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E-government and Environmental Governance: Case Study Cuba
Get PDFE-government has emerged as a key component in the evolution of public administration into the digital age. This paper examines the intersection between e-government, governance, and the environment. It explores the ways in which information and communication technologies (ICTs) can strengthen environmental governance and facilitate informed decision-making in environmental public policy. In addition, the case study Cuba, where the National Environmental Information System was developed to facilitate the collection, analysis and dissemination of environmental data in real time, with the objective of informing citizens and decision makers, is analyzed. This specific case illustrates how e-government can improve transparency, citizen participation and collaboration between governmental and non-governmental actors by promoting efficient, sustainable environmental initiatives with lasting impac
Social responsibility of small and medium enterprises in Vietnam through digital transformation and application of artificial intelligence
Get PDFThe study on the social responsibility of small and medium enterprises (SMEs) in Vietnam through digital transformation and the application of artificial intelligence explored key aspects such as challenges faced during digital transformation, the importance of SMEs in the Vietnamese economy, and the significance of corporate social responsibility (CSR). It emphasized the need for SMEs to adapt to remain competitive and contribute more significantly to the state budget. The research highlighted the landscape of SMEs in Vietnam from 2017 to 2021, focusing on their classification, numbers, and characteristics, noting a steady increase in the number of SMEs each year. The document discussed the limited adoption of advanced technologies like artificial intelligence among Vietnamese SMEs and the need for increased support and resources for effective digital transformation, especially adopting AI technology. Additionally, it touched upon the social responsibility aspects of SMEs in the context of digital transformation, addressing opportunities and challenges related to environmental impact, labor productivity, financial transparency, and animal welfare. Through a qualitative analysis approach, the study aimed to provide insights into the evolving landscape of SMEs in Vietnam and their integration of digital technologies to enhance social responsibility practice
Design and implementation of an IoT monitoring system for the optimization of solar stills for water desalination
Get PDFThe project "Design and Implementation of an IoT Monitoring System for the Optimization of Solar Distillers in Water Desalination" sought to improve the efficiency of desalination in La Guajira, a region with critical water scarcity. The objective was to develop an IoT system to optimize solar stills, offering a sustainable solution. A prototype solar still with IoT monitoring was built. The study included the creation of circuits to integrate sensors and an HTML dashboard to visualize real-time variables, such as internal and external temperatures, humidity, and water level in the basin, facilitating the calculation of efficiency. The IoT monitoring system proved to be effective in increasing efficiency and providing valuable data for design decisions, marking a step towards water autonomy
Enhancing IoT Data Analysis with Machine Learning: A Comprehensive Overview
Get PDFMachine learning techniques are essential for processing the vast volume of IoT data efficiently, improving performance, and managing IoT applications effectively. Machine learning algorithms play a crucial role in detecting malicious attacks and anomalies in real-time IoT data analysis, thereby enhancing the security of IoT devices. The integration of big data analytics methods with machine learning techniques can further enhance IoT data analysis, improving the performance of IoT applications and overcoming related challenges. Real-time data collection using sensors like DHT11 and Gas level sensors, coupled with machine learning algorithms, enables efficient analysis of IoT data, aiding in the identification of anomalies and attacks. The comprehensive overview of enhancing IoT data analysis with machine learning provides insights for future research, including exploring advanced machine learning algorithms and optimizing data preprocessing techniques to enhance IoT data analysis capabilities
Advancing Medical Image Analysis: The Role of Adaptive Optimization Techniques in Enhancing COVID-19 Detection, Lung Infection, and Tumor Segmentation
Get PDFArtificial intelligence (AI) holds significant potential to revolutionize healthcare by improving clinical practices and patient outcomes. This research explores the integration of AI in healthcare, focusing on methodologies such as machine learning, natural language processing, and computer vision, which enable the extraction of valuable insights from complex medical imaging and clinical data. Through a comprehensive literature review, the study highlights AI’s practical applications in diagnostics, treatment planning, and predicting patient outcomes. Additionally, ethical issues, data privacy, and legal frameworks are examined, emphasizing the importance of responsible AI usage in healthcare. The findings demonstrate AI’s ability to enhance diagnostic accuracy, streamline administrative tasks, and optimize resource allocation, leading to personalized treatments and more efficient healthcare management. However, challenges remain, including data quality, algorithm transparency, and ethical concerns, which must be addressed to ensure safe and effective AI deployment. Continued research, collaboration between healthcare professionals and AI experts, and the development of robust regulatory frameworks are essential for maximizing AI’s benefits while minimizing risks. This research underscores the transformative potential of AI in healthcare and stresses the need for a multidisciplinary approach to address the ethical and regulatory complexities involved in its widespread adoptio
A Framework for Institution to Enhancing Cybersecurity in Higher Education: A Review
Get PDFThe increasing prevalence of cybersecurity threats has highlighted the urgent need for Higher Education Institutions (HEIs) to prioritize and enhance their cybersecurity measures. This research article presents a comprehensive framework aimed at guiding institutions in strengthening their cybersecurity posture within the higher education sector. The framework addresses the unique challenges faced by HEIs, taking into account the multifaceted nature of cybersecurity and the evolving threat landscape. The proposed framework incorporates a systematic approach that encompasses key components essential for effective cybersecurity management. These components include governance and leadership, risk assessment and management, technical controls, awareness and training, incident response, and collaboration with external stakeholders. The framework emphasizes the integration of these components to establish a robust and holistic cybersecurity strategy. The research article draws upon a thorough review of existing literature, best practices, and industry standards to provide practical insights for HEIs. The framework offers a structured approach that enables institutions to assess their current cybersecurity posture, identify gaps, and implement targeted measures to enhance their overall security resilience. By adopting this framework, institutions can proactively address cybersecurity challenges, mitigate risks, and protect sensitive data and systems. The framework serves as a valuable resource for HEI leaders, policymakers, and cybersecurity professionals seeking to enhance cybersecurity in the higher education landscap
Smart watch for early heart attack detection and emergency assistance using IoT
Get PDFThis research introduces a Smart Watch equipped with advanced physiological monitoring capabilities for the early detection of heart attacks and automatic initiation of emergency assistance. Cardiovascular diseases, particularly heart attacks, are a leading cause of global mortality. Rapid response during a heart attack significantly improves patient outcomes, emphasizing the need for innovative solutions. The proposed Smart Watch integrates a combination of sensors, including ECG (Electrocardiogram) and PPG (Photoplethysmography), to continuously monitor the user\u27s heart rate, rhythm, and other relevant physiological parameters. Machine learning (Time Series Analysis algorithm) is employed to analyse the collected data in real-time, identifying patterns indicative of a potential heart attack.Upon detecting abnormal cardiac activity, the Smart Watch triggers an immediate response by connecting to a dedicated mobile application. The application utilizes built-in communication features to establish a connection with emergency services, providing vital information about the user\u27s condition, location, and medical history. Simultaneously, the Smart Watch alerts predefined emergency contacts, ensuring a swift response from friends or family members.
Artificial Intelligence as a tool for analysis in Social Sciences: methods and applications
Get PDFArtificial Intelligence (AI) transforms the social sciences by providing new methodologies and tools for data analysis. This article was based on a comprehensive literature review that analyzed the role of artificial intelligence as an analytical tool in the social sciences. It was observed that the ability of AI to process text, images, and audio in an integrated manner allows researchers to address complex problems with greater accuracy and efficiency. Multimodal tools facilitate the analysis of large volumes of data, the interpretation of financial documents, and the evaluation of facial expressions, which improves decision making in social research. Specialized databases offer access to a wide range of AI tools that optimize tasks such as literature review, data collection and visualization of results. In addition, safety and ethics in the use of AI are key priorities, with the creation of alliances and regulatory frameworks that ensure responsible and safe development of these technologies. Initiatives such as the AI Safety Alliance and the European Union\u27s Artificial Intelligence Act set global standards for the ethical and safe use of AI, safeguarding both individuals and society at large
Enhancing Urban Green Spaces: AI-Driven Insights for Biodiversity Conservation and Ecosystem Services
Get PDFUrban green spaces (UGS) enhance biodiversity and provide essential ecosystem services like air purification, climate regulation, water management, and recreation. Despite their importance, UGS are often overlooked in urban planning, limiting their potential for resilience and sustainability. This study examines biodiversity in UGS and their capacity to deliver ecosystem services using field surveys, GIS mapping, stakeholder interviews, and AI-driven analytics. AI-based image recognition and remote sensing automate species identification and assess vegetation health, improving biodiversity assessments. Machine learning models analyze spatial and environmental data to predict UGS contributions to mitigating heat islands, air pollution, and stormwater runoff. Findings show that UGS serve as biodiversity hotspots, hosting diverse flora and fauna. Ecosystem service provision varies based on green space type, size, and management. AI-driven insights reveal key biodiversity factors like vegetation composition, spatial configurations, and human activities, offering data-driven recommendations for urban planning. Integrating AI into urban ecology supports evidence-based decision-making, urging policymakers and communities to optimize UGS management for biodiversity and human well-being
Artificial intelligence as a resource for teaching mathematics. Integral calculus as a specific case
Get PDFThe use of artificial intelligence, AI, has increased in recent years, offering tools to generate content and solve problems in different areas of knowledge. Questioning their relevance in areas such as integral calculus, 11 AI tools were tested to solve from basic to advanced integrals, described in different ways such as natural language or images. The results were compared with the solutions given in the literature, analyzing precision, number of steps, clarity of explanations and ease of use. Finding that the Chat GPT-Wolfram Alpha partnership stood out for its ability to identify appropriate integration techniques and offer detailed and understandable explanations; While Copilot is more complex to understand if you do not use the LaTeX language, the rest present some problems when interpreting instructions and images. Although these tools are not designed to solve mathematical problems, they proved to be effective in most cases, promoting an interactive space to clarify doubts in real time and generate debate; however, their effectiveness depends on the use given to them, since either as support in the classroom to deepen the analysis of the problem or simply use it as a black box to obtain quick answers