Volume 14 | Issue 3

 Abstract

A wireless sensor network (WSN) consists of geographically distributed, self-governing sensors that collect information about the network's environment. While biomedical sensors are effective and secure in their data collection and prevent potentially dangerous user actions within the network, it is still difficult to identify attacks from regular sensor nodes. Data requests and responses must be validated as part of authentication in wireless sensor networks (WSNs). Authentication is therefore the most crucial security measure. The Internet of Things requires lightweight authentication solutions for low-resource sensor nodes to operate effectively. Three factors were used in the development of a novel authentication system to achieve these objectives. As per the study's findings, the proposed system outperforms all previous comparable protocols, which makes it ideal for applications that use the WSN. Its efficiency can be measured by examining the transmission and computation expenses. This makes it possible for authorized users to access real-time sensing data from WSN sensor nodes after registering for the service. Before granting access to the network, WSN sensor and gateway nodes must verify a user. Among these are their mobility, scalability, dependability, and power efficiency. Performance can be energy efficient. It is unable to account for noise and increased traffic. They employ energy-efficient performance, protocols, modulation techniques, and algorithms. The cross-layer design of the wireless sensor network was covered in this survey. The network life time and throughput are being improved by further implementing the new low power MAC technology and dynamic node traffic analysis.

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Keywords: - Block chain, WSN, Cluster Protocol, Data Aggregation Authentication.

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The Blind AI Assistant is an intelligent assistive system designed to support visually impaired individuals in performing daily activities independently and safely. Visually challenged users often face difficulties in navigation, object identification, reading printed materials, and interacting with digital content. This project integrates Artificial Intelligence technologies such as Computer Vision, Speech Recognition, Optical Character Recognition (OCR), and Text-to-Speech (TTS) to provide real-time assistance through voice feedback. The system enables object detection, environment description, text reading, and voice-controlled interaction. A unique feature of this project is the volume button multi-press control mechanism, which allows users to switch between Navigation Mode, Assistant Mode, and Reading Mode without relying on touch screens. The proposed solution is cost-effective, portable, and designed to function on smartphones or embedded systems like Raspberry Pi. The system aims to enhance independence, confidence, and safety for visually impaired individuals. Index Terms - Blind AI Assistant, Computer Vision, Object Detection, OCR, Text-to-Speech, Voice Assistant, Assistive Technology, Navigation System, Artificial Intelligence.

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 Keywords

Blind AI Assistant. Artificial Intelligence , Computer Vision, Object Detection, Optical Character Recognition (OCR) , Text-to-Speech (TTS) ,Speech Recognition, Voice Assistant ,Assistive Technology, Navigation System , Emergency Alert System , Smartphone-based AI Application Accessibility Technology , Visually Impaired Assistance.

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Mahajanapadas and the rise of Buddhism and Jainism: Republics, philosophical reforms and early state formations

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Mahajanapadas and the rise of Buddhism and Jainism: Republics, philosophical reforms and early state formations

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CampusConnect is an innovative AI-powered chatbot system designed to enhance the accessibility and efficiency of college information retrieval for students and visitors. The system integrates Retrieval-Augmented Generation (RAG) technology with natural language processing to provide accurate, context-aware, and document-based responses to user queries. It assists users in obtaining information related to admissions, courses, examinations, campus facilities, departmental details, and institutional policies through an interactive conversational interface. By combining vector embeddings, semantic search, and large language models, CampusConnect retrieves relevant information from official institutional documents and generates reliable answers grounded in authentic data. Unlike traditional static websites or basic rule-based chatbots, this system ensures higher accuracy and reduces the risk of misinformation. The platform is designed to be user-friendly, scalable, and accessible through web or hardware kiosk interfaces. It reduces administrative workload, provides 24/7 automated support, and improves the overall student experience. This AI-based solution aims to deliver a cost-effective, intelligent, and efficient information retrieval system tailored specifically for educational institutions.

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CampusConnect, Artificial Intelligence, Retrieval-Augmented Generation (RAG), AI Chatbot, Natural Language Processing (NLP), Information Retrieval, Large Language Models (LLM), Vector Database, Educational Chatbot, Student Information System.

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In Ayurveda, a woman's life span is divided into different stages, among which Vriddhavastha corresponds to the geriatric age group. This stage is comparable to menopause i.e, Rajonivrutti, during which Vata dosha becomes predominant. Due to this dominance of Vata, there is an increased susceptibility to Vataja disorders such as rukshata of the yoni, leading to symptoms like vaginal dryness, discomfort, itching -yoni kandu, dyspareunia, burning sensation- yoni daha and recurrent vaginitis. Yoni shaithilya which is commonly encountered condition which may result in urinary complaints like stress and urge incontinence which further contribute to increased frequency of micturition and recurrent urinary tract infections, with advancing age there will be weakening of supports of pelvic organs which increases the risk of genital organ prolapse. There are various therapeutic approaches to manage these gynecological disorders in Ayurveda, one among them is Sthanika Chikitsa i.e, local therapeutic measures such as Yoni dhavana, Yoni pichu, Yoni dhoopana, Yoni lepana, and Yoni purana which can be employed both as preventive and curative modalities in these gynecological disorders in menopausal women. It helps in relieving discomfort caused by rukshata and manages conditions like mahayoni associated with yoni shaithilya. Each type of sthanika chikitsa has its own clinical significance and demonstrates better outcomes like, it improves local circulation, enhances tissue nourishment, maintains vaginal health, alleviates symptoms like dryness, burning sensation, dyspareunia and recurrent infections. The use of medicated oils and gh?itas possessing snigdha, vatahara, rasayana, and balya properties supports tissue rejuvenation and slows degenerative changes. Sthanika chikitsa administered with appropriate indications, strict aseptic precautions, and due care when combined with shamana and rasayana therapies, offers a holistic, safe, cost-effective and beneficial in disease management in Menopausal women, thus it plays a crucial supportive role in improving physical comfort, psychological well-being and overall quality of life in postmenopausal women.

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Rajonivrutti, Post Menopausal women, Sthanika Chikitsa, Quality of life

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E-retail and digital payment systems have become an important part of the Indian economy. In recent years, more people have started using online platforms to buy products and make payments. This study examines the growth, opportunities, and challenges of e-retail and digital payments in India using secondary data from reports, government publications, and industry sources. The analysis shows that increased internet use, smartphone adoption, and digital payment platforms have supported the expansion of online retail. Systems developed under institutions such as the Reserve Bank of India and the National Payments Corporation of India have also helped strengthen the digital payment ecosystem. The study finds that e-retail is expanding beyond large cities and reaching smaller towns and new customer groups. At the same time, issues such as cybersecurity risks, data privacy concerns, digital literacy gaps, and infrastructure limitations still affect growth. Overall, the results suggest that e-retail and digital payments will continue to develop in India, supported by technology, policy initiatives, and changing consumer behaviour.

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E-Retail, Digital Payments, UPI, Online Shopping, FinTech, Digital Economy

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ABSTRACT Self-awareness and self-esteem are fundamental psychological constructs that significantly influence personal growth and transformation. This paper explores how self-awareness fosters an accurate understanding of one's thoughts, emotions, values, and behaviors, while self-esteem reflects one's overall evaluation of self-worth. Through review of empirical studies and theoretical perspectives, this research demonstrates that a dynamic interplay between self-awareness and self-esteem facilitates adaptive functioning, resilience, and purposeful life choices. The findings emphasize the importance of fostering these constructs through educational interventions, counseling practices, and organizational development programs to support individual transformation.

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KEYWORDS: Self-Awareness, Self-Esteem, Personal Growth, Transformation, Psychological Development

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Education should change according to the needs and demands of society. Access to education, Preparation to implement NEP, learning through online portals is a new issues in higher education . Internationalisation of education, free movements of students and teachers are the issues which needs to be addressed. This paper identifies Crisis and challenges of Higher education in India after COVID19 and tries to find out ways to overcome these challenges. Pandemic has created a need for technology .Technology based teaching and learning has created multiple challenges after pandemic. Teaching, research and Extension form the basis of Indian higher education . During Pandemic teaching, learning had become the major issue. Face to face interaction with students was replaced by virtual class. Adoption of new technology in the learning process has brought up the issues of access ,acceptance of technology. After pandemic adoption of technology in teaching ,learning and evaluation is gaining importance. It also examines acceptance of technology and social factors in Higher education.

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Post pandemic, Teaching and learning, Challenges

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The selected autobiographies titled I Know Why the Caged Bird Sings and Gather Together in My Name unravels Maya Angelou's own life experiences in the broader context of the black community. While these narratives bring to the fore various challenges and struggles experienced by her people, it also opens up the scope of dialogue and change as evident in her own share of literary work combined with socio-political activism. Angelou assumes a critical position while discussing the shaping events in her life and presents an insider's view while bringing her people into the context. Thus, she also highlights the aspects of how black lives uphold resistance, resilience, pride and adaptability through their share of difficulties. The present paper aims to study the aspects of social and individual identity with regard to the black individual and community in order to locate Angelou's position within the same. It also examines black struggles, as represented in the select autobiographical texts against various systemic social inequalities prevalent in the American society. Further, it analyses the role of family in shaping Angelou's individuality, perspectives and convictions while also highlighting the impact of social inequalities on the quality of black experience and life.

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Angelou's Experiences, Struggles, Social Inequalities, Role of Family, Convictions and Change

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There is no denying the fact that Dalit literature, in recent years, has been gaining importance in the global academic discourse. The range of scholarly journals, the kind of research which has been carried out by the academicians, the wide-spanning publication houses, and the level of academic discussions through seminars and conferences on this topic, in recent years, are the case in point. It is also true that, until recently, unlike the other genres of Dalit literature, Dalit drama has played a somewhat subdued role in creating awareness among the masses against the atrocities of caste discrimination. Dalit dramas, hence, have remained a less discussed topic in Dalit studies than their other counterparts like novels, short stories and poetry. The primary aim of this paper, therefore, would be to highlight the role of Dalit drama in creating a space in this growing Dalit literary discourse. The other end of this paper is to investigate how far Dalit drama has become a potential mode of resistance against the injustices of caste atrocities meted out to the Dalits by the caste-Hindus for a long period of time. The paper also tries to shed light on the rich body of Dalit drama exist in many regional languages, which need global attention through translation. My study, through analytical mode, however, for certain reasons, would focus on some of the Dalit dramas across India which are translated into English. .

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resistance, discourse, Dalit literature, discrimination, translation

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Influencer marketing via social media has transformed how brands engage consumers, emerging as a rapidly growing component of contemporary marketing strategies (Campbell & Farrell, 2020; Vrontis et al., 2021). This theoretical study examines how different social media platforms shape influencer-follower dynamics and advertising effectiveness by synthesizing evidence from recent data-driven research. Prior studies consistently indicate that influencer credibility--reflected through trustworthiness, expertise, and perceived authenticity--plays a pivotal role in shaping consumer attitudes and purchase intentions (Saima & Khan, 2020; Kim & Kim, 2021). Moreover, platform-specific features and technological affordances influence the development and intensity of parasocial relationships between influencers and followers, which subsequently affect advertising outcomes and brand evaluations (Lou et al., 2023; Ki et al., 2020). The analysis further highlights the importance of social identity and influencer-audience congruence in amplifying marketing effectiveness across platforms (Farivar & Wang, 2022; Belanche et al., 2021). Existing evidence also suggests that influencer marketing campaigns often generate higher returns on investment than traditional promotional channels, with a substantial proportion of marketers reporting favorable performance outcomes (Dimitrieska & Efremova, 2021). However, such effectiveness is contingent upon strategic alignment, including the careful matching of influencer attributes with the target audience and platform characteristics, the maintenance of influencer credibility, and the facilitation of authentic and meaningful engagement. Overall, this integrative perspective contributes to a comprehensive understanding of the current influencer marketing landscape, its critical success factors, and the potential for leveraging social media analytics to optimize influencer-driven campaigns.

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Influencer marketing; Social media platforms; Credibility; Parasocial relationships; Congruence; Consumer engagement

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This study undertakes a comparative analysis of Kazuo Ishiguro's Never Let Me Go and Valeria Luiselli's Lost Children Archive, both in terms of their treatment of the related themes of silence, exile, and belonging in contemporary literary discourse. Ishiguro's dystopian fiction presents a picture of cloned children living in a controlled environment in England, meant to donate their organs, while Luiselli's politicised fiction deals with the issue of migrant children in the border region between Mexico and the U.S. Although both fictions differ in genre, location, and narrative style, they both examine the ways in which human life is controlled and regulated. Drawing on the works of psychology, trauma, and biopolitics, this study argues that silence in both novels does not simply refer to the absence of speech but, in fact, refers to a structural condition created by power relations. In Never Let Me Go, silence is internalized and becomes a form of emotional survival that works against rebellion, despite the partial revelation of the truth. The compliance of the clones with their predetermined fate, for instance, demonstrates the nuanced violence of institutional power, where belonging is meticulously crafted but remains conditional in its very construction. Memory, especially in relation to Kathy's narrative, appears as a tenuous substitute for freedom, an intimate space wherein dignity and identity are maintained. In contrast, Lost Children Archive understands silence as something enforced through politics. The voicelessness of the migrant children is caused by the borders and the legal system. The multi-layered narrative of Luiselli, who uses documentation and testimony in the narrative, is reminiscent of the fragmentary experience of the migrant communities. Exile is understood here as physical and generational rather than existential. Belonging is still tenuous and filtered through narrative. The act of archiving is understood here as an ethical imperative and a form of resistance to the politics of disappearance. Through the juxtaposition of the two works, the study reveals the manner in which contemporary fiction brings together dystopian fantasy and political realism to address the concerns that are shared in terms of vulnerability, precarity, and the value of human life. The two works follow the trajectory of innocence to revelation, constructed belonging to irrevocable exile, and finally, the rejection of incendiary revolt in favor of endurance and the preservation of the narrative. This juxtaposition situates literature as a key site to explore the manner in which the individual navigates identity in terms of systems that commodify, displace, and silence them. In an interdisciplinary dialogue with psychoanalysis, trauma studies, and migration studies literature, this study seeks to make an additional contribution to the scholarly discussions on marginality, memory, and ethics in twenty-first-century literature. The study contends that while Ishiguro and Luiselli write from different contexts, they share a common emphasis on the human affirmation of storytelling, in terms of memory or documentation

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Silence, Exile, Belonging, Trauma, Psychoanalysis, Biopolitics.

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 Abstract

The matrix is a very useful and significant mathematical construct of contemporary society. Originally formed as a methodical way of solving linear systems of equations, matrix theory has developed into a large framework that supports many disciplines, including quantum physics, linear algebra, numerical analysis, engineering design and most recently, data science. Matrix analysis allows for the development of complex multivariable systems, through the use of a structured, compact representation of linear transformations. Matrices are important in the practical sciences as well as in theoretical mathematics. They are used to create large-scale simulations, optimization methods, and computational models. Computers also rely heavily on matrices for their ability to represent input-output and optimization models in economics, to represent quantum states and coordinate transformations in physics, and in developing machine learning techniques and computer graphic transformations. Through the combination of analytic methods and existing literature, this paper investigates the theoretical foundation, key computational methods and interdisciplinary applications of matrices. The paper illustrates that matrices will remain vital for the development of modern scientific and technological inquiry and will serve as a common mathematical language between various disciplines.

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- Numerical analysis, multidisciplinary applications, computational methods, matrix theory, and linear algebra.

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The growth of digital fashion platforms has increased the need for intelligent and personalized styling systems. This paper presents an AI-powered Smart Wardrobe that combines deep learning-based clothing classification with a hybrid recommendation engine. Users can upload garment images and receive outfit suggestions based on body type, skin tone, and wear history. A transfer learning approach using ResNet50 is applied for clothing classification. The model achieved 93.2% validation accuracy and 88.7% real-world test accuracy. The system enhances wardrobe utilization, minimizes outfit repetition, and promotes sustainable fashion through automated personalization.

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Smart Wardrobe, Deep Learning, ResNet50, CLIP, Visual Embeddings, Personalized Recommendation, Computer Vision

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The people has seen fast alterations in anti- technology over the last few decades, and with the rise of cloud computing, the way we develop applications has changed quickly. This has made it easier to build applications that are both efficient and scalable. In recent years, the digital world has introduced many new innovations, especially with the use of Artificial Intelligence, or AI. This paper looks at how AI and cloud computing work together to help modernize applications by offering better services and infrastructure. By using both AI and cloud technologies, companies can now manage resources more smartly, use predictive analytics, automate deployment and scaling, and improve security, which helps them offer better solutions to their customers. Additionally, using cloud and AI technologies allows businesses to save money and deliver better services. The paper also talks about some challenges, like protecting personal data, and how strong AI governance can help solve these issues.

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AI, Cloud Computing

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Although comparative oncologists two decades ago may have tended to be on the defensive when arguing that fish, which are water-dwelling, poikilothermic vertebrates of greatly diverse form, might be of interest to cancer investigators, justification of their use no longer seems necessary. As testified by the increasing number of publications on fish tumors appearing in international journals, various fish species have now become widely accepted as useful tools for cancer research with, in some cases, distinct advantages over models using rodents or avian species. In particular, the study of tumors in lower aquatic animals has recently gained considerable importance as a means of detecting injurious agents in the environment. Investigation of fish tumors is also integral part of the basic biological approach to understanding possible common mechanisms involved in cancer development at various phylogenetic levels. The finding that tumors can be readily induced at various sites in fish species by different chemical carcinogens or viruses was of central significance in this context. Also if such fish is eaten by humans what are the possibilities of effect of such fishes can be further studied.

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fish, cancer, tumor, pathomorphology, tumorigenesis

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A medicinal compound's physicochemical characteristics, stability, manufacturability, and ultimately its therapeutic efficacy are all significantly influenced by its solid-state crystal structure. Detailed knowledge of molecular arrangement, intermolecular interactions, and polymorphism in drug substances has been made possible by advances in structural characterization techniques, particularly single-crystal and powder X-ray diffraction. This study examines the connection between pharmaceutical performance and crystal structures, emphasizing the effects of hydrogen bonding networks, polymorphism, solvate formation, and crystal engineering techniques. In contemporary pharmaceutical development, case studies of clinically important medications demonstrate how structural insights inform formulation design, regulatory choices, and lifecycle management.

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Solid-state crystal structure, Medicinal compounds, Pharmaceutical performance, physicochemical properties, Polymorphism, Hydrogen bonding networks, Solvate formation, Crystal engineering, Single-crystal X-ray diffraction

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Nanocavity Zeolite Y Encapsulated M(II) (M= Co, Ni, Cu & Zn) ternary complexes of L-Tyrosine and L-Histidine in situ in Na-Y Zeolites were synthesized using the ion exchange and flexible ligand methods. Initially, the metal ions were introduced into the zeolite framework through ion exchange with Na? ions, followed by diffusion of the amino acid ligands tyrosine and histidine into the super cages of the zeolite, where coordination with the metal centers occurred to form encapsulated ternary complexes by the reaction of ion exchanged process and flexible ligand method. The geometry and binding modes were explained by using various characterization techniques such as TGA, XRD, ESR, SEM, EDX, UV and IR spectroscopy

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Zeolite-Y, L-Tyrosine, L-Histidine, Flexible ligand synthesis, Encapsulation

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Artificial Intelligence (AI) has become the new technological paradigm that changes the industry of healthcare, finance, education, manufacturing, and autonomous systems. The strategic choice of programming languages is the main aspect of AI creation as it has a direct impact on the system performance, scalability, development efficiency, and deployment possibility. The paper is an analytical review of the programming languages in relation to Artificial Intelligence, the discussion of their development from symbolic AI to machine learning and deep learning models in modern times. The article assesses high-level languages such as Python, R, C++, Java, Lisp, and Prolog covering their paradigms, strengths, weaknesses, and areas of use. The research is comparative and descriptive in nature as it examines the suitability of language in fields of AI, including machine learning, deep learning, natural language processing, computer vision and robotics. The results have shown that high-level languages have high prototyping speed and large ecosystem advantages, whereas low-level languages offer better execution speed and hardware-level accessibility. The paper adds up to the conclusion that there is no single programming language that can fit all AI requirements; a hybrid and multi-language architecture is the best approach to the development of modern AI systems. The study offers advice to researchers, developers, and higher learning institutions on the suitable programming language that can be used, depending on the complexity of the project, the performance, and the scaling aspects of the project.

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Artificial Intelligence, Programming Languages, Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Python, R, C++, Java, Lisp.

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Driven by the need for financial sustainability, global aviation has shifted toward privatization, with private airports now managing 41% of global passengers despite making up only 14% of facilities worldwide. This study evaluates the impact of this transition on operational performance, revealing that private sector involvement--especially through Private Equity--can increase passengers per flight by 20% and overall traffic by up to 84% compared to government-run hubs. By integrating 2026 "digital-first" technologies like biometric tunnels, these airports have successfully reduced passenger processing times and boosted non-aeronautical revenue, which is projected to grow at a CAGR of 8.7% through 2030. Ultimately, while privatized airports excel in asset utilization and capacity growth, the research concludes that robust regulatory oversight is essential to prevent monopolistic pricing and ensure private profit aligns with public interests and carbon-neutrality targets.

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Airport Privatization, Operational Performance, Industry 4.0, Non-Aeronautical Revenue, Public-Private Partnership (PPP), Asset Utilization.

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