Soundscape tourism has become one type of tourism, and its trend is emerging in most areas with hilly, forested, and natural landscapes, such as Bantul Indonesia, becoming a mainstay for region development and its community. This article explores four human manufactured soundscape tourism destinations in Bantul, Indonesia, examining the interrelationships between each tourism stakeholder and pinpointed development from a socio-economic perspective. We adopt a cross-case study approach, drawing main sources from government statistics, regulations, social media narratives, and online news. Using the NVivo 12 Plus software, we coded and annotated the research source. Our research revealed that in four case studies, tourism soundscapes emerged as the primary tourist attractions, with other attractions only marginally contributed. Presenting music or acoustic stages enabled tourism industry to reap benefits, particularly for local community and regional income. However, it is important to emphasize sustainability issues, thus, the continuous increased in music soundscape in nature has led to the formation of collaborations among tourism actors, with local communities “Pokdarwis” posed as the principal driving force behind destination development. This study demonstrates that human-manufactured soundscapes have the potential to increase visitor numbers and outperform natural soundscapes in natural destinations.

With the deep integration of artificial intelligence technology in education, the development of AI integration capabilities among pre-service teachers—as the core of future educational human resources—has become crucial for enhancing educational quality and driving digital transformation in education. Based on the AI-TPACK (Artificial Intelligence-Technological Pedagogical Content Knowledge) theoretical framework, this study employs questionnaire surveys and structural equation modeling to explore the structural characteristics, influencing factors, and formation mechanisms of AI-TPACK competencies among pre-service teachers in Chinese universities. Findings indicate that while pre-service teachers demonstrate moderately high overall AI-TPACK levels, their technical knowledge (AI-TK) and technological integration competencies (e.g., AI-TPK, AI-TCK) remain relatively weak. School technical support, technological attitudes, and technological competence significantly influence their AI-TPACK capabilities, with institutional level and teaching experience serving as important external moderating factors. Building on these findings, this paper proposes a systematic framework for developing pre-service teachers' AI integration capabilities from a human resource development perspective. This framework encompasses four dimensions: curriculum optimization, practice enhancement, resource support, and policy guidance. It aims to provide theoretical foundations and practical pathways for pre-service teacher training and teacher human resource development in higher education institutions.

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.

This study compares Human Resource Development (HRD) in Vietnam and Malaysia, looking at their methods, problems, and institutional frameworks in the context of ASEAN economic integration and Industry 4.0. Based on Cho and McLean’s (2004) integrated HRD model, this paper looks at recent research (from 2018 to 2023) to look at important topics such globalization, demographic changes, vocational training alignment, and technology disruption. Vietnam has a vast workforce, but it still has problems with low productivity, skill mismatches, and not being ready for the global market. On the other hand, Malaysia’s institutional HRD structures are making more progress, even though its workforce is getting older and not everyone is adapting to digital transformation at the same rate. The study shows that we need HRD policies that are tailored to each industry, training that is delivered in a decentralized way, and stronger relationships between the public and commercial sectors. It also stresses how important it is for national HRD policies to include global competences and initiatives that help everyone learn new skills. The study adds a unique framework for comparing HRD and gives policymakers, educators, and practitioners useful information, even though it is constrained by its use of secondary data. Future study should use mixed-methods to confirm results and look into interventions that work in specific situations. The study shows that Vietnam and Malaysia need personalized, inclusive, and forward thinking HRD systems to produce strong and competitive workforces in the post-pandemic, digital driven global economy.

The article examines the appearance of various unfortunate situations and tragic events in modern Kazakh novels that arise due to human and natural ecology problems. The research’s primary goal is to analyze human and natural ecology issues based on contemporary Kazakh novels. We have chosen A. Nurpeyisov’s novel “The Last Duty” as our research material, which focuses on issues of human and natural ecology, and we will discuss the large-scale issues concerning the fate of human, nature, and society as a collective. The research topic’s practical significancelies in examining Kazakh novels that address crucial issues like safeguarding the ecological environment and preserving the green earth, which directly impact the destiny and future of humanity. It also aims to highlight their role in advancing societal development, elevating human values, and safeguarding our spiritual heritage. The research method involves mentioning the names of Kazakh novels that specifically and indirectly focus on the topic of human and natural ecology and summarizing their common features. The article also employed research methods such as analysis, comparison, and discussion. The novelty of the research result: Here are some relevant points. First, in the article, the core topic of the problem of human and natural ecology, which is common to all humanity in modern Kazakh novels, was highlighted. Second, analyzing the three characters, Zhadiger, Pakizat and Azim, which reveal the actual idea of the novel “The Last Duty,” the writer’s stylistic features and skillful aspects were also mentioned during the analysis of the character image through deep psychological analysis, landscape description, clear image, and artistic language, and theoretical conclusions and analyses were presented.