Volume 6 | Issue 2 |

 Abstract

The history of foreign domination in India is replete with a courage, sacrifice and dedication to the cause of freedom. But over the decades, the fight for freedom of the country was continued with the same dedication, singleness of purpose and solidarity. The heroes of our freedom struggle came from every corner of the country. They did not speak one language. They did not belong to one religion or one caste. They rose above these narrow loyalties and considerations and had in tense love for their motherland and keenness to see the country free. That was the single thread of unity that bound them all. Free India has been built on untold sacrifices made by numerous individuals. Freedom movement was started not merely to drive the Britishers out of India, but the struggle continued to gain recognition for our nation among the other advanced nations of the world. "Indians should be the Masters of India" was the dictum. The main aim was that the Indian had to be an equal to the world citizen. This may call as freedom movement is related to human life, namely ,traditions, economic activities, rich cultural background and goals, Gandhiji dreamt of Swaraj. In this world Swaraj means, "The wealth of the nation is being washed away, we Indians are very poor. We should come out from poverty. Although India is a rich land, people suffer from epidemic diseases. Until and unless the Britishers are driven away from India, we will not rest in peace.

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 Keywords

freedom movement, domination, solidarity, revolt

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Abstract The rapid advancement of artificial intelligence (AI) and unmanned aerial vehicles, commonly known as drones, has opened new possibilities for precision agriculture. This paper presents a novel approach for the detection of plant diseases using AI-based drone technology. The system leverages high-resolution aerial imagery captured by drones and employs advanced machine learning algorithms to identify and classify various plant diseases in real-time. The use of unmanned aerial vehicles is revolutionizing the agricultural industry. Cashews are grown by approximately 70% of small and marginal farmers, and the cashew industry plays a critical role in their economic development. Several fungal and algal diseases threaten the cashew tree, resulting in substantial losses in yield. Some cashew-growing regions are particularly susceptible to powdery mildew, damping off, anthracnose, and inflorescence blight. To take timely countermeasures against plant diseases and infections, it is imperative to monitor and detect diseases as early as possible and take suitable measures. Using, such as those that are equipped with artificial intelligence, can assist farmers by providing early detection of crop diseases and precision pesticide application. To facilitate efficient and effective crop monitoring, a equipped with a camera will be deployed to take aerial photographs. An edge computing paradigm of Artificial Intelligence is employed to process this image in order to make decisions with the least amount of latency possible. This paper discusses the system architecture, including the drone hardware, imaging sensors, and the AI algorithms used for image processing. It also addresses implementation challenges such as varying environmental conditions and the need for large annotated datasets for training the AI models. Preliminary field trials demonstrate the system's effectiveness in detecting common plant diseases, with promising results that suggest significant potential for improving crop management and yield. Future work will focus on expanding the range of detectable diseases, enhancing the robustness of the AI models, and integrating the system with existing agricultural management platforms.

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Keywords: deep learning, plant disease, CNN, agriculture, classification, EfficientNet.

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Abstract Cyber attacks are prevalent in the age of the Internet. Each year, both the quantity and severity of cybercrimes increase. Protection against cyber-attacks has become a primary responsibility, Significant in the internet society of today. However, providing cyber security is a highly difficult task that requires experience in the field of attacks and the ability to evaluate the possibility of threats. The continual evolution of cyber attacks is the biggest challenge in this industry. In the increasingly digital world, the frequency and sophistication of cyber attacks continue to rise, posing significant threats to individuals, organizations, and nations. Traditional cyber security measures often fall short in identifying and mitigating novel and evolving threats. This paper presents a machine learning-based cyber security technique designed to detect and predict upcoming cyber attacks. The proposed system leverages advanced machine learning algorithms to analyze vast amounts of network data and identify patterns indicative of potential threats. Experimental results demonstrate the system's capability to detect a wide range of cyber attacks, including zero-day exploits, phishing, and distributed denial-of-service (DDoS) attacks. The proposed technique shows promising results in terms of detection accuracy, false positive rate, and response time, highlighting its potential as a robust solution for proactive cyber defense. This research contributes to the field of cyber security by providing a scalable, adaptive, and efficient approach to threat detection. Future work will focus on enhancing the model's scalability, integrating it with existing security infrastructure, and conducting extensive field tests to validate its performance in real-world scenarios. The most effective method of protection from these attackers is to conduct vulnerability analysis against newly emerging threats for the systems we use and to rectify identified vulnerabilities. In this research paper, the weaknesses of wireless communication towards remote connection usage of the mini electric autonomous vehicle were investigated, which we developed and produced its mechanics, electronics, and software.

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Keywords: Cyber security, Machine Learning, Artificial Intelligence (AI), Cyber Attacks, Supervised Learning Unsupervised Learning Reinforcement Learning Deep Learning

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In the present scenario the amount of medical image data being generated is enormous. Statistics say that the storage needs have increased by 25% accounting to petabytes of image data [1]. The major reasons for this increase in the imaging data is the growth in the aged population, awareness among people, increase in the size and resolution of the images and also due to retention policies and backup images [2]. Also the cost involved in per gigabytes data storage is very high. This has caused serious challenge in the storage and transmission of medical images. Though doctors are reluctant to use lossy compression, it is predominantly the solution that decreases the amount of storage. JPEG compression are widely used because of their advantage. In this research an effort has been made to investigate, evaluate and analyse the effects of compression on the size and quality of the image using popular JPEG compression algorithms. Hundreds of images from radiological modalities (CT, MRI and Digital X-Ray) were subjected to JPEG compression at varying qualities [100% to 5%]. Subjective validation was carried out with the help of Physicians by using side-by-side (or "flicker") comparison of original image and compressed image using 5 Point scoring scale. Quantitative assessment was accomplished by comparing MSE, PSNR, CR and BPP

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Medical images, JPEG compression, Scalability

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The healthcare infrastructure of the developed economies has not been able to deliver services to their citizens. The World Health Organization defines universal health coverage (UHC) as means to enable all people and communities to use primitive, preventive, curative, rehabilitative, and palliative health services they need, of sufficient quality to be effective. Ayushman Bharat Pradhan Mantri Jan Arogya Yojana (AB-PMJAY) is India's Government-funded health insurance scheme that covers more than 10.74 crore poor and vulnerable families. Karnataka has been at the forefront of successfully implementing this health care schemes through Suvarna Arogya Suraksha Trust on an Assurance Mode, for the benefit of a large section of BPL and APL families. Hence this systematic analysis on utilization of the Ayushman Bharat-Scheme will be helpful to understand the efficiency of the scheme in Mysore District. This study is carried out with the primary objective to analyze the utilization of Ayushman Bharat-Scheme in Mysore District and examine the various benefits available through the scheme with the help of primary data gathered from 120 users of the scheme selected as respondents through the structured questionnaire by following the convenient sampling technique and the research design being conclusive and quantitative. Finally it was observed that, the components of Ayushman Bharat scheme such as treatment package, coverage amount, diagnostics covered, post-discharge benefits, treatment without e-card, separate card for each family member, emergency treatment, usage of scheme in other state, no requirement of renewal of the card and there is no requirement for pre checkup to utilize the scheme are utilized by the card holders in Mysore district which describes the positive relation in utilization of the scheme.

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 Keywords

Key Words: Ayushman Bharat Schemes, Health Insurance, BPL and APL families, Universal Health Coverage,

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Abstract This study examines how participating in microfinance affects the income and spending habits of low-income households. We analyzed a sample of 100 households and found that microfinance participation is associated with a significant increase in household income and a decrease in spending on non-essential items. We also found that financial literacy plays a crucial role in the effectiveness of microfinance programs. Our results suggest that microfinance can effectively promote financial inclusion and improve the well-being of low-income households. However, policymakers and microfinance institutions need to prioritize financial literacy training and sustainable financial practices to ensure the long-term success of these programs. Additionally, our study underscores the importance of financial literacy in determining the effectiveness of microfinance programs. We observed that households with higher levels of financial literacy are more likely to see an increase in income and a decrease in spending on non-essential items. This highlights the potential of microfinance programs in promoting financial inclusion and improving the well-being of low-income households but emphasizes the need for financial literacy and sustainable financial practices to ensure their long-term impact.

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Micro-finance, Household income, Expenditure patterns, financial literacy, Financial inclusion

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Women entrepreneurship refers to the act of starting, managing, organizing, and running a business enterprise. Historically, women entrepreneurship was not given much importance in society, but over time, many women have emerged and participated in entrepreneurship. Micro, Small and Medium Enterprises (MSMEs) have been instrumental in promoting industrial development, contributing nearly 6% to India's GDP, 33% to manufacturing, and 45% to exports. Increasing women's participation in MSMEs is considered a development goal, aiming to reduce poverty, improve family health, and empower women's economic status. MSMEs provide employment and are labor-intensive, yet they are successful in generating entrepreneurship. This sector requires minimal capital and local resources, allowing women from all backgrounds to pursue their entrepreneurial dreams. This paper aims to study the percentage distribution of MSMEs run by women entrepreneurs and analyzes the motivating and challenging factors for these entrepreneurs.

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women entrepreneurs, MSME, challenges, motivating factors

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The growing reliance on digital data has made data security a top priority for individuals, organizations, and governments. Traditional data security measures are frequently rendered ineffective in the face of sophisticated cyber threats, resulting in data breaches, theft, and unauthorized access. Blockchain technology, best known for its role in cryptocurrencies such as Bitcoin, is poised to revolutionize data security. Blockchain technology, with its decentralized and transparent nature, could provide a solution to this problem. This study proposes a blockchain-based framework for securing IoT data that takes advantage of blockchain technology's immutability and auditability to ensure the integrity and confidentiality of sensitive information. This paper describes the proposed research methodology, findings, and analysis, emphasizing the effectiveness of blockchain technology in revolutionizing data security. The introduction of blockchain technology has heralded a new era of secure data management. As traditional data security mechanisms struggle to keep up with the growing sophistication of cyber threats, blockchain provides a decentralized, transparent, and immutable solution for protecting sensitive data. This research article investigates the potential of blockchain technology to revolutionize data security. We investigate the key features of blockchain that make it an ideal candidate for secure data management, propose a comprehensive research methodology to assess its effectiveness, and examine the findings of our study. Our findings demonstrate blockchain's transformative impact on data security, emphasizing its benefits while addressing potential challenges.

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 Keywords

Blockchain, Data Security, Cloud Computing, Data Storage

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Pollution adversely affect the aquatic life and human beings. Removal of hazardous materials from waste water is very important for aquatic life as well as human life. Many methods including adsorption are used for the removal o toxic metal ions and dyes from waste water. The adsorbent binds with metal ions and dyes and remove them. A novel adsorbent, shellac and its iron loaded derivative was prepared. The iron loaded polyacryamide grafted shellac was used to remove cadmium from waste water. The synthesised iron loaded polyacrylamide grafted shellac was characterised by FTIR and XRD. Shellac and shellac derivative are efficient adsorbent for the removal of toxic metal ions from waste water. The amount adsorbed was found higher than that observed in conventional adsorbents.

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Key Words: Shellac, Polygrafted, Iron loaded shellac.

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Physical Growth, Relationship, Obesity, Private Aided, International, School Going Girls

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