• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.6
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• pp.1076-1085
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• 2004

Recently, the demands for real-time service and multimedia data are rapidly increasing. There are significant redundancies between header fields both within the same packet header and in consecutive packets belonging to the same packet stream. And there are many overheads in using the current UDP/IP protocol. Header compression is considered to enhance the transmission efficiency for the payload of small size. By sending the static field information only once initially and by utilizing dependencies and predictability for other fields, the header size can be significantly reduced for most packets. This work describes an implementation for header compression of the headers of IP/UDP protocols to reduce the overhead on Ethernet network. Typical UDP/IP Header packets can be compressed down to 7 bytes and the header compression system is designed and implemented in Linux environment. Using the Header compression system designed between a server and clients provides have the advantage of effective data throughput in network. Since the minimum packet size in Ethernet is 64 bytes, the amount of reduction by header compression in practical chatting environment was 6.6 bytes.

• Korean Journal of Agricultural Science
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• v.47 no.3
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• pp.425-435
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• 2020

Official development assistance (ODA) projects are conducted under the auspices of donor countries and on the principle of time-limited implementation for economic development and welfare improvement in a host country. Exit strategies on how to end official assistance are therefore crucial. Sudden economic recession in a donor country could lead to the suspension of ODA projects, which would affect diplomatic relations and project outcomes. Further, exit strategies can help continue the original project and create links with other ODA projects. This study shows how to employ exit strategies in the Korea-Mongolia Greenbelt Plantation Project and has implications for sustainability of development assistance. Exist strategies were not taken into consideration initially. In the course of implementation and management transfer upon the completion of plantation, various facets were considered later on in developing exit strategies. An ideal exit strategy is to reach the extent to which a host country no longer needs official assistance or has capacity of project implementation on its own. A year-by-year transfer of planted areas can be a phase-over strategy. The Korea Forest Service fulfilled transparent cooperation with Mongolian local governments, established appropriate arrangements with stakeholders, secured institutional and financial foundation for follow-up management by a host country, and realized predictability, responsibility, and sustainability. As a local institution, the plantation technology management center has been established for follow-up activities such as the introduction of agro-forestry. When the Korea Forest Service designed an urban forest project as an exit strategy, sustainability was ensured, which has implications in implementing other ODA projects.

• Nuclear Engineering and Technology
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• v.25 no.1
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• pp.37-50
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• 1993

To evaluate the sequence of event and the Thermohydraulic behavior during total loss of feedwater accident and recovery procedure, a RELAP5/MOD3 calculation is performed and compared with the LOFT L9-l/L3-3 experiment. Also, the predictability of the code for the major Thermohydraulic phenomena following the accident is assessed. As a result, it is found that a pressure control using the spray until the time the water level reaches the top of the pressurizer, an overpressure protection by pressurizer PORV, a recovery of the secondary heat removal capability by refilling steam generator, and an effective cooldown by the continued natural circulation can be performed without core uncovery. It is also found that the plant-specific evaluation is necessary to confirm the effectiveness of the current symptom-oriented emergency operating procedure, especially in an overpressure protection performance and steam generator recovery performance.

• Atmosphere
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• v.29 no.2
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• pp.149-164
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• 2019

The purpose of this study is to introduce the improvement of current operational climate prediction system of KMA and to compare previous and improved that. Whereas the previous system is based on GloSea5GA3, the improved one is built on GloSea5GC2. GloSea5GC2 is a fully coupled global climate model with an atmosphere, ocean, sea-ice and land components through the coupler OASIS. This is comprised of component configurations Global Atmosphere 6.0 (GA6.0), Global Land 6.0 (GL6.0), Global Ocean 5.0 (GO5.0) and Global Sea Ice 6.0 (GSI6.0). The compositions have improved sea-ice parameters over the previous model. The model resolution is N216L85 (~60 km in mid-latitudes) in the atmosphere and ORCA0.25L75 ($0.25^{\circ}$ on a tri-polar grid) in the ocean. In this research, the predictability of each system is evaluated using by RMSE, Correlation and MSSS, and the variables are 500 hPa geopotential height (h500), 850 hPa temperature (t850) and Sea surface temperature (SST). A predictive performance shows that GloSea5GC2 is better than GloSea5GA3. For example, the RMSE of h500 of 1-month forecast is decreased from 23.89 gpm to 22.21 gpm in East Asia. For Nino3.4 area of SST, the improvements to GloSeaGC2 result in a decrease in RMSE, which become apparent over time. It can be concluded that GloSea5GC2 has a great performance for seasonal prediction.

• The Journal of Bigdata
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• v.3 no.2
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• pp.101-112
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• 2018

The purpose of the study is to predict the number of police calls using neural network which is one of the machine learning and negative binomial regression, by using the data of 112 police calls received from Chungnam Provincial Police Agency from June 2016 to May 2017. The variables which may affect the police calls have been selected for developing the prediction model : time, holiday, the day before holiday, season, temperature, precipitation, wind speed, jurisdictional area, population, the number of foreigners, single house rate and other house rate. Some variables show positive correlation, and others negative one. The comparison of the methods can be summarized as follows. Neural network has correlation coefficient of 0.7702 between predicted and actual values with RMSE 2.557. Negative binomial regression on the other hand shows correlation coefficient of 0.7158 with RMSE 2.831. Neural network has low interpretability, but an excellent predictability compared with the negative binomial regression. Based on the prediction model, the police agency can do the optimal manpower allocation for given values in the selected variables.

• The Journal of the Korean dental association
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• v.56 no.11
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• pp.631-640
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• 2018

Nowadays computer-guided "flapless" surgery for implant placement using templates is gaining popularity among clinicians and patients. The advantages of this surgical protocol are its minimally invasive nature, accuracy of implant placement, predictability, less post-surgical discomfort and reduced time required for definitive rehabilitation. Aim of this study is to describe the digital implant protocol, thanks to which is now possible to do a mini-invasive static guided implant surgery. This is possible thanks to a procedure named surface mapping based on the matching between numerous points on the surface of patient's dental casts and the corresponding anatomical surface points in the CBCT data. With some critical points and needing an adequate learning curve, this protocol allows to select the ideal implant position in depth, inclination and mesio-distal distance between natural teeth and or other implants enabling a very safe and predictable rehabilitation compared with conventional surgery. It represents a good tool for the best compromise between anatomy, function and aesthetic, able to guarantee better results in all clinical situations.

• Journal of Periodontal and Implant Science
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• v.51 no.2
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• pp.100-113
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• 2021

Purpose: Previous studies have solely focused on fresh extraction sockets, whereas in clinical settings, alveolar sockets are commonly associated with chronic inflammation. Because the extent of tissue destruction varies depending on the origin and the severity of inflammation, infected alveolar sockets may display various configurations of their remaining soft and hard tissues following tooth extraction. The aim of this study was to classify infected alveolar sockets and to provide the appropriate treatment approaches. Methods: A proposed classification of extraction sockets with chronic inflammation was developed based upon the morphology of the bone defect and soft tissue at the time of tooth extraction. The prevalence of each type of the suggested classification was determined retrospectively in a cohort of patients who underwent, between 2011 and 2015, immediate bone grafting procedures (ridge preservation/augmentation) after tooth extractions at Seoul National University Dental Hospital. Results: The extraction sockets were classified into 5 types: type I, type II, type III, type IV (A & B), and type V. In this system, the severity of bone and soft tissue breakdown increases from type I to type V, while the reconstruction potential and treatment predictability decrease according to the same sequence of socket types. The retrospective screening of the included extraction sites revealed that most of the sockets assigned to ridge preservation displayed features of type IV (86.87%). Conclusions: The present article classified different types of commonly observed infected sockets based on diverse levels of ridge destruction. Type IV sockets, featuring an advanced breakdown of alveolar bone, appear to be more frequent than the other socket types.

• Journal of the Korean earth science society
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• v.42 no.6
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• pp.605-622
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• 2021

Seasonal forecasting has numerous socioeconomic benefits because it can be used for disaster mitigation. Therefore, it is necessary to diagnose and improve the seasonal forecast model. Moreover, the model performance is partly related to the ocean model. This study evaluated the hindcast performance in the upper ocean of the Global Seasonal Forecasting System version 5-Global Couple Configuration 2 (GloSea5-GC2) using a multivariable integrated evaluation method. The normalized potential temperature, salinity, zonal and meridional currents, and sea surface height anomalies were evaluated. Model performance was affected by the target month and was found to be better in the Pacific than in the Atlantic. An increase in lead time led to a decrease in overall model performance, along with decreases in interannual variability, pattern similarity, and root mean square vector deviation. Improving the performance for ocean currents is a more critical than enhancing the performance for other evaluated variables. The tropical Pacific showed the best accuracy in the surface layer, but a spring predictability barrier was present. At the depth of 301 m, the north Pacific and tropical Atlantic exhibited the best and worst accuracies, respectively. These findings provide fundamental evidence for the ocean forecasting performance of GloSea5.

• Journal of Information Science Theory and Practice
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• v.10 no.spc
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• pp.135-142
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• 2022

Recently, with the development of data processing technology and the increase of computational power, methods to solving social problems using Artificial Intelligence (AI) are in the spotlight, and AI technologies are replacing and supplementing existing traditional methods in various fields. Meanwhile in Korea, heavy rain is one of the representative factors of natural disasters that cause enormous economic damage and casualties every year. Accurate prediction of heavy rainfall over the Korean peninsula is very difficult due to its geographical features, located between the Eurasian continent and the Pacific Ocean at mid-latitude, and the influence of the summer monsoon. In order to deal with such problems, the Korea Meteorological Administration operates various state-of-the-art observation equipment and a newly developed global atmospheric model system. Nevertheless, for precipitation nowcasting, the use of a separate system based on the extrapolation method is required due to the intrinsic characteristics associated with the operation of numerical weather prediction models. The predictability of existing precipitation nowcasting is reliable in the early stage of forecasting but decreases sharply as forecast lead time increases. At this point, AI technologies to deal with spatio-temporal features of data are expected to greatly contribute to overcoming the limitations of existing precipitation nowcasting systems. Thus, in this project the dataset required to develop, train, and verify deep learning-based precipitation nowcasting models has been constructed in a regularized form. The dataset not only provides various variables obtained from multiple sources, but also coincides with each other in spatio-temporal specifications.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.39-46
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• 2023

We present an efficient packet transmission strategy for massively multiplayer online first-person shooter (MMOFPS) games using movement-adaptive packet transmission interval. The player motion in FPS games shows a wide spectrum of movement variability both in speed and orientation, where there is room for reducing the number of packets to be transmitted to the server depending on the predictability of the character's movement. In this work, the degree of variability (nonlinearity) of the player movements is measured at every packet transmission to calculate the next transmission time, which implements the adaptive transmission frequency according to the amount of movement change. Server-side prediction with a few auxiliary heuristics is performed in concert with the incoming packets to ensure reliability for synchronizing the connected clients. The comparison of our method with the previous fixed-interval transmission scheme is presented by demonstrating them using a test game environment.