Volume 13 | Issue 4 |

 Abstract

- Railway level crossings are critical points where road traffic intersects with railway tracks, often leading to accidents due to human error or malfunctioning systems. This review paper explores existing technologies and approaches for enhancing safety at these crossings, focusing on automated systems for real-time obstacle detection and gate management. Various sensor-based solutions, including infrared, ultrasonic, and image processing techniques, are examined for their effectiveness in detecting obstacles such as vehicles, pedestrians, or debris. These systems aim to alert both road users and trains through alarms, flashing lights, and barrier controls to prevent collisions. Additionally, the review discusses automation of level crossing gates using GPS or track-based sensors to open and close gates without human intervention. Such automation reduces reliance on manual operations and minimizes the risk of errors, improving overall safety. The paper highlights the potential for integrating these systems into existing infrastructure, offering a cost-effective approach to modernizing railway crossings. Through the review of current technologies and studies, this paper aims to provide insights into the future development of automated, real-time safety systems at railway intersections.

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 Keywords

Safety system, Level crossing system, Real-time Obstacle Detection, train

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Creative Commons Attribution 4.0 and The Open Definition

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This paper presents the development of CreativeNexusAI, a novel platform for multimodal content generation powered by Large Language Models (LLMs). The project aimed to integrate theoretical knowledge with practical application, focusing on the deployment, scalability, and optimization of LLMs. The methodology involved a phased approach, starting with foundational research on LLM architectures like BERT and GPT, progressing to practical implementations with tokenization, vector databases, and Retrieval-Augmented Generation (RAG). We utilized Google Gemini and Hugging Face APIs for text, image, video, and meme generation, integrated within a modular architecture using FastAPI and MongoDB. Results demonstrate the platform's capability to generate context-aware, high-quality content across various media types, with preliminary user testing (n=30) showing 89% satisfaction with blog content quality and 83% with image-text coherence. Response times averaged 3.4 seconds for text generation and 4.8 seconds for image creation, demonstrating the system's efficiency. This research contributes to the field by providing a practical demonstration of how advanced AI techniques can be applied to real-world content creation, offering insights into the scalability and efficiency of LLM-driven platforms.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Content generation, Large Language Models, Multimodal AI, CreativeNexusAI, Natural Language Processing, Vector Databases, Retrieval-Augmented Generation

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Creative Commons Attribution 4.0 and The Open Definition

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Harpreet Kaur Research Scholar, Faculty of Nursing, DBU, Mandi Gobindgarh, Punjab Sukhmanpreet Kaur Associate Professor, Faculty of Nursing, DBU, Mandi Gobindgarh, Punjab ABSTRACT: Background-Critical care nurses are playing an essential role in care of patients of intensive care units. They are frequently involved in taking ABG but for analyzing the report they regularly dependent on doctors. They need to be aware regarding the Interpretation. Objective-To assess the knowledge of critical care nurses regarding ABG Procedure and ABG analysis interpretation. Material and Method-A descriptive design was conceded for the present study. Total 200 Critical care nurses were working different critical care units were enrolled. Non randomized convenient sampling technique was used. A pre validated self-structured questionnaire including of 10 questions related to knowledge about the ABG procedure and 20 ABG analysis interpretations was developed and administered to assess the knowledge of critical care nurses. Results- The majority of the Critical Care Nurses are between 20-30 years i.e. 74%, the next main group is 31-40 i.e.91% of the critical were nurses are female (61% of the working were GNM, 27% were B.Sc. and 9% were P.B.BSc and 3% were M.Sc. Nursing A significant majority have 0-5 year experience 84%- 59% of them had knowledge about Allen Test. 70% of critical care nurses correctly knew about pH normal range 38 percent knew about respiratory acidosis and only 20% nurses were able to solve the equation of ABG interpretation. According to category the Good, Average and poor. The majority of participants (88%) score in the "Poor" category range i.e. (0-49), with 10% scoring in the "Average" range i.e. (50-79) and only 2% achieving a "Good" range score i.e. (80-100) This indicates that critical care nurses have lower knowledge of ABG analysis interpretation. Conclusion-Critical care had gap in ABG procedure and ABG Analysis interpretation knowledge. They need to be taught regarding ABG procedure and ABG Analysis interpretation.

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Key Words -Critical care nurses, ABG Analysis interpretation.

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Six distinct colonies were isolated from the intestine of Mickey Mouse molly Xiphophorus maculatus through serial dilution, pour plate, spread plate and streak plate methods. Based on the biochemical tests, the isolated bacteria were S1 (Leuconostoc sp.,) S2 (Bacillus sp.,) S3 (Lactobacillus sp.,) S4 (Paracoccus sp.,) S5 (Lactobacillus sp.,) and S6 (Bacillus sp.). Enzymatic productivity (Amylase, Protease and Lipase) of the isolated bacteria were carried out. Mass multiplication of Leuconostoc sp., Bacillus sp., Lactobacillus sp., Paracoccus sp., Lactobacillus sp., Bacillus sp., was done in nutrient broth. Antibacterial activity of the intestinal bacteria of Mickey Mouse Molly was carried out with the help of selective media along with a commercial antibiotic (Streptomycin).Five different feeds having different bacteria such as control ( without bacteria) Feed I(1ml of Bacillus sp), Feed II (1 ml of each Bacillus sp., and Lactobacillus sp.,), Feed III (Bacillus sp., Lactobacillus sp., Paracoccus sp.,), Feed IV (1 ml of each Bacillus sp., Lactobacillus sp., and Paracoccus sp.,)Feed V (1ml of each Bacillus sp., Lactobacillus sp., Paracoccus sp., and Leuconastoc sp.,) were prepared. Feed utilisation parameters of Mickey Mouse Molly were estimated after 21 days. Based on the antibacterial test, the Bacillus sp., Lactobacillus sp., Paracoccus sp., and Leuconostoc sp. have higher inhibition. The feed consumption, feed conversion efficiency and growth, assimilation, metabolism Gross and net growth efficiency were higher in Feed V.

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Intestinal bacteria, biochemical, antibacterial, growth, Micky mouse molly

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Mahilao ka sashkt evam atamnirbharta mein gramin mahila vikas yojana ka mahtav ek adhyayan

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Mahilao ka sashkt evam atamnirbharta mein gramin mahila vikas yojana ka mahtav ek adhyayan

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Creative Commons Attribution 4.0 and The Open Definition

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This study aims to benchmark the financial performance of two major players in the Indian power sector Tata Power Limited and Adani Power Limited using key financial analysis over a year. The power sector in India plays a vital role in economic development and understanding the financial health of its leading companies is essential for investors, stakeholders and policymakers. The research employs a comparative analytical methodology focusing on various financial parameters. Analysis is used to examine the growth patterns and performance consistency of both companies.The findings reveal significant differences in financial strategies and risk management approaches adopted by Tata Power and Adani Power. While one company demonstrates stability and consistent returns, the other reflects aggressive expansion backed by higher leverage. This benchmarking offers a clear picture of each company's financial strengths and vulnerabilities, thus helping in informed decision-making for stakeholders.The study concludes with key insights and suggestions to enhance financial performance and maintain sustainable growth in a competitive and evolving energy market.

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Tata Power, Adani Power, Financial Performance, Ratio Analysis, Trend Analysis

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Aim and Objective: To assess the knowledge regarding teenage pregnancy among adolescent girls in selected school, Coimbatore. Materials and Methods: A descriptive study was adopted to assess the knowledge among adolescent (13-17 years) school students (40 Samples) studying in 9th standard in school at Ashokapuram Village, Coimbatore who filled the inclusion and exclusion criteria. Convenient purposive sampling technique used to select the samples. Tool was prepared and validity of the tool was obtained from Subject experts. Descriptive and inferential statistics was administered to assess the knowledge among adolescent (13-17 years) school students. Results: The study finding revealed that among 40 samples, majority of the adolescent 36 (90%) are in the age group 16-17, 4 (10%) are in the age group of 13-15 years. Conclusion: The study results revealed that most of the adolescent girls possess a basic understanding of teenage pregnancy, there remain sufficient significant gaps in knowledge regarding its causes, consequences and method of prevention

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Keywords: Teenage, Pregnancy, adolescent.

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A smart grid includes a variety of intelligent control systems for power generation and also for increasing the energy efficiency of the system. These systems include smart power converters, but also renewable energy and highly efficient resources. Multilevel inverters are considered modern and basic elements of high voltage power supply systems; however, the failure of electronic power components strongly affects the reliability of the entire system. The important goal in defining and dimensioning of smart grids is the measuring and determining of the boundary conditions and operating regimes of the power components. This paper presents an innovative technique for the fault detection of power components for a three-phase multilevel inverter, which is one of the typical components of a smart grid. Single, double and triple switch failures can be diagnosed by this method. The detection mechanism is based on the analysis of the stator current, with the possibility to differentiate between the simple and multiple switching failures. Also, these models can achieve the harmonic analysis to verify the system correctness and can simulate different operational scenarios to test the functioning of the control system.

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Simulation and Fault Detection Techniques for Multilevel Inverters used in Smart Grids

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This abstract highlights about Vehicle headlights have long been a critical safety component, but their technology has remained relatively stagnant despite advancements in smart cars. The issue of blindingly bright headlights causing accidents persists. The intense glare from high beams poses risks, leading to temporary blindness and potentially fatal collisions.To address this, we propose an innovative automatic headlight intensity control system. Our prototype employs Light Dependent Resistors (LDR) to detect oncoming vehicles and adjust headlight intensity accordingly, dimming them to reduce glare and enhance safety. This system eliminates the need for manual adjustments by drivers, significantly reducing the risk of accidents caused by dazzling headlights. According to the regulations of the Indian Roads and Transport Council, vehicles should primarily use low-intensity lights. However, drivers often misuse high beams due to poor visibility with low beams. Our automatic dipper system intelligently manages headlight intensity, optimizing visibility while ensuring compliance with regulations.

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 Keywords

SMART VEHICLE HEAD LIGHT AUTO SWITCHING AND INTENSITY CONTROL

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Train collisions pose a significant threat to railway safety, often resulting from signal failures, human error, or poor communication. This research presents a comprehensive solution integrating RFID technology with ultrasonic sensors, GSM modules, ESP32 microcontrollers, and motor driver systems to create an automatic train collision prevention system. The proposed system identifies train positions using RFID, detects proximity threats via ultrasonic sensors, communicates real-time alerts through GSM, and controls train movement using motor drivers--all orchestrated by an ESP32 controller. The design emphasizes cost-effectiveness, scalability, and real-time responsiveness, particularly suited for developing countries

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

RFID Technology, Ultrasonic Sensor, ESP32, Automatic braking system

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Creative Commons Attribution 4.0 and The Open Definition