• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.5
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• pp.506-513
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• 2020

Due to climate change, there is an increasing risk of complex (hybrid) disasters, comprising rising sea-levels, typhoons, and torrential rains. This study focuses on Marine City, Busan, a new residential city built on a former landfill site in Suyeong Bay, which recently suffered massive flood damage following a combination of typhoons, storm surges, and wave overtopping and run-up. Preparations for similar complex disasters in future will depend on risk impact assessment and prioritization to establish appropriate countermeasures. A framework was first developed for this study, followed by the collection of data on flood prediction and socioeconomic risk factors. Five socioeconomic risk factors were identified: (1) population density, (2) basement accommodation, (3) building density and design, (4) design of sidewalks, and (5) design of roads. For each factor, absolute criteria were determined with which to assess their level of risk, while expert surveys were consulted to weight each factor. The results were classified into four levels and the risk level was calculated according to the sea-level rise predictions for the year 2100 and a 100-year return period for storm surge and rainfall: Attention 43 %, Caution 24 %, Alert 21 %, and Danger 11 %. Finally, each level, indicated by a different color, was depicted on a complex disaster risk map.

• Journal of Korea Multimedia Society
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• v.6 no.3
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• pp.444-454
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• 2003

An analysis of heart movement is to estimate a role which supplies blood in human body. We have constructed a left ventricle myocardium model and mathematically evaluated the motion of myocardium. The myocardial motility was visualized using some parameters about cardiac motion. We applied the myocardium model in the gated myocardium SPECT image that showed a cardiac biochemical reaction, and analyzed a motility between the gated myocardium SPECT image and the myocardium model. The myocardium model was created of the based on three dimensional super-ellipsoidal model that was using the sinusoidal function. To express a similar form and motion of the left ventricle myocardium, we calculated parameter functions that gave the changing of motion and form. The LSF algorithm was applied to the myocardium gated SPECT image data and the myocardium model, and finally created a fitting model. Then we analyzed a regional motility direction and size of the gated myocardium SPECT image that was constructed on a fitting model. Furthermore, we implemented the Bull's Eye map that had evaluated the heart function for presentation of regional motility. Using myocardium's motion the evaluation of cardiac function of SPECT was estimated by a contraction ability, perfusion etc. However, it is not any estimation about motility. So, We analyzed the myocardium SPECT's motility of utilizing the myocardium model. We expect that the proposed algorithm should be a useful guideline in the heart functional estimation.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.8
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• pp.80-88
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• 2007

High adaptability and scalability are two critical issues in implementing a very complex system in a single chip. To obtain high adaptability and scalability, novel system design methodology known as communication-based system design has gained large attention from SoC designers. NoC (Network-on-Chip) is such an on-chip communication-based design approach for the next generation SoC design. To provide high adaptability and scalability, NoCs employ network interfaces and routers as their main communication structures and transmit and receive packetized data over such structures. However, data packetization, and routing overhead in terms of run time and area may cost too much compared with conventional SoC communication structure. Therefore, in this research, we propose a novel methodology which automatically generates a hybrid communication structure. In this work, we map traditional pin-to-pin wiring structure for frequent and timing critical communication, and map flexible and scalable structure for infrequent, or highly variable communication patterns. Even though, we simplify the communication structure significantly through our algorithm the connectivity or the scalability of the communication modules are almost maintained as the original NoC design. Using this method, we could improve the timing performance by 49.19%, and the area taken by the communication structure has been reduced by 24.03%.

• Journal of Forest and Environmental Science
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• v.11 no.1
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• pp.81-101
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• 1995

Random amplified polymorphic DNA (RAPD) technology, a recent approach in molecular genetics, is much usable to select the elite trees and to maximize the genetic gain in forest tree breeding program, providing a clue to determine the genetic marker-trait correlation. This review intorduces research on bark thickness and breeding strategy in Pinus elliottii, Pinus caribaea and their hybrid by Queensland Forest Service and ForBio Research Pty Ltd, University of Queensland, which employ RAPD technology. Genetic linkage map of $F_1$ hybrids includes 186 RAPD markers and 16 linkage groups (1641 cM long in total) and 6 quantitative trait loci are located putatively for bark thickness. Following recent research results and experiences in pine breeding programs, the forseeable stages in the application and development are proposed for marker assisted selectin; stage 1-determination of species specific markers for genes controlling traits of commercial interest, and stage 2-determination of marker-allele association for specific allelic variants within pure species. As pines inherit their megagametophytes from the seed parent and zygotic embryos from both male and female parents, the determination of marker-trait correlation is possible even in embryo stage, eventually making ways for the early selection of elite individuals.

• Korean Journal of Agricultural and Forest Meteorology
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• v.13 no.1
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• pp.35-40
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• 2011

While high-definition precipitation maps with a 270 m spatial resolution are available for South Korea, there is little information on geospatial availability of precipitation water for the famine - plagued North Korea. The restricted data access and sparse observations prohibit application of the widely used PRISM (Parameter-elevation Regressions on Independent Slopes Model) to North Korea for fine-resolution mapping of precipitation. A hybrid method which complements the PRISM grid with a sub-grid scale elevation function is suggested to estimate precipitation for remote areas with little data such as North Korea. The fine scale elevation - precipitation regressions for four sloping aspects were derived from 546 observation points in South Korea. A 'virtual' elevation surface at a 270 m grid spacing was generated by inverse distance weighed averaging of the station elevations of 78 KMA (Korea Meteorological Administration) synoptic stations. A 'real' elevation surface made up from both 78 synoptic and 468 automated weather stations (AWS) was also generated and subtracted from the virtual surface to get elevation difference at each point. The same procedure was done for monthly precipitation to get the precipitation difference at each point. A regression analysis was applied to derive the aspect - specific coefficient of precipitation change with a unit increase in elevation. The elevation difference between 'virtual' and 'real' surface was calculated for each 270m grid points across North Korea and the regression coefficients were applied to obtain the precipitation corrections for the PRISM grid. The correction terms are now added to the PRISM generated low resolution (~2.4 km) precipitation map to produce the 270 m high resolution map compatible with those available for South Korea. According to the final product, the spatial average precipitation for entire territory of North Korea is 1,196 mm for a climatological normal year (1971-2000) with standard deviation of 298 mm.

• Journal of the Korean Geographical Society
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• v.52 no.1
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• pp.123-141
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• 2017

This study predicted urban green spaces for 2020 based on two scenarios keeping or freeing the green-belt in the Daegu metropolitan city using a hybrid Cellular Automata(CA)-Markov model and analyzed the spatial dynamics of urban green spaces between 2009 and 2020 using a land cover change detection technique and spatial metrics. Markov chain analysis was employed to derive the transition probability for projecting land cover change into the future for 2020 based on two land cover maps in 1998 and 2009 provided by the Ministry of Environment. Multi-criteria evaluation(MCE) was adopted to develop seven suitability maps which were empirically derived in relation to the six restriction factors underlying the land cover change between the years 1998 and 2009. A hybrid CA-Markov model was then implemented to predict the land cover change over an 11 year period to 2020 based on two scenarios keeping or freeing the green-belt. The projected land cover for 2009 was cross-validated with the actual land cover in 2009 using Kappa statistics. Results show that urban green spaces will be remarkably fragmented in the suburban areas such as Dalseong-gun, Seongseo, Ansim and Chilgok in the year 2020 if the Daegu metropolitan city keeps its urbanization at current pace and in case of keeping the green-belt. In case of freeing the green-belt, urban green spaces will be fragmented on the fringes of the green-belt. It is thus required to monitor urban green spaces systematically considering the spatial change patterns identified by this study for sustainably managing them in the Daegu metropolitan city in the near future.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.2
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• pp.127-134
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• 2019

With the advancement of IT technology, the amount of data generated has been growing exponentially every year. As an alternative to this, research on distributed systems and in-memory based big data processing schemes has been actively underway. The processing power of traditional big data processing schemes enables big data to be processed as fast as the number of nodes and memory capacity increases. However, the increase in the number of nodes inevitably raises the frequency of failures in a big data infrastructure environment, and infrastructure management points and infrastructure operating costs also increase accordingly. In addition, the increase in memory capacity raises infrastructure costs for a node configuration. Therefore, this paper proposes an in-memory-based hybrid big data processing scheme for improve the big data processing rate. The proposed scheme reduces the number of nodes compared to traditional big data processing schemes based on distributed systems by adding a combiner step to a distributed system processing scheme and applying an in-memory based processing technology at that step. It decreases the big data processing time by approximately 22%. In the future, realistic performance evaluation in a big data infrastructure environment consisting of more nodes will be required for practical verification of the proposed scheme.

• Journal of Cadastre & Land InformatiX
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• v.53 no.1
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• pp.47-63
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• 2023

The Seoul Metropolitan Government is building and operating digital twin-based urban spatial information to solve various problems in the city and provide public services. Two essential factors to ensure the stable utilization of spatial information for the implementation of such a digital twin city are the latest and quality of the data. However, it is time-consuming and costly to maintain continuous updating of high-quality urban spatial information. To overcome this problem, we studied efficient urban spatial information construction technology and the operation, management, and update procedures of construction data. First, we demonstrated and applied automatic 3D building construction technology centered on point clouds using the latest hybrid sensors, confirmed that it is possible to automatically construct high-quality building models using high-density airborne lidar results, and established an efficient data management plan. By applying differentiated production methods by region, supporting detection of urban change areas through Seoul spatial feature identifiers, and producing international standard data by level, we strengthened the utilization of urban spatial information. We believe that this study can serve as a good precedent for local governments and related organizations that are considering activating urban spatial information based on digital twins, and we expect that discussions on the construction and management of spatial information as infrastructure information for city-level digital twin implementation will continue.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.6
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• pp.151-171
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• 2023

For the efficient establishment of a channel strategy for banks, this study aims to propose a channel model by classifying channels into types, and carrying out a correspondence analysis per type. A survey of bankers was conducted to visualize categorical data and create a positioning map. As a result, first, 12 banking channels were classified into 4 types based on business processing subjects and places, which were then, further grouped into the categories of full-banking and self-banking. Second, a correspondence analysis according to the classified types was carried out, and it was found that the branch-type is suitable for product description and customer management, while the banking-type is suitable for efficient business processing without time and space constraints. Furthermore, the analysis also showed that the machine-type and banking-type are inappropriate for customer management, and the mobility-type demonstrates low operational effectiveness due to a lack of awareness. The aforementioned findings suggest the need for a hybrid convergence channel that reflects the characteristics of banking tasks and fills in the gaps between the different channels. Third, a channel model was derived by adding a common area to the 2×2 model consisting of the business processing subjects and places. Therefore, this study is meaningful in that it examines the diversification of channels and factors in the division of roles by channel type based on customers' banking channel selection factors, and presents basic research findings for future channel strategy establishment and efficient channel operation.

• Proceedings of the KOSOMBE Conference
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• v.1991 no.05
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• pp.65-70
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• 1991

A hybrid model which uses a probabilistic model and a MLP(multi layer perceptron) model for pattern recognition of EMG(electromyogram) signals is proposed in this paper. MLP model has problems which do not guarantee global minima of error due to learning method and have different approximation grade to bayesian probabilities due to different amounts and quality of training data, the number of hidden layers and hidden nodes, etc. Especially in the case of new test data which exclude design samples, the latter problem produces quite different results. The error probability of probabilistic model is closely related to the estimation error of the parameters used in the model and fidelity of assumtion. Generally, it is impossible to introduce the bayesian classifier to the probabilistic model of EMG signals because of unknown priori probabilities and is estimated by MLE(maximum likelihood estimate). In this paper we propose the method which get the MAP(maximum a posteriori probability) in the probabilistic model by estimating the priori probability distribution which minimize the error probability using the MLP. This method minimize the error probability of the probabilistic model as long as the realization of the MLP is optimal and approximate the minimum of error probability of each class of both models selectively. Alocating the reference coordinate of EMG signal to the outside of the body make it easy to suit to the applications which it is difficult to define and seperate using internal body coordinate. Simulation results show the benefit of the proposed model compared to use the MLP and the probabilistic model seperately.