Volume 13 | Issue 4 |

 Abstract

Heart disease remains one of the leading causes of mortality worldwide, making early and accurate diagnosis critically important. In this project, we explore the use of machine learning techniques to predict the likelihood of heart disease in patients based on key clinical and demographic features. The system utilizes supervised learning algorithms trained on the Cleveland Heart Disease dataset, which includes variables such as age, gender, chest pain type, resting blood pressure, cholesterol levels, maximum heart rate, and more. Data preprocessing techniques such as normalization, encoding of categorical features, and handling of missing values were applied to ensure the quality and usability of the data. Various machine learning models including Logistic Regression, Random Forest, Support Vector Machines, and XGBoost were implemented and evaluated based on accuracy, precision, recall, F1-score, and ROC-AUC metrics. The experimental results demonstrate that ensemble models like Random Forest and XGBoost offer high predictive accuracy and robustness, making them suitable for medical diagnostic support systems. This work emphasizes the potential of machine learning to assist healthcare professionals in making informed decisions and improving patient outcomes through early diagnosis and intervention.

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A broad category of heart-related conditions, including blocked arteries, irregular heart rhythms, and heart failure, affecting the heart's ability to function properly. o

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The female reproductive tract is a complex and dynamic system responsible for sexual reproduction, menstruation, and childbirth. It comprises the vulva, vagina, cervix, uterus, fallopian tubes, and ovaries, which work in harmony to facilitate gamete transport, fertilization, embryogenesis, and parturition. Hormonal fluctuations regulate the tract's function, with the menstrual cycle preparing the uterus for potential pregnancy. Understanding the female reproductive tract's anatomy, physiology, and pathology is crucial for addressing reproductive health issues, such as infertility, endometriosis, and cervical cancer, and promoting women's overall well-being. Congenital anomalies of the female reproductive tract are developmental defects of mullerian derivates associated with various malformations of the female reproductive system. Congenital anomalies of the female genital tract encompass various structural irregularities that arise during embryonic development. These anomalies may involve the uterus, cervix, fallopian tubes, and vagina, manifesting as deviating from the typical anatomical configuration. These structural irregularities may also contribute to a spectrum of gynecological issues, affecting menstrual health, urinary and bowel function, and overall quality of life for affected individuals. Understanding female genital tract anomalies is paramount in reproductive medicine, gynecology, and obstetrics. These anomalies can profoundly impact reproductive outcomes, influencing fertility, pregnancy, and childbirth.

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 Keywords

Embryogenesis, Congenital anomalies, Female genital tract, Fertility.

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Health education i? a vital component of promoting health and well-being in both rural and urban communitie?. De?pite differing challenge? and opportunitie?, health education can empower individual? with knowledge, ?kill?, and attitude? to make informed deci?ion? about their health. In rural area?, health education can addre?? unique challenge? like limited re?ource? and healthcare acce??, while in urban area?, it can tackle i??ue? like health di?paritie? and life?tyle-related di?ea?e?. By integrating comprehen?ive health education into ?chool? and communitie?, we can improve health outcome?, enhance quality of life, and reduce healthcare co?t?. Thi? ab?tract highlight? the importance of health education in bridging the gap between rural and urban health di?paritie? and promoting overall well-being.

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 Keywords

Education, Skill, Health education, Communitie?, Urban ?chool, Rural ?chool

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Creative Commons Attribution 4.0 and The Open Definition

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YouTube is a video-sharing platform that was created in 2005 by three former PayPal employees: Chad Hurley, Steve Chen, and Jawed Karim. It is one of the most popular websites in the world, with over 2 billion monthly active users. On YouTube, users can upload, share, and view videos. The platform features a wide variety of content, including music videos, movie trailers, short films, educational videos, vlogs, and more. Users can also interact with each other by liking, commenting on, and sharing videos. YouTube has become an important tool for content creators and businesses to reach a global audience. Many creators have built successful careers on the platform, with some becoming household names. Additionally, businesses use YouTube to advertise their products and services, often through collaborations with popular YouTubers or by creating their own branded contentYouTube is changing the outlook of the integral world. This video sharing site receives billions of viewers daily, the latest reports show that more than half the viewers are students. "Teens constitute the dominant demographic on YouTube in terms of their viewership, comments, and rating and other feedback mechanisms". The exploration of YouTube videos in recent days are elaborated in review of literature.As such, the platform offers a wide variety of user-generated and corporate media videos. Available content includes video clips, TV show clips, music videos, short and documentary films, audio recordings, movie trailers, live streams, and other content such as video blogging, short original videos, and educational videos.

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A STUDY ON USER BEHAVIOR AND IMPACT OF YOUTUBE VIDEOS WITH REFERENCE TO COIMBATORE CITY

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition

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This project presents a novel hybrid framework integrating Multi- Constrained Joint Non-Negative Matrix Factorization (MC-JNMF) with Convolutional Neural Networks (CNNs) to study lung metastasis in soft tissue sarcomas using imaging and genomic data. By jointly analyzing high-dimensional data from medical images (such as CT or MRI scans) and corresponding genomic information, the proposed method seeks to identify critical latent features that contribute to the detection and understanding of lung metastasis. The MCJNMF frameworks integrate multiple constraints to better reflect the biological relationships between the two modalities, while CNNs automatically extract imaging features to improve prediction accuracy. This hybrid approach aims to improve clinical decisionmaking by providing more interpretable models and more accurate predictions regarding lung metastasis development in sarcoma patients. Preliminary results indicate that the integration of imaging and genomic data enhances the model's performance compared to traditional methods.

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CNN,MCJNMf,STS,U-Net,MRI,CT,Cancer

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The process of filing tax return of an assessee through digital or electronic mode is called e-filling. This method aims to substitute and overcome the traditional tax return procedure which create hindrances like stand in long queue, lots of manual paper works, time consuming process etc. The advancement in the technology with high-speed internet connectivity, minimizes the tax compliances in very short period of time with more degree of accuracy compared to previous years. Emerging software advancement in the present era has required huge awareness of its use. The present study concentrates the Facilities, awareness and satisfaction level of the taxpayers regarding e-filling of income tax return. A field survey was conducted at Keonjhar district of Odisha comprising various category of tax payer including men and women. For the above purpose data was collected through structured questionnaire and 280 no. of respondent's response had been received and data are analyzed with the help of various statistical tools like Crosstab technique, Chi-square test etc. The software technology like SPSS and MS Excel also used. The study made a conclusive finding that Gender wise similar response have been received regarding satisfaction on filing IT returns online and variations have been observed on the satisfaction of accessibility & easiness of return filing. Exiting e-filling user satisfied with the modern procedures and new users having lack of awareness regarding this facility.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

E-filing, Satisfaction level. Assessee, Return filing

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Standing how costs change in response to changes in activity levels. It's a crucial aspect of cost analysis, helping businesses make informed decisions about pricing, production, and overall profitability. Cost analysis, in turn, is the study of how costs are incurred and how they relate to different aspects of a business, such as production, sales, and various operational activities.

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Costing, Cost Behaviour, Cost Analysis, Costing factors

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The Directive Principles of State Policy (DPSP) enshrined in Part IV of the Indian Constitution serve as a guiding framework for the governance of the country. Although non-justiciable, these principles provide a roadmap for the state to pursue social, economic, and political justice, thereby striving to balance social welfare and economic growth. This paper explores the role of DPSP in India's constitutional framework, examining their significance in shaping policies that aim to promote the well-being of all citizens, especially the marginalized sections of society. It delves into how these principles influence the formulation of laws and policies concerning education, healthcare, labor rights, and environmental protection. The paper critically analyzes the intersection of DPSP with the Fundamental Rights, exploring the ongoing judicial balancing act between promoting individual freedoms and ensuring social and economic justice. In addition, the paper assesses the practical challenges in implementing these directives within the context of a rapidly growing economy. One of the central themes is the tension between fostering economic growth through liberalization and global integration, while simultaneously ensuring that the benefits of growth are equitably distributed through welfare-oriented policies. The role of the judiciary in interpreting the DPSP and guiding the legislature in balancing these competing demands is also highlighted. By examining landmark cases such as Minerva Mills Ltd. v. Union of India (1980) and State of Madras v. Champakam Dorairajan (1951), the paper demonstrates how judicial review has shaped the dynamic relationship between welfare and growth. The paper concludes with a reflection on the need for a nuanced approach that integrates both economic advancement and social justice within India's constitutional framework.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Directive Principles of State Policy, Social Welfare, Economic Growth, Judicial Review, Constitutional Framework

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 Abstract

Introduction: Post-stroke depression (PSD) is one of the most common complications of stroke with a prevalence of 55%. It limits the recovery of a patient's motor and cognitive functions and also affects the rehabilitation and quality of life. The present study aims to compare the effect of Transcranial Direct Current Stimulation and Virtual Reality on Post-Stroke Depression. Methods and materials: In this study 20 participants were included and were randomized into two groups. Stroke patients with post-stroke depression between the age group of 21-75 years old of both genders were included. They were allocated to two groups ie. Virtual Reality coupled with conventional physiotherapy (Group A) and Transcranial Direct Current Stimulation coupled with conventional physiotherapy (Group B) by envelope method. The primary outcome measure was the Hamilton Depression Rating Scale (HDRS) and the secondary outcome measures were the Montreal Cognitive Assessment Scale (MOCA) and Functional Independence Measure (FIM). Results: Statistical analysis showed significant improvement across all measures in both groups. However, participants in the VR group demonstrated greater reductions in depression scores, enhanced cognitive performance, and improved functional independence compared to those receiving tDCS. Conclusion: The present study concluded that Virtual Reality improved post-stroke depression, cognitive function, and activities of daily living (ADLs) in patients with post-stroke depression

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 Keywords

Keywords: Post-stroke depression, Transcranial Direct Current Stimulation, Virtual Reality, Subacute and Chronic Stroke.

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Creative Commons Attribution 4.0 and The Open Definition