Volume 13 | Issue 4 |

 Abstract

Abstract: This research explores the application of machine learning (ML) techniques in analyzing societal crime patterns to enhance predictive policing and inform policy-making. By leveraging advanced algorithms, including supervised and unsupervised learning models, we analyze large-scale crime datasets encompassing demographic, geographic, and temporal features. Our methodology integrates feature engineering, anomaly detection, and predictive modeling to identify crime hotspots, forecast crime trends, and uncover underlying socio-economic factors contributing to criminal activities. The results demonstrate high accuracy in predicting crime occurrences and reveal actionable insights into crime distribution and prevention strategies. This study underscores the potential of ML in transforming law enforcement practices and fostering safer communities through data-driven decision-making, while addressing ethical considerations such as bias mitigation and data privac

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 Keywords

Machine Learning, Crime Analysis, Predictive Policing, Societal Crime Detection, Data-Driven, Crime Prediction, Crime Forecasting

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This study explores the investment trends and behavioral patterns of college students in the stock market. With the increasing accessibility of trading platforms and financial information through digital media, more young individuals, especially college students, are showing interest in stock market investments. The main objective of this research is to analyze how college students invest, what motivates their decisions, and the factors influencing their investment behavior such as risk appetite, financial literacy, peer influence, and use of digital tools.

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Stock Market, Investment Behavior, Risk, Investment Trends , Awareness

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India got Independence on 15th Aug. 1947, since independence till now as country India achieved various milestone in the field of science, technology, Research and Development, health etc. A country facing famine and epidemic before independence today recognized as "the pharmacy of the world" and supplier of food to the world community. The political prestige of India is today recognized all over the world. At the Domestic Level India has introduced big changes in economy infrastructure and development initiatives. Simultaneously Indi's proactive role in multilateral fora such as the United Nations General Assembly, the Brazil, Russia, India, China, South Africa (BRICS) summit, and the G-20 summit were significant achievements at Global level seeking investment and development Priorities. India successfully held G-20 Delhi summit that manifests it's voice and important role in of global governance and world politics. But even after all these developments a lot have been left to be achieved. Even now the country ranked lowest in Hunger, Happiness, literacy, health in the world. Even today million died because of non-availability of better health and sanitation facility and by hunger. This paper is an effort to highlight the issues on which country fared better and to streamline those issues on which the country needs to act in a vigorous manner for the greater good of country and humanity.

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Demography, Pandemic, Pharmacy of the world, Atmnirbhar Bharat, G-20,

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Alum is also known as the "Potash Alum" It is a naturally occurring compound known for its astringent, antiseptic, and hemostatic properties. Although traditionally used in medicine, alum has recently studied the possibility of wound-healing action, especially in the case of mouth ulcers. Its antibacterial, anti-inflammatory, and tissue-regenerating properties help it speed up recovery; therefore, it is a great medication. By comparing their potency with traditional therapies, this review analyses alum-based medicines' chemical composition, pharmacological action, dosage forms, and commercial formulations. Using mechanisms such as protein coagulation, vasoconstriction, bacterial inhibition, and epithelial regeneration, alum helps in damage control, blood reduction, and better tissue repair. Although it has many advantages, alum should be handled carefully since long-term use of alum raises possibilities of irritability and toxicity. Although historical evidence and early research suggest its effectiveness, more clinical trials are needed to set standard guidelines for secure and ideal applications. Alum-based treatments in wound care and oral medicine might have even better therapeutic value in the future with such developments as nano-formulations and bioactive enhancement.

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Alum, Hemostatic, Anti-inflammatory, Antibacterial Properties, Nanoformulations, Bioactive Enhancement

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Paan Masala poses persistent hygiene, health, and aesthetic challenges in Indian cities, imposing substantial cleaning costs. Existing manual enforcement under the Swachh Bharat Abhiyan remains inefficient and unsustainable. This paper proposes Swachh AI, an AI-based real-time surveillance and enforcement system for detecting public spitting incidents and identifying offenders. The system integrates (i) a YOLOv11-based instance segmentation model to detect spitting actions with pixel-level accuracy, and (ii) an OCR-based license plate recognition module for offender identification. Together, these modules enable automated evidence capture, offender tracking, and data logging for civic enforcement. Swachh AI is designed for modular integration, scalability, and privacy compliance, suitable for deployment in smart cities and public infrastructure. Experimental evaluations demonstrate high detection accuracy in varied outdoor conditions, affirming its potential for scalable urban hygiene management.

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Spitting detection, YOLOv11, instance segmentation, OCR, license plate recognition, public hygiene, AI surveillance, smart cities.

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Human activity detection for video surveillance system is an automated way of processing video sequences and making an intelligent decision about the actions in the video. It is one of the growing areas of Computer vision and artificial intelligence. Suspicious Human Activity Detection is the process of detecting unwanted human activities in a crowded place and alerting the concerned authority about the activity. This is done by converting video into frames and analyzing the persons and their activities from the processed frames. This paper gives an overall idea of the development of the system that detects suspicious human activities.

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Suspicious crowd behavior, Video surveillance, Transfer learning, Anomaly detection, Computer vision

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Food waste reduction, as a major application area of the Internet of Things (IoT) and big data technologies, has become one of the most pressing issues. In recent years, there has been an unprecedented increase in food waste, which has had a negative impact on economic growth in many countries. Food waste has also caused serious environmental problems. Agricultural production, post-harvest handling, and storage, as well as food processing, distribution, and consumption, can all lead to food wastage. This wastage is primarily caused by inefficiencies in the food supply chain and a lack of information at each stage of the food cycle. In order to minimize such effects, the Internet of Things, data science, and various management models are used to reduce food waste in food supply chains. This paper provides a comprehensive review of IoT and data science based food waste management models, algorithms, and technologies with the aim of improving resource efficiency and highlights the key challenges and opportunities for future research. Food waste has become a critical global challenge, with significant economic, environmental, and social implications. This project focuses on developing a data-driven solution for food menu recommendation and waste management using data science. By leveraging historical data and predictive analytics, the system aims to optimize food utilization and minimize waste at the household and organizational levels. Machine learning models are employed for predicting waste and recommending efficient menus based on consumption patterns, ensuring resource efficiency and sustainability. This project presents a comprehensive solution to improve decision-making in food management while reducing waste.

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Food waste reduction Internet of Things (IoT) Data science Predictive analytics Machine learning Food supply chain optimization Resource efficiency Menu recommendation systems Waste management Consumption pattern analysis Sustainability Food utilization Decision support systems

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Education sector is the main pillar of social development of any Nation throughout the world wise. Teachers have a critical role in the development and transformation of the educational system and society as a whole. They functioned as a focal point for intentional, meaningful, and successful teaching and learning. The present study was planned to examine the relationship between Self-Esteem and Organizational Citizenship Behavior of teachers to Build Stronger Educational Environment. A purposive sample of 200 post graduate Government school teachers was taken in present study. A correlational research design was used to examine the relationship between Self-Esteem and Organizational Citizenship Behavior of teachers. Self-esteem scale by Rosenberg (1979) and Organizational Citizenship Behaviour scale by Podsakoff, MacKenzie, Moorman, and Fetter (1990) was used in present study. Correlational coefficient result of the study showed a significant positive relationship between Self-Esteem and Organizational Citizenship Behavior among school teachers. Results of the study revealed that more the teacher have self-esteem; also have high overall and various dimensions of organizational citizenship behaviour e.g. altruism, Conscientiousness, Sportsmanship, Courtesy and Civic Virtue. Present study suggested that if teachers were having more positive beliefs and appraisals about oneself are more efficacious and concerned about and connected or attached to their schools/ institutions.

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Self-Esteem, Organizational Citizenship Behavior altruism, Conscientiousness, Sportsmanship, Courtesy and Civic Virtue.

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Phytic acid (myo-inositol hexakisphosphate or IP6) is a biochemical compound found abundantly in seeds, grains, and legumes. It plays multiple important role in plants such as in metabolism, defense, tolerance towards stress, including its crucial importance in phosphorus storage and germination of seed. Inspite of its significant potential in plants, phytic acid is not considered as favourable for animal and human nutrition due to its chelating interaction with minerals. This review intend to explore the biological importance of phytic acid in plants and environment as well associated challenges.

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phytate, antinutrient, chelate, pronutrient, bioavailability

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bearings are vital components in rotating machinery, significantly impacting performance and reliability. As machines operate under increasingly demanding conditions, bearings must withstand higher loads and temperatures. However, these conditions can lead to increased vibration, accelerating fatigue failure. There are two primary types of bearings: radial hydrodynamic bearings, which rely on fluid film lubrication, and hydrostatic bearings, which utilize external pressure. Hydrodynamic bearings operate under elasto-hydrodynamic lubrication conditions, while journal bearings are prone to self-induced vibrations due to radial clearance. To ensure reliable operation, monitoring bearing performance is crucial. Vibration analysis has emerged as a popular method for detecting potential issues and predicting bearing health. This study focuses on the vibration and tribological analysis of various bearings.

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Vibration Analysis, Tribological Analysis, FFT Analyzer

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