Volume 13 | Issue 5 |

 Abstract

As global levels of greenhouse gases keep rising, the temperature of the planet increases, causing ice caps to melt and drastic changes in global weather patterns. Today, it is approximated that the world's built environment accounts for about one-third of all global greenhouse gas emissions and uses 40% of the world's energy. The dilemma for environmental architecture is how to satisfy increasing demand for creative architectural solutions with less strain on the ecosystem. The paper discusses studies of user experience in different categories of energy-efficient buildings with emphasis on indoor climate and overall satisfaction. Energy users have varying concerns. Two key solutions are suggested to minimize CO2 emissions and combat climate change by substituting fossil fuels with renewable ones whenever feasible. Zero energy buildings can exchange energy with the grid, having a net energy balance of zero each year. The paper discusses zero energy buildings in detail.

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 Keywords

Ecological Design, Sustainable Development, Green Architecture, Zero energy building, materials, Ecosystem, Green design, Passive houses, Energy resources, Carbon emission, and Energy conservation.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The Pink Tax denotes a type of gender-based pricing where there is a differential in charge for similar goods and services for men and women. The study examines the consumer's awareness and economic impacts of discriminatory pricing in the Pink Tax context among both male and female consumers in Ernakulam district, India. Using a quota sample of 190 respondents and both descriptive and inferential statistical methods (i.e., Chi-square, ANOVA, and correlation analysis), this study discovered that men and women differ in terms of their awareness levels and that the Pink Tax has a real impact on consumer behaviour. The outcomes highlighted the need for public education and effective campaigns targeted at ameliorating the financial and social consequences of the Pink Tax as well as the need for ongoing policy changes; and consumer rights education and empowerment to address the gender gap and discriminatory pricing practices.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Pink Tax, Gender-Based Pricing, Economic Disparity, Consumer Awareness, Price Discrimination

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The Mughal Empire, which ruled large parts of the Indian subcontinent from the early 16th to the 18th century, left a profound cultural and architectural legacy. This paper explores how Mughal architecture served as a powerful expression of imperial authority while simultaneously reflecting a fusion of diverse cultural traditions. By examining key architectural elements and the broader sociopolitical context, this study demonstrates how Mughal rulers used architectural patronage not only to assert dominance but also to cultivate a rich cultural identity. Drawing from Indo-Islamic, Persian, and Central Asian traditions, Mughal architecture developed a distinct style characterized by monumental structures, symmetrical planning, ornate decoration, and the symbolic use of gardens and domes. This paper also delves into the syncretic nature of Mughal structures, showcasing how religious and cultural inclusivity played a role in shaping architectural decisions. Through a detailed analysis of early Mughal constructions and their symbolic meanings, the study highlights how architecture functioned both as a tool of governance and as a canvas of cultural expression.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Mughal Architecture, Indo-Islamic Architecture, Symbol of Power, Mughal Empire

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Mahendra Bhishm Krit Me Payal..Upnayas Me Abhiyakti Kinner Vimarsh Ka Adhunik Sandharbh

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Creative Commons Attribution 4.0 and The Open Definition

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Mahendra Bhishm Krit Me Payal..Upnayas Me Abhiyakti Kinner Vimarsh Ka Adhunik Sandharbh

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Creative Commons Attribution 4.0 and The Open Definition

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Agriculture, a cornerstone of global food security and economic development, faces numerous challenges including unpredictable weather patterns, crop diseases, and climate change. In recent years, the integration of machine learning (ML) techniques has revolutionized traditional agricultural practices by enabling data-driven decision-making and precise forecasting. This review paper explores the application of two widely used supervised learning algorithms--K-Nearest Neighbors (KNN) and Random Forest--in the domains of crop and weather prediction. The paper presents a comparative analysis of these models based on their accuracy, efficiency, scalability, and suitability for various agricultural datasets. Through a detailed examination of recent studies and real-world implementations, we highlight the strengths and limitations of each algorithm in addressing specific agricultural problems. Additionally, the review discusses the challenges of data quality, model interpretability, and scalability, while proposing potential directions for future research, including hybrid approaches and real-time predictive systems. By offering insights into the effectiveness of KNN and Random Forest, this paper aims to support the development of intelligent agri solutions for enhanced productivity and sustainability.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Review, KNN ,Random ,Forest ,Intelligent ,Agriculture, Predictive Analytics

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Creative Commons Attribution 4.0 and The Open Definition

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Herbal gummies formulated with Ashwagandha, Vitamin D3, and Brahmi offer a promising natural solution for managing emotional balance and alleviating symptoms of depression. Ashwagandha, an adaptogen, helps the body cope with stress, reduce anxiety, and promote a calm mental state. Brahmi, an herb traditionally used in Ayurvedic medicine, is believed to enhance cognitive function, improve memory, and reduce mental fatigue, further supporting emotional well-being. Vitamin D3 is vital for regulating mood and has been linked to reduced risk of depression, especially during periods of low sunlight exposure. This combination of ingredients works synergistically to help stabilize mood, enhance mental clarity, and support overall emotional health, providing a natural alternative to conventional antidepressants. The formulated chewable gummies exhibited excellent physicochemical properties, including uniform hardness, optimal moisture content, and a palatable organoleptic profile, ensuring high patient acceptability.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Chewable gummies, antidepressant formulation, Ashwagandha, Brahmi, Vitamin D, mental health innovation.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Artificial Intelligence (AI) has become deeply embedded in everyday life, enhancing convenience, efficiency, and decision-making across sectors like healthcare, education, and transportation. From virtual assistants to personalized algorithms, AI is reshaping how people interact with technology. However, it also presents serious challenges, including job displacement, privacy concerns, algorithmic bias, and lack of transparency. This paper explores both the benefits and drawbacks of AI, emphasizing the need for ethical development, inclusive policies, and public education to ensure its responsible use.

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Creative Commons Attribution 4.0 and The Open Definition

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Keywords Artificial Intelligence (AI), Daily Life, Smart Technology, Automation, Machine Learning, AI Ethics, AI in Healthcare, AI Challenges, Data Privacy, Human-AI Interaction, Job Automation, Intelligent Systems

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Creative Commons Attribution 4.0 and The Open Definition

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The rapid increase in online financial transactions has elevated the risk of credit card fraud, posing significant challenges for financial institutions and consumers. Traditional fraud detection methods often fail to identify complex and evolving fraudulent patterns. This paper introduces a machine learning-based framework that enhances fraud detection accuracy by leveraging advanced classification algorithms, data preprocessing, and model evaluation techniques. Using a real-world credit card transaction dataset, models such as Random Forest, Support Vector Machine, and XGBoost were implemented and evaluated using performance metrics like precision, recall, and F1-score. Our approach demonstrates improved detection capabilities, providing financial institutions with a powerful tool to mitigate fraud risks.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Credit Card Fraud, Machine Learning, Fraud Detection, Classification, Anomaly Detection, Data Preprocessing, Imbalanced Data, Cybersecurity, Financial Risk, Predictive Modelling

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Creative Commons Attribution 4.0 and The Open Definition

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Abstract This research investigates the use of artificial intelligence (AI) tools among Calicut district college students. It uses a mixed-method framework using surveys and interviews among 30 students to study usage patterns, benefits, ethical issues, and institutional reactions. The results show high use of AI, especially ChatGPT, for academic activities such as research and writing. While AI enhances efficiency, students are wary of dependency, information inaccuracy, and cheating. The research highlights the importance of ethics training in AI and institutional regulations to strike a balance between innovation and academic ethics.

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 Keywords

Keywords: artificial intelligence, higher education, academic integrity, ChatGPT, student learning, ethics in AI, AI tools

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Creative Commons Attribution 4.0 and The Open Definition

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Impurity profiling of any compound that lies under the pharmaceutical category is important to make sure that the drug is safe, efficient, and follows all regulatory compliance. This study presents comprehensive knowledge to identify and quantify impurities in any formulation that is intended for clinical use. We can use various advanced analytical techniques, like the UV spectrophotometer, to identify impurities through absorbed light at specific wavelengths. High-performance liquid chromatography coupled with mass spectrometry was employed to separate, identify, and characterize the impurities present. This study involves optimization of chromatographic conditions to improve resolution and sensitivity along with application of statistical analysis for data elucidation. Impurity levels were ensured against previously published standard pharmacopeia to make sure the drug follows safety guidelines. The results were validated by detecting the presence of several known and unknown impurities. This study helps to identify and eradicate impurity involving the pharmaceutical process of drug development.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Impurity, ICH Guidelines, Chromatography, Pharmaceutical drug

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Creative Commons Attribution 4.0 and The Open Definition