Browse Items (14428 total)
Sort by:
-
Farmers' Rights in the Age of Agricultural Intellectual Property: From Soil to Statute
This chapter explores the evolving landscape of Farmers' Rights in the context of intensifying agricultural intellectual property regimes. It critically examines the intersection of international legal frameworks, national legislations, and customary practices that shape farmers access to seeds, biodiversity, and knowledge systems. Through a multidisciplinary lens combining legal theory, environmental justice, and agroecological insights, the chapter interrogates how intellectual property regimes, such as UPOV and TRIPS, impact traditional seed systems, biodiversity conservation, and food sovereignty. It highlights tensions between privatized biotechnological innovations and community- centric stewardship of genetic resources, particularly in the face of climate change and digital sequence information. By tracing the trajectory from soil to statute, farmers' rights emerge from grassroots agricultural practices and struggles, evolving into legal recognition and protection through policy and law. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Safeguarding Traditional Knowledge and Farmers Rights: A Balanced Approach to IP Protection
Traditional Knowledge and farmers rights are considered to be the backbone of the agriculture system that is responsible for preserving the biodiversity, cultural heritage and sustainable development practices. Intellectual Property Rights (IPRs) protection is inclined towards the protection of the commercial interest rather than the rights of the creators or individuals. A balanced approach towards the protection of traditional knowledge and IPRs is required that safeguards the rights of farmers as well. The inclusive policies that enable and ensure equitable benefit sharing, protect the rights of the community, harmonize the customary laws with the IPRs are crucial in the present time. By promoting and advocating for the participatory governance, this chapter analyses the rights of farmers that foster sustainability and protect traditional knowledge simultaneously. It also examines the international legal instruments that recognize the protection of traditional knowledge. 2026, IGI Global Scientific Publishing. -
The analytical study of public sentiments about nCovid-19 using twitter comments
People's sentiments are the mirror of their cognition, and these sentiments play a very significant role in predicting and shaping one's behaviour. At present the entire world is fighting with this pandemic situation due to the nCOVID-19 outbreak and people are experiencing a variety of sentiments. This research aims to explore various sentiments that people are experiencing during this epidemic. To achieve this objective sentiment analysis was conducted on 30,000 random Twitter comments using R software. Data mining of data was done using three hashtags: #Coronavirus, #Covid19 and #Covid19India. After the analysis, it was found that the nature of people's sentiments about nCOVID-19 is majorly positive. This study also elicits other noticeable patterns of netizen's expression through their comments while combating nCOVID-19. The present research provides insight into the type of sentiments which people are undergoing across the world during this pandemic situation and based on the obtained data, risk prediction can be done, and various awareness programmes can be designed to overcome the present issue which is prevailing worldwide. 2026 Author(s). -
An Exploratory Study on Vancharya as a Therapeutic Approach to the Bio-field of Young Adults Using Electronic Photographic Imaging
Background: Amid the fast-paced world, nature has a therapeutic modality for healing individuals both physiologically and psychologically. One such practice mentioned in an ancient Indian text is Vanacharya, which provides a deep connection with nature and a means of achieving overall well-being. Vancharya is a practice with profound roots in Indian spiritual and philosophical traditions that view the environment as a sacred and valuable source of knowledge and healing. Purpose: This purpose of this experimental research is to explore the therapeutic benefits of vancharya, in healing subtle systems of energy or the biofield present within the body like Aura Field (AF), Overall Alignment of Chakra (OAC), Overall, Chakra Energy (OCE), Stress Level (SL), Overall Energy Level (OEL). Methods: This research aims to evaluate the effect of vancharya, by examining 50 young adult participants over a one-week period (7 days). The study utilised a non-experimental single-group pre- and post-research design. The data collection was done using an advanced Biowell machine. The obtained data were analysed through a Paired Sample t-test by using SPSS software. Results: The obtained results indicated significant changes in the AF, OAC, OCE, while showing no significant impact on participants SL and OEL. Subjects also reported improved sleep patterns, less impulsivity, reduced aggression and fewer fluctuations of mood during their sessions in day-to-day activities. Conclusion: Therefore, the research indicates that Vancharya as a therapeutic modality had a significant impact on the subtle systems of energy among young adults. The obtained result from this intervention programme clearly indicates that subtle systems present in the body can have an impact as early as within 7 days itself, whereas, for visible impact within the individual (for instance stress level or overall energy level of the body), the duration of the intervention can be increased. The Author(s) 2025. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage). -
The impact of audit committee independence and competence on investors investment decision making: A study in the Indian context
This study examined the impact of an independent and competent audit committee on the decision-making process of investors in the Indian capital market and adopted a quantitative approach in which cross-sectional data are gathered with the help of a self-administered questionnaire survey. The selection of participants involves a stratified random sample technique, specifically targeting 441 regular investors associated with nine prominent brokerage houses in the Delhi NCR engaged in equity market investments. Descriptive analysis is applied to discern respondent characteristics, whereas correlation and regression analyses are utilised to test and elucidate the relationships and influences among variables in the model. The findings of this study, which indicate a notable correlation between investors' investment decision-making in India and the independence and competence of the audit committee, are in line with the expectation that independence and competence are essential attributes that the audit committee must possess. These characteristics, in turn, have a notable influence on investors' investment decisions. The outcome of this paper fills a gap in the literature by offering insights into the vital attributes of audit committee independence and competence that notably contribute to investment decision-making in India. This research examined the impact of an independent and competent audit committee on the decision-making process of investors in the Indian capital market, which has never been examined before. Thus, the findings shed light on the influence of board independence and competence on the decision-making process of investors in the Indian capital market. 2025, Malque Publishing. All rights reserved. -
Spotlighting recruitments: is AI dominating human resource practices? Qualitative research using NVIVO
Technology enriches and empowers organizations, making them more competitive and profitable. Any organization function is now technology-driven, helping to make faster and better decisions. Human resource management practices are also automated nowadays. Artificial Intelligence (AI) has gained enough importance in the recruitment process. Most of the literature emphasizes the use of technology and AI in establishing an effective and efficient recruitment process; however, the dominance of AI arouses the need to cast light upon the imbalance created after Al implementation. This study focuses on identifying the adverse impact of automated recruitment processes, which, due to a lack of human consciousness and intelligence, may sometimes not find the right candidate for the vacant position. Thus, a qualitative study was conducted to check the need for a balance of collaboration between humans and AI in recruitment. Primary data was collected through structured interviews with 21 HR professionals of IT companies in India implementing AI in their recruitment process. The findings highlight the positive impact of AI tools on recruitment efficiency but raise concerns about the loss of human connection, the potential misuse of AI, and the need for balanced decision-making in the hiring process. Based on the study's findings, it is recommended that a framework that combines humans and AI can be created. This study enables organizations to develop a customized recruitment process aligned with their vision, optimizing the use of AI and human intelligence to improve procedures and understand the impact of AI on hiring. The Author(s), under exclusive licence to Springer Nature B.V. 2025. -
VERTEX COLOURING OF FINITE NETWORKS WITH RESPECT TO AVERAGE DISTANCE
For a finite network, represented as a graph G = (V, E) with average distance (G), the average distance colouring of G is a function c from V to the set of non-negative integers, such that for any v ? V, |c(v) ? c(u)| ? 1 for all u ? V such that d(u, v) ? ??. In this paper, we find the average distance colouring number of some special types of networks and present a greedy algorithm to colour any graph with average distance colouring constraint. 2025, Diogenes Co. Ltd.. All rights reserved. -
Unveiling the Impact of Adverse Childhood Experiences on Adult Criminal Behavior: A Qualitative Enquiry
This qualitative study explored how adverse childhood experiences contribute to criminal behavior among 20 male prisoners (aged 2040) in Kerala. Using semi-structured interviews, thematic analysis revealed seven key themes: family dysfunction, emotional struggle, abuse, economic struggle, peer pressure, coping mechanisms, and sensation seeking. Findings showed that family dysfunction creates baseline trauma, fostering emotional voids and maladaptive coping. The study emphasizes the interconnectedness of multiple adversities in shaping criminality. It highlights the need for early interventions addressing trauma, emotional dysregulation, and unhealthy coping patterns through supportive networks to prevent criminal behavior later in life. 2025 Taylor & Francis Group, LLC. -
AI tools for enhancing student engagement
Artificial Intelligence (AI) is revolutionizing the learning environment with adaptive technologies that offer new possibilities to engage, support, and empower learners. Throughout this chapter, we examine how AI technologies are transforming student engagement from the past to enable more personalized, responsive, and inclusive learning environments. From intelligent tutoring systems and adaptive learning systems to chatbots, game- based learning, and predictive analytics, AI offers teachers more and more tools to make behavioral, cognitive, and emotional connections with learners. Based on actual case studies of K- 12 and higher education, including DreamBox Learning and Civitas Learning, the chapter discusses real- world success with respectful consideration of the ethical, technical, and social issues of AI deployment. Issues from data privacy through algorithmic bias and student agency protection are discussed in detail. In the future, the chapter discusses briefly trends such as affective computing, AI- powered AR/VR environments, and human- AI collaboration construction for education's future. Rather than recommending AI as a replacement for teachers, the chapter argues for an equitable partnership-where AI as a system itself can be an effective collaborator to human teachers, enhancing their capacity to create rich learning environments. In the end, the chapter is appealing for an intentional, ethical, and equitable stance in adopting AI, so technology can be used in the name of education not only by facilitating engagement, but also in safeguarding human dignity, equity, and creativity. 2026, IGI Global Scientific Publishing. All rights reserved. -
AI and Multimedia Integration for Smart Mining and Renewable Energy Sustainability
This chapter focuses on how Artificial Intelligence (AI) and multimedia technologies are used to encourage sustainable smart mining and renewable energy optimization. AI boosts the accuracy in planning energy, smart grid use and supporting the management of demand, which saves money. The use of AI, predictive maintenance, geospatial analytics, and real- time monitoring in mining ensures optimisation of resource extraction and insignificant impacts on the environment. The research is powered by the international case studies and the initiatives of the private sector and points out the transformational impact AI can and is making in the sphere of operational efficiencies and sustainable industrial development in the spheres of energy and mining industries. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Global policies and legal frameworks for sustainable internet of vehicles
The Operational vehicles utilize vehicular networks which work through Internet of Vehicles to reach better safety results and enhanced traffic outcomes and environmental benefits in real-time conditions. Multiple barriers restrict implementation worldwide because different jurisdictions maintain different rules about privacy regulations and security standards along with sustainability boundaries. This paper examines the EU GDPR alongside the California CCPA along with the Indian FAME scheme and new data protection laws and Singapore Smart Mobility 2030 and Germany's EU Aligned frameworks. Different governance standards prevent organizational systems from integrating with each other resulting in difficulties during deployment procedures. The proposal establishes environmentally friendly and accessible IoV systems while meeting transport environment regulatory standards through combined implementation of privacy-by-design principles and cybersecurity protocols and standardized protocols. 2025, IGI Global Scientific Publishing. All rights reserved. -
Navigating the complex terrain of medical big data: A synthesis of data security and legal frameworks
This paper will focus on medical big data, in terms of the detail of legal frameworks of medical big data in terms of the significance of data breach incidents such as the Anthem as well as WannaCry ransomware attacks as key focal points for urgent need in toughen data security compliance with legal and ethical norms. Amongst key regulations, we analyze HIPAA, GDPR along with an impending India regulation Digital Personal Data Protection Act that will hold similar strict non-compliance penalties. Issues such as privacy, informed consent and algorithmic bias in healthcare data-managed are also covered. It helps support the usage of current technologies like blockchain and zero trust architecture to enhance data authenticity and trust. Finally, a harmonized legal, technical and ethical approach is proposed to improve global healthcare systems in view of mitigating security threats and assuring the secure, ethical use of medical big data for the best possible global healthcare outcomes. 2025, IGI Global Scientific Publishing. -
Impact of Homophily on Patient Empowerment: A Study of Online Patient Support Groups
Internet facility has led to emergence of patient support groups. These have gained prominence as these fulfils important benefits to patients. One such benefit is patient empowerment. These online groups provide opportunity to patients to interact with similar ailments and predicaments and who can understand the pain and discomfort felt by the patient. This provides validation for the patient and patients experiences. How does this homophily impacts patient empowerment? This question has been explored in this study. The methodology is based on an online survey of patients visiting such online platforms. In all 701 patients provided the data. Independent variable (homophily) and dependent variable (patient empowerment) have been measured using a 7-point Likert scale. Findings provide that both are weakly correlated, but this correlation is significant. Regression analysis led to a regression model that is fit statistically. This provides basis to encourage patients to visit online support groups. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Gucchi (Morchella esculenta)
This chapter focuses on Morchella esculenta as a nutraceutical and functional food, its habit, habitat, general characteristics, availability, biologically active compounds present and pharmacological and medicinal value. Mushrooms are spore-bearing fleshy fruiting bodies of fungus often present above the ground. Greeks and Romans included mushrooms in their diet. Romans considered mushrooms as the food of supernatural beings, despite the Chinese contemplating them as the elixir of the human being. Functional foods that are prepared from morel mushrooms are of high medicinal properties. The production of M. esculenta worldwide is 1.5 million tonnes of fresh weight and 150 tonnes of dry weight. India and Pakistan are the major morel-producing countries and each country has about 50 tonnes of dry morels. The pharmacological properties of Morchella species show its use in Chinese traditional medicine since 2, 000 years and in Malaysia and Japan to cure several diseases. 2023 Deepu Pandita and Anu Pandita. -
Hybrid Convolutional Neural Network and Extreme Learning Machine for Kidney Stone Detection
When it comes to diagnosing structural abnormalities including cysts, stones, cancer, congenital malformations, swelling, blocking of urine flow, etc., ultrasound imaging plays a key role in the medical sector. Kidney detection is tough due to the presence of speckle noise and low contrast in ultrasound pictures. This study presents the design and implementation of a system for extracting kidney structures from ultrasound pictures for use in medical procedures such as punctures. To begin, a restored input image is used as a starting point. After that, a Gabor filter is used to lessen the impact of the speckle noise and refine the final image. Improving image quality with histogram equalization. Cell segmentation and area based segmentation were chosen as the two segmentation methods to compare in this investigation. When extracting renal regions, the region-based segmentation is applied to obtain optimal results. Finally, this study refines the segmentation and clip off just the kidney area and training the model by using CNN-ELM model. This method produces an accuracy of about 98.5%, which outperforms CNN and ELM models. 2023 IEEE. -
Phishing attack detection using Machine Learning
Phishing is a type of digital assault, which adversely affects people where the client is coordinated to counterfeit sites and hoodwinked to screen their touchy and private data which integrates watchwords of records, monetary data, ATM pin-card data, etc. Recently safeguarding touchy records, it's fragile to cover yourself from malware or web phishing. AI is an investigation of information examination and logical investigation of calculations has demonstrated outcomes. Contradicting phishing sprinters with remarkable perception and felonious outcomes comparable as care shops, and custom against phishing approaches. This paper examines the association of Machine Literacy routes in identifying phishing assaults and records their advantages and drawbacks. There are countless Machine Learning calculations that have been dug to proclaim the relevant decision that act as against phishing apparatuses. We made a phishing section framework that extracts capacities that are expected to descry phishing. We likewise utilize numeric outline, as well as an overall investigation of customary Machine Learning methodologies comparable as Decision Tree, Random Forest, Multi-layer Perceptron's, XG Boost Classifier, SVM, Light BGM Classifier, Cat Boost Classifier, and covering grounded highlights choice, which contains the metadata of URLs and assists with deciding if a site is licit or not. 2022 The Authors -
An Enhanced Pathfinder Algorithm for Optimal Integration of Solar Photovoltaics and Rapid Charging Stations in Low-Voltage Radial Feeders
Most low-voltage (LV) feeders have large distribution losses, poor voltage profiles, and inadequate voltage stability margins owing to their radial construction and high R/X ratio branches, and they may not be able to handle substantial solar photovoltaics (SPVs) and EV penetration. Thus, optimal integration of SPVs and rapid charging stations (RCSs) can solve this problem. This paper offers an extended pathfinder algorithm (EPFA) with guiding elements and three followers' life lifestyle procedures based on animal foraging, exploitation, and killing. First, the EV load penetration was used to evaluate the LV feeder performance. Subsequently, the required RCSs and SPVs were appropriately integrated to match the EV load penetration and optimise feeder performance. An Indian 85-bus real-time system was used for simulations. The losses and GHG emissions increased by 150% and 80%, respectively, without the SPVs and RCS for zero-to-full EV load penetration. RCSs allocation alone reduced the losses by 40.1%, whereas simultaneous SPVs and RCSs allocation reduced the losses by 66%. However, the GHG emissions decreased by 13.7% and 54.33%, respectively. This study shows that SPVs and RCS can enhance the LV feeder performance both technically and environmentally. In contrast, EPFA outperformed the other algorithms in terms of the global solution and convergence time. The Author(s).