Volume 13 | Issue 3 |

 Abstract

Media is the fourth pillar of democracy. India is one of the biggest democracies in the world and is ranked second in print media. News publications faced many issues and challenges during British rule. The press faced obstacles from colonial rule and illiteracy and had to overcome many rules that suppressed free speech. The press became an important tool to raise awareness about the need to unify against the British and achieve independence. The press was a major advocate of modern ideas such as democracy, freedom, equality, and patriotism. The press has played a vital role in shaping the Indian freedom struggle. From its early days, it has been a powerful tool for communication, spreading ideas, and mobilizing the masses against colonial rule. Through various publications, the press helped create a sense of national identity and unity among Indians, making it an essential part of the fight for independence. This article explores the significant contributions of the press during this transformative period in Indian history. The Indian press began with the Bengal Gazette in 1780, marking the start of print media in India. Prominent leaders like Gandhi and Tilak used newspapers to spread nationalist ideas and connect with the masses. The Vernacular Press Act of 1878 aimed to control the Indian press but ultimately sparked resistance and resilience among journalists. The press served as a platform for discussing social issues and reforms, influencing public opinion and policy. Post-independence, the press became a cornerstone of democracy, promoting accountability and national identity. The press played a notable role in the freedom struggle. They helped in the dispersal of revolutionary ideas, which helped in forming an opposition against the British government. Protected by the First Amendment to the U.S. Constitution, a free press helps maintain the balance of power in government. Numerous journalists worldwide have been killed while working to fulfill their essential role in free and open societies.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Press and Freedom Struggle, Colonial Policies, Key Aspects, Role, Importance, Institutions, National Repression, Various Bodies, Challenges, Strategies, Limitations, Restrictions, Measures, Criticism and Recommendations, Findings And Suggestions.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The project is intended to create a cost-effective and easy-to-use eye disease detection and classification system for children and adults in economically underprivileged regions. The system proposed is either a mobile or a Desktop Application. The system takes as input a photo of an unadorned human eye. The picture of the eyes can be taken through a basic mobile camera or laptop camera without too much worry about light or lighting. The system can identify eye diseases such as cataracts, glaucoma, and other diseases where intervention by doctors for disease prediction is needed. The proposed method utilizes an algorithm that makes use of the VGG-19 Convolutional Neural Network (CNN) model with normalization techniques to categorize fundus images into five distinct classes: Cataract, Diabetic, Glaucoma, Normal, and Other. The primary objective is to provide an accessible technology for early detection and intervention of eye disorders in underserved communities. By employing a robust deep-learning model, we intend to enhance visual health outcomes and overall well-being among children and adults in these regions. The user-friendly interface and affordability of the system play pivotal roles in facilitating its seamless deployment and effective use, addressing the healthcare access disparity prevalent in these communities.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Eye Disease Classification, Children's Eye Health, Fundus Image Analysis, Machine Learning in Ophthalmology, VGG-19 Model, Healthcare Access in Underserved Communities, Affordable Healthcare Technology, Early Detection and Intervention, User-friendly Healthcare Solutions

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study examines the effects of the diversity training program at the Central GST & Customs Office in Vadodara and evaluates how it affects employee performance and workplace inclusivity. This study examines the effects of diversity training programs on inclusion in the workplace and employee performance. In an increasingly diverse workplace, creating an inclusive culture is essential to organizational success. A mixed-methods strategy was applied in the research. The findings demonstrate that effective diversity training significantly raises employees' perceptions of inclusion, which enhances collaboration and job satisfaction. The study also demonstrates a positive correlation between increased workplace diversity and overall employee performance metrics. This study investigates the effects of diversity training programs on workplace inclusion and employee performance. As companies recognize the importance of diversity, effective training programs are now crucial to establishing an inclusive workplace. This study used a mixed-methods approach that blends quantitative surveys and qualitative interviews to assess the effectiveness of diversity training across several industries. The findings demonstrate that systematic diversity training significantly raises employees' awareness of inclusivity, promotes positive workplace relationships, and enhances overall performance metrics. The study also demonstrates that training principles must be continuously supported and reinforced in order to maintain inclusive practices. These findings have significant implications for businesses hoping to cultivate a diverse and effective workforce, which will eventually result in a more equitable workplace culture.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Diversity training program , employee performance , workplace inclusion, job satisfaction, diverse workplace

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

ABSTRACT This study examines the crucial roles of internal and external auditors in maintaining financial integrity within private companies in coimbatore. With rising demands for transparency and accountability, auditors serve as key safeguards against financial mismanagement. Internal auditors focus on assessing internal controls, risk management, and compliance, while external auditors provide independent verification of financial statements. The research highlights the collaborative efforts between both audit functions and explores challenges faced in fraud detection and regulatory compliance. Using a descriptive research design, data was collected through surveys and analyzed using percentage analysis, Chi-square tests, and ANOVA. Findings indicate that experience and age do not significantly influence audit practices. The study suggests strengthening auditor collaboration, investing in technology, and enhancing training programs to improve financial oversight. By adopting proactive risk-based auditing and ethical practices, public organizations can ensure greater financial accountability and transparency. Keywords: Internal Auditors, External Auditors, Financial Integrity, Public Organizations,

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Internal auditors, external auditors

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Abstract -- Liver cirrhosis is a severe and chronic liver condition that often goes undiagnosed until advanced stages, leading to significant morbidity and mortality. Early detection is critical for effective treatment and improved patient outcomes. This project focuses on the development of a predictive model for liver cirrhosis using the Random Forest algorithm, a robust machine learning technique known for its high accuracy and interpretability. The system utilizes a dataset of patient information, including demographic details, liver function test results, and other relevant clinical factors. After preprocessing the data by handling missing values and encoding categorical variables, the Random Forest classifier is trained to predict whether a patient is at risk of liver cirrhosis. The model demonstrates its reliability in identifying potential cirrhosis cases. A Flask-based web application is integrated with the predictive model to provide an accessible interface for medical professionals and researchers

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Keywords: Liver Cirrhosis, Random Forest Classifier, Predictive Model, Flask Web Application

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Aim: This review article aims to evaluate the treatment outcomes and patient satisfaction after orthodontic treatment. Understanding these outcomes will help orthodontists better plan treatments for future patients. Materials and Methods A systematic literature search was conducted using electronic databases, including PubMed, Google Scholar, and relevant orthodontic journals. Studies focusing on patient perceptions of extraction versus non-extraction cases following orthodontic treatment were included in this review. Conclusion: According to the American Board of Orthodontics (ABO) and their Objective Grading System (OGS), also known as the ABO Grading System, the final occlusion of patients treated with extractions appeared more acceptable than those treated without extractions.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

extraction , ABO, OGS , Non extraction

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This work presents the automatic elucidation and categorization of red lesions in retinal images as a supporting mechanism to diagnose diabetic retinopathy (DR). Early identification of diabetic retinopathy is critical for preventing loss of vision, as it is among the most common causes of visual impairment in patients with diabetes. The critical indicators for DR grading and diagnosis are the red lesions, such as microaneurysms, hemorrhages, and exudates. The Proposed system uses CNN to detect and classify stages of the DR, from No_DR to DR using advanced deep learning on retinal fundus images especially in DR Detection. The methods include preprocessing to filter and improve input images, feature extraction using denoised retinal images with deep learning-based CNNs, followed by utilization of TensorFlow/Keras frameworks for training the model. Retinal images are trained by a standardized dataset to test and strengthen robustness. Thus, this work provides a viable solution to the design of automatic detection and categorization of diabetic retinopathy, which has a significant impact on the early diagnosis and blindness of diabetic patients.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Deep Learning, CNN, TensorFlow

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Peer-to-peer (P2P) networks have become a popular architecture for large-scale distributed systems due to their scalability, fault tolerance, and decentralized nature. However, efficiently processing queries in such networks is challenging due to dynamic node availability, network latency, and resource constraints. Exact query processing can be computationally expensive, making approximate query processing (AQP) an attractive alternative for achieving faster and resource-efficient query execution. This paper presents an efficient AQP framework for P2P networks that leverages probabilistic data structures, sampling techniques, and distributed indexing mechanisms to provide high-accuracy query results with reduced communication overhead. The proposed approach dynamically adapts to network changes, ensuring robustness in highly dynamic environments. Through simulations and real-world experiments, we demonstrate that our method significantly improves query response times while maintaining acceptable accuracy levels compared to traditional exact query processing methods. Our findings highlight the effectiveness of AQP in P2P networks, making it a promising solution for large-scale data retrieval and analysis applications. Peer-to-peer (P2P) databases are increasingly used for distributing and sharing documents, applications, and other digital media over the Internet. Answering large-scale ad hoc analysis queries, such as aggregation queries, poses unique challenges due to the distributed and dynamic nature of P2P databases. Exact solutions can be time-consuming and difficult to implement. This paper presents novel sampling-based techniques for approximate answering of ad hoc aggregation queries in P2P databases. The proposed approach includes an adaptive two-phase sampling method based on random walks of the P2P graph and block-level sampling techniques. Extensive experimental evaluations demonstrate the feasibility of the proposed solution

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Peer-to-Peer Networks, Approximate Query Processing, Distributed Query Execution, Sampling, Sketching, Query Optimization, Scalability, Bandwidth Efficiency

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

A crucial government program, the Chief Minister Girl Child Protection Scheme works to improve the welfare, education, and financial stability of girls, especially those from low-income households. This study assesses the program's efficacy critically in the Coimbatore district, concentrating on how it affects financial empowerment, socioeconomic advancement, and educational attainment. Structured questionnaires were used to survey a sample of 99 respondents in order to evaluate beneficiaries' awareness, accessibility, and satisfaction with the program. In order to comprehend more general implementation patterns, other data sources were also examined. While the program has improved female literacy rates, financial independence, and gender equality, the report points out that there are still major obstacles to overcome, such as a lack of knowledge, red tape, and delays in money disbursement.The results highlight the necessity of more effective awareness efforts, streamlined application processes, and better monitoring systems to guarantee the program successfully reaches its target audience. The report ends with legislative recommendations meant to increase the scheme's effectiveness and help Tamil Nadu's girls become more empowered overall.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Girl Child Protection Scheme, Female Education, Socio-Economic Impact, Government Welfare Programs, Coimbatore, Policy Evaluation

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

With the rapid growth of cloud computing, efficient resource allocation is a major challenge. This project introduces an optimized cloud resource management system using container technology to enhance scalability and cost-effectiveness.The model focuses on Cloud Service Providers (CSPs), tenants, and end-users, ensuring optimal resource allocation. It features a Profit/Loss Calculator to predict financial impacts, improving cost-efficiency for tenants and profitability for CSPs. A trust mechanism evaluates data transfer security, reliability, and performance to maintain data integrity.The system includes a Probabilistic Demand Allocation (PDA) model that predicts tenant demands based on historical data, optimizing server resources while maintaining Service Level Agreement (SLA) compliance. Built with Java and MySQL, the project uses Java Swing for the frontend and advanced backend data processing techniques.By integrating optimization, trust mechanisms, and predictive analytics, this solution improves cloud resource allocation, security, and efficiency, making cloud services more scalable and reliable.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Cloud Computing, Resource Allocation, Container Technology, Predictive Analytics, Trust Mechanism

  License

Creative Commons Attribution 4.0 and The Open Definition