Volume 13 | Issue 4 |

 Abstract

The economic decline of France in the 18th century was intricately tied to its aggressive military expenditures, which severely strained the state's finances and laid the groundwork for revolutionary upheaval. Major conflicts such as the war of the Spanish succession (1701-1714), the war of the Austrian succession (1740-1748), the seven years' war (1756-1763), and the American war of independence (1775-1783) cumulatively contributed to an alarming rise in public debt, estimated to have reached 4 billion livres by 1789, which would approximate EUR100 billion in contemporary economic terms. This fiscal crisis was exacerbated by a regressive tax system that exempted the clergy and nobility while overwhelmingly burdening the peasantry and urban poor. Despite the efforts of reformist finance ministers such as Turgot, Necker, and Calonne, attempts at restructuring state finances were systematically blocked by entrenched aristocratic interests. The objective of this study is to investigate the causal connection between war-induced debt, socio-economic instability, and revolutionary sentiment in late 18th-century France. Using a qualitative methodology to historical research, the paper examines primary financial documents, official records, and secondary scholarly analyses. The study focuses on six important questions concerning fiscal mismanagement, unequal taxation based on social class, the reasons behind the failure of reform efforts, and the influence of military funding in sparking revolutionary transformations. The results indicate that the downfall of the French monarchy was not solely due to poor financial management, but rather a consequence of continuous military overextension, feudal privileges, and resistance to economic progress within the institutions. By anchoring the discussion within the broader frameworks of fiscal sociology, political economy, and revolutionary theory, this paper concludes that the revolution of 1789 was fundamentally precipitated by an unsustainable fiscal regime shaped by war, privilege, and failed reform. This case also provides a broader perspective on how unresolved financial crises in autocratic systems can serve as catalysts for political revolution and systemic transformation.

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 Keywords

French Revolution, livres, wars, debt, fiscal, economic collapse

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 Abstract

Tendinitis is a common occupational health issue among housekeeping staff due to repetitive physical tasks and improper ergonomic practices. This study evaluates the effectiveness of a structured teaching programme aimed at preventing tendinitis among housekeeping personnel in Rajindra Hospital, Patiala. A pre-experimental one-group pre-test post-test design was employed, involving 60 housekeeping staff selected through purposive sampling. A structured questionnaire was used to assess knowledge before and after the intervention. The post-test scores showed a statistically significant improvement, indicating the success of the teaching programme. The study concludes that health education can play a pivotal role in preventing work-related musculoskeletal disorders like tendinitis

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 Keywords

Tendinitis, Structured Teaching Programme, Housekeeping Staff, Occupational Health

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Creative Commons Attribution 4.0 and The Open Definition

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Skin diseases are among the most common health concerns worldwide, affecting millions of people every year. Early detection plays a crucial role in preventing complications and ensuring timely treatment. This project, titled "Enhancing Healthcare Decision: Image Processing Techniques for Detection of Skin Diseases," aims to build a web-based system for automated skin disease classification using Convolutional Neural Networks (CNN). The front-end of the system is developed using React JS, providing users with an intuitive interface to upload skin lesion images. Flask is used as the backend framework to handle API requests and communicate with the CNN model, which processes the images and predicts the likelihood of various skin diseases. The model is trained on a large dataset of skin lesion images and utilizes advanced image processing techniques to enhance prediction accuracy. Our system aims to assist healthcare professionals by providing quick and reliable diagnostics, reducing the burden on clinical resources. This project demonstrates the effectiveness of deep learning in medical applications and highlights the potential of integrating machine learning models with modern web technologies.

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 Keywords

Skin Disease Detection, Convolutional Neural Network, Image Processing, React JS, Flask, Deep Learning, Healthcare Technology, Medical Diagnostic

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The evolution of digital recruitment has significantly transformed the landscape of human resource management, particularly in large multinational corporations like Amazon. This study investigates the impact of digital recruitment processes on employees at Amazon's Chettipalayam warehouse in Coimbatore. With the widespread use of AI-based screening, online assessments, and automated on boarding systems, recruitment has become more efficient but not without challenges. The research aims to understand employee perspectives regarding digital hiring, the difficulties they face, and its effect on job satisfaction and organizational inclusion. The study is based on primary data collected from 80 employees using structured questionnaires and analyzed using statistical tools like percentage analysis, Likert scale, rank correlation, chi-square test, and t-test. Findings show that although digital recruitment improves hiring speed and accessibility, it can lead to digital exclusion, lack of personalized communication, and increased pressure due to algorithm-based evaluations. The study recommends integrating human interaction with digital tools to enhance inclusivity and employee satisfaction.

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Recruitment Process, Human Resource Management, Employees

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Creative Commons Attribution 4.0 and The Open Definition

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This study investigates the attitudes of parents in Coimbatore towards sales promotions of confectionery products for children. It explores the factors that influence parents' purchasing decisions, their purchasing behaviour, and their concerns regarding the impact of sales promotions on children's consumption. A survey of 120 parents was conducted. The findings indicate that while parents are influenced by sales promotions, particularly price-based incentives, they also have significant concerns about the health implications of confectionery products, especially concerning sugar content and dental health. The study concludes that confectionery marketers need to consider these dual influences to develop effective and responsible promotional strategies.

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Confectionery product

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Energy Consumption Forecasting, Deep Learning, LSTM, Transformer, Hybrid Model, XGBoost, Time Series Analysis, JERICHO-E-usage Dataset, Sustainable Energy, Machine Learning

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Abstract-- Effective quality control in luxury leather goods manufacturing requires objective assessment methodologies. This paper introduces an automated leather bag quality analysis system with a three-layer architecture: input for image preprocessing, processing for defect detection, and output for results visualization. By integrating threshold analysis with edge analysis, the system achieves comprehensive defect identification across varying leather textures. Results demonstrate the system's ability to reliably detect material authenticity and surface defects while quantifying quality metrics with high precision. We conclude that approximately 95% of manual inspection inconsistencies can be eliminated through this approach. This methodology offers potential applications beyond leather goods to other natural material products requiring automated quality assessment.

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Keywords: computer vision; defect detection; quality control; image processing; leather manufacturing

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Creative Commons Attribution 4.0 and The Open Definition

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This study explores the evolving landscape of digital food service marketing with a focus on the impact of user reviews and ratings on brand reputation in Zomato, specifically in Coimbatore city. With the increasing reliance on digital platforms and consumer-generated content, reviews and ratings have become a vital part of brand perception and customer decision-making. The study aims to understand customer perceptions, identify key influencing factors, and assess the extent to which online reviews shape restaurant reputation. Data was collected from 125 respondents through structured questionnaires using a combination of exploratory and descriptive research methodologies. The analysis utilizes tools such as simple percentage analysis, ranking, and Likert scale analysis to interpret consumer behavior and their interaction with online reviews. Findings reveal that factors such as star ratings, reward programs, social media engagement, and review authenticity significantly influence customer trust and restaurant selection. The study concludes with recommendations to strengthen review credibility, improve brand responsiveness to feedback, and leverage digital marketing strategies to enhance brand reputation in the competitive online food service environment.

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 Keywords

User reviews and ratings, Food delivery, Brand reputation.

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Creative Commons Attribution 4.0 and The Open Definition

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This paper investigates how the European Union evolves its position in global governance along with its expanding control in economic policies and political relations and security management. The EU operates as a distinct supranational body which exercises substantial power through its creation of regulations as well as its diplomatic initiatives and business trade systems. The research investigates how EU foreign policy develops through institutional mechanisms between the European Commission and European Parliament alongside the European Council. The paper dedicates significant attention to analyze how the EU influences trade at the global level and manages climate change and peacekeeping measures. Through multilateralism the EU demonstrates its status as a political leader while utilizing economic power together with normative influence to construct international agreements between nations and organizations. The analysis covers the EU involvement in international security operations that includes its work for crisis management activities along with peacekeeping roles and counterterrorism efforts. Because of its extensive worldwide power, the EU continues to confront internal and external difficulties. Historical events like Brexit along with nationalistic trends and social and economic differences between member nations join with geopolitical tensions against countries like the United States, China and Russia regarding international coordination power of the EU. Foreign policy operations of the EU face difficulties due to the complex processes needed to reach agreement among its 27 member states. The research terminating statement points out that the EU continues being fundamental in international matters yet its worldwide impact requires developing national unity combined with better institutional operations and planetary geopolitical developments. Continuous reforms coupled with strategic partnerships will guarantee the EU's position as a major governing authority on the world stage.

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European Union (EU), global governance,foreign policy, multilateralism, trade policy, security and defense, geopolitical challenges, Brexit ,International diplomacy

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Abstract Purpose: The purpose of this study is to investigate the impact of personality traits and external factors on the use of Chat GPT, a generative AI tool, among university students. Understanding the psychological and technological factors of AI use is critical for optimizing learning outcomes and increasing digital engagement as it becomes more integrated in higher education. Design/Methodology/Approach: The research takes a quantitative approach, with a standardized questionnaire delivered to university students. The study is based on the Big Five Personality Traits framework and known technology adoption frameworks, including the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT). The data will be evaluated using statistical methods such as SPSS to investigate the correlations between personality traits, perceived utility, simplicity of use, and behavioral intent to use Chat GPT. Findings: According to preliminary expectations, personality traits such as openness and conscientiousness are predicted to correlate positively with the perceived usefulness and simplicity of use of Chat GPT. Additionally, social influence and favorable environments are predicted to have a substantial impact on adoption behavior. These findings are intended to emphasize the complex interaction of individual psychological elements and external technical cues in affecting user behavior. Practical Implications: The findings of this study can help educators, developers, and institutions create AI-based instructional tools that are suited to different personality types and user preferences. Institutions may boost student engagement, increase learning efficiency, and promote responsible AI use in academic contexts by matching implementation techniques with student behavior and personality profiles. Originality/Values: This study offers new insights by combining personality psychology with technology adoption frameworks to evaluate Chat GPT usage in higher education. It addresses a significant research vacuum by concentrating on both system-related aspects and user-centric psychological motivations, providing a more comprehensive understanding of AI adoption behavior.

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 Keywords

Personality Traits, ChatGPT Adoption, University Students, Technology Acceptance Model (TAM), UTAUT, AI in Education, Big Five Model, AI Tools, Higher Education, and Digital Learning

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Creative Commons Attribution 4.0 and The Open Definition