Abstract-The banking sector is under increasing pressure to ensure secure and seamless digital payment processes. Tokenization, a method of securing sensitive payment data, has emerged as an effective strategy for mitigating security risks and ensuring compliance with Payment Card Industry Data Security Standards (PCI DSS). This paper explores the implementation of tokenization strategies within the banking sector, emphasizing its role in achieving PCI compliance. Through case studies, statistics, and the presentation of real-world examples, the paper highlights both the challenges and benefits of adopting tokenization strategies.

Abstract-This paper explores the role and impact of Generative Artificial Intelligence (AI) in developing countries, emphasizing its potential to address significant socio-economic challenges. Unlike traditional AI, which primarily focuses on decision-making based on existing data, Generative AI can create new content, making it a powerful tool for innovation. This technology offers unique opportunities for sectors such as healthcare, education, agriculture, and infrastructure development, particularly in nations with limited resources and technological infrastructure. Generative AI can revolutionize healthcare by enhancing diagnostic tools, supporting drug discovery, and enabling remote medical services. In agriculture, it assists in optimizing crop yields and improving food security through advanced monitoring techniques. Additionally, the technology can personalize educational experiences and democratize access to learning materials. Despite these advantages, the adoption of Generative AI faces challenges, including ethical concerns, data privacy issues, and the risk of job displacement. The paper concludes that Generative AI holds immense potential to drive sustainable development in developing countries. However, careful implementation and strategic investments in infrastructure and education are required to overcome existing barriers and ensure equitable access to these technologies.

Abstract-This paper investigates the factors influencing the adoption of digital payments globally. It discusses the drivers, challenges, and potential future research areas required to enhance the digital payment ecosystem. Emphasis is placed on technology advancements, consumer preferences, and regulatory frameworks, with a data-driven approach. Tables, graphs, and statistical analyses provide insights into the current adoption trends across regions. Future research directions focus on improving the security, user experience, and accessibility of digital payments.

Abstract-The current pandemic of COVID-19 for global medical care has high demand on rapid and correct diagnosis, especially in a cardiac population with prior heart disease being a large proportion among these patients. In this work, a predictive machine learning (ML) model based on convolutional neural networks (CNNs) is proposed to recognize COVID-19 and heart disease from chest X-ray images. The COVID-19 positive and normal X-ray images were used to train the CNN model. The objective behind was to automate the diagnosis so that it helps in early detection of diseases which can save lives and improve patient management. The model was accurate and demonstrated promising results in clinical scenarios.

Abstract-Lifestyle diseases, such as cardiovascular diseases, diabetes, obesity, and hypertension, are significantly influenced by environmental factors and individual habits, including diet, physical activity, and stress. Advances in bioinformatics have allowed researchers to leverage genomics, proteomics, metabolomics, and transcriptomics data for early detection and effective management of these diseases. By analyzing gene expression, protein interactions, and metabolic pathways, bioinformatics helps identify biomarkers and therapeutic targets. This paper explores how bioinformatics-driven approaches can aid in understanding the molecular mechanisms behind lifestyle diseases, facilitating early diagnosis, personalized treatments, and improved health outcomes.

Abstract-This paper examines the increasing importance of robust cybersecurity measures in the digital payments industry. As the volume and value of online financial transactions continue to grow exponentially, the sector faces a corresponding surge in cyber-attacks, necessitating advanced cybersecurity protocols. This study explores key cybersecurity measures and implementation strategies, including encryption, multi-factor authentication (MFA), tokenization, artificial intelligence (AI)-based fraud detection, and regulatory compliance, to safeguard digital payments against various cyber threats. Through a detailed review of existing literature, case studies, and statistical analysis, the article provides strategic insights into how organizations can enhance security in digital payment ecosystems, maintain compliance, and achieve resilience in the face of evolving cyber threats.

Abstract-The PhilHealth Konsulta program aims to improve healthcare access and affordability in the Philippines by offering full primary care services such as consultations, diagnostic testing, and prescriptions. This study looks at the quality and availability of diagnostic examinations provided by accredited PhilHealth Konsulta providers in Baguio City. A quantitative research approach was used, with a survey disseminated to staff and outpatients from various PhilHealth Konsulta facilities in Baguio City. The study used a Likert scale to assess satisfaction levels in 10 areas of service quality and diagnostic availability, ranging from 1 (least satisfied) to 5 (very highly satisfied). A total of 117 people responded, including 48 personnel and 69 outpatients. Findings indicate generally high satisfaction levels among both healthcare providers and patients regarding consultation services, queue management, and patient instructions within the PhilHealth Konsulta framework. However, moderate satisfaction was noted regarding the availability of medications and diagnostic tests, highlighting potential areas for enhancement in inventory management and diagnostic infrastructure. Disparities between staff and patient perceptions suggest a need for improved communication and alignment in service delivery expectations. While the PhilHealth Konsulta program in Baguio City typically satisfies the demands of patients with moderate to high satisfaction, there are several crucial areas that need to be addressed to increase service quality and diagnostic availability. The study emphasizes the importance of increasing diagnostic test availability through enhanced equipment procurement and supply chain management. Strengthening healthcare manpower by recruiting additional staff and implementing training programs to optimize service delivery efficiency is also advised. Furthermore, leveraging technology to streamline administrative processes and improve patient management systems can enhance overall patient experience and operational effectiveness. This research contributes valuable insights to policymakers, healthcare managers, and practitioners involved in optimizing primary healthcare delivery under the PhilHealth Konsulta program. By addressing identified gaps and leveraging strengths, this study aims to support efforts towards achieving equitable healthcare access and improving health outcomes for residents of Baguio City and similar settings across the Philippines.

Abstract-The recognition of food on social media has spawned an growing interest in automated food recognition and recipe era. We gift a system that combines both neighborhood and global functions to create spatiotemporal convnet, this paper outlines the venture of creating particular but special recipes from snap shots of food. on this paper, we use convolutional neural networks and a generative antagonistic community to robotically convert meals photographs into textual content based totally recipes. To generate coherent and contextually relevant recipe instructions, our approach combines image popularity techniques based totally on Convolutional Neural Networks (CNN) [17] for the identity and category of food with herbal Language Processing (NLP)—fashions utilized in conjunction to analyze textual data. extra records: The authors present a large-scale dataset with various meals categories and corresponding recipe (i.e., cooking method) for schooling their proposed framework. at the photograph- to-recipe mission, our experiments set up that it is able to certainly generate a recipe carefully matching with food objects in snap shots. Quantitative assessment benchmarks on preferred datasets display superiority as compared to baseline models and qualitative evaluation verifies that our architecture can produce human-like recipe commands. these consequences assist our approach as a benchmark for more state-of-the-art packages closer to automated culinary content creation by way of offering users with more food-related experience in digital interfaces.

Abstract-Agriculture is crucial for the Indian economy. Rice is a staple crop to more than half of world population. Conventional transplanted rice production faces issues like lowering water tables, lower productivity, methane emissions, soil health deterioration, and labour scarcity. Puddling, a crucial step in wetland rice production, can improve transplanting and weed management but can also cause soil conditions that are unfavourable for post-rice crops. Puddled transplanted rice is energy-intensive and contributes to climate change by emitting methane and nitrous oxide. Direct seeded rice (DSR) technologies can minimize environmental impact and increase productivity. DSR was introduced in 2009-10 to address labour constraints, rising labour prices, and a diminishing groundwater table in Punjab. With agricultural water requirements expected to increase by 20% by 2050, DSR requires about 50% less water under Indian conditions. This review article studies the condition of current rice production practices, the major constrains and DSR, its advantages along with agronomy as substitute of current TPR method.