Volume 12 | Issue 3 |

 Abstract

: A chronic eye condition called glaucoma has a deleterious effect on the optical nerve, which links the brain and eye to transmit visual information. Early detection is essential for stopping the condition's progression. Glaucoma is one of the most prevalent eye conditions, and it's important to catch it early because it can cause blindness and neurological issues. In this study, a Deep Learning system is proposed for the early detection of glaucoma. The eye image undergoes pre-processing to eliminate any noise and prepare them for further analysis. The system utilizes enlarged images of the eyes as input data for the deep learning method. The suggested system classifies new eye images as No_glaucoma Glaucoma_early, Glaucoma_moderate, and Glaucoma_advanced and also provides respective preventive measures based on the features it learned during training.

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 Keywords

Glaucoma, Deep Learning, pre-processed, Fundus Images.

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Creative Commons Attribution 4.0 and The Open Definition

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This article aims to forecast future outcomes using machine learning as a crucial tool for supporting decisions in crop yield prediction, such as choosing crops and managing them throughout their growth. Agricultural planning is crucial for the economic growth and food security of countries relying on agriculture. Despite its significance, the agricultural sector faces numerous challenges. Farmers invest considerable time, money, and effort into farming activities, with crop selection being a particularly daunting task. Choosing the wrong crop can lead to financial hardships for farmers. Given the imperative to sustainably feed the global population, advancements in agricultural production are essential. While past research has explored methods like statistical analysis and data mining for crop and soil classification, predicting the most suitable crop for a given soil remains challenging. Machine learning techniques have emerged as a promising solution to this issue. The proposed work aims to predict the optimal crop and recommend suitable fertilizers by analyzing soil composition and properties using machine learning algorithms. This approach seeks to address existing challenges and improve prediction accuracy, ultimately assisting farmers in selecting the right crops to maximize yields and earnings.

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 Keywords

Crop Yield Prediction,Machine Learning,Expert Knowledge Integration,Agricultural DataAnalytics,Remote Sensing,Climate Change Adaptation,Precision Agriculture

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 Abstract

China witnessed momentous changes in the countryside after the Third Plenum in December 1978 as major changes in public policy and institutions unfolded. With the onset of reforms, the rural economy posted impressive growth in agriculture and rural industrialization. Did the growth translate into better incomes and consumption, and how was rural income distributed are pertinent questions to ask given the fact that although there was hardly any significant intra-village rural inequality, the peasants were unhappy over their nearly stagnant income and consumption level despite agricultural sector and the rural economy generating enough resources for China's heavy industrialization led economic development. This question is also important because the Deng Xiaoping regime had recognized the peasantry's unhappiness and discontent as a reason for adversely affecting their work -incentive and declining productivity in agriculture and also as an important factor in straining the Party-state-peasant relationship. This paper, from a political economy perspective, drawing upon literature on rural reforms in China, deals with the impact of changes in policy and institutions on the income and consumption levels of the Chinese peasantry during the first decade of post-Mao rural reforms, i.e., 1978-1988. Additionally, this paper looks at the impact of the growth process on poverty and rural income distribution. It finds that while output, employment, and real income grew rapidly, which enabled peasants to enjoy improved diets, have more housing space to themselves, and use new items/articles of consumption, and many came out of absolute poverty, all this was accompanied with rapidly rising rural incomes within villages across rich and poor regions, which became a matter of concern as it portended societal and political disquiet. This period is a prelude to the rise of China as a great power.

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 Keywords

China's rural reforms, peasants, income, consumption, poverty, rural income inequality

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The LGBT communities all around the world have been in a constant battle against the discrimination they face on a daily basis. They are segregated from the mainstream of the society and failed to find their identity with any other sex categories. However, in the recent years they are trying to organize themselves to fight out their concern. Yet they are continues to be ostracized. People in the LGBT community are fighting for equal rights and acceptance. Trans people especially, face a lot of difficulty in finding acceptance. The constitution provides for the fundamental right to equality, and tolerates no discrimination on the grounds of sex, caste, creed or religion. Article 23 prohibits trafficking in human beings as beggars and other similar forms of forced labour. The problem of transgender is more critical compared to other sex. The Supreme Court in the case of "National Legal Services Authority Vs Union of India" declared transgender people to be the third gender. The case affirms that fundamental rights guaranteed in the constitution will be equally applicable to transgender people and entitled to maintain their self-identity as a separate gender. The constitution affirms equality in all spheres of life but the moot question is whether it is being applied to the LGBTs. In this article it is an attempt is made to analyses the rights of LGBTs in India.

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 Keywords

LGBT, Transgender, Constitutional Protection, Gender Justice.

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Creative Commons Attribution 4.0 and The Open Definition

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postpartum blue, antenatal mothers, effectiveness, structured teaching programme, knowledge.

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The pharmaceutical industry plays a vital role in safeguarding global health. However, its supply chain is complex, susceptible to fraud, and often inefficient. Pharmaceutical supply chains are characterized by multiple stakeholders, including manufacturers, distributors, suppliers, and healthcare providers. The intricate nature of this supply chain makes it vulnerable to issues like counterfeit drugs and data inaccuracies. Blockchain, with its inherent features of transparency, immutability, and decentralization, offers a compelling framework to mitigate these challenges. Blockchain enhances transparency by creating an immutable ledger of all transactions. Each drug batch is assigned a unique identifier, recorded on the blockchain and associated with relevant data such as manufacturing details, shipping records and quality test results. Stakeholders across the supply chain can access this information in real-time, ensuring complete visibility and traceability. Counterfeit drugs cause serious problem to public health. Blockchain's secure, tamper-proof records enable consumers and healthcare professionals to verify the authenticity of pharmaceutical products. Smart contracts, self-executing agreements triggered by predefined conditions can automate verification processes, reducing the risk of counterfeit drugs entering the supply chain. Blockchain's cryptographic techniques ensure data security, privacy and protecting sensitive information. Pharmaceutical recalls can be costly and time-consuming. Blockchain's traceability allows for targeted recalls, pinpointing affected batches quickly. Smart contracts can automate the recall process, notifying relevant parties and facilitating the return of products. This efficiency not only saves resources but also enhances patient safety.

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Blockchain, Counterfeit drugs, Pharmaceutical supply chain, Smart contract

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Creative Commons Attribution 4.0 and The Open Definition

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This study explores the intricate and multifaceted world of social media's effects on young people. The study investigates the complex effects of social media usage on several facets of youth development through a thorough analysis of case studies and secondary sources. The results show a conflict between the advantages of self-expression, community building, and connectedness and the disadvantages of diversions, cyberbullying, and mental health issues. The study sheds light on the difficulties young people encounter when navigating this digital environment. As we examine the educational ramifications, we talk about the necessity of digital literacy initiatives, parental supervision, and legislative changes to lessen the harm and encourage young people to use social media responsibly. The goal of this study is to provide a comprehensive knowledge of the dynamic interactions between kids and social media, guiding researchers, educators, parents, and policymakers on how to effectively navigate this rapidly changing landscape.

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 Keywords

Youth development; Social Media effects; Mental health; Digital environment; Parental supervision; Responsible use; Policy Guidance

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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This paper presents a groundbreaking fitness application that leverages state-of-the-art technologies to redefine the wellness journey. The project seamlessly integrates a Smart Camera, powered by TensorFlow and Flask, allowing users to effortlessly identify and access information about gym equipment. The inclusion of a Pedometer, driven by accelerometer sensors, provides a practical dimension by tracking daily physical activity. A sophisticated Diet Recommendation system formulates personalized diets based on individual profiles, calculating daily caloric needs and organizing them into breakfast, lunch, and dinner. The Exercise section, categorized by body parts, enables users to select and perform exercises with detailed instructions. The integration of Google's Palm API establishes a direct channel for users to engage with fitness-related information. Themes, authentication, and authorization mechanisms using Firebase contribute to a secure and user-friendly environment. This project represents a comprehensive fusion of technology and holistic wellness, poised to reshape the landscape of fitness applications.

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 Keywords

fitness,Fitness Optimization, Smart Vision, AI Enhanced Fitness, FitHub Application, TensorFlow Integration, Flask Framework, Pedometer Tracking, Diet Recommendation System, Exercise Instruction, Google Palm API, Firebase Authentication, Machine Learning Algorithms, React Native Development, Gym Machine Detection, Chatbot Interaction, Holistic Wellness, Personalized Fitness Experience, Smart Camera Technology, User Engagement, Health Technology Integration, react, health, diet, chatbot, gym, and

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The virtual trial room system operates by receiving real-time video feeds from camera and processing the data using the OpenCV computer vision library and Haar Cascade classifier. To ensure accurate face identification in the video feed, the Haar Cascade classifier undergoes training on a substantial dataset of human faces. OpenCV's algorithms extract attributes from detected faces and monitor their movements in real-time. Distinguishing itself from typical security systems that require physical security officers, the virtual trial room system functions autonomously, thus reducing the need for additional staff and associated costs. This autonomy makes it well-suited for various environments, including office buildings, public spaces, and retail establishments where real-time tracking and monitoring are essential for safety and security. Notably, the system's affordability stands out as one of its key advantages. Moreover, the system excels in real-time tracking and monitoring, crucial for maintaining building safety and security. Its capability to reliably detect and track human faces even in challenging lighting conditions is owed to the utilization of advanced computer vision techniques like the Haar Cascade classifier and OpenCV. Additionally, the system is highly expandable, allowing for the integration of additional cameras and sensors as required. Data gathered by the system is securely stored and managed using Dlib, ensuring efficient data storage and retrieval for analysis purposes. Additionally, the virtual trial room system can be programmed to send notifications if it detects any unexpected movements or behaviors, enabling proactive measures to be taken and enhancing overall security protocols.

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 Keywords

Virtual trial room, Haar Cascade classifier, Dlib, OpenCV, Real-time tracking.

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Creative Commons Attribution 4.0 and The Open Definition