This study highlights the need for significant improvements in managing and communicating change within IT governance frameworks. Key findings reveal that stakeholders often face confusion and misalignment due to poor communication and unclear processes. To address these issues, the research recommends enhancing transparency through clearer communication channels and structured feedback mechanisms. Regular updates and comprehensive training on change management protocols are also suggested to bridge gaps between current practices and stakeholder expectations. The study emphasizes the importance of continuous improvement in IT governance practices. By prioritizing enhanced communication and stakeholder engagement, organizations can ensure their governance frameworks remain agile and effective in addressing emerging challenges. Engaging stakeholders in change planning and implementation fosters buy-in and support, leading to more sustainable governance practices. Regular monitoring and evaluation of change management processes are essential to maintaining alignment with stakeholder needs. Ultimately, investing in improved communication, transparency, and stakeholder engagement can significantly enhance IT governance effectiveness. A holistic approach, fostering a culture of collaboration and continuous learning, enables organizations to adapt to technological advancements and business needs, driving better outcomes and maintaining operational efficiency.

This paper investigates reveals a highly favorable assessment of the Integrated Workforce Management System (ISWM), demonstrating its significant role in reducing administrative workload and enhancing organizational efficiency. With a strikingly low disagreement rate (0.9%) and no strong disagreements, ISWM is widely approved by its users. The system is perceived as economically beneficial, with 60% of respondents recognizing its effectiveness in cutting administrative costs. Additionally, 75.2% of users affirm ISWM’s strength in ensuring compliance and safeguarding sensitive data. The system's adaptability is also noted, with 82.1% feeling capable of customizing it to their organizational needs. However, a small fraction of respondents expressed skepticism or neutrality regarding customization, indicating a need for further support. The findings underscore ISWM’s value in optimizing HR functions, supporting financial management, and meeting compliance standards. Addressing service quality concerns will enhance overall satisfaction. In sum, ISWM is validated as a critical tool for improving operational effectiveness and efficiency in modern businesses.

This study investigates the dynamics of population growth and the spread of infectious diseases using delay differential equations (DDEs). Traditional models often ignore the long-term effects found in real-world processes, leading to less accurate predictions. By incorporating time lags, DDEs provide a more realistic framework for understanding population dynamics and the spread of disease. The study begins with an introduction to the importance of demographic variables and the role of time lags, followed by a comprehensive review of the literature. A detailed mathematical model has been developed, which includes both basic and delayed components. This model is analyzed to ensure stability and behavior under various conditions, with numerical simulations used to illustrate key concepts. Research applies these models to real-world data, focusing on population growth and the impact of infectious diseases, particularly COVID-19. The simulation results highlight the effectiveness of DDEs in capturing the complexity of population dynamics and provide insight into the potential implications of epidemics. The study also explores the integration of DDEs with machine learning methods to improve prediction accuracy. Key findings include the importance of accounting for time delay in human models, the performance of DDEs in real-world situations, and the value of combining DDEs with machine learning for better predictions. The study concludes with recommendations for future research, emphasizing the need for continued evaluation of DDEs in population dynamics and public health.

The survey data provides a detailed evaluation of marketing strategies for mobile phone brands, emphasizing the critical role of both online and offline channels in shaping consumer satisfaction and brand success. The findings indicate that online platforms are generally perceived as intuitive and user-friendly. High ratings for visual design, product information, and checkout processes underscore the effectiveness of e-commerce strategies. Personalized marketing significantly influences consumer behavior, with many respondents positively impacted by personalized recommendations, customized promotions, and assistance. Data analytics is recognized as crucial in enhancing online marketing effectiveness, with a notable appreciation for the integration of online and offline data. Offline shopper marketing and visual merchandising are also vital, with an emphasis on the importance of store layout, design, and effective visual merchandising. Interactions with knowledgeable staff and in-store experiences are highly influential, with a preference for in-store shopping over online options. Overall, the survey underscores the need for mobile phone brands to invest in visual merchandising, interactive displays, and consistent online-offline strategies to enhance engagement and drive purchasing decisions.

This comprehensive program protects image data from unauthorized access and provides methods for authentication, tamper detection, and image quality assessment using intelligent algorithms. The first module focuses on ECC; a powerful encryption algorithm known for its power in securing digital data. By generating ECC keys, encrypting image data, and using decryption procedures, we have ensured a secure framework for protecting sensitive physical information. This forms the basis of cryptographic security. In the second module, we strengthened image security by introducing a two-layer encryption strategy, which combines ECC with a strong RSA algorithm. This hybrid approach utilized the strengths of both cryptographic techniques, improving encryption strength and resilience against potential attacks. The combination of ECC and RSA creates a formidable defense, making it more challenging for adversaries to compromise the security of encrypted images. Going beyond encryption, the third module delved into steganography, a secret communication technique that hides information within the pixels of an image. By embedding private messages or images within the cover image, we introduce an extra layer of security. This method hides sensitive information and makes it difficult for unauthorized entities to access or manipulate hidden content, thereby improving the overall security posture. In the fourth module, we introduced a quality measurement system based on machine learning. Using advanced algorithms and carefully selected datasets, our system automatically checks image quality. This innovation is important in identifying possible manipulation or modification of images. A machine learning model, trained on a diverse set of images, provides intelligent ways to check the authenticity of visual content, accompanied by cryptographic and steganographic layers of security.