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Sustainable tourism management : Issues and challenges of eco wildlife resorts in karnataka
Sustainable tourism principles comprise of visitor satisfaction, the economic newlinesustainability of the industry, environment conservation, socio-cultural and economic newlinedevelopment of local communities. The tourism industry has to consider all these elements while developing any form of tourism for its long-term sustainability. Eco and wildlife resorts are one of the prominent and attractive segments of the accommodation sector. It has a major implication for implementing sustainable tourism practices in their daily operations since they are set close to nature and reside in pristine wildlife regions. It is inevitable for eco and wildlife tourism, to consider all newlinethe elements of sustainable tourism practices and to implement it in their day to day newlineactivities. At the same time, they might have to face issues and challenges in newlineimplementing sustainable practices. So, the main objective of the research is to newlineunderstand operational issues and challenges of eco and wildlife resorts in achieving newlinesustainable tourism principles. The purpose of the study is to investigate the issues and challenges faced by eco and wildlife resorts in implementing sustainable tourism practices and understanding the indicators used by the resorts to measure their sustainable tourism newlinepractices. The scope of the study covers selected eco and wildlife resorts in Karnataka because most eco and wildlife reserve areas are shared by pristine natural areas and are located near villages. The targeted respondents of the study are eco and wildlife resort managers and visitors of eco and wildlife resorts. Based on purposive sampling, 30 resorts are selected for the study, and 410 visitors are selected based on convenient sampling technique. The study employs a mixed-method research design. newlineTriangulation design is used in the study. The study adopted a tool to identify the newlinesustainable tourism indicators used by the resorts to measuring their sustainable newlinetourism practices. -
Sustainable tourism management: Issues and challenges of eco and wildlife resorts in Karnataka
Sustainable tourism principles comprise of visitor satisfaction, the economic sustainability of the industry, environment conservation, socio-cultural and economic development of local communities. The tourism industry has to consider all these elements while developing any form of tourism for its long-term sustainability. Eco and wildlife resorts are one of the prominent and attractive segments of the accommodation sector. It has a major implication for implementing sustainable tourism practices in their daily operations since they are set close to nature and reside in pristine wildlife regions. It is inevitable for eco and wildlife tourism, to consider all the elements of sustainable tourism practices and to implement it in their day to day activities. At the same time, they might have to face issues and challenges in implementing sustainable practices. So, the main objective of the research is to understand operational issues and challenges of eco and wildlife resorts in achieving sustainable tourism principles. -
SUSTAINABLE TOURISM PRACTICES: A PERCEPTION of BACKWATER TOURISM DESTINATIONS in SOUTH KERALA, INDIA
The Tourism Industry in South Kerala focuses more on Houseboat Tourism and Backwater Tourism. The unique, natural features set this destination apart from nearby places, as backwater destinations are rich in numerous natural resources. The sustainable development of these resources will highly enhance the livelihood of the communities in the backwater regions. They will be able to attract tourists seeking unique backwater experiences. Therefore, this article intends to comprehend the stakeholders' perceptions on Sustainable Tourism Development in the backwater destinations of South Kerala in India. A total of 277 respondents participated in the research and the study adopted a quantitative research design, while considering the influence of various factors on the Economic, Social and Environmental Sustainability. The data gathered from the study illustrated that the perception of stakeholders about Sustainable Tourism Development varied across different groups. Hence, all the stakeholders in the Tourism Industry need to work together, as this coordination will help to strengthen future development plans, in order to minimize the negative impacts of tourism in the backwater destinations of South Kerala. The study has also identified key turning points that will help to reshape the Sustainable Development of backwater tourism destinations of South Kerala. 2021 Editura Universitatii din Oradea. All rights reserved. -
Sustainable Waste Management and Womens Empowerment
Waste management is a problem faced by major cities. Rural migration to urban areas created unplanned residential areas and high population density, and temporary living structures have a direct impact on poor waste management systems in urban areas. From September 2020 until February 2021, a case study was conducted (the first lockdown period of the COVID-19 Pandemic) among women members from an urban slum in Bangalore with objectives to understand the prevalent process of waste management and comprehend the association between womens empowerment and sustainable waste management in a slum community. The purposive sampling technique was applied to select 10 women members of the slum community for this community-based participatory research as co-researchers from the slum community, along with all stakeholders. The results show that the women members could implement the immediate plans on waste management, including educating their neighbours on waste management, to ensure that a large part of the society they are living in is aware of it. The women members demonstrated their motivation and willingness in their actions in the slum neighbourhood concerning sustainable waste management. They applied their participatory activities to empower other women in the area by focussing on every stretch of the slum and educating on the management of waste. All the actions by the women members in the urban slum community and the stakeholders of waste management in that community intend to support the quality of life and strengthen the resilience to climate change through sustainable waste-management and are reflected in SDG 3, SDG 5, SDG 11, and SDG 13. 2024 CRC Press. -
Sustainable X-Band Microwave Absorber Using Tea Waste and Recycled Carbon Composites
This paper introduces an innovative eco-friendly flat microwave absorber designed for X-band applications, utilizing plant waste and recycled materials, thereby contributing to a circular economy. The composite material is composed of 75 % used tea powder and 25 % carbon sourced from discarded batteries. The electromagnetic (EM) absorption performance of the proposed composite has been characterized, revealing enhanced absorption capabilities, averaging around 26.2 % for a thickness of 5 mm, compared to a 100 % tea waste configuration across the X-band frequency range. Furthermore, the results indicate that EM absorption improves with increasing frequency. The environmental advantages of this composite, including waste reduction and a minimal carbon footprint, position it as an attractive alternative to conventional RF absorbers. This sustainable solution shows promise for applications in EM interference shielding and microwave energy harvesting. 2025 European Association on Antennas and Propagation. -
Sustaining livelihoods and culture through tourism development: The case of sriniketan in West Bengal, India
The rural area of Sriniketan in West Bengal, India is full of cultural embodiments that can not only serve as a base to develop tourism but also generate sustainable livelihoods. However, the Sriniketan region suffers from chronic poverty and its unique culture is getting depleted thanks to the lack of awareness and interest among locals. With the help of the DFID Sustainable Livelihood Framework (DFID-SLF), this study tries to analyse the contributions that culture-based tourism can make towards generating sustainable livelihoods at Sriniketan. A modified SLF has been prepared with an added element of cultural capital as a contribution to the existing livelihood literature and guiding sheet for future practitioners. Based on the primary (in-depth interviews of fifteen households and five key respondents) and secondary data collected, this paper concludes that tourism development in Sriniketan can not only aid its cultural preservation but also generate an alternate source of livelihood and thereby, making both (culture and livelihoods) sustainable 2023, IGI Global. All rights reserved. -
Sustaining Sustainable: Investigating the Full Spectrum of Food Waste, from Production Through Consumption to Disposal
Purpose: The purpose of this research is to explore the primary factors that contribute to food waste. Additionally, it creates practical strategies to cope with food waste and encourages to perform sustainable practices to improve the environment. Additionally, the study presents an analytical framework for supply chain problems as well as the methods that are environmentally friendly. Methodology: The research begins by defining how sustainable development should be incorporated in the hospitality sector and by briefly outlining its attributes. Next, it discusses the expanding interest in supply chain management and outlines an overview of the breadth of academic research on sustainability in the literature related to the hotel industry. Findings: The paper examines the enormous ecological and economic effects of food waste, including how it contributes to the adverse global warming, the dwindling of natural resources, and also the loss of worthwhile financial investments. Additionally, it highlights the social effects of food wastage, such as how it contributes to gaps in access to nourishing foods and food insecurity. Research Limitations: It attempts to shed light on the scope of food loss, identify major contributing variables, and suggest methods to reduce food loss along the whole supply chain through an examination of current literature and data. Practical Implication: The practical application of this research is to offer evidence-based insights and practical recommendations to policymakers, organizations, and people with an aim to decrease food waste and enhance the effectiveness of the food system. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Sustaining teacher social-emotional competence: a systematic review of implementation and retention strategies; [??????????? ?????????-????????????? ?????????????? ????????: ??????????????? ????? ????????? ?????????? ? ???????????]
Social-emotional competence (SEC) refers to educators capacity to regulate emotions, sustain psychological resilience, and cultivate constructive relationships with students, colleagues, and school leadership. Elevated levels of SEC among teachers are strongly associated with enhanced well-being, emotionally supportive classrooms, and improved student engagement and achievement. Despite growing attention to SEC development initiatives, critical gaps remain regarding demographic variability in outcomes, optimal implementation strategies, and enduring institutional barriers. This systematic review, conducted in accordance with PRISMA guidelines, screened 1519 studies published between 2012 and 2024, yielding 16 peer-reviewed articles that met the inclusion criteria. Findings demonstrate that SEC interventions reliably enhance educators emotional regulation, mindfulness, and overall psychological well-being, irrespective of gender, professional experience, or cultural context. However, the long-term sustainability of these benefits is contingent upon enabling school environments, strong leadership, continuous professional development, and adequate resource allocation. Implementation challenges including time constraints, inconsistent program fidelity, and varying levels of teacher readiness underscore the need for adaptive, context-sensitive models. This review provides evidence-based recommendations for the effective design, integration, and sustained impact of SEC programs across diverse educational settings. Ved A., Kareem J., 2026. -
Sustaining Tomorrow: Strategies for Long-Term Environmental Governance
Long-term environmental governance (EG) is crucial for addressing global environmental challenges such as climate change, biodiversity loss, and resource depletion. This chapter explores the principles, challenges, and emerging trends in EG, emphasizing the necessity of sustainability-focused policies that transcend short-term interests. It discusses key governance frameworks, including the Paris Agreement and the Convention on Biological Diversity (CBD), highlighting their successes and limitations. The study underscores the role of corporate responsibility, technological innovations, and collaborative governance in promoting sustainable environmental management. It also identifies political, economic, and global disparities as significant barriers to effective governance. This chapter concludes with policy recommendations advocating adaptive governance structures, enhanced international cooperation, and localized sustainability initiatives. By integrating scientific advancements, stakeholder engagement, and long-term policy planning, EG can ensure a balanced approach to development and ecological preservation, securing a sustainable future for coming generations. 2026 John Wiley & Sons Ltd. All rights reserved. -
SVD-CLAHE boosting and balanced loss function for Covid-19 detection from an imbalanced Chest X-Ray dataset
Covid-19 disease has had a disastrous effect on the health of the global population, for the last two years. Automatic early detection of Covid-19 disease from Chest X-Ray (CXR) images is a very crucial step for human survival against Covid-19. In this paper, we propose a novel data-augmentation technique, called SVD-CLAHE Boosting and a novel loss function Balanced Weighted Categorical Cross Entropy (BWCCE), in order to detect Covid 19 disease efficiently from a highly class-imbalanced Chest X-Ray image dataset. Our proposed SVD-CLAHE Boosting method is comprised of both oversampling and under-sampling methods. First, a novel Singular Value Decomposition (SVD) based contrast enhancement and Contrast Limited Adaptive Histogram Equalization (CLAHE) methods are employed for oversampling the data in minor classes. Simultaneously, a Random Under Sampling (RUS) method is incorporated in major classes, so that the number of images per class will be more balanced. Thereafter, Balanced Weighted Categorical Cross Entropy (BWCCE) loss function is proposed in order to further reduce small class imbalance after SVD-CLAHE Boosting. Experimental results reveal that ResNet-50 model on the augmented dataset (by SVD-CLAHE Boosting), along with BWCCE loss function, achieved 95% F1 score, 94% accuracy, 95% recall, 96% precision and 96% AUC, which is far better than the results by other conventional Convolutional Neural Network (CNN) models like InceptionV3, DenseNet-121, Xception etc. as well as other existing models like Covid-Lite and Covid-Net. Hence, our proposed framework outperforms other existing methods for Covid-19 detection. Furthermore, the same experiment is conducted on VGG-19 model in order to check the validity of our proposed framework. Both ResNet-50 and VGG-19 model are pre-trained on the ImageNet dataset. We publicly shared our proposed augmented dataset on Kaggle website (https://www.kaggle.com/tr1gg3rtrash/balanced-augmented-covid-cxr-dataset), so that any research community can widely utilize this dataset. Our code is available on GitHub website online (https://github.com/MrinalTyagi/SVD-CLAHE-and-BWCCE). 2022 Elsevier Ltd -
SVM Based AutoEncoder for Detecting Dementia in Young Adults
Dementia's impact on cognitive function necessitates timely diagnosis for effective intervention. Understanding the need for timely detection, the proposed work integrates SVM's decision boundary determination and autoencoder's noise reduction capabilities. The proposed work advances in dementia detection in young adult. Results indicate promising performance, with the model achieving high accuracy around 85.33%. The ROC curve illustrates a balanced trade-off between sensitivity and specificity, while the precision-recall curve highlights effective classification. Importantly, the model surpasses existing literature, underscoring its practical utility. While acknowledging limitations, such as parameter fine-tuning, this study lays the groundwork for refining and expanding this innovative methodology. In summary, this research contributes to the urgent field of early dementia detection, potentially transforming patient care and intervention strategies. 2023 IEEE. -
SVM Ensemble for Insurance Data Analysis
Data mining is the process of analysing data from different perspectives and summarizing it into useful information. Companies with a strong consumer focus use data mining. The information getting from datamining is useful to increase revenue and reduce overall costs of the company. It is applied in retail field, financial sector, communication media, and in marketing organizations. Datamining facilitate these companies to determine relationships among company internal factors such as price, product positioning, or staff skills, and external factors such as competition in products, economic indicators, and customer demographics. Ensemble learning is a machine-learning paradigm where multiple models or learners are trained to solve the problem. This research explores the usage of SVM ensemble for Insurance Data Analysis. The number of Insurance firms is increasing day by day. The main objective of this research is to find out the best policy from a given list of Insurance policies. In this research a detailed study of SVM ensemble is done. An insurance dataset obtained from UCI knowledge discovery in Databases Archive is taken in the research analysis. From the dataset five different Non-life insurance policies were selected and used in this research work. The categories of policies include Fire policy, Home policy, Car policy, Kissan policy and Boat policy. AdaBoost, multiclassifier SVM ensemble was created and tested with the insurance dataset. SVM ensemble produces better accuracy than other ensembles. The knowledge flow of SVM ensemble is loaded in Weka. From each category, the policy that gives a highest accuracy value for SVM ensemble is considered to be the best policy. A graphical user interface is also developed using .NET framework, to view the policy output. This system helps the user to find out a best policy from the analysed data. KEYWORDS: SVM ensemble, Insurance policy, Accuracy, ROC, Support Vector Machine. -
SVM Ensemble Model for Investment Prediction
International Journal of IT, Engineering and Applied Sciences Research, Vol-1 (2), pp. 19-23. ISSN-2319-4413 -
Svsl on combination of star with path
Super Vertex Sum Graph is a graph which admits super vertex sum labeling. In this paper, we combine stars and paths under different combinations which results in formation of new graphs and construct algorithm to obtain optimal super vertex sum labeling for the new graphs formed and their super subdivided graphs. 2020 Author(s). -
Swarm Intelligence Decentralized Decision Making In Multi-Agent System
This research aims to understand how groups of agents can make decisions collectively without relying on a central authority. The research could focus on developing algorithms and models for distributed problem solving, such as consensus-reaching and voting methods, or for coordinating actions among agents in a decentralized manner. The research could also look into the application of these methods in various fields like distributed robotics, swarm intelligence, and multi-agent systems in smart cities and transportation networks. Swarm intelligence in decentralization is an emerging field that combines the principles of swarm intelligence and decentralized systems to design highly adaptive and scalable systems. These systems consist of a large number of autonomous agents that interact with each other and the environment through local communication and adapt their behaviors based on environmental cues. The decentralized nature of these systems makes them highly resilient and efficient, with potential applications in areas such as robotics, optimization, and block chain technology. However, designing algorithms and communication protocols that enable effective interaction among agents without relying on a centralized controller remains a key challenge. This article proposes a model for swarm intelligence in decentralization, including agents, communication, environment, learning, decision-making, and coordination, and presents a block diagram to visualize the key components of the system. The paper concludes by highlighting the potential benefits of swarm intelligence in decentralization and the need for further research in this area. 2023 IEEE. -
Sway of Social Media Financial Content on Financial Literacy of Youngsters in a Metropolitan City
On social media, the financial material has steadily been shaping the financial actions and knowledge levels of youngsters globally. This research was intended to study the influence of social media financial content on the financial literacy of youngsters in Bengaluru, a metropolitan city in India. The study looked into the patterns of social media usage for financial information acquisition, the types of financial content consumed, and the perceived impact on financial decision-making processes and overall financial literacy levels. The results showed that while gender and marital status significantly influence the type of financial content consumed, factors such as age, educational background, occupation, and income level did not exhibit significant variations in content preferences. The study highlighted that the diversity of social media platforms and the nature of content available on these platforms play pivotal roles in shaping the financial literacy levels of youngsters. The conclusion reflects that there is a clear relationship between social media engagement and financial information acquisition. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. -
Sweet, Identity, and Bengaluru!
[No abstract available] -
SwinTransConv and Tab-FCNN: a novel SwinTransConv neural network features and tab-fully connected neural network in pap smear images for cervical cancer classification
The primary objective of this paper is to delineate a Deep Learning (DL) methodology for cervical cancer from Pap smear imagery. In the interest of augmenting the quality and equilibrium of the dataset, the initial phase involved executing ROI detection on the Pap smear images. ROI detection is executed using YOLO V4 model in the input Pap smear images for detecting superficial, intermediate and parabasal layers. Then, the segmentation phase is performed to delinate cytoplasm and the nucleus, employing the YOLOv11 model. Subsequently, the feature extraction is executed by the proposed SwinTransConv, which integrates the Swin Transformer with a Convolutional Neural Network (CNN) to yield a robust and hierarchical representation of salient cellular features. The derived features act as input for the classification phase, for which a Tabular-Fully Convolutional Neural Network (Tab-FCNN) model is proposed by combining Tabular Network (TabNet) and Fully Convolutional Neural Networks (FCNN). TabNet identifies significant features from the input dataset utilizing attention-based mechanisms tailored for tabular data, whereas FCNN enhances the final decision-making process by assimilating complex feature interactions. Experimental findings state that the proposed approach reached an accuracy of 97.9%, a sensitivity of 95.4% and a specificity of 99.4%. 2026 Taylor & Francis Group, LLC. -
Switchable surface activity of Bi2Al4O9 nano particles: A contemporary approach in heterocyclic synthesis
Ferroelectric catalysis is emerging as an efficient chemical transformation strategy, especially in the field of clean energy production, wastewater treatment and degradation of pollutants. The core of ferroelectric catalysis is the dynamically switchable electrical polarization on their surface. It enables them to switch their surface activity, more precisely due to binding strength with the substrate. Even though a plethora of reports are available, the introduction of ferroelectric catalytic surfaces for the generation of heterocyclic compounds is a novel aspect. Here, we introduce ferroelectric Bismuthaluminate nanoparticles as catalysts for generating derivatives of azalactone, tetrahydro-benzopyran and pyranopyrazole with improved catalytic efficiency. This can be achieved by switching the direction of polarization of the catalyst which indeed alters the surface electronic states and stimulates the reaction followed by the excellent yield. Here the switchable property is due to the thermally induced polarization of water. Graphical Abstract: [Figure not available: see fulltext.]. 2023, The Author(s), under exclusive licence to Springer Nature B.V.