectors, with the New Deal serving as a practical example. A central focus is the concept of sustainable development, traced from its origins in forestry to its adoption by global institutions. The article emphasizes the need to balance economic growth with environmental protection and social equity. Ecological agriculture is presented as a model aligned with sustainability principles, despite its lower input efficiency. The article synthesizes diverse theoretical perspectives and empirical insights, advocating for a multidimensional approach to development that harmonizes economic, social, and ecological goals. The analysis is based on Polish academic publications, translated by the author for the purpose of this study.
Copyright (c) 2025 Lukasz Chryniewicz (Author) https://creativecommons.org/licenses/by/4.0
Therapeutic Plants Used for Maintaining/Enhancing Health Conditionsin Owode-Yewa South Local Government, Ogun State, Nigeria: An Ethno-Pharmacological Survey
Herbal therapy involves the use of plant-based products for therapeutic purposes and remains a popular and effective treatment option for various illnesses. This study aimed to conduct an ethnobotanical survey of therapeutic plants used for maintaining/enhancing health conditions in Owode-Yewa South Local Government, Ogun State, Nigeria. A total of 50 questionnaires were distributed to gather information about the use of medicinal plants in the treatment of diseases. The collected data were analyzed using Excel 2016 and SPSS 20.Results revealed that sixty (60) therapeutic plants were identified for treating or maintainingthirty (30) different illnesses, with trees (49%) and shrubs (31%) being the most common types. The leaves (42%) and bark (19%) were the most frequently utilized parts of the plants, while decoction (49%) was the predominant method of preparation, with water (67%) serving as the primary solvent. Large number of the plants are mono-therapeutic while few are known as poly-therapeutic while majority of treated of maintained illnesses are Infectious (47%). This study contributes valuable insights into the medicinal plants used in the local area and highlights the urgent need for conservation efforts and the integration of these practices into formal healthcare systems.
Copyright (c) 2025 Umoren Otoh Dayo (Author) https://creativecommons.org/licenses/by/4.0
Rethinking the Northeast : Spatial Politics, Market Imperatives, and Cultural Contestation’s
The North east region of India historically, has been viewed through a strategic lens, during the colonial era the region acted as a strategic buffer against China and France. Post-independence, the Indian state has continued to hold the same perception of the northeast as a region of strategic importance. These imaginaries of the northeast throughout the years have put the region in a state of what many scholars refer to as “ territorial trap”. It was only after the advent of globalization that India adopted a new spatial imagery, under the Look East policy. The northeast was then imagined as a transit point to connect the mainland with Southeast Asian countries, thereby boosting trade and economic activity. However, this evolving perception towards the northeast has been driven by several factors, including geopolitical aspects, the region's internal quest for identity, and the chronic underdevelopment that has persisted throughout the decades. To overcome the challenges faced by the region, the Indian state has invested a considerable amount of capital in building infrastructure and boosting development. However, the region has not witnessed the realized growth that was assumed by policymakers at the center and has only sustained the prevailing state of underdevelopment and marginalization in the region, which, according to scholars like Sanjib Barua, has described as ‘durable disorder’. The paper aims to examine the historical spatial imaginations of the northeastern region and their ramifications. Also, look into the new issues emerging from the overlap of these spatial imaginaries, in doing so the research takes up qualitative method for enquiry, using primary sources like governments reports along with secondary data using works of relevant scholar’s in relevant field.
Copyright (c) 2025 Kunsang Bhutia (Author) https://creativecommons.org/licenses/by/4.0
Green Synthesis of Mediated Ag/MgO Nanohydroxyapatite from Crayfish Using Orange Peel Extract (Citrus aurantium delcis)for BiomaterialsApplications
Conversion of waste such as crayfish shell to resourceful biomaterial like Hydroxylapatite is a led-light to the realization of United Nation vision 2030.Waste crayfish shell are being generated in tons of million across the globe annually thus constituting environmental pollution, while the demand for the synthesis of pure and biologically active materials is on the increase.This present work is aimed at investigating the facile synthesis of crayfish waste derived hydroxyapatite (CFSHAP) and substituent synthesis of its orange peel extract mediated Ag/MgOnHAP nanocomposite, as a potential biomaterial in bone tissue engineering application. The phase purity, composition, size, functional groups and surface morphology of the apatite were elucidated using spectroscopic (X-ray Diffraction (XRD); FourierTransform Infrared Spectroscopy (FR-IR) and Scanning Electron Microscopy). The results SEM showed that Ag/MgO- CFSHAP nanoparticles have round morphologies and the SEM-EDS revealed the characteristic Ag, Mg, Ca/P and O composition, FT-IR analysis confirmed relevant hydroxylapatite functional groups like carbonate, phosphate and hydroxyl groups while XRD analysis revealed a well crystalline monophasic HAp powder comparabie to the MAP reference model (JCPDF no. 00-064-0738). The 1000°c calcined Ag/MgO-CFSHAP also displayed stable phase stability which could lead to increased densification and porosity.The use of Ag will introduce antibacterial properties, while MgO will introduce osseointergration into the HAp
Copyright (c) 2025 Adeyinka Ademilua (Author) https://creativecommons.org/licenses/by/4.0
Assessment of E-Waste Workers Knowledge Levels Regarding Potential Health Risks Associated With Electronic Waste In Ladipo Market, Lagos State, Nigeria
The growing challenge of electronic waste (E-waste) management, particularly in developing countries like Nigeria, has become a significant environmental and public health concern. This study assessed the knowledge levels and practices of e-waste workers regarding health risks associated with e-waste in Ladipo Market, Lagos State, Nigeria. Using a descriptive cross-sectional design, 96 e-waste workers, including repairers, recyclers, and waste scavengers, were surveyed through structured questionnaires. Socio-economic characteristics, awareness levels, and work practices were analyzed using frequencies, percentages, and correlation techniques. Results indicate a significant knowledge gap, with only 35% of respondents aware of long-term health risks such as respiratory issues and toxic metal exposure. Despite this, 85% of participants reported engaging in informal disposal methods, including open burning and improper handling. which contribute to environmental degradation and public health risks. Correlation analysis revealed a strong positive relationship (r = 0.72) between knowledge levels and the adoption of safety measures, emphasizing the role of education in promoting safer practices. Furthermore, workers with higher education levels demonstrated better adherence to safety measures. This study highlights the urgent need for structured interventions, including targeted educational programs and policy-driven regulatory frameworks, to improve awareness and promote sustainable e-waste management practices. Recommendations include enforcing stricter environmental laws, establishing formal recycling systems, and creating community awareness campaigns to mitigate the health and environmental risks associated with e-waste.
Copyright (c) 2025 Festus Adewole Adenekan (Author) https://creativecommons.org/licenses/by/4.0
Spiritual Growth Analysis using Fuzzy Logic in Hinduism: A Scientific Consecration Model
Spiritual growth is a fundamental aspect of Hindu philosophy, emphasizing self-awareness, devotion, meditation, ethical conduct, and detachment as key elements of self-realization and enlightenment. However, measuring an individual's spiritual progress remains subjective and lacks a structured quantitative approach. This research presents a fuzzy logic-based framework to model and evaluate spiritual growth by incorporating key Hindu spiritual principles. The study defines five key input variables—Self-Awareness, Devotion (Bhakti), Meditation (Dhyana), Ethical Conduct (Dharma), and Detachment (Vairagya)—and a single output variable, Spiritual Level. A Mamdani fuzzy inference system is developed using MATLAB, employing trapezoidal and triangular membership functions to handle uncertainties in spiritual assessment. The system integrates rule-based inference to categorize an individual’s spiritual state into four levels: Beginner, Intermediate, Advanced, and Enlightened. The proposed model offers a structured methodology to analyze spiritual progress, aiding spiritual practitioners and researchers in assessing personal growth through computational intelligence. Simulation results validate the model's effectiveness, demonstrating its potential application in personalized spiritual guidance.
Copyright (c) 2025 Prithwiraj Jana, Parthajit Bisal (Author) https://creativecommons.org/licenses/by/4.0
Synthesis and Characterization of Copper (II) Complex Bearing 1-Phenyliminomethyl-Naphthalen-2-ol
A novel Schiff base ligand, 1-phenyliminomethyl-naphthalen-2-ol was synthesized by condensation of 2-hydroxyl-1-naphtaldehyde and aniline, and subsequently complexed with Cu(II) ions to become a stable metal-ligand complex. The synthesized Schiff base and Cu(II) complex have been characterized using UV–Visible spectroscopy and Fourier-transform infrared spectroscopy. The UV-Vis analysis revealed that metal-ligand charge transfer which depicted low band at 406, 350 nm (for the two molar ratio 1:1, 2:1) respectively. The FTIR absorption spectra confirmed the formation of the imine (C=N) bond and coordination of the phenolic oxygen and azomethine nitrogen. NH bonds revealed coordination at 3340 and 3366 cm-1 while CN bonds showed no coordination and 1161 cm-1, both at 1:1, 2:1 respectively. In conclusion, these findings supports the successful formation of a bidentate Schiff base to Cu(II) complex with a potential application in biological and catalysis studies.
Copyright (c) 2025 Idowu Daniel, Daniel Ayodele Idowu, Chidera Godswill Obideje, Ejikeme Peter Igwe, Okiki Quadri, Emmanuel Ogbonnia Oko, Gabriel Lagbel (Author) https://creativecommons.org/licenses/by/4.0
Creative Accounting and Accountability Failures in the Philippine Health Sector: A Case Study of PhilHealth during COVID-19
This study investigates creative accounting practices in the Philippine Health Insurance Corporation (PhilHealth), focusing on financial manipulation and accountability breakdowns during the COVID-19 pandemic. The current paper uses a qualitative case study and document analysis of government audit reports, legislative inquiries, and media investigations (2018–2021) to reveal how procurement irregularities, unliquidated cash advances, and disguised operating losses distorted the agency’s financial position. These practices, facilitated by weak internal controls and governance failures, undermined transparency and jeopardized the implementation of universal health care. Anchored in public sector accountability and creative accounting theories, the study concludes with actionable recommendations, including the institutionalization of forensic audits, digital transparency reforms, and stronger whistleblower protections. The findings underscore systemic weaknesses that enabled financial misreporting and highlight the pressing necessity for structural reforms in public financial management.
Copyright (c) 2025 TIMOLEON LIANZA (Author) https://creativecommons.org/licenses/by/4.0
Evaluating the NEP 2020 Vision For Higher Education In India: A Critical Perspective
The National Education Policy 2020 has brought a revolutionary change in the education system of India. Emphasis is placed on each stage of education. This study seeks to analysis how the National Education Policy 2020 (NEP 2020) supports student-focused and skill-oriented higher education, while also assessing the inclusive strategies it proposes for diverse social groups within the higher education sector. Education is about access, equity, quality, affordability, and accountability. The emphasis will be on learning, regardless of the student. Along with education, moral development and holistic development have also been said about. The study used only secondary sources such as authoritative government publications and policy documents, research journal articles, and reliable online sources. It explores the key ideas, goals and potential impacts of the National Education Policy (NEP) 2020 through a systematic analytical approach.
Multidisciplinary and Vocational Education
Internationalization of Indian Education
Copyright (c) 2025 PRITI GOSWAMI, SUSMITA SAU (Author) https://creativecommons.org/licenses/by/4.0
Bibliometric Review of Financial Risk Tolerance: A Scientometric Analysis using Biblioshiny
This study provides a bibliometric analysis of financial risk tolerance research papers. This study addressed bibliometric analysis using information from Scopus. The study in this work is exploratory and descriptive, based on bibliometric methodologies and tools used to documents contained in the Scopus bibliographic database, which yielded a total of 1084 documents spanning the years 1979 to 2025. This study report made use of Biblioshiny, an open-source platform based on the R programming language, as well as VOS viewer, in order to carry out a variety of bibliometric studies and assessments. The topic of financial risk tolerance was examined using the bibliographic data, which provided a complete description of the subject matter. According to the findings of the analysis, the most significant areas of focus for research on risk tolerance over the past several years have been on financial literacy, personality factors, and financial decision making. Over the past two decades, there has been an upward trend in the amount of research done on the FRT.
Copyright (c) 2025 VYSHAK P K, Dr. JAYARAJAN T K (Author) https://creativecommons.org/licenses/by/4.0
Empowering the Grid: Applications and Challenges of Machine Learning in Renewable Energy Resources
Integration of renewable energy systems, into the electrical grid has been investigated in the present research, with a special focus on the use of machine learning (ML) techniques in power system operations. In the framework of renewable energy, it critically investigates the applications of machine learning (ML) in forecasting, efficiency improvement, problem detection, and system optimization. The paper also discusses the primary challenges to implementing AI-driven solutions in contemporary power systems, including the need for quick decisions, cybersecurity risks, limitations on data availability and quality, and the difficulties of integrating with current grid infrastructure. This paper aims to provide an in-depth understanding of how intelligent algorithms are transforming the future of the electrical sector by highlighting both the revolutionary potential and the implementation challenges of AI technology in energy systems.
Copyright (c) 2025 Akshay Juneja, Deepak Painuli, Ishant Jagotra, Priyanka Kumari, Hutashan Vishal Bhagat (Author) https://creativecommons.org/licenses/by/4.0
Understanding North-East Woman’s Participation in State Governance- A Power Dynamics
The northeastern states of India, popularly known as the Seven Sisters of India (Assam, Manipur, Meghalaya, Nagaland, Tripura, Mizoram, and Arunachal Pradesh), along with their brother state Sikkim, stand out with their unique geographical location and are home to several multi-ethnic communities. The region has witnessed several ethnic uprisings following the complexities of autonomy-related movements, the integration process, and the share in the natural resources. Needless to say, with the kind of societal structure prevailing in this region, women’s participation has been a major factor in ethnic movements in the past and even in the present. Indubitably, their participation in the societal and civil sphere of life is impressive. However, their involvement and presence in the larger political scenario, such as state institutions, are hardly felt. The central inquiry of the paper is to analyse the role of women in ethno-political conflicts and parallelly examine the power-sharing dynamics of women in North-Eastern regions. Methodologically, this research involves a comprehensive study of documents from the Election Commission of India, focusing mainly on the percentage of women candidates in the northeast contesting in Lok Sabha elections from the time period of 2014 to 2024. Through the analysis of this data, the research will try to underscore the reason for the invisibility of women's role in larger power sharing where there is paradoxically huge participation of women in ethno-political issues.
Copyright (c) 2025 Srikant Mahali, Reshmi Biswas (Author) https://creativecommons.org/licenses/by/4.0
Strategic Inventory Control for Deteriorating Products under Time-Sensitive Demand
Efficient management of inventory is essential for businesses handling perishable or time-sensitive products. This study delves into advanced inventory models incorporating time-varying demand, pricing dynamics, and product deterioration. Drawing on a comprehensive review of research conducted by A. Sharma and collaborators between 2016 and 2024, the article presents strategic approaches to optimize inventory levels, reduce operational costs, and enhance overall supply chain performance. It emphasizes the role of dynamic pricing mechanisms, partial backordering, and accurate demand forecasting in developing responsive inventory control systems. The findings offer valuable insights for retailers, manufacturers, and logistics professionals while outlining promising avenues for future research in this evolving domain.
Copyright (c) 2025 Trilok Chand Bagh (Author) https://creativecommons.org/licenses/by/4.0
SENSOR FUSION TECHNIQUES FOR DRONES IN IOT-BASED SURVEILLANCE SYSTEMS
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 information to classify areas as damaged or undamaged with very high precision. Robustness of the system is emphasized using multi-sensor data acquisition, efficient preprocessing, and application of transfer learning to deliver optimal performance. Results reflect a high classification accuracy of over 99%, validating the system's capability in real-time landslide detection and disaster management. The current work seeks to contribute to more scalable and efficient disaster management systems using IoT and AI technologies.
Copyright (c) 2022 Dinesh Kumar Reddy Basani, Basava Ramanjaneyulu Gudivaka, Raj Kumar Gudivaka, Rajya Lakshmi Gudivaka, Sri Harsha Grandhi, Aravindhan Kuruntha chalam (Author) https://creativecommons.org/licenses/by/4.0
Cloud-Based E-Commerce Sales Exploratory Data Analysis and Cloud Storage Integration
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.e., Random Forest, Decision Tree, Logistic Regression, etc., in predicting customer churn. The performance of the models is compared against metrics such as Accuracy 92.5%, Precision 91.0%, Recall 93.0%, F1-Score 92.0%, and AUC-ROC 0.94 which identify Random Forest as the most superior performing model. The study then continues to probe the impact of integration of the cloud into storage and discovers that it is efficient, scalable, and secure when handling vast data. The key contribution of the cloud solutions in the e-commerce environment is in accordance with this research as scalability in business, optimized utilization, and hassle-free customer experience emerge. This book finishes by providing lines of future work on hybrid cloud solutions, real-time prediction systems, and protection of data privacy.
Copyright (c) 2021 Karthikeyan Parthasarathy, G. Arulkumaran (Author) https://creativecommons.org/licenses/by/4.0
Cloud-Based AI solutions for credit card fraud detection with feedforward neural networks in banking sector
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 based on Feedforward Neural Networks (FNNs) provide the best option when looking for an advanced adaptive approach. This solution benefits from cloud storage to provide highly efficient management of large volumes of transactional data with maximum scalability and flexibility. FNNs aid in differentiating and recognizing complex fraud patterns, while cloud technology ensures that such a system is proficient in adjusting to transaction volume fluctuations. The integration of these technologies resulted in the model achieving a 99.89% accuracy, 98.67% precision, and 95.76% recall. The F1-score of 96.78% shows a balanced performance in precision versus recall. This convergence of AI and cloud technologies promotes accurate fraud transaction detection with reduced false-positive responses and the possibility of continuous adaptation to new fraud schemes. All said, Cloud-Based AI with FNNs is a system that is most potent to secure financial transactions and customers' interests in the banking sector.
Copyright (c) 2021 Charles Ubagaram, Karthick.M (Author) https://creativecommons.org/licenses/by/4.0
Real-Time Path Planning for IoT-Enabled Autonomous Vehicle Robotics Using RRT and A * Algorithms
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 the environment rapidly to derive an initial feasible path across the configuration space. Following the developments of RRT paths, the A algorithm* will address topics brought about by their construction in order for the route to be smooth, efficient, and have the shortest length. A synergism between the two techniques makes these systems adapt in real time to changes in the environment and in transportation conditions while preserving computational economy. From the performance evaluation, joining the strategy increases these very important parameters, such as the energy consumption, path length, and the time to reach the destination, by a huge percentage. The model consumes energy that is reduced by about 23% in comparison with conventional approaches, decreases path length by 12-15% and decreases time to objective up to 50%. These results indicate that the RRT + A* model works very well to enhance the effectiveness and efficiency of autonomous vehicle navigation in changing conditions. This framework can be used in applications like robotics and autonomous driving, and it represents a viable answer for real-time energy-efficient optimal path planning.
Copyright (c) 2021 Nagendra Kumar Musham, R.Hemnath (Author) https://creativecommons.org/licenses/by/4.0
High- and Low-Frequency TENS with Paravertebral Ozone Therapy for Chronic Low Back Pain and Radiculopathy: A Pilot Study
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 study was conducted with 88 consecutive patients meeting the inclusion criteria. Participants underwent 12 sessions of combined HLF-TENS and POT, without a control group. Pain intensity, neuropathic symptoms, and disability were assessed using the Numeric Rating Scale (NRS); the modified Michigan Neuropathy Screening Instrument (MNSI), and the modified Oswestry Disability Index (ODI), respectively. Assessments were performed at baseline, midpoint, and post-treatment, with long-term follow-up (1–2 years) via telephone interviews. Results: The study included 35 men (40%) and 53 women (60%), mean age of 51.3 years (range 20–80). Post-treatment, 80% of participants showed statistically significant improvements in pain, neuropathic symptoms, and disability. Pain NRS scores decreased from 8.58 to 1.64, neuropathic symptom scores from 7.34 to 1.14, and ODI scores from 8.05 to 2.12 (p< 0.001). At long-term follow-up (1–2 years), 80% of respondents remained asymptomatic, with no adverse effects reported. Conclusions: The combination of HLF-TENS and POT significantly reduced pain, neuropathic symptoms, and disability in CLBP patients with radiculopathy. These findings suggest a promising, non-invasive treatment option; however, randomized controlled trials are necessary to confirm efficacy.
Transcutaneous electrical nerve stimulation
Copyright (c) 2025 Reinaldo Milla (Author) https://creativecommons.org/licenses/by/4.0
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 developing the company's annual budget. Over time, a company's estimation could suffer if its sales projections are consistently inaccurate. Sales forecasting therefore affects the entire company to improve their overall growth strategy. An essential part of any business's sales operations is sale forecasting. For a business to supply the necessary quantity at the appropriate time, an accurate sales forecast is essential. Executives use the predictions to assess future performance and plan for organizational expansion. In this study, we use the machine learning techniques of naive forecasting and linear regression to try and predict a retail company's sales. The difference between the linear regression and naïve forecasting approaches is demonstrated using a computational example, and we have found that the linear regression yields better results than the naïve forecasting approaches. Additionally, we used the ARIMA model for the linear regression approach to forecast the sales for the upcoming five days.
Copyright (c) 2025 Dr. Manish Kumar (Author) https://creativecommons.org/licenses/by/4.0
A Fuzzy Logic-Based Decision Support System for Early Detection of COVID-19: A Review and Comparative Analysis
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 systematic review of published fuzzy logic models for the COVID-19 diagnosis along with details of their methodologies, accuracy, and clinical usability. Results support that fuzzy logic systems improve diagnostic efficiency, lessen healthcare pathways, and enable decision-making in a timely manner.
Copyright (c) 2025 Nidhi Mishra (Author) https://creativecommons.org/licenses/by/4.0
Optimizing Inventory Management: Strategies for Deteriorating Items with Time-Based Demand
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 improving supply chain efficiency. The analysis highlights the importance of dynamic pricing, fractional backlogging, and demand forecasting in inventory control systems. Practical implications for retailers, manufacturers, and logistics managers are discussed, along with future research directions.
Copyright (c) 2025 B V Padamwar BVP (Author) https://creativecommons.org/licenses/by/4.0
Assessing Stakeholder Awareness and Perception of NEP-2020: A Study on Policy Implementation and challenges
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 survey. The findings reveal a low level of awareness and mixed perceptions regarding the policy. The study suggests targeted awareness programs and parental engagement initiatives for effective policy implementation.
Copyright (c) 2025 Jagirdar Lubna Batool Batool (Author) https://creativecommons.org/licenses/by/4.0
India-UK Relations Roadmap 2030 And Beyond: A Comprehensive Strategic Vision
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 roadmap serves as a forward-looking framework to deepen collaboration. The paper critically examines the five key pillars of the roadmap: economic cooperation, with a focus on the much-anticipated India-UK Free Trade Agreement (FTA); defense and security, including intelligence-sharing and Indo-Pacific cooperation; health and innovation, emphasizing joint research, pandemic preparedness and digital healthcare; climate action, highlighting commitments under COP26 and joint green energy initiatives; and people-to-people ties, driven by diaspora contributions, education partnerships, and evolving immigration policies. Additionally, the paper explores the challenges that may hinder progress, such as unresolved trade barriers, geopolitical divergences, security trust deficits, post-Brexit uncertainties, and strategic misalignments in the Indo-Pacific. Beyond 2030, India-UK relations will need strategic recalibration to adapt to emerging global trends. The paper examines possible future scenarios—ranging from strengthened economic integration to potential geopolitical divergences—and outlines strategic pathways to institutionalize cooperation in an evolving multipolar world. The significance of this study lies in its comprehensive analysis of how India and the UK can navigate these opportunities and challenges to create a sustainable, forward-thinking and adaptive partnership beyond 2030. It aims to provide strategic insights into how the roadmap can serve as a living document, evolving with emerging global realities, and evolve beyond 2030, ensuring that bilateral ties remain dynamic, resilient, and mutually beneficial.
Copyright (c) 2025 SALONI BAL, Akansha Khaiba (Author) https://creativecommons.org/licenses/by/4.0
Exploring Teachers' Perceptions of Parent-Teacher Partnership to Support Learners with Intellectual Disabilities in Primary Schools
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 hamper effective partnerships between parents and teachers in mainstream primary schools, a certain level of teamwork exists between parents and teachers, with more opportunities – yet to be fully explored – to strengthen this partnership further. Hence, a need to harness various strategies to improve parent-teacher relationships to create a more functional environment that meets the needs of learners with intellectual disabilities.
Copyright (c) 2025 Mahlape Tseeke (Author) https://creativecommons.org/licenses/by/4.0
Relationship between Purpose in Life and Psychological Distress among Older Adults
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 females. Results reveal a significant negative correlation between purpose in life and psychological distress, indicating that higher purpose in life is associated with lower psychological distress. Furthermore, a t-test analysis shows no significant gender difference in purpose in life, suggesting similar perceptions of life purpose among male and female participants. However, a significant gender difference is observed in psychological well-being with females reporting higher levels of distress than males. These findings highlight the protective role of purpose in life against psychological distress and the need for gender-sensitive interventions to support older adults' mental well-being.
Copyright (c) 2024 SHIMIL (Author) https://creativecommons.org/licenses/by/4.0