• Journal of Korea Water Resources Association
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• v.56 no.8
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• pp.471-484
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• 2023

Deep learning models based on generative adversarial neural networks are specialized in generating new information based on learned information. The deep generative models (DGMR) model developed by Google DeepMind is an generative adversarial neural network model that generates predictive radar images by learning complex patterns and relationships in large-scale radar image data. In this study, the DGMR model was trained using radar rainfall observation data from the Ministry of Environment, and rainfall prediction was performed using an generative adversarial neural network for a heavy rainfall case in August 2021, and the accuracy was compared with existing prediction techniques. The DGMR generally resembled the observed rainfall in terms of rainfall distribution in the first 60 minutes, but tended to predict a continuous development of rainfall in cases where strong rainfall occurred over the entire area. Statistical evaluation also showed that the DGMR method is an effective rainfall prediction method compared to other methods, with a critical success index of 0.57 to 0.79 and a mean absolute error of 0.57 to 1.36 mm in 1 hour advance prediction. However, the lack of diversity in the generated results sometimes reduces the prediction accuracy, so it is necessary to improve the diversity and to supplement it with rainfall data predicted by a physics-based numerical forecast model to improve the accuracy of the forecast for more than 2 hours in advance.

• Land and Housing Review
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• v.14 no.4
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• pp.47-62
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• 2023

Using the dynamic panel model, this study investigates rent determinants for small and medium-sized office buildings in Korea's CBD and Gangnam areas, key business districts. The results reveal that rents for small and medium-sized office buildings in CBD and Gangnam areas are influenced by macroeconomic fluctuations and characteristics of buildings and locations, suggesting a market with both spatial consumer and investment goods attributes. There are several investment implications as follows. First, even if the location in the CBD area is advantageous, the practical limitations in renovating aging small and medium-sized office buildings must be taken into account when investing. Second, parking conditions are a key factor influencing rent prices in CBD areas, so evaluating the parking facilities and improvement potential of small and medium-sized office buildings is essential for investors. Finally, due to the high sensitivity of Gangnam's small and medium-sized office market to macroeconomic trends, it's vital to prioritize monetary policy shifts as a key factor in investment decisions.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.2
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• pp.141-156
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• 2023

The advancement of Information and Communication Technology (ICT), along with the expansion of government and private investment in startup discovery and funding, has led to the emergence of startups seeking to generate outstanding results based on innovative ideas. As successful startups serve as role models, the number of aspiring entrepreneurs preparing to launch their own startups continues to increase. However, unlike entrepreneurs who challenge themselves with serial entrepreneurship after experiencing success, early-stage startups face various challenges such as team building, technology development, and fundraising. Accelerators play a dual role of mentor and investor by providing education, mentoring, consulting, network connection, and initial investment activities to help startups overcome various challenges they face and facilitate their growth. This study investigated whether there is a correlation between the characteristics of startups and their entrepreneurial performance, and analyzed whether accelerators mediate the relationship between startup characteristics and entrepreneurial performance. A total of 11 hypotheses were proposed, and a survey was conducted on 302 startup founders and employees located across the country, including the metropolitan area, for empirical research. SPSS 23.0 and Amos 23.0 were used for statistical analysis. Through this study, it was found that factors such as innovation, organizational culture, financial characteristics, and learning orientation among the characteristics of startups, rather than having a direct impact on entrepreneurial performance, are linked to entrepreneurial performance through the role of accelerators. By analyzing the impact factors of startup characteristics on entrepreneurial performance, this study presents research on the role of accelerators and provides institutional improvements. It is expected to contribute to the expansion of investment and differentiated acceleration programs, enabling startups to seize the market and grow stably in the market.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.2
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• pp.77-84
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• 2024

In the fourth industrial-revolution era, the construction industry is transitioning from traditional methods to digital processes. This shift has been challenging owing to the industry's employment of diverse processes and extensive human resources, leading to a gradual adoption of digital technologies through trial and error. One critical area of focus is the safety management at construction sites, which is undergoing significant research and efforts towards digitization and automation. Despite these initiatives, recent statistics indicate a persistent occurrence of accidents and fatalities in construction sites. To address this issue, this study utilizes large-scale language-model artificial intelligence to analyze big data from a construction safety-management information network. The findings are integrated into on-site models, which incorporate real-time updates from detailed design models and are enriched with location information and spatial characteristics, for enhanced safety management. This research aims to develop a big-data-driven safety-management platform to bolster facility and worker safety by digitizing construction-site safety data. This platform can help prevent construction accidents and provide effective education for safety practices.

• Korean Journal of Construction Engineering and Management
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• v.25 no.3
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• pp.3-16
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• 2024

The government announced the Housing Welfare Roadmap (November 2017), to expand the supply of public rental housing by reconstructing aged long-term public rental complexes. Also, remodeling projects for complexes with low business feasibility of reconstruction projects are recognized as an alternative to supplying public rental housing in urban area. This study analyzed influence factors by dividing them into project feasibility, architectural plan, urban & residential environment plan, and legal system groups in order to establish a plan for long-term public rental housing remodeling project. Futhermore, this work conducted the principal component analysis to get the principal component factors among the influence factors of each group, and the weight analysis to calculate weighting of them. In addition, major influence factors were derived by calculating the relative importance score (RIS) of each factor. Lastly this paper validated the major influence factors and applicability of the procedure to select 3 complexes that can be reviewed for remolding project among 33 long-term public rental housing complexes located in Seoul. The results of this study are expected to be useful when establishing a remodeling project plan for long-term public rental housing.

• Informatization Policy
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• v.31 no.1
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• pp.53-71
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• 2024

Digital transformation calls for a new social contract that must transform the existing norms and paradigms of our society. Digital constitutionalism is a way of building new order through a new social contract and is an ideology that aims to establish and ensure a normative framework for the protection of fundamental rights and balance of power in the digital environment. The Internet/Digital Bill of Rights is a representative example of constitutionalization based on this ideology. Initially, it took the form of an informal, non-binding declaration led by civil society organizations or various stakeholders, setting forth normative principles adapted to the changing nature of digital society. More recently, they have taken the form of formal charters, declarations, or laws containing principles at the national or regional level. The "Digital Bill of Rights" proposed by the Korean government can be seen as an example of this trend, but it does not fully reflect the recent trend of Internet/Digital Bills of Rights in terms of substantive and procedural legitimacy. Even if the government provides a certain normative direction, it needs to be combined with a concrete action plan in each area to create a balance of norms with digital technologies and industries instead of simply being a "declaration".

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.1
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• pp.52-66
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• 2024

The purpose of this study is to identify the spatial system and characteristics of the urban center by deriving the boundaries of the urban center set in the urban basic plan for Busan Metropolitan City and diagnosing the role and status of the center. To this end, four indicators representing the characteristics of the center were selected through a review of previous studies, and the boundaries of the center were derived using spatial statistical techniques with strengths in geographical boundary analysis. Then, using the indicators of center characteristics and population potential functions, we diagnosed the influence and potential of each center in the spatial structure of Busan Metropolitan City. The analysis showed that the scale of the centers varies greatly, and the unutilized areas where commercial areas are not activated and the expansion areas that spread beyond commercial areas to residential and industrial areas are different for each urban center. The results of the potential measurement, which indicates the attractiveness of the center, also showed areas with strong and weak population potential. Therefore, systematic management and strategies based on the hierarchical characteristics and influence measurement results are needed to strengthen the function of urban centers. The results analyzed in this study can be used as a resource for responding to various urban planning needs and policy changes in the future, along with station area development plans and spatial innovation zones for building a sustainable urban growth system, balanced development, and strengthening the function of centers.

• International Journal of Computer Science & Network Security
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• v.24 no.9
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• pp.30-40
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• 2024

Building an accurate 3-D spatial road network model has become an active area of research now-a-days that profess to be a new paradigm in developing Smart roads and intelligent transportation system (ITS) which will help the public and private road impresario for better road mobility and eco-routing so that better road traffic, less carbon emission and road safety may be ensured. Dealing with such a large scale 3-D road network data poses challenges in getting accurate elevation information of a road network to better estimate the CO₂ emission and accurate routing for the vehicles in Internet of Vehicle (IoV) scenario. Clustering and regression techniques are found suitable in discovering the missing elevation information in 3-D spatial road network dataset for some points in the road network which is envisaged of helping the public a better eco-routing experience. Further, recently Explainable Artificial Intelligence (xAI) draws attention of the researchers to better interprete, transparent and comprehensible, thus enabling to design efficient choice based models choices depending upon users requirements. The 3-D road network dataset, comprising of spatial attributes (longitude, latitude, altitude) of North Jutland, Denmark, collected from publicly available UCI repositories is preprocessed through feature engineering and scaling to ensure optimal accuracy for clustering and regression tasks. K-Means clustering and regression using Support Vector Machine (SVM) with radial basis function (RBF) kernel are employed for 3-D road network analysis. Silhouette scores and number of clusters are chosen for measuring cluster quality whereas error metric such as MAE ( Mean Absolute Error) and RMSE (Root Mean Square Error) are considered for evaluating the regression method. To have better interpretability of the Clustering and regression models, SHAP (Shapley Additive Explanations), a powerful xAI technique is employed in this research. From extensive experiments , it is observed that SHAP analysis validated the importance of latitude and altitude in predicting longitude, particularly in the four-cluster setup, providing critical insights into model behavior and feature contributions SHAP analysis validated the importance of latitude and altitude in predicting longitude, particularly in the four-cluster setup, providing critical insights into model behavior and feature contributions with an accuracy of 97.22% and strong performance metrics across all classes having MAE of 0.0346, and MSE of 0.0018. On the other hand, the ten-cluster setup, while faster in SHAP analysis, presented challenges in interpretability due to increased clustering complexity. Hence, K-Means clustering with K=4 and SVM hybrid models demonstrated superior performance and interpretability, highlighting the importance of careful cluster selection to balance model complexity and predictive accuracy.

• Journal of Korean Society of Rural Planning
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• v.30 no.3
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• pp.19-28
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• 2024

This study investigated and analyzed the landscape conservation activity promotion process targeting the 'Alassiasdeuli Community Farming Association Corporation', which is carrying out continuous rural landscape conservation activities led by local residents in the area of Yeohang Mountain, Yeohang-myeon, Haman-gun, Gyeongsangnam-do. Through this, the factors necessary to promote rural landscape conservation activities led by residents were identified, and implications necessary for rural landscape conservation activities led by residents were derived. The first factor that allowed Alassiasdeuli to pursue resident-led rural landscape conservation activities was the fact that an economically stable foundation was established before pursuing conservation activities. Rural landscape conservation activities are carried out based on continuous agricultural activities, and agriculture is closely related to the economic aspect. Accordingly, Alassiasdeuli had a small but regular income from the package business, and was able to carry out various rural landscape conservation activities based on this. Second, within the community, a sense of purpose for rural landscape conservation was shared as a common value. It started with common values that were in line with rural landscape conservation, such as an economic community based on agriculture, indigenous seed conservation, and eco-friendly agriculture, and later, awareness of traditional agriculture and rural landscape conservation was gradually established through members' continued empowerment and related experiences. It has been done. Third, various connections and cooperative relationships were established with residents, related organizations, and administration. We established cooperative relationships by recruiting local organizations and residents as active participants beyond program participation, and exchanged information and expanded the scope of activities by establishing networks with organizations such as the 'Gyeongnam Darang-Non Network'. In addition, through connection with administration, we experienced various projects and ensured the sustainability of activities through support. Fourth, there was a keyman who could organize activities and control the scale of support projects, taking into account the awareness and capabilities of members. In particular, it is thought that this was possible because the Secretary General was based on building a relationship of trust with residents before Alassiasdeuli was formed. Therefore, in order for resident-led rural landscape conservation activities to be continuously carried out, an organization must be formed centered on farmers, and the economic sustainability of the organization, sharing of common values, and trust relationships among members are the basis, and the Sustainable activities can be promoted through various cooperative relationships between residents, organizations, and administration.

• Journal of the Korean Geotechnical Society
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• v.40 no.4
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• pp.91-103
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• 2024

In this study, we propose an outlier detection method that considers the spatial distribution of intelligent compaction measurement values (ICMVs) to address the high variability of ICMVs measured continuously across an entire construction area. The proposed method initially identified cases where the CMV at a specific location decreased despite an increase in the number of compaction passes. Among these, values that significantly differed from those measured within a 1.5-m radius were classified as outliers. Applying this method to CMV data obtained from field tests, we found that it effectively excluded the influence of changes in roller operating conditions unrelated to compaction quality while considering the inherent heterogeneity of the soil. However, after removing the outliers, the coefficient of variation of CMV (21.4%-26.3%) remained higher than the 20% suggested by relevant standards. Further field tests are needed to modify the proposed outlier detection method and to establish reasonable criteria for the variability of ICMV.