Volume 13 | Issue 1 |

 Abstract

Customer segmentation and behavior prediction play pivotal roles in enhancing business strategies, personalizing marketing campaigns, and optimizing inventory management in E-commerce platforms. This research focuses on analyzing a comprehensive E-commerce dataset containing transactions of ~4,000 customers over one year to uncover purchasing patterns, classify customer types, and anticipate future buying behaviors. Data preprocessing involved handling missing values, removing duplicates, and identifying order cancellations to ensure clean and reliable data for analysis.A detailed exploratory data analysis (EDA) was conducted to investigate product categories, customer attributes, and purchase trends. Advanced clustering techniques, including k-Means, were employed to segment customers into meaningful groups based on purchase frequency, spending patterns, and preferences. Machine learning models, such as Support Vector Machines (SVM), Logistic Regression, Decision Trees, Random Forest, Gradient Boosting, and k-Nearest Neighbors (k-NN), were utilized to classify customers into predefined categories, achieving moderate to high precision scores.To enhance predictive accuracy, deep learning models were incorporated. A Convolutional Neural Network (CNN) achieved the highest precision of 94.94%, leveraging its capability to extract complex patterns and relationships from high-dimensional data. An Artificial Neural Network (ANN) also demonstrated strong performance with a precision of 91.62%. Comparative analyses revealed the superiority of CNN and ANN over traditional machine learning models in handling complex datasets.This study introduces a novel approach to predicting customer behavior based on their first transaction. By integrating insights from clustering, classification models, and deep learning techniques, this research provides a robust framework for understanding customer dynamics and forecasting future purchases. The proposed methods empower businesses to optimize decision-making, improve customer satisfaction, and achieve sustainable growth in competitive E-commerce environments.

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 Keywords

Deep Learning,Machine Learning,Imaging,Disease Classification,Research Publications

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Creative Commons Attribution 4.0 and The Open Definition

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In India, the intersection of climate change and human rights presents complex challenges, particularly for marginalized and vulnerable communities. Climate change exacerbates existing socio-economic inequalities, impacting the most disadvantaged groups, such as indigenous populations, rural farmers, women, and low-income urban dwellers. This paper examines the concept of climate justice in the Indian context, emphasizing how climate change threatens fundamental human rights, including the rights to food, water, shelter, and livelihood. Through an analysis of India's climate policies, legal frameworks, and case studies, the paper critiques the adequacy of current responses and explores the gaps in addressing human rights concerns related to climate change. It highlights the need for a rights-based approach to climate action that integrates human rights considerations into policy frameworks, strengthens the legal protection of vulnerable communities, and promotes inclusive, participatory governance. Furthermore, the paper proposes recommendations aimed at empowering marginalized communities, addressing gender disparities, improving public awareness, and enhancing climate resilience through better social protection mechanisms and international cooperation. Ultimately, this research emphasizes the ethical and legal imperatives of safeguarding human rights in the face of a changing climate in India and globally.

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Creative Commons Attribution 4.0 and The Open Definition

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Climate Justice, Human Rights, Legal Protection, Social Protection, Environmental Justice

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Creative Commons Attribution 4.0 and The Open Definition

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Artificial intelligence is changing the landscape of the pharmaceutical industry simply because it analyzes humongous data, which hastens the process of clinical trials and drug development. For the exact purpose to instance, with machine learning, natural language processing, and predictive analytics, the process of finding drug candidates can be fine-tuned along with predictions on how a patient is going to react to a treatment and hence developing specific therapy plans. This strategy reduces both the time and expenses associated with introducing new drugs to the market. Furthermore, AI technologies evaluate chemical and biological information during the drug discovery phase to predict safety and effectiveness, thus speeding up screening processes. AI-driven solutions pinpoint patient populations and track real-time data to refine trial designs and ensure regulatory compliance. The implementation of AI in the pharmaceutical industry necessitates collaborative efforts aimed at the future, engaging technologists, regulatory bodies, and academic institutions to advance pharmaceuticals. Highlighting the significance of data integrity, privacy, and ethics, and generating real-world evidence is vital for enhancing patient safety and enabling proactive medication assessments. This application will encourage adaptable, patient-focused healthcare, hasten the availability of medications, and improve treatment options to achieve optimal results. The goal of integrating these systems is to drive progress in treatment alternatives.

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Artificial Intelligence, AI in Pharma, Drug design, Drug development, and Drug discovery

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Creative Commons Attribution 4.0 and The Open Definition

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Administration system of Morya Empire

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Administration system of Morya Empire

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Creative Commons Attribution 4.0 and The Open Definition

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Sand Stupas and Other Landforms in the Dhar Desert

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Sand Stupas and Other Landforms in the Dhar Desert

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Creative Commons Attribution 4.0 and The Open Definition

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The wastewater generated in residential or commercial buildings from streams devoid of fecal contamination--that is, any streams other than those that include toilet waste--is referred to as grey water. Grey water comes from a variety of sources, including sinks, showers, bathtubs, and dishwashing machines. As it contains fewer pathogens than residential wastewater, grey water is frequently safer to handle, quicker to clean, and more readily repurposed on-site for non-potable uses like as crop irrigation, landscaping, and toilet flushing. Sometimes referred to as "black water," sewage is grey water that has been mixed with effluent from toilets. Sewage should be managed in on-site sewage facilities, often septic systems, or sewage treatment facilities. When separated, it could lead to interesting decentralized treatment and reuse options. The concept of source separation, which is commonly employed in ecological sanitation techniques, encompasses the distinct handling of grey water. The primary advantage of segregating grey water from toilet wastewater lies in the significantly reduced pathogen load, which facilitates the cleaning and recycling process of grey water.

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Grey Water, Treatment, Recycling, Reuse, Quality, Quantity

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Age related macular degeneration is leading causes of vision loss in older adults worldwide .Emerging evidence suggests that dietary habits may influence the risk and progression of ARMD.The present study was aimed to study the eating habits and risk of age related macular degeneration. Age-related macular degeneration(AMD) is one of the main socioeconomical health issues worldwide. This is prospective study include all patients of age related macular degeneration above 50 years of age presenting in the Department of Ophthalmology at Dr.RPGMC Tanda. Total 86 patients were examined. There were 40(46.51%) patients who were vegetarian while 46(53.49%) patients were non vegetarian. Finding indicated that ARMD was more in non-vegetarians.

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Eating Habits, Age related Macular Degeneration

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Creative Commons Attribution 4.0 and The Open Definition

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Decision-making is a psychological phenomenon. It includes cognitive processes and is hence affected by the psychology of humans. Biases are the influencers that influence human psychology; particularly in the finance domain, and result in either financial loss or gain. The real-estate market is an imperfect market, which change its nature from person to person and location to location. Purpose: This study is conducted to assess the influence of psychological factors (heuristic, Herding and prospect) on the investment decisions of real-estate investors. Design/ Methodology/Approach: In this research samples have been collected using the stratified random sampling method from individual investors using an instrument formed using a Likert scale and with the medium of personal survey. For analysis of data, SMART PLS 4 software is used. Findings: This research coincides with the previous researches on the theme that psychological behaviour influence investment decisions but heuristic and prospect has a significant influence; however herding does not significantly influence investment decision of the real-estate investors.

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Keywords: Heuristic, Herding, Prospect, Psychological behaviours, investment, investment decision

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Creative Commons Attribution 4.0 and The Open Definition

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The children are the supreme asset of any nation; they are the greatest gift of humanity and a very important segment of human society. But unfortunately child has been exploited and discriminated every day in every society. Children working as labourers have been found as the cheapest and most disciplined labour. They can be found working in homes doing household chores, in factories- sometimes even in hazardous factories, fields, hotels, restaurants. Children are generally made to work under unhygienic conditions for long hours and the wages paid to them are generally very low. For strangers with perverted mentality, children are the easiest victim of sexual abuse. Children are also abused for organ and flesh trade. The fact is that children today, as they live in human rights and social justice, belong to the disadvantaged minority group. There are a range of laws in India and policy measures to protect the interests of children have been taken into account. It reveals, however, that children's rights are still not achieved in India. In this article an attempt is made to reveal the issues and challenges, constitutional provisions, legislations, and policy of the state prevailing in India for the enforcement of children's right.

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Creative Commons Attribution 4.0 and The Open Definition

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Children, Rights, Constitution, Policies.

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Creative Commons Attribution 4.0 and The Open Definition