• Journal of Convergence for Information Technology
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• v.9 no.9
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• pp.133-140
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• 2019

Following the recent US trade deficit, the trade war began between Korea and Japan in July. Korea's trade dependence is about 60% or more, indicating high export dependence and import dependence. The purpose of this study is to examine export amount, export volume, export price index, Treasury bond interest rate and analyze how index affects export amount. This study attempts to analyze the comovement and volatility with export amount. For this purpose, monthly data for each indicator were selected for a total of 234 months from January 2000 to June 2019. As a result of analysis, exports amount and exports volume showed very high comovement, exports amount and interest rates showed low comovement, but exports amount and exports prices showed very low comovement. In the future, Korea should continue to increase exports amount in view of its high dependence on trade, along with policies to expand the domestic market. To this end, strategy to increase exports volume should be presented. Korea should increase the logistics environment and competitiveness of each port and airport, improve domestic and overseas network construction and support services of logistics companies.

• 한국사회정책
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• v.23 no.2
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• pp.113-139
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• 2016

This article tries to compare exchange relations between welfare and dictatorship in the East Germany and the North Korea. Unlike capitalist welfare aiming at correcting market results socialist welfare has been proposed to satisfy people's basic needs, but it had operated as instrument of dictatorship. Relation between welfare and dictatorship could be distinguished as hard exchange and soft one in line with social construction of welfare. Welfare-dictatorship relation in East Germany had developed from its formation(1949-1970s), crisis(1980s) and dissolution(1989-1990). There had established hard exchange relation in which the legitimacy of dominance had debted to welfare as social rights. While crisis of the exchange relation had been modest in a form of insufficient supply of consumption goods, it was one of the elements of collapse of dictatorship, leading to the unification with West Germany. The journey of the exchange relation in North Korea can be characterized by its formation(1948-1980), crisis(1990s-2000s), and transformation(2010s). Unlike East Germany, welfare was socially constructed as gift form the ruler to the ruled, which made the combination of welfare and dictatorship loosely coupled. Although economic crisis was severe compared to East German one the rulers have succeeded maintaining dictatorial dominance by creating dual exchange relation. They separated core group and subordinated one supporting the former at the expense of the latter. They blocked out most of the people from soft exchange relation making bad use of muddling-through life style dependent on market activities. This strategy led to a 'dictatorship neutral welfare extinction'. Taking the high degree of institutionalization of newly establishing welfare-dictatorship relation into account, lives of most people are hardly expected to be improved by gift by their rulers even if North Korean economy will recover in the future.

• Journal of Internet Computing and Services
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• v.23 no.1
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• pp.77-86
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• 2022

The Republic of Korea is a country in which coastal surveillance is an imperative national task as it is surrounded by seas on three sides under the confrontation between South and North Korea. However, due to Defense Reform 2.0, the number of R/D (Radar) operating personnel has decreased, and the period of service has also been shortened. Moreover, there is always a possibility that a human error will occur. This paper presents specific guidelines for developing an AI learning model for the intelligent coastal surveillance system. We present a three-step strategy to realize the guidelines. The first stage is a typical stage of building an AI learning model, including data collection, storage, filtering, purification, and data transformation. In the second stage, R/D signal analysis is first performed. Subsequently, AI learning model development for classifying real and false images, coastal area analysis, and vulnerable area/time analysis are performed. In the final stage, validation, visualization, and demonstration of the AI learning model are performed. Through this research, the first achievement of making the existing weapon system intelligent by applying the application of AI technology was achieved.

• Journal of Navigation and Port Research
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• v.45 no.6
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• pp.333-345
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• 2021

Amid the rapidly changing logistics environment and demand changes in the post-corona-19 era, the importance of the cold chain logistics sector is being highlighted. The scope of cold chain is not limited to food, but is expanding to various fields such as pharmaceuticals, semiconductors, and flowers. The demand on the storage and transportation of corona vaccines is rapidly increasing. The rapid increase in domestic low-temperature facility construction and renovation may lead to the saturation of the cold chain related industry in the future and slow growth. In preparation for this, it is necessary to accumulate infrastructure know-how using IT technologies, and to consider entering into the UN procurement market as a potential niche market, by taking advantage of Korea's recent global status. The demand for cold chain in the UN procurement market is increasing mainly in underdeveloped countries, and it is expected to continue to grow. In this paper, the capabilities of domestic cold chain related companies were analyzed, domestic and overseas cold chain logistics market trends and overseas market entry status were investigated. An in-depth survey was conducted to present strategies for domestic cold chain logistics related companies to enter the UN procurement market.

• Journal of the Korea Society for Simulation
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• v.19 no.2
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• pp.29-41
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• 2010

Due to the recent technological advance, new types of AS/RS which can handle containers are being developed, and it is expected that they will be applied to related industries before long. Some companies and institutes in our country have constructed pilot systems for high-density-high-stacking systems and tested them to develop AS/RS-typed warehouses for containers. Along with this kind of construction efforts, development of rules to operate such systems efficiently and safely is also important. When outward-bound shipment is scheduled in container port, re-marshalling which rearranges containers in the yard to make shipment easy is conducted. In this paper, operating rules for the re-marshalling as well as simulation experiments to evaluate the performance of the rules are presented. We suggested two kinds of alternative sets of operating rules for re-marshalling and described the relevant logics corresponding to all possible cases for each alternative of operating rules. Through various simulation experiments, we found that each alternative has the merits and demerits at the same time and we could not say the one is always superior to the other. As a useful strategy, changing the applying operating rule is recommended from moment to moment depending on the expected number of operations at the landside input/output position.

• Geophysics and Geophysical Exploration
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• v.26 no.3
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• pp.114-125
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• 2023

The physics-informed neural network (PINN) has been proposed to overcome the limitations of various numerical methods used to solve partial differential equations (PDEs) and the drawbacks of purely data-driven machine learning. The PINN directly applies PDEs to the construction of the loss function, introducing physical constraints to machine learning training. This technique can also be applied to wave equation modeling. However, to solve the wave equation using the PINN, second-order differentiations with respect to input data must be performed during neural network training, and the resulting wavefields contain complex dynamical phenomena, requiring careful strategies. This tutorial elucidates the fundamental concepts of the PINN and discusses considerations for wave equation modeling using the PINN approach. These considerations include spatial coordinate normalization, the selection of activation functions, and strategies for incorporating physics loss. Our experimental results demonstrated that normalizing the spatial coordinates of the training data leads to a more accurate reflection of initial conditions in neural network training for wave equation modeling. Furthermore, the characteristics of various functions were compared to select an appropriate activation function for wavefield prediction using neural networks. These comparisons focused on their differentiation with respect to input data and their convergence properties. Finally, the results of two scenarios for incorporating physics loss into the loss function during neural network training were compared. Through numerical experiments, a curriculum-based learning strategy, applying physics loss after the initial training steps, was more effective than utilizing physics loss from the early training steps. In addition, the effectiveness of the PINN technique was confirmed by comparing these results with those of training without any use of physics loss.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.7
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• pp.427-437
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• 2016

This study has the goal of analyzing the techniques and characteristics of urban development, after additionally constructing the high-speed railway in Japan's Kyushu district and building a new railway station to enable the existing traditional stations accommodate with the high-speed railway. Such analysis is made in order to draw the conclusion of its intended (designed) meaning and attributes and to further research on finding an applicable urban development method in the domestic railway station development. The object of this study includes examples of stations renewed within the five years when Shinkansen in the Kyushu district was extended or stations which are in process of development such as Hakata station, Kumamoto station, and Kagoshima-chuo station. From the analysis of this study, the strategies are as follows.; active connecting both geographical location and function of Station, re-establishment of relation with city center and Station, establishment of close linking system for both tourist spot development, methods of Shinkansen line construction and extension a development opposite site of railway, securing the living population from high density & Mixed use development of Station Building.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.3
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• pp.205-216
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• 2024

Recently, seismic Probabilistic Safety Assessment (PSA) methods have been developed for process plants, such as gas plants, oil refineries, and chemical plants. The framework originated from the PSA of nuclear power plants, which aims to assess the risk of reactor core damage. The original PSA method was modified to adopt the characteristics of a process plant whose purpose is continuous operation without shutdown. Therefore, a fault tree, whose top event is shut down, was constructed and transformed into a Bayesian Network (BN), a probabilistic graph model, for efficient risk-informed decision-making. In this research, the fault tree-based BN from the previous research is further developed to consider the multi-hazard of earthquake-induced fire and explosion (EQ-induced F&E). For this purpose, an event tree describing the occurrence of fire and explosion from a release is first constructed and transformed into a BN. And then, this BN is connected to the previous BN model developed for seismic PSA. A virtual plot plan of a gas plant is introduced as a basis for the construction of the specific EQ-induced F&E BN to test the proposed BN framework. The paper demonstrates the method through two examples of risk-informed decision-making. In particular, the second example verifies how the proposed method can establish a repair and retrofit strategy when a shutdown occurs in a process plant.

• Information Systems Review
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• v.20 no.2
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• pp.87-110
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• 2018

This study reviews previous studies about the effects of RFID capabilities on strategic supply chain competence and business performance in the Chinese context. This study introduces a new perspective that measures the degree to which RFID capability levels contribute to business performance. Such an assumption is based on the fact that companies build their own capabilities through RFID capabilities and that these capabilities provide a competitive advantage for enterprises. Data on all sorts of logistics, distribution, and manufacturing companies that introduced RFID system in China were collected for data analysis. This study analyzes the structural equation modeling using Smart-PLS 2.0 program. This study confirms that internal reliability, convergent validity, and discriminant validity are satisfied. The hypothesis test result on the relationship between RFID capacity and strategic supply chain competence and strategic supply chain competence and company results is partially adopted. This study aids in establishing a RFID system construction strategy to enhance supply chain competence by suggesting guidelines for the successful introduction of RFID system through identifying the causal relationship between RFID capacity and strategic supply chain competence. This study also suggests the influence of RFID competency on visibility, agility, flexibility, and collaborations.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.209-223
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• 2024

In the context of the fourth industrial revolution, data-driven decision-making has increasingly become pivotal. However, the integrity of data analysis is compromised if data quality is not adequately ensured, potentially leading to biased interpretations. This is particularly critical for water level data, essential for water resource management, which often encounters quality issues such as missing values, spikes, and noise. This study addresses the challenge of noise-induced data quality deterioration, which complicates trend analysis and may produce anomalous outliers. To mitigate this issue, we propose a noise removal strategy employing Wavelet Transform, a technique renowned for its efficacy in signal processing and noise elimination. The advantage of Wavelet Transform lies in its operational efficiency - it reduces both time and costs as it obviates the need for acquiring the true values of collected data. This study conducted a comparative performance evaluation between our Wavelet Transform-based approach and the Denoising Autoencoder, a prominent machine learning method for noise reduction.. The findings demonstrate that the Coiflets wavelet function outperforms the Denoising Autoencoder across various metrics, including Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Mean Squared Error (MSE). The superiority of the Coiflets function suggests that selecting an appropriate wavelet function tailored to the specific application environment can effectively address data quality issues caused by noise. This study underscores the potential of Wavelet Transform as a robust tool for enhancing the quality of water level data, thereby contributing to the reliability of water resource management decisions.