Volume 13 | Issue 1 |

 Abstract

This study investigates the development of advanced feature engineering tools and techniques to uncover potential associations between polycystic ovary syndrome (PCOS) and gynecological cancers, such as ovarian cancer. By leveraging variables derived from ultrasound imaging and metabolic data, this research establishes a systematic approach to feature extraction, transformation, and selection for predictive modelling. Key ultrasound variables, such as follicle count and ovarian volume, are integrated with metabolic indicators, including glucose levels and hormonal profiles, to construct a comprehensive dataset. These features are then processed using methodologies like recursive feature elimination, correlation analysis, and principal component analysis (PCA) to identify the most significant predictors. Machine learning models, including logistic regression and random forests, are trained on the engineered features to evaluate the predictive accuracy and robustness of the approach. The results highlight the pivotal role of combining multimodal datasets in achieving high predictive performance, with random forests achieving an F1-score of 0.87. Furthermore, this research emphasizes the importance of feature engineering in medical diagnostics, offering insights into the complex interrelations between PCOS and ovarian cancer. The findings advocate for continued advancements in data integration and model development to support personalized healthcare interventions.

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 Keywords

PCOD/PCOS, Gynecological cancer, Machine Learning, Deep Learning

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Abstract--The rapid advancement of technology, particularly machine learning (ML) and the Internet of Things (IoT), is revolutionizing agriculture by optimizing crop production and ensuring sustainability. This paper presents a web-based platform developed to assist farmers in selecting suitable crops, predicting fertilizer requirements, and diagnosing plant diseases. The platform uses data from Kaggle, ML models implemented in Flask, and ReactJS for the frontend. Farmers can input NPK values and city names to receive insights on temperature, humidity, and fertilizer requirements, while also benefiting from disease prediction through image uploads and SMS alerts. The system aims to improve farming practices, promote sustainability, and enhance productivity [3], [4].

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 Keywords

Keywords--Machine Learning, Precision Agriculture, ReactJS, Flask, Crop Prediction, Disease Detection, SMS Alerts, Fertilizer Recommendation

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'Causality' and 'freedom' are central to discussions in Philosophy of action. Causality and freedom have been addressed from ontological as well as ethical perspectives. Ontologically, causality refers to the dynamics of changes signifying the way there is continual success of cause and effect. Needless to say that cause and effect are relative terms .That which is a cause in relation to the effect can be seen as the effect in relation to its antecedent which is the cause. The relationship between cause and effect is one of necessity such that given the cause effect can be predicted in advance and given the effect the cause can be inferred retrospectively. Causal necessity lives no room for human freedom, Therefore moral judgments cannot be passed on the causal process in the state of nature. 'Freedom' on the other hand is a moral concept. Freedom of will makes sense only in human domain, because human beings are endowed with autonomy of will. Given the circumstances, different individual are free to act differently. Causality and freedom do not go hand in hand. State of nature is understood and explained in terms of causal laws whereas it is the freedom of will which defines the distinctiveness of human action. The distinction between action and event is fundamental. Event is causally determined whereas action is determined by free will. In other words an event is caused whereas action is willed. Morality makes sense only in the domain of human actions, because human agents hare autonomy of will. The 'will' can be used and abused as well on account of which the moral judgments are rendered meaningful. The dissertation is an exercise to a undertake analysis of the notion of 'causality' and 'freedom' in Buddhist Philosophy.

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 Keywords

Causality, Freedom, Determinism, Samsara, Nirvana, Law of karma, suffering.

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Ayurvedic medicine is an ancient system that originated in India thousands of years ago and has been used for prevention and treatment of heart disease with the support of cardiovascular health. Heart-related illnesses are mainly caused by imbalances in the three doshas, and treating CVDs can be difficult when trying to restore their balance. Historically, herbal treatments have been used to cure a wide range of illnesses in many traditional medical systems, demonstrating their importance in human healthcare. Various Ayurvedic herbs like Ashwagandha, Arjuna, and Guggulu are scrutinized for their roles in circulating blood, lowering cholesterol, and controlling blood pressure. But a review of clinical studies and case reports indicates that if used in conjunction with conventional therapies, Ayurvedic treatments may promote heart health. More research and clinical trials are necessary to comprehend their efficacy in contemporary cardiology. The paper notes that integrating ayurvedic medicine with conventional treatments may provide comprehensive management of heart disease.

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 Keywords

Ayurveda, Heart Disease, Cardiovascular Health, Herbal Medicine, Arjuna, Ashwagandha, Guggulu.

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Various essential elements are crucial for the survival and well-being of human beings. other beings for their survival, agriculture plays a crucial role in the development of the economy of India. The major impediment to food security is population growth resulting in increasing demand for food. To increase the supply, farmers need to grow more on the same land. Tech can help farmers produce more through crop yield prediction. 1. The primary goal of this. paper is to predict 3. Applying crop yield. rainfall, crop, meteorological conditions, area, production, and yield variables, which have threatened the long-term sustainability of agriculture (Mahmood et al., 2017). Crop yield forecasting: a decision-making tool that employs machine learning and deep learning techniques to assist in making informed choices regarding agricultural production

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 Keywords

Deep Learning, Machine Learning.

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In light of the growing importance of environmental sustainability, the transition to renewable energy sources like solar energy has become crucial. Solar products, which harness solar energy for various applications, hold significant potential in addressing energy needs while minimizing environmental impact. However, the widespread adoption of these products is heavily influenced by consumer awareness and understanding of their benefits and functionality. This study examines how demographic variables such as age, monthly family income, and educational qualification impact consumer awareness of solar products. Using a descriptive and exploratory approach, the research gathered data from 120 participants in Haryana through a structured questionnaire. The analysis, which includes Chi-square tests and descriptive statistics, reveals significant associations between consumer awareness and demographic factors. Younger consumers, those with higher income, and individuals with higher educational qualifications are more likely to be informed about solar products. The findings emphasize the need for targeted education and outreach to enhance awareness, promoting the adoption of solar energy solutions for a more sustainable future.

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 Keywords

Exploring, Awareness, Consumers, Solar, and Products.

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 Abstract

The protection of personal identification numbers and passwords is a significant barrier for cybersecurity. Deceptive login pages soliciting personal information deceive billions of users daily. A variety of nefarious approaches are employed to deceive individuals into accessing harmful websites, such as phishing emails, clickjacking, malware, SQL injection, session hijacking, man-in-the-middle attacks, denial of service, and cross-site scripting. The offender creates a fraudulent yet convincingly comparable website to deceive victims into divulging their credentials. Researchers have offered many security solutions to mitigate these vulnerabilities; however, these methods are both ineffective and susceptible to error. We introduce and implement a client-side defence system that employs machine learning to detect phishing attempts and recognise fraudulent web sites. Our machine learning algorithm serves as a proof of concept for the Google Chrome plugin PhishCatcher, which classifies URLs as either trustworthy or suspicious. The random forest classifier evaluates a login page for authenticity after acquiring four web properties. The precision and validity of the extension were evaluated on multiple real-world web applications. The findings exhibited a precision and accuracy rate of 98.5% when evaluated on 400 authentic URLs and 400 identified phishing URLs. We assessed the latency of our technique using forty phishing URLs. We improved Random Forest by integrating XGBOOST, a technique that evaluates datasets through forest trees or ensembles of estimators to optimise features more efficiently and achieve superior accuracy.

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 Keywords

IOT devices, Support Vector Machine (SVM) and Random Forest (RF).

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This theoretical conceptualization evaluated the importance of green leadership in bringing about a sustainable change in the educational institutions particularly focusing on the psychological factors influencing the stakeholder behaviour. This framework discusses the Theory of Planned Behaviour, Value-Belief-Norm theory, and Social Identity Theory. This paper also identifies the key characteristics of green leaders that include sustainable knowledge, visionary thinking, effective communication and emotional intelligence. Simultaneously, the challenges are also identified that are faced by the green leaders in implementing the sustainable change.

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Green leaders, sustainable change, psychological factors, stakeholders, educational institutions

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Creative Commons Attribution 4.0 and The Open Definition

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Gray Baby Syndrome (GBS) is a rare but potentially life-threatening condition observed in neonates, primarily linked to the administration of chloramphenicol, an antibiotic. This poster explores the causes, effects, and management strategies for GBS, aiming to enhance awareness among healthcare professionals. The syndrome arises from immature liver enzyme systems in neonates, which impair the metabolism and excretion of chloramphenicol, leading to toxic drug levels. Clinical manifestations include ashen-gray skin discoloration, abdominal distension, respiratory distress, and cardiovascular collapse. Early diagnosis is crucial, often relying on clinical symptoms and elevated serum chloramphenicol levels. Management involves immediate discontinuation of the drug, supportive care, and in severe cases, exchange transfusion to reduce toxicity. This research underscores the importance of careful drug selection, dosage adjustments, and pharmacovigilance in neonates to prevent GBS and highlights the need for continued research into safer antibiotic alternatives and early diagnostic tools.

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 Keywords

gray baby, syndrome,graysh skin, abdominal, hypotension

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Creative Commons Attribution 4.0 and The Open Definition

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Employee engagement plays a crucial role in driving organizational success, influencing various aspects of work performance such as productivity, creativity, retention, and overall job satisfaction. This study examines the role of behavioral principles in enhancing employee engagement by exploring foundational theories like the Hawthorne Studies, Maslow's Hierarchy of Needs, and Herzberg's Two-Factor Theory. The paper further investigates the application of these theories through case studies of industry leaders such as Google, Zappos, and Netflix, which have successfully integrated intrinsic and extrinsic motivators into their employee engagement strategies. The study concludes that fostering autonomy, mastery, and purpose--while also managing hygiene factors effectively--can significantly improve employee outcomes, including satisfaction, productivity, and retention. The research also explores the evolving role of technology, leadership, and organizational culture, particularly in the context of hybrid and remote work environments.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Employee Engagement, Behavioral Principles, Motivation, Organizational Behavior, Hybrid Work Models, Leadership, Technology.

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Creative Commons Attribution 4.0 and The Open Definition