International Journal of Scientific Research and Innovative Studies https://www.ijsrisjournal.com/index.php/ojsfiles <p><strong>IJSRIS is a Peer Reviewed Open access International Journal publishing multidisciplinary research articles.</strong></p> <p>IJSRIS stands as a platform to bring out the research talent and the works of scientists, academia, engineers, practitioners, research scholars and students. </p> <p>All the submitted articles should report original, unpublished research arcitles, experimental or theoretical and it will undergo the double blind review process. Articles submitted to the journal should meet these criteria and must not be under consideration for publication elsewhere. Manuscripts submitted should follow the style of the journal and are subject to both review and editing.</p> <p>IJSRIS is a scholarly open access Online Journal which helps to academic person as well as student community. IJSRIS provides the academic community and industry for the submission of original research and applications. The journal also invites clearly written reviews, short communications and notes dealing with numerous disciplines covered by the fields. We also accept extended version of papers which are previously published in conferences and/or journals.</p> <p>All the papers selected for publication are also available freely as full-text in on-line.</p> <p><img src="https://www.ijsrisjournal.com/public/site/images/azizmoumen/mceclip0-75ddd441a5a22fe1d11721c1b6f8db70.png" /></p> IJSRIS Journal en-US International Journal of Scientific Research and Innovative Studies 2820-7157 Optimized Social Recommendations Using Graphs and Language Model Integration https://www.ijsrisjournal.com/index.php/ojsfiles/article/view/319 <p>The rapid growth of e-commerce and social-centric digital platforms has heightened the demand for personalized recommendations that account for both temporal user prefer- ences and social relationships. Session-based Social Recommen- dation (SSR) models combine session-based dynamics with social interactions but face challenges in capturing personalized user information and maintaining computational efficiency. Existing SSR methods rely heavily on graph-based algorithms that, while effective, are computationally expensive during inference. To address these limitations, we propose LLM-BRec, a novel framework for efficient session-based social recommendations. Our approach employs a Social-aware Heterogeneous Graph (SHG) to integrate user-item interactions, item-side information, and social network data, enabling the learning of enhanced user and item representations. For session modeling, we leverage a BERT-based model, which provides faster inference by utiliz- ing a self-attention mechanism to capture temporal dynamics within sessions. Additionally, Large Language Models (LLMs) are employed post-training to generate comprehensive user pro- files, optimizing personalization while minimizing computational overhead. Experiments on both social and non-social datasets demonstrate that LLM-BRec significantly outperforms state- of-the-art SSR models in accuracy and efficiency, reducing inference time by 80% while maintaining robust recommendation performance. This work sets a new benchmark for session-based social recommendation by combining lightweight computation with advanced personalization.</p> <p>&nbsp;</p> <p><strong>Received Date:</strong> December 18, 2024&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <strong>Accepted Date:</strong> January 09, 2025&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <strong>Published Date:</strong> February 01, 2025</p> <p><strong>Available Online at </strong><a href="https://www.ijsrisjournal.com/index.php/ojsfiles/article/view/319">https://www.ijsrisjournal.com/index.php/ojsfiles/article/view/319</a></p> <p><a href="https://doi.org/10.5281/zenodo.14878385"><strong>https://doi.org/10.5281/zenodo.14878385</strong></a></p> Anshul Gandhi Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-nd/4.0 2025-02-01 2025-02-01 4 1 25 34 The Influence of Personality on Job Satisfaction of Public Sector Employees https://www.ijsrisjournal.com/index.php/ojsfiles/article/view/312 <p>The relationship between personality and job satisfaction has garnered increasing interest from researchers in recent years. However, few studies have specifically examined the context of the public sector, which presents distinct organizational and cultural characteristics. This article aims to fill this gap by thoroughly examining the impact of personality traits on job satisfaction of public sector employees. A comprehensive review of empirical literature was conducted, including quantitative, qualitative, longitudinal, and comparative studies. The results show that certain personality traits, such as conscientiousness and emotional stability, are particularly determinant for job satisfaction of public servants. These traits seem to be in line with the requirements of rigor, performance, and stress management inherent to the public sector. Conversely, other traits like extraversion and agreeableness, although more strongly related to satisfaction in the private sector, play a less crucial role in the public context. The article also explores the underlying mechanisms of these relationships, drawing on qualitative studies that reveal the importance of recognition of efforts, balance between demands and resources, as well as the fit between personality and work environment. Practical implications for human resource management in the public sector are then developed,</p> <p>particularly in terms of recruitment, task assignment, and competency development.</p> <p> </p> <p><strong>Keywords :</strong> Personality, Job Satisfaction, Public Sector, Personality Traits, Human Resource Management.</p> <p> </p> <p><strong>Received Date:</strong> December 18, 2024 </p> <p><strong>Accepted Date:</strong> January 09, 2025 </p> <p><strong>Published Date:</strong> February 01, 2025</p> <p><strong>Available Online at </strong><a href="https://www.ijsrisjournal.com/index.php/ojsfiles/article/view/312"><strong>https://www.ijsrisjournal.com/index.php/ojsfiles/article/view/312</strong></a></p> <p><a href="https://doi.org/10.5281/zenodo.14782935"><strong>https://doi.org/10.5281/zenodo.14782935</strong></a></p> Oursoula BAYAD Assia BENABID Touri BOUZEKRI Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-nd/4.0 2025-02-01 2025-02-01 4 1 01 06 Urban mobility in Morocco ahead of the FIFA World Cup in 2030: current situation, challenges and prospects https://www.ijsrisjournal.com/index.php/ojsfiles/article/view/313 <p>In recent decades, Morocco has witnessed considerable advancement in urban mobility, largely due to the establishing of contemporary infrastructure such as tramways and Bus Rapid Transit (BRT) systems. Nevertheless, the country continues to confront significant structural impediments that impede the implementation of genuinely sustainable mobility solutions. This paper examines the principal developments achieved, particularly in the period preceding the 2030 World Cup, while also identifying persistent deficiencies, including inadequate infrastructure, a lack of institutional coordination, and a reliance on private vehicles. Furthermore, this paper presents an in-depth analysis of the negative externalities of mobility, such as congestion and pollution, while emphasizing the potential benefits of new technologies and the transition to intelligent mobility. It thus proposes a reflection on the strategies to be adopted to meet the challenges of urban mobility in Morocco by 2030, considering economic, environmental, and social requirements.</p> <p> </p> <p><strong>Key words:</strong> Urban mobility, Sustainability, Intelligent mobility, FIFA World Cup, Intelligent transport system</p> <p><strong>Received Date:</strong> December 18, 2024 </p> <p><strong>Accepted Date:</strong> January 09, 2025 </p> <p><strong>Published Date:</strong> February 01, 2025</p> <p><strong>Available Online at </strong><a href="https://www.ijsrisjournal.com/index.php/ojsfiles/article/view/313"><strong>https://www.ijsrisjournal.com/index.php/ojsfiles/article/view/313</strong></a></p> <p><a href="https://doi.org/10.5281/zenodo.14782976"><strong>https://doi.org/10.5281/zenodo.14782976</strong></a></p> <p> </p> Elbroumi Soufiane Assaad Idrissi Maha Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-nd/4.0 2025-02-01 2025-02-01 4 1 07 21 Evaluating Safety Management Practices in the Phosphate Mining Industry: A Case Study of OCP Morocco https://www.ijsrisjournal.com/index.php/ojsfiles/article/view/314 <p>This study evaluates the safety management practices at OCP Morocco, focusing on their impact on worker safety and accident reduction in phosphate mining operations. A mixed-methods approach was employed, involving the analysis of safety audits, employee surveys, and interviews with key safety personnel. The results indicate that the introduction of automated monitoring systems and regular employee safety training have significantly reduced incidents. However, challenges remain in adhering to international safety standards, and resistance to new technologies persists among some workers. Recommendations for enhancing safety practices include improving compliance with safety regulations and investing in advanced safety technologies.</p> <p> </p> <p><strong><em>Key words:-</em></strong>Phosphate mining, OCP Morocco, Worker safety, Safety management systems, Accident reduction.</p> <p><strong>Received Date:</strong> December 18, 2024 </p> <p><strong>Accepted Date:</strong> January 09, 2025 </p> <p><strong>Published Date:</strong> February 01, 2025</p> <p><strong>Available Online at </strong><a href="https://www.ijsrisjournal.com/index.php/ojsfiles/article/view/314"><strong>https://www.ijsrisjournal.com/index.php/ojsfiles/article/view/314</strong></a></p> <p><a href="https://doi.org/10.5281/zenodo.14783013"><strong>https://doi.org/10.5281/zenodo.14783013</strong></a></p> <p> </p> Ismail Haloui Li Yang Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-nd/4.0 2025-02-01 2025-02-01 4 1 22 24