Volume 13 | Issue 10 |

 Abstract

The study is about the complicated problem of teaching and learning English as a second or foreign language, in particular, in the non-native backgrounds. It highlights the linguistic, cultural, psychological and socio-economic hindrances that rob the success of linguistic acquisition. The issues facing the teachers are lack of training, outdated manner of doing things, overcrowded classes and on the other hand, the learners have issues of being lowly motivated, full of anxiety and are not exposed to the use of real languages. The study follows a qualitative and exploratory study because it involves the synthesis of secondary information to provide a general picture of these challenges. The findings indicate the need to invest more in teacher training or development, use learner-centered pedagogies and enhance access to resources when breaking through the barriers. An overall solution to all three issues has the potential of facilitating improved communicative competence and widening academic, professional, and social opportunities of learners in the globalized world.

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 Keywords

English Language Teaching, Language Learning Challenges, Teacher Training, Socio-economic Barriers, Communicative Competence

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Creative Commons Attribution 4.0 and The Open Definition

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In Today's technological world images play a vital role. With the tremendous growth of digital media, protecting and transferring of images has become progressively important. With the usage of images everywhere, there arise the storage and network issues during transfer of data. To overcome this disadvantage a concept called Compression is introduced where the redundant data is eliminated. In this paper we discuss about compression, need for compression, types of compression, different types of compression techniques that are used and the new method we are going to use. This study introduces a hybrid framework that combines image compression, watermarking and hexadecimal conversion to protect data. This method not only verifies the authenticity but also prevents tampering or unauthenticated or unauthorized access. The proposed method establishes equilibrium between compression efficiency and data security, making it experimental for real world applications.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Image Compression, Digital Watermarking, Hexadecimal Conversion, Key Insertion, Secure Image Transmission.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Web applications are constantly targeted by attackers due to their role in delivering interactive services and processing sensitive information. Vulnerabilities such as SQL Injection (SQLi), Cross-Site Scripting (XSS), Cross-Site Request Forgery (CSRF), and insecure coding practices can compromise both data integrity and user trust. This review synthesizes findings from representative studies, highlighting de tection and mitigation approaches including AI-driven models, static and dynamic analysis, automated remediation tools, and platform-specific scanners. By examining objectives, methods, strengths, and limitations, the paper identifies patterns and practical lessons for embedding robust security practices throughout the soft ware development lifecycle.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

WebApplication Security, SQL Injection, Cross-Site Scripting, Detection Frameworks, Secure Coding, Artificial Intelligence

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Creative Commons Attribution 4.0 and The Open Definition

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Two-factor authentication (2FA) has become essential for digital security as mobile devices and Internet-of-Things (IoT) environments shape our daily interactions. It helps reduce risks linked to password issues like phishing and credential theft. This review paper examines how acoustic based authentication has evolved, focusing on active sound sensing methods that provide secure, zero-interaction 2FA. We start with early ambient audio techniques for shared key generation. The discussion then moves to sensor fusion methods, proximity detection in voice-enabled IoT settings, and finishes with advanced echo-based systems like Proximity-Echo. We explain the reasons behind each development phase and compare the technical trade-offs, especially regard ing usability, attack resistance, and efficiency. We also discuss the implications for embedded mobile systems. The paper ends with a practical workflow that combines active beep emission and echo signature analysis. We also suggest future research areas, including multi-modal sensor integration, post-quantum adaptations, and energy-efficient designs.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Two-Factor Authentication (2FA), Active Sound Sensing, Proximity Detection, Acoustic Fingerprinting, Zero-Interaction Authentication, Relay Attacks, Man-in-the-Middle Attacks, IoT Security

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Creative Commons Attribution 4.0 and The Open Definition

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Sri Sri Aniruddhadeva, born in the 16th century, was an eminent saint-scholar and a social reformer in Assam. He played a significant role in the growth of the Bhakti movement in the region. The Bhakti movement in Assam is unique because it is a syncretic blend of various religious and philosophical traditions, including indigenous beliefs. By the time Aniruddhadeva came onto the scene, the Bhakti movement was already a strong social and spiritual force in Assam, primarily due to the contributions of Sankardeva, another saint-scholar, who had initiated the Neo-Vaishnavism movement in Assam. Aniruddhadeva took it upon himself to disseminate the teachings and philosophies further. He was instrumental in composing a large number of devotional songs, dramas, and theological works. His writings were largely in the Assamese language, making them accessible to the common people, and he encouraged the use of local idioms and styles in religious discourse, which added a unique Assamese flavor to the Bhakti movement. Aniruddhadeva was also a social reformer who worked tirelessly to dismantle the rigid caste system and other social inequalities. He advocated for a society based on devotion to God rather than birth or social standing. His contributions also included the establishment of Satras, or monastic centers, that became hubs of social and cultural activities. These Satras not only functioned as centers of religious discourse but also promoted social cohesion by bringing together people from different strata of society. Moreover, Aniruddhadeva's role in promoting communal harmony is noteworthy. His teachings emphasized the essential unity of all religious paths and encouraged an open-minded approach to the interpretation of religious texts. This has been pivotal in making Assam's Bhakti movement one of the most inclusive and diverse forms of Bhakti in India. Sri Sri Aniruddhadeva was a key figure in the growth of the Bhakti movement in Assam. His work in spreading the teachings of Neo-Vaishnavism, initiating social reforms, and fostering communal harmony has left an indelible mark on Assamese society and culture. Sri Sri Aniruddhadeva, played a significant role in propagating the Bhakti movement in Assam. He contributed to the Neo-Vaishnavism movement in Assam. Aniruddhadeva's teachings focused on love, devotion, and surrender to God. His contributions are not only religious but also social and cultural. He composed hymns, organized community prayers, and was involved in translating important texts. Sri Sri Aniruddhadeva was a saint and a significant figure in the Neo-Vaishnavism movement in Assam. He lived in the 16th century and Aniruddhadeva's contributions were multifaceted, including religious, social, and cultural arenas.

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 Keywords

Bhakti Movement, Sankardeva, Aniruddhadeva, Vaishnavisim,

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Quality and relevance of features used in training are key factors in machine learning models' efficacy and dependability. Overfitting, higher computational complexity, and worse predictive performance can result from the redundant or unnecessary features that are frequently present in high-dimensional datasets. This work suggests a thorough architecture for feature selection that blends embedding, filtering, and wrapping methods to find the most important predictors while reducing noise. For the best subset selection, wrapper-based recursive feature elimination (RFE) is used after filter techniques like correlation analysis and chi-square tests are used to eliminate redundant features. To guarantee robust selection during model training, embedded strategies are employed, such as Lasso and tree-based feature significance algorithms. The suggested approach increases accuracy across a variety of machine learning techniques, decreases training time, and improves model interpretability. Comparing experimental outcomes to baseline models with all characteristics, and the F1-score show notable increases. This study highlights how crucial systematic feature selection is as a first step in creating scalable and effective predictive modelling pipelines.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Feature Selection, Dimensionality Reduction, Machine Learning, Recursive Feature Elimination, Lasso Regression, Model Optimization, Predictive Modeling

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Creative Commons Attribution 4.0 and The Open Definition

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The longevity and success of the Metaverse as a socio-technical medium are critically dependent on sustained user engagement, referred to as continuance intention. This paper employs a systematic literature synthesis to model the antecedents of continuance intention, focusing specifically on non-technological factors: Trust and Privacy Protection. Empirical research confirms that for experienced users, continuance intention is positively affected by perceived usefulness, enjoyment, innovativeness, and crucially, trust and satisfaction. This aligns with consumer data prioritizing data/privacy protection (77%), ease of use (75%), and affordability. We identify a fundamental governance deficit, noting that current architectural models lack dedicated layers for enforcing accountability and interoperability. Furthermore, the emerging neurosociological paradigm, which uses implicit neural data (interbrain synchrony) to dynamically adjust virtual environments, introduces acute ethical risks to cognitive liberty, demanding specialized regulatory protection. This research validates a framework wherein sustained adoption is contingent upon the mandatory integration of explicit socio-regulatory mechanisms--such as unified digital identity systems and Neurorights legislation --into the core architecture, transforming external policy into internal system design to build user confidence and govern the future of immersive interaction.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Metaverse, Human-Computer Interaction (HCI), Extended Reality (XR), User Adoption, Continuance Intention, Trust, Privacy Protection, Neuro-Governance, Structural Equation Modeling, Neurorights.

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Creative Commons Attribution 4.0 and The Open Definition

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Amitav Ghosh's fiction addresses significant topics related to human emotions and relationships across various social and political contexts. His storytelling connects the readers' sensitive emotions with the essential emotions of the characters. His fiction possesses a broad allure, resonating with readers worldwide. He skillfully integrates topics with the societal issues arising in the creation of a literary masterpiece. Amitav Ghosh, as a conforming academic of the postmodern era, advocates for a notion of art that fulfills both the analytical demands of literary critics and the emotional needs of general readers. As both a writer and educator, Ghosh possesses a keen insight into human misery and anguish, and his psychological acumen about delicate interpersonal relationships is exceptional. This research paper examines the themes of dilemma and tragedy in the books of Amitav Ghosh.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

quandary, captivating, ethnography, consequence, kaleidoscope

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Creative Commons Attribution 4.0 and The Open Definition

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Businesses must optimize their sales income in order to be profitable in ever-changing markets. Demand elasticity, competitive pricing, and real-time market variations are not taken into account by traditional approaches like cost-based pricing, rule-based pricing, and basic regression models, which results in less-than-ideal revenue outcomes in this research, we enhance pricing tactics by combining cutting-edge mathematics and machine learning approaches. The price-demand connection is modelled using quadratic regression, and high-accuracy demand forecasting is achieved by integrating long-term sequence learning (LSTM) with short-term trend analysis (ARIMA) in ARIMA-LSTM hybrid models. Our approach uses reinforcement learning (Q-learning) and game theory (Nash Equilibrium) to dynamically modify pricing in response to real-time changes in demand and competitive activities. Higher revenue optimization, improved demand forecasting, and improved competitive positioning are all made possible by these techniques, which also allow for clever pricing schemes that adjust to customer behaviour and market developments.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Dynamic Pricing, Revenue Optimization, Price-Demand Modelling, ARIMA-LSTM Hybrid Forecasting, Reinforcement Learning, Q-Learning, Game Theory, Intelligent Pricing Strategy

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Creative Commons Attribution 4.0 and The Open Definition

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The material business in India is the principal business that has delivered enormous work especially for both disabled and unskilled workers. Soap business is one of the major earning for many home makers, even as a type of partial/side business. Soaps are used as cleansing and emulsifying agent, available in liquid and bar forms and comprise a wide variety of fragrances. The workers are in risk of several problems or diseases, as because of lack of adequate knowledge regarding hazards and preventive measures. This study mainly aims to identify the knowledge of occupational health hazards and to evaluate the effectiveness of a self instructed educational module among workers of a selected Soap Factory, in Kanpur city, India. A sample of 70 women workers working in the Soap factory, were selected by random sampling technique. One group pre-test post-test design was used and the data was collected using self structured questionnaire. The pre test score shows majority of respondents had poor knowledge (52.85%) while only 7.14% demonstrated adequate knowledge. After administration of self instructed education module, the post-test shows that, 20% of participants demonstrated high knowledge, while low knowledge was reduced to 35.71%. The pre test mean knowledge score was 9.5 (SD 4.56) and the post test mean knowledge score was 12.84 (SD 5.65), with the t-value of 3.88. This indicates the effectiveness of the self education module.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Soap Factory, Worker, Occupational Health Hazards, Educational Module

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Creative Commons Attribution 4.0 and The Open Definition