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Cybersecurity Implications for Digital Competence
This chapter explores the critical role of cybersecurity in enhancing digital competence within agile and hierarchical organisational structures. It provides a theoretical framework connecting digital skills, technology, and cybersecurity, emphasising their collective importance in modern business environments. The chapter examines how agile organisations prioritise adaptability in addressing cybersecurity threats, while hierarchical organisations rely on structured processes to ensure security and compliance. The chapter identifies each structures strengths and challenges in integrating cybersecurity through comparative analysis. It further discusses the future of digital competence, highlighting how cybersecurity drives digital transformation and impacts operational performance. Best practices and recommendations are provided for organisations to integrate cybersecurity effectively, ensuring long-term resilience and sustainability in an evolving cyber landscape. 2026 selection and editorial matter, Festus Adedoyin; individual chapters, the contributors. -
Cybersecurity Threats Detection in Intelligent Networks using Predictive Analytics Approaches
The modern scenario of network vulnerabilities necessitates the adoption of sophisticated detection and mitigation strategies. Predictive analytics is surfaced to be a powerful tool in the fight against cybercrime, offering unparalleled capabilities for automating tasks, analyzing vast amounts of data, and identifying complex patterns that might elude human analysts. This paper presents a comprehensive overview of how AI is transforming the field of cybersecurity. Machine intelligence can bring revolution to cybersecurity by providing advanced defense capabilities. Addressing ethical concerns, ensuring model explainability, and fostering collaboration between researchers and developers are crucial for maximizing the positive impact of AI in this critical domain. 2024 IEEE. -
Cybersecurity vulnerabilities in federated learning
Federated Learning (FL) has been conceived as a dispersed machine learning paradigm facilitating collaborative learning at edge devices without exposing raw data. The model is amenable to privacy preservation and data protection regulation, for example, General Data Protection Regulation compliance. Yet, more widespread deployment of FL reveals a new and extreme spectrum of cybersecurity risks. These consist of data poisoning attacks that can potentially severely contaminate model integrity, model inversion attacks that can potentially recover sensitive data from exchanged gradients, adversarial manipulations where malicious agents take advantage of model weaknesses, and incidental privacy leakage. The impact and real world implication of these attacks differs, for example, a successful poisoning attack in medicine can result in misdiagnosis, model inversion in the finance sector could leak client confidential data, and adversarial attacks in Internet of Things (IoT) would control autonomous devices with safety consequences. This chapter critically reviews these threats taking into consideration attack feasibility, harm extent, and detectability, inspired by recent case studies illustrating their applicability in real world FL deployments. We also analyze the effectiveness of current state of the art countermeasures like robust aggregation methods, differential privacy, and cryptographic methods like secure multiparty computation and homomorphic encryption. By synthesizing current research on attack paradigms and counterattack architectures, the chapter offers practical knowledge towards constructing secure, robust, and trustworthy FL systems, particularly in high-risk applications like medicine, finance, and critical infrastructure. 2026 selection and editorial matter, Swati Sah, Rejwan Bin Sulaieman, and Aditya Dayal Tyagi; individual chapters, the contributors. -
Cyclic property of iterative eccentrication of a graph
The eccentric graph of a graph G, denoted by Ge, is a derived graph with the vertex set same as that of G and two vertices in Ge are adjacent if one of them is an eccentric vertex of the other. The process of constructing iterative eccentric graphs, denoted by Gek is called eccentrication. A graph G is said to be ?-cyclic(t,l) if G,Ge,Ge2,...,Gek,Gek+1,...,Gek+l are the only non-isomorphic graphs, and the graph Gek+l+1 is isomorphic to Gek. In this paper, we prove the existence of an ?-cycle for any simple graph. The importance of this result lies in the fact that the enumeration of eccentrication of a graph reduces to a finite problem. Furthermore, the enumeration of a corresponding sequence of graph parameters such as chromatic number, domination number, independence number, minimum and maximum degree, etc., reduces to a finite problem. 2023 World Scientific Publishing Company. -
Cyclic property of iterative eccentrication of trees
A tree graph is an acyclic graph. The eccentric graph of a graph G, denoted by Ge is a derived graph with the vertex set same as that of G and two vertices in Ge are adjacent if one of them is an eccentric vertex of the other. The process of finding eccentric graph of a graph is called eccentrication and that of constructing iterative eccentric graphs, denoted by Gek, is called iterative eccentrication. A graph G is said to be ?-cyclic(t,l) if G, Ge, Ge2,?, Gek, Gek+1,?, Gek+l are the only non-isomorphic graphs, and the graph Gek+l+1 is isomorphic to Gek. In this paper, we prove the existence of an ?-cycle for any tree graph on n vertices. We also obtain some important results on eccentric graphs of trees. Then, we present a conjecture on the cyclic property of eccentrication of a general graph G. Finally, an analogy between the concept of ?-cycle for a graph and the dichotomy of the Riemann sphere into Fatou sets and Julia sets is presented. We also state some open problems in the area. 2025 World Scientific Publishing Company. -
Cytogenetic Consequences Of Food Industry Workers Occupationally Exposed To Cooking Oil Fumes (Cofs)
Background: Cooking oil fumes (COFs) with smoking habits is a substantial risk that aggravates genetic modifications. The current study was to estimate the biological markers of genetic toxicity counting Micronucleus changes (MN), Chromosome Aberrations (CA) and DNA modifications among COFs exposures and control subjects inherent from South India. Materials and Methods: Present analysis comprised 212 COFs with tobacco users and equivalent number of control subjects. Results: High frequency of CA (Chromatid type: and chromosome type) were identified in group II experimental subjects also high amount of MN and DNA damage frequency were significantly (p < 0.05) in both subjects (experimental smokers and non-smokers). Present analysis was observed absence of consciousnessamong the COFs exposures about the destructive level of health effects of tobacco habits in working environment. Conclusion: COFs exposed workers with tobacco induce the significant alteration in chromosomal level. Furthermore, a high level of rate of genetic diseases (spontaneous abortion) were identified in the experimental subjects. This finding will be helpful for preventive measures of COFs exposed workers and supportive for further molecular analysis 2021,Asian Pacific Journal of Cancer Prevention. All Rights Reserved. -
Cytokine see-saw across pregnancy, its related complexities and consequences
During pregnancy, a woman's immune system adapts to the changing hormonal concentrations, causing immunologic transition. These immunologic changes are required for a full-term pregnancy, preserving the fetus' innate and adaptive immunity. Preterm labor, miscarriage, gestational diabetes mellitus, and pre-eclampsia are all caused by abnormal cytokine expression during pregnancy and childbirth. A disruption in the cytokine balance can lead to autoimmune diseases or microbiologic infections, or to autoimmune illness remission during pregnancy with postpartum recurrence. The cytokine treatments are essential and damaging to the developing fetus. The current review summarizes the known research on cytokine changes during pregnancy and their possible consequences for pregnant women. Studies suggest that customizing medication for each woman and her progesterone levels should be based on the cytokine profile of each pregnant woman. Immune cells and chemicals play an important function in development of the placenta and embryo. During pregnancy, T cells divide and move, and a careful balance between proinflammatory and anti-inflammatory cytokines is necessary. The present review focuses on the mother's endurance in generating fetal cells and the immunologic mechanism involved. 2022 International Federation of Gynecology and Obstetrics. -
D-GRAM: Dynamic Game-Theoretic Risk Modeling for Adaptive Cyber Defense
Cybersecurity threats are increasing in scale and sophistication, requiring strategic decision-making for cost-effective defense. This work presents a non-cooperative game-theoretic framework to model the interaction between a rational attacker and a defender with limited resources. Each player selects from a finite set of strategies, and payoffs are computed dynamically based on the probability of attack success, defense cost, and potential impact. A loss-risk relationship is used to populate the payoff matrix, ensuring that outcomes reflect realistic operational conditions. A mixed-strategy Nash equilibrium is calculated to determine optimal attack and defense probabilities, thereby balancing resource use and risk mitigation. To improve practicality, an adaptive defense mechanism is introduced, allowing the defender to update strategy probabilities incrementally based on observed attacker behavior. Sensitivity analysis reveals how equilibrium strategies adjust in response to variations in attack cost, defense cost, and impact severity. The results highlight how adaptive learning enhances resilience while minimizing unnecessary defense efforts, making the approach suitable for resource-constrained network environments. 2025 IEEE. -
Dalit Activism
In the post-Ambedkar era, Dalit activism has expanded beyond traditional modes and methods of protest by adopting diverse strategies. This includes social media campaigns like #DalitLivesMatter, which align with global movements such as #BlackLivesMatter. It signals a shift towards more globalised and intersectional forms of protest. There is a notable transition from an exclusive focus on domestic advocacy to transnational alliances for greater impact. Caste-based oppression has been framed as a violation of fundamental human rights, which demands accountability from both national and international agencies. Many scholars find the gap between international advocacy for Dalit rights and grassroots-level Dalit activism quite concerning. Some scholars believe that Dalit activism has lost much of its transformative potential and revolutionary vigour, and the movement has been reduced to a mere pressure group. These political pitfalls allow us to understand the challenges and complexities of Dalit activism and the factors that shaped its course. This chapter aims to trace the trajectory of Dalit activism and provide a detailed background to facilitate a critical engagement with the concept of activism. It explores its historical progression, strategic shifts, and ongoing struggles to offer a comprehensive view of how Dalit activism has evolved into its current form. 2026 selection and editorial matter, Mahitosh Mandal and Sanjiv Kondekar; individual chapters, the contributors. -
Dalit Historiography
Dalit historiography positions itself as a direct challenge to the casteist narratives of Brahmanical historiography, which have long dominated historical accounts of India. It critiques mainstream historiographies for being casteist, for excluding Dalit voices, and for misrepresenting Dalit experiences within societal and institutional frameworks. Grounded in the experiences of oppression faced by Dalits, the Dalit historiographic approach seeks to expose the biases of Brahmanical knowledge systems and the exclusionary practices embedded within colonial and nationalist histories. Drawing from Ambedkars critique of positivist history and his call for a history that addresses caste-based inequalities, Dalit historiography emphasises the need for alternative narratives. It underscores the active role of Dalits as key participants in shaping history. Through life narratives, folklore, and oral traditions, it highlights the contributions and experiences of Dalit communities that have long been overlooked. By confronting caste discrimination and advocating for social justice, Dalit historiography aims to dismantle the hegemonic Brahmanical structures and offer a more inclusive and intersectional understanding of history. 2026 selection and editorial matter, Mahitosh Mandal and Sanjiv Kondekar; individual chapters, the contributors. -
Dalit Studies
Dalit Studies emerged as a pivotal academic discipline in South Asia in the 1990s with a unique set of research agendas that offer new frameworks for understanding caste, gender and marginalised identities. The field stands out for integrating theoretical frameworks into the lived experiences of caste-oppressed communities. It was shaped by the confluence of material, ideological and intellectual shifts, including the critique of caste-Hindu dominance in academia. By prioritising the experiences of Dalits, it bridges the gap between theory and practice and engages with critical debates on representation, particularly insider vs. outsider perspectives in articulating Dalit experiences. It equips the learners not only with intellectual tools but also with the skills to attain self-reliance and dignity in their socio-political lives. As a critical tool, it calls for a rethinking of knowledge production, methodology and representation. Its growing global relevance is evident in universities across the United States, the United Kingdom, and South Africa, where programs and courses explore the intersections of caste, race, and gender within broader contexts of subjugation and resistance. This chapter traces the evolution of Dalit Studies, examining its theoretical foundations, key concepts and debates, and its growing visibility in academic institutions worldwide 2026 selection and editorial matter, Mahitosh Mandal and Sanjiv Kondekar; individual chapters, the contributors. -
Damaged Relay Station: EEG Neurofeedback Training in Isolated Bilateral Paramedian Thalamic Infarct
Stroke is a major public health concern and leads to significant disability. Bilateral thalamic infarcts are rare and can result in severe and chronic cognitive and behavioral disturbances - apathy, personality change, executive dysfunctions, and anterograde amnesia. There is a paucity of literature on neuropsychological rehabilitation in patients with bilateral thalamic infarcts. Mr. M., a 51 years old, married male, a mechanical engineer, working as a supervisor was referred for neuropsychological assessment and rehabilitation with the diagnosis of bilateral paramedian thalamic infarct after seven months of stroke. A pre-post comprehensive neuropsychological assessment of his cognition, mood, and behavior was carried out. The patient received 40 sessions of EEG-Neurofeedback Training. The results showed significant improvement in sleep, motivation, and executive functions, however, there was no significant improvement in memory. The case represents the challenges in the memory rehabilitation of patients with bilateral thalamic lesions. 2024 Neurology India, Neurological Society of India. -
Dampers to Suppress Vibrations in Hydro Turbine-Generator Shaft Due to Subsynchronous Resonance
There are numerous applications to evaluate the damage caused by subsynchronous resonance (SSR) to a turbine-generator shaft. Despite multiple applications, there are relatively few studies on shaft misalignment in the literature. In this paper, stresses in the existing turbine-generator shaft due to subsynchronous resonance were studied using finite element analysis (FEA). The 3D finite element model reveals that the most stressed part of the shaft is near the generator terminal. A new nonlinear damping scheme is modeled to reflect the torsional interaction and to suppress the mechanical vibration caused by subsynchronous resonance (SSR). Stresses developed due to the addition of capacitors in the system at high rotational speeds and deformation of the shaft during various modes of oscillations were evaluated. Experimental investigations are carried out in reaction turbine connected to a 3kVA generator. Simulation is carried out for the experimental setup using ANSYS. According to the simulation results, the damper installed near the generator terminal provides satisfactory damping performance and the subsynchronous oscillations are suppressed. 2021, Springer Nature Singapore Pte Ltd. -
Dandelion Algorithm for Optimal Location and Sizing of Battery Energy Storage Systemsin Electrical Distribution Networks
This paper describes a new way to improve the performance of an EDN by integrating distributed battery energy storage systems (BESs) in the best way possible. This method is based on the Dandelion Algorithm (DA). The search space for BES locations is first predetermined using loss sensitivity factors (LSFs), and then DA is used to determine the optimal locations and sizes. The reduction of real power distribution loss is regarded as the primary objective function, and the impact of BESs is extended to examine the network voltage profile, voltage stability, and GHG emissions. IEEE 33-busEDN is used to calculate the computational efficiency of LSF-DA. Results show that DA is more efficient than Archimedes optimization (AOA), future search algorithm(FSA), pathfinder algorithm(PFA), and butterfly optimization algorithm(BOA) algorithms. Furthermore, the results show that the proposed DA enhances all technological and environmental factors and RDN performance. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
DarcyForchheimer Nanoliquid Flow and Radiative Heat Transport over Convectively Heated Surface with Chemical Reaction
Abstract: Improving the heat transport of energy transmission fluids is a vital challenge in numerous engineering applications such as photovoltaic thermal management, heat exchangers, transport and energy-saving processes, solar collectors, automotive refrigeration, electronic equipment refrigeration, and engine applications. Nanofluids address the challenges of thermal management in engineering applications. The DarcyForchheimer flow of magneto-nanofluid initiated by a stretched plate is investigated with application of the Buongiorno model. The features of the nth order chemical reaction, Rosseland thermal energy radiation, and non-uniform heat sink/source are also scrutinized. The Buongiorno nanoliquid model is implemented, which includes the frenzied motion of the nanoparticles and the thermal diffusion of the nanoparticles (NPs). Thermal and solutal convection heating boundary conditions are also incorporated. Boundary layer approximations are used in the mathematical derivation. The non-linear control problem is deciphered with application of the RungeKutta shooting method (RKSM). The results for the relevant parameters are analyzed in dimensionless profiles. In addition, the friction factor on the plate, the heat transport rate, and the mass transport rate of the nanoparticles are calculated and analyzed. 2022, Pleiades Publishing, Ltd. -
DarcyForchheimerBrinkman flow of a Newtonian fluid through an enclosure with two straight boundaries and one curved boundary
The study examines the flow and heat transfer of a Newtonian fluid in a porous medium inside an enclosure with two straight boundaries and one curved boundary. This setup is important for heat storage and energy systems. The aim of this study is to solve the Brinkman-Forchheimer (BF) equation in an enclosure with two straight and one curved boundary. The research also looks to perform a thorough heat transfer analysis to improve the understanding of thermal behaviour in porous medium BF flow. Additionally, the study calculates the Nusselt number using a compatibility condition to ensure the results are physically consistent. Finally, it fits the Nusselt number as a function of the shape factor (s) and the Forchheimer number (F). This helps in capturing the trends in convective heat transfer behaviour within the medium.The main assumptions include a steady, fully developed flow in the z-direction with a constant axial pressure gradient -, and zero axial velocity (w = 0) on all boundaries. The domain in three-dimensions is defined in cartesian coordinates (x,y,z), with on the curved boundary,ensuring the spatial constraint of the geometry. The quasi-linearisation method is used to linearise the governing equations, resulting in a system of linear algebraic equations that is subsequently solved using the alternate direction implicit (ADI) method with an accuracy of. The findings show that an increase in the shape factor (s) results in a plug flow behaviour and better heat retention, as in higher temperature profiles and centreline velocities. In contrast, higher Forchheimer numbers causes a drop in both velocity and temperature due to increased flow resistance. But as F goes up, the Nusselt number always increases, meaning heat is better transferred through convection. The study also shows that hot spots and heat islands form inside the enclosure, especially when the shape factor is higher, because the heat builds up more quickly when there is less resistance, which is an essential thing to think about for things like heat storage systems, where it is crucial to have better thermal efficiency. The Author(s), under exclusive licence to Springer Nature India Private Limited 2025. -
Dark matter, dark energy, and alternate models: A review
The nature of dark matter (DM) and dark energy (DE) which is supposed to constitute about 95% of the energy density of the universe is still a mystery. There is no shortage of ideas regarding the nature of both. While some candidates for DM are clearly ruled out, there is still a plethora of viable particles that fit the bill. In the context of DE, while current observations favour a cosmological constant picture, there are other competing models that are equally likely. This paper reviews the different possible candidates for DM including exotic candidates and their possible detection. This review also covers the different models for DE and the possibility of unified models for DM and DE. Keeping in mind the negative results in some of the ongoing DM detection experiments, here we also review the possible alternatives to both DM and DE (such as MOND and modifications of general relativity) and possible means of observationally distinguishing between the alternatives. 2017 COSPAR -
Data acquisition using NI LabVIEW for test automation
In a fighter aircraft, the pilot's safety is of utmost importance, and the pressure sensing in the pilot's mask is essential for ensuring the pilot's safety. This innovative solution ensures the swift and accurate measurement of pressure, minimizing the risk of potential hazards and enhancing military aviation safety. Additionally, it provides a robust and reliable solution that can withstand the harsh and challenging conditions often encountered in the field. This chapter explores the advanced capabilities and benefits of utilizing the National Instrument USB-6363, programmed with LabVIEW, in military aviation, highlighting its potential for revolutionizing pressure measurement processes in this critical field. It describes a research study on developing a pressure-sensing system for pilot masks using NI USB 6363 and LabVIEW. 2023, IGI Global. -
Data Analysis and Machine Learning Observation on Production Losses in the Food Processing Industry
Food wastage and capturing lineage from production to consumption is a bigger concern. Yielding, storage and transportation areas have evolved to a great extent associated to manufacturing and automation which lead to technical advancements in food processing industry. In such situation, losses are generally observed in the crop production which are sometimes minimal and ignored. However, in some cases these losses are huge and are becoming a threat to the both producers and consumers. Here we considered data related to dairy products and analysed the production losses especially while processing them in the treating unit. Literature on parameters and associated data analysis in the form of graphical representation are provided in the appropriate sections of the paper. Linear regression and correlation were envisaged in view of incorporating machine learning techniques understanding production losses. Karl Pearson's correlation provides an observation related to association of parameters which are desired to be less coupled in terms of employing proposed newer methodology. 2023 IEEE. -
Data analysis in road accidents using ann and decision tree
Road accidents have become some of the main causes for fatal death globally. A report tells that road accident is the major cause for high death rate other than wars and diseases. A study by World Health Organization (WHO), Global status report on road safety 2015 says over 1.24 million people die every year due to road accidents worldwide and it even predicts by 2020 this number can even increase by 20-50%. This can affect the GDP of the Country, for developing countries this can affect adversely. This paper shows the use of data analytics techniques to build a prediction model for road accidents, so that these models can be used in real time scenario to make some policies and avoid accidents. This paper has identified the attributes which has high impact on accident severity class label. IAEME Publication.