8333 research outputs found
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Email Spam Detection: Leveraging Fine-Tuned Transformer Models with Attention Mechanism
No full textDue to ongoing threats to email security, it is becoming increasingly important to use advanced methods to consistently get rid of unwanted emails. To meet this need three advanced machine learning (ML) techniques DistilBERT, XLM-RoBERTa, and RoBERTa are tested to see how well they can find spam emails. Along with that pre-trained ML systems are tuned on the Enron-Spam dataset, which is a standard way to test how well spam identification works. Metrics like accuracy, precision, recall, and F1-score are used to test and analyze these improved systems in great depth to see how well they work. The research also investigates how focusing features built into these designs can make the models more accurate and clearer. The results show that the best method is the improved DistilBERT model, which is 96% accurate. The study shows that focusing mechanisms are important for making these models work better by helping with more accurate feature extraction and classification. Furthermore, this study adds to the progress in email security by showing how advanced ML can be used to find spam and how important narrowing methods are for making models work better. These findings are important for making spam filtering technologies better and more reliable. This will improve email security and the user experience in today's digital world
Personalized Skincare Recommendations Using Multi-Modal Deep Learning Techniques
No full textSkincare is the most essential for health as skin issues which are untreated may lead to serious problems. But finding the right products for skincare is challenging because everyone's skin is different. People have various skin types such as oily, dry, sensitive makes hard to find the products which is suitable to everyone. This study uses deep learning techniques which is used to create recommendation system that helps to find the best product based on their skin types. Unlike older methods which use limited data and algorithms, our approach uses cutting edge technology to analyze large amounts of diverse data. It helps to understand how different skin types interact with various skincare products. It also collects feedback from users to make sure that the system provides personalized recommendations which are accurate and effective. This method aims to improve skin health and provide user satisfaction by offering skincare solutions aligned to individual needs
E-Learning for Agile Teams: A Qualitative Study of Business Oriented E-Learning Platforms on Enhancing Team Efficiency in the Irish Technology Sector
No full textThe purpose of this qualitative study was to review the influence of business-oriented electronic learning systems on increasing team effectiveness within the local technology sector in Ireland. Ten participants from various Irish IT businesses participated in semi-structured interviews as part of a primary qualitative data-gathering method. This study which was based on thematic analysis investigated the integration of e-learning platforms, collaborative use of technology resources, and the impact on collaboration and productivity. Findings have revealed that e-learning platform integration in the company has resulted in increased team cooperation, knowledge sharing and task coordination. The assistance of Slack, Trello and Zoom as collaborative tools was significant as they facilitated the process of communication and project management. Nonetheless, obstacles including cultural resistance and scalability problems were considered which emphasise the importance of special training and support for them. Based on this analysis, a need was seen for further research on, how, the evolution of integration of e-learning, affects team dynamics and organisational performance over time. Overall, the analysis obtained from this research helped in giving a clear picture of the part played by e-learning platforms in improving productivity within the Irish technology sector
Cosmetic Brand Preferences: An Analogy between Irish and Indian Youth
No full textThis study delves into patron behaviour within the cosmetics marketplace, with a specific emphasis at the elements influencing buying picks and logo possibilities, particularly concerning L'Oréal and Maybelline. Primary information turned into accumulated thru surveys administered to a numerous sample, spanning a long time from 18 to over 50, with a concentration within the 25–40 age range. The contributors protected people of Irish and Indian nationalities, with a minor illustration of Indian respondents. The findings reveal that customers make splendour purchases on a month-to-month or irregular basis, with skin care and haircare emerging as the most well-known classes. Influential elements which consist of social media presence, logo recognition, pricing, and product satisfactory drastically form clients' buying selections. The analysis gives treasured insights into how age, gender, nationality, and educational backgrounds effect purchaser preferences, with implications for each L'Oréal and Maybelline's advertising strategies. Moreover, the test underscores the significance of digital marketing and advertising strategies in shaping purchaser perceptions of beauty manufacturers. While initial observations propose differing logo choices among Irish and Indian youngsters, in addition research is warranted for a comprehensive records. Overall, this has a study contributes vital insights into consumer behaviour inside the cosmetics market, facilitating informed advertising and advertising and marketing strategies and enriching enterprise information, for L'Oréal and Maybelline
Studying the Evolution and Development in the Field of Bid and Proposal Management
No full textThis research paper examines the impact of technological innovations and automation on bid and proposal management, a critical process for securing contracts and fostering business growth. The study uses a mixed methods approach that combine both quantitative and qualitative primary data collection method to analyse the key factors shaping the development of bid and proposal management field. It also assesses the key challenges and examines the role of automation in increasing the efficiency and effectiveness of bids and proposals. The quantitative aspect involves survey questionnaires involving bid and proposal management professionals along with examining the adoption and impact of automation tools. The qualitative component includes semi-structured interviews with bid and proposal management professionals and experts to gain in-depth insights on the same.
The study contributes to the understanding of the evolution and development of bid and proposal management practices, highlighting the critical role of automation and technology in enhancing efficiency, quality, and organisational competitiveness. The analysis reveals a pronounced adoption of automation tools, including proposal generation software and workflow automation platforms, which have been instrumental in streamlining processes, enhancing collaboration, and improving decision-making capabilities within the field. Despite the evident benefits associated with these technological advances, the research also identifies challenges associated with their integration into the current practices. These challenges highlights the need for further research aimed at overcoming adoption challenges and maximising the potential of these innovations.
By addressing gaps in existing literature and focusing on the impact of digital transformation and automation, this research aims to contribute valuable insights and sets the foundation for future academic research in this ever-evolving field of bid and proposal management
Job Satisfaction, Productivity and achieving a Work-Life Balance. A comparative analysis on Traditional vs. Hybrid Working Environments conducted based on Civil Servants
No full textThis paper titled: “Job Satisfaction, Productivity and achieving a Work-Life Balance. A comparative analysis on Traditional vs. Hybrid Working Environments conducted based on Civil Servants”, aims to provide insight and enhance employee well-being and organizational effectiveness in the ever-evolving landscape of work. Through a mixed-methods approach, incorporating quantitative surveys and qualitative insights, the study delves into the factors shaping job satisfaction among civil servants. Quantitative research analysis reveals high levels of job satisfaction among civil servants working in a hybrid environment. Qualitative insights further elaborate on the role of factors such as work-life balance, professional development opportunities, and supportive leadership in shaping job satisfaction. The findings underscore the importance of organizational factors in fostering satisfaction within the civil service sector. Overall, this research contributes to the advancement of knowledge in organizational behaviour and human resource management, offering valuable insights for policymakers and organizational leaders. By understanding the determinants of job satisfaction, organizations can develop evidence-based strategies to enhance employee well-being and organizational effectiveness in the ever-evolving landscape of work
Ultra-Wide Band Radar Empowered Driver Drowsiness Detection with Convolutional Spatial Feature Engineering and Artificial Intelligence
No full textDriving while drowsy poses significant risks, including reduced cognitive function and the potential for accidents, which can lead to severe consequences such as trauma, economic losses, injuries, or death. The use of artificial intelligence can enable effective detection of driver drowsiness, helping to prevent accidents and enhance driver performance. This research aims to address the crucial need for real-time and accurate drowsiness detection to mitigate the impact of fatigue-related accidents. Leveraging ultra-wideband radar data collected over five minutes, the dataset was segmented into one-minute chunks and transformed into grayscale images. Spatial features are retrieved from the images using a two-dimensional Convolutional Neural Network. Following that, these features were used to train and test multiple machine learning classifiers. The ensemble classifier RF-XGB-SVM, which combines Random Forest, XGBoost, and Support Vector Machine using a hard voting criterion, performed admirably with an accuracy of 96.6%. Additionally, the proposed approach was validated with a robust k-fold score of 97% and a standard deviation of 0.018, demonstrating significant results. The dataset is augmented using Generative Adversarial Networks, resulting in improved accuracies for all models. Among them, the RF-XGB-SVM model outperformed the rest with an accuracy score of 99.58%. © 2024 by the authors
The Impact of Performance Appraisal on Employees' Performance: A Case Study of Employees working in the Nigerian Private Sector
No full textThe rate of under-producing organizations in Nigeria is a phenomenon that requires critical investigation, as the number of organizations operating below standard continues to rise. Previous studies have linked these low outputs to the unmotivated attitudes of employees and suggested that performance appraisals are crucial for identifying and addressing training needs. This study investigates how performance appraisal systems impact employee productivity within the Nigerian private sector, focusing on three key areas: the frequency of appraisals, the quality of feedback, and the availability of training and development opportunities. Using a quantitative approach with stepwise regression analysis, the study analyzes data from 50 employees, employing a non-probability sampling approach to ensure relevant representation. The study reveals that frequent performance appraisals and high-quality feedback have a significant positive impact on employee productivity. Additionally, access to training and development opportunities further enhances performance. These findings suggest that well-implemented performance appraisal systems can lead to considerable improvements in organizational effectiveness, highlighting their crucial role in optimizing employee performance and driving overall organizational success. To foster better organizational performance, it is recommended that companies increase the frequency of appraisals, improve feedback mechanisms, and ensure that training and development opportunities are readily available
AI in recruitment and its relationship with employer branding: Exploring candidate’s perception within the Irish market
No full textNowadays Artificial Intelligence (AI) has attracted significant attention and is transforming businesses in a rapid, more agile way through automation. Bringing unforeseen opportunities to the working environment. This paper’s main aim is to generate insights on the possible relation AI-based technology applied in the recruiting process has with employer branding within the Irish context, through empirical investigation of applicant’s perception.
Being a revolutionary factor, AI, can represent a shock to the system and foster new ways of working. Therefore, it is imperative to understand the powerful role it plays at recruiting and what challenges and opportunities it carries to the Human Resources (HR) strategy, through company’s image, thus impacting its attraction and retention
Zoomers to the Rescue: How the Irish Public Service can overcome its recruitment gaps by attracting and retaining Generation Z
No full textThis dissertation explores how the Irish public service can address its recruitment challenges by attracting and retaining Generation Z candidates. The Irish public and civil service currently faces issues in recruiting the “Generation Z” age group, at a time when the public sector is also facing a retirement “cliff edge” as many of its older workforce retires. The purpose of this research is to explore how best to attract this cohort from the perspective of public service recruiters and hiring managers. Qualitative research was carried out using semi-structured interviews with 10 senior civil service staff members who fit the identified criteria. The interviews, which utilised open-ended questions, were designed with a view to addressing the research question and objectives. The researcher subsequently thematically analysed the results, critically reviewing them alongside the identified existing literature on the topic of Generation Z, their workplace values and preferences, and public sector recruitment. This research demonstrates that the Irish public service is not currently attracting Generation Z candidates in any significant numbers, but that there is potential to entice this cohort by emphasising the rewarding “mission” of the public service and enhancing and promoting the current benefits on offer, particularly at entry level. Furthermore, the research shows that promoting and implementing a more adaptable, flexible approach to employment will be critical if the public service is to better attract Generation Z candidates and establish itself as an employer of choice