Integrated Resource Management plays a crucial role in sustainable development by ensuring efficient allocation and utilization of natural resources. Remote Sensing (RS) and Geographic Information System (GIS) have emerged as powerful tools for collecting, analyzing, and managing spatial data, enabling comprehensive and integrated decision-making processes. This review article uniquely focuses on Integrated Resource Management (IRM) and its role in sustainable development. It specifically examines the application of RS and GIS in IRM across various resource management domains. The article stands out for its comprehensive coverage of the benefits, challenges, and future directions of this integrated approach.

This study aims to investigate the effectiveness of community involvement in waste management through participatory research. Its objective is to bridge the theoretical underpinnings of participatory research with its practical implementation, particularly within the realm of waste management. The review systematically analyzes global instances where community engagement has been incorporated into waste management initiatives. Its principal aim is to evaluate the efficacy of participatory strategies by scrutinizing methodologies and assessing outcomes. To achieve this, the study identified 74 studies that met rigorous criteria through meticulous search efforts, encompassing various geographical locations, cultural contexts, and waste management challenges. In examining the outcomes of participatory research in waste management, the study explores successful practices, shortcomings, and potential opportunities. Moving beyond theoretical discourse, it provides a detailed analysis of real-world applications across various settings. The evaluation not only highlights successful engagement strategies and indicators but also critically assesses challenges and opportunities. By conducting a comprehensive review of existing research, this study establishes a foundation for future studies, policy development, and the implementation of sustainable waste management practices through community engagement. The overarching goal is to derive meaningful insights that contribute to a more inclusive, effective, and globally sustainable approach to waste management. This study seeks to inform policymaking and guide future research initiatives, emphasizing the importance of community involvement in addressing the complexities of waste management on a global scale.

This study simultaneously examined the linkages among environmental dynamism, three dynamic capabilities, and the competitive advantages of retail businesses, which have not been identified before. Furthermore, this study fills the significant gaps in the literature and practical guidelines for retail development through improving retailer’s dynamic capabilities in response to environmental dynamism. The study used a quantitative approach by partial least squares SEM (PLS-SEM) to examine the hypotheses. Data were collected from 304 Vietnamese retail business managers. The results show that environmental dynamism plays a significant role in fostering the improvement of retailers’ dynamic capabilities. The findings also reveal positive linkages among the three dynamic capabilities before they significantly improve retailers’ competitive advantage. These are the valuable guidelines for retailers to nurture their dynamic capabilities, including service innovation capabilities, multi-channel integration, and brand orientation for sustaining their competitive advantages.

This research presents a comprehensive model for enhancing the road network in Thailand to achieve high efficiency in transportation. The objective is to develop a systematic approach for categorizing roads that aligns with usage demands and responsible agencies. This alignment facilitates the creation of interconnected routes, which ensure clear responsibility demarcation and foster efficient budget allocation for road maintenance. The findings suggest that a well-structured road network, combined with advanced information and communication technology, can significantly enhance the economic competitiveness of Thailand. This model not only proposes a framework for effective road classification but also outlines strategic initiatives for leveraging technology to achieve transportation efficiency and safety.

The cost of diagnostic errors has been high in the developed world economics according to a number of recent studies and continues to rise. Up till now, a common process of performing image diagnostics for a growing number of conditions has been examination by a single human specialist (i.e., single-channel recognition and classification decision system). Such a system has natural limitations of unmitigated error that can be detected only much later in the treatment cycle, as well as resource intensity and poor ability to scale to the rising demand. At the same time Machine Intelligence (ML, AI) systems, specifically those including deep neural network and large visual domain models have made significant progress in the field of general image recognition, in many instances achieving the level of an average human and in a growing number of cases, a human specialist in the effectiveness of image recognition tasks. The objectives of the AI in Medicine (AIM) program were set to leverage the opportunities and advantages of the rapidly evolving Artificial Intelligence technology to achieve real and measurable gains in public healthcare, in quality, access, public confidence and cost efficiency. The proposal for a collaborative AI-human image diagnostics system falls directly into the scope of this program.