Volume 12 | Issue 1 |

 Abstract

In today's dynamic digital era, influencer marketing stands as a transformative force, redefining brand-consumer relationships. As traditional advertising diminishes in impact, influencers on social media platforms emerge as trusted voices shaping consumer behavior. This article explores the multifaceted influence of this strategy on businesses, emphasizing its role in amplifying brand visibility, fostering authenticity, and delivering measurable returns on investment. The ecosystem, ranging from macro to micro-influencers, allows for tailored, personalized approaches, while the rise of niche influencers targets specific audience segments with precision. Evolving dynamics encompass sustained relationships, challenges in credibility management, and the exploration of innovative content formats. Looking ahead, influencer marketing's future lies in video content, augmented reality integration, social responsibility alignment, exploration of new platforms, and adherence to data privacy regulations. In navigating this landscape, brands that prioritize authenticity and adaptability are poised to thrive in the ever-changing digital realm.

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INFLUENCER MARKETING IN TODAY'S DIGITAL WORLD BY LAKME

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In today's dynamic digital era, influencer marketing stands as a transformative force, redefining brand-consumer relationships. As traditional advertising diminishes in impact, influencers on social media platforms emerge as trusted voices shaping consumer behavior. This article explores the multifaceted influence of this strategy on businesses, emphasizing its role in amplifying brand visibility, fostering authenticity, and delivering measurable returns on investment. The ecosystem, ranging from macro to micro-influencers, allows for tailored, personalized approaches, while the rise of niche influencers targets specific audience segments with precision. Evolving dynamics encompass sustained relationships, challenges in credibility management, and the exploration of innovative content formats. Looking ahead, influencer marketing's future lies in video content, augmented reality integration, social responsibility alignment, exploration of new platforms, and adherence to data privacy regulations. In navigating this landscape, brands that prioritize authenticity and adaptability are poised to thrive in the ever-changing digital realm.

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Artificial intelligence, machine learning, bank, financial institutions, consumer satisfaction.

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Making investments in the startups will stand as the major decision as these are the only ideas that cannot be predicted and has not been taken birth as a fully exposed company. But the process of transformation need investments. People those are interested in investing in the startups are high risk takers. Investments in startups provide wings to the innovation. THE ANGEL INVESTORS plays a vital role as they invest for ideas that has no physical existence. They provided the initial capital or the SEED capital to the startups. And the other investors like HIGH NETWORTH INDIVIDUALS, BRIDGE INVESTORS are the there types of those investors who provides investments once the establishment of startup has taken place which helps in potential growth, risk of these investors in predictable.

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 Investments  Idea  Prediction  Capital  Investors  Potential growth  Physical existence  Angel investors

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This article delves into the dynamic landscape of electronic banking (e-banking) and examines the significant impact of electronic banking on consumer satisfaction. Given the increasing prevalence of electronic banking services, our study reviewed the existing literature to identify the complex aspects that shape the user experience. We investigate the impact of user-friendly interfaces, transaction efficiency, security protocols, and customer support on consumer satisfaction. Additionally, the article examines the accessibility of services across devices, the integration of innovative features, and the level of customization and personalization that e-banking platforms offer. The results highlight the important role that clear communication, cost efficiency and compliance with regulatory standards play in overall satisfaction. As the digital realm continues to redefine traditional banking paradigms, this article provides a comprehensive synthesis of current knowledge and identifies gaps for future research. By investigating the complex relationship between e-banking features and consumer satisfaction, we aim to help both academics and industry participants improve the quality of e-banking services.

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E-banking, customer satisfaction, E-commerce, cost saving, 24/7 access.

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The Kampli-Hampi corridor along the Tungabhadra basin in Karnataka, India, serves as a vital crossroad in South Indian history. Preceding the consolidation of the Vijayanagara Empire (1336-1646 CE), the Kampli kingdom functioned as a crucial transition state between medieval regional chiefdoms and an imperial polity. This study analyses the surviving architectural monuments, defensive structures, and socio-religious complexes across Kampli and its neighbouring imperial core. By Analysing spatial layouts, material culture, and construction techniques, we examine how architectural forms evolved from military strongholds into complex Indo-Islamic and Dravidian monuments. Particular attention is paid to defensive gateways, rock-cut fortifications, and hybrid civic structures. The research provides a comprehensive assessment of how physical monuments reflected political legitimacy, defensive necessity, and elite courtly life.

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ARCHITECTURAL AND SPATIAL ARCHETYPES OF THE KAMPLI-HAMPI CULTURAL SPHERE: A SOCIO-POLITICAL AND TYPOLOGICAL STUDY

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Contribution: This study examines the advantages and obstacles associated with the development, implementation, and assessment of a large language model (LLM) chatbot, MoodleBot, within computer science educational environments. It shows how LLMs could be used in LMSs like Moodle to help with self-regulated learning (SRL) and help-seeking behaviour. Computer science teachers have a lot of trouble adding new tools to LMSs to make the learning environment more supportive and interesting. MoodleBot solves this problem by giving students and teachers a place to interact with each other. Questions for Research: This study examines two questions, notwithstanding challenges such as bias, hallucinations, and the reluctance of teachers and educators to adopt new AI technologies. (RQ1) How much do students think MoodleBot is a useful tool for helping them learn? (RQ2) How accurate are the answers that MoodleBot gives, and how well do they fit with the course content that has already been set? Methodology: This study examines pedagogical literature regarding AI-driven chatbots and employs the retrieval-augmented generation (RAG) methodology for the design and data processing of MoodleBot. The technology acceptance model (TAM) looks at how much users accept something by looking at things like how useful they think it is and how easy it is to use. Forty-six students took part, and thirty of them filled out the TAM questionnaire. Results: Chatbots that use LLM, like MoodleBot, can make teaching and learning a lot better. This study found that there was a high accuracy rate (88%) in helping with course-related tasks. Students' positive feedback shows that AI-powered educational tools work and can be used in real life. These results show that educational chatbots can be used in courses to make learning more personalised and make teachers' jobs easier, but automated fact-checking needs to get better.

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Artificial Intelligence, Large Language Models, Retrieval-Augmented Generation, Learning Management Systems, AI Chatbot, Personalized Learning, Higher Education.

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Creative Commons Attribution 4.0 and The Open Definition

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Tumours of the kidney are among the most serious problems of urology. They often develop without any obvious symptoms in their early stages. Symptoms are often absent, so many cases are not diagnosed until the disease has progressed to a later stage, when treatment is less effective and survival rates are lower. Therefore, early and accurate problem identification is critical for improving patient outcomes. Computed Tomography (CT) imaging is often used in the diagnosis of kidney tumours, as it provides detailed cross-sections of renal structures. But manually reviewing CT scans is slow and subjective. This study addresses such issues by introducing an intelligent and automated system for the detection of kidney tumours, integrating fuzzy image enhancement, deep learning, ensemble machine learning, and MLOps practices. The proposed method is based on a fuzzy inference system for the improvement of the CT images of the kidneys. Medical images often suffer from low contrast, noise and inconsistent illumination that may obscure subtle tumour regions. The fuzzy system analyses the distributions of pixel intensity and uses adaptive enhancement rules based on the fuzzy logic principles of Lotfi . A. Zadeh. The fuzzy based method improves the features to be more prominent without losing the detail and over-saturation as in the case of traditional contrast enhancement methods. This preprocessing step highlights important structural details before feature extraction. Following the upgrade, the system employs two pre-trained deep convolutional neural networks, DenseNet121 and ResNet101. The ideas for DenseNet came from Gao Huang and the ideas for ResNet came from Kaiming He. DenseNet121 uses dense connectivity patterns to enable feature reuse and gradient flow across layers. This allows the fast learning even on small medical datasets. On the other hand, ResNet101 has residual connections that allow very deep networks to train well without running into problems with gradients that vanish. Both models utilise transfer learning on large image datasets to extract high-level, discriminative features from augmented CT scans. We use the feature fusion strategy to combine the features taken from the two PT-DCNNs to make the classification work even better. This combined representation uses information from both architectures that complement each other, providing us with a richer and more useful feature set. We don't just use deep learning for classification. Instead we use a weighted ensemble classifier combining Support Vector Machines (SVM) and Random Forest (RF) to do the job. SVM helps with classification with a strong margin. Random Forest makes things more stable using multiple decision trees. Their predictions are combined through a weighted averaging mechanism to make a final decision that is more stable and reliable. To increase the dataset and make it more generalisable and stable, data augmentation techniques were applied. We ran various versions of the CT images, adding controlled noise and fake distortions to simulate problems encountered in the real world of imaging. This process makes the model more capable to work properly in different clinical settings. Moreover, the application of Machine Learning Operations (MLOps) techniques enables to make all the processes reproducible, scalable and easily deployable in clinical practice. System is getting better all the time with model versioning, monitoring and retraining tools The experimental results show that the model performs excellently with accuracy of 99.2% on high quality CT images and 98.5% on noisy images. These results are better than many traditional machine learning and deep learning methods that work alone. The suggested automated system can assist urologists and radiologists by providing them with a reliable second opinion, reducing the number of diagnostic errors, making their work easier and allowing prompt action. Ultimately, this intelligent framework represents a major step forward in computer-assisted medical diagnosis and could help patients live longer and health care become more efficient.

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Kidney tumor detection, fuzzy logic, machine learning, image segmentation, CAD systems.

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Rights to human beings are basic rights and liberties that everyone deserves by virtue of being a human, no matter what their race or colour is; it does not depend on an individual’s nationality, religion or gender etc.. In fact, these rights are guaranteed by international human right treaties and regional human rights systems the legal basis of protection and promotion on a global scale for everyone. This paper seeks to offer a thorough investigation into the international human rights treaties and also regional systems of human rights that are highlighting their importance, peculiarities as well as in what way they contribute for the development of Human Rights worldwide.

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INTERNATIONAL HUMAN RIGHTS AND REGIONAL ARRANGEMENTS: A FRESH LOOK

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The Internet of Things (IoT) represents a paradigm shift that enables seamless interconnectivity between cognitive devices, machines, and location-based data processing platforms, fostering the development of smart environments. As the total number of connected and newly integrated devices proceeds to rise, IoT introduces significant challenges in both operational management and information technology, particularly in network design and security. The development of advanced technologies like emerging network technologies, containing technologies like SDN (Software-Defined Networking), SD-WAN (Software-Defined Wide Area Networking), and NFV (Network Functions Virtualization), have meaningfully transformed modern communication infrastructures and Internet Exchange Points (IXP) has flagged the way for innovative networking frameworks that improve the security and scalability of IoT infrastructures. This paper discovers the critical security tasks faced by IoT networks and proposes a security architecture leveraging able to execute and virtualized innovations, specifically SDN and NFV. The design based on its architecture, its implications, and its applications in IoT ecosystems are analyzed in detail. Furthermore, an extensive review of existing research in this domain is presented, along with future directions to address cyber security and the privacy risk in diverse IoT systems and the networks.

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Internet-of-Things; IoT, SDN, SD Networking, cyber security, infrastructure, NFV

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Seventy percent of global freshwater withdrawals are attributed to agricultural irrigation. Irrigation efficiency has become a critical goal for sustainable agricultural development in response to climate variability and increasing food demand. Water Use Efficiency (WUE) refers to the ratio of crop yield to the volume of water applied. Irrigation technologies generally follow two approaches to water application. This study examines how different irrigation methods affect crop productivity. It draws on literature from field studies and global assessments to evaluate the relative performance of flood irrigation and modern irrigation systems in terms of water applied, crop yield, and irrigation water-use efficiency. A standard framework for estimating crop evapotranspiration and net irrigation requirements is provided by the Food and Agriculture Organization (FAO).

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Drip irrigation; Flood irrigation; Water use efficiency (WUE); Crop productivity; Irrigation management; Crop water requirement (CWR); FAO CROPWAT; Sustainable agriculture; Water resource optimization.

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Creative Commons Attribution 4.0 and The Open Definition