Volume 13 | Issue 4

 Abstract

Abstract: Chaos-based encryption, when combined with ElGamal cryptographic frameworks, offers a robust approach to securing communication in distributed systems. This project explores a hybrid cryptosystem that leverages the sensitivity to initial conditions in chaotic functions and the discrete logarithm problem underlying ElGamal encryption. By integrating chaotic key generation techniques, such as logistic maps and Gray code transformations, with ElGamal's asymmetric encryption, the system ensures enhanced data confidentiality, integrity, and resilience to cryptographic attacks. The experimental evaluation demonstrates that the proposed hybrid model achieves significant improvements in security, computational efficiency, and resistance to cryptanalysis, including side-channel and brute force attacks. Additionally, the system is designed to facilitate efficient key management, while ensuring adaptability for lightweight devices and real-time secure communication protocols. This contribution highlights the potential of chaos-based-ElGamal hybrid cryptography as a secure and scalable solution for modern communication networks.

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Keywords-- Chaos-Based Encryption, ElGamal Cryptosystem, Secure Communication, Hybrid Cryptography, Logistic Maps

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This paper explores the theoretical challenges and opportunities presented to Human Resource Management (HRM) by the rapid advancement of digital technologies. The digital age has fundamentally reshaped work, the workforce, and expectations for both employees and organizations. This necessitates a re-evaluation of traditional HRM theories and practices. This paper argues that while digitalization presents significant challenges, it also offers unprecedented opportunities for HRM to become more strategic, efficient, and impactful. Theoretically, the digital age challenges established HRM frameworks in several ways. Firstly, the increased use of artificial intelligence (AI) and automation raises questions about the future role of human labor and the need for new skill sets. This necessitates revisiting theories of job design, training and development, and talent management. Secondly, the rise of remote work and the gig economy challenges conventional notions of the employment relationship and requires new theoretical approaches to managing dispersed and contingent workforces. Thirdly, for HRM, the enormous volume of data produced by digital technologies offers both possibilities and difficulties. Data analytics raises ethical questions about privacy, bias, and algorithmic management even though it can offer insightful information for decision-making. However, digitalization also presents significant opportunities for HRM. Data analytics can be leveraged to better understand workforce trends, predict future talent needs, and personalize HR interventions. Furthermore, digital technologies can facilitate more effective communication, collaboration, and knowledge sharing within organizations. This paper proposes a theoretical framework for understanding HRM in the digital age, highlighting the need for HRM to embrace digital technologies, adapt to changing workforce dynamics, and prioritize ethical considerations. This framework emphasizes the importance of integrating digital tools with human-centric HRM approaches to maximum organizational performance and employee well-being.

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 Keywords

Human Resource Management, Digital Age, Challenges, Opportunities

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This project explores the integration of a vertical axis wind turbine (VAWT) with a carbon capture system to promote sustainability in energy generation and air purification. The VAWT produces 2-3V of electricity, which is stored in a 9V battery and used to power an LED streetlight. The circuit is designed with a PCB incorporating a 555 timer IC, resistors, diodes, LEDs, and an LDR sensor for automatic activation based on ambient light levels. The carbon capture system absorbs CO2, presenting an innovative method to curb emissions while utilizing renewable energy sources.

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Wind Energy, Carbon Capture, Sustainable Power, PCB, 555 Timer IC, LDR Sensor.

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 Abstract

Cardiac arrest remains one of the most prevalent causes of sudden mortality across the globe. Early identification of individuals at risk is essential for timely intervention and prevention. This study presents an algorithmic framework designed to evaluate the risk of cardiac arrest by analyzing age alongside various health-related factors. A scoring-based system is developed and implemented using Python to categorize individuals into distinct risk levels. Additionally, the paper provides a comprehensive review of existing cardiac risk prediction models and assesses their effectiveness. The proposed method offers a practical and accessible tool for preliminary risk screening, with the potential for future enhancement through integration with machine learning technologies.

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 Keywords

Cardiac Arrest Risk, Health Data Analysis, Risk Scoring Algorithm, Rule-Based Prediction, Wearable Health Devices, Patient Risk Classification, Age-Based Health Risk, Cardiovascular Risk Factors, Early Risk Detection,

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Employee performance in insurance companies is critical to achieving organizational goals and ensuring sustained business growth. This paper explores the role of motivation in enhancing employee performance within the insurance sector. By examining various motivational theories and their application to the insurance industry, the study identifies key drivers that influence employee engagement, productivity and overall job satisfaction. Factors such as intrinsic and extrinsic motivation, leadership styles, reward systems and the work environment are analyzed to understand their impact on performance outcomes. Implementing effective motivational strategies such as performance-based incentives, professional development programs and a positive organizational culture can help retain top talent and reduce turnover rates. The findings highlight the importance of creating a supportive, empowering work culture, alongside effective incentive programs to maximize employee potential and enhance organizational performance in the competitive insurance market.

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 Keywords

Motivation, Employee Performance, Insurance company, Monetary and Non-Monetary Benefits

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The industrial wastewater treatment is a critical aspect of the environmental management, ensuring compliance with the discharge regulations and minimizing the ecological impacts. This study analyzes the wastewater samples collected from an electroplating industry in Bangalore to assess their physico-chemical characteristics. The parameters including pH, temperature, electrical conductivity, total dissolved solids, total suspended solids, turbidity, chemical oxygen demand, biological oxygen demand and heavy metal concentrations like chromium and lead were tested across the ten different samples. The obtained results were compared with the standard permissible limits. The findings indicate the variations in pollutant concentrations across the samples. The research underscores the importance of the regular monitoring and the effective wastewater management to mitigate the industrial pollution and safeguard the aquatic ecosystems.

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Wastewater, Physico-chemical Analysis, BOD, COD, Heavy metals, Environmental pollution, WQA.

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Consumer behavior is heavily influenced by impulse buying, especially in the FMCG industry. This research examines the main elements that affect impulsive purchases, such as sales, marketing, store design, and channels of shopping. According to data gathered from a structured questionnaire, limited-time deals, in-store displays, and promotions have a big influence on impulsive purchases. Consumers are more prone to make impulsive purchases in physical places than online, according to research, and many of them regret their decisions after making them. FMCG companies may improve customer engagement and sales by utilizing these information to improve their marketing tactics.

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Impulse Buying, Consumer Behavior, FMCG (Fast-Moving Consumer Goods), Promotional Strategies, Discounts and Offers, Store Layout and Display Advertising, Influence Online vs. Offline Shopping, Point-of-Sale Marketing, Limited-Time Offers, Unplanned Purchases, Product Packaging, Loyalty Programs, Post-Purchase Regret, Psychological Triggers.

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Recognizing hand gestures plays a vital role in enhancing interaction between humans and computers, particularly in assistive technologies, sign language interpretation, and real-time communication. This study explores effective methods for detecting hand gestures using Convolutional Neural Networks (CNN) and advanced deep learning techniques. The approach includes three main steps: capturing hand images using a webcam, removing noise and other distractions during image processing, and deploying a CNN architecture capable of recognizing various hand gestures, both static and dynamic. To evaluate the system's performance, a custom dataset with diverse hand gestures was created, achieving an accuracy rate exceeding 90%. Additionally, the proposed method enhances hand segmentation, accommodates gesture variability across users, and supports real-time gesture recognition, expanding the potential for interaction. The findings demonstrate that deep learning techniques significantly improve user interaction, especially for hearing-impaired individuals, by increasing recognition accuracy.

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Hand Gesture Recognition, Sign Language, Convolutional Neural Networks, Deep Learning, Real-time Processing, MediaPipe, Image Processing, Machine Learning, Gesture Variability, Hand Tracking, Feature Extraction, Transfer Learning, Dataset Creation, Accuracy Improvement, Computational Efficiency, Lightweight Convolutional Neural Network Architectures, Embedded Systems

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Beauty and cosmetic concept is as ancient as mankind and civilization. Cosmetics play a vital role in human life. Herbal cosmetic is one of the most effective areas of cosmetic technology. Herbal cosmetics are developed by the coalition of bioactive ingredients and pharmaceutical products. Herbs are used for beautification purpose of body, preparation of cosmetics, flavouring and coloring agent. Hair plays a vital role in personality of human and we use a lots of cosmetics product for the care of hair. The aim of study is to reviewing the importance of herbal oil and their use in the common hair problem such as baldness, hair fall, hair dryness, dandruff etc. Various beauty and cosmetic products are used which contain herbs to give young and charming look. Various herbal ingredients are used in herbal hair formulation. They provide essential nutrients such as vitamins, antioxidant, etc. Herbal hair oil has been widely used for nourishment of hair and for the protection of hair from hair fall and hair damage.

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Herbal hair oil, Dandruff, Cosmetics, Nourishment, Hair fall.

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Creative Commons Attribution 4.0 and The Open Definition

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The development of digital assets such as cryptocurrencies and financial products based on blockchain, has contributed to the rise in the number of serious regulatory issues for various nations. India is also in an important position to develop a well-integrated legal framework for digital assets with its expanding fintech industry. This research study explores the development of digital asset regulation in India, outlining the transition from initial legal hurdles and government disapproval to current legislative and judicial developments. It also analyzes the legal implications of existing and future legislative frameworks as well as their compliance with international norms and constitutional rights. As much as evaluating the legitimate economic gains of adopting blockchain innovation, the author in this research paper, considers the monetary risks that accompany the unregulated digital asset markets such as financial instability, capital flight and frauds. It further highlights the intricate balance, which the governments must maintain between promoting consumer protection, financial integrity and national security and innovation in technology. Drawing on similar regulatory strategies and stakeholder perspectives, the research paper provides strategic suggestions for a balanced, adaptive, future-proof regulatory framework for digital assets in India.

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Digital Assets, Cryptocurrency Regulation, Blockchain Technology, Fintech in India, Legal Framework, Economic Risks, Consumer Protection, Financial Innovation, Regulatory Policy, India Digital Economy, Virtual Currencies, Compliance and Enforcement, Technology Law, Digital Finance, Public Policy

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There are multiple methods available for monitoring traffic conditions on roadways. With the advancement of artificial intelligence (AI) in image processing technology, there is an increasing interest in creating traffic monitoring systems that utilize camera vision data. This research paper presents a technique for extracting traffic information from a camera positioned at an intersection, aimed at enhancing road monitoring systems. The approach employs a deep learning model (YOLOv4) for processing images to detect vehicles and classify their types. Vehicle trajectories are estimated lane by lane by correlating the detected vehicle positions with a high definition map (HD map). From these estimated trajectories, the traffic volumes for each lane's direction of travel are calculated. The effectiveness of the proposed method was evaluated using samples across distinct criteria: vehicle detection rate, traffic volume estimation. The findings indicate a 99% success rate in vehicle detection, introduced in this research demonstrates the potential for gathering detailed traffic data installed at an intersection. The integration of AI technologies represents the primary contribution of this study, highlighting significant potential for enhancing existing traffic monitoring systems

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Vehicle detection and counting, YOLO, artificial Intelligence

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Employee engagement and perception are vital for delivering high-quality healthcare services and achieving organizational effectiveness in private hospitals. This paper explores the impact of organisational culture on employee engagement and perception within the healthcare sector, with a focus on private hospitals. By examining various cultural frameworks and their relevance to hospital settings, the study identifies key factors that shape employee attitudes, motivation, and involvement in their roles. Elements such as leadership approach, communication style, shared values, and work environment are analyzed to understand their influence on employee satisfaction and commitment. The findings emphasize the importance of fostering a positive organisational culture that promotes trust, inclusiveness, and professional growth, ultimately enhancing employee engagement and the overall patient care experience.

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Keywords: Organisational Culture, Employee Engagement, Employee Perception, Private Hospitals, Work Environment

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Abstract The present study investigates the psychological implications of binge-watching behavior, particularly its impact on youth personality traits. Binge-watching, defined as viewing multiple episodes of a TV series in one sitting, has become increasingly common due to the rise of streaming platforms. This research explores the correlation between binge-watching and various personality factors using a questionnaire developed by Flayelle et al. (2020) and administered to 40 participants aged 18-25 through simple random sampling. The study reveals that binge-watching serves as a coping mechanism for many individuals, offering instant gratification, emotional regulation, and escapism. However, it also presents significant negative consequences, including increased isolation, disrupted sleep patterns, poor task management, and social withdrawal. Graphical data analysis supports the hypothesis that binge-watching significantly affects personality, often intensifying traits such as irritability, laziness, and emotional instability. The findings underscore the dual nature of binge-watching: while it offers entertainment and temporary relief, its excessive engagement poses risks to mental and social well-being, suggesting the need for awareness and balanced media consumption habits.

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Keywords: Binge-watching, personality traits, psychological effects, youth behavior, media consumption, coping mechanisms, emotional regulation

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The paper focus on social media and students. Today generation students live in social media. To understand how social media is used by student for studies is the main agenda of the paper. The primary and secondary data is used in preparing the paper. Google forms are used to collect data. 56 convenient samples are used in the paper. MBA student from Mysore are taken. To know about social media usage among students. Percentage analysis is used to analyze the data. The results indicate that students use social media for Entertainment and learning.

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KEY WORDS: Students, social media, you tube, Entertainment and learning.

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 Abstract

Introduction of Swiggy and Zomato

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Customer satisfaction, equality, price level

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This study investigates emotion-driven food recommendation systems, ingredient-identifying recipe proposals, and advancements in text-to-speech (TTS) technology. Emotion-based platforms such as 'MoodieFoodie' and 'Mood Canteen' leverage facial recognition and social media insights to recommend dishes aligned with users' feelings, enhancing satisfaction and emotional well-being. Recipe recommendation platforms like 'Makeat' and 'RecipeIS' employ YOLOv5 and CNNs for ingredient detection, providing customized suggestions based on available ingredients, thereby minimizing food waste. TTS systems, including Tacotron and WaveNet, apply deep learning techniques to produce natural and expressive speech, enabling multilingual and emotion-rich interactions. Together, these technologies enhance personalized and interactive experiences in food selection, cooking, and digital communication.

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Emotion-based recommendation, Ingredient recognition, Recipe suggestions, Text-to-speech (TTS), Facial recognition, Deep learning, Personalized recommendations.

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Cognitive Image Processing (CIP) analyzes and extracts meaningful data from images, aiding sectors like banking and healthcare. The manual entry of bank details into forms is prone to typographical errors and is time consuming. This paper presents an automated approach using CIP to extract relevant details from bank passbook images and auto fills bank forms. The system integrates image processing techniques to enhance text clarity and Optical Character Recognition (OCR) to extract relevant details with Natural Language Processing (NLP) techniques, including Regular Expressions (Regex) and Levenshtein Distance to enhance text extraction accuracy. The extracted data is used to automatically fill the forms. A user-friendly mobile application is developed using Replit. The application auto-fills bank forms, reducing typographical errors and improving efficiency. Users can capture passbook images, verify extracted details, and edit as needed. This solution streamlines form-filling, minimizing errors and saving time.

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Cognitive Image Processing, Tesseract OCR, NLP, Regex, Levenshtein Distance, Bank Form Automation.

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This research explores the impact of training and development on employee performance. The study aims to understand how structured training programs enhance skills, productivity, and job satisfaction. A mixed-method approach, including surveys and interviews, was employed to assess training effectiveness. Findings suggest that organizations investing in training witness improved employee engagement, reduced turnover, and higher efficiency. The study highlights the need for continuous learning and strategic training initiatives to maintain a competitive workforce.

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Training, Development, Employee Performance, Skill Enhancement, Job Satisfaction, Productivity, Learning Culture

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The traditional paper-based menu system in restaurants often leads to inefficiency and wastage due to the manual ordering process. This paper aims to address these issues by introducing a digital ordering system. Customers will be able to order dishes directly from their tables, eliminating the need for waiters and reducing wait times. The proposed system is expected to improve customer satisfaction, reduce operational costs, and minimize paper waste.

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 Keywords

Digital Ordering System, Restaurant Management, Customer Satisfaction, Operational Efficiency, Paperless Menu

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 Abstract

Now-a days, Talent analytics, People analytics are all terms used to describe the practice of applying analysis processes to workforce data to understand workforce-related business issues in all organisations. There are different ways in which HR can use talent analytics, it consists of a number of processes, enabled by technology that use descriptive, visual and statistical methods to interpret talent/people data, such as human capital, HR systems and processes, organisational performance. It helps in addressing HR challenges and organisational issues and provides an opportunity for every organisation to review and re-frame their strategies for organisational development and proper utilisation of talents. The discussion paper is meant for HR professionals and others who are looking for the Talent Analytics framework for long term HR management policies such as, key approaches, competencies and tools.

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Talent Analytics, Approaches, Outcomes, Barriers and Tools.

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