• Journal of the HCI Society of Korea
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• v.9 no.2
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• pp.23-31
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• 2014

A variety of writing support systems focus on the information management or the feature analysis of the commercially successful narrative texts. In these approaches, the reader's role in the narrative creating process is overlooked. During a writing work, an author anticipates the reader's response or expectation to the narrative and he/she organizes the narrative either along or against the prediction about readers. Assessing and controlling the reader's comprehension in the development of events influences the aesthetic quality of the narrative. In this paper, we suggest a writing support system to visualize and adjust the characteristics of a narrative text related to the reader's comprehension, which is theoretically based on the narrative structure model and the event-indexing situation model. Under the development of the support system, we designed an interactive framework to create events as the basic units of story and arrange them onto both story- and discourse-time axes. Using this framework, we analyzed the organization of events about an actual film narrative. We also proposed both the continuity of the situational dimensions and the cognitive complexity as the characteristics to affect the reader's comprehension, hence we devised a method to visualize and evaluate them. This method was applied to the actual film narrative and the result was discussed in the aspect of the features of the narrative and wiring support strategies.

• Journal of the Earthquake Engineering Society of Korea
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• v.1 no.2
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• pp.1-15
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• 1997

This paper presents substructural identification methods for the assessment of local damages in complex and large structural systems. For this purpose, an auto-regressive and moving average with stochastic input (ARMAX) model is derived for a substructure to process the measurement data impaired by noises. Using the substructural methods, the number of unknown parameters for each identification can be significantly reduced, hence the convergence and accuracy of estimation can be improved. Secondly, the damage index is defined as the ratio of the current stiffness to the baseline value at each element for the damage assessment. The indirect estimation method was performed using the estimated results from the identification of the system matrices from the substructural identification. To demonstrate the proposed techniques, several simulation and experimental example analyses are carried out for structural models of a 2-span truss structure, a 3-span continuous beam model and 3-story building model. The results indicate that the present substructural identification method and damage estimation methods are effective and efficient for local damage estimation of complex structures.

• The Transactions of the Korea Information Processing Society
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• v.1 no.2
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• pp.225-236
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• 1994

Many research result conducted by neural network researchers claimed that the degree of generalization of the neural network system is higher or at least equal to that of statistical methods. However, those successful results could be brought only if the neural network was trained by appropriately sound data, having a little of noisy data and being large enough to control noisy data. Real data used in a lot of fields, especially business fields, were not so sound that the network have frequently failed to obtain satisfactory prediction accuracy, the degree of generalization. Enhancing the degree of generalization with noisy data is discussed in this study. The suggestion, which was obtained through a series of experiments, to enhance the degree of generalization is to remove inconsistent data by checking overlapping and inconsistencies. Furthermore, the previous conclusion by other reports is also confirmed that the learning mechanism of neural network takes average value of two inconsistent data included in training set［2］. The interim results of on-going research project are reported in this paper These are ann architecture of the neural network adopted in this project and the whole idea of developing on-line credit evaluation system,being intergration of the expert(resoning)system and the neural network(learning system.Another definite result is corroborated through this study that quickprop,being agopted as a learing algorithm, also has more speedy learning process than does back propagation even in very noisy environment.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.3
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• pp.360-369
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• 2012

Parent material, climate, topography, biological factors, and time are considered five soil forming factors. This study was conducted to elucidate the effects of several environment factors on soil distribution using quantitative analysis method, called soil series estimation algorithm in the soils of Jeju Island. We selected environment factors including mean temperature, annual precipitation, surface geology, altitude, slope, aspect, altitude difference within 1 $km^2$ area, topographic wetness index, distance from the shore, distance from the mountain peak, and landuse for a quantitative analysis. We analyzed the ranges of environment factors for each soil series and calculated probabilities of possible-soil series for certain locations using estimation algorithm. The algorithm can predicted exact soil series on the soil map with correctness of 33% on $1^{st}$ ranking, 62% within $2^{nd}$ ranking, 74% within $5^{th}$ ranking after estimating using randomly extracted environment factors. In predicted soil map, soil sequences of Entisols-Alfisols-Andisols on northern area and Alfisols-Ultisols-Andisols on western area can be suggested along increasing altitude. More modeling studies will be needed for the genesis process of soils in Jeju Island.

• Atmosphere
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• v.23 no.2
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• pp.171-186
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• 2013

Recently, the number of observations used in a data assimilation system is increasing due to the enormous amount of observations, including satellite data. However, it is not clear that all of these observations are always beneficial to the performance of the numerical weather prediction (NWP). Therefore, it is important to evaluate the effect of observations on these forecasts so that the observations can be used more usefully in NWP process. In this study, the adjoint-based Forecast Sensitivity to Observation (FSO) method with the KMA Unified Model (UM) is applied to two high-impact weather events which occurred in summer and winter in Korea in an effort to investigate the effects of observations on the forecasts of these events. The total dry energy norm is used as a response function to calculate the adjoint sensitivity. For the summer case, TEMP observations have the greatest total impact while BOGUS shows the greatest impact per observation for all of the 24-, 36-, and 48-hour forecasts. For the winter case, aircraft, ATOVS, and ESA have the greatest total impact for the 24-, 36-, and 48-hour forecasts respectively, while ESA has the greatest impact per observation. Most of the observation effects are horizontally located upwind or in the vicinity of the Korean peninsula. The fraction of beneficial observations is less than 50%, which is less than the results in previous studies. As an additional experiment, the total moist energy norm is used as a response function to measure the sensitivity of 24-hour forecast error to observations. The characteristics of the observation impact with the moist energy response function are generally similar to those with the dry energy response function. However, the ATOVS observations were found to be sensitive to the response function, showing a positive (a negative) effect on the forecast when using the dry (moist) norm for the summer case. For the winter case, the dry and moist energy norm experiments show very similar results because the adjoint of KMA UM does not calculate the specific humidity of ice properly such that the dry and moist energy norms are very similar except for the humidity in air that is very low in winter.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.1
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• pp.593-601
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• 2014

In this study, we investigated the methods of improving the capturing ability of acid fume by assessing the performance of slot-type external hood installed on both sides of an open surface tank for acid washing process. A field survey and the results of computational fluid dynamics revealed that capturing performance of existing hoods is very poor. To solve such problem, 'push-pull hood' that pushes from one side of an open surface tank and pulls on the other side was suggested. The initial prediction was that if a push-pull hood is used, the acid fume of an acid-washing tank surface could be moved towards the hood through the push flow. However, this study has confirmed that if the push flow velocity becomes too high, it could spread to other areas due to flooding from the hood. Therefore, if the push air supply is maintained at around 25 $m^3/min$(push 10 m/s), proper control flow is formed on the surface of a tank and acid fume that stayed at the upper part of the tank is smoothly captured toward the hood, significantly enhancing the capturing performance.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.11
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• pp.256-264
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• 2020

Industrial Wireless Sensor Networks (IWSNs) is exploited to achieve various objectives such as improving productivity and reducing cost in the diversity of industrial application, and it has requirements such as low-delay and high reliability packet transmission. To accomplish the requirement, the network manager performs graph construction and resource allocation about network topology, and determines the transmission cycle and path of each node in advance. However, this network management scheme cannot treat mobile devices that cause continuous topology changes because graph reconstruction and resource reallocation should be performed as network topology changes. That is, despite the growing need of mobile devices in many industries, existing scheme cannot adequately respond to path failure caused by movement of mobile device and packet loss in the process of path recovery. To solve this problem, a network management scheme is required to prevent packet loss caused by mobile devices. Thus, we analyse the location and movement cycle of mobile devices over time using machine learning for predicting the mobility pattern. In the proposed scheme, the network manager could prevent the problems caused by mobile devices through performing graph construction and resource allocation for the predicted network topology based on the movement pattern. Performance evaluation results show a prediction rate of about 86% compared with actual movement pattern, and a higher packet delivery ratio and a lower resource share compared to existing scheme.

• Journal of the Korean Society for Nondestructive Testing
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• v.17 no.2
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• pp.89-99
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• 1997

Although discontinuously reinforced metal matrix composite(MMC) is one of the most promising materials for applications of aerospace, automotive industries, the thermal residual stresses developed in the MMC due to the mismatch in coefficients of thermal expansion between the matrix and the fiber under a temperature change has been pointed out as one of the serious problem in practical applications. There are very limited nondestructive techniques to measure the residual stress of composite materials. However, many difficulties have been reported in their applications. Therefore it is important to establish analytical model to evaluate the thermal residual stress of MMC for practical engineering application. In this study, an elastic model is developed to predict the average thermal residual stresses in the matrix and fiber of a misoriented short fiber composite. The thermal residual stresses are induced by the mismatch in the coefficient of the thermal expansion of the matrix and fiber when the composite is subjected to a uniform temperature change. The model considers two-dimensional in-plane fiber misorientation. The analytical formulation of the model is based on Eshelby's equivalent inclusion method and is unique in that it is able to account for interactions among fibers. This model is more general than past models to investigate the effect of parameters which might influence thermal residual stress in composites. The present model is to investigate the effects of fiber volume fraction, distribution type, distribution cut-off angle, and aspect ratio on thermal residual stress for in-plane fiber misorientation. Fiber volume fraction, aspect ratio, and distribution cut-off angle are shown to have more significant effects on the magnitude of the thermal residual stresses than fiber distribution type for in-plane misorientation.

• Magazine of the Korea Concrete Institute
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• v.7 no.3
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• pp.187-198
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• 1995

This paper develops practical and reallstic reliabllity models and methods for the evaluation of system rehability and system rellabllity based ratlng of R.C box glrder bridge superstructures. The precise prediction of reberved carrying capacity of bridge as d system is extremely difficult especially when the brldges are highly redundant and slgnlficantly deter 1or;itcd or dainagetl. Thls papel proposes a nt2w approach for the evaluation of reseived system c,drrying capaaty of br~dges in terms ot equ~vdleiit system strength, which may b~ ddcflned as a brtdge system strength correipcmdlng tu the system rehability of the bridge. This cm be ticrAvcd from an Inverse process bami or1 the con~ept of FOSM(F1rst Order Second Moment) form of system reliabihty index. The sf rength llmt state models for K C box girder br~dges suggested In the paper dre based on the basi~ bending and shear strength And thc system reliatxllty pro,~lerri of box gritier super structure 1s formuldted as parallel serles models obtalncd f ~ o m thc FMA(Fdilure blode Rp proath) based on major failure mc>clmusrns or c~itlcal fdure ,>tatcs of each nuder .WOSM(Ad-vanced First Order Second Moment) and IST(1mportance Sampling Technique) simulation algorithm are used for the reliability analysis of the proposed models.

• Genomics & Informatics
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• v.16 no.1
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• pp.10-13
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• 2018

Until now microsatellite (MS) have been a popular choice of markers for parentage verification. Recently many countries have moved or are in process of moving from MS markers to single nucleotide polymorphism (SNP) markers for parentage testing. FAO-ISAG has also come up with a panel of 200 SNPs to replace the use of MS markers in parentage verification. However, in many countries most of the animals were genotyped by MS markers till now and the sudden shift to SNP markers will render the data of those animals useless. As National Institute of Animal Science in South Korea plans to move from standard ISAG recommended MS markers to SNPs, it faces the dilemma of exclusion of old animals that were genotyped by MS markers. Thus to facilitate this shift from MS to SNPs, such that the existing animals with MS data could still be used for parentage verification, this study was performed. In the current study we performed imputation of MS markers from the SNPs in the 500-kb region of the MS marker on either side. This method will provide an easy option for the labs to combine the data from the old and the current set of animals. It will be a cost efficient replacement of genotyping with the additional markers. We used 1,480 Hanwoo animals with both the MS data and SNP data to impute in the validation animals. We also compared the imputation accuracy between BovineSNP50 and BovineHD BeadChip. In our study the genotype concordance of 40% and 43% was observed in the BovineSNP50 and BovineHD BeadChip respectively.