• KIPS Transactions on Software and Data Engineering
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• v.12 no.5
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• pp.199-206
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• 2023

The current software becomes the huge size of source codes. Therefore it is increasing the importance and necessity of static analysis for high-quality product. With static analysis of the code, it needs to identify the defect and complexity of the code. Through visualizing these problems, we make it guild for developers and stakeholders to understand these problems in the source codes. Our previous visualization research focused only on the process of storing information of the results of static analysis into the Database tables, querying the calculations for quality indicators (CK Metrics, Coupling, Number of function calls, Bad-smell), and then finally visualizing the extracted information. This approach has some limitations in that it takes a lot of time and space to analyze a code using information extracted from it through static analysis. That is since the tables are not normalized, it may occur to spend space and time when the tables(classes, functions, attributes, Etc.) are joined to extract information inside the code. To solve these problems, we propose a regularized design of the database tables, an extraction mechanism for quality metric indicators inside the code, and then a visualization with the extracted quality indicators on the code. Through this mechanism, we expect that the code visualization process will be optimized and that developers will be able to guide the modules that need refactoring. In the future, we will conduct learning of some parts of this process.

• Korean Journal of Legislative Studies
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• v.26 no.1
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• pp.105-145
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• 2020

This study analyzes the effect of institutionalization of Korean metropolitan councils on legislation productivity. Based on the theory of institutionalization of legislatures, three independent variables (stability, complexity and adaptability) were selected to measure the level of institutionalization of a metropolitan council and nine sub-analysis indicators. The main results of the analysis of the effect of the institutionalization of the metropolitan council on legislation productivity are as follows: First, the factors that determine the number of reported bills were the ratio of first-term lawmakers, average number of elected of the chairmen, number of special committees, number of legislative experts, actual age of metropolitan councils, and number of voters per lawmaker. Second, the factors that determine the rate of reported bills were the average number of elected of the chairmen, the number of special committees, the number of legislative experts, the actual age of metropolitan councils, and the number of voters per lawmaker. Third, the factors that determine the number of reported bills per lawmaker is the average number of elected of the chairmen, the actual age of metropolitan councils, and the number of voters per lawmaker. The above result points out that legislation productivity differences of past metropolitan councils can be understood as differences arising from legislative institutionalization levels and several policy considerations can be made to enhance legislation productivity of metropolitan councils.

• Tunnel and Underground Space
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• v.33 no.6
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• pp.594-609
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• 2023

TBM (Tunnel Boring Machine) method is gaining popularity in urban and underwater tunneling projects due to its ability to ensure excavation face stability and minimize environmental impact. Among the prominent models for predicting disc cutter life, the NTNU model uses the Cutter Life Index(CLI) as a key parameter, but the complexity of testing procedures and rarity of equipment make measurement challenging. In this study, CLI was predicted using multiple linear regression analysis and tree-based machine learning techniques, utilizing rock properties. Through literature review, a database including rock uniaxial compressive strength, Brazilian tensile strength, equivalent quartz content, and Cerchar abrasivity index was built, and derived variables were added. The multiple linear regression analysis selected input variables based on statistical significance and multicollinearity, while the machine learning prediction model chose variables based on their importance. Dividing the data into 80% for training and 20% for testing, a comparative analysis of the predictive performance was conducted, and XGBoost was identified as the optimal model. The validity of the multiple linear regression and XGBoost models derived in this study was confirmed by comparing their predictive performance with prior research.

• Journal of the Economic Geographical Society of Korea
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• v.26 no.3
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• pp.202-222
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• 2023

This study traces the growth and changes in the spatial distribution and characteristics of media cluster in Seoul by focusing on the co-evolution of film and TV production. To identify the spatial distribution and aggregation of film and broadcast TV production, we measure their spatial auto-correlation based on Moran's I and LISA, using the data from the Census on Establishments of the National Statistical Office. In addition, the eleven semi-structured interviews conducted with workers in the media industries, such as film crews and TV drama producers, help to clarify the complexity and dynamics of diverse factors that affect spatial distribution of media cluster. This multi-method study shows the increasing polycentricity of media cluster in the last decade. Gangnam, Mapo, Yeouido, Gangseo-Yeongdeungpo, and Seongsu have emerged as key hubs for media industries, particularly in light of changes in the transportation system and the real estate market. The finding indicates the co-evolution of film and broadcast TV production, demonstrating how the characteristics of the creative industry and metropolitan changes are intertwined with each other in shaping the geographical pattern of the media cluster.

• Information Systems Review
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• v.23 no.3
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• pp.97-125
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• 2021

Blockchain is a core technology to solve personal information leakage and data management issues, which are limitations of existing Genomic Sequencing services. Due to continuous cost reduction and deregulation, the market size of Genomic Sequencing has been increasing, also the potential of services is expected to increase when Blockchain's security and connectivity are combined. We created our research model by combining the Technology Acceptance Model (TAM) and the Innovation Resistance Theory also analyzed the factors affecting the acceptance intention and innovation resistance of the Blockchain Based Genomic Sequencing Information Platform. A survey was conducted on 150 potential users of Blockchain and Genomic Sequencing services. The analysis was conducted by setting the four Blockchain variables: Security, transparency, availability, and diversity). Also, we set the Perceived Usefulness, Perceived risk, and Perceived Complexity for Technology Acceptance and Innovation Resistance variables and analyzed the effect of the characteristics of the Blockchain on acceptance intention and innovation resistance through these variables. Through this analysis, key variables that need to be considered important to reduce resistance and increase acceptance intention could be identified. This study presents innovation factors that should be considered in companies preparing a new Blockchain Based Genomic Sequencing Information Platform.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.37-42
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• 2024

This paper suggests polynomial time algorithm for cutwidth minimization problem that classified as NP-complete because the polynomial time algorithm to find the optimal solution has been unknown yet. To find the minimum cutwidth CW_f(G)=max_𝜈∈_VCW_f(𝜈)for given graph G=(V,E),m=｜V｜, n=｜E｜, the proposed algorithm divides neighborhood N_G[𝜈_i] of the maximum degree vertex 𝜈_i in graph G into left and right and decides the vertical cut plane with minimum number of edges pass through the vertex 𝜈_i firstly. Then, we split the left and right N_G[𝜈_i] into horizontal sections with minimum pass through edges. Secondly, the inner-section vertices are connected into line graph and the inter-section lines are connected by one line layout. Finally, we perform the optimization process in order to obtain the minimum cutwidth using vertex moving method. Though the proposed algorithm requires O(n²) time complexity, that can be obtains the optimal solutions for all of various experimental data

• Journal of Ecology and Environment
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• v.47 no.4
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• pp.228-240
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• 2023

Growing complexity in ecosystem structure and functions, under impacts of climate and land-use changes, requires interdisciplinary understandings of processes and the whole-system, and accurate estimates of the changing functions. In the last three decades, observation networks for biodiversity, ecosystems, and ecosystem functions under climate change, have been developed by interested scientists, research institutions and universities. In this paper we will review (1) the development and on-going activities of those observation networks, (2) some outcomes from forest carbon cycle studies at our super-site "Takayama site" in Japan, and (3) a few ideas how we connect in-situ and satellite observations as well as fill observation gaps in the Asia-Oceania region. There have been many intensive research and networking efforts to promote investigations for ecosystem change and functions (e.g., Long-Term Ecological Research Network), measurements of greenhouse gas, heat, and water fluxes (flux network), and biodiversity from genetic to ecosystem level (Biodiversity Observation Network). Combining those in-situ field research data with modeling analysis and satellite remote sensing allows the research communities to up-scale spatially from local to global, and temporally from the past to future. These observation networks oftern use different methodologies and target different scientific disciplines. However growing needs for comprehensive observations to understand the response of biodiversity and ecosystem functions to climate and societal changes at local, national, regional, and global scales are providing opportunities and expectations to network these networks. Among the challenges to produce and share integrated knowledge on climate, ecosystem functions and biodiversity, filling scale-gaps in space and time among the phenomena is crucial. To showcase such efforts, interdisciplinary research at 'Takayama super-site' was reviewed by focusing on studies on forest carbon cycle and phenology. A key approach to respond to multidisciplinary questions is to integrate in-situ field research, ecosystem modeling, and satellite remote sensing by developing cross-scale methodologies at long-term observation field sites called "super-sites". The research approach at 'Takayama site' in Japan showcases this response to the needs of multidisciplinary questions and further development of terrestrial ecosystem research to address environmental change issues from local to national, regional and global scales.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.501-506
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• 2024

Humans have been shown to engage in multitasking behavior when searching for information on two or more topics or searching an information system at the same time. When processing multiple information tasks, priorities must be established as there are cognitive and physical limitations in processing multiple information tasks at once. The level of cognitive attention involved in multitasking behavior can vary depending on the complexity and importance of the information task. The objectives of this study are to understand: (a) the relationship between attention and information task prioritization behavior when people interact with information retrieval systems to find information for multiple tasks; (b) The effect of the degree of attention on information task prioritization behavior when people interact with an IR system to find information for multiple tasks. A review of the relevant literature shows that when people interact with information retrieval systems to find information for multiple tasks, their level of attention affects how they prioritize multiple information tasks. It should be noticed that people pay more attention to things they find interesting or important. Human-centered system design based on a conceptual understanding of multitasking is discussed.

• The Transactions of the Korea Information Processing Society
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• v.13 no.7
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• pp.326-334
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• 2024

Extra-oral imaging techniques such as Panoramic X-rays (PXs) and Cone Beam Computed Tomography (CBCT) are the most preferred imaging modalities in dental clinics owing to its patient convenience during imaging as well as their ability to visualize entire teeth information. PXs are preferred for routine clinical treatments and CBCTs for complex surgeries and implant treatments. However, PXs are limited by the lack of third dimensional spatial information whereas CBCTs inflict high radiation exposure to patient. When a PX is already available, it is beneficial to reconstruct the 3D oral structure from the PX to avoid further expenses and radiation dose. In this paper, we propose 3DentAI - an U-Net based deep learning framework for 3D reconstruction of oral structure from a PX image. Our framework consists of three module - a reconstruction module based on attention U-Net for estimating depth from a PX image, a realignment module for aligning the predicted flattened volume to the shape of jaw using a predefined focal trough and ray data, and lastly a refinement module based on 3D U-Net for interpolating the missing information to obtain a smooth representation of oral cavity. Synthetic PXs obtained from CBCT by ray tracing and rendering were used to train the networks without the need of paired PX and CBCT datasets. Our method, trained and tested on a diverse datasets of 600 patients, achieved superior performance to GAN-based models even with low computational complexity.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.389-395
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• 2024

This study aims to deeply analyze the military strategies and tactics used in the battles between Israel and Hamas, to understand the military approaches, technical capabilities, and their impact on the outcomes of the conflict. To achieve this, methodologies such as literature review, data analysis, and case studies were utilized. The research findings confirm that Hamas employed asymmetric tactics, such as rocket attacks and surprise attacks through underground tunnels, to counter Israel's military superiority. On the other hand, Israel responded to Hamas's attacks with the Iron Dome interception system and intelligence-gathering capabilities, but faced difficulties due to Hamas's underground tunnel network. After six months of fighting, the casualties in the Gaza Strip exceeded 30,000, and more than 1.7 million people became refugees. Israel also suffered over 1,200 deaths. Militarily, neither side achieved a decisive victory, resulting in a war of attrition. This study suggests that the Israel-Hamas war exemplifies the complexity of modern asymmetric warfare. Furthermore, it recommends that political compromise between the two sides and active mediation efforts by the international community are necessary for the peaceful resolution of the Israel-Palestine conflict.