Volume 13 | Issue 4 |

 Abstract

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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 Keywords

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

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

SMART VEHICLE HEAD LIGHT AUTO SWITCHING AND INTENSITY CONTROL

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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

 Abstract

AIDS stand for acquired immune deficiency syndrome. It is a disease of the human immune system caused by Human Immunodeficiency Virus AIDS was first report in the United State in 1981 and the HIV virus isolated in 1983.AIDS is the most advanced state of HIV infection A study was conducted using quantitative research approach, descriptive research design at Era College of Nursing, Hayat Institute of Nursing, Bora Institute of Nursing. The total sample size was 150 samples selected by convenience sampling technique. The data was collected by administering structured knowledge questionnaire. Finding related to assessment of knowledge on HIV/AIDS and its prevention among ANM 2nd year students, study finding reveals-26.7% ANM 2nd year students having adequate knowledge regarding HIV/AIDS and its prevention.73.3% ANM 2nd year students having inadequate knowledge regarding HIV/AIDS and its prevention.

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 Keywords

S.NO. ABBREVIATIONS EXPANDED FORM 1 AIDS Acquired Immune Deficiency Syndrome 2 HIV Human immunodeficiency Virus 3 ART Antiretroviral Therapy 4 ARV Antiretroviral 5 FSW Female Sex Worker 6 > Greater than 7 < Less than 8 STI/STD Sexually Transmitted Infection/Sexually Transmitted Disease 9 % Percentage 10 N Number of subjects 11 S.D. Standard Deviation 12 R Reliability 13 S Significant 14 ANM Auxiliary Nurse and Midwife

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This project introduces a Smart Shoe system paired with a Pocket Device that enables offline voice-based interaction using the ESP32 Dev Module. It incorporates wake word recognition via TensorFlow Lite Micro, local command processing using ESP-SR, and voice feedback through ESP-TTS, with audio delivered over Bluetooth--completely independent of internet connectivity or cloud services. The Pocket Device serves as the processing hub, interpreting data from sensors embedded in the shoe and providing instant auditory responses through connected wireless earphones. Designed for energy efficiency and compactness, the system enhances mobility, safety, and accessibility--particularly for individuals with visual impairments.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

ESP32, Smart Shoe, Pocket Device, Wake Word Detection, Offline Voice Assistant, Bluetooth TTS, ESP-SR.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Wireless sensor networks (WSNs) represent a sophisticated technology that faces challenges in managing numerous sensor nodes, data collection, transmission, and enabling actions across diverse applications, including tracking, surveillance, and forest fire detection, in both civilian and military sectors. This architecture is considerably more vulnerable to threats, hacking, and exploitation due to the distribution context, features of the sensor-equipped nodes, and their transmission procedures, in contrast to traditional networks. Consequently, an ideal strategy is necessary to provide protection in these networks while considering essential limits related to energy conservation and data protection. This research presents an energy-efficient secure multipath transmission method for grid-based wireless sensor networks (EESMPT). The proposed approach contains three phases. The initial phase involves the creation of the grid-based network. At this stage, a grid header was chosen via the multi-criteria optimization technique. The second stage involves the development of a lightweight cryptographic method for secure data transport. In the third stage, multiple paths are chosen to identify the quickest route for secure data transmission. The subsequent measures are employed to evaluate the efficacy of the suggested approach: energy usage, packet delivery ratio, and the count of active and dead nodes.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Wireless Sensor Network, Energy Efficient, Secure data transmission, Light weight cryptography, Multi-path transmission, Grid based network.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The rapid spread of fire in remote, elevated, or structurally compromised locations poses a substantial risk to both property and lives. Traditional firefighting approaches, while effective on the ground, are often restricted by physical and environmental limitations. This project presents the development of a cost-effective, manually operated Fire-Fighting Drone (FFD) capable of deploying fire extinguisher balls over targeted fire zones. The drone is equipped with a basic mechanical payload dropping mechanism triggered by a switch on the remote controller, enabling safe operation at a distance. Unlike autonomous UAVs, the proposed FFD is simple, affordable, and accessible for emergency services in rural or low-resource settings. The system is tested under controlled fire conditions and shown to effectively suppress small-scale fires with improved targeting accuracy and safe operational distance. The paper discusses the design process, mechanical integration, performance analysis, and potential applications, along with the limitations and suggestions for future enhancements.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Fire-Fighting Drone, Manual UAV, Fire Extinguisher Ball, Payload Mechanism, Remote Operation, Emergency Suppression

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Phishing attacks continue to dominate the global cyber threat landscape, exploiting newly registered and visually deceptive domains to lure users into compromising sensitive information. This review examines how artificial intelligence (AI) and machine learning (ML), when combined with open-source intelligence (OSINT) and content similarity techniques, offer a powerful, proactive defense against such threats. By leveraging domain metadata, web content features, and visual analysis, modern detection frameworks can identify phishing domains at the time of or shortly after their registration. This article synthesizes state-of-the-art research, evaluates AI model performance, and introduces a lifecycle-based theoretical model for AI-powered phishing detection. The review also highlights current gaps in explainability, scalability, and integration, providing a roadmap for future development in this critical domain of cybersecurity

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Phishing Detection, AI in Cybersecurity, WHOIS Data, Domain Intelligence, Machine Learning, Webpage Similarity, OSINT, CNN, LSTM, Visual Phishing, Explainable AI, Federated Detection.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The lip serum with SPF is a concentrated product that provides protection from sunlight, hydration, plumping, and healing effect on lips upon application. This also provides a brown tint to the lips. Lip serums contain smaller molecules when compared to lip oils which helps to penetrate deeper into the skin. The projects aim to formulate a Herbal lip serum with SPF that provides protection from sunlight, heals sunburn, and prevents Actinic cheilitis. The objective of the project was to formulate a multifunctional lip product that provides protection, hydration, and healing effect. The Herbal lip serum with SPF was prepared by using carrot seed oil, coconut oil and other ingredients in specific quantity. The formulation was prepared by incorporating Carrot seed oil and Coconut oil into melted shea butter and beeswax and is stabilized by vitamin E. Five formulations (F1-F5) was prepared with varying concentrations of ingredients The formulations were evaluated for organoleptic properties, SPF, pH, irritancy and spreadability to ensure product quality and consistency. The formulation F4 was found to be the best among the five preparations as it showed greater consistency, SPF, and homogeneity. The results demonstrated the successful development of a Lip serum with sun protection, uniform brown tint, smooth texture, ideal pH and good spreadability. The findings suggest that the developed Lip serum to be a stable, safe, and effective lip care product which can deliver multiple benefits. The formulation successfully meets the intended objectives, providing moisturization, soothing, sun protection and healing effect, making it suitable for diverse lip types. The developed formulation holds promise as a natural, effective, and high-quality addition to lip care routines, which can be used both day and night and whenever required. Further higher studies are required to explore the efficacy and safety of this formulation in larger population.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Lip serum, Protection, sunlight, SPF

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In financial engineering, stock market prediction is a crucial subject, particularly given the ongoing advancement of innovative methods and strategies in this area. In this study, we look into how sentiment exhibited in Twitter tweets affects the ability to predict stock prices. Twitter is the social networking site that gives everyone a free forum to publicly share their opinions. In specifically, we use the API to retrieve the company's live Twitter tweets. Every special character and stop word in the dataset is taken out. The Random Forest classifier is used to analyze sentiment in the filtered data. As a result, the tweets are categorized as neutral, negative, and positive. To get the outcome, the machine learning model receives the stock data and the tweet data as input. The stock market price is predicted using the ML classifier as a model. The real stock market value is contrasted with the predicted value that was obtained. Experiments employing real-time Twitter data and daily stock data from a number of businesses. The project's objective is to forecast the future price of a stock of interest by combining sentiment analysis of news headlines and Twitter tweets with previous stock data.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Stock Market, Data Analysis, Machine Learning, Stock price Prediction, Social Media.

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Creative Commons Attribution 4.0 and The Open Definition