Volume 13 | Issue 4

 Abstract

The adoption of e-banking services has transformed the banking sector, offering convenience and efficiency to customers. However, employees in private sector banks face several challenges in adapting to this technological shift. This paper investigates the key obstacles faced by bank employees in adopting e-banking services in the private sector banks of Tirupur. By exploring various factors, including technological barriers, lack of training, resistance to change, and the impact of organizational culture, the study sheds light on the difficulties encountered by employees in integrating e-banking solutions into their daily operations. Additionally, the paper examines how these challenges affect employee productivity, customer service, and overall job satisfaction. The findings underscore the importance of providing comprehensive training programs, fostering a culture of innovation, and addressing technical challenges to ensure smooth adoption of e-banking services and to enhance overall organizational performance.

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 Keywords

E-banking, Employee Challenges, Technology Adoption, Training, Resistance to Change.

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Agriculture is a backbone of the global economy, and empowering farmers with advanced technology and tools can enhance productivity and sustainability. Traditional agricultural methods were based on manual tools, natural fertilizers, practices like crop rotation and rainwater harvesting to sustain productivity and soil health. Farmers used their predictive, observational knowledge for weather, crop prediction and recommendation natural pest control remedies, though these methods lacked scalability and resilience against environmental changes. Machine learning offers a promising solution by providing the prediction and recommendation capabilities by analyzing vast datasets, including soil, weather, and crop patterns, to forecast yields, recommend and predict suitable crops, and optimize fertilizer usage. This paper proposes a machine learning-based crop, fertilizer recommendation and prediction, weather and rainfall prediction. The system uses 4 features for crop prediction, 8 features for crop recommendation, 9 features for fertilizer recommendation and 7 features for yield prediction. Along with tools for farmer's assistance like news feed, chatbot support. We evaluate four models--Decision Tree Classifier, Random Forest Classifier, Random Forest Regressor and Statistical Analysis --showing that the models achieve high accuracy by leveraging data-driven patterns, feature importance analysis to optimize predictions and recommendations for agricultural needs.

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 Keywords

Machine learning, Agriculture, prediction, Recommendation, Decision Tree, Random Forest classifier, Random Forest Regressor, Statistical Analysis, Recall, F1 score.

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A global challenge that has become a menace is the example of cancers such as lung and colon cancer (LC AND CC) Colon cancer(CC). The path of this research, therefore, in this very important area, is early detection through the use of AI in histological image analysis. The study introduces a novel hybrid feature set aiming to improve classification accuracy by integrating DenseNet201 with color histogram techniques. The validation of this feature set works with eight major ML algorithms-KNN, SVM, Light GBM, CatBoost, XGBoost, decision trees, random forests, and multinomial naive Bayes. This comprehensive study, therefore, highlights an exotic model that achieved an accuracy of 99.683% on the LC AND CC25000 dataset. Taking the same concept to breast cancer detection using the Break His dataset shows a great accuracy of 94.808%. These results highlight the revolutionary potential of AI in the challenging area of histopathological analysis and therefore stand to become a transformative player in accelerating diagnostic accuracy. A thorough comparative analysis showcases the strengths and weaknesses of current AI practices in medical imaging, outlining a pathway for improvement and future clinical application.

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 Keywords

Densenet201, histopathological images, image processing, lung and colon cancer, machine learning.

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The construction industry in India faces increasing pressure to meet international quality standards and customer expectations. This study explores the application of Total Quality Management (TQM) and Six Sigma methodologies within the sector to enhance construction quality and project performance. It emphasizes TQM as a comprehensive philosophy involving continuous improvement, employee participation, and customer satisfaction across all project stages. Through a detailed case study of a construction project. The paper evaluates the quality of concrete work using Six Sigma performance metrics. The findings reveal disparities in quality perceptions among stakeholders and identify barriers such as inadequate training, communication gaps, and poor quality control practices. By integrating TQM principles with Six Sigma tools, the research advocates for a structured quality management framework, including stakeholder training, establishment of quality circles, and development of national bodies to promote quality awareness. The proposed model offers a practical approach for enhancing competitiveness and achieving defect-free construction outcomes.

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TQM, SIX Sigma

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Image steganography has recently received much attention as a form of secure communication whereby one or more hidden data are embedded into an image. Among the most widely used techniques for data hiding is the Least Significant Bit (LSB) method, where the least significant bits of pixel values are replaced with secret data. However, LSB based steganography often results in visible distortions that can be detected easily. This paper proposes an improved method that utilizes image balancing methods prior to data embedding to reduce such distortions. The method consists of preprocessing the image to balance its brightness, contrast, and colour balance in such a manner that the hidden data will not significantly alter the visual look of the image. The secret data is then embedded into the least significant bits of the balanced image. Experimental results have shown The proposed method successfully conceals data and keeps the quality of the cover image intact. Besides, extraction of the hidden information is carried out with less error rate, indicating the success of the proposed method in both security and visual integrity. This approach is tested through the usage of image quality metrics and accuracy of data extraction that makes it a good approach for practical use in secure communication.

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 Keywords

Image Steganography, Least Significant Bit (LSB), Image Balancing, Data Hiding, Image Processing.

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Keywords: Drotaverine HCl, Aceclofenac, UV spectrophotometry, Simultaneous equation method, Method validation

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A decentralized social media application using Ethereum redefines the nature of interaction on the internet with an emphasis on privacy, ownership, and transparency. There is no one point of control such as for central sites, making censorship and abuse of data unthinkable. User activity like posting and sharing is controlled by automatically acting smart contracts that bring in trust and finality. Web3 wallets like MetaMask eliminate the traditional logins with added security and reduced data breaches. Direct users own their contents, encouraging the existence of an uncensored society. A rewarding system compensates users for user participation in blockchain tokens, encouraging user-led and fair social networking.

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Ethereum, Metamask, Smart Contact, IPFS, Block chain

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In the new evolving world, traffic rule violations have become a central issue for majority of the developing countries. The numbers of vehicles are increasing rapidly as well as the numbers of traffic rule violations are increasing exponentially. Managing traffic rule violations has always been a tedious and compromising task. Even though the process of traffic management has become automated, it's a very challenging problem, due to the diversity of plate formats, different scales, rotations and non-uniform illumination conditions during image acquisition. The principal objective of this project is to control the traffic rule violations accurately and cost effectively. The proposed model includes an automated system which uses camera to capture video. The project presents Automatic Number Plate Recognition (ANPR) techniques and other image manipulation techniques for plate localization and character recognition which makes it faster and easier to identify the number plates. After recognizing the vehicle number from number plate the SMS based module is used to notify the vehicle owners about their traffic rule violation. An additional SMS is sent to Regional Transport Office (RTO) for tracking the report status

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Motivation In all the countries there are driving rules available for people to drive carefully by being honest and respecting. When these rules are broken it is defined as a road violation. There road violations that happens in day to day traffic. For an example most common violations such as red light violation, over-speeding, overtaking other vehicles through double white lines and single white lines. These road protocols are applied thoroughly for the places where most of the accidents happe

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This study analyzes the methods through which Rupi Kaur writes and spreads poetry on Instagram by examining the impact digital media including Instagram has had on modern literary practice. Social media has influenced the development of Insta poetry into its hybrid format which unites brief texts with basic images for delivering interactive reader experiences. Kaur employs online platforms to reshape poetic expression through her poetry which deals with subjects such as love healing and feminism along with identity exploration. The Instagram visual format enables poets to develop designs and spacing arrangements that generate more impactful emotional responses. The analysis of Kaur's work pertains to digital humanities because this discipline focuses on understanding technological intersections between literature and art and humanistic knowledge. Social media enables her poetry to achieve worldwide distribution which increases both accessibility and literary inclusivity for all readers. Insta poetry allows users to engage right away with their interaction through various social functions that transform it into a dynamic literary encounter beyond traditional academic spheres. Digital poetry receives opposite reactions between those who view it as a democratic art form reaching diverse audiences and individuals who consider it cheapens the art while transforming it into a commercial product. Digital media has not replaced poetry but transformed it according to Kaur's success story which created new opportunities for poets to engage with their audience. The research demonstrates that technological advancements have turned poetry into a more vibrant form that both readers and viewers can experience easily along with its refined visual presentation. Kaur's Insta poetry creates a major transformation in contemporary literature which generates essential dialogues concerning the digital modifications of poetry.

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 Keywords

Digital Poetry, Rupi Kaur, Instapoetry, Social Media, Visual Identity, Digital Humanities

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Distributed Denial-of-Service (DDoS) attacks remain a persistent and evolving threat in the contemporary digital landscape, capable of inflicting significant financial losses, reputational damage, and operational disruptions. While rudimentary DDoS attacks emerged in the late 1990s, the threat landscape has dramatically transformed. Today's DDoS attacks leverage vast botnets, often comprising compromised Internet of Things (IoT) devices, and employ sophisticated techniques such as amplification and application-layer attacks to overwhelm targets. These attacks can cripple critical infrastructure, disrupt online services, and extort businesses. This survey paper provides a comprehensive overview of DDoS attacks, including their historical evolution, contemporary attack strategies, and the diverse array of tools used by threat actors. It further categorizes and analyzes the expanding arsenal of attack and defense mechanisms. Finally, it identifies critical research gaps and proposes directions for future work, emphasizing the need for proactive, adaptive, and collaborative defense strategies to effectively mitigate the growing threat of DDoS attacks in an increasingly interconnected world.

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Adaptive,proactive

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As teachers, we always look forward to new and innovative pedagogies that enhance the students' interests, motivation, and learning outcomes, and we can carry out effective learning experiences in this digital world. One of the most recent approaches gaining momentum in the educational world is gamification in learning. Embedding gaming elements into the learning process can enable teachers to turn sluggish classrooms into a dynamic canvas for exploration and growth among learners. This paper explores the integration of gamification in education and its impact on learners' motivation, engagement, and academic enhancement. Gamification in education refers to the use of gaming components, their dynamics, and mechanisms in classroom instructions to increase student motivation, involvement, and engagement that help achieve better learning outcomes. The paper underlines the research evidence that unfolds improved academic performances, an increase in student engagement in academic activities, and better information retention by students through the application of gamification in the field of education. It further identifies the issues experienced in the implementation of gamification in teaching practices. The paper also discusses future directions of gamification in education, emphasizing the contribution of new technologies to educational practices.

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Innovative Pedagogies, Gamification, Motivation, Learning Outcomes.

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The swift incorporation of Artificial Intelligence (AI) and self-operating technologies across different industries in India prompts significant inquiries regarding legal responsibility and constitutional rights. As AI systems play a growing role in decision-making in fields such as healthcare, finance, and governance, the issue of assigning accountability for their actions becomes increasingly pressing. This study examines the constitutional issues and legal responsibilities associated with AI in India, particularly highlighting the impact of these technologies on fundamental rights like privacy, equality, and life as defined by the Indian Constitution. The significance of this research stems from the increasing dependence on autonomous technologies and the possible dangers they present to personal liberties, underscoring the necessity for an all-encompassing legal structure. Though there is a global discussion on AI and legal responsibility, the literature surrounding this topic in India is still developing. Earlier research has examined the effects of AI on fundamental rights, privacy, and accountability, yet a thorough investigation of constitutional issues unique to India is still lacking. This study seeks to address that void by analyzing pertinent judicial precedents, legal statutes, and international comparative frameworks. This study adopts a qualitative, doctrinal methodology, examining constitutional texts, case law, and secondary sources. It additionally contains comparative perspectives from global jurisdictions to suggest practical remedies for India's legal system. The main research question focuses on how India's legal framework can guarantee accountability and safeguard fundamental rights in relation to AI. Secondary inquiries delve into the constitutional issues surrounding AI, the legal responsibility of autonomous systems, and the effects on privacy and equality. The goals of the research encompass evaluating current legal frameworks, suggesting reforms, and providing a comparative analysis. The anticipated results encompass legal perspectives on AI responsibility, suggestions for AI regulatory policies, and an addition to the ongoing discussion regarding AI governance in India.

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Artificial Intelligence, Accountability, Constitutional Law, India, Autonomous Technologies

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Meditation is an approach that involves focusing or clearing your mind through a mix of mental and physical methods. Relying on meditation style people select, some might meditate for relaxation, to help anxiety or stress, and other purposes. Meditation has so many advantages like reduces signs of anxiety, depression, capacity of thinking clearly, concentrate etc. Since mental health positively influences physical well-being, these benefits often lead to enhancement in sleep quality, blood pressure, heart functions and other aspects. Tantra and Yantra artwork significantly contribute to meditation by acting as strong visual and spiritual tools that improve concentration, energy alignment, and self-awareness. The word "Tantra" translate to "loom" or "weave" in Sanskrit. The basis of tantric paintings, is mix of unique spiritual, metaphysics and art forms. Yantra paintings are enchanting and ancient art forms that is heavily implanted in Indian spiritual heritage. It combines geometry, spirituality, and artistic creativity, resulting in powerful symbols believed to have mystical properties. The patterns and lines are found in Yantra are not simply ornamented but they signify different phases of reality and consciousness. The detailed designs typically emphasize triangles, circles, and lotus petals, each representing various universal energies. Using these sacred paintings in meditation has great impact in mental health.

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Art, Meditation, Paintings, Tantra, Yantra

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Inscriptions are of great value since they are the mirror of the cultural life of the contemporary society as well as the colloquial language and expressions of the period to which they belong. While some of them are composed in excellent classical style some are written in the language of the common people. The main purpose of the inscriptions is to record an endowment made to an individual or institution with necessary details. But scholars while composing inscriptions availed the opportunity to give expression to their erudition an as a result we have classical inscriptions which stand in comparison to classical literature. The present paper deals with the classical inscriptions of the Kakatiyas of Orugallu or Warangal as gleaned from the inscriptions.

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Classical, Cultural, Inscriptions, Kakatiyas, Mini Kavya, Orugallu or Warangal, Sabhdalankara, Sanskrit, Society, Telugu Country.

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This study assessed knowledge about diabetes and the public perception of the affordability and availability of antidiabetic medicines in Vadodara. A cross-sectional survey was carried out among the residents of different socioeconomic strata using a structured questionnaire. Their findings show that even though most participants are aware of diabetes and its complications, there are still knowledge gaps in prevention and long-term management. Many respondents reported that regular antidiabetic medications were too expensive, particularly among low-income groups. Availability of medicines in public healthcare facilities is erratic. Private pharmacies may be better stocked, but their prices tend to be prohibitive. The study also highlights a paucity of awareness regarding government schemes and subsidies. Literacy and income stood out as major determinants for both awareness and access. Overall, the study establishes the need for amped-up health education and an improved public healthcare infrastructure. Awareness campaigns, more distribution of essential medicines, and assistance for the disadvantaged are recommended.

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 Keywords

Cross-sectional survey, Knowledge gaps, Prevention ,Long-term management, Low-income groups, Public healthcare facilities, Private pharmacies, Government schemes, Subsidies, Literacy, Income ,Awareness ,Health education ,Healthcare infrastructure, Awareness campaigns ,Essential medicines

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The primary objective of SynapAI: AI-Powered Detection precise for Brain Tumors is to develop an advanced system for identifying brain tumors from MRI scans using a hybrid deep learning model integrating Convolutional Neural Networks (CNNs), Vision Transformers (ViT), and Capsule Networks (CapsNet). This system aims to assist medical professionals by providing an automated, accurate, and efficient diagnostic tool, enhancing precision while reducing manual effort. With brain tumors posing a significant health challenge, early detection is critical. SynapAI combines CNNs for local feature extraction, ViT for global context analysis, and CapsNet for preserving spatial hierarchies, achieving over 90% accuracy. Integrated with a Flask-based web interface using HTML and Tailwind CSS, the system processes uploaded MRI scans, applies preprocessing, and delivers real-time tumor classification. Historical MRI datasets ensure robust training and validation, positioning SynapAI as a valuable contribution to medical imaging technology.

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Brain tumor detection, Artificial Intelligence (AI), Deep learning, Medical imaging, Convolutional Neural Networks (CNNs), Vision Transformers (ViT), Capsule Networks (CapsNet), Hybrid models, MRI scans, Tumor classification, Data preprocessing, Model training, Accuracy metrics, Flask, Tailwind CSS, Early detection.

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This paper explores the portrayal and presentation of female madness as both symptom of patriarchal domination and an act of rebellion in Sylvia Plath's The Bell Jar and Charlotte Perkins Gilman's The Yellow Wallpaper. This study through feminist literary theory and psychological understanding analyses how both books present mental illness not as intrinsic pathology but as a reaction to societal restraints placed upon women.

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Female madness, Resistance, Feminist literature, Women's mental health, Narratives of female authors, Psychiatry, Feminism, Sylvia Plath, Charlotte Perkins Gilman, Rest-Cure

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The demand for effective, secure, and readily accessible therapeutic solutions has grown due to the increasing prevalence of neurodegenerative disorders and issues related to memory. This study aims to develop an advanced nervine tablet that incorporates a blend of medicinal herbs known for their neuroprotective, adaptogenic, and cognitive-enhancing properties. The takes advantage of the combined effects of herbs such as Nardostachys jatamansi, Hyoscyamus reticulatus, Mimosa pudica, Zingiber officinale, and Piper nigrum, which have been shown to enhance memory, reduce oxidative stress, and overall improve cognitive function. By merging modern pharmacological techniques like molecular docking and high-performance liquid chromatography with traditional herbal knowledge, this product aims to address existing gaps in the treatment of cognitive impairments and memory loss. Offering a natural alternative to synthetic medications that may have serious side effects, the nervine tablet provides a holistic approach to mental well-being. Furthermore, it shows promise for reducing stress, preventive care, and improving the quality of life for both individuals looking to enhance cognitive abilities and those suffering from neurodegenerative conditions. This research highlights the importance of integrating contemporary scientific methods with traditional healing practices to tackle complex neurological challenges on a global scale.

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Cognitive enhancement, Nervine tablet, Memory improvement, Neuroprotection, Traditional herbal medicine, Cognitive function, Alzheimer's disease, Herbal formulations, Stress management, Pharmacological techniques

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Development of facial sheets masks using niacin (vitamin B3) and melaleuca alternifolia (tea tree oil) for increased skin care. Niacin is known to strengthen the skin obstruction, improve skin tone and reduce signs of aging, while tea tree oil provides antimicrobial and anti -inflammatory benefits, causing it to renovate acne and soothing irritation. And determine the optimal level of niacin and tea tree oil to maximize the benefits without causing skin-safe materials and irritation for masks. Facial sheet mask is designed using non-woven fabrics of bamboo, a biodegradable, environmentally friendly material that is both durable and functional. Bamboo fabric is known for its better exploitative, soft texture, and the ability to follow the skin well, which ensures an optimal distribution system for active ingredients. The laboratory had tested masks stability, pH balance and safety, and its effectiveness was evaluated. The test assessed skin hydration, acne deficiency and improvement in skin glow. Participants reported positive experiences, highlighting noticeable improvements in the skin texture and tone. The product also demonstrated excellent skin compatibility, in which no adverse reaction was recorded. This research shows the ability to combine niacin and tea tree oil in facial sheets masks to give many skin benefits.

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Niacin, Melaleuca Alternifolia,antimicrobial,skin obstruction balance.

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This research investigates class struggles in British working-class women's fiction through an analysis of Pat Barker's Union Street (1982) and Andrea Levy's Small Island (2004). Barker brings out gendered class struggles in industrial England, and Levy analyses racialized class struggles in post-WWII Britain. This research, applying Marxist, feminist, and postcolonial theories, examines how both writers critique patriarchy, capitalism, and colonialism in fiction. The research highlights literature's ability to promote empathy and sensitivity to socio-economic inequalities, pointing to its long-lasting potential to subvert mainstream narratives, give voice to marginalized communities, and provoke critical reflection on class, gender, and race.

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The Representation of Class Struggles in Working- Class British Women's Fiction A Study of Pat Barker's Union Street and Andrea Levy's Small Island

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