Volume 11 | Issue 11 |

 Abstract

In our rapidly urbanizing world, ensuring road safety is a pressing concern. The development of advanced driver assistance systems has become imperative to reduce accidents and enhance driver awareness. Maintaining full attention on the road is essential to prevent accidents. Distracted or inattentive driving is a leading cause of traffic accidents. When drivers are not fully engaged, their reaction times are slower, and they may fail to respond to sudden or unexpected events on the road. This study presents a comprehensive Lane and Speed Breaker Warning System designed to improve the safety of vehicles on the road. Fueled by cutting-edge machine learning techniques and trained on data containing videos of lanes and speed breakers, a system can be created that proficiently identifies lanes and speed breakers, offering timely alerts to drivers. This paper meticulously delves into the broader implications of our work in striving to prevent accidents on the road. As urbanization and vehicular traffic increase, road safety has never been more crucial. The Lane and Speed Breaker Warning system is a proactive step towards mitigating risks. By harnessing the power of machine learning, we empower the system to perceive and respond to its surroundings. This not only enhances driver awareness but also minimizes the potential for accidents and discomfort while driving. The Lane and Speed Breaker Warning System exemplifies a versatile solution for monitoring road conditions.

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 Keywords

Lane and Speed Breaker Warning System, Road Safety, Machine Learning, Accident Prevention

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 Abstract

In this study, we investigate the insulation properties of epoxy nanocomposites of Aluminium dioxide (alumina) and Silicon carbide (SiC). Epoxy nanocomposites have emerged as promising materials for electrical insulation applications due to their improved performance compared to traditional insulation materials. In this study, a comparative analysis is conducted to evaluate the insulation properties of epoxy nanocomposites enhanced with aluminium oxide (alumina) and silicon carbide (SiC) nanoparticles at various weight ratios, utilizing the COMSOL software for simulation and analysis. The dispersion and distribution of nanoparticles within the epoxy matrix are crucial factors affecting the insulation performance. Scanning electron microscopy (SEM) analysis confirms the homogeneous dispersion of alumina and SiC nanoparticles within the epoxy resin. The simulation is performed using the COMSOL software, which enables the evaluation of the electrical properties and breakdown strength of the nanocomposites. By systematically varying the weight ratios of nanoparticles to epoxy, the dielectric breakdown strength of the epoxy nanocomposites is assessed under different electrical field conditions. Through COMSOL simulations, the electric field distribution and breakdown behaviour of the nanocomposites are analysed for a comparative evaluation of the insulation performance between alumina and SiC nanoparticles at different weight ratios. The results obtained from the COMSOL simulations provide insights into the insulation properties of epoxy nanocomposites with varying weight ratios. The comparative analysis enables the identification of optimal weight ratios for achieving enhanced insulation performance. Furthermore, the simulations aid in understanding the impact of nanoparticle concentration on the electrical properties of the nanocomposites. This study contributes to the understanding of the insulation characteristics of epoxy nanocomposites with alumina and SiC nanoparticles at different weight ratios. The use of COMSOL software facilitates efficient simulation and analysis, enabling the optimization of weight ratios for achieving desired insulation properties. The findings have implications for the design and development of advanced electrical insulation systems with improved performance and reliability.

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 Keywords

Epoxy nanocomposites , Insulation properties , Aluminum nanoparticles ,Silicon carbide nanoparticles , Nanofillers , Electrical insulation

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The contemporary focus of technology is on harnessing the abundant energy resources available. Various methods for utilizing this energy source have been introduced, with one such application being the solar drying of crops. Crop drying is essential for enhancing crop quality and protecting against issues like moisture, pest/insect attacks, and interference from birds/animals. To achieve accurate and precise automation, artificial intelligence methods are employed to determine optimized values for parameters such as dryer efficiency and drying time. This software system incorporates machine learning techniques to boost the efficiency and effectiveness of solar drying. It leverages real-time data from diverse sensors, including temperature, humidity, solar radiation, and wind speed, to continuously monitor and control the drying process. The AI algorithm processes this data, enabling intelligent decisions that contribute to improved drying efficiency and product quality. This holistic approach, combining technology and artificial intelligence, represents a significant advancement in agricultural practices.

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 Keywords

Regression, ANN, Drying Efficiency, Drying Rate, Solar Drying System

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The study aimed to comprehend the life experiences of health workers during the COVID-19 pandemic in Dagupan City, focusing on their tasks, especially in caring for COVID-19 patients amidst numerous challenges. This research aimed to prompt the government to develop comprehensive solutions for health management, covering manpower, facilities, supplies, equipment, and action plans. Thirty health workers from a private hospital in Dagupan City participated as respondents, selected through non-probability sampling. Interviews were conducted using various communication platforms to collect information on their lived experiences. Additionally, the researchers documented necessary information, adhering to transparency and data privacy regulations. Utilizing descriptive and phenomenological designs with statistical analysis, the study revealed that physical and psychological distress was the primary challenge faced by health workers in Dagupan City during the pandemic. Ten out of 30 respondents reported significant impacts, including sleeplessness, extended duty hours, wearing personal protective equipment (PPE), and irregular meal times. The research offers timely and relevant recommendations tailored to the needs of health workers in the private hospital in Dagupan City. These recommendations, integral to hospital management and individual experiences, aim to empower and foster growth among health workers and the institution. The researcher formulated these suggestions to align with the overarching goal of assisting the government in implementing programs that support health workers.

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 Keywords

Covid 19, Health Workers, Dagupan City

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study delves into the intricate tapestry of political and social movements in South Asia and Southeast Asia. From historical roots to contemporary dynamics, it scrutinizes the impact of these movements on the region's economic growth. The objectives encompass exploring historical backgrounds, analyzing influential political movements, and examining socioeconomic changes. The significance lies in understanding how political disruptions affect economic policies, the role of governance, and the region's integration into the global economy. With a focus on demographics and interconnectedness, the research aims to inform evidence-based policies for sustainable economic development in this populous and dynamic part of the world. he historical analysis, comparative approach, and incorporation of qualitative and quantitative methods provide a holistic understanding. The case studies on Bangladesh, India, and Pakistan offer valuable insights into their political histories. The economic impact discussion effectively links political movements to economic outcomes, and the 2005 economic snapshot adds a relevant context. Your recommendations for a deeper dive into cultural dimensions, specific examples, gender perspective, future developments, regional cooperation, environmental challenges, media's role, comparative analysis, ethnic and religious diversity, and global context are excellent for enhancing the study's depth and relevance.

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 Keywords

Economic Growth, Bangladesh, India, Pakistan

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The recent study highlights the inadequate accessibility of rural godowns and warehouses for farmers, leading them to predominantly rely on household-level storage. However, the persistent lack of sufficient storage facilities in agriculture remains a pressing issue. Effective storage plays a pivotal role in safeguarding harvested crops from damage and preserving their quality. Storage facilities are fundamental infrastructure components essential for preserving farm produce before its sale. Key elements in establishing efficient agricultural storage solutions include managing moisture levels, ensuring security, and selecting appropriate locations.In this context, this paper aims to analyze the storage practices and the economic benefits associated with agricultural products in Dharwad district. Drawing upon data collected from a sample of farmers residing in 10 selected villages within the district, this paper seeks to explore the storage practices and their consequential economic advantages concerning agricultural products

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 Keywords

Key Words: Agricultural production, storage Practices, storage Benefits.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Image restoration is the operation of taking a corrupt/noisy image and estimating the clean, original image. Corruption may come in many forms such as motion blur, noise and camera mis-focus. There have a lot of approaches to remove noise from an affected image and to reconstruct a clean image with high visual quality. Some of the non-CNN related approaches are much efficient to remove noise from affected images. But these methods also show some issues like complex optimization, Computational expenses, etc. while performing denoising. To beat the disadvantages of these denoising approaches, CNN related methodologies are created to enhance the denoising performance. These denoising strategies are in acceptable considerations for their efficient performance in image rebuilding. They utilize some techniques like residual learning to enhance the denoising performance. So this paper provides a review on some CNN related image denoising approaches.

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 Keywords

Denoising, CNN, Residual Learning

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 Abstract

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by a range of social communication and behavioral challenges. One significant aspect of social communication that has garnered substantial research attention is the eye gaze behavior of individuals with ASD. Eye gaze is a fundamental component of non-verbal communication, serving as a critical means to establish social connections, convey emotions, and share attention. Research consistently shows that individuals with ASD often exhibit atypical patterns of eye gaze behavior. Specifically, they tend to avoid or exhibit reduced eye contact during social interactions, which can hinder their ability to form and maintain social relationships. These eye gaze deficits can be observed from infancy and persist across the lifespan. Understanding the implications of eye gaze deficits in individuals with ASD is crucial for developing effective interventions and support strategies. Improved knowledge in this area can help tailor interventions that target specific social communication challenges. Interventions such as social skills training, eye gaze-based therapies, and assistive technologies have shown promise in addressing these deficits and enhancing social functioning in individuals with ASD. In conclusion, eye gaze deficits in individuals with ASD are a significant aspect of the social communication difficulties that characterize the disorder. A comprehensive understanding of the underlying mechanisms and implications of these deficits is essential for the development of targeted interventions aimed at improving the social and communicative well-being of individuals with ASD. Future research in this field will likely provide further insights and innovative solutions for addressing the unique challenges associated with eye gaze in individuals with autism spectrum disorder.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Autism Spectrum Disorder, Eye Gaze Deficits

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

India's digitalization has led to a shift from traditional manual systems to a centralized online process for registering complaints, but the security of the First Information Report (FIR) system remains a critical concern. This paper proposes a solution that leverages blockchain technology to enhance the security of FIRs, addressing the need for a more secure, traceable, and chronological record-keeping system. The paper analyses existing police case-related procedures, the potential of blockchain technology, and proposed systems, including an integrated police record management system that incorporates blockchain, Machine Learning (ML), and the Internet of Things (IoT). The paper also proposes a mechanism to prevent tampering with e-FIR data, which can be compromised due to local control. The main issues with traditional methods include trustworthiness of e-FIR data, counterfeit registrations, and non-registrations. Corruption, inefficiency, and lack of transparency are the underlying causes of these problems. Implementing a system free from corruption is imperative, and blockchain technology is employed to protect the integrity of e-FIR data and prevent fake registrations, ensuring a more transparent and trustworthy system.

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 Keywords

Forensic Investigation, Law Enforcement, Blockchain Technology, Cybersecurity, Cryptographic Techniques, Security Breaches.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

A significant component of the research is the Worm Detection System, which uses Convolutional Neural Networks (CNN) to detect worms in crops. This system uses advanced image processing algorithms to identify and alert farmers regarding possible worm infestations based on pictures of crops. This study provides effective, sustainable, and technologically advanced solutions to modern farming challenges, marking a major advancement toward precision agriculture. Assessing the condition and nutrient levels of the soil is the main objective of the soil analysis component. To detect important characteristics including pH, moisture content, temperature, and nutrient concentrations, soil sensors are used. Crop Recommendation is the third system pillar. The system generates customized crop suggestions for farmers through the integration of information from aerial photographs, previous climate data, crop databases, and worm detection and soil analysis data.

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 Keywords

Machine Learning Techniques, Recommendation System, Crop selection, Soil analysis, Real-time monitoring

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Creative Commons Attribution 4.0 and The Open Definition