• The Journal of the Korea Contents Association
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• v.8 no.5
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• pp.52-60
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• 2008

A simple Time Division Multiplex(TDM) switching system which has been widely in satellite networks provides any size of bandwidth for a number of low bandwidth subscribers by allocating proper number of time slots in a frame. In this paper, we propose a new approach based on graph coloring model for efficient time slot assignment algorithm in contrast to network flow model in previous works. When the frame length of an initial matrix of time slot requests is 2's power, this matrix is divided into two matrices of time slot requests using binary divide and conquer method based on the graph coloring model. This process is continued until resulting matrices of time slot requests are of length one. While the most efficient algorithm proposed in the literature has time complexity of $O(N^{4.5})$, the time complexity of the proposed algorithm is $O(NLlog_2L)$, where N is the number of input/output links and L is the number of time slot alloted to each link in the frame.

• Journal of the Korea Society of Computer and Information
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• v.12 no.4
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• pp.95-102
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• 2007

Recently, a lot of researchers focus on the sensor middleware that hide the complexity of application developments and provide the abstraction of functions to upper application layer. Although there we several factors to design sensor middleware, the attribute-based naming is considered to be an essential factor among them. However, most existing researches were not designed to reflect the characteristics of sensor networks and have the limitation of attribute-based query extension. This study adopts the concept of Virtual Counterpart to suggest the structure there attribute-based naming is supported by virtual sensor nodes of the middleware on the sink node. Unlike traditional data-centric middleware in which individual sensor nodes process attribute-based query, virtual sensor nodes mapped to physical sensor nodes are running on the middleware of the sink node and process attribute-based query as a proxy of the physical sensor. This approach enables attribute-based naming independent of physical infrastructure and easy extensibility.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.253-259
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• 2017

Recent development in science and technology has modernized the weapon system of ROKN (Republic Of Korea Navy). Although the cost of purchasing, operating and maintaining the cutting-edge weapon systems has been increased significantly, the national defense expenditure is under a tight budget constraint. In order to maintain the availability of ships with low cost, we need accurate demand forecasts for spare parts. We attempted to find consumption pattern using data mining techniques. First we gathered a large amount of component consumption data through the DELIIS (Defense Logistics Intergrated Information System). Through data collection, we obtained 42 variables such as annual consumption quantity, ASL selection quantity, order-relase ratio. The objective variable is the quantity of spare parts purchased in f-year and MSE (Mean squared error) is used as the predictive power measure. To construct an optimal demand forecasting model, regression tree model, randomforest model, neural network model, and linear regression model were used as data mining techniques. The open software R was used for model construction. The results show that randomforest model is the best value of MSE. The important variables utilized in all models are consumption quantity, ASL selection quantity and order-release rate. The data related to the demand forecast of spare parts in the DELIIS was collected and the demand for the spare parts was estimated by using the data mining technique. Our approach shows improved performance in demand forecasting with higher accuracy then previous work. Also data mining can be used to identify variables that are related to demand forecasting.

• Journal of Information Management
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• v.43 no.2
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• pp.43-66
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• 2012

The purpose of this study is to see the intellectual structure in the field of veterinary sciences in Korea, using author profiling analysis(APA), a bibliometric approach. Three journals are selected on the basis of citation data, exchanging most citations with Korean Journal of Veterinary. And then, 50 authors who published most articles at selected journals during the given period of time were chosen. The analysis of similarity and dissimilarity among authors by comparing co-word appearance patterns from article title, abstracts, and keywords was made. Authors can be grouped 11 minor clusters under 4 major clusters, depending on their interests in the area of veterinary sciences in Korea. The subjects for each cluster at the veterinary sciences are decided by the matching the keyword, representing author's research interest. As a result, it is possible to figure out the current research trends and the researcher network in the field of veterinary sciences.

• Korean Journal of Remote Sensing
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• v.15 no.3
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• pp.277-288
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• 1999

The aim of this review is to provide perspectives on the application of remote sensing techniques for observation of marine environmental changes on various spatio-temporal scales. Currently available remote sensing technologies are reviewed and future direction is suggested. For better utilization of remote sensing, a comprehensive plan should be developed by a demand-side and problem-solving approach. Marine environmental changes should be observed on proper spatio-temporal scales where the processes occur. For appropriate observation and monitoring of various environmental changes in coastal regions, more sensors must be utilized. Platforms other than satellites should also be utilized to expand the spatio-temporal scales of observation. Calibration/validation activities, required for accurate interpretation of remotely sensed data, could utilize buoys and ship-of-opportunity sensors. It is desirable that such systems by developed as a part of an integrated monitoring network.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.3
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• pp.333-340
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• 2019

A combat system performs a given mission enduring various threats. It is important to analyze the reliability of combat systems in order to increase their ability to perform a given mission. Most of studies considered no threat or on threat and didn't analyze all the dependent relationships among the components. In this paper, we analyze the loss probability of the function of the combat system and use it to analyze the reliability. The proposed method is divided into two layers, A lower layer and a upper layer. In lower layer, the failure probability of each components is derived by using FTA to consider various threats. In the upper layer, The loss probability of function is analyzed using the failure probability of the component derived from lower layer and BBN in order to consider the dependent relationships among the components. Using the proposed method, it is possible to analyze considering various threats and the dependency between components.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.1
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• pp.103-111
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• 2009

Recently, cyber attacks against public communications networks are getting more complicated and varied. Moreover, in some cases, one country could make systematic attacks at a national level against another country to steal its confidential information and intellectual property. Therefore, the issue of cyber attacks is now regarded as a new major threat to national security. The conventional way of operating individual information security systems such as IDS and IPS may not be sufficient to cope with those attacks committed by highly-motivated attackers with significant resources. As a result, the monitoring and control of cyber security, which enables attack detection, analysis and response on a real-time basis has become of paramount importance. This paper discusses how to improve efficiency and effectiveness of national cyber security monitoring and control services. It first reviews major threats to the public communications network and how the responses to these threats are made and then it proposes a new approach to improve the national cyber security monitoring and control services.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.6
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• pp.145-152
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• 2009

SCADA(Supervisory Control And Data Acquisition) systems are widely used for control and monitoring of critical infrastructures including electricity, gas and transportation. Any compromise in the security of SCADA systems could result in massive chaos and disaster at a national level if a malicious attacker takes the control of the system. Therefore, sound countermeasures must be provided when the SCADA systems are being developed as well as when they are being operated. Unlike general information processing system, SCADA systems have different service responses, communication protocols and network architectures and therefore a different approach should be applied to each SCADA systems that takes into consideration of each system's security characteristics and architectures. In addition, legal basis should be established to ensure the nationwide management of the systems security. This paper examines the vulnerabilites of SCADA systems and proposes action plans to protect the systems against cyber attacks.

• Journal of agricultural medicine and community health
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• v.46 no.2
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• pp.98-108
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• 2021

Objectives: This study aimed to describe the current public programs for community walking in Korea and to discuss their challenges. Method: We identified the literature related to community walking including five laws, 22 white papers from government departments and 84 program reports from the Seoul Metropolitan Government. Results: Korean law guarantees legal rights and validity to create safe, convenient and equitable environments for community walking. The government department, which has jurisdiction over legislation relating to community walking, has dominated community walking programs, and the role of public health department has been insufficient. Almost all sectors in the department of Seoul Metropolitan Government were involved in community walking programs. However, inter-sectoral cooperation system for community walking was insufficient. Conclusion: It is necessary to revise the condolences of the National Health Promotion Act to establish the role and perspective of public health in community walking promotion. Institutional efforts should be made to expand the network structure between sectors of community walking programs by establishing an organizational, budget, and performance sharing system for inter-sectoral approach.

• Journal of Korean Society for Quality Management
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• v.50 no.4
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• pp.701-716
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• 2022

Purpose: This study aims to predict the dry cargo transportation market economy. The subject of this study is the BDI (Baltic Dry Index) time-series, an index representing the dry cargo transport market. Methods: In order to increase the accuracy of the BDI time-series, we have pre-processed the original time-series via time-series decomposition and data augmentation techniques and have used them for ANN learning. The ANN algorithms used are Multi-Layer Perceptron (MLP), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM) to compare and analyze the case of learning and predicting by applying time-series decomposition and data augmentation techniques. The forecast period aims to make short-term predictions at the time of t+1. The period to be studied is from '22. 01. 07 to '22. 08. 26. Results: Only for the case of the MAPE (Mean Absolute Percentage Error) indicator, all ANN models used in the research has resulted in higher accuracy (1.422% on average) in multivariate prediction. Although it is not a remarkable improvement in prediction accuracy compared to uni-variate prediction results, it can be said that the improvement in ANN prediction performance has been achieved by utilizing time-series decomposition and data augmentation techniques that were significant and targeted throughout this study. Conclusion: Nevertheless, due to the nature of ANN, additional performance improvements can be expected according to the adjustment of the hyper-parameter. Therefore, it is necessary to try various applications of multiple learning algorithms and ANN optimization techniques. Such an approach would help solve problems with a small number of available data, such as the rapidly changing business environment or the current shipping market.