• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3946-3965
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• 2018

Network anomaly detection in Software Defined Networking, especially the detection of DDoS attack, has been given great attention in recent years. It is convenient to build the Traffic Matrix from a global view in SDN. However, the monitoring and management of high-volume feature-rich traffic in large networks brings significant challenges. In this paper, we propose a moving window Principal Components Analysis based anomaly detection and mitigation approach to map data onto a low-dimensional subspace and keep monitoring the network state in real-time. Once the anomaly is detected, the controller will install the defense flow table rules onto the corresponding data plane switches to mitigate the attack. Furthermore, we evaluate our approach with experiments. The Receiver Operating Characteristic curves show that our approach performs well in both detection probability and false alarm probability compared with the entropy-based approach. In addition, the mitigation effect is impressive that our approach can prevent most of the attacking traffic. At last, we evaluate the overhead of the system, including the detection delay and utilization of CPU, which is not excessive. Our anomaly detection approach is lightweight and effective.

• Journal of Information Processing Systems
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• v.3 no.1
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• pp.1-7
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• 2007

In mobile ad hoc networks, an application scenario requires mostly collaborative mobility behavior. The key problem of those applications is scalability with regard to the number of multicast members as well as the number of the multicast group. To enhance scalability with group mobility, we have proposed a multicast protocol based on a new framework for hierarchical multicasting that is suitable for the group mobility model in MANET. The key design goal of this protocol is to solve the problem of reflecting the node's mobility in the overlay multicast tree, the efficient data delivery within the sub-group with group mobility support, and the scalability problem for the large multicast group size. The results obtained through simulations show that our approach supports scalability and efficient data transmission utilizing the characteristic of group mobility.

• Journal of the Korea Institute of Military Science and Technology
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• v.7 no.3 s.18
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• pp.11-20
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• 2004

In this paper, the acceptance criteria(Striking Velocities) for the A12519 weldments have been developed. Dynamic impact simulation of A12519 plate was achieved by using LS-DYNA, and predict the projectile velocity and the crack length. Also, Ballistic impact tests of A12519 plate have been performed, and compared with analysis results. Critical velocities of A12519 plate were acquired respectively, and striking velocities of A12519 weldments were calculated. Present work data will be used by basic data in ballistic impact test for A12519 weldments.

• Journal of Applied Reliability
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• v.18 no.2
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• pp.95-103
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• 2018

Purpose: Environment test aim to validate the guarantee of required capability of materiel against various environment conditions which exposed during materiel life-cycle. In this paper, environment test design procedure and tailoring guideline for Korean peninsula and periphery climate are proposed. Methods: To design tailoring guideline, climate data which are regarding Korean peninsula and periphery regions provided from Korea Meteorological Administration (KMA) and National Climatic Data Center (NCDC) are used. Conclusion: For effective environment test, it is important that environment test have to design in considering environment conditions during materiel life-cycle. It is concluded that the high temperature test level can be softer than the test criteria in MIL-HDBK-310, however, the low temperature test level will be expected to be $2{\sim}6^{\circ}C$ harsher than MIL-HDBK-310.

• Spatial Information Research
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• v.22 no.5
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• pp.43-52
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• 2014

Recently, Big Data is a buzzword in the creative economy generation. The organizations related to spatial information society focus on building the spatial big data systems. As spatial big data is a combination of spatial information and big data, the data visualization is essential in order to utilize them efficiently. One of the great methodologies for data visualization is infographics. Nationally, Chousn.com initiated the infographics news in 2010. Korean Administration Branches also recognized the importance of infographic and they adopted infographics for their briefings from 2013. Internationally, Visual.ly is leading company in the infographics market and they produced noticeable interactive infographics for Egypt Parliamentary Elections results. In the defense part, Guardian's datajournalism of Afghanistan war log was a good example of utilizing infographics. Throughout the research, five requirements are extracted. First source data should have precision and accuracy in terms of time and space manner. Second, infographics images have a compressibility. Third, the infographics is properly processed for military commanders. Fourth, sharing, openness and communication are essential for high quality infographic. Lastly, infographics should be an analytic tool for predicting future event based on the past data. Infographics is not a direct representation of data but an analytic tool for helping user's choice and decision in critical moments.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1749-1760
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• 2022

In modern society, human and social damages caused by natural disasters and frequent disaster accidents have been increased year by year. Prompt access to dangerous disaster sites that are inaccessible or inaccessible using state-of-the-art Earth observation equipment such as satellites, drones, and survey robots, and timely collection and analysis of meaningful disaster information. It can play an important role in protecting people's property and life throughout the entire disaster management cycle, such as responding to disaster sites and establishing mid-to long-term recovery plans. This special issue introduces the National Disaster Management Research Institute (NDMI)'s disaster management technology that utilizes various Earth observation platforms, such as mobile survey vehicles equipped with close-range disaster site survey sensors, drones, and survey robots, as well as satellite technology, which is a tool of remote earth observation. Major research achievements include detection of damage from water disasters using Google Earth Engine, mid- and long-term time series observation, detection of reservoir water bodies using Sentinel-1 Synthetic Aperture Radar (SAR) images and artificial intelligence, analysis of resident movement patterns in case of forest fire disasters, and data analysis of disaster safety research. Efficient integrated management and utilization plan research results are summarized. In addition, research results on scientific investigation activities on the causes of disasters using drones and survey robots during the investigation of inaccessible and dangerous disaster sites were described.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.2
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• pp.200-206
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• 2008

To implement a mobile radio system, wave-propagation models are necessary to determine propagation characteristics accurately, Currently, the empirical/theoretical prediction models for urban environments are fairly well-developed. But there is a lack of a suitable prediction model for mountain region. So in this paper, to develop the prediction model for mountain region, propagation environments are classified based on three basic mechanisms: reflection, diffraction, penetration(absorbtion and scattering), and measurements have been performed for the classified mountain regions including open area, forest and ridge. Using the measurement data, empirical modeling of propagation characteristics are performed, and then a prediction model for mountain region is proposed.

• Journal of the Korean Society of Clothing and Textiles
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• v.46 no.5
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• pp.836-847
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• 2022

This study establishes basic data for the development of a new Chemical, Biological, and Radioactive (CBR) protective clothing by selecting the ventilation position to optimize thermal comfort on the basis of the opening and closing of each part. Participants were eight men in their 20s who had previously worn CBR protective clothing. After vigorous exercise and perspiration, the microclimate of the clothing and skin temperature was measured. Results revealed that when the ventilation zipper was opened after exercising, the skin and clothing microclimate temperatures, which had increased during the exercise, decreased in the chest and shoulder blade regions. The clothing microclimate humidity decreased in the chest area. The change was greatest in the chest region; the skin temperature decreased by 0.2℃, the clothing microclimate temperature by 2.7℃, and the clothing microclimate humidity by 3.2%RH through ventilation. Thus, the opening that allows the exchange of accumulated heat and moisture while wearing the CBR protective clothing is efficient.

• Korean Journal of Agricultural Science
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• v.47 no.3
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• pp.471-483
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• 2020

Flood prediction is an important issue to prevent damages by flood inundation caused by increasing high-intensity rainfall with climate change. In recent years, machine learning algorithms have been receiving attention in many scientific fields including hydrology, water resources, natural hazards, etc. The performance of a machine learning algorithm was investigated to predict the water elevation of a river in this study. The aim of this study was to develop a new method for securing a large enough lead time for flood defenses by predicting river water elevation using the a long- short-term memory (LSTM) technique. The water elevation data at the Oisong gauging station were selected to evaluate its applicability. The test data were the water elevation data measured by K-water from 15 February 2013 to 26 August 2018, approximately 5 years 6 months, at 1 hour intervals. To investigate the predictability of the data in terms of the data characteristics and the lead time of the prediction data, the data were divided into the same interval data (group-A) and time average data (group-B) set. Next, the predictability was evaluated by constructing a total of 36 cases. Based on the results, group-A had a more stable water elevation prediction skill compared to group-B with a lead time from 1 to 6 h. Thus, the LSTM technique using only measured water elevation data can be used for securing the appropriate lead time for flood defense in a river.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.18 no.2
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• pp.89-103
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• 2013

National demands for the ocean forecasting system have been increased to support economic activity and national safety including search and rescue, maritime defense, fisheries, port management, leisure activities and marine transportation. Further, the ocean forecasting has been regarded as one of the key components to improve the weather and climate forecasting. Due to the national demands as well as improvement of the technology, the ocean forecasting systems have been established among advanced countries since late 1990. Global Ocean Data Assimilation Experiment (GODAE) significantly contributed to the achievement and world-wide spreading of ocean forecasting systems. Four stages of GODAE were summarized. Goal, vision, development history and research on ocean forecasting system of the advanced countries such as USA, France, UK, Italy, Norway, Australia, Japan, China, who operationally use the systems, were examined and compared. Strategies of the successfully established ocean forecasting systems can be summarized as follows: First, concentration of the national ability is required to establish successful operational ocean forecasting system. Second, newly developed technologies were shared with other countries and they achieved mutual and cooperative development through the international program. Third, each participating organization has devoted to its own task according to its role. In Korean society, demands on the ocean forecasting system have been also extended. Present status on development of the ocean forecasting system and long-term plan of KMA (Korea Meteorological Administration), KHOA (Korea Hydrographic and Oceanographic Administration), NFRDI (National Fisheries Research & Development Institute), ADD (Agency for Defense Development) were surveyed. From the history of the pre-established systems in other countries, the cooperation among the relevant Korean organizations is essential to establish the accurate and successful ocean forecasting system, and they can form a consortium. Through the cooperation, we can (1) set up high-quality ocean forecasting models and systems, (2) efficiently invest and distribute financial resources without duplicate investment, (3) overcome lack of manpower for the development. At present stage, it is strongly requested to concentrate national resources on developing a large-scale operational Korea Ocean Forecasting System which can produce open boundary and initial conditions for local ocean and climate forecasting models. Once the system is established, each organization can modify the system for its own specialized purpose. In addition, we can contribute to the international ocean prediction community.