Journal of the Korean BIBLIA Society for library and Information Science
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v.33
no.1
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pp.371-401
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2022
If the blockchain means storing information in a distributed environment that cannot be forged or altered, it is mentioned that this is similar to what librarians collect, preserve, and share authoritative information. In this way, this study examined blockchain technology as a way to collect and provide reliable information, increase work efficiency inside and outside the library, and strengthen cooperative networks. This study attempted to propose various ways to utilize blockchain technology in book relations based on literature surveys and case studies in other fields. To this end, this study first analyzed the field and cases of blockchain application to confirm the possibility and value of blockchain application in the library field, and proposed 12 ways to utilize it based on this. The utilization model was proposed by dividing it into operation and service sectors. In the operation sector, it is a digital identity-based user record storage and authentication function, transparent management and traceable monitoring function, voting-based personnel and recruitment system, blockchain governance-based network efficiency function, and blockchain-based next-generation device management and information integration function. The service sector includes improved book purchase and sharing efficiency due to simplification of intermediaries, digital content copyright protection and management functions, customized service provision based on customer behavior analysis, blockchain-based online learning platforms, sharing platforms, and P2P-based reliable information sharing platforms.
With rapid advancements taking place in the Fourth Industrial Revolution, human-robot interactions have been garnering increasing attention. Robots are being actively adopted in building systems and facilities. In this study, we developed robot-friendly building certification indicators. Because these indicators were being developed for the first time, we focused only on commercial buildings. We conducted exploratory research using methodologies such as focus group interviews and the analytic hierarchy process. First, the concept of the robot-friendly building was defined through focus group interviews, and the requirements were categorized by the appropriateness of operating facilities and systems and the appropriateness of architectural and robot operating systems and networks. Next, the relative importance of the evaluation items (23 items in total) was calculated using the analytic hierarchy process. Their average score of the marks was 4.4, and the minimum and maximum were 2.0 and 11.3, respectively. This study is significant because we collected the basic data necessary to develop a one-of-its-kind evaluation system for certifying the robot-friendliness of buildings using scientific methods.
The Journal of the Convergence on Culture Technology
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v.9
no.3
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pp.715-720
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2023
The military is driving innovative changes such as AI, cloud computing, and drone operation through the Fourth Industrial Revolution. It is expected that such changes will lead to a rapid increase in the demand for information exchange requirements, reaching all lower-ranking soldiers, as networking based on IoT occurs. The flow of such information must ensure efficient information distribution through various infrastructures such as ground networks, stationary satellites, and low-earth orbit small communication satellites, and the demand for information exchange that is distributed through them must be appropriately dispersed. In this study, we redefined the DSCP, which is closely related to QoS (Quality of Service) in information dissemination, into 11 categories and performed research to map each cluster group identified by cluster analysis to the defense "information exchange requirement list" on a one-to-one basis. The purpose of the research is to ensure efficient information dissemination within a multi-layer integrated network (ground network, stationary satellite network, low-earth orbit small communication satellite network) with limited bandwidth by re-establishing QoS policies that prioritize important information exchange requirements so that they are routed in priority. In this paper, we evaluated how well the information exchange requirement lists classified by cluster analysis were assigned to DSCP through M&S, and confirmed that reclassifying DSCP can lead to more efficient information distribution in a network environment with limited bandwidth.
Proceedings of the Korean Institute of Navigation and Port Research Conference
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2022.06a
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pp.391-393
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2022
In recent years, technologies forecasting demand based on deep learning and big data have accelerated the smartification of the field of e-commerce, logistics and distribution areas. In particular, ports, which are the center of global transportation networks and modern intelligent logistics, are rapidly responding to changes in the global economy and port environment caused by the 4th industrial revolution. Port traffic forecasting will have an important impact in various fields such as new port construction, port expansion, and terminal operation. Therefore, the purpose of this study is to compare the time series analysis and deep learning analysis, which are often used for port traffic prediction, and to derive a prediction model suitable for the future container prediction of Busan Port. In addition, external variables related to trade volume changes were selected as correlations and applied to the multivariate deep learning prediction model. As a result, it was found that the LSTM error was low in the single-variable prediction model using only Busan Port container freight volume, and the LSTM error was also low in the multivariate prediction model using external variables.
Journal of the Korean Regional Science Association
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v.40
no.2
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pp.91-106
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2024
Around the world, many countries experiencing the issue of shrinking cities are continually expanding high-speed rail networks to enhance regional accessibility and address imbalances. This study analyzed the effects of high-speed train operations on the age-specific population migration in South Korean municipalities from 2012 to 2019, taking into account the risk levels of shrinking cities. For this purpose, an analysis was conducted using age-specific net in-migration population as the dependent variable, employing the spatial panel autoregressive model. The research results indicated that the influence of high-speed rail on regional population inflow varies depending on the risk level of shrinking city. In other words, high-speed railway operations had positive effects on population inflow in the capital areas and some major cities, while explained population outflow in the other regions. High-speed railways particularly exerted a significant impact on the inflow of the young and middle-aged population, representing the working age, but this effect was also limited to regions with a low risk of shrinkage. The findings of this study emphasize the importance of considering planned population and industrial attraction when installing high-speed rail with the goal of achieving regional balanced development and mitigating shrinkage. The results of this study also suggest the need for subsequent research to explore factors that positively influence population structure and inflow based on the level of shrinkage risk in each region, as well as the introduction of new policies tailored to the specific situations of each local government.
The advancement of IT and the "Fourth Industrial Revolution" blurred the boundary between industries. The importance of strategic cooperation between enterprises is emphasized. IT companies must consider their existing business areas and create new territories to drive changes in the industry. They must also secure their competitive edge and manage economic costs to enable them to compete with their global counterparts. By utilizing their resources effectively, these firms can create value through inter-firm cooperation. This study analyzes the collaborative network of global IT companies using social network analysis and examines the effect of this network on firm performance. Collaborative linkages and betweenness centrality, which represent the bridging position of a firm in a network, significantly affect firm performance. This result highlights the importance of the structural position of a firm in a cooperative network of IT companies. This study also characterizes clusters in a network of IT companies. Most of these clusters comprise a combination of IT companies in diverse IT industries. These clusters suggest that these companies engage in multilateral cooperation without boundaries to maximize their business capabilities. This study offers practical implications for establishing a cooperative strategy and framework that can capture business trends in the IT industry from a macroscopic view. This study also visualizes collaborative networks in a multifaceted way using social network analysis to provide researchers and business practitioners with an informative viewpoint.
Journal of the Korea Society of Computer and Information
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v.29
no.9
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pp.1-7
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2024
In this paper, we proposes a Convolutional Neural Networks(CNN) equipped with Batch Normalization(BN) for handwritten digit recognition training the MNIST dataset. Aiming to surpass the performance of LeNet-5 by LeCun et al., a 6-layer neural network was designed. The proposed model processes 28×28 pixel images through convolution, Max Pooling, and Fully connected layers, with the batch normalization to improve learning stability and performance. The experiment utilized 60,000 training images and 10,000 test images, applying the Momentum optimization algorithm. The model configuration used 30 filters with a 5×5 filter size, padding 0, stride 1, and ReLU as activation function. The training process was set with a mini-batch size of 100, 20 epochs in total, and a learning rate of 0.1. As a result, the proposed model achieved a test accuracy of 99.22%, surpassing LeNet-5's 99.05%, and recorded an F1-score of 0.9919, demonstrating the model's performance. Moreover, the 6-layer model proposed in this paper emphasizes model efficiency with a simpler structure compared to LeCun et al.'s LeNet-5 (7-layer model) and the model proposed by Ji, Chun and Kim (10-layer model). The results of this study show potential for application in real industrial applications such as AI vision inspection systems. It is expected to be effectively applied in smart factories, particularly in determining the defective status of parts.
Journal of the Korea Academia-Industrial cooperation Society
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v.19
no.2
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pp.279-292
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2018
Unlike the global art market which experienced rapid recovery from the impacts of the Global Financial Crisis in 2008, the Korean art market has not yet fully recovered. The gallery-oriented distribution system, vulnerable primary art market functions, and the market structure centered on a small number of collectors make it difficult for young and medium artists to enter the market and, as a result, deepen the economic polarization of artists. In addition, the high price of art works limits market participation by restricting the general public. This study began with the idea that the interest of the public in the art market as well as their participation in the market are urgent. To this end, we noted that public awareness of art transactions can be a starting point for improving the constitution of the fragile art market, focusing on the 'Artist-centered Art Fair' rather than existing art fairs. To examine the contribution of such an art fair to the popularization of the art market, we analyzed the case of the 'Visual Artist Market (VAM)' project of the Korea Arts Management Service. Results found that the 'Artist-centered Art Fair' focuses on providing opportunities for market entry to young and medium artists rather than on the interests of distributors, and promotes the popularization of the art market by promoting low-priced works to the general public. Also, the 'Artist-centered Art Fair' seems to play a primary role in the public sector to foster solid groups of artists as well as to establish healty distribution networks of Korean Art market. However, in the long run, it is necessary to promote sustainable development of the 'Artist-centered Art Fair' through indirect support, such as the provision of a publicity platform or consumer finance support, rather than direct support.
Journal of Korea Society of Industrial Information Systems
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v.23
no.5
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pp.119-134
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2018
Today, many firms face the environment of high uncertainty and severe competition due to the rapid technology development and the diverse needs of customers. In the business environment, one of the most important ways to gain sustainable competitive advantage and future growth engine is related to NPD (New Product Development), which is a very important issue for practice and academia. Thus, this study intends to provide new values to practitioners and researchers related to NPD by analyzing current research trends and future trends in NPD field. For this, we bibliometrically analyzed keyword networks which consist of keywords that were already published in the eminent journals from Scopus database to generate insights that have not been captured in the previous reviews on the topic. As a result, we could understand the extant research streams in NPD field, and suggest the changes of specific research topics based on the connected relationships among keywords over the time. In addition, we also foresaw the general future research trends in NPD field based on the keywords according to preferential attachment processes. Through this study, it was confirmed that NPD keyword network is a small world network that follows the distribution of power law and the growth of network is formed by link formation by keyword preferential attachment. In addition, through component analysis and centrality analysis, keywords such as Innovation, New product innovation, Risk management, Concurrent engineering, Research and development, and Product life cycle management are highly centralized in NPD keyword network. On the other hand, as a result of examining the change of preferential attachment of keywords over the time, we suggested the required new research direction including i) NPD collaboration with suppliers, ii) NPD considering market uncertainty, iii) NPD considering convergence with the other academic areas like technology management and knowledge management, iv) NPD from SME(Small and medium enterprises) perspective. The results of this study can be used to determine the research trends of NPD and the new research themes for interdisciplinary studies with other disciplines.
Journal of Korean Society of Environmental Engineers
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v.36
no.6
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pp.421-428
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2014
For the analysis of water supply network, demand-driven and pressure-driven analysis methods have been proposed. Of the two methods, demand-driven analysis (DDA) can only be used in a normal operation condition to evaluate hydraulic status of a pipe network. Under abnormal conditions, i.e., unexpected pipe destruction, or abnormal low pressure conditions, pressure-driven analysis (PDA) method should be used to estimate the suppliable flowrate at each node in a network. In order to carry out the pressure-driven analysis, head-outflow relationship (HOR), which estimates flowrate at a certain pressure at each node, should be first determined. Most previous studies empirically suggested that each node possesses its own characteristic head-outflow relationship, which, therefore, requires verification by using actual field data for proper application in PDA modeling. In this study, a model pipe network was constructed, and various operation scenarios of normal and abnormal conditions, which cannot be realized in real pipe networks, were established. Using the model network, data on pressure and flowrate at each node were obtained at each operation condition. Using the data obtained, previously proposed HOR equations were evaluated. In addition, head-outflow relationship at each node was analyzed especially under multiple pipe destruction events. By analyzing the experimental data obtained from the model network, it was found that flowrate reduction corresponding to a certain pressure drop (by pipe destruction at one or multiple points on the network) followed intrinsic head-outflow relationship of each node. By comparing the experimentally obtained head-outflow relationship with various HOR equations proposed by previous studies, the one proposed by Wagner et al. showed the best agreement with the exponential parameter, m of 3.0.
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