Volume 13 | Issue 6 |

 Abstract

Abstract The widespread use of mobile phones has transformed digital engagement across various age groups, influencing both social and behavioral patterns. This cross-sectional study examines the relationship between age, gender, and screen time among residents of Jabalpur city. Data were collected through a structured survey, capturing mobile usage habits across different demographic groups. The findings reveal that younger individuals, particularly those aged 12-28, exhibit the highest screen time, with a significant proportion using smartphones for extended hours. Gender disparities are also evident, with young women showing higher mobile usage than a male counterparts, while middle-aged groups display an inverse trend. Excessive mobile phone use, particularly among adolescents and young adults, raises concerns about potential health risks, including digital addiction, anxiety, and sleep disturbances. The study emphasizes the need for awareness regarding responsible technology use and balanced digital habits. Future research could explore the long-term implications of excessive screen time and interventions for promoting healthier digital behaviors.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Keywords Mobile phone, screen time, smartphone dependence, mental health, digital well-being, technology and behavior.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper proposes the study of design and manufacturing of 20MW induction motor. This paper aims to design, analyze, and optimize the performance of a 20MW induction motor, focusing on its electrical and thermal characteristics. The study will investigate the motor's design parameters, operating conditions, and performance metrics to identify areas for improvement. Motor Design: Detailed design of the induction motor, including electromagnetic and thermal analysis. Performance Analysis: Analysis of the motor's performance under various operating conditions. Optimization: Application of optimization techniques to improve the motor's efficiency, power factor, and reliability. Thermal Management: Investigation of thermal management strategies to ensure reliable operation. The project is expected to provide: 1. A detailed design and analysis of a 20MW induction motor. 2. Optimized performance characteristics. 3. Effective thermal management strategies. This project will contribute to the field of electrical engineering, providing valuable insights into the design and operation of large-scale induction motors.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Induction Motor, Efficiency, Power Factor.

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Creative Commons Attribution 4.0 and The Open Definition

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Abstract The digital era has revolutionized the creation, distribution, and consumption of intellectual property (IP). While this transformation has led to unparalleled access and innovation, it has also introduced significant challenges to existing Intellectual Property Rights (IPR) frameworks. This paper explores the evolving nature of digital content, legal complications, and the roles of technology and policy in safeguarding IP. It discusses case studies from industries such as music, film, and software, and evaluates how technologies like blockchain and AI are shaping the future of IP enforcement. Ultimately, this research underscores the need for dynamic and globally harmonized legal systems to balance protection with innovation in the digital economy.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Abstract The digital era has revolutionized the creation, distribution, and consumption of intellectual property (IP). While this transformation has led to unparalleled access and innovation, it has also introduced significant challenges to existing Intellectual Property Rights (IPR) frameworks. This paper explores the evolving nature of digital content, legal complications, and the roles of technology and policy in safeguarding IP. It discusses case studies from industries such as music, film,

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This project presents a smart and efficient system for detecting faults in solar panels using deep learning techniques. Solar energy is a clean and sustainable power source, but faults in photovoltaic (PV) panels--such as short circuits, shading, or panel degradation--can reduce energy output and efficiency. The proposed system uses artificial neural networks (ANNs) trained on historical voltage, current, and temperature data, as well as thermal images, to automatically identify different types of faults in real-time. The model was tested using a dataset collected under varying environmental conditions and achieved high accuracy in classifying normal and faulty panel behavior. By enabling early fault detection, this system helps reduce maintenance time, minimize power losses, and improve the overall performance of solar installations. This work supports the move toward smarter, more reliable, and sustainable energy solutions.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Solar Panel Fault Detection Photovoltaic System (PV) Deep Learning Artificial Neural Network (ANN) Thermal Imaging UAV Monitoring Machine Learning Power Loss Reduction Predictive Maintenance Current and Voltage Analysis Smart Energy System Renewable Energy

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Creative Commons Attribution 4.0 and The Open Definition

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As we know that accurate prediction of patient in Intensive Care Units is vital for optimizing clinical decision-making and resource allocation. Efficient management of Intensive Care Units (ICUs) is critical for optimizing patient outcomes and resource allocation. This study explores the application of machine learning (ML) techniques to predict patient mortality and length of stay (LOS) using ICU patient dataset. By employing algorithms such as Random Forest (RF), Logistic Regression (LR), XGBoost and Bidirectional LSTM, we aim to enhance predictive accuracy over traditional scoring systems like APACHE II. Our findings indicate that ML models, particularly RF and LSTM, outperform conventional methods, offering valuable tools for clinical decision-making and hospital management.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Machine Learning, ICU, Mortality Prediction, Length of Stay, Random Forest, Bidirectional LSTM., XGBoost.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

With the increase in development of smart cities, the idea of keeping the cities clean is the utmost requirement. The amount of garbage produced is too large and the manual efforts required to process it is very tedious. With evolution of technology in every field, automated ways can be adopted to prevent the piling of the garbage. The waste segregator is designed to provide ease in the disposal of waste that is collected. The system consists of three bins, each one for wet, metal, and dry waste. The conveyer belt system detects the incoming waste and classifies it as metal, dry or wet using different sensors connected to the system and deflects it in the respective bin.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Dry, wet, metal, sensors, Arduino UNO, Embedded C

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

According to food and agriculture organization (FAO), India's 70% of rural households still depend primarily on agriculture for their livelihood. Nowadays, millions of farmers are quitting farming in search of better opportunities because of agricultural problems like more wages, wastage of seeds during seeding, theft in storage areas, lack of irrigation, more time requirement for every operation, lower yield of crops and so on. In this report documents and presents the results of the work carried out on the ways of designing and developing a prototype of Agri bot that can be helpful to overcome the problems currently faced by a farmer. In the implemented system, HC-06 Bluetooth module is interfaced with Arduino UNO to control the functionality of the robot. The implemented prototype of Agri bot can perform the tasks like ploughing the land, Drilling, sowing the seeds and water sprinkling.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Seed Sowing, Arduino Uno, HC 05 Bluetooth Module, L298 Motor Driver, DC Motors, Gear Motors.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The interaction between man and nature has always been a topic of exploration. It has shown to be the unbreakable link in the development of successful human civilizations across rivers in a way that is both sustainable and effective at meeting fundamental needs, that has effectively led to the inventions, and advancement of the human races. This is reflected in the arts, crafts, dietary patterns, and attire indicating evidence of ecocentrism being the basis behind evolution of the Bihu festival which is being studied. Circular economy quite often focuses on local production and consumption but this is not a new concept in Indian culture and tradition as evident from various instruments, accessories that are used in Bihu. Finding these connections between traditions and sustainability is the main goal of this paper which includes evidence-based literature methods. In this study, various types of Bihu, its association with farming cycles and its close linkage with nature in terms of celebration, accessories, and musical instruments evolved from locally available material is explored. Literature and ground experience gathered during study suggests that the gatherings are one of the nodal centres for dissemination of information and intergenerational knowledge preservation at rural level. It is thus necessary to include the roots of our IKS well embedded in our day-to-day life into designing new approaches for community developments. From the findings, it can be safely stated that developmental policies recognising the sustainable connections in culture is the need of the hour to comply with international sustainability commitments.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

sustainability, Bihu, culture, Indian Knowledge System

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The extract of the red mud waste prepared in the laboratory is almost equivalent to the lechate leaking from red mud pond of the contaminated site. The red mud waste extract is deadly toxic to the germinating crop seeds in field conditions. Experiments were conducted at sub-lethal concentrations to study the impact of lechate waste on green gram seed biological parameters. Toxicity study indicated that lechate extract is deadly toxic. In petriplate culture experiments the lechate waste is deadly toxic but toxicity depleted when tested in pot culture due to interaction of lechate waste with soil particles. Seed germination and seedling establishment significantly depleted with the increase in lechate concentration when compared to control seedlings. The total chlorophyll, pheophytin and carotene content of green gram plant leaves decreased significantly with the increase in lechate concentration compared to their respective control values after 144hr of germination. The photosynthetic rate, respiration rate and GPP values significantly decreased in the exposed green gram seedlings with the application of lechate compared to control green gram seedlings in petri plate culture. The residual alumina accumulation increased with the increase in toxicant (lechate) concentration in the leaves and roots. Lechate exposed roots accumulated more amount of alumina than the leaves of the exposed seedlings/ plants. The complex bio molecules like DNA, RNA, Protein, FAA content decreased in lechate exposure seedlings compared to control seedlings The photosynthetic rate, respiration rate and gross primary production significantly declined in exposed seedlings compared to control seedlings. Little insignificant increment in the photosynthetic rate was noted at sub-lethal concentration of the lechate. The enzyme activity tested decreased in the exposed green gram seedlings with the application of lechate compared to control green gram seedlings in Petri plate culture. The study on seed biology indicated that the red mud waste dumped by the industry is deadly toxic and if released accidentally even into the environment, will cause environmental havoc. Present study aims at understanding the impact of RM (red mud) RM Waste lechate on the seed germination, seedling establishment, eco-physiological studies, biomolecular studies and enzymological studies of a crop seed germinating under lechate stress.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Alumina, Lechate, Green Gram, Germination, Pigments, Photosynthetic efficiency, Biomolecules, Enzyme.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In many developing nations, gathering readings from utility meters and identifying unauthorized electricity use is and time-consuming process that demands considerable human resources. Implementing an energy meter reading and monitoring system through the Internet of Things offers an efficient and cost-effective method to wirelessly transmit information about the energy consumed by users. Moreover, it helps in detecting electricity theft. This study focuses on measuring household electricity use and automatically generating bills using IOT and telemetry communication methods. Additionally, it seeks to identify and address energy theft. An Arduino microcontroller is utilized to manage operations with the digital energy meter and to link the system to a WIFI network, subsequently connecting to the Internet and a server. A passive infrared sensor is integrated to detect any unauthorized alterations in the metering system. If such activities are detected, the system will send an alert to the server and can automatically disconnect and reconnect the electricity supply. The proposed system is capable of continuously monitoring energy consumption and notifying both providers and consumers about the amount of power used. Energy consumption is computed automatically, and bills are updated online using an IOT network. This automation can lessen the demand for manual labor significantly.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Internet of Things (IOT), Microcontroller, Electricity theft, AMR

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Creative Commons Attribution 4.0 and The Open Definition