Volume 13 | Issue 5 |

 Abstract

This research explores the impact of artificial intelligence (AI) on architecture and the future employment of architects. AI is altering architectural design, enabling data-driven insights to enhance building efficiency. Beyond design, AI revolutionizes project management, construction, and facility management, streamlining workflows and promoting sustainability. However, its integration presents challenges, including ethical and creative concerns. Architects must adapt by embracing AI education and interdisciplinary collaboration. While AI augments architects' skills, it cannot replace human creativity, cultural sensitivity, and ethical judgment. The profession's future depends on architects leading this transformation, ensuring technology enhances rather than diminishes architectural integrity. To explore this transition, a survey via Google Forms will gather diverse perspectives on AI in architecture, focusing on public sentiment, AI education, and interdisciplinary collaboration. The study aims to provide valuable insights into AI's evolving role in architecture, helping architects navigate this technological transition while preserving their unique vision and ethical responsibilities.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

AI in Architecture, Architectural Design, Building Efficiency, Project Management, Sustainability, AI Education, Interdisciplinary Collaboration, Ethical Concerns, Creativity, Technological Transformation, Future of Architects.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In today's fast-paced and competitive hospitality landscape, delivering exceptional guest experiences is paramount. One of the critical factors influencing guest satisfaction is the efficiency and responsiveness of hotel services. Traditional communication methods such as in-room telephones, intercom systems, or physical visits to the front desk are often time-consuming, prone to errors, and inconvenient for both guests and staff. EaseInn is a QR code-based digital solution designed to modernize and streamline guest service management in hotels. By simply scanning a QR code placed in hotel rooms or common areas, guests are directed to a mobile-responsive web interface. This interface enables them to place requests for room service, housekeeping, checkout support, or technical assistance without the need for app installations or direct staff interaction. The system automates the service request workflow by routing requests directly to the concerned department, minimizing delays and improving service quality. It not only enhances the guest experience through real-time updates but also optimizes staff productivity by digitizing request handling and tracking. This paper explores the system architecture, technical implementation, core functionalities, and the potential for scalability and integration with other smart hotel systems.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Hospitality Technology; QR Code; Guest Service Automation; Contactless Service; Web-Based Interface; Operational Efficiency; Room Service Digitization; Hotel Management System.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In modern grocery shopping, the challenge of precisely measuring loose items, especially grains like wheat, is persistent. It is still done manually and time is wasted in checking the right amount before billing. A fresh approach to tackle this challenge is done through the implementation of a specialized dispenser system. This system aims to revolutionize the weighing process for grains and other loose commodities ensuring smooth grocery shopping. Highlighting the growing demand for precise measurements, the proposed system aims to control the dispenser without direct human intervention, ensuring efficiency in both time and user experience. It focuses on creating a suitable mechanical design for the regulated flow of loose items. The goal is to enhance convenience and accuracy in dispensing products.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

grocery shopping, precision weighing, dispenser system, loose items, grains

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This quantitative research paper examines the entrepreneurial spirit of young sportspersons. The research seeks to examine the motivations, challenges, and effects of entrepreneurship among young athletes through intensive data analysis of 50 respondents. Through a structured survey, the research examines the drivers of young sportspersons towards entrepreneurship, the challenges they encounter, and the effects of their entrepreneurial activities on their professional and personal lives. This research paper examines the entrepreneurial spirit of young sportspersons, with a focus on the nexus of sports and entrepreneurship. As the professional sports landscape continues to grow, many athletes are increasingly looking for opportunities beyond their playing careers, motivated by a need for financial freedom, personal branding, and social responsibility. Employing a quantitative research design, this research surveys a representative sample of young athletes across various sports categories to examine their entrepreneurial intentions, drivers, and perceived barriers. The data gathered through structured questionnaires were analyzed using statistical analysis, and the results show strong correlations between athletic experience, personality, and entrepreneurial aspirations. Results show that the majority of young sportspersons have a strong inclination towards entrepreneurship, with the main drivers being the pursuit of passion, financial security, and the need to make a positive impact in their communities. Additionally, the research identifies common barriers among these athletes, including limited access to resources, mentorship, and business education. The results highlight the need to develop an entrepreneurial spirit within sports programs and provide practical implications for sports industry stakeholders, including coaches, sports organizations, and policymakers. This research adds to the existing literature on sports entrepreneurship and identifies the potential of young athletes as future business leaders.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Entrepreneurship, Sportspersons, Young Entrepreneurs, Quantitative Analysis, Survey, motivations, challenges and impact of entrepreneurship.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study explores the relationship between perfectionism and impostor syndrome in college students, with a focus on self-efficacy as a mediating factor. Data from 300 participants aged 18 to 25 were collected using FMPS, CIPS, and GSE scales. Findings indicate a strong positive link between perfectionism and impostor syndrome, with self-efficacy partially mediating this relationship. Female students reported lower self-confidence and higher impostor feelings than males. The results highlight the importance of interventions that enhance Resilience, Motivation, and Self-Belief, promote achievable goal setting, and address gender-specific Academic Pressures. Such strategies are essential for supporting Academic Outcomes, Emotional Well-Being, and overall Mental Health, thereby fostering Student Success in Higher Education through the Mediation Model.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Perfectionism, Impostor Syndrome, Self-Efficacy, College Students, Gender Differences, Academic Stress, Psychological Well-Being, Mental Health, Resilience, Motivation, Academic Performance, Self-Confidence, Mediation Model, Higher Education, Student Success

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study investigates employee perspectives on HR digitalization within manufacturing organizations in the context of Industry 4.0. It focuses on key factors such as ease of use, training effectiveness, and communication quality, and how these influence employee satisfaction and adoption of digital HR systems. A structured questionnaire was administered to 132 employees, and data were analyzed using SPSS, employing Mann-Whitney U, Kruskal-Wallis H, and Friedman tests. Findings reveal that while employees recognize the benefits of digitalization--such as improved communication and work-life balance--they also face challenges like technical difficulties and limited training. The study concludes that prioritizing employee feedback, continuous support, and system usability is essential for successful HR digital transformation

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

HR digitalization, Industry 4.0,System usability, Training effectiveness, Digital transformation and Employee satisfaction .

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

A Go-kart is a small four wheeled vehicle. Go-kart, by definition, has no suspension and no differential. They are usually raced on scaled down tracks but are sometimes driven as entertainment or as a hobby by non-professionals. Our goal is to design and fabricate the go-kart that offers exceptional performance, driver comfort, and safety. The primary focus is on creating a lightweight kart that delivers impressive performance. Adherence to the rulebook of Edge line Championship is mandatory and significantly influences our objectives. The go-kart, which is propelled by a rear- wheel internal combustion engine without suspension or differential, has been designed in accordance with standard principles. All critical factors and design parameters have been considered, resulting in a thoroughly failure-analysed and ergonomically optimized go-kart. Comprehensive calculations have been conducted for each component, followed by 3D modelling and simulation using professional software tools. The analysis was carried out with different iterations and finally the optimum design of each part of the Go kart was done so as to obtain the optimum result.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Go-kart, Design, Frame, Analysis, Steering System, Braking System, Engine, Transmission, Innovation.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Leaf detection is a critical task in agriculture, aiding in the early identification of plant leaf to ensure optimal benefits. This paper presents a comprehensive approach to automating leaf detection using advanced image processing and deep learning techniques in Python. The methodology involves pre-processing the input images to enhance features and extract meaningful information. Subsequently, a Convolutional Neural Network (CNN) model is trained on a curated dataset comprising healthy plant leaves. The CNN learns to classify leaves into respective categories, enabling automated detection. The trained model is evaluated based on various metrics such as accuracy, precision, assess its benefits. In this paper, the performance of a pre-trained ResNet34 model in detecting disease is investigated. Additionally, a real-world application of the model is demonstrated through predictions on unseen leaf images. The results showcase the efficacy of the proposed approach in accurately identifying plant leaf, laying the foundation for further advancements and integration into agricultural practices.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Image Processing, Convolutional Neural Networks (CNN) , Leaf Detection

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Deep learning has transformed medical imaging, particularly cancer detection. This paper introduces a Vision Transformer (ViT)-based approach for ovarian cancer classification. Unlike CNN-based models such as ResNet-50, ViTs utilize self-attention mechanisms to enhance feature extraction interpretability. The proposed model incorporates Swin Transformers and hierarchical feature fusion techniques, achieving superior classification accuracy. Evaluations on hematoxylin and eosin (H&E) stained histopathology slides reveal that ViTs outperform conventional models, achieving 99.2% accuracy, 99.1% sensitivity, and 99.0% specificity. These findings suggest significantly that ViTs improve early cancer detection rates and assist pathologists in reliable diagnostics.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Ovarian Cancer, Vision Transformer, Swin Transformer, Medical Imaging, Deep Learning, Histopathology, Self-Attention Mechanism, AI in Healthcare.

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Creative Commons Attribution 4.0 and The Open Definition