Volume 12 | Issue 5

 Abstract

Transmission shafts constitute pivotal components in mechanical systems, responsible for transferring power from the engine to various mechanisms. The integrity and longevity of these systems hinge on the robustness of transmission shafts, necessitating comprehensive stress analysis. This paper presents an in-depth exploration into stress analysis methodologies applied to transmission shafts. Analytical, numerical, and experimental approaches are scrutinized, with a focus on their efficacy, limitations, and advancements. Material properties, geometric configurations, loading conditions, and manufacturing intricacies are dissected to discern their influence on shaft behavior. Through this comprehensive examination, this paper endeavors to contribute to the advancement of transmission shaft design, ensuring reliability and performance across diverse engineering applications.

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This paper presents an in-depth exploration into stress analysis methodologies applied to transmission shafts

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For decades, farmers have been using biological or chemical fertilizers to enhance crop production and soil fertility. They also play a crucial role in meeting food requirement. To meet the demand for fertilizers, the fertilizer industry emerged in India. The Indian fertilizer industry, established in 1906, has consistently accelerated its growth over the years. Every nutrient requirement of the soil is either fulfilled domestically or imported to meet demands. This industry encompasses private, public, and cooperative sectors, each making significant and collaborative contributions to the agricultural and economic development of India. This study primarily focused on the distinctive contribution of cooperative sector in conventional form of fertilizer and development of Nano fertilizer, which effectively alleviate logistical burdens.

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Fertilizer, Indian Fertilizer industry, Nano fertilizer, Cooperative sector, Public sector, Private sector

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ABSTRACT Background Unintentional and irrational usage of oral/parenteral steroids is the root cause of chronic iatrogenic cushing's syndrome. Case presentation Here, we present a iatrogenic cushing's syndrome case which is caused by longterm exposue to both parenteral and oral intake of steroids. Conclusion An evidence of constant use of over-the-counter medications is required to identify the source of exogenous glucocorticoids in iatrogenic Cushing's syndrome.

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Cushing's syndrome, steroids, cortisol

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This research paper proposal delves into the significant role played by Amar Singh Jhabal in the Gurdwara Reform Movement, a crucial chapter in Sikh history during the early 20th century. He was born on 1888 in Punjab, India and his evolution from a police sub-inspector to a prominent leader underscores his unwavering commitment to Sikh rights and religious freedom. This proposal provides an overview of Amar Singh Jhabal's background, education, and his instrumental involvement in various aspects of the Gurdwara Reform Movement. It emphasizes his vocal opposition to the confiscation of kirpans, his efforts in mobilizing the Sikh community, and his advocacy for reform in the Gurdwara management. His personal sacrifices, including imprisonment, and his pivotal contributions to the enactment of the Sikh Gurdwara Act, 1925, a landmark achievement for the Sikh community in their quest for religious autonomy and Gurdwara management under the Shiromani Gurdwara Parbhandhak Committee. His enduring legacy in Sikh history and his integral role in the broader struggle for civil and religious liberties in India.

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Akhand Path, Gurdwara, Gur Asthan, Kirpan, Central Sikh League, Tankhaiya, Gurdwara Guru Kotha, Guru ka Bagh Morcha, Gurmata,

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The importance of artificial intelligence (AI) in forming public relations (PR) strategies within digital marketing has grown in the age of digital transformation. In order to better understand AI's revolutionary impact on audience engagement, content development, data analytics, and crisis management, this study examines the various effects of AI on PR tactics. The way PR professionals engage with audiences has changed dramatically with the introduction of AI technology. Artificial Intelligence (AI) facilitates more meaningful and focused contact with customers by using complex algorithms. PR professionals may examine enormous volumes of data to determine audience preferences, attitudes, and behaviors by utilizing machine learning algorithms. This allows them to create customized message that appeals to particular groups of people. The importance of artificial intelligence (AI) in forming public relations (PR) strategies within digital marketing has grown in the age of digital transformation. In order to better understand AI's revolutionary impact on audience engagement, content development, data analytics, and crisis management, this study examines the various effects of AI on PR tactics. The way PR professionals engage with audiences has changed dramatically with the introduction of AI technology. Artificial Intelligence (AI) facilitates more meaningful and focused contact with customers by using complex algorithms. PR professionals may examine enormous volumes of data to determine audience preferences, attitudes, and behaviors by utilizing machine learning algorithms. This allows them to create customized message that appeals to particular groups of people. Furthermore, in the PR industry, AI technologies have completely changed crisis management tactics. Organizations may protect their brand and sustain stakeholder trust by promptly identifying and addressing potential crises with real-time monitoring systems that are equipped with AI-driven sentiment analysis. PR experts can determine the importance of a crisis, pinpoint important stakeholders, and adjust their communication plans by using sentiment analysis of news stories and social media conversations. Nevertheless, there are moral and legal issues with using AI into PR tactics. Ethical rules and careful thought are necessary for addressing concerns related to data privacy, algorithmic bias, and the legitimacy of content created by artificial intelligence. PR pros need to be on the lookout for ways to ensure accountability, equity, and transparency in their AI-driven projects as the technology develops.

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Keywords: Artificial Intelligence (AI), Machine learning (ML), Digital Marketing (DM)

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Potholes are areas of road surface that have cracked, worn away, and eventually formed a hole. Potholes make a ride bumpy and potentially dangerous. They can damage vehicle tires and even affect the alignment of a vehicle's wheels. With advancing urbanization, roads serve as a most important way of communication. But the increasing potholes on the roads pose a bigger danger towards public safety. Identifying and locating road potholes promptly has become a major challenge for urban construction. To address the need for improved infrastructure management, the aim of the project is to propose a pothole detection and alert system using the YOLOv8 object detection algorithm on urban road images. To enable accurate segmentation of fine-grained features, this project optimized the PothNet, which enables the segmentation head to generate high-quality masks for more accurate prediction. The proposed system serves a dual purpose, providing timely alerts to both car drivers traversing the same route and municipal authorities responsible for road maintenance. By leveraging intelligent algorithms, the system not only detects potholes but also identifies road segments in urgent need of repair. This holistic approach helps address imbalances in infrastructure maintenance efforts across cities, promoting a more equitable distribution of resources. The intelligent Pothole Detection and Alert System contribute significantly to enhancing road safety and fostering a smoother driving experience.

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YOLOv8,PothNet,CNN,Deep Learning.

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The cornerstone of every democratic society in existence is freedom of speech. At its core, free speech is the ability to communicate openly and to receive information from others. It is regarded as the main requirement for autonomy. It is regarded as the "mother" of all other freedoms and one of the most important civil liberties that is shielded from restriction or repression by the government1. This fundamental right to freedom of speech and expression is guaranteed by Article 19(1)(a) of the Indian Constitution. Article 19 of the Universal Declaration of Human Rights (UDHR) defines freedom of expression as a human right, and the International Covenant on Civil and Political Rights (ICCPR) states that the right to free speech is recognised under international human rights law. Since the right of freedom of expression is not unqualified, certain restrictions are placed on it under Article 19(2). Nevertheless, law is the only means of restricting the right to free expression. Within the scope of this freedom is the ability to publish, market, and spread information.

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Constitution, Fundamental Rights, Freedom of Speech, Democracy, Digital India Act

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India is a diverse country. Cities are at the heart of urban governance. They act as the first point of reference for its citizens. There are many challenges to urban governance in India, especially in a city like Mumbai. Taking some initiatives toward reforming this sector is a need of the hour. Municipal leadership needs to be stronger and more efficient enough to tackle the issues of governing the city. The 74th Constitutional Amendment Act took some measures to reform the urban local self-governing institutions in India. The constitution has provided a broad framework to establish urban local bodies in each state. It has not been mentioned the details of the structure of urban governance to be followed by each state, the tenure of the mayor, qualifications, the election method to be followed to choose the mayor of a city, and the like. Therefore, these characteristics differ from state to state. The recent debate regarding municipal leadership was whether to have the direct or indirect election of a mayor. This article focuses on the analysis of the election method for a mayor in the city of Mumbai. It talks about the merits and demerits of both methods. This article tries to assess whether the direct election method has any effect on the working pattern of a mayor and whether it is constitutional to adopt it in India.

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Urban Local Bodies, 74th Constitutional Amendment Act, Municipal Corporation of Greater Mumbai, Election of a Mayor, Direct Election, Indirect Election, Devolution of Powers, urban reforms.

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The College Enquiry Chatbot is an innovative artificial intelligence (AI) application designed to streamline and enhance the communication process between prospective students, current enrollees, and the college administration. This chatbot leverages advanced Natural Language Processing (NLP) algorithms to understand and respond to user queries in real-time, providing a user-friendly interface for individuals seeking information about the college.Key features of the College Enquiry Chatbot include its ability to engage in natural language conversations, accommodating both text and speech interactions across multiple platforms such as websites and messaging apps. The chatbot excels in task automation, efficiently handling inquiries related to admission procedures, course details, faculty information, campus facilities, and more. With its 24/7 availability, the chatbot ensures that users receive instant responses, catering to diverse time zones and schedules. The system incorporates machine learning techniques to continuously improve its performance based on user feedback and evolving patterns of inquiries. Through integration with college databases and information systems, the chatbot ensures the accuracy and up-to-date nature of the information provided.The College Enquiry Chatbot represents a modern and efficient solution for addressing the informational needs of individuals interested in the college. By offering a personalized and responsive experience, the chatbot aims to optimize user satisfaction, streamline administrative processes, and contribute to a more efficient and user-centric communication framework within the educational institution.

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Chatbot, College Enquiry, Realtime, NLP

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A two-wheeler's frame is a crucial component since it supports the weight of the bike. It must therefore be robust enough to withstand stressors such as shock, twist, vibration, and others. Different kinds of failure in vehicle chassis are caused by both static and dynamic loading moments. Natural frequency, damping, and mode shapes are examples of intrinsic structural characteristics that can be discovered through 3D printing experiments. The aim of this research is to extend the lifespan of two-wheeler bike chassis by the use of 3D printing experiments. Our goal is to lessen the impact of these vibrations because, although undesirable, vibration cannot be completely eliminated

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To improve the life of frame

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Abstract : Integrating IoT technology has been crucial in modern healthcare for improving patient care and monitoring. This research presents a novel ICU patient monitoring system that utilizes the internet of things (IoT) to continuously monitor vital signs like temperature, humidity, pulse rate, and blood pressure in real-time. The system's data processing and collection is powered by Arduino microcontrollers, and its storage and analysis is made easy by the sophisticated cloud-based platform ThingSpeak. Medical practitioners may see and evaluate patient data in real-time using ThingSpeak's powerful analytics features. When anything out of the ordinary happens with your vitals, you may set up alerts and notifications to let the doctors know. In order to improve healthcare delivery efficiency and allow for remote monitoring, the system offers a user-friendly interface that can be accessed by online or mobile apps.

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IOT, Thingspeak, Arduino microcontrollers, Remote monitoring, Cloud-based platform, Healthcare delivery efficiency.

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BACKGROUND: Nurses engage in various activities from the time of a patient's admission to his or her discharge from the hospital, helping patients to meet their needs that also include the recording and reporting. Each of the activities done by the nurses and the condition of the patient should be documented properly as authentic and crucial evidence. Current health care system required that documentation ensures continuity of care, furnishes legal evidence of the process of care and supports evaluation of quality of patient care. National Accreditation Board for Hospitals and Healthcare Providers (NABH) is a constituent board of Quality Council of India (QCI), set up to establish and operate accreditation and other allied programs for healthcare organizations. The mission of NABH is to operate accreditation and allied programs in collaboration with stakeholders focusing on patient safety and quality of healthcare by adopting various national and international best practices. NABH is an Institutional Member as well as a Board member of the International Society for Quality in Health Care (ISQua) and on the board of the Asian Society for Quality in Healthcare (ASQua). Patient safety can be evaluated by mapping adverse events that occur in healthcare units. Studies done by Panesar et al. in 2015 have shown that 1-24 adverse incidents occur during every 100 consultations in the primary care context. A link between patient safety and inadequate documentation has previously been reported by studies examining documentation and adverse events in primary care. Andersson et al. in 2018, examined serious adverse events reports submitted by nurses in Swedish nursing homes to the Health and Social Care Inspectorate and found that a "lack of competence" and "incomplete or lack of documentation" were the two most common factors that contributed to adverse events.

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KNOWLEDGE AND ATTITUDE REGARDING NABH DOCUMENTATION GUIDELINES AMONG NURSING STUDENTS IN SELECTED NURSING COLLEGES, GUWAHATI, ASSAM: A DESCRIPTIVE STUDY

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Abstract Natural remedies are more acceptable in the belief that they are safer with fewer side effects than the synthetic ones. Herbal formulations have growing demand in the world market. The objective of this work is to formulate and evaluate a cosmetic preparation polyherbal face pack made from herbal ingredients. Kaoline, tragacanth, orange peel powder, neem powder, chandan powder, aloe juice powder, turmeric powder , Fullers earth and Cicer arientinum Powder were procured from the local market in dried, powdered and then passed through sieve no 80, mixed thoroughly prepared and evaluated for its organoleptic, physico-chemical and microscopical characters . The dried powder of combined form had passable flow property which is suitable for a face pack. Herbal face packs or masks are used to stimulate blood circulation, rejuvenates and help to maintain the elasticity of the skin and remove dirt from skin pores. It is a very good attempt to establish the herbal face pack containing different powders of plants. The advantage of herbal cosmetics is their non-toxic nature, reduce the allergic reactions and time tested usefulness of many ingredients. Thus in the present work, we found good properties of the face packs and further optimization studies are required on this study to find the useful benefits of face packs on human, use as cosmetic product.

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Keywords:- Cosmetic, Face Pack, Herbal, Ingredients, Natural Formulation.

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This project pioneers a novel method for human behavior recognition, introducing two innovative channel attention modules: the space-time interaction and depth separable convolution modules. Utilizing convolutional neural networks (CNNs), renowned for image and video processing, a multi-scale CNN approach segments behavior videos, applies low-rank learning for behavior information extraction, and integrates findings along the time axis for holistic comprehension. This method not only simplifies information extraction but also adapts flexibly to diverse network structures, enhancing recognition accuracy while minimizing computational complexity. Further, by amalgamating CNN, GRU, and Bidirectional algorithms, the model achieves superior accuracy with just 1000 parameters, outperforming existing algorithms. This hybrid approach optimizes training features, securing even higher accuracy in behavior recognition.

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Human Behaviour, CNN

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This project introduces a groundbreaking solution to the security vulnerabilities encountered by resource-limited Internet of Things (IoT) devices during software updates. Traditional methods are fraught with security risks and inefficiencies due to multiple data transfers. The proposed blockchain-based framework revolutionizes this process by leveraging Ciphertext-Policy Attribute-Based Encryption (CP-ABE) for cryptographic tasks, custom authorization policies for enhanced security, and smart contracts to ensure secure delivery and payment. By storing encrypted software update blocks across multiple IPFS nodes and recording their addresses on the blockchain, the system mitigates the risk of a single point of failure. This innovative approach not only guarantees secure, efficient, and auditable software updates but also significantly bolsters IoT device security compared to conventional methods.

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Blockchain, Ciphertext

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Pneumonia is the leading cause of death and morbidity in children, and early and accurate diagnosis is essential for timely intervention. In our project, we solve the challenge of separating chest and lung x-rays. To achieve this, we use the power of neural network (CNN) and state-of-the-art transformers. Our method involves the use of a pre-trained CNN model and Vision Transformer to extract complex features from X-ray images, allowing us to identify transformation patterns and defect. We carefully preprocessed the children's chest X-ray image database to ensure that the information was complete and balanced. We have implemented the most efficient and effective testing methods to reduce translation time and cost and improve early detection of childhood pneumonia. Our system is accurate and effective in classifying lung diseases in children; It demonstrates the potential of deep learning and visual interpretation to improve doctors' ability to quickly and accurately diagnose life-threatening diseases.

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Pneumonia , CNN, Vision Transformer, X-ray

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Since this study delves into the profound impacts of self-harm on individuals and economies, emphasizing the inadequacy of traditional statistics in tracking national trends. Introducing the innovative FAST framework, it harnesses social media data to forecast self-harm incidents. By training language models to discern mental health signals from online messages, this method transforms them into insightful time series data. Using machine learning regressors, the framework demonstrated superior forecasting accuracy. In a Thai case study, it surpassed conventional methods by over 40%. Additionally, incorporating the Decision Tree algorithm enhanced accuracy, reducing Mean Absolute Error compared to other algorithms. This research pioneers a transformative approach to predict nationwide self-harm trends and potentially forecast socioeconomic factors using social media analytics.

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Self-Harm, Social Networks

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as the project pioneers the use of open-source cyber threat intelligence (OSCTI) to bolster network security via a cybersecurity knowledge graph. This innovative graph streamlines access to a range of threat information, empowering informed decision-making. Leveraging attribution technology, the initiative detects and pinpoints advanced persistent threats (APTs) across diverse attack scenarios. Integrating cutting-edge knowledge graph technology with research on cyber threat attribution, the team introduces CSKG4APT, a robust cybersecurity platform. This platform harnesses ontology theory to craft an APT-centric knowledge graph model and deploys deep learning algorithms for knowledge extraction and updating. By introducing effective APT attack attribution techniques, the project amplifies network defense strategies, enabling proactive defense against rapidly evolving threats.

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Cybersecurity, deep learning algorithms

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Generative AI transforms healthcare by enhancing medical imaging, accelerating drug discovery, and enabling personalized medicine. Challenges include ethics, biases, and interpretability. Future directions involve customized models and regulatory frameworks. Responsible adoption is crucial for realizing generative AI's potential. In the realm of medical imaging, generative AI reconstructs high-resolution images from low-quality scans, aiding radiologists in precise diagnoses. Additionally, it synthesizes realistic images of organs and tissues, providing valuable visual information. Personalized medicine optimization involves analyzing patient data to tailor interventions. Disease progression prediction and individualized drug dosages improve patient outcomes. While generative AI holds immense promise, addressing ethical concerns, mitigating biases, and ensuring interpretability is essential. Collaborative efforts and thoughtful regulation will drive responsible adoption and transformative impact in healthcare.

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generative ai, artificial intelligence, machine learning,healthcare,medical,chat gpt

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The Internet of Things (IoT) has revolutionized healthcare by facilitating the development of innovative solutions for remote health monitoring. This paper introduces an IoT-based health monitoring system tailored to address the challenges of monitoring vital health parameters, particularly in rural or remote areas. The system incorporates a comprehensive array of sensors, including the MAX30100 for Blood Pressure Monitoring (BPM) and Blood Oxygen Saturation (SpO2), the DS18B20 temperature sensor for precise temperature monitoring, a DHT11 sensor for humidity measurement, and a GPS module for accurate location tracking. These sensors are seamlessly integrated into a dedicated PCB board, optimizing space and efficiency. Data collected from the sensors are wirelessly transmitted to a centralized server through the Blynk IoT platform, enabling real- time analysis and visualization. An intuitive user interface empowers healthcare providers and patients to monitor health parameters and receive alerts promptly in case of deviations from normal values. Rigorous testing and validation ensure the system's reliability and accuracy across various environmental conditions. This IoT-based health monitoring system holds significant promise for enhancing. The Internet of Things (IoT) has revolutionized healthcare by facilitating the development of innovative solutions for remote health monitoring. This paper introduces an IoT-based health monitoring system tailored to address the challenges of monitoring vital health parameters, particularly in rural or remote areas. The system incorporates a comprehensive array of sensors, including the MAX30100 for Blood Pressure Monitoring (BPM) and Blood Oxygen Saturation (SpO2), the DS18B20 temperature sensor for precise temperature monitoring, a DHT11 sensor for humidity measurement, and a GPS module for accurate location tracking. These sensors are seamlessly integrated into a dedicated PCB board, optimizing space and efficiency. Data collected from the sensors are wirelessly transmitted to a centralized server through the Blynk IoT platform, enabling real- time analysis and visualization. An intuitive user interface empowers healthcare providers and patients to monitor health parameters and receive alerts promptly in case of deviations from normal values. Rigorous testing and validation ensure the system's reliability and accuracy across various environmental conditions. This IoT-based health monitoring system holds significant promise for enhancing.

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 Keywords

iot devices, internet connectivity, cloud platform, data security, mobile or web application, data analytics, alerting mechanisam, integration with electronic health records.

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