Volume 13 | Issue 5 |

 Abstract

Federated Learning (FL) is an emerging decentralized machine learning approach that enables model training across multiple devices or clients without transferring raw data to a central server. By maintaining data locality, FL enhances data privacy and reduces the risks associated with data breaches. This method is particularly suitable for sensitive domains like healthcare, finance, and IoT applications. The report explores the architecture, core mechanisms, advantages, challenges, and security strategies of FL, including techniques such as differential privacy and secure multi-party computation. The paper also discusses different types of FL such as Horizontal, Vertical, and Federated Transfer Learning and highlights its applications and future research directions

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 Keywords

Artificial Intelligence , Federated Learning , Decentralized Training , Data privacy , Edge Devices

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The rapid advancement of Internet of Things (IoT) technology has revolutionized home automation by enabling seamless remote control and monitoring of smart devices. This project focuses on designing and implementing a smart home automation system using the Blynk IoT platform, which provides an intuitive interface for managing various household appliances via smartphones or other internet-enabled devices. The system is built around the ESP8266 Wi-Fi module, known for its low power consumption, integrated TCP/IP stack, and efficient processing capabilities. With a 32-bit Tensilica L106 processor operating at 80-160MHz, 16MB flash memory support, and Wi-Fi Direct (P2P) connectivity, the ESP8266 ensures reliable real-time communication between devices. Additionally, its GPIOs, ADC input, and multiple concurrent TCP connections allow for the integration of various sensors and actuators, making the system highly adaptable. This project explores the setup, configuration, and implementation of a smart home automation system that controls devices such as lights, thermostats, and security cameras. The integration of Blynk enhances the system's flexibility, scalability, and ease of use, allowing users to monitor and manage their home environment efficiently. By leveraging IoT-based automation, this project demonstrates how smart homes can improve convenience, energy efficiency, and security. The findings and implementation steps serve as a valuable resource for IoT enthusiasts, researchers, and homeowners looking to adopt smart home solutions.

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 Keywords

Internet of Things (IoT)

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

As the production of electric vehicle has scaled up in the recent years in order to meet the objective of lowering the carbon footprint and eco-friendly transportation. The raise in the production of electric vehicles in accordance with hike in the price of petroleum and diesel has shifted the huge market share of the automobile industry from ICE engines to the battery powered engines. The shift in turn pushes the demand for installation of charging stations for electric vehicles at most locations. But the installation of such EV charging base stations requires high capital and sophisticated spatial infrastructure in densely populated area. Therefore, the paper proposes the AIS based mobile wireless charging system for electric vehicles which is cost effective and reliable. The system is best suited for densely populated areas, parking arenas at theatres, malls, parks etc., The Wireless Sensor Network is implemented to effectuate adaptive intelligent system, therefore leading to better accuracy and modularity.

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 Keywords

Battery Management, Wireless Charging, Electric Vehicles, IOT, Battery Performance Optimization

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The increasing integration of technology in education has paved the way for more dynamic and accessible learning environments. This project presents the development of an EdTech website, a comprehensive online learning platform designed to enhance educational experiences for students, instructors, and administrators. Leveraging the MERN stack (MongoDB, Express.js, React.js, Node.js), the system offers interactive tools such as quizzes, personalized content, and real-time analytics. Key features include secure user authentication, course management, responsive UI, and scalable cloud deployment using services like Vercel Render, and MongoDB Atlas. Agile development methodologies guided the project's progress, with continuous stakeholder engagement and iterative feedback. The result is a secure, engaging, and user-centric platform. This initiative highlights the potential of EdTech solutions in revolutionizing modern education.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

EdTech, MERN Stack, Online Learning, Agile Development, MongoDB Atlas, Vercel

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 Abstract

Abstract: This study explores the use of machine learning techniques, focusing on the Random Forest Classifier, to predict the directional shifts of the S&P 500 stock market index. The research frames the problem as a binary classification challenge, aiming to determine whether the market will rise or fall on the subsequent day. By analyzing historical OHLCV (Open, High, Low, Close, Volume) data collected over a period of three decades, we evaluate the model's reliability and predictive capabilities. The approach incorporates rolling-window backtesting, with performance assessed through precision and confusion matrix metrics. Our results suggest that the Random Forest model demonstrates competitive effectiveness, especially in low volatility environments, and establishes a solid foundation for more sophisticated ensemble and hybrid methodologies.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Stock Market Prediction, S&P 500, Random Forest, Machine Learning, Time Series, Financial Forecasting, Backtesting, OHLCV

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Organizational commitment is vital in determining the long-term stability and success of any company. This study aims to evaluate the level of commitment and workforce involvement in a private finance company. The results reveal significant relationships between motivation and employee performance, with specific areas identified for improvement. Various factors such as motivation, job satisfaction, leadership, and performance were studied using both primary and secondary data. Statistical tools like Chi-Square Test, Mann-Whitney U, Kruskal-Wallis H Test, Spearman Correlation were used for analysis. The findings show that performance and motivation are strongly correlated, as well as areas that need work.

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Keywords: (Motivation, Job Satisfaction, Employee Performance, Workforce involvement)

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Creative Commons Attribution 4.0 and The Open Definition

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In the dynamic world of manufacturing, Big Data is considered to be among those disruptive technologies, which carries incredible potential for improving operational effectiveness. This paper consolidates insights from recent literature to investigate how BDA competencies support process efficiency, sustainability, quality control, and strategic decision-making in manufacturing. We also complement the literature with empirical and theoretical basis to provide a systematic knowledge of BDA effects, reinforced with models like the Resource-Based View, Institutional Theory, and with dynamic capabilities. Despite the growing recognition on the potential benefits of BDA, this paper highlights significant adoption challenges, such as data integration complexity, infrastructure inadequacy and organisational culture. The review also identifies potential trends in predictive analytics, real-time monitoring and smart manufacturing within the context of the wider Industry 4.0 framework. Combining insights from various disciplines, the article provides a holistic account of how BDA is reshaping business operations, and enabling sustainable, data-driven, transformation in manufacturing.

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 Keywords

Big Data Analytics, Operational Efficiency, Manufacturing, Predictive Analytics, Industry 4.0, Resource- Based View, Data-Driven Decision Making, Supply Chain Optimization

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Chronic musculoskeletal pain often involves dysfunction not isolated to a single region but distributed along interconnected movement chains. The kinetic chain concept borrowed from biomechanics , views the body as linked segments (joints and muscles) whose coordinated function influences whole-body movement. In parallel, fascial chains or myofascial meridians (e.g., the Superficial Back Line) represent continuous connective-tissue pathways that transmit tension and link distant muscles. This narrative review explores how dry needling (DN) might act along these chains to relieve chronic pain. We discuss theoretical mechanisms whereby needling one muscle could modulate distant structures and summarize emerging evidence for chain-based needling approaches. Notably, clinical and experimental studies suggest that inserting a needle at a distal site can reduce trigger-point irritability elsewhere. For example, dry needling the forearm extensor relieved neck/upper-trapezius pain, likely via spinal reflexes. Recent human have confirmed remote effects of dry needling in chronic neck pain. Additionally, dry needling has been shown to influence autonomic function positively in fibromyalgia patients. Although no high-quality trials have explicitly tested a chain protocol in chronic pain, preliminary findings imply that augmenting conventional therapy with distal needling may enhance outcomes. We integrate theoretical frameworks and draw parallels with related therapies to outline the rationale for chain-oriented needling. Gaps include the lack of standardized protocols and limited clinical data. We highlight the potential of viewing dry needling within a kinetic-chain model and call for mechanistic and clinical research to validate whether chain-based approaches yield superior pain relief in chronic musculoskeletal conditions.

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 Keywords

Keywords: dry needling, kinetic chain, myofascial meridians, chronic pain, fascial chain, trigger point, rehabilitation

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Punjabi music's global reach and rising popularity is leading to growing questions about the lyrical content, especially with regard to drug and alcohol references. Already struggling with high rates of drug usage, Punjab finds a cultural dilemma whereby entertainment media can be instrumental in normalizing and even encourage drug use. With an eye toward youthful audiences, the study explores the degree to which Punjabi music and entertainment shape public attitudes, perceptions, and behaviors about drug usage. Based on theories like Social Learning Theory, Cultivation Theory, and the Theory of Planned Behaviors, the study investigates how music including drug-related material can influence social norms, decrease perceived dangers, and aid in behavioural modelling. Preparatory discoveries propose a critical relationship between frequent utilization of Punjabi music and a more tolerant state of mind toward drug use, particularly among people matured. Respondents too details the expanded presentation to drug references in social occasions and a sense of normalization due to the monotonous nature of such substance. Besides, numerous members expresses concerns that these depictions adversely influence the worldwide picture of Punjabi culture and contribute to the disintegration of cultural values.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Keywords: Drugs, Alcohol, Punjabi Music, Entertainment, Culture.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

no

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Creative Commons Attribution 4.0 and The Open Definition

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no

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Creative Commons Attribution 4.0 and The Open Definition