Volume 13 | Issue 4

 Abstract

These days, mosquito-borne illnesses are a serious health concern. Mosquitoes are largely responsible for the transmission of several diseases, such as dengue, malaria, and yellow fever Herbal dhoop is a natural product made from plant parts that naturally repel mosquitoes. It is safe, non-toxic, and environmentally friendly. It is manufactured from a special combination of plant extracts and aromatic oils that keep insects and mosquitoes away. The essential oils and plant extracts used in this study were evaluated at varying doses using a handcrafted mosquito stick in a room with a lot of insects. The findings showed that certain herbal plant combinations have mosquito-repelling properties. Use of camphor, neem, tulsi, marigold, and other plants that have been shown to have the strongest insect repellents and no irritation is safe and environmentally beneficial

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Herbal Dhoop, Mosquito repellent, Sandalwood, Marigold flower.

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In our society there are people who suffer from paralytic diseases that cause them sev eral disabilities like damage to brain or spinal cord, that can happen in a car accident, fall, or sports injury. An EMG (electromyography) signal is a biomedical signal that measures the electrical activity of muscles. EMG signals are used to study neuromuscu lar activities and muscle force. Prostheses are artificial replacements that a person can wear in place of a missing body part. Here we are using a robotic arm for a handicapped person. The project is working under the principle of EMG. The Signals are generated when muscles contract, which creates charged particles in the muscle membrane and these signals are measured using electrodes placed on the skin. Different types of upper limb exoskeletons are deployed in the robotic-based rehabilitation purposes according to the functionality of the robotic devices.

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EMG, Robotic Arm, Arduino

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This study explores the key factors influencing consumer trust in credit card tokenization systems, focusing on aspects such as privacy concerns, ease of use, user experience, and reliability. Through a combination of descriptive statistics, correlation analysis, and multiple regression analysis, we analyzed data collected from 150 respondents to identify the most significant determinants of trust in tokenization. The descriptive analysis revealed that respondents generally hold moderate perceptions of tokenization, with a slight inclination towards viewing the system as reliable. Correlation analysis indicated positive relationships between trust in tokenization and factors such as reliability and security perception, though privacy concerns showed a weaker correlation with trust. The multiple regression analysis identified reliability as the most significant predictor of trust, with a strong positive impact, while other factors like privacy concerns, ease of use, and user experience did not show statistically significant effects. These findings underscore the importance of enhancing the reliability of tokenization systems to build and maintain consumer trust. The study concludes that while privacy and usability are important, the perceived reliability of tokenization systems is the most critical factor in fostering consumer confidence and ensuring widespread adoption of tokenized payment methods.

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 Keywords

Credit Card Tokenization, Privacy Concerns, Consumer Trust, Digital Payments

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This research examines the patterns of how college students utilize library resources beyond regular academic hours. Due to the rising expectations of students to perform well academically, students often advance their study times beyond what is scheduled and need a space on campus to study, carry out research, complete an assignment, or engage in self-study, and libraries are often these spaces. The study examines elements that affect student after-hour library use such as accessibility to library resources, types of available resources, use of digitally-based tools, and student preferences. Student data were collected through online surveys and observations which helped to notify the research on understanding and making improvements to the library's services for student engagement. The findings are intended to assist educational institutions in optimizing library resources to provide improved support to student learning.

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 Keywords

Library Usage, College Students, After-Hours Study, Academic Resources, Digital Libraries, Student Engagement, Library Services.

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The study explains that Gen Z users prioritize speed and simplicity when using UPI, with 78% valuing instant transaction processing as a key factor. Security concerns, however, remain a significant barrier, as 62% express apprehension about potential fraud or data breaches. Despite this, the convenience of cashless payments, coupled with the ability to split bills and make seamless online purchases, drives consistent usage. The research further highlights that while rewards and cashback offer attract initial adoption, sustained usage depends more on reliable service, ease of dispute resolution, and minimal transaction failures. Additionally, the study underscores the growing preference for contactless payments, with QR code scanning emerging as the most common method of UPI transactions. To foster long-term loyalty, fintech platforms must prioritize robust security measures, personalized offers, and enhanced app features tailored to Gen Z preferences.

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 Keywords

UPI, Gen Z, digital payments, fintech, Google Pay, social influence, rewards.

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Cybercrime cases against women are increasing tremendously. This study will discuss about reasons of targeting women and various kinds of cybercrime as well as its critical analysis. It is essential to combat these crimes against women because it is against fundamental rights. Strict laws must be implemented and awareness must be created among women about technology and must gain knowledge about new cybercrimes.

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Cybercrime, women, cybercriminals

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 Abstract

Hinsa Prabhavit mahilao hetu sarkar ki ek pahal:one stop centre

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Hinsa Prabhavit mahilao hetu sarkar ki ek pahal:one stop centre

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Non- linear optical crystals have a great impact on information technology and industrial applications.The present paper deals with the growth and characterization of Semicarbozidehydrocloride adipate (SCHA). An organic non-linear optical material of SCHA was synthesized ethanol as a solvent .The single crystals were grown by slow evaporation technique at room temperature. The cell dimensions obtained by single crystal X-ray diffraction studies reveal that the crystal belongs to the orthorhombic system. The occurrence of prospective functional groups was initially identified by FTIR and FT-Raman spectroscopic studies. The optical transparency of the crystals was determined by UV- Visible studies in the wavelength range of 200-1200 nm. Second harmonic generation conversion efficiency found using the Kurtz and Perry method is about 4.2 times that of KDP. The thermal stability of the compound was determined by TG-DTA analysis of the specimen. The microhardness test was carried out and the load dependent hardness was measured.

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X-ray diffraction, FT-IR, Optical transmission, Second harmonic generation, TGA/DTA

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Life insurance is a vital financial tool that offers protection and serves as a long-term investment avenue. This study investigates consumer perceptions, preferences, and the factors influencing investment decisions in life insurance products. Based on a survey of 63 respondents, the study evaluates various insurance policies and their investment potential. Findings indicate that a majority of investors consider life insurance for tax benefits and financial security, yet concerns regarding high premiums, complex policy structures, and lack of transparency impact their decision-making. The study also presents comparative insights between life insurance and other investment options like mutual funds and fixed deposits. Recommendations include enhancing policy transparency, reducing premium costs, and increasing awareness regarding investment-linked insurance products.

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Life Insurance, Investment, Risk Management, Tax Benefits, Financial Planning, Consumer Behavior

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The research suggests the joint effect of incubation and funding towards entrepreneurial start-up success. Funding supplies strategic capital that is needed for product development, marketing, and expansion, while incubation provides strategic advice, networking, and business expansion services. The research analyzes the joint effects of these two towards start-up survival, expansion, and long-term viability.With a mixed-methodology, the study applies quantitative assessment to analyze the interconnection of startup success, funding, and incubation, and qualitative case studies to gather more information. Results show that startups that receive both incubation and funding support perform better than those receiving funding support or incubation support separately. It suggests that there is a necessity for integrated support systems with a mix of financial and non-financial forms of assistance to obtain the best entrepreneurial outcomes.

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Entrepreneurship, Startup Success, Funding, Business Incubation, Venture Capital, Business Growth, Startup Ecosystem, Innovation, Entrepreneurial Support, Small Business Development

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 Abstract

Electrical hazards pose serious risks in industrial, commercial, and household environments, often leading to electric shocks, fires, and equipment damage. This project focuses on designing a wearable electrical hazard detection system using a transistor-based circuit instead of complex microcontrollers. The system detects live electrical fields and leakage currents, providing real-time alerts through an led and buzzer. The circuit is lightweight, portable, and energy- efficient, making it suitable for electricians, industrial workers, and general users. Rigorous testing and troubleshooting ensured accuracy, stability, and reliability. This project contributes to enhanced safety measures and can be further improved with wireless alerts, smart integration, and advanced hazard prediction.

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Leakage current, Hazard, Electrical shocks ,Real time alert

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In this pioneering research, we leverage the direct and fixed-point approaches to meticulously prove the Ulam-Hyers-Rassias stability of a cubic functional equation characterized by a complex and innovative mean sum formulation of successive function variables in quasi-?-Banach space.

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Cubic functional equation, UHR Stability, Quasi-Beta- Banach space, Complete Normed Space, Fixed point, Hyers Approach, Contractive Mapping.

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The value chain in Gujarat's solid-liquid separator sector is examined in this research report. The study analyzes Rotofilt Engineers Ltd.'s major and supporting activities using a descriptive research design. Surveys and questionnaires were used to collect primary data, and corporate records and industry reports were used to obtain secondary data. The results highlight important obstacles and potential opportunities for value chain optimization, especially with regard to resource allocation, cost structure comprehension, and customer value delivery. The analysis advances our knowledge of this industry's competitive advantage and strategic decision-making.

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Supply Chain, Manufacturing, Competitive Advantage, Process Efficiency, Solid-Liquid Separation, Gujarat, Industrial Equipment, Value Chain Analysis

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The safety and efficiency of railway transportation depend significantly on the integrity of rail tracks. Traditional methods of rail track defect detection are often time-consuming and prone to errors. With advancements in artificial intelligence, deep learning techniques have emerged as a powerful tool for automating defect detection, improving accuracy, and reducing maintenance costs. This paper presents a comprehensive review of deep learning-based approaches for rail track defect detection, highlighting various methodologies, datasets, and challenges in the field. Furthermore, it discusses real-world applications, potential improvements, and future research directions to enhance railway monitoring systems.

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Deep Learning, Artificial Intelligence, Accident, Neural Networks

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The monitoring Spy The goal of the robot project is to create a mobile robot that can navigate indoor spaces on its own and carry out a variety of security and surveillance-related duties. Real-time video data transmission, obstacle detection, and remote operator communication should all be possible for the robot. The robot ought to be resilient, stealthy, and situation-and scenario-adaptable. The project intends to show that employing robots for security and surveillance purposes in a variety of fields, including the military, law enforcement, industry, and the home, is both feasible and promising. The primary objective of the suggested system is to offer an economical and efficient solution for missions involving surveillance and reconnaissance. There are numerous applications for the robot, including journalism, security, intelligence, law enforcement, and the military. The robot can gather important data covertly and enter areas that are hazardous or challenging for people to access. The robot may also sneakily interact with the environment or the victim, and if needed, it can flee or destroy itself. By offering a remote-controlled, safe, and effective way to rescue injured persons, the Revolutionary Rescue Unmanned Vehicle seeks to transform emergency response and wartime situations. Because of its ability to manoeuvre over challenging and dangerous terrain, this autonomous vehicle can remove wounded soldiers from combat areas without endangering other human rescuers. Its sophisticated sensors, cameras, and communication devices allow for accurate mane variability and real-time operator feedback, guaranteeing efficient navigation and prompt rescue operations.

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SPY Robot, Sensor, Bluetooth, Motor

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This study examines how Coimbatore City consumers view Zudio's brand image by examining the variables that affect consumer loyalty, brand awareness, and purchase behaviour. Zudio, a quickly expanding retail brand owned by Tata Trent Limited, provides stylish, reasonably priced clothing to a wide range of customer demographics. This study investigates consumer preferences, brand comparisons, and purchasing reasons using a structured survey. Although issues like product availability, customer service effectiveness, and rivalry from companies like Max and H&M still exist, research indicates that Zudio's appeal is largely driven by its affordable prices and stylish designs. In a competitive fashion retail environment, the study offers suggestions for strengthening brand loyalty, improving customer experience, and improving Zudio's brand positioning. Fast-fashion company Zudio, owned by Tata Trent Limited, has grown quickly thanks to its stylish apparel and reasonable prices. Using a structured survey with 120 respondents, the study focuses on young urban consumers between the ages of 18 and 35. Brand perception, product quality, pricing, customer service, and rivalry from companies such as Max and H&M are among the important elements that are examined. The results show that although customer preference is influenced by pricing and trendy designs, issues like product availability, lengthy billing lines, and trial room accessibility have an effect on the entire shopping experience. Furthermore, the report emphasizes how sustainability and digital influence shape customer choices.

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In a competitive fashion retail environment, the study offers suggestions for strengthening brand loyalty, improving customer experience, and improving Zudio's brand positioning.

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Customer satisfaction has become a critical factor in business success as competition in the food delivery industry has increased. While service quality and pricing have been thoroughly researched, the impact of brand image and market value on customer satisfaction is largely unknown. This study looks into the impact of these characteristics, specifically how brand perception and financial stability affect consumer trust and loyalty. A descriptive research design was adopted, which combined primary and secondary data sources. Surveys, interviews, and focus groups were used to acquire customer insights, with industry publications providing further context. The data were examined using regression and moderation analysis to determine the relationship between brand image, market value, and customer satisfaction. The findings show that a strong brand image considerably improves customer happiness, while market value is critical in reinforcing customer trust. Furthermore, market value was discovered to regulate the association between brand image and satisfaction, emphasising its importance in driving consumer behaviour. This study adds to the literature by including financial stability as an important element in consumer decision-making. To increase client trust, firms can work on developing a strong brand presence and implementing transparent financial processes. Future research should look at these relationships across different market groups and assess the influence of sustainability initiatives in brand perception.

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 Keywords

Brand image, market value, customer satisfaction, consumer trust, financial stability, the food delivery industry, business growth, market positioning, and consumer loyalty

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 Abstract

Through machine learning and computer vision the Genage Detector uses advanced technology to forecast human characteristics based on image pictures. The deep learning system uses large dataset training models to generate precise outcomes. Both administrative and end-user modes let users access the system easily while the internal database tracks user behavior and stored trait predictions for research purposes. The Genage Detector shows output right after video processing happens. This report explains what the project aims to achieve and details its technical capabilities to serve different industries including marketing, health and security fields. The Genage Detector breakthrough technology analyzes human features by reading video footage. People should have better ways to handle digital image and video content since this data type reduces daily. Using advanced facial image analysis Genage Detector enhances user experience and creates new ways to use its age-gender prediction data. The Genage Detector serves as an effective and dependable technology for detecting people's age and gender. The app uses advanced deep learning models to handle images instantly as it returns exact and useful outcome data. The technology gives useful information to marketers for personalized campaigns and helps doctors understand patient health risks through age-based analysis.The Genage Detector puts user needs first because it creates a basic system that lets you add new pictures or pick live video streams for analysis. Through its full backend system the Genage Detector records and stores user actions while keeping track of predicted traits to enhance future prediction accuracy.

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Genage Detector, Machine Learning, Computer Vision, Future Prediction Accuracy.

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 Abstract

Companies need signature fraud detection systems to prove valid signatures on official documents across various industries. Fraudulent signatures harm many different sectors by causing damage to finances and creating identity theft problems along with legal problems. Forensic experts who check signatures by hand take too long and produce results that depend on their own feelings and mistakes. Digital platforms need an automatic security system that accurately spots fake signatures because of growing document threats and rising electronic transactions. This project creates a system that uses CNNs to identify irregular signatures through deep learning technology. CNNs show remarkable results when classifying images which make them good at differentiating real signatures from frauds. The application runs on the web through a Flask framework and lets users add signature images for evaluation. The deep learning model needs processed images first which means the system prepares the images by adjusting their size and quality while removing noise for optimal performance. Our model works with diverse data to examine signature images and inform users if their input is an original or a fake. This system working model fits different industries including bank, law, business security, and official government use as they all depend on accurate signature verification. Using advanced machine learning helps our system identify signatures better which reduces document fraud risk and creates a reliable solution for organizations that need secure verification. The system can develop additional security features by adding electronic signature tracking alongside multiple security checks and block chain network connections.

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 Keywords

Fraudulent Signatures, Flask Framework, Machine Learning, Deep Learning Model, Block Chain.

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 Abstract

A state-of-the-art software application uses artificial intelligence to enable users to manage tasks and access information and control system functions by speaking commands. Through the integration of modern systems including speech recognition and natural language processing (NLP) and machine learning the assistant operates multiple functions that cover application launching as well as media playback and system parameter changes and immediate feedback about weather and battery indicators. The system works with Google Gemini APIs to generate smart responses and supports offline wake word detection which improves privacy features. The web-accessible interface of this assistant functions through Python Flask development leading to seamless cross-platform implementation. As a voice-operated solution this project serves to minimize human-computer interface complexities through hands-free command control for daily operations which makes it applicable at both personal and workplace environments. The tool offers multiple capabilities to schedule events and give users information while handling smart device interaction which leads to better user efficiency and ease. Through the combination of speech recognition along with machine learning algorithms and cloud technology the virtual assistant obtains knowledge from user dialogues so it can improve its solutions throughout time. This project responds to modern interface requirements by creating user-friendly technology systems that serve wider user groups. The assistant will provide functionality to execute concurrent tasks which lets users expect assistance for multiple requirements through a single interface. This document provides an overview of project goals and territory as well as motivation and identification of concerns followed by a review that examines present solutions connected to their weaknesses. The artificial intelligence system combines state-of-the-art natural language processing with machine learning to execute automation tasks and supply information in order to boost productivity. Users can expect personalized service from the system because it keeps high command understanding and execution accuracy during all interactions while tailoring itself to individual preferences. The project responds to the expanding necessity for teamwork that exists during the development of software. The assistant achieves smooth teamwork by integrating with version control systems which lets developers share code while conducting change reviews to support project-wide high-quality standards.

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 Keywords

Natural Language Processing (NLP), Machine Learning, Python Flask, Google Gemini.

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Creative Commons Attribution 4.0 and The Open Definition