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Watching the Watchers: Digital Panopticism in the Age of Algorithmic Culture
The chapter deals with the ideology of Digital Panopticism as basically one of the major features of the algorithmic culture where power is exercised through the routine surveillance, data extraction, and predictive analytics. Using Michel Foucaults idea of the Panopticon as a starting point, the authors suggest that digital systems - for example, social media and algorithmic governance - are control structures that are spread out and therefore it is difficult to distinguish the zones where one is being observed and the zones where one is participating. The chapter links the concept of Digital Panopticism with the theories of the radical surveillance and digital capitalism and also examining the impact of the phenomena on subjectivity, autonomy, and behavior. The authors end the chapter by looking at moral theories and resistance movements to facilitate openness, taking responsibility, and the peoples control in the age of digital technology. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Skilful Leadership and Management: The Importance of Emotional Intelligence
Emotional intelligence (EI) has become more important in the study of organisational behaviour, particularly in relation to management and effective leadership. EI is the ability to identify, understand, and control ones own emotions as well as those of others. Those with high EI find it easier to navigate complex social interactions, build strong relationships, and resolve conflicts. EI is the ability to recognise, manage, and evaluate emotions. The ability to express ones emotions in a healthy way and to empathise with others is a sign of great emotional intelligence in a leader, and it will enhance both performance and workplace relationships. The study employed a range of machine learning (ML) methods, such as ANN, BRDT, Naive Bayes, and Random Forest, to predict EI based on behaviour credits. ML approaches have become more and more common. The results showed that the BRDT has the accuracy of 98.3 which is higher in all other machine learning models and gives better results. Seven behavioural attributes and seven additional individual attributes made up the prediction dataset. 2024 selection and editorial matter, Prof. (Dr.) Dorota Jelonek, Prof. (Dr.) Narendra Kumar, Prof. (Dr.) Mamta Chahar, Prof. (Dr.) Rusudan Kinkladze and Prof. (Dr.) Lilla Knop; individual chapters, the contributors. -
Artificial Intelligence in Mental Wellbeing in a Unit of Healthcare Industry in India
Artificial Intelligence is of great help in healthcare sector in saving the human lives from deadly diseases like cancer, brain tumour etc. The present conceptual paper emphasise over a prominent unit of health care which is mental health care. Method: The paper envisages the role of artificial intelligence in identifying and curing mental disorders. For this the literature was collected from the database of scopus, WOS, government websites, newspaper articles and WHO. Results: Further the results revealed that with the use of AI enabled technology, (Machine learning, Deep learning, Natural Language Processing, Teletherapy, Computer vision), the medical professionals are able to diagnose and cure the mental disorders accurately and at early stage. With the government assistance for research centers, the inclusion of AI in mental healthcare can prove to be a great help for the wellbeing of mankind specifically in a developing country like India. 2026 by IGI Global Scientific Publishing. All rights reserved. -
AI and human collaboration in tourism: a framework for scalable, authentic, and engaging content
This study examines the effectiveness of AI-generated content in tourism marketing by comparing it to human-generated narratives. While AI enhances scalability and factual accuracy, its ability to replicate emotional engagement and cultural authenticity remains unexplored. Using the Information Quality Framework (IQF), the study employs readability analysis, sentiment analysis, and thematic analysis to assess AI- and human-generated content. AI-generated travel narratives were sourced from large language models, while human content came from tourism blogs and vlogs. Findings reveal that AI-generated content is well-structured and highly readable but lacks emotional depth and trust-building elements. Sentiment analysis shows stronger emotional responses in human narratives, while thematic analysis highlights richer cultural insights. The study proposes a Hybrid AI-Human Collaboration Model, leveraging AI's efficiency with human creativity. These insights contribute to AI ethics, tourism storytelling, and digital marketing, offering practical recommendations for integrating AI into tourism content creation. 2025 Asia Pacific Tourism Association. -
Designing an artificial intelligence-enabled large language model for financial decisions
Purpose Artificial intelligence (AI) has profoundly reshaped financial decision-making, introducing a paradigm shift in how institutions and individuals navigate the complex finance landscape. The study evaluates the significant impact of integrating advanced AI and large language models (LLMs) in financial decision analytics. Design/methodology/approach The study offers FinSageNet, a novel framework designed and tested to harness the potential of LLMs in financial decisions. The framework excels in handling and analyzing large volumes of numerical and textual data through advanced data mining techniques. Findings FinSageNet demonstrates exceptional text summarization capabilities, outperforming models like FLAN and GPT-3.5 in Rouge score metrics. The proposed model has shown more accuracy than generic models. Originality/value The study emphasizes the significance of consistently updating models and adopting a comprehensive approach to integrating AI into financial decisions. This study improves our understanding of how artificial intelligence transforms financial analytics and decision-making processes. 2025 Emerald Publishing Limited -
Prehistorian indoor navigation based on sensory invasion for visually challenged people /
Patent Number: 202141024018, Applicant: Dr. M. Kasiselvanathan.
In this era, navigation continues to be a vital component in both outdoor and indoor environments, and many solutions have been given in both cases. Usually GPS is used for navigation, but in an indoor or underground environment, its signal is almost never available. In this work, we used LiDAR (Light Detection And Ranging) sensor and IMU sensor. LIDAR sensor is a famous remote sensing strategy utilized for estimating the specific distance of an item on the world's surface. -
Secured automated contactless vehicle door access system based on thermal mechanism of sensory devices /
Patent Number: 202141043350, Applicant: Dr.S.Balakrishnan.
Automatic entrance/exit door control is widely used in public places such as grocery stores, businesses, transportation stations, airports, and wholesale department stores to eliminate the need of manually opening and closing actions in this pandemic outbreak. Contemporary sensor based automatic door control technologies include infrared, ultrasonic/radio, or other wireless sensing methods. In this work, we designed a smart device which helps to perform a contact less temperature sensing door opening system. -
An IOT based system for antitheft security detection in a cloud environment /
Patent Number: 202241007566, Applicant: Dr. S. Brinthakumari.
Internet of Things (IOT) is the connection of things / objects through networks, in which things or objects can interact with each other without or minimal human intervention. Now-a-days, Security has grown to be the maximum tough task. Everyone wishes protection however in present scenario, not anything is secure now no longer even of their very own houses. In this work, we are proposing an IoT based system for Antitheft Security Detection in a Cloud Environment. In this system we used PIR sensor, ultrasonic sensor and Vibration sensor. -
From Nodes to Notables a Graph Theoretic Framework for Uncovering Emerging Influencers
Identification of new effects in social networks is important for effective digital marketing, information dissemination and community engagement. This article introduces a new graph-theoretical framework designed to systematically reveal impressively by analyzing structural network properties. Our function benefits from the main centrality matrix - including degrees, beach, proximity and self vector center - to evaluate the effect of users in the complex network. In addition, we use social identity algorithms such as the Luven and label suggestions to identify opinions of opinions and important contacts in networking groups. The processing of data affecting recent progress in Graph Neural Network (GNNS) is integrated to limit the impressive identity in order to detect the treatment and the fine effect pattern. Experimental results accurately demonstrate the efficiency of our hybrid approaches in influencing pinpointing, leading to actionable insight into targeted marketing campaigns and the effect of impact monitoring is increased. The challenges related to interpretation and dynamic network situations are discussed for future research. 2026 IEEE. -
Optimizing Cybersecurity in Digital Domain Through Proactive Cyber Monitoring
In todays linked digital landscape, cybersecurity is a top priority for individuals, organizations, and governments alike. As cyber threats grow in sophistication and frequency, the necessity for proactive and comprehensive defense strategies become more pressing. This study paper goes into the topic of improving cybersecurity through proactive cyber monitoring, providing an in-depth analysis of both hacker approaches and defense strategies. The study takes a multifaceted approach, starting with a thorough examination of common hacking strategies used by cyber enemies. By deconstructing popular attack routes such as phishing, virus propagation, and social engineering, the article sheds light on the complexities of cyber threats and hostile actors strategies for exploiting system vulnerabilities. Building on this foundation, the study investigates proactive cyber monitoring as a proactive defensive measure. Organizations can improve their cybersecurity posture by using advanced monitoring technologies, anomaly detection algorithms, and threat intelligence feeds to identify and mitigate possible threats before they become full-scale attacks. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Regression Analysis for Longitudinal Aging Study in India Data
This paper examines the Longitudinal Aging Study in India (LASI) and its role in providing valuable insights into the health, social, psychological, and economic well-being of the older Indian population. The paper examines the use of dependent independent variables in a multiple linear regression model, tests assumptions of linearity, and examines the significance of the overall model and the individual variables. There are 190 variables in the dataset being used. This paper presents the results of comparing the regression models obtained through basic, forward, and stepwise selection methods where the model obtained using the stepwise selection method, when all the linearity assumptions are satisfied, explains 86.51% of the variation in the dependent variable and the Adjusted R-squared of the model is 0.8374. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Global Anti-Discrimination Law and AI Concerning Imposter Syndrome and Legal Frameworks: Gender, Diversity, and Intersectional Bias in Professional Advancement Technology
In the age of artificial intelligence, strong anti-discrimination laws are important for more than just following the rules. It includes social, ethical and economic issues of interest to technologists and non-technologists alike. The regulations would help reduce the chance that AI perpetuates stereotypes that limit women and other groups, based on preconceived ideas. Lost impostor syndrome, behind-thescenes and careers being ruined by AI-bias fuel psychological damage to self-esteem, job satisfaction, retention etc.AI bias If bias exits in neural networks that has emerged in the workforce, " then its best to circumvent such bias before problems arise. In that chapter, it examines how international antidiscrimination law links to AI, with examples of impostor syndrome. It also explores the intersection of this technology with global anti-discrimination laws, and in doing so, reveals significant legal and sociotechnical implications. 2026 by IGI Global Scientific Publishing. All rights reserved. -
An Explainable AI Techniques for Advancing Diabetes Prediction Using Machine Learning
Researchers have developed an automated system to identify diabetes risk. This system combines data from two sources: a collection of female patients in Bangladesh and an expanded dataset from a local textile factory. The expanded dataset includes information from 203 additional patients. The system uses several techniques to improve its accuracy. It first identifies the most important factors for predicting diabetes, then employs a special model to estimate insulin levels. It also addresses challenges like imbalanced data (where one outcome is more common) and explains its predictions using artificial intelligence techniques. This system achieved the superlative results has an 81.0% accuracy rate, 0.812 F1 score, and 0.844 Area Under the Curve (AUC).. These metrics indicate strong performance in identifying diabetes risk. 2025 IEEE. -
Enhanching the Performance Metrics of Overlay Network for QoS in Media Transfer Using Genetic Algorithm
Quality of Service (QoS) of real time video applications is difficult to realize in wireless mobile networks because of the limited resource availability. Software-Defined Networking (SDN) Overlay networks are becoming popular to solve routing, traffic engineering and QoS due to the rapid increase in the adoption and investment in SDN. The SDN market size is projected to grow by a double-digit CAGR within the next decade and reached the low tens of billions USD in 2023, which shows a positive adoption of the industry. Real-time streaming and live content demand have also risen to an all-time high - the live-streaming market is growing at an average rate of about -20-23% CAGR through 2030, and the role of QoS in high-volume media is becoming more and more relevant. 2025 IEEE. -
Causal relationship among various development indices: A panel study
The concept of development has been regarded as a broader phenomenon encompassing various interrelated factors leading to improvement in the overall human wellbeing. So, it is important to understand the interlinkages between various dimensions of development. The present study was an attempt to analyze the causal relationship between the four aspects of development measured by the indices, namely the Economic Development Index (EDI), Social Development Index (SDI), Environment Development Index (ENDI), and Institutional Development Index (IDI) for a panel of 102 counties from 1996 to 2015. The long?run relationship between these indices through the panel ARDL model were also examined. The results indicated that there existed a bidirectional causal relationship between EDI and SDI, IDI and SDI, ENDI and SDI, and between IDI and ENDI. The one-way causality runs from IDI to EDI and ENDI to EDI. Further, given the nature of the variables considered here, panel autoregressive distributed lag models were used to examine the long?run relationship between the indices of development. The results showed that the impact of development indices with one another was statistically significant in the long run. 2021 The Society of Economics and Development, except certain content provided by third parties. -
Challenges To Democratic Consolidation In Ecuador - Space For Opposition And Indigenous Representation Under Rafael Correa And Lenin Moreno
The illiberal democratic trend currently sweeping the world has emerged as a major obstacle for democratic consolidation, leading to its acceptance as the new normal of democracy. This trend has been successfully reversed in Ecuador, but the country has encountered and still grapples with several obstacles that must be overcome in order to return to the democratic consolidation route. The study focuses on the issues of consolidation, emphasizing the space allotted for participatory democracy by the ruling elites. The study examines Rafael Correas and Lenin Morenos governments in the context of the democratic consolidation framework to determine their strategic actions, behavior, and interests. The scope of the investigation will be limited with the focus made-on the space allowed for the opposition and indigenous community representation, from 2008 to 2021, to determine the extent to which Ecuadors liberal democratic process is being consolidated. 2021 Taylor & Francis Group, LLC. -
Review on impacts of micro- and nano-plastic on aquatic ecosystems and mitigation strategies
The rapid proliferation of microplastics (MPs) and nanoplastics (NPs) in our environment presents a formidable hazard to both biotic and abiotic components. These pollutants originate from various sources, including commercial production and the breakdown of larger plastic particles. Widespread contamination of the human body, agroecosystems, and animals occurs through ingestion, entry into the food chain, and inhalation. Consequently, the imperative to devise innovative methods for MPs and NPs remediation has become increasingly apparent. This review explores the current landscape of strategies proposed to mitigate the escalating threats associated with plastic waste. Among the array of methods in use, microbial remediation emerges as a promising avenue for the decomposition and reclamation of MPs and NPs. In response to the growing concern, numerous nations have already implemented or are in the process of adopting regulations to curtail MPs and NPs in aquatic habitats. This paper aims to address this gap by delving into the environmental fate, behaviour, transport, ecotoxicity, and management of MPs and NPs particles within the context of nanoscience, microbial ecology, and remediation technologies. Key findings of this review encompass the intricate interdependencies between MPs and NPs and their ecosystems. The ecological impact, from fate to ecotoxicity, is scrutinized in light of the burgeoning environmental imperative. As a result, this review not only provides an encompassing understanding of the ecological ramifications of MPs and NPs but also highlights the pressing need for further research, innovation, and informed interventions. 2023 Elsevier B.V. -
Cassava (Manihot esculenta Crantz)A potential source of phytochemicals, food, and nutrition-An updated review
Cassava (Manihot esculenta Crantz) is believed to be an important staple food crop providing potential valuable food source as well as variety of phytoconstituents. Its starchy tubers provide a significant source of energy for around 500 million individuals. Among staple crops, it is regarded to be one of the top suppliers of carbohydrates. Its physicochemical qualities, as well as its availability, have made it a captivating food component. Cassava starch is a valuable raw material used to make a variety of both native and modified starch for cooking purposes. They have also been used for a variety of industrial uses. Cassava starch and flour have the potential to be valuable alternatives to rice, maize, and wheat crops. The advantages included being a staple diet for humans, a component of animal feeds, a raw ingredient for food processing, edible coatings, locally produced alcoholic beverages, and ethanol manufacturing. The roots consist of cyanogenic glycosides, which can lead to lethal cyanide poisoning if tubers arse not properly detoxified using different processing methods include washing, fermentation, boiling, peeling and chemical processing to escape toxin content. The current review summarizes cassava's bioactive components which could be a potential source of various pharmaceutical drugs as well as a source of traditional and modern food applications. 2024 The Authors. eFood published by John Wiley & Sons Australia, Ltd on behalf of International Association of Dietetic Nutrition and Safety. -
Bioactive Compounds and Biological Activities of Cassava (Manihot esculenta Crantz)
The most significant tropical tuberous crop, cassava (Manihot esculenta Crantz), is grown extensively around the world. It has a lot of minerals that have been linked to health benefits, is high in calories, and contains vitamin C, an antioxidant that supports the creation of collagen and boosts immunity. It is known to be the biggest generator of carbohydrates among stable crops, with its roots serving as the main source of starch and dietary energy. Currently, cassava flour is being used in gluten-free or gluten-reduced foods as a novel food application. The cassava plant extract is a rich source of major phytochemicals consisting of flavonoids, tannins, cardiac glycosides, anthraquinone, phlobatannins, saponins, and anthrocyanosides along with other antinutritive factors that contribute to its diverse pharmacological activities like antibacterial activity, in vitro ovicidal and larvicidal activity, antioxidant activity, anti-inflammatory activity, and analgesic and antipyretic activities. This chapter provides a comprehensive overview of the botanical features, production statistics, nutritional composition and benefits, phytochemicals present and their biological activities present in different parts of cassava plants, toxicity, food applications, and various strategies of breeding for crop improvement. Springer Nature Switzerland AG 2024. -
Exploring the Photocatalytic and Cytotoxic Potential of Quassia indica-Derived Bimetallic Silver-Zinc Oxide Nanocomposites
In response to the escalating need for nanomaterials characterized by enhanced properties and reduced environmental impact, this study addresses critical challenges associated with conventional nanomaterial synthesis methods, particularly focusing on concerns related to environmental toxicity and economic feasibility. In this study, we report the eco-friendly synthesis of silver-zinc oxide nanocomposites using leaf extracts of Quassia indica (QI- Ag: ZnO NC). The synthesized QI- Ag: ZnO nanocomposites were characterized using various techniques including UV-visible spectroscopy, X-ray diffraction (XRD), Fourier-Transform Infrared Spectroscopy (FTIR), Dynamic Light Scattering (DLS), Field-Emission Scanning Electron Microscopy (FE-SEM) with Energy Dispersive X-ray Spectroscopy (EDX), High Resolution Transmission Electron Microscopy (HR-TEM), and Selected Area Electron Diffraction (SAED). The photocatalytic activity of the biosynthesized QI- Ag: ZnO NC was evaluated against several textile dyes. Reactive Blue-220 exhibited the highest percentage of degradation (99.97%), closely followed by Reactive Blue-222 (99.37%), while Reactive Red-120 displayed significant degradation (94.62%). Remarkably, these nanocomposites exhibited significant photocatalytic degradation of the tested dyes, suggesting their potential application in wastewater treatment for dye removal. Furthermore, phytotoxicity studies were conducted to assess the impact of the nanocomposites on plant growth and brine shrimp mortality. To evaluate their cytotoxicity, the nanocomposites synthesized were assessed using the MTT assay on MCF-7 and MDA-MB-231 cancer cells. These findings suggest that QI- Ag: ZnO NCs have promising applications in environmental remediation and cancer therapy, opening avenues for further advancements in the arena of nanomaterial synthesis and utilization. The Author(s), under exclusive licence to Springer Nature B.V. 2024.