Volume 12 | Issue 5 |

 Abstract

First aid is a crucial life skill that reduces fatalities and enables faster treatment for injuries. It also gives staff and the public a sense of purpose and the potential to save lives. School is a significant part of children's lives, impacting their physical and mental health. This study aims to assess the level of knowledge regarding first aid management of selected emergencies among school teachers at Royal Global School in Guwahati, Assam, and to find the association between knowledge scores and selected demographic data. A descriptive study was conducted with 100 samples drawn using a convenient sampling technique. Teachers' knowledge was assessed using a self-administered structured questionnaire. Results showed that the majority of teachers (34%) were over 35 years old, 53% were female, 60% were Hindu, 40% had a postgraduate degree, and 32% had 6-10 years of teaching experience. Findings revealed that 81% of teachers had moderately adequate knowledge, 15% had adequate knowledge, and 4% had inadequate knowledge of first aid management. A significant association was found between teachers' knowledge and educational status (x2=18.7, p<0.00). The moderately adequate knowledge among teachers regarding first aid highlights the need for improvement. Deliberate efforts should be made to enhance school teachers' first aid knowledge through training and awareness programs.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Knowledge, First aid, School Teachers.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This survey paper presents a mobile application designed to streamline the process of food donation, addressing the inefficiencies and logistical challenges often encountered by traditional donation methods. The application leverages technology to connect donors, recipients, and volunteers, facilitating the efficient collection, distribution, and utilization of surplus food. Through an instance analysis approach, we demonstrate the effectiveness of the application in reducing food waste, increasing accessibility to nutritious meals for those in need, and fostering community engagement. Furthermore, we discuss the scalability and potential impact of such a solution in addressing food insecurity on a larger scale. Overall, this research contributes to the ongoing efforts to use technology to advance social justice, particularly within the framework of food sustainability and humanitarian aid.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Food waste reduction, Humanitarian aid, Mobile Application, Food donation, Social Impact

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In our city, overloaded public garbage bins often lead to unpleasant odors and unsightliness, posing health risks and facilitating the spread of diseases. To address this issue and promote public health and cleanliness, we propose implementing a Smart Waste Collection and Management System. This system includes Smart bins equipped to detect hazardous gases and monitor bin fullness, with data transmitted via wireless mesh network. This data helps waste management providers and cleaners make informed decisions, improving public cleanliness and health. The system alerts the municipal web server when bins need cleaning based on garbage levels and hazardous gas presence, using ultrasonic and gas sensors connected to a microcontroller. A WIFI module and IoT technology facilitate this process, enabling real-time monitoring of waste collection by municipal authorities. Additionally, a web-based application linked to the server notifies authorities of alerts and allows remote monitoring, reducing manual oversight and enabling timely action.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Smart waste management, Internet of things (IoT), Smart Garbage Bins (SGB's), Waste Monitoring, IoT Based Garbage or Dustbins, IoT in Waste Management.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Despite Scads research to explore the association between (CSR) Corporate social responsibility spending and financial performance, literature are yet inconclusive. The study attempts to examine the relationship of financial characteristics of companies and the CSR spending in Indian emerging market. This research examine the influence of CSR spending disclosure upon the firm's performance through panel regression of samples comprising of 386 companies listed within S&P BSE 100 index, covering all primary players in capital market for four year period from 2014 - 2015 and 2017-2018. The inferences reveals out the trend in exploring the negative association of CSR spending on Firm's value and profitability (characteristics). This negative impact are majorly affected by Social and environmental spending disclosure score. The inverse relationship is highlighted by exposing the adverse impact of financial characteristics (Company's value and Profitability) on the CSR spending parameters. The research yields out implications to the policymakers, managers, investors and consumers of company. The inferences contributes to literature through offering CSR insights spending and the company's performance (Indian Emerging market) to have increased international focus. Further to this, the CSR disclosure measurement through (ESG)environmental score, Social score and then governance score stands as novel in this context.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

CSR-Corporate social responsibility, BSE-Bombay Stock-Exchange, disclosure, financial characteristics, performance, profitability

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Microfinance operations span across 641 districts across 36 States and Union Territories in India. Banks lead with a presence in 636 districts, followed by Small Finance Banks (SFBs) in 616 districts, and Non-Banking Financial Companies - Microfinance Institutions (NBFC-MFIs) in 613 districts. NBFCs operate in 538 districts, while Non-profit Microfinance Institutions (MFIs) are active in 384 districts. The study provides a comprehensive analysis of the SHG-Bank Linkage Programme in India from 2017-18 to 2022-23, focusing on Non-Performing Assets (NPAs) as key performance indicators. The objectives include examining trends in Gross NPAs, NPA as a percentage of Loan Outstanding, and regional variations. Secondary data from NABARD's annual reports on microfinance in India served as the primary data source. Growth rates were computed to analyze year-on-year changes. The findings reveal fluctuating Gross NPAs over the study period, reflecting varying asset quality and repayment performance. NPA as a percentage of Loan Outstanding decreased consistently from 6.12 per cent in 2017-18 to 2.79 per cent in 2022-23, indicating improved credit risk management. Regional analysis showed diverse NPA trends, with some regions demonstrating significant improvements while others faced ongoing challenges.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

SHG-BLP, NPAs, different regions

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Creative Commons Attribution 4.0 and The Open Definition

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Abstract: This project presents the design and implementation of an Arduino-based boundary detection system utilizing load cells, LED indicators, and a tare switch. The system is aimed at detecting when an object crosses a predefined weight threshold, indicating it has reached a boundary.The hardware setup includes an Arduino microcontroller interfaced with an HX711 load cell amplifier module and various peripheral components. LED indicators are employed to visually signal boundary detection, while a tare switch allows for resetting the weight measurement after each boundary crossing. Additionally, a 16x2 LCD display provides real-time feedback on the weight status.The project workflow encompasses initialization, continuous weight monitoring, boundary detection, and tare functionality. The Arduino reads weight data from the load cell, compares it with the predefined threshold to detect boundaries, and triggers LED indicators accordingly. Upon boundary detection, the system waits for the user to press the tare switch for weight reset.Future enhancements may include data logging capabilities, threshold adjustment mechanisms, and remote monitoring options, expanding the system's versatility and applicability in various scenarios.This project serves as a foundation for building robust boundary detection systems suitable for applications such as object sorting, inventory management, and industrial automation.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

HX711, 16x2 LCD, LED, Arduino board etc.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

An evaluation of the design, development and performance of a robotic device specifically designed for borewell operations is presented in this paper. In this project, traditional methods are used to monitor the live demonstration of the robotic arm with the help of advanced technologies such as Blynk 2.0 software, Camera, UltraSonic Sensor, which reduce manual work and pose inherent safety risks. The proposed robotic device is designed to increase the efficiency, safety and precision of drilling operations.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

- Blynk 2.0, IOT (Internet of Things), Sensor Technology, Camera, Robotic Arm, Ultra Sonic Sensor, Motor Driver, DC Motor, ESP 32

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Potholes on roads pose a significant hazard to drivers and can cause damage to vehicles, leading to safety concerns and increased maintenance costs. Traditional methods for pothole detection often rely on manual inspection or specialized equipment, which can be time-consuming and expensive. In recent years, deep learning techniques have emerged as a promising approach for automating pothole detection. This paper presents a comprehensive review of deep learning-based methods for pothole detection, including the use of convolutional neural networks (CNNs) and other advanced architectures. It discusses various datasets and preprocessing techniques commonly employed in this domain and analyze the strengths and limitations of existing approaches. Additionally, it highlights future research directions and potential applications of deep learning in pothole detection, such as real-time monitoring systems and integration with autonomous vehicles. Overall, this review provides valuable insights for researchers and practitioners interested in leveraging deep learning for improving road safety and infrastructure maintenance.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Potholes, Convolutional Neural Networks (CNN), Deep Learning, Road safety, Infrastructure maintenance

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The hotel industry in India is growing at considerable phase but with this growth there also comes problems like attrition of manpower. The research says that training practices play a major role in controlling attrition. This paper focuses on the training practices adopted by the hotels in Gujarat. The data was collected from 540 respondents from 55 different 5 star, 4 star, 3 star, 2 star and star not allotted category hotels in different cities of Gujarat during the period of January to June 2021. It concludes that training practices adopted by 4 and 5 star hotels was regularly and in order to improve the caliber of its workforce in this competitive world, these hotels give compulsory training to their employee

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

training, practices, hotel industry, Gujarat

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Creative Commons Attribution 4.0 and The Open Definition