Volume 12 | Issue 3 |

 Abstract

In the quest for a balanced coexistence between economic development and environmental preservation, this research explores the dynamic relationship between environmental law, sustainable development, and the pivotal role of Environmental Impact Assessment (EIA). By examining international and national legal frameworks, the study investigates evolving principles that guide the intersection of law and sustainability. Emphasizing the importance of striking a harmonious balance, the paper delves into the critical function of EIAs in evaluating potential environmental impacts associated with developmental projects. Through case studies and analysis, it identifies best practices, challenges, and recommends strategies to strengthen legal frameworks, fostering a comprehensive approach to achieving sustainable development goals. This research aims to contribute valuable insights to the ongoing discourse on reshaping environmental laws for a resilient and ecologically sound future.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

EIA (Environmental impact assessment), SDG(sustainable development goal) Eco centric approach, environmental jurisprudence, Anthropocentrism

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Respiratory diseases, such as asthma and chronic obstructive pulmonary disease (COPD), are a major global health concern, affecting millions of people worldwide. Traditional methods for diagnosing and monitoring respiratory conditions often rely on invasive procedures, such as spirometry, which can be inconvenient and uncomfortable for patients. In recent years, there has been a growing interest in developing non-invasive and user-friendly methods for respiratory disease diagnosis and monitoring. Machine learning (ML) has emerged as a powerful tool for analyzing large amounts of data and identifying patterns that can be used to predict and classify respiratory conditions. ML algorithms have been successfully applied to a variety of tasks in respiratory medicine, including asthma risk prediction, classification of respiratory sounds, and automatic detection of respiratory events. In this review paper, the recent advance in ML-based methods for respiratory disease diagnosis and monitoring is discussed. The papers of Asthma risk prediction, Classification of respiratory sounds and Automatic detection of respiratory events are focused on. ML has the potential to make a significant contribution to the fight against respiratory diseases. By developing and deploying ML-based methods for respiratory disease diagnosis and monitoring, the quality of care for patients with these conditions has improved and improves the burden of respiratory diseases on healthcare systems.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Respiratory Disease diagnosis, Respiratory Disease Monitoring, A Survey of Recent Advances

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This research addresses the challenges faced by visually impaired individuals in recognizing people, interpreting facial expressions, and engaging in social activities. Current visual implant systems, like the RPS, suffer from low resolution phosphene images, limiting their effectiveness in artificial vision solutions. To overcome these limitations, our project introduces a pioneering VT-based approach, adapting a deep learning architecture for natural image recognition. Our innovative method utilizes the VT to extract and process crucial information from the user's surroundings. By comprehending the visual environment, this system provides enhanced perception for visually impaired individuals, offering insights into count, familiarity, gender, estimated ages, facial emotions, surrounding objects, and approximate distances of individuals nearby. The integration of the VT into the artificial vision system aims to transcend the constraints of current technologies, providing visually impaired individuals with a transformative tool. This research not only contributes to the advancement of artificial vision but also has the potential to significantly enhance the quality of life for those with visual impairments.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Vision Transformer(VT),Retinal Prothesis System(RPS)

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The compared to composite materials that are entirely synthetic, natural fibers are more affordable and more plentiful. The goal of the current work is to forecast the compressive and tensile properties of natural fiber-reinforced composite materials. The results were compared. The Prosopis Juliflora and Maize Fiber composite used in this experiment was made by hand utilizing the lay-up technique. Specimens were cut from the manufactured laminate in accordance with ASTM D 638 guidelines for the tensile test. Following that, the experiment is run through a universal testing machine (UTM). The tensile and compressive properties of the Prosopis Juliflora and Maize Fiber composite material were discussed based on the test findings. Because of their superior qualities, Prosopis Juliflora and Maize Fiber are widely utilized in a variety of engineering applications as a suitable substitute material.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

NFRC, Prosopis Juliflora, hand-lay-up method, tensile & compressiveProperties, UTM,

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Reverse vending machines, strategically placed in public areas like train stations and airports, focus on collecting plastic water bottles and employ mobile applications to incentivize users. This innovative approach aims to boost recycling rates, particularly addressing the issue of plastic waste, and contributes to reducing the volume of water bottles ending up in landfills. The system not only minimizes energy consumption and greenhouse gas emissions but also plays a role in job creation and conserving valuable resources through plastic recycling. Operating with AI technology, these machines offer a user-friendly process for both individuals and the backend system. In essence, reverse vending machines promote recycling, contribute to waste reduction, and engage individuals in sustainable practices, emphasizing their crucial role in modern sustainability efforts.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Reverse Vending Machine, AI, modern sustainability.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

A vital tool for businesses everywhere, forensic accounting provides invaluable insights into financial abnormalities, fraud identification, and litigation support. This abstract explores the deep effects that forensic accounting has on businesses, emphasizing how important it is for preserving financial integrity, improving transparency, and reducing risks. A specialist area of accounting called "forensic accounting" is devoted to identifying financial irregularities, deciphering intricate transactions, and offering knowledgeable testimony in court. It is used by businesses in a wide range of industries, including as banking, insurance, government, and corporations. Businesses are using forensic accounting to strengthen their internal controls and compliance measures in a time of increased regulatory scrutiny and sophisticated financial crimes. Financial fraud identification and prevention is one of the main functions of forensic accounting in businesses. Forensic accountants can spot unlawful transactions, embezzlement, and suspicious activity by carefully reviewing financial records, analysing large amounts of data, and using forensic technological tools. Proactive steps like these assist businesses in reducing financial risks, protecting assets, and preserving investor confidence. Furthermore, forensic accounting is essential to assisting businesses in court cases and other dispute resolution situations. Forensic accountants act as expert witnesses, offering reliable analysis and proof to support claims in commercial litigation, regulatory inquiries, or accusations of financial malfeasance. Their competence, impartiality, and meticulous nature greatly aid in the settlement of legal issues and the advancement of justice.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

forensic accounting, government, companies, corporations

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Biological processes are inherently complex, requiring an understanding not only of individual components but also of their intricate interconnections. Graphs, or networks, provide a natural framework for representing such relationships, enabling the depiction of both biological entities and their interactions. Recent advancements in high-throughput experimental technologies have led to an exponential increase in the generation of biological network data, which is now readily accessible to the scientific community through online databases facilitated by internet web services. Consequently, there is a growing demand for novel techniques to query, analyze, and process this wealth of data, with the aim of extracting insights into molecular biology, physiology, electronic health records, biological networks, and biomedicine as a whole. Machine learning, owing to its ability to effectively handle large datasets and generate accurate predictions using sophisticated statistical models, has emerged as a powerful tool for meeting these demands, promising rapid growth and widespread utilization in biomedical research.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Machine Learning; Biological Network; Bioinformatics Approach

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Today the incidence of diabetes mellitus is increasing devastatingly, and cataracts are one of the most common causes of visual impairment. Advances in cataract surgery techniques and instruments have generally improved outcomes. However, surgery may not be safe or effective for certain people with preexisting retinal disease or vision loss. Functional vision is essential in our everyday vision. Different tasks in our daily life use different parts of the visual system, which reflects our perspective in real-world situations where we need to see both small, high-contrast and large, low-contrast images. This review article addresses different aspects related to cataracts in people with diabetes. Most cataracts are caused by the aging of the eye lens, which continues to grow throughout life as new lens fibers continue to be laid down in the lens of the eye rather than replacing existing ones. It is maintained by many interdependent factors that contribute to optical homogeneity.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Cataract, Eye, Eye lens, Etiology, Surgery

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper presents a comprehensive review of recent advances in the field of surveillance and disaster relief drones. Unmanned Aerial Vehicles (UAVs) have emerged as pivotal tools in addressing a myriad of challenges, ranging from enhancing public safety to facilitating rapid responses in disaster-stricken areas. The review encompasses key components of these drones, including airframes, propulsion systems, and communication modules. Emphasis is placed on the integration of cutting-edge technologies such as high- resolution cameras, infrared sensors, and autonomous navigation systems, enabling drones to provide real-time data for surveillance and efficient disaster response.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

NA

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Abstract: This study investigates the impact of organizational citizenship behavior (OCB) on job satisfaction among middle level employees. A sample of 134 employees completed a survey measuring their OCB and job satisfaction. Regression, correlation and chi square analysis were conducted to analyze the data. The findings revealed a significant positive influence of OCB on job satisfaction, indicating that employees who engage in more OCB behaviors tend to be more satisfied with their jobs. Additionally, the study found that specific dimensions of OCB such as courtesy and altruism were positively associated with job satisfaction to a larger extent. The study suggests certain ideas and initiatives to organizations for promoting job satisfaction by fostering a culture that encourages OCB behaviors.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Organizational Citizenship Behavior, Job Satisfaction, Team Performance, OCB Dimensions

  License

Creative Commons Attribution 4.0 and The Open Definition