Journal of Hunan University Natural Sciences

This study investigates the dual role of cocoa as both a cultural resource and an economic asset within the Dayak Kenyah community in Lung Anai, East Kalimantan, Indonesia. Existing research on cocoa in Indigenous contexts in Kalimantan remains limited, with most studies focusing on broader agrarian issues, particularly oil palm and coal extraction.
Adopting an ethnographic approach based on field observations and in-depth interviews, this study demonstrates that cocoa extends beyond its function as a market commodity. It is embedded in cultural practices that shape collective identity, social relations, and local ecological knowledge. Cocoa cultivation and consumption are closely linked to ritual activities and community gatherings, reinforcing social cohesion and the community’s relationship with nature.
The study further examines the socio-economic implications of Indonesia’s new capital development, Ibu Kota Nusantara (IKN), which introduces both opportunities and challenges for the Dayak Kenyah community. These include pressures on land rights, shifts in livelihood strategies, and processes of cultural and identity transformation.
The findings contribute to interdisciplinary discussions on Indigenous economies, cultural sustainability, and rural transformation, highlighting the importance of integrating local knowledge systems into national development agendas.

Keywords: Cocoa production; Dayak Kenyah community; indigenous livelihoods; cultural sustainability; rural transformation; Ibu Kota Nusantara (IKN).

DOI https://doi.org/10.55463/issn.1674-2974.53.3.13

Concrete bridge crack detection plays a critical role in intelligent infrastructure inspection and structural safety assessment. However, existing automated approaches still face significant challenges, including the high miss rate of fine cracks, strong interference from complex backgrounds, and insufficient boundary delineation accuracy.
To address these limitations, this study proposes a novel two-stage collaborative detection–segmentation framework that integrates an enhanced YOLOv11 detector with a dual-branch DualUNet architecture. The framework follows a “coarse localization–guided fine segmentation” strategy. In the detection stage, YOLOv11 is improved by incorporating a P2 high-resolution feature layer and a C2PSA attention module, enabling accurate localization of fine cracks while effectively suppressing background noise and generating reliable region-of-interest (RoI) priors.
In the segmentation stage, a dual-branch DualUNet with a shared ResNet34 encoder is developed. The global branch captures contextual semantic information from the full image, whereas the RoI branch refines local crack features by integrating detection priors with a Multi-Scale Squeeze-and-Excitation (MSSE) module. This design enhances the representation of fine structural details and mitigates the limitations of single-stage segmentation methods.
To address the severe class imbalance caused by sparse crack pixels, a hybrid loss function combining weighted binary cross-entropy and Dice loss is adopted. Additionally, a boundary supervision mechanism is introduced to improve contour accuracy.
Experimental results on the Crack500 dataset demonstrate that the proposed framework achieves superior performance, with recall and precision reaching 0.79 and 0.75, respectively. Compared with baseline models, the proposed method improves Boundary IoU by 26%, indicating significantly enhanced edge delineation. Visual results further confirm that the method effectively suppresses background interference while preserving crack continuity, making it suitable for practical bridge inspection applications.

Keywords: Concrete crack detection; Bridge inspection; YOLOv11; Dual U-Net; Attention mechanism; Boundary segmentation.

DOI https://doi.org/10.55463/issn.1674-2974.53.4.2

This study examines the relationship between inventory optimization and cost reduction within strategic logistics management, with the aim of identifying how effective inventory practices enhance operational efficiency and reduce overall logistics costs. In the context of increasing pressure for cost efficiency, the study addresses a gap in the literature concerning the integrated role of inventory management in achieving both cost savings and service performance improvements.
A structured literature review was conducted, drawing on academic publications, industry reports, and case studies. The analysis focuses on inventory optimization techniques, cost reduction strategies, and emerging technological solutions, using a thematic synthesis approach to identify key patterns and relationships.
The findings demonstrate that inventory optimization contributes significantly to reducing warehousing and transportation costs through improved inventory turnover and minimized holding levels. The adoption of advanced technologies, including AI-driven forecasting and RFID systems, further enhances inventory accuracy and operational performance. In addition, optimized inventory systems improve customer service outcomes by increasing order fulfillment rates and reducing stockouts. However, the study also identifies key challenges, particularly high implementation costs and organizational resistance to change.
This study contributes to the literature by providing an integrated perspective on the role of inventory optimization in cost efficiency and logistics performance. The findings highlight the importance of aligning inventory management practices with broader supply chain strategies. Future research should further examine the long-term impact of digital technologies on inventory optimization and cost structures.

Keywords: Inventory optimization; Logistics cost reduction; Supply chain management; Artificial intelligence; RFID; Operational efficiency.

DOI https://doi.org/10.55463/issn.1674-2974.53.1.14

Socio-economic transformation is driven by changes in work structures, cultural norms, and patterns of social interaction. However, existing studies have largely examined these dimensions in isolation, leaving a conceptual gap in understanding how they jointly shape transformative processes within communities. This study aims to integrate work patterns and interaction patterns as interconnected dimensions of socio-economic transformation by means of a systematic literature review (SLR). The review draws on scholarly publications indexed in Scopus, Web of Science, JSTOR, ScienceDirect, and Google Scholar, using keywords related to work patterns, social interaction, socio-economic transformation, labor migration, social networks, and Indigenous and Local Knowledge (ILK). A thematic synthesis approach was employed to identify recurring concepts and develop analytical linkages. The review reveals three key findings. First, work patterns are being reshaped by digitalization, platform labor, automation, and labor migration, which together transform job structures, employment stability, and work-related cultural values. Second, interaction patterns are being reconfigured by urbanization and digital connectivity, leading to hybrid forms of community, new modes of participation, and changing socio-spatial relations. Third, ILK plays a significant role in strengthening social resilience, supporting ecological stewardship, and shaping adaptive livelihood strategies, particularly in indigenous and rural communities. Migration functions both as a mechanism for risk diversification and as a catalyst for social reorganization, although it may also generate vulnerabilities where institutional protection is weak. The study concludes that socio-economic transformation is best understood as a co-evolving process in which work patterns and interaction patterns mutually reinforce one another across structural and cultural contexts. This integrated framework contributes to transformation research and offers practical insights for the design of community-based development policies that are socially inclusive and culturally grounded.

Keywords: Socio-economic transformation; Work patterns; Interaction patterns; Indigenous and Local Knowledge (ILK); Migration.

DOI https://doi.org/10.55463/issn.1674-2974.53.1.13

This study examines the role of digital communication strategies in strengthening brand identity among young digital entrepreneurs. In the context of rapid digital transformation, effective online communication has become a critical factor in building credibility, visibility, and meaningful engagement with audiences. Despite growing interest in digital branding, limited attention has been given to how communication strategies shape brand identity among emerging entrepreneurs.
This study adopts a qualitative research design based on a structured review of the literature combined with illustrative case studies of young entrepreneurs actively using social media platforms such as Instagram, TikTok, and LinkedIn. The analysis focuses on key communication practices, including content strategy, storytelling, and audience interaction.
The findings indicate that consistent storytelling, interactive content, and the strategic use of social media analytics significantly enhance perceived brand authenticity and audience engagement. Digital communication also enables entrepreneurs to articulate personal values, differentiate their brands, and build long-term trust with their audiences.
This study contributes to the literature by providing an integrated perspective on digital communication as a core mechanism of brand identity formation in entrepreneurial contexts. The results highlight the importance of aligning communication strategies with personal branding and audience expectations to achieve sustainable growth. Future research should examine the role of AI-driven personalization, influencer collaboration, and community-based engagement models in advancing digital branding practices.

Keywords: Digital communication; Brand identity; Digital entrepreneurship; Social media strategy; Audience engagement.

DOI https://doi.org/10.55463/issn.1674-2974.53.2.13