Volume 13 | Issue 4 |

 Abstract

This research paper explores the disparities between rural and urban unemployment, analysing the root causes, patterns, and socioeconomic impacts in each setting. The paper also examines the effectiveness of government policies aimed at reducing unemployment and proposes context-specific strategies to create sustainable employment opportunities. It focuses on a comprehensive comparative analysis of unemployment dynamics in rural and urban India, examining the distinct causes, prevalent trends, and the efficiency of current policy interventions in each context. Recognizing the significant heterogeneity in socio-economic structures and labour market characteristics between rural and urban landscapes, this study posits that a nuanced understanding of these differences is crucial for formulating targeted and effective employment generation strategies. To provide an empirical foundation, the research analyses recent trends in unemployment, drawing primarily on data from the Periodic Labour Force Survey (PLFS). While acknowledging the latest available data for urban India (October-December 2024), the study aims to contextualize these findings within broader historical trends and, where possible, compare them with corresponding rural unemployment data. Key indicators such as unemployment rates, labour force participation rates, and worker population ratios are examined, with a particular focus on gender disparities and regional variations within both rural and urban areas. The analysis seeks to identify emerging patterns and shifts in unemployment dynamics over time.

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 Keywords

Rural, Urban, Employment, Unemployment, Policies

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Health care associated infection are defined as infection at the time of admission to a health care settinghealth associated infection are those infection acquired in hospital first appear in 48 hours or more after hospital admission within 30 days after discharge. There was significant difference in overall mean knowledge score and practice score between the staff nurses of government hospital Hisar and govt hospital fatehbad regarding the prevention of hospital acquired infection, the obtained "t" value 6.707 (P< 0.05, df = 58) was greater than the table value at 0.05 level of significance. There was significant difference between the mean knowledge and practice score of the staff nurses of government hospital hisar and govt hospital fatehbad . The obtained "t" value 4 of the government hospital hisar was greater than the table value at 0.05 level of significance and the obtained "t" value 2.523 of the govt hospital fatehbad was greater than the table value at 0.05 level of significance. There was significant association between the age of the staff nurses and the level of knowledge regarding the prevention of hospital acquired infection (?2 =10.671, P <0.05, df=3, "t" value= 7.82 and ?2 = 6.696, P< 0.05, df= 2, "t" value= 5.99).There was significant association between the area of practice of the staff nurses and practice regarding the prevention of hospital acquired s infection (?2 =16.5, P< 0.05, df= 6 "t" value= 12.59).

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 Keywords

comparative, Assess, Association, knowledge ,practice , staff nurses ,Hospital Acquired Infection.

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Creative Commons Attribution 4.0 and The Open Definition

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Users' crucial data is stored in databases by the web-based applications that collect it. Due to their Internet accessibility, these applications and the databases that are connected to are exposed to a variety of information security risks. The threats include cyber attacks like Cross Site Scripting (CSS), Denial of Service Attack (DoS), and SQL Injection Attacks. When considering web-based applications, the top ten vulnerabilities includes SQL Injection attacks. An organization or corporation may suffer harm as a consequence of this kind of attack since the attacker can obtain or steal sensitive information. In order to classifying and recognize SQL Injection attacks, we are considering utilizing an algorithm from machine learning approaches. Any web system must include a robust SQL injection detection to counteract this risk. In this project, machine learning is applied to provide using training data, which is then analyzed against testing data. The outcomes of the detection demonstrates that the proposed approach generates high accuracy in differentiating between malicious and harmless web requests.

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Keywords: CROSS SITE SCRIPTING(CSS), DENIAL OF SERVICES(DOS), SQL INJECTION....

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Cassia alata L. is an outstanding plant of Chhattisgarh in India. different parts of the plant such as leaves, stem, root and seeds have medicinal properties. The study investigated the effect of light and temperature on scarified seed of Cassia alata on the germination percentage because seeds are the main source of perpetuation in Cassia alata. Seeds have a wide range of adaptation capacity to survive in the adverse environmental conditions in the higher plants. Six months old seeds are incubated at 15?,20?,25?,30?,35?,40? and 45? which is coupled with acid scarification and mechanical scarification. (Seeds did not germinate without scarification.). In this study maximum percentage of germination was obtained between 25? to 30?. Seed germination was observed from 3rd day up to 7th day. Maximum germination percentage in the direct light was 85% at the temperature of 300c and minimum percentage was 23% at the temperature of 40?. At 45? no germination has been occurred. In diffused light condition, maximum germination percentage was 93.75% at 30?, and minimum percentage was 45.75% at the temperature of 40?. In dark, maximum germination percentage was 86.25% at the temperature of 30? to 35?, and minimum germination percentage was 33.75% at 40?. The length of dormancy was studied by continuous observation of collected seeds up to 6 months. Seeds were collected in January 2024, and germination occurred in August 2024. Six months old seeds show 80-95% germination at 25? to 30?.

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 Keywords

Germination percentage, Viability test, Cassia alata

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Ramchatrit Manas ke Ram ki manviya vyavhar ki samsamayikta ki ek vishleshnatmak adhyayan

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Ramchatrit Manas ke Ram ki manviya vyavhar ki samsamayikta ki ek vishleshnatmak adhyayan

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Creative Commons Attribution 4.0 and The Open Definition

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Artificial Intelligence is a mechanism that makes machines think, learn, and solve problems, like humans do. This paper presents the development of a conversational AI Chatbot designed to make learning storieseasier for a learner.By combining rule-based techniques with NLP and transformer-based models, the Chatbot offers interactive dialogue on the knowledge base that it is supported with. The system emphasizes both accuracy and engagement, drawing on simplified data to maintain authenticity. User feedback indicates strong engagement, suggesting that conversational agents can enhance learning experiences. This paper demonstrates how AI can play a meaningful role in creating Chatbots for educational domain, through interactive, accessible technologies

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Chatbot, knowledge graph, Neo4j, Vectorization, RAG, Graph RAG

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Creative Commons Attribution 4.0 and The Open Definition

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The advancement of smart healthcare systems has led to innovative solutions for real-time patient monitoring and disease detection. This project introduces an IoT-based Health Monitoring System designed to track vital health parameters and detect potential diseases using multiple biosensors and machine learning techniques. The system integrates PPG, DHT11, gas sensors, piezoelectric sensors, flex sensors, MAX30100, and an ESP32 camera module to collect physiological data such as heart rate, temperature, oxygen saturation, sweat analysis, bone health conditions and detects wound. The collected data is processed using NodeMCU, MCP3008, and a Buck Converter for efficient sensor interfacing and power management. The system employs machine learning algorithms, including K-Nearest Neighbors (KNN) and Convolutional Neural Networks (CNN), for accurate disease classification and wound detection. TensorFlow's Adam optimizer enhances the model's training efficiency, improving detection accuracy. The processed health data is then transmitted to a web-based interface with cloud connectivity (ThingSpeak) for real-time remote monitoring, enabling healthcare providers and patients to access insights into health conditions. This smart healthcare solution can detect 10 different diseases, ensuring early intervention and preventive care. The integration of IoT, machine learning, and cloud computing in this system makes it an efficient, cost-effective, and scalable solution for remote health monitoring. The proposed system aims to enhance healthcare accessibility, improve early disease detection, and provide real-time health insights, contributing to modern telemedicine and patient-centric care.

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Keywords: IoT-based healthcare, machine learning, disease detection, biosensors, remote health monitoring, KNN, CNN, Adam optimizer, ThingSpeak, real-time diagnostics.

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This report analyzes India's precarious balance between national security and individual rights, specifically preventive detention.This report envision a tightrope walker's delicate balance, where each step negotiates opposing forces. This report examine real-life stories and ethical dilemmas that arise when India preempts potential threats by holding individuals without trial. We unpack arguments for and against this practice, acknowledging the need to protect the country while highlighting the human cost. We explore the legal framework, the real-world impact on individuals and families, and the judiciary's and international human rights standards' vital roles. Ultimately, this report fosters a deeper understanding of this contentious issue, advocating for a humane and just approach that safeguards both the nation and its people.

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Preemptive Liberty, National Safety vs. Personal Freedom, India's Balancing Act, Human Cost of Security

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Creative Commons Attribution 4.0 and The Open Definition

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This project introduces a secure academic document verification system that leverages artificial intelligence and blockchain technology to ensure authenticity and integrity. Authorized administrators upload documents, which are verified using an AI-based method and then hashed using SHA-256. The resulting document hash is stored on the Ethereum blockchain via smart contract interactions, facilitated through MetaMask wallet integration for secure and user-friendly transaction signing. Students can verify documents by entering the hash ID, which is matched against the blockchain without needing access to the original file. This system ensures transparency, tamper resistance, and decentralized trust in academic credentials.

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Creative Commons Attribution 4.0 and The Open Definition

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Keywords-- IPFS, Blockchain, Verification, Smart Contract

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Balod : Saksharta pratiroop

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Balod : Saksharta pratiroop

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