• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.5
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• pp.1039-1055
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• 2012

It is required for us to enhance the national cyber capability as the worldwide countries have been doing effort to strengthen their cyber capabilities. However, we are encountering the difficulty in estimating national cyber capability due to the absence of any cyber capability assessment methodology. This paper presents the national cyber capability assessment methodology which is used for settle up national cyber policy. We also introduce the result of five major nations(US, China, Japan, Russia, Korea)' cyber capability assessment using the proposed methodology. The methodology is developed using open data and includes three areas; base capability, attack capability and defense capability. The assessment result shows the in the order of US, China, Korea, Russia, Japan. As the analysis of that result, in order to enhance the our cyber capability, we recommend that first, cyber budget and human resources for the base capability should be more invested, second, the strategy for attack capability enhancement is strongly required and lastly, the patch ratio and security monitoring level should be upgraded.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.552-560
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• 2021

Currently, the domestic aquaculture industry is pursuing smartization, but it is still proceeding with human subjective judgment in many processes in the aquaculture stage. The prerequisite for the smart aquaculture industry is to effectively grasp the condition of fish in the farm. If real-time monitoring is possible by identifying the number of fish populations, size, pathways, and speed of movement, various forms of automation such as automatic feed supply and disease determination can be carried out. In this study, we proposed an algorithm to identify the state of fish in real time using underwater video data. The fish detection performance was compared and evaluated by applying the latest deep learning-based object detection models, and an algorithm was proposed to measure fish object identification, path tracking, and moving speed in continuous image frames in the video using the fish detection results. The proposed algorithm showed 92% object detection performance (based on F1-score), and it was confirmed that it effectively tracks a large number of fish objects in real time on the actual test video. It is expected that the algorithm proposed in this paper can be effectively used in various smart farming technologies such as automatic feed feeding and fish disease prediction in the future.

• Journal of Advanced Navigation Technology
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• v.25 no.3
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• pp.248-255
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• 2021

The main causes of the July 2013 OZ 214 accident were poorly performed approach and the failure to recognize the autothrottle in the HOLD position which the automated speed control was not provided. The pilots late decision for go-around was also a critical factor leading to the accident. The B777 POM restricts the use of FLCH mode beyond the FAF. This research utilized the QAR data of an airline's B777 fleet in the period of two years where 44 cases were found. In many cases, the FLCH mode was used for rapid descent from an higher than normal situation. In addition, in the base turn, continuous use of FLCH mode even when the path was below the glide path were observed. Airports with elevation above 500 ft MSL had a higher rate of occurrence. In this research, the proper descent planning and vertical path monitoring, and the adherence to the limitation set in the manuals and the stabilized approach criteria were re-emphasized as mitigation to reduce event occurences.

• Journal of agriculture & life science
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• v.53 no.6
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• pp.45-53
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• 2019

The purpose of this study is to analyze the status of the joint forest project, which is one of the national forest management system, by using stakeholder participation, transparency of decision making, accountability of actors and stakeholders, The questionnaire survey was conducted using the 5 - point scale and the written form. As a result of the questionnaire survey, various stakeholder participation items had the highest opportunity to participate with an average of 3.3 and the lowest score with 2.3 points for establishing conflict and conflict resolution structures. Transparency was analyzed to be 3.4 points for the project disclosure, 2.7 points for information sharing and education promotion activities for local residents, 3.3 points for the detailed role of the project implementer, and 2.7 points for internal and external monitoring and evaluation of the project with various stakeholders. The results of this research, analyzed through the participatory forest management index, are deemed to be used as basic data for the establishment of a plan for the revitalization of national forest participation management.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.807-818
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• 2020

In this study, hydrophones using acoustic sensors were used to estimate the amount of bedload discharge in a forested watershed. The reaction characteristics were analyzed through hydrophone flume tests and field tests, and the quantitative bedload discharge was calculated and compared with that measured by a pit sampler. The hydrophone reaction changed the pulse according to the flow rate change, but did not react to standard sand. The pulse was different depending on the particle size and weight, and accordingly, there was a specific channel showing a suitable response. For a hydrophone installed in the field, by using an automatic impact device, the reaction characteristics of each channel were analyzed to confirm normal operation of the sensor and the suitability of the output value of each channel. In addition, a suitable channel was selected for the estimation of bedload discharge. The bedload discharge formula was developed using a hydrophone pulse and the average flow rate, and was compared with the measured data in the pit sampler in the study site. As a result of the study, if a hydrophone is used for monitoring the bedload in forested watersheds, it is considered effective in quantitatively estimating the weight of bedload discharge.

• Journal of Wetlands Research
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• v.23 no.1
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• pp.27-34
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• 2021

In this study, the main influencing factors of the occurrence of cyanobacteria at each of the eight Multifunctional weirs were derived using a random forest, and a categorical prediction model based on a Algal bloom warning system was developed. As a result of examining the importance of variables in the random forest, it was found that the upstream points were directly affected by weir operation during the occurrence of cyanobacteria. This means that cyanobacteria can be managed through efficient security management. DO and E.C were indicated as major influencers in midstream. The midstream section is a section where large-scale industrial complexes such as Gumi and Gimcheon are concentrated as well as the emissions of basic environmental facilities have a great influence. During the period of heatwave and drought, E.C increases along with the discharge of environmental facilities discharged from the basin, which promotes the outbreak of cyanobacteria. Those monitoring sites located in the middle and lower streams are areas that are most affected by heat waves and droughts, and therefore require preemptive management in preparation for the outbreak of cyanobacteria caused by drought in summer. Through this study, the characteristics of cyanobacteria at each point were analyzed. It can provide basic data for policy decision-making for customized cyanobacteria management.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.7
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• pp.931-941
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• 2020

There is a growing interest this paper for ocean sensing where autonomous vehicles can play an essential role in assisting engineers, researchers, and scientists with environmental monitoring and collecting oceanographic data. This study was conducted to develop a rigid sail for the autonomous sailing drone. Our study aims to numerically analyze the aerodynamic characteristics of curvy twin sail and compare it with wing sail. Because racing regulations limit the sail shape, only the two-dimensional geometry (2D) was open for an optimization. Therefore, the first objective was to identify the aerodynamic performance of such curvy twin sails. The secondary objective was to estimate the effect of the sail's spacing and shapes. A viscous Navier-Stokes flow solver was used for the numerical aerodynamic analysis. The 2D aerodynamic investigation is a preliminary evaluation. The results indicated that the curvy twin sail designs have improved lift, drag, and driving force coefficient compared to the wing sails. The spacing between the port and starboard sails of curvy twin sail was an important parameter. The spacing is 0.035 L, 0.07 L, and 0.14 L shows the lift coefficient reduction because of dramatically stall effect, while flow separation is improved with spacing is 0.21 L, 0.28 L, and 0.35 L. Significantly, the spacing 0.28 L shows the maximum high pressure at the lower area and the small low pressure area at leading edges. Therefore, the highest lift was generated.

• Journal of the Korea Convergence Society
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• v.12 no.8
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• pp.31-37
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• 2021

As the size of buildings increases due to urbanization due to the development of industry, the need to purify the air and maintain a comfortable indoor environment is also increasing. With the development of monitoring technology for refrigeration systems, it has become possible to manage the amount of electricity consumed in buildings. In particular, refrigeration systems account for about 40% of power consumption in commercial buildings. Therefore, in order to develop the refrigeration system failure diagnosis algorithm in this study, the purpose of this study was to understand the structure of the refrigeration system, collect and analyze data generated during the operation of the refrigeration system, and quickly detect and classify failure situations with various types and severity . In particular, in order to improve the classification accuracy of failure types that are difficult to classify, a three-step diagnosis and classification algorithm was developed and proposed. A model based on SVM and LGBM was presented as a classification model suitable for each stage after a number of experiments and hyper-parameter optimization process. In this study, the characteristics affecting failure were preserved as much as possible, and all failure types, including refrigerant-related failures, which had been difficult in previous studies, were derived with excellent results.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.123-134
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• 2021

This study was conducted for the purpose of convergence exploration of evidence-based practices for the advancement of performance analysis of the extracurricular activities at Duksung Women's University. The research method consisted of an expert meeting procedure along with a procedure for analyzing previous studies dealing with the performance analysis of the university's extracurricular activities in the field of pedagogy. The contents of this study consisted of presenting some facts that should be based on evidence for the advancement of performance analysis of the extracurricular activities after the establishment of the center for extracurricular activities in Duksung Women's University. And in practices, the development and diagnostic analysis of tools for diagnosing extracurricular customized learning capabilities, data-based multidimensional analysis (IR system), continuous monitoring analysis through extracurricular certification, and analysis based on feedback tools were presented in a convergence perspective and context. As a result of the study, the evidence-based practices for the advancement of the performance analysis of the extracurricular activities at Duksung Women's University guarantees the validity and stability of the performance evaluation and feedback system of the extracurricular activities at Duksung Women's University, and has a close influence on the extracurricular education work of other universities analyzed as possible.

• Journal of Korean Society of Forest Science
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• v.111 no.2
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• pp.302-310
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• 2022

Here we aimed to classify the major coniferous tree species (Pinus densiflora, Pinus koraiensis, and Larix kaempferi) by tree measurement information and machine learning algorithms to establish an efficient forest management plan. We used national forest monitoring information amassed over nine years for the measurement information of trees, and random forest (RF), XGBoost (XGB), and light GBM (LGBM) as machine learning algorithms. We compared and evaluated the accuracy of the algorithm through performance evaluation using the accuracy, precision, recall, and F1 score of the algorithm. The RF algorithm had the highest performance evaluation score for all tree species, and highest scores for Pinus densiflora, with an accuracy of about 65%, a precision of about 72%, a recall of about 60%, and an F1 score of about 66%. The classification accuracy for the dominant trees was higher than about 80% in the crown classes, but that of the co-dominant trees, the intermediate trees, and the overtopper trees was evaluated as low. We consider that the results of this study can be used as reference data for decision-making in the selection of thinning trees for forest management.