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Improved Indian currency recognition: neighbourhood-centred image processing and CNNs with region of pixel selection techniques
The paper proposes an improved approach for Indian currency recognition using neighbourhood-centred image processing and convolutional neural networks (CNNs) with region of pixel selection techniques. The method includes image pre-processing steps such as noise reduction, contrast enhancement, and resizing. A neighbourhood-centred image processing technique is applied to capture contextual information from local neighbourhoods around each pixel. A CNN-based model is then trained on the pre-processed images to learn discriminative features for currency recognition. To enhance accuracy and efficiency, a region of pixel selection technique is introduced to select only relevant regions of interest for CNN training and inference, reducing computational overhead. Experimental results demonstrate the effectiveness of the proposed approach, achieving high accuracy in currency recognition and improved efficiency in terms of computational time and memory requirements. The proposed method has potential applications in automated cash-handling machines, vending machines, and mobile payment systems where reliable currency recognition is essential. Copyright 2025 Inderscience Enterprises Ltd. -
Eco-market dynamics: deciphering Indias agricultural pricing in the context of carbon emissions and inflation
This study explores the intricate relationship between carbon emissions, agricultural commodity prices, and inflation in India. Using monthly data from January 2014 to March 2022 and structural vector auto regression (SVAR) modelling, the analysis reveals diverse dynamics among key; commodities. An inverse relationship is found between wheat prices and inflation, suggesting consumer benefits. Turmeric shows a strong negative correlation, indicating unique market behaviour, while refined soybean oil and cotton prices exhibit minimal negative impacts. In contrast, crude palm oil prices positively influence inflation. A noteworthy finding is the negative correlation between carbon emissions and inflation, highlighting the environmental-economic linkage. These insights enhance understanding of how specific agricultural prices interact with inflation, and how environmental variables play a role. The findings can guide evidence-based policies for agricultural stability, environmental sustainability, and economic growth in India. The implications extend globally, offering valuable insights for developing economies facing similar challenges. Copyright 2025 Inderscience Enterprises Ltd. -
AMAA-GMM: adaptive Mexican axolotl algorithm based enhanced Gaussian mixture model to segment the cervigram images
Colposcopy is a crucial imaging technique for finding cervical abnormalities. Colposcopic image evaluation, particularly the accurate delineation of the cervix region, has considerable medical significance. Before segmenting the cervical region, specular reflection removal is an efficient approach. Cervical cancer can be found using a visual check with acetic acid that turns precancerous and cancerous areas white and these could be viewed as signs of abnormalities. Similarly, bright white regions known as specular reflections obstruct the identification of aceto-white areas and should therefore be removed. So, in this paper, specular reflection removal with segmenting the cervix region in a colposcopy image is proposed. The proposed approach consists of two main stages, namely, pre-processing and segmentation. In the pre-processing stage, specular reflections are detected and removed using a swin transformer. After that, cervical regions are segmented using an enhanced Gaussian mixture model (EGMM). For better segmentation accuracy, the best parameters of GMM are chosen via the adaptive Mexican axolotl optimisation (AMAO) algorithm. The performance of the proposed approach is analysed based on accuracy, sensitivity, specificity, Jaccard index, and dice coefficient, and the efficiency of the suggested strategy is compared with various methods. Copyright 2026 Inderscience Enterprises Ltd. -
Cyberdeviance among students a multidimensional scaling approach
Cyberdeviance off late has been gaining a lot of attention because of the increased use. Educational institutions have also made the internet available to its student to improve their exposure to various educational information. Hence, it becomes essential to identify a model that helps understand college factors to cyberdivert. The study focused on assessing whether college students are involved in cyberdeviation and the demographic effect on internet behaviour and cyberdeviance. The multidimensional approach was used to understand cyberdeviance. Data were collected from 264 students using convenience sampling in Bengaluru city, India. The study found that the respondents prefer to use the internet mainly for games and prefer least for theft, harassment, adult content, and hacking. They misused the internet due to the fear of unemployment and were involved in internet fraud to deploy knowledge. Copyright 2025 Inderscience Enterprises Ltd. -
Privacy over instant messaging platforms: are users making the right decisions?
This article explores the impact of perceived vulnerability, self-efficacy, resistance to change, and habit on users perception of privacy over users intention to use messaging platforms. The conceptual model includes perceived vulnerability, self-efficacy, resistance to change, habit, and its impact on users perception of privacy over users intention to use messaging platforms. A structural equation and hierarchical regression model were used for data analysis. The results show that age and profession affect peoples decision of shifting to a different platform significantly. The study is based on a few specific instant messaging platforms at one particular point in time and is undertaken in India; hence, the findings cannot be extended/applicable to other countries. The paper discusses the factors impacting the users sensitivity to data privacy while using a communication application through an electronic device, especially a mobile phone. Copyright 2025 Inderscience Enterprises Ltd. -
Comparative study of benchmarking models for higher education institutions
Benchmarking is a systematic and ongoing process of assessing an organisations business processes against those of business process leaders to obtain data that will enable the firm to take corrective action to enhance performance (Pattison, 1993). Eight benchmarking models, namely the European Foundation for Quality Management (EFQM) excellence model, American Productivity and Quality Centre (APQC) consortium framework, Commonwealth Higher Education Management Service (CHEMS) model, Mckinnon model, Henderson-Smart et al. model, educational development efficiency (EDE) model, Tee benchmarking model, and fourth generation balanced scorecard method are being studied, analysed, evaluated and compared. While most models effectiveness depends on the cooperation and participation of benchmarking partners, few depends on secondary data are an exception. Most benchmarking models lack the implementation and are fluid and flexible models. This comparative benchmarking study helps an institution understand which benchmarking model needs to be used, as the study details each models essential features, advantages, and limitations. Copyright 2025 Inderscience Enterprises Ltd. -
Detection and classification of lung cancer using deep neural network
Lung cancers hold a critical spot among the reasons for most cancer deaths among humans. The better way to maximise the survival rate is the detection of cancer at the earliest. But existing traditional techniques are time-consuming and error-prone. This study is a significant and efficient method for the detection and classification of lung cancer into large cell carcinomas, small cell, adenocarcinoma, squamous cell carcinomas, or benign respectively. In the proposed technique, a novel algorithm is implemented to generate the Image patches from whole slide histopathological images. Then, histogram normalisation is carried out to remove noise and enhance the image. Then a novel extended Mobius transformation technique is used for image augmentation. Finally, Dense EfficientNetB7 is trained to extract the features for the detection and classification of lung cancer. The performance of the proposed technique is proved more efficient and par with histologists attaining an accuracy of 98.87%. Copyright 2025 Inderscience Enterprises Ltd. -
Exploring the impact of influencer marketing strategies on sustainability in the fashion industry
Social medias explosive expansion has forced firms to rethink their marketing tactics to communicate with a wider range of customers by providing value and enabling two-way dialogue. Influencers may contribute to increasing brand awareness and giving value to companies when they work with brands and the appropriate target audience. This study aims to evaluate the influence of source credibility dimensions such as trustworthiness, attractiveness, and perceived expertise on consumer attitudes toward fashion influencers and to assess how these attitudes impact consumers intentions to make purchases and provide recommendations. Also, determine the direct impacts of source credibility on these purchase and recommendation intentions. The research includes 342 individuals who follow a famous fashion influencer in India by using the convenient sampling method. Hierarchical regression analysis has been performed on data using SPSS. The outcome of the study shows the effect of trustworthiness and perceived expertise on attitudes toward influencers in the fashion industry. Copyright 2025 Inderscience Enterprises Ltd. -
Adoption barriers of blockchain technology in Indian automotive supply chain: an MCDM approach
The Indian automobile industry faces intense competition from international firms, making technological upgrades essential. Blockchain, known for powering cryptocurrencies, offers a transparent, immutable, and decentralised database beneficial for supply chains. Despite its potential and widespread use in other sectors, the Indian automobile industry has been slow to adopt it. This paper examines the barriers to blockchain adoption in this sector using Delphi and DEMATEL techniques. The study reveals that trust-building among partners and collaboration challenges due to blockchains complexity are the primary obstacles hindering adoption. These barriers make it difficult for firms to decide on implementing blockchain technology in their supply chains, with other obstacles being secondary but interconnected. Overcoming these obstacles requires transforming company cultures, establishing efficient governance systems, and ensuring transparent data disclosure. Governments can support this by stimulating innovation through legislation and creating blockchain sandboxes for safe testing, helping to develop standards with organisations like ISO and IEEE. 2025 Inderscience Publishers. All rights reserved. -
Social capital as a catalyst for leadership excellence: the mediating role of institutional reputation in Indian higher education
Drawing upon social capital theory, this study aims to investigate the impact of social capital on leadership effectiveness through mediating role of institutional reputation in higher educational institution. Data were collected from 310 academic leaders, including HODs, area chairs, and deans, using a structured online questionnaire. The sampling technique used was purposive sampling. Partial least squares structural equation modelling (PLS-SEM) was employed for analysis. The results indicate a significant positive relationship between social capital and leadership effectiveness, highlighting the importance of interpersonal trust, collaborative culture, and professional networks in influencing strategic vision, decision-making, and transformational leadership skills. Moreover, institutional reputation is identified as a partial mediator in this relationship, indicating that robust social capital not only improves direct leadership outcomes but also enhances the perceived credibility and prestige of institutions, hence strengthening leadership legitimacy and influence. This study enhances the sparse empirical literature linking social capital and leadership within the Indian higher education sector and provides pragmatic insights for policymakers and institutional leaders aiming to cultivate trust-based cultures and reputational capital. The study concludes with ideas for cultivating social capital via inclusive governance, faculty involvement, and external collaborations to improve leadership efficacy and ensure sustained institutional success. Copyright 2025 Inderscience Enterprises Ltd. -
Technopedagogy in teacher education: exploring challenges and possibilities
Digital technologies allowed teachers to overcome spatial and temporal limitations in education, particularly during the COVID-19 pandemic-imposed restrictions. While access to technological resources proved beneficial, teachers faced initial challenges. It is crucial to address the significance of digital education training in teacher education institutions, particularly in implementing the Integrated Teacher Education Programme based on the National Education Policy 2020 in India. This study explores approaches to techno-pedagogical skills in teacher education in Kerala, India, and the potential solutions to bridge the digital gap between training and teaching in the classroom. The researchers have used qualitative methods to gather and analyse data, including archival research and interviews with teacher educators and student teachers in the Bachelor of Education Programme. The findings indicate an urgent need for infrastructural upgrades and continuous professional development practices. Copyright 2025 Inderscience Enterprises Ltd. -
A systematic literature network analysis approach to assess the topology of modern-era supply chain risk management research
Over the past decade, there has been a significant increase in research on supply chain risk management (SCRM). This review uses a systematic literature network analysis to provide an overview of the SCRM research landscape, with emphasis on optimisation approaches, mathematical modelling tools, and the identification of seminal studies and relevant keywords used in SCRM research. However, there are few quantitative models that represent the relationship between supply chain surplus, sustainability, and resilience in SCRM literature. The study has limitations since it only sources from a single database, and more clarity is needed on the effectiveness of optimisation in SCRM, which can be further evaluated through case studies and empirical studies. Copyright 2025 Inderscience Enterprises Ltd. -
Brand protection in Indias digital economy: trademarks vs. competition regulation
The digital economy in India has significantly impacted brand protection, with the need for robust trademark protection intensifying to combat issues like counterfeiting, cybersquatting, and unauthorised use. Competition regulation aims to ensure fair market practices, prevent monopolistic behaviour, and foster innovation. This study examines the legislative and judicial framework governing trademarks in India, highlighting key provisions under the Trade Marks Act, of 1999, and their application in the digital context. It also assesses the role of the Competition Commission of India (CCI) in addressing anti-competitive practices. The study identifies tensions and synergies between trademark protection and competition regulation, examining how digital platforms, e-commerce, and social media influence these legal domains. Comparing the study with jurisdictions like the EU and the USA, the paper proposes a balanced approach that harmonises trademark enforcement with competition law principles to ensure brand protection efforts do not stifle competition and innovation in Indias burgeoning digital economy. Recommendations include policy reforms, enhanced cooperation between regulatory bodies, and the adoption of technology-driven solutions to safeguard brands while promoting a competitive and fair digital marketplace. Copyright 2025 Inderscience Enterprises Ltd. -
Predicting emotional intelligence, creative performance and knowledge management in higher education using multiple regression
Higher education institutions are paramount in emerging nations like India. Post-globalisation, India witnessed the growth of HEIs, especially in the private sector. However, today most of the institutions are struggling for their existence. One of the most vital reasons for such a staggering performance is the absence of creativity. It will not be an exaggeration to say that the present era is the era of creativity and performance and organisations that cant perform are bound to perish. Creativity can be nurtured and yield success only if it is supported by the emotional intelligence (EI) of the employees and knowledge management (KM) processes. The current paper explored the nexus between emotional intelligence, knowledge management processes and creative performance in HEIs in India and implied that though emotional intelligence affects creative performance, the impact gets manifolded in the presence of the knowledge management process. Copyright 2025 Inderscience Enterprises Ltd. -
Artificial intelligence in higher education: the challenges, opportunities and the road ahead
This paper investigates to deliver an overview of literature from 2012 to 2023 on the phenomena of implementing artificial intelligence in education (AIEd). With the help of the Scopus indexing database, data from 441 articles were extracted, analysed based on the keywords and preliminary reading and synthesised according to explicit inclusion and exclusion criteria and article compilation was on the parameters of scientific procedures and rationales for systematic literature review protocol (SPAR4SLR). Drawing on the recent literature depicts that the inception of artificial intelligence in education is still in its initial stage and much research is required. This article implies that although there are benefits and challenges talked about in the article delving into the application of AIEd in higher educations system of teaching and learning that shall lead the education system to newfound intelligence and automation, however, things are at the very initial stage and filled with conjectures. The findings demonstrate that the artificial intelligence-based teaching and learning phenomenon has a bright future as educational institutes understand its upcoming impact. The greatest challenge for educational institutes now is to start planning, designing, developing and implementing artificial intelligence-based courses for multidisciplinary and holistic training for future employees. Copyright 2025 Inderscience Enterprises Ltd. -
Scientific competence and acquisition challenges in education managed by analytics
Integration of instructional, informational, and communication technology underpins modern higher education. After decades without computer networks, these technologies have transformed learning. E-learning has transformed the education sector, solving its problems. The similarities between technology and cognition make this change noteworthy. Artificial intelligence-inspired model-based reinforcement learning lets agents predict states and outcomes across activities and settings to modify their behaviour. The human brain has similar mechanisms, especially in model selection, which is a fascinating mystery. This study examined the brains model selection process and found that sensory prediction errors motivate the brain to choose between computational models. The theory was contrasted with internal modelling and incentive predictive performance to show how prediction errors influence computational model selection. The brain can choose an internal validation learning model based on incentive prediction mistakes, as empirical evidence demonstrates that the policy gradient method matches these models. These models were intended to address higher education issues like administration, academic delivery, instructional design, and ethics. The report also suggested that e-learning could help solve industry issues like student concentration on campuses, brain drain, and resource shortages. This research shows how technology can change higher education and the future of learning. Copyright 2025 Inderscience Enterprises Ltd. -
A case study on challenges, opportunities and sustainable development of waste management in India
Waste management solutions for a country as large and densely populated as India with several infrastructure bottlenecks required a thorough understanding of the local context, waste generation patterns, and available infrastructure. Waste Ventures India invested in research and development to develop innovative waste management solutions to address challenges faced in India. By collecting and analysing data on waste generation patterns and available infrastructure, the company was able to design waste management systems that were tailored to Indian system. This case study highlights the importance of using evidence to inform policies and practices in waste management. Companies and governments can use data to design waste management systems that are effective, sustainable, and tailored to the needs of specific communities. This case guides analysis on how to ensure value for the stakeholders; how to identify benefits on a global and local front; and was the business scalable to ensure sustained impact. Copyright 2025 Inderscience Enterprises Ltd. -
Digital entrepreneurship in modern techno world: mapping the literature and future research agenda
Digital entrepreneurship (DE) leverages internet services for business and financial gain. This study reviews past research, highlighting trends and gaps. Using the POWER framework and PRISMA techniques, 733 articles were analysed with VOSViewer and manual text analysis. Key findings include 2023 having the most publications, the UK leading in published articles, the journal Technological Forecasting for Social Change having the highest impact, and A. Ghezzi being the most influential author. Trending topics are entrepreneurs, digital entrepreneurship, and sustainability. Emerging themes include digital entrepreneurship ecosystems, opportunities for women and education, entrepreneurial funding, government adoption, and digital technologies. Future research should focus on entrepreneurial education, AI innovations, digital venture performance, and IoT adoption. Frameworks like lean start-up, business model innovation, and value creation can enhance DE performance, with further exploration encouraged by the identified future research agenda. Copyright 2026 Inderscience Enterprises Ltd. -
Digital marketing effectiveness and success factors for small and medium enterprises
Digital marketing is crucial for the organisation success. Therefore, this paper explores how research in digital marketing can enhance marketing strategies, drive consumer engagement and boost revenue generation. It highlights how businesses of varying sizes can leverage these insights to thrive in the competitive online market. The study conducts a bibliometric analysis of digital marketing research, tracing its evolution from inception to present day. Focusing on authorship patterns, international collaborations, and geographical influences, it assesses the potential future impact of research in this area. Using the Scopus database, 1,126 relevant articles were selected for detailed analysis. Employing the R Software and bibliometric package, an extensive scientific mapping analysis was performed. The findings present a thorough exploration of author contributions, source evaluations, document analytics, cluster mapping-citations, and collaborative networks. These findings provide valuable guidance for researchers and practitioners interested in emerging domain of digital marketing. Copyright 2026 Inderscience Enterprises Ltd. -
A frequent itemset generation approach in data mining using transaction-labelling dynamic itemset counting method
A significant amount of data is generated, gathered, stored, and evaluated in real-world applications as a result of technology breakthroughs. Data mining (DM) combines a number of disciplines to efficiently discover hidden patterns from vast archives of historical information. To significantly reduce complexities associated with data, the proposed method, transaction-labelling dynamic itemset counting (TL-DIC), utilises a labelling approach on the given transactional database to logically arrange and process the underlying transactions. This method generates frequent itemsets thereby improving the performance of conventional dynamic itemset counting (DIC) method. Based on experimental findings, the average scan count in DIC and M-Apriori is 4% and 3.66%, respectively higher than TL-DIC, for different support counts. TL-DIC executes 20% and 16% quicker than DIC and M-Apriori, respectively, in terms of execution time. These results validate the proposed approachs efficacy in creating frequent itemsets from large datasets. Copyright 2025 Inderscience Enterprises Ltd.