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Application of experiential, inquiry-based, problem-based, and project-based learning in sustainable education
This chapter explores integrating pedagogical approaches for sustainable teaching and learning, emphasizing the capacity to meet present requirements without compromising the future. It highlights the merits of experiential, inquiry-based, problem-based, and project-based methods in sustainable practices in education. Experiential learning emphasizes practical application and reflection, whereas inquiry-based learning promotes inquiry and exploration. Problem-based learning immerses students in real-world sustainability challenges and interdisciplinary collaboration, whereas project-based learning enables students to take on leadership roles. Integrating these techniques offers a variety of options for addressing complex environmental issues. Future obstacles include integrating technology and ensuring equitable access. Integrated educational practices require learner-centred approaches, collaboration, and continuous feedback, empowering students to become proactive sustainability advocates and promoting positive change for a sustainable future. 2024, IGI Global. All rights reserved. -
Algae-Based Nanoparticles for Contaminated Environs Nanoremediation
Currently, the rapidly growing human interference has increased the percentage of pollutants that include organic and inorganic and this has been threatening the ecosystems. Remediation by conventional physicochemical methods, bioremediation has gained immense acceptance due to their ecofriendly, economical, and sustainable approach. Microbial-based nanoparticles act as facilitators in remediating contaminants by microbial growth and immobilization of remediating agents, by inducing microbial remediating enzymes or enhanced biosurfactants that helps to improve solubility of hydrophobic hydrocarbons to create a conducive milieu for remediation. Algal-NPs can be produced easily using low-cost medium and simple scaling up process which is economically feasible. Silver nanoparticles (AgNPs) and gold nanoparticles (AuNPs) have been synthesized using Nannochloropsis sps (NN) and Chlorella vulgaris (CV), while, brown seaweeds Petalonia fascia, Colpomenia sinuosa, and Padina pavonica were used with iron oxide NPs along with their aqueous extracts. These applications have shown to be promising alternative bioremediating methods that are safe. Algal-based NPs can act as a pollution abatement device that can help to effectively target the pollutants for efficient nanobioremediation and helps to promote environmental clean-up for eliminating heavy metals, dyes, and other organic and inorganic waste from the environment. 2025 by Apple Academic Press, Inc. -
Bionanoparticles Impact on Human Health, an In Vitro and In Vivo Status
In the hunt for a safe replacement for hazardous conventional nanoparticles that are applied in biomedicine field, bionanoparticles are known to be the ideal choice. The term bionanoparticles refers to nanoparticles made using biomolecules or that use a biomolecule to enclose or immobilize a more conventional nanomaterial. For the creation of bionanoparticles, biomolecules are taken from bacteria, plants, agricultural wastes, insects, marine life, and some mammals. Bionanoparticles, possess unique qualities with lot of potential that make them applicable in different field such as, pharmacy, aerospace engineering, biosensors, material sciences and so on. These bionanoparticles have improved biocompatibility, bioavailability, and bioreactivity and display minimal or insignificant toxic effects in humans, animals, and at the environment level. Nanoparticles can be introduced into the body either by biomedical procedures as a part of treatment, diagnosis, or the application of cosmetics. The mode of entry is usually via intravenous, intradermal, intramuscular and peritoneal injections. Unintentional entry of nanoparticles is a result of environmental pollution or accidental release. The effect of bionanoparticles on human health received much importance as they are biologically synthesized and biocompatible. The goal of this chapter is to review human exposure to bionanoparticles with an emphasis on the effects on human cells and animal models. 2025 selection and editorial matter, Shakeel Ahmed; individual chapters, the contributors. -
Measurement Model of CO-PO Attainment in Higher Education: A Simplified Approach
The educational system in most countries are moving toward Outcome-Based Education (OBE) which is a student-centric teaching and learning methodology. The basic idea behind the adoption of OBE model is that the graduates should possess a sound knowledge in their respective disciplines and also have global mobility and acceptance. The Outcome-Based Education (OBE) should be based on the vision and mission of the institution. The institutions should clearly spell out the learning objectives of the program and course. The Course Outcome (CO), Program Outcome (PO), Program Specific Outcome (PSO) and Program Educational Objectives (PEO) determine clearly what the students are expected to accomplish, post their course or program respectively. This study aims to provide the simplified approach on assessment, evaluation and calculating the attainment levels of students through COs and POs in a management program. To assess the CO attainment for management courses, the authors have identified the subject Entrepreneurship Development offered in the first semester from the 2018-2020 batch of 60 students from the MBA program of an autonomous institute. The Course Outcome (CO) and Program Outcome (PO) are mapped with the Continuous Internal Assessments (CIA) and Semester Exam End (SEE) and thus the attainment levels of each CO are measured. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
HR Analytics: An Indispensable Tool for Effective Talent Management
Business organizations have changed tremendously in the way they visualize the human capital of the organization and make all efforts to create a workforce that is productively engaged and is ready to embrace the challenges posed by uncertainty and turbulence in the business environment. This calls for a decision-making approach that is based on observed people behaviours rather than relying on intuition and gut feel. These observed behaviours are reactions or consequences to stimuli and therefore the science of Human Resource Management can be better understood as predicting these dependent variables based on a set of independent variables. This chapter attempts to present a complete framework of HR analytics in terms of concept, need and how it can add immense value to effective talent management in the organizations. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Application of Artificial Intelligence on Smart Tourism Eco Space: An Integrated Approach in Post-COVID-19 Era
The AI-integrated approach in recent times has evolved with innovative techniques and gained much importance in the post-COVID-19 scenario. This chapter extends contemporary and exponential research findings for Smart Tourism Practices and the Application of AI-enabled systems for the Tourism Ecosystem. It highlights for various service segments like hotels, motels, resorts, restaurants, cafes, airlines, and destinations under this large umbrella known as the hospitality sector. Smart tourism eco space capacitates an ICT-enabled system consolidates tourism resources and information technologies. Perhaps, with multiple challenges, a successful implementation of smart tourism approaches empowers and supports a smart system in place. The tourism eco space is highly vulnerable, and this situation in the service sector creates an intense requirement of a comprehensive view of digitally enabled smart tourism eco space with innovative mechanisms to remain contact-free with less human intervention. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Harnessing the Power of Big Data Analytics to Transform Supply Chain Management
The study aims to conduct a systematic literature review and bibliography analysis to explore the role of big data analytics in transforming supply chain management. The systematic literature review was conducted according to the PRISMA guidelines extended into a three-phase approach. The articles were reviewed from different databases like Scopus, Web of Science, and ABDC. 239 articles were reviewed through abstract screening, and 191 articles were finally selected after full-text screening. The results of the analysis reflected the publication trend from January 2011 to January 2024, keyword analysis, co-citation and network analysis, and theme identification from the domain. Moreover, the study theoretically contributes by suggesting growing trends in the field of supply chain management, and the managerial implications of the study suggest the benefits of implementing big data analytics in supply chain management. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
A Comparative Analysis of Machine Learning Algorithms for Image Classification: Evaluating Performance
Image classification plays a crucial role in various applications, and selecting the most effective machine learning algorithm is essential for achieving accurate results. In this study, we conducted a comparative analysis of several well-known supervised machine learning techniques, including logistic regression, support vector machine (SVM), k-nearest neighbours (kNN), nae Bayes, decision trees, random forest, AdaBoost, and artificial neural networks (ANN). To assess the performance of these algorithms, we utilised different fonts of the English alphabet as our dataset and performed the analysis using the R programming language. We evaluated the algorithms based on standard performance criteria, such as the area under the Receiver Operating Characteristic curve (ROC), accuracy, F1 score, precision, and recall. Our research findings demonstrated that the classification performance varied depending on the training size of the dataset. Notably, as the training size increased, neural networks exhibited superior performance compared to other machine learning techniques. Consequently, we conclude that neural networks and SVM are the most effective algorithms for image classification based on our study. By conducting this comprehensive analysis, we contribute valuable insights into selecting appropriate machine learning algorithms for image classification tasks. Our findings emphasise the significance of considering the training dataset size and highlight the advantages of neural networks and SVM in achieving high classification accuracy. This study provides valuable guidance for practitioners and researchers in choosing the most suitable machine learning algorithm for image classification, considering their specific requirements and dataset characteristics. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Centring African indigenous knowledge: Afro-feminist perspectives on women's empowerment
This chapter explores the Afro-feminist perspective of the significance of African indigenous knowledge in the context of women's emancipation. The recognition of gender inequities in Africa prompts a need for the incorporation of intersectionality in feminist discussions that include a wide range of cultural contexts. The chapter emphasizes the significance of intergenerational learning in preserving knowledge and empowering older women via examining power relations, colonial legacies, and the integration of Western-traditional medicine. This chapter examines the impact of indigenous community and feminist organization involvement on legislative progress, focusing on protecting indigenous women. Global connections, cross-cultural discussions, and unity facilitate the empowerment of Afro-feminism. These elements surpass geographical boundaries and incorporate indigenous traditions. 2024, IGI Global. All rights reserved. -
ChatGPT and Academia: Exploring the transformations and transitions
Since its launch in November 2022, this tool has brought massive transformations in almost every imaginable field. Among those fields, academia is perhaps the most discussed domain. However, much of what ChatGPT can do is still understudied. Therefore, this chapter aims to investigate the potential impact of ChatGPT in the domain of academia while exploring the possibilities for the future. The study emphasizes the theories that link ChatGPT's presence to its effects on academia and research. 2024, IGI Global. All rights reserved. -
Cross-disciplinary collaborations and partnerships for sustainability education: Including community-based learning, industry partnerships, and international collaborations
Multidisciplinary collaboration is crucial to sustainable education. It places a strong emphasis on combining many academic disciplines to address complex environmental issues and promote sustainable lifestyles. Students can put their knowledge into practice and raise awareness of the world through community-based learning, corporate partnerships, and international collaborations. The chapter emphasizes effective methods for evaluating the effectiveness and impact of collaborative activities. It highlights how crucial innovation, knowledge sharing, and international cooperation are to building a sustainable future. Social justice, action-oriented learning, and lifetime professional growth are all components of sustainability education. Institutional barriers, cultural differences, and resource constraints impact these cooperative initiatives. Future generations' perceptions of the Earth can be affected via interdisciplinary collaboration and partnerships. 2024, IGI Global. All rights reserved. -
Orality, Literacy, and Modernity: A Reading of The Legends of Khasak
What is the relationship between literacy and culture? It is not possible to give a simple answer to this question. Eric Havelock, while commenting on ancient Greek culture and literacy, observes that the classic culture of Greece had attained an advanced stage even before the emergence of Greek script. It continued to exist as an oral culture for a long time (Havelock 1963, 117120). A culture without a script is not uncivilized or underdeveloped. Havelock observes: One can propose with assurance that the pre-Homeric epoch the Dark Age yields for the historian what might be called a controlled experiment in non-literacy. Here, if anywhere, we can study those conditions on which a total culture, and a very complex one, relied for its preservation upon oral tradition alone. (pp. 11718) 2025 selection and editorial matter, E.V. Ramakrishnan and K.C. Muraleedharan; individual chapters, the contributors. -
Bionanomaterials in Improving Food Quality and Safety
Current inventions in the area of nanotechnology opened several transformations in scientific and industrial sectors. One such rapidly developing technology gets a lot of application in the food industrys changing the culture of food cultivation to its several branches, like production, processing, packaging, preservation, detection of foodborne pathogens, transportation, shelf life and bioavailability of its valuable nutrients. Far smaller in size and in surface area is strongly related to its stability in terms of chemical and biological activities. Hence, food nanotechnology empowers advancement in several novel bio-nanomaterials with an extensive choice towards potential applications. Nanotechnology benefits the food industry in several ways: to extend and predictable for the growth due to recent and swiftly developing technology influences the characteristic of the food products, which should not get exposed to human and microbial activities. Therefore, implication of bio-nanomaterials in food-related industries pose a significant contribution for economy and also a key community concern. The involvement of nanotechnology throughout the life cycle of food processing, storage, transportation, safety, and potential benefits to mankind are also briefly reviewed in this chapter. Acceptance of nano-based ingredients by the public in various phases of the food business and their associated safety and regulatory measures pertaining to food items can be improved by many methods of nanotechnology. 2025 selection and editorial matter, Shakeel Ahmed; individual chapters, the contributors. -
A case study on a beacon of hope transition: India's renewable energy integration and the Ujwal DISCOM assurance Yojana (UDAY)
This case study examines the transformative impact of the Ujwal DISCOM Assurance Yojana (UDAY) on India's energy landscape, focusing on its role in facilitating renewable energy integration. India's energy sector faced daunting challenges, including financially distressed power distribution companies (DISCOMs) and high aggregate technical and commercial (AT&C) losses. UDAY's financial restructuring and operational efficiency improvements led to remarkable reductions in DISCOMs' debt burdens and AT&C losses, respectively. The policy aligned with India's renewable energy goals, driving DISCOMs to procure renewable energy sources. Consequently, India witnessed significant growth in its renewable energy capacity, environmental benefits through reduced emissions, and economic growth via job creation. This case study offers insights into the challenges faced, technological advancements incentivized, and the long-term sustainability of these reforms. Moreover, it presents broader lessons for energy sector reform and renewable energy integration, both within India and globally. 2024, IGI Global. All rights reserved. -
Bionanomaterials in Food Applications and their Risk Assessment
Nanotechnology has increased impressively during the last decade for their diverse potential uses in food, environment, medical, sustainable energy and so forth. Nanomaterial synthesis by chemical methods has unintended properties on the ecological pollution and also effect on human welfare. To overcome these challenges green synthesized nanoparticles (NPs) has been used from plants and animals. The green synthesized NPs include gold (Au NPs), copper (Cu NPs), silver (AgNPs), iron and its oxides (Fe NPs). Abundant microbes and plants are used for the synthesizing NPs that are eco-friendly, cost effective and potentially safe. Further, these can be constructed using agri-food waste sources such as agricultural crops, fruits and vegetables, cereals, oil cakes, alcoholic beverages, and so forth, for synthesizing sustainable NPs, reducing environmental issues. These green synthesized metallic NPs needs to be further characterized for the synthesis, factors affecting the parameters and their potential applications in various fields with major challenges that needs to be researched such as toxicity and translational research. 2025 selection and editorial matter, Shakeel Ahmed; individual chapters, the contributors. -
Plant, Animal, and Microbial Sources of Dyes and Mordants
Synthetic dyes and mordants have been used by various industries, including food, cosmetics, textiles, and pharmaceuticals, for many decades. However, their potential hazards to the environment and human health, such as carcinogenicity and teratogenicity, have raised global concerns. In earlier decades, people used naturally extracted dyes and mordants from plants and insects for purposes like painting, dyeing clothes, and enhancing skin and hair, using substances like henna, turmeric, and saffron. However, chemically synthesized dyes quickly replaced natural dyes due to their easy availability and low cost. Currently, consumers are becoming more conscious of the use of synthetic dyes and their effects, which can cause allergies and toxicity. This has led to a resurgence of eco-friendly dyes and biocolors, which have gained importance. There has been advanced and increased development in utilizing naturally occurring bioresources to produce sustainable biocolors with multifunctional applications. Natural colors have not only increased their market value due to their aesthetic appeal but also for their various properties, including antibacterial, antiviral, anticancer, anti-inflammatory, and antioxidant effects. Indeed, biocolors derived from plants, animals, and microorganisms have better degradability and compatibility with the environment. These naturally occurring pigments need to be explored from various natural sources to meet the increasing global demand, using suitable techniques for their extraction. 2025 Apple Academic Press, Inc. -
Natural Language Processing in Medical Applications
Medical applications of machine learning are very new, and there are still several obstacles that limit their widespread use. There is still a need to address issues like high dimensionality data and a lack of a standard data schema. An intriguing way to explore the possibilities of machine learning in healthcare is to apply it to the difficult problem of cardiovascular disease diagnosis. At the present day, cardiovascular disorders account for the majority of deaths worldwide. It is often too late to adopt appropriate treatment for many of them because they progress for a long time without showing any symptoms. Because of this, its crucial to get checked up on routinely so that any developing diseases can be caught early. If the sickness is caught early enough, effective therapy can be put into place to stop the progression of the illness. This is done with the intention of analysing data from many sources and making use of NLP to overcome data heterogeneity. This paper evaluates the usefulness of several machine learning methods (such as the Naive Bayes (NB), Transductive Neuro-Fuzzy Inference, and Terminated Ramp-Support Vector Machine (TR-SVM)) for healthcare applications and suggests using Natural Language Processing (NLP) to address issues of data heterogeneity and the transformation of plain text. The implementation, testing, comparison of performance and analysis of the parameters of the algorithms used for diagnosis have simplified the process of selecting an algorithm better suited to a certain instance. TWNFI is particularly effective on larger datasets, while Terminated Ramp-Support Vector Machine is well suited to lesser datasets with a lower number of magnitudes due to performance difficulties. 2024 Scrivener Publishing LLC. -
Ecofriendly Approaches for Ameliorating the Adverse Effects of Cadmium in Plants by Regulating Physiological and Defense Responses: An Overview
Mitigating cadmium stress in agricultural plants becomes extremely critical in order to assure food sufficiency in the scenario of a rapidly growing population. An extensive review of environmentally friendly methods for reducing cadmium toxicity in plants is provided in this chapter, with special attention to a variety of tactics like phytohormones, polyamines, melatonin, mineral ions, nanoparticles, and transgenic techniques. Nanoparticles are capable of changing the distribution of cadmium, activating antioxidant defense mechanisms, and boosting physiological processes that are crucial for plant resilience and growth. Microorganisms greatly increase plant resistance to cadmium stress by modifying phytohormones and regulating defense-related proteins. Phytohormones can increase a plants adaptability to cadmium stress through a number of mechanisms, such as the regulation of gene expression and physiological processes. Melatonin and polyamines provide protection against oxidative stress and heavy metal toxicity, while mineral ions such as silicon, calcium, zinc, iron, and selenium increase plant resistance to cadmium, minimizing pollution-related harm. Transgenic plants that are tolerant to cadmium exhibit enhanced detoxification processes and reduced metal accumulation. These findings provide important insights for long-term plant cadmium mitigation and highlight the significance of interdisciplinary approaches in managing heavy metal stress in agricultural systems. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Regression Approach for Predictive Analysis in Cognitive Decline
Cognitive decline refers to the deterioration of cognitive abilities, including memory, thinking, and reasoning, often associated with aging or neurological disorders like Alzheimer's disease. Machine learning (ML) methods can be used for predicting cognitive decline. Techniques such as Generative Adversarial Networks (GANs), feed-forward neural networks, supervised, and unsupervised learning process and analyse data patterns to forecast cognitive changes. By analyzing large datasets, ML algorithms can identify subtle cognitive shifts and predict future decline, enabling early intervention and personalized healthcare strategies. These diverse ML methods provide valuable tools for understanding, detecting, and potentially mitigating cognitive decline, advancing our ability to address cognitive health challenges. Some of these methods have been discussed later. In this research paper, a model to predict cognitive decline using principles of logical regression is proposed. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
AI-based online interview bot with an interactive dashboard
In recent years, video interviews have become increasingly popular in the recruitment process due to their convenience and efficiency. However, evaluating a candidates communication skills and perceived personality traits from a video interview can be challenging. The agent utilizes natural language processing and computer vision techniques to analyze the candidates verbal and nonverbal behavior during the interview. Specifically, the agent focuses on linguistic features such as fluency, grammar, and vocabulary, as well as nonverbal cues such as facial expressions and body language. Based on these features, the agent predicts the candidates communication skills and perceived personality traits. To validate the effectiveness of the agent, a Talk was conducted with a group of participants who completed video interviews with and without the agent. The results show that the agents predictions of communication skills and perceived personality traits are highly correlated with the ratings given by human evaluators. Additionally, the agent is able to provide valuable insights into the candidates performance that may not be immediately apparent to human evaluators. Overall, the intelligent video interview agent proposed here has the potential to improve the recruitment process by providing more accurate and objective evaluations of candidates communication skills and perceived personality traits. 2025 selection and editorial matter, A. Vadivel, K. Meena, P. Sumathy, Henry Selvaraj, P. Shanmugavadivu and Shaila S. G.; individual chapters, the contributors.