• Journal of the Korean Society of Industry Convergence
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• v.27 no.4_2
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• pp.925-933
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• 2024

Identification of potential technology convergence opportunities is crucial to drive innovation and growth in modern enterprises. In this study, we proposed a framework to explore technological convergence opportunities based on CPC code sequences from patents by utilizing the BERT model. We relied on the BERT architecture to train a new model using about 1.3 million patents registered at the Korean Intellectual Property Office, and achieved an accuracy of approximately 73% based on HitRate@10 metric. A case study using patents related to wearable technologies was conducted to demonstrate practicability and effectiveness of the proposed framework. The key contributions of this research include: (1) enabling in-depth analysis that takes into account the complex interactions between CPC codes and contextual variability; (2) enabling the exploration of diverse technology convergence scenarios beyond simple sequential patterns. This study is one of the first studies to apply the BERT model for exploring technology convergence opportunities, and is expected to contribute to the establishment of technology innovation and R&D strategies by providing a more accurate and practical tool for enhancing the speed and efficiency of technology opportunity-related decision-making processes.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.4_2
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• pp.909-923
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• 2024

This study aims to classify the types of financial super apps and analyzes their evolution and growth paths by type. Super apps, which provide various services on a single platform, are gaining attention as a key strategy for digital transformation in the financial sector. By adopting the grounded theory methodology, this research has categorized financial super apps into three types: "lifestyle financial super app", "integrated financial super app", and "universal financial super app". Ansoff Matrix was used as a theoretical framework to understand how each type of super app grew and evolved through various strategies. Our analysis revealed that super apps of each type grew using a different mix of 'market penetration', 'product development', 'mark et development', and 'diversification' strategies, with each mix showcasing a distinct evolutionary path. The findings of this study are expected to enhance understanding of financial super app typology and evolutionary trajectories, contributing to the development of practical strategies, such as channel optimization for financial super apps in the future.

• Journal of Practical Agriculture & Fisheries Research
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• v.26 no.2
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• pp.14-24
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• 2024

To enhance the usability of smart agriculture, methods for utilizing smart farm data are required. Therefore, this study proposes a scheme for utilizing regional smart farm data by linking it to services. The current status of domestic and foreign smart farm data collection and linkage services is analyzed. To collect and link regional smart farm data, necessary data collection, data cleaning, data storage structure and schema, and data storage and linkage systems are proposed. Based on the standards currently being implemented for regional smart farm internal data storage, a farm schema, environmental information schema, facility control information schema, and growth information schema are designed by extending the crop schema and crop main environmental factor information database schema. A data collection and management system structure based on the Hadoop Ecosystem is designed for data collection and management at regional smart farm data centers. Strategies are proposed for utilizing regional smart farm data to provide smart farm productivity improvement and revenue optimization services, image-based crop analysis services, and virtual reality-based smart farm simulation services.

• Asia-Pacific Journal of Business
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• v.15 no.2
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• pp.125-142
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• 2024

Purpose - This study investigated the effect of paternalistic leadership on Chinese employees' creative work involvement. In addition, it also examined the mediating effects of group cohesiveness and employees' voice behavior in the above relationship. Design/methodology/approach - Based on survey data from 452 employees working in Chinese firms, empirical analysis was conducted by using hierarchical regression model. Findings - As a result, it was found that the authoritative of paternalistic leadership had a negative effect on employees' creative work involvement, and the moral and compassion of paternalistic leadership have a positive effect on employees' creative work involvement. Second, we found that loneliness had a positive mediate effect in the relationship between the paternalistic leadership and employees' creative work involvement. Research implications or Originality - This paper confirmed the paternalistic leadership still has an important impact on the creativity of Chinese employees, making up for the lack of previous literatures. In addition, it was confirmed that group cohesiveness and voice behavior play an important mediating role between paternalistic leadership and employees' creative work involvement. We also discuss important theoretical and practical implications of these findings.

• International Journal of Precision Engineering and Manufacturing-Green Technology
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• v.9
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• pp.1563-1573
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• 2021

The impinging jet technique is a critical process for enhancing mechanical properties. Sensors for the precise diagnosis of the nozzle status are necessary to maintain product quality and reduce cost. The application of commercial sensors for this purpose is difficult because sensors in the casting, rolling, and reheating processes should provide sensitivity to small impact variations, durability, anticorrosion, waterproofing, and high-temperature endurance. We developed a sensor module to satisfy these engineering requirements. The sensor monitored impact pressures based on the reduction in the collision force caused by abnormal impinging jet flows. Smart signal filtering based on a low-pass filter was employed to achieve a short CPU time, noise discrimination, and the preservation of signal characteristics. A method for nozzle position synchronization and a new performance index for impinging jets for multiple-nozzle sensing in practical applications were also developed. The developed sensor module was validated using artificial abnormal nozzles and tested in the field. The validations showed that the developed sensor with the smart filter and nozzle synchronization method could provide an individual jet status with a high precision. The developed sensor is expected to contribute to the improvement of machine health monitoring technology in various fields with jet nozzles.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.18-24
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• 2024

Efficient path planning for mobile crane lifting operations in the construction industry is essential for ensuring smooth machinery operation, worker safety, and the timely completion of projects. The inherently complex construction sites, characterized by dynamic environments, constantly changing conditions, and numerous static and mobile obstacles, underscore the necessity for advanced algorithms capable of generating optimal paths under various constraints. Mobile crane path planning algorithms have been researched extensively and possess the potential to resolve the challenges presented by construction sites. However, the application of these algorithms in actual construction sites is rare, suggesting a need for ongoing research and development in this field. This paper begins by systematically identifying and analyzing relevant research papers using predetermined keywords, providing a comprehensive review of the current state of mobile crane path planning algorithms. Specifically, it categorizes mobile crane path planning algorithms into four main groups: Graph search-based algorithms, Sampling-based algorithms, Nature-inspired algorithms, and Newly developed algorithms. It performs a critical analysis of each category, offering guidance to researchers exploring path planning solutions suitable for the dynamic and complex environments of construction sites. Through this review, we affirm the need for continued interest and attempts at new methodologies in mobile crane path planning, suggesting improvements for further research and practical application of these algorithms.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.327-334
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• 2024

Bridge inspection is crucial for infrastructure maintenance. Current inspections based on computer vision primarily focus on identifying simple defects such as cracks or corrosion. These detection results can serve merely as preliminary references for bridge inspection reports. To generate detailed reports, on-site engineers must still present the structural conditions through lengthy textual descriptions. This process is time-consuming, costly, and prone to human error. To bridge this gap, we propose a deep learning-based framework to generate detailed and accurate textual descriptions, laying the foundation for automating bridge inspection reports. This framework is built around an encoder-decoder architecture, utilizing Convolutional Neural Networks (CNN) for encoding image features and Gated Recurrent Units (GRU) as the decoder, combined with a dynamically adaptive attention mechanism. The experimental results demonstrate this approach's effectiveness, proving that the introduction of the attention mechanism contributes to improved generation results. Moreover, it is worth noting that, through comparative experiments on image restoration, we found that the model requires further improvement in terms of explainability. In summary, this study demonstrates the potential and practical application of image captioning techniques for bridge defect detection, and future research can further explore the integration of domain knowledge with artificial intelligence (AI).

• International conference on construction engineering and project management
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• 2024.07a
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• pp.745-752
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• 2024

This paper presents a study that compares and analyzes the practices of utilizing BIM (Building Information Modeling) for construction cost estimation in Japan and China. The study delves into the nuanced differences and similarities in cost estimation methodologies between the two countries. The overview section explored their respective standard specifications, and the methodologies for construction quantities take-off, covering both the bottom-up estimating approach and the all-in unit rate approach. Additionally, the paper delves into the item code system used in BQ (Bills of Quantities), elaborating on its introduction and practical application. The paper meticulously breaks down the process of quantities take-off facilitated by BIM models and cost-estimating software. The study also delves into the developmental trends in comprehensive BIM standards about construction cost, coupled with the proposition of a BIM code for seamless integration into construction cost practices as part of a forward-looking research plan. In conclusion, the paper encapsulates the comparative findings, highlighting the strengths, weaknesses, and potential areas for improvement in the BIM-enabled construction cost estimation practices of Japan and China. This study contributes to a deeper understanding of the utilization of BIM technology in the construction industry, offering valuable insights for practitioners, researchers, and policymakers alike.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.524-531
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• 2024

Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR) epitomize the technological frontier of the Fourth Industrial Revolution, bearing significant relevance to the construction sector. These immersive technologies, closely aligned with the burgeoning metaverse paradigm, have spawned a variety of applications within the construction industry, notably in the whole construction stage. However, their transition to on-field applications remains limited, especially in South Korea. This study aims to meticulously scrutinize the current landscape of VR, AR, and MR research in construction by delving into various overseas studies that employ these technologies across the construction lifecycle. Utilizing the RISS, Dbpia, KCI database, a systematic accumulation of bibliographic data from pertinent research papers will be conducted to discern the prevailing research trends and the practical implications of VR, AR, and MR in Korean AEC field. The analysis will encompass a review of the goals, methodologies, and outcomes of these studies, providing a scaffold for future research in this domain. The investigation will also shed light on the potential synergy between these immersive technologies and Building Information Modeling (BIM), which encapsulates the whole construction lifecycle, thereby illuminating pathways for enhanced digital model utilization in pre-construction processes. This endeavor not only seeks to bridge the existing research gap but strives to propel the Korean AEC field towards a digitally-augmented horizon by leveraging the capabilities of VR, AR, and MR.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.1188-1194
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• 2024

High-energy manufacturing processes, including laser welding, are actively being adopted not only in precision machinery industries but also in the shipbuilding and construction sectors. Laser welding, in particular, is gaining prominence in the industry due to its faster welding speed and reduced distortion compared to conventional arc welding methods. Integration of automated welding systems is anticipated to address challenges in shipbuilding and construction industries, which are currently facing a shortage of skilled labor. For successful implementation of automated welding systems, it is essential to predict and design for the post-welding effects, such as residual deformation and stresses. However, in the case of high-energy manufacturing like laser welding, the welding bead morphology differs from that of arc welding, and the heat load conditions applied during simulation are distinct. To facilitate accurate simulation predictions, the development of a suitable heat source for predicting welding bead morphology in high-energy manufacturing processes is crucial. The Block-dumping method is proposed for rapid simulation and on-site application, with the shape of the welding bead being imperative for its effectiveness. In this study, data on the welding bead morphology of Nickel-based steel was obtained. Using Deep Learning techniques, we successfully predicted the bead morphology and confirmed minimal discrepancies when compared to actual results. This outcome allows for the simulation of welding under untested conditions, offering practical applicability in the field. Additionally, we present a heat source model (heat load condition) to ensure a highly accurate interpretation of the results.