Volume 12 | Issue 6

 Abstract

A few centuries ago, the English language consisted of a collection of dialects spoken mainly by monolinguals within the shores of a small island. However, English serves many purposes throughout the world now-a-days. At the beginning there was only one variety of English existed that is the native variety. There are so many varieties of English worldwide. Even within the native land of English i.e. the British Isles, one can find so many variants of English. It is not an exaggeration to state that English is a language- the language on which the Sun does not set, whose users never sleep (Quirk, 1985:1).

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Varieties, British Isle, Native, England, Received Pronunciation.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Road accidents remain a significant public health concern worldwide, leading to loss of lives, injuries, and economic losses. To address this issue, researchers have increasingly turned to machine learning techniques for analyzing road accident data to understand contributing factors, predict accident occurrences, and propose preventive measures. This paper provides a comprehensive review of the state-of-the-art machine learning-based approaches for road accident analysis. We systematically categorize and summarize the various machine learning methods employed in accident detection, severity prediction, causality analysis, and risk assessment. Additionally, we discuss the challenges associated with these approaches, including data availability, feature selection, model interpretability, and scalability. By highlighting the recent advancements, limitations, and future directions in road accident analysis using machine learning, this review aims to provide insights for researchers, policymakers, and practitioners working in the field of road safety.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Road accidents, public health, severity prediction, road safety, machine learning.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Background: Sleep is essential for health but gender differences might impact the sleep patterns. Extensive study has revealed physiological and behavioral differences in sleep cycles between men and women including duration, phases and rhythms. Community actions are critical for increasing awareness and teaching about gender-specific sleep requirements. Creating comfortable sleeping conditions and managing stress are also critical. Communities that promote sleep awareness can empower individuals to priorities their sleep health, hence enhancing overall quality of life. Objectives: To study the difference between the sleep cycles of males and females along with the factors affecting it. To make people aware about the importance and benefits of adequate sleep and measures to maintain regular sleep cycles. Methodology: 400 participants were taken for the data collection. Global Sleep Assessment Questionnaire (GSAQ) which contained 11 questions regarding sleep experiences of an individual was used. Patients were prescribed with various relaxation techniques and recommendations to improve their sleeping habits. For the very purpose data has been collected from January 2024 to April 2024. Results: The analysis of the GSAQ Score showed that sleep cycle of Males is more disturbed than that of Females. The average score of males was 7.3 while as in females it was 6.65. Conclusion: The study concluded that on gender differences in sleep patterns, with males experiencing more interrupted sleep cycles than females. This highlights the importance of targeted therapies to improve sleep quality, particularly among men. Community sleep awareness projects can empower people to priorities their sleep health, resulting in a higher quality of life overall.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Sleep Cycle, Global Sleep Assessment Questionnaire, Sleep Quality, Sleep Disorder, Health

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Eye sight plays a major role in collecting most of the information from the real world and that information will be processed by brain. Many people around the world are blind or not able to see clearly or recognisation the objects properly. Visually impaired people suffer inconveniences in their daily and social life with respect to challenges during commuting. This condition leads to the loss of the valuable sense of vision. The need for assistive devices was and will be continuous. There is a wide range of navigation systems and tools existing for visually impaired individuals. The blind person truly requires an aid in identifying objects. Smart Blind Stick is an interactive device which mainly aims at helping the blind to navigate easily and in a safer manner. In a normal day to day situation a blind person waves the blind stick ahead of them in order to check for any objects or obstacles. The smart stick helps them in this by detecting if any obstacle is blocking the path being taken by the subject. The device detects the obstacle with the help of a camera attached to the front of the stick. On detection of the obstacle, it is identified and appropriate instructions are provided to the user. The instructions to the blind person are sent over earphones. Thus, the stick provides a safer and a better navigation experience for the visually challenged.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Object detection, Machine Learning, IoT, Raspberry pi, pi Camera, YOLO algorithm.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The prevalence of skin diseases, particularly skin cancer, presents a global health challenge an increasing impact on the economy and workforce. Melanoma, arising from dysfunctional melanocytes, is the most aggressive form of skin cancer, in constrast non-melanoma skin cancers (NMSC) like squamous cell carcinoma (SCC) and basal cell carcinoma (BCC) account for the majority of cases. The incidence of NMSC has risen significantly, with men being at higher risk due to genetic, phenotypic, and environmental factors. Advances in polymeric micro/nano carrier-based therapies offer promising avenues for skin cancer management, including drug and gene delivery, and combination therapies. These innovative approaches hold the potential for overcoming current treatment limitations and advancing both research and clinical applications in the field. Nisosomes can be important nanomolecules For the cancer management and drug delivery. In this review, we are discussing the nisosomes as a nanocarrirer for drug delivery in skin cancer.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Skin cancer, niosomes, drug carrier, nanocarrier, cancer treatment

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This project details the design, development, and evaluation of a prototype cycloidal gearbox. Cycloidal gear systems are known for their high torque transmission, compact size, and low noise levels. The main goal of this study is to create a functional prototype to demonstrate the feasibility and effectiveness of cycloidal gearboxes for various applications. The project starts with a comprehensive literature review to understand the principles, benefits, and challenges associated with cycloidal gearing. Utilizing this information, a thorough design process is conducted, including CAD modeling and finite element analysis (FEA) for optimization. Special focus is placed on the design of the cycloid disk and pins to ensure efficient power transmission and minimal wear. After the design phase, the prototype is manufactured using precision machining techniques. Rigorous testing is performed to evaluate its performance characteristics, including torque transmission efficiency, speed variability, and noise levels. Comparative analyses with conventional gear systems are conducted to highlight the unique advantages of the cycloidal design. The findings of this project contribute to the advancement of cycloidal gearbox technology, offering valuable insights into their practical implementation and performance capabilities. Additionally, the prototype serves as a foundation for further research and development in the field of mechanical power transmission systems

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Cycloidal Gearbox, Speed Reduction, Cycloidal Gearing System, Gear Design, High Torque Transmission, Gearbox Manufacturing, CAD Modeling, Cycloid Disk, Precision Machining, Power Transmission Efficiency, Gearbox Optimization, Gearbox Testing, Noise Reduction, Comparative Analysis, Mechanical Power Transmission.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Predicting future sales accurately is crucial for businesses to optimize inventory management, plan marketing strategies, and enhance overall profitability. In this paper, we propose a comprehensive analysis of predictive sales analytics for variable timeframes utilizing machine learning models, specifically XGBoost, Linear Regression, Random Forest, and Long Short-Term Memory (LSTM) networks. Through empirical evaluation and comparative analysis, we demonstrate the efficacy of XGBoost in forecasting sales for different timeframes, namely daily, weekly, and monthly. Our findings highlight the superior performance of XGBoost in terms of accuracy and robustness, making it an ideal choice for businesses seeking reliable sales predictions across diverse temporal scales.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Predictive analytics, Sales forecasting, XGBoost, Random Forest, Linear Regression, LSTM, Variable timeframes, Streamlit.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The rapid advancement of intelligent transportation systems (ITS) has necessitated the development of efficient and accurate methods for accident detection and impact evaluation. This review paper examines the latest image processing approaches utilized in the detection and analysis of traffic accidents. We explore a variety of techniques, including machine learning algorithms, deep learning models, and traditional computer vision methods, assessing their effectiveness in real-time accident detection, severity estimation, and post-accident analysis. The paper discusses the strengths and limitations of each approach, highlighting key innovations and their practical applications within ITS. Additionally, the review addresses the integration of image processing with other sensor technologies, such as LiDAR and radar, to enhance the reliability and accuracy of accident analysis. Current challenges, including data quality, computational demands, and implementation in diverse traffic environments, are also considered. Finally, we outline potential future research directions aimed at improving the robustness and scalability of image processing techniques for comprehensive accident impact evaluation. This review serves as a valuable resource for researchers and practitioners seeking to advance the field of traffic accident analysis through image processing innovations.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

accident detection, impact evaluation, image processing, machine learning (ML).

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The rapid spread of COVID-19 has prompted urgent research efforts to develop effective diagnostic tools for timely identification and management of the disease. Chest X-ray imaging has emerged as a valuable modality for detecting COVID-19 pneumonia, offering a non-invasive and widely available means of screening and diagnosis. Deep learning models, particularly convolutional neural networks (CNNs), have shown promising results in automated detection of COVID-19 from chest X-ray images. This review paper provides a comprehensive overview of the current trends and future perspectives in the application of deep learning models for COVID-19 detection from chest X-ray images. We systematically analyze the literature to highlight the evolution of deep learning techniques, the performance of different CNN architectures, and the challenges and limitations encountered in COVID-19 diagnosis. Additionally, we discuss emerging trends, such as transfer learning, ensemble methods, and multimodal approaches, and their potential impact on improving the accuracy and reliability of COVID-19 detection. By synthesizing existing research findings and identifying areas for future exploration, this review aims to provide valuable insights for researchers, clinicians, and policymakers involved in combating the COVID-19 pandemic through advanced diagnostic strategies.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

COVID-19, convolutional neural networks (CNN), Chest X-ray, Deep learning.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The early and accurate detection of brain tumors is crucial for effective treatment and improved patient outcomes. Image segmentation plays a vital role in isolating tumor regions from medical imaging modalities, and advancements in computer vision have significantly enhanced this process. This review paper provides a comprehensive overview of the latest image segmentation techniques for brain tumor detection using OpenCV, a popular open-source . Image segmentation library. We delve into various methods, including thresholding, edge detection, region-based segmentation, and machine learning approaches integrated with OpenCV functionalities. Additionally, we discuss the effectiveness, limitations, and computational efficiency of these techniques. By analyzing recent studies and developments, this review paper aims to highlight the strengths and weaknesses of different segmentation methods, offering insights into their practical applications and potential future improvements. Our review underscores the importance of continued innovation in image processing algorithms and the integration of advanced machine learning models to enhance the accuracy and reliability of brain tumor detection.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

OpenCV, brain tumors, Image segmentation, Image segmentation, machine learning.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The present study entitled "In vitro propagation of Insulin plant (Costus pictus)" was conducted in the tissue culture laboratory for rapid multiplication of Insulin plant to produce large number of sprouting buds and disease free plantlets. In vitro propagation was done by using nodal segments as explants which were initiated on Murashige and Skoog (1962) medium supplemented with different concentrations of BAP in combination with IAA. After the seven weeks of initiation maximum number of sprouting bud was obtained in medium supplemented with 1.5mg/l BAP + 1.0mg/l IAA with survival percentage 75%. Buds or shoot lets were regenerated from nodal ex plants through shoot proliferation. The best response of rooting obtained on MS supplemented with 1.5mg/l IBA + 1.0mg/l IAA + 0.5gm/l AC. The well rooted plantlets transferred to green house condition for primary hardening.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

in vitro propagation, Nodal segment, BAP, IBA, and IAA.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study investigates the impact of the Ayushman Bharat health scheme on dialysis patients in Kashmir, a region characterized by tough terrain and hilly landscapes. Dialysis, a crucial treatment for patients with end-stage renal disease (ESRD), poses significant challenges in regions with limited healthcare infrastructure and economic constraints. The Ayushman Bharat scheme, introduced in 2018, aims to provide financial protection and improve healthcare access for economically vulnerable populations in India. This research examines how the scheme has influenced the accessibility and affordability of dialysis services, the financial burden on patients, and their overall health outcomes. A mixed-methods approach was employed, combining quantitative data from structured surveys with qualitative insights from semi-structured interviews. The study sample comprised 150 dialysis patients from various healthcare facilities in Kashmir, including government hospitals, private clinics, and specialized dialysis centers. Data analysis involved statistical evaluation of survey responses and thematic analysis of interview transcripts. The results indicate a significant improvement in the accessibility of dialysis services post-Ayushman Bharat implementation. Patients reported fewer logistical and financial barriers to receiving regular dialysis treatments. The financial burden on patients has notably decreased, with many reporting substantial reductions in out-of-pocket expenses due to the scheme's coverage. Improved financial access has translated into better health outcomes, with patients experiencing fewer complications and a higher quality of life. Despite these positive findings, certain challenges persist. Some patients continue to face difficulties in navigating the scheme's administrative processes, and logistical challenges related to the region's geography still impact healthcare access. The study underscores the importance of addressing these issues to fully realize the scheme's potential benefits. In conclusion, the Ayushman Bharat scheme has had a profound positive impact on dialysis patients in Kashmir, enhancing access to essential medical services and alleviating financial strain. The findings highlight the critical role of comprehensive health coverage programs in improving healthcare outcomes in challenging environments. Policymakers are encouraged to consider these insights for future healthcare initiatives aimed at vulnerable populations in similar regions.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Chronic kidney disease (CKD), Dialysis, Ayushman Bharat scheme.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study investigates workplace hazard reduction in the MDV weld shop through the implementation of engineering controls. A comparative analysis of various hazard reduction methods is conducted, focusing on key performance evaluation parameters such as incident rates, risk reduction percentages, safety compliance scores, and training effectiveness indices. The proposed method emphasizes the integration of engineering controls to mitigate occupational risks and enhance workplace safety. Through empirical research and data analysis, the study demonstrates the superiority of the proposed method over alternative approaches, highlighting its effectiveness in reducing workplace hazards and protecting employee well-being. The findings underscore the importance of proactive safety measures and engineering interventions in mitigating occupational risks and promoting a culture of safety in industrial environments. By providing evidence-based insights into hazard reduction strategies, this study contributes to the advancement of occupational safety and health management practices. The implications of the findings extend to practitioners, policymakers, and researchers involved in promoting workplace safety and mitigating occupational risks. Overall, the study enhances our understanding of effective hazard reduction strategies and underscores the importance of proactive safety measures in ensuring a safe and healthy work environment.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Compliance, Controls, Engineering, Hazard, Occupational, Performance, Reduction, Safety, Training, Workplace.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

FaceCognizance, powered by machine learning (ML), revolutionizes national security with precise facial recognition and advanced threat assessment. Its ability to handle vast datasets enhances decision-making and ensures real-time adaptation to evolving threats. This proactive approach leads to faster reactions during critical situations, minimizing harm and setting a standard for responsible technological integration. However, ethical considerations, such as privacy and algorithmic biases, remain crucial. Achieving a balance between civil liberties and security measures is imperative to maintain public confidence. FaceCognizance not only advances surveillance but also serves as a benchmark for ethical ML use, reaffirming its role in shaping the future of national security.1

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

FaceCognizance's, surveillance, security, identification, machine learning, national security, public safety, facial recognition, ethical considerations, privacy concerns, algorithmic biases, data security, innovation, responsible technology integration.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

ABSTRACT The goal of this research is to create a herbal soap by using powdered Azadirachta indica (Neem) and Ocimum tenuiflorum (tulsi) extracts. With Ayurvedic cosmetics becoming more and more popular due to its natural ingredients this composition aims to incorporate botanical elements that are strongly ingrained in traditional medicine practices, with minimum adverse effects. Renowned for its therapeutic qualities, neem plays a significant role. It is notable for its anti-inflammatory, antihyperglycemic, antimalarial, and antibacterial qualities. The study employs a thorough methodology to investigate the effects of several Neem leaf extracts. The herbal soap is meticulously crafted, incorporating Neem and Tulsi, demonstrating specific efficacy against dermatophytes, while Tulsi showcases remarkable antiviral properties. This research serves to underscore the vast potential inherent in herbal formulations, shedding light on the manifold benefits of Neem and Tulsi and their transformative applications in skincare products.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Keywords-herbal neem soap

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This project explores the development of a semi-automated Mini Land Cultivation Machine utilizing a 99cc 4-S Champion two-wheeler engine. Designed to minimize manual labour in ploughing operations, this machine integrates basic mechanical components to overcome the lack of electricity and high costs associated with fully automated sys-tems. By employing a gasoline-powered engine coupled with motors and power transmission equipment, the design aims to enhance efficiency in various crop cultivation environments. The feasibility study focuses on designing and fabricating a cost-effective ploughing solution that addresses the challenges faced by rural agricultural practices. This approach ensures accessibility and ease of use, striving to reduce manpower while maintaining affordability.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Semi-automation, Fabrication, Cost-effective, Cultivation, Transmission.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

A study on Relationship between Talent Management and Organizational Performance Dr. Smita Kalokar Assistant Professor Ranibai Agnihotri Institute of Computer Science And Information Technology, Wardha Email: Sakalokar@gmail.com Prof. Amol Mashankar Assistant Professor Datta Meghe Institute of Higher Education and Research, Wardha Email: amol369mashankar@gmail.com Abstract Abstract: Organizations all over the world have realized that the success of their businesses largely depends upon the talents of people. Talent management solutions are becoming more and more vital to the growth and profitability of today's organization. Why? Because companies invest a tremendous amount of money in their employees. The expenses associated with soliciting, acquiring, training, promoting, and retaining staff members can take up a huge portion of any corporate budget. But, as the workforce continues to be viewed as an increasingly strategic asset, these costs are all considered to be money well spent. It is also needed for the both to improve company performance and also to boost employees' well-being. As organization continue to pursue high performance and improved results through Talent Management practices. The performance of every organization depends on the performance of their employees. The purpose of the study is to find out to find out the relationship between Talent Management and organizational performance. The objectives were achieved through a descriptive study. Keywords: Talent Management, Talent Management Practices, Organizational Performance

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Talent Management, Talent Management Practices, Organizational Performance

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Science fiction, often abbreviated as sci-fi, is a genre of speculative fiction that explores imaginative and futuristic concepts that are often based on scientific principles, discoveries, and technologies. It is a genre that allows authors and creators to envision and explore alternate realities, future societies, advanced technologies, and the consequences of scientific advancements. Science fiction can be found in various forms, including literature, film, television, comics, and video games. Here are some key elements commonly found in science fiction - advanced technology, space exploration, alternate realities, dystopian and utopian societies, alien life: Extraterrestrial life forms, time travel, cyberpunk, post-apocalyptic worlds, AI and Robotics, ethical and philosophical questions. Science fiction in Indian English literature has a growing presence and is gaining recognition for its unique blend of Indian culture, traditions, and futuristic concepts. While Indian literature is rich in mythology, folklore, and historical narratives, modern Indian authors have embraced science fiction as a means to explore contemporary and future-oriented themes. This paper will try and chart the growth of Science Fiction in Indian English Literature by analyzing the works of six prominent Sci-Fi writers in IEL.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Science Fiction, Indian English Literature, Extraterrestrial life forms, Futuristic Concepts, Advanced Technology

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The purpose of this research paper is to obtain access to the teacher empowerment of secondary school teachers in relation to their gender. For the conduct of the research, the Descriptive survey method was used. The Teacher Empowerment Scale (2019) which was created by Dr. Manju N.D. and Dr. G. Sheela is used to gather data from teachers in secondary schools. Samples of 100 secondary school teachers from the Prayagraj City were randomly chosen for this research. To analyze the results, statistical techniques such as Mean, SD, and t-test were used. The result showed that there is no significant difference between female and male high school teachers.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Teacher Empowerment, Secondary School Teachers

  License

Creative Commons Attribution 4.0 and The Open Definition