• KIPS Transactions on Computer and Communication Systems
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• v.12 no.8
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• pp.235-242
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• 2023

In recent years, as online counseling for infants and adolescents has increased, CNN-based deep learning models are widely used as assistance tools for emotion recognition. However, since most emotion recognition models are trained on mainly adult data, there are performance restrictions to apply the model to infants and adolescents. In this paper, in order to analyze the performance constraints, the characteristics of facial expressions for emotional recognition of infants and adolescents compared to adults are analyzed through LIME method, one of the XAI techniques. In addition, the experiments are performed on the male and female groups to analyze the characteristics of gender-specific facial expressions. As a result, we describe age-specific and gender-specific experimental results based on the data distribution of the pre-training dataset of CNN models and highlight the importance of balanced learning data.

• The Journal of Fisheries Business Administration
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• v.40 no.2
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• pp.49-70
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• 2009

This study proviedes GARCH model(Bollerslev, 1986) to analyze the structural characteristics of price volatility in domestic aquacultural fish market of Korea. As a case study, flatfish and rock-fish are analyzed as major species with relatively high portion in an aspect of production volume among fish captured in Korea. For analyzing, this study uses daily market data (dating from Jan 1 2000 to June 30, 2008) published by the Noryangjin Fisheries Wholesale Market which is located in Seoul of Korea. This study performs normality test on trading volume and price volatility of flatfish and rock-fish as an advanced empirical approach. The normality test adopted is Jarque-Bera test statistic. As a result, first, a null hypothesis that "an empirical distribution follows normal distribution" was rejected in both fishes. The distribution of daily market data of them were not only biased toward positive(+) direction in terms of kurtosis and skewness, but also characterized by leptokurtic distribution with long right tail. Secondly, serial correlations were found in data on market trading volume and price volatility of two species during very long period. Thirdly, the results of unit root test and ARCH-LM test showed that all data of time series were very stationary and demonstrated effects of ARCH. These statistical characteristics can be explained as a reasonable ground for supporting the fitness of GARCH model in order to estimate conditional variances that reveal price volatility in empirical analysis. From empirical data analysis above, this study drew the following conclusions. First of all, from an empirical analysis on potential effects of seasonality and the day of week on price volatility of aquacultural fish, Monday effects were found in both species and Thursday and Friday effects were also found in flatfish. This indicates that Monday is effective in expanding price volatility of aquacultural fish market and also Monday has higher effects upon the price volatility of fish than other days of week have since it has more new information for weekend. Secondly, the empirical analysis led to a common conclusion that there was very high price volatility of flatfish and rock-fish. This points out that the persistency parameter($\lambda$), an index of possibility for current volatility to sustain similarly in the future, was higher than 0.8-equivalently nearly to 1-in both flatfish and rock-fish, which presents volatility clustering. Also, this study estimated and compared and model that hypothesized normal distributions in order to determine fitness of respective models. As a result, the fitness of GARCH(1, 1)-t model was better than model where the distribution of error term was hypothesized through-distribution due to characteristics of fat-tailed distribution, was also better than model, as described in the results of basic statistic analysis. In conclusion, this study has an important mean in that it was introduced firstly in Korea to investigate in price volatility of Korean aquacultural fishery products, although there was partially a limited of official statistic data. Therefore, it is expected that the results of this study will be useful as a reference material for making and assessing governmental policies. Also, it is looked forward that the results will be helpful to build a fishery business plan as and aspect of producer, and also to take timely measures to potential price fluctuations of fishery products in market. Hence, it is advisable that further studies related to such price volatility in fishery market will extend and evolve into a wider variety of articles and issues in near future.

• Journal of Korea Water Resources Association
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• v.46 no.8
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• pp.833-842
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• 2013

The quantile mapping is utilized to reproduce reliable GCM(Global Climate Model) data by correct systematic biases included in the original data set. This scheme, in general, projects the Cumulative Distribution Function (CDF) of the underlying data set into the target CDF assuming that parameters of target distribution function is stationary. Therefore, the application of stationary quantile mapping for nonstationary long-term time series data of future precipitation scenario computed by GCM can show biased projection. In this research the Nonstationary Quantile Mapping (NSQM) scheme was suggested for bias correction of nonstationary long-term time series data. The proposed scheme uses the statistical parameters with nonstationary long-term trends. The Gamma distribution was assumed for the object and target probability distribution. As the climate change scenario, the 20C3M(baseline scenario) and SRES A2 scenario (projection scenario) of CGCM3.1/T63 model from CCCma (Canadian Centre for Climate modeling and analysis) were utilized. The precipitation data were collected from 10 rain gauge stations in the Han-river basin. In order to consider seasonal characteristics, the study was performed separately for the flood (June~October) and nonflood (November~May) seasons. The periods for baseline and projection scenario were set as 1973~2000 and 2011~2100, respectively. This study evaluated the performance of NSQM by experimenting various ways of setting parameters of target distribution. The projection scenarios were shown for 3 different periods of FF scenario (Foreseeable Future Scenario, 2011~2040 yr), MF scenario (Mid-term Future Scenario, 2041~2070 yr), LF scenario (Long-term Future Scenario, 2071~2100 yr). The trend test for the annual precipitation projection using NSQM shows 330.1 mm (25.2%), 564.5 mm (43.1%), and 634.3 mm (48.5%) increase for FF, MF, and LF scenarios, respectively. The application of stationary scheme shows overestimated projection for FF scenario and underestimated projection for LF scenario. This problem could be improved by applying nonstationary quantile mapping.

• The Korean Journal of Nuclear Medicine
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• v.27 no.2
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• pp.170-174
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• 1993

The quantitative methods for the assessment of the cerebral blood flow using $^{99m}Tc$-HMPAO brain SPECT utilize the measured count distribution in some specific reconstructed tomographic slice or in algebraic summation of a few neighboring slices, rather than the true volumetric distribution, to estimate the relative regional cerebral blood flow, and consequently produce the biased estimates of the true regional cerebral blood flow. This kind of biases are thought to originate mainly from the arbitrarily irregular shape of the cerebral region of interest(ROI) which are analyzed. In this study, a semi-automated method for the direct quantification of the volumetric regional cerebral blood flow estimate is proposed, and the results are compared to those calculated by the previous planar approaches. Bias factors due to the partial volume effect and the uncertainty in ROI determination are not considered presently for the methodological comparison of planar/volumetric assessment protocol.

• Journal of Distribution Science
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• v.17 no.3
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• pp.85-95
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• 2019

Purpose - The existing marketing studies using Social Network Analysis have assumed that network structure variables are time-invariant. However, a node's network position can fluctuate considerably over time and the node's network structure can be changed dynamically. Hence, if such a dynamic structural network characteristics are not specified for virtual goods purchase model, estimated parameters can be biased. In this paper, by comparing a time-invariant network structure specification model(base model) and time-varying network specification model(proposed model), the authors intend to prove whether the proposed model is superior to the base model. In addition, the authors also intend to investigate whether coefficients of network structure variables are random over time. Research design, data, and methodology - The data of this study are obtained from a Korean social network provider. The authors construct a monthly panel data by calculating the raw data. To fit the panel data, the authors derive random effects panel tobit model and multi-level mixed effects model. Results - First, the proposed model is better than that of the base model in terms of performance. Second, except for constraint, multi-level mixed effects models with random coefficient of every network structure variable(in-degree, out-degree, in-closeness centrality, out-closeness centrality, clustering coefficient) perform better than not random coefficient specification model. Conclusion - The size and importance of virtual goods market has been dramatically increasing. Notwithstanding such a strategic importance of virtual goods, there is little research on social influential factors which impact the intention of virtual good purchase. Even studies which investigated social influence factors have assumed that social network structure variables are time-invariant. However, the authors show that network structure variables are time-variant and coefficients of network structure variables are random over time. Thus, virtual goods purchase model with dynamic network structure variables performs better than that with static network structure model. Hence, if marketing practitioners intend to use social influences to sell virtual goods in social media, they had better consider time-varying social influences of network members. In addition, this study can be also differentiated from other related researches using survey data in that this study deals with actual field data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.2
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• pp.139-147
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• 2009

The gravity data collected and reserved in Korea is seriously biased in its distribution. That is, only the west-southern part of the peninsula including Chungcheong and Jeonla area has dense distribution while only a part is covered in Gyoungsang area. Especially, the low density of the gravity data in mountainous area basically limits the accuracy of the gravimetric geoid in Korea. As one of the solution to overcome the problem, an airborne gravity survey were conducted from Dec. 2008 $\sim$ Jan. 2009. In this study, free-air gravity anomaly derived from the airborne gravity data which has consistent quality are presented. The data processing for the airborne gravity is composed of several corrections of errors such as errors from gravity measurement, errors from flight dynamics, errors from GPS, and errors from time synchronization. We presented detailed explanations on the data processing with the final cross-over results. The free-air anomaly from airborne gravity finally shows the cross-over accuracy of 2.21mGal which reflects the precision of each track is 1.56mGal. It is expected that the result from this study will play a role as input data in precision geoid determination with ground and ship-borne gravity data after appropriate fusion process.

• Journal of the Earthquake Engineering Society of Korea
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• v.12 no.1
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• pp.11-20
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• 2008

In probabilistic seismic analysis of nonlinear structural system, dynamic analysis is performed to obtain the distribution of the response estimate using input ground motion time histories which correspond to a given seismic hazard level. This study investigates the differences in the distribution of the responses and the failure probability according to input ground motion models. Two types of input ground motion models are considered: real earthquake records scaled to specified intensity level and artificial input ground motion fitted to design response spectrum. Simulation results fir a nonlinear SDOF system demonstrate that the spectrum matched input ground motion produces larger failure probability than those of scaled input ground motion due to biased responses. Such tendency is more remarkable in the site of soft soil conditions. Analysis results show that such difference of failure probability is due to the conservative estimation of design response spectrum in the range of long period of ground motion.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.233-243
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• 2021

Photovoltaic panels are hazardous electronic waste that has heavy metal as one of the hazardous components. Each year, hazardous electronic waste is increasing worldwide and every heavy rainfall exposes the photovoltaic panel to become the source of heavy metal soil contamination. the development needs a monitoring technology for this hazardous exposure. this research use relationships between SAR temporal baseline and coherence of Sentinel-1 satellite to detected photovoltaic panel. Also, the photovoltaic plant detection tested using the difference between that photovoltaic panel and the other difference surface of coherence. The author tested the photovoltaic panel and its environment to calculate differences in coherence relationships. As a result of the experiment, the coherence of the photovoltaic panel, which is assumed to be a permanent scatterer, shows a bias that is biased toward a median value of 0.53 with a distribution of 0.50 to 0.65. Therefore, further research is needed to improve errors that may occur during processing. Additionally, the author found that the change detection using a temporal baseline is possible as the rate of reduction of coherence of photovoltaic panels differs from those of artificial objects such as buildings. This result could be an efficient way to continuously monitor regardless of weather conditions, which was a limitation of the existing optical satellite image-based photovoltaic panel detection research and to understand the spatial distribution in situations such as photovoltaic panel loss.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2020.12a
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• pp.65-65
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• 2020

Bakanae disease, caused by Gibberella fujikuroi, is one of the most devastating diseases threatening rice production in Korea. In recent years, the incidence of bakanae disease became alarming due to the mechanical transplanting practice where the spread of bakanae can be amplified during accelerating seeds growth, due to the use of seeding boxes. The development of resistant rice cultivars could be the primary and effective method for controlling bakanae disease. However, the effects of individual resistance genes are relatively small. Therefore, pyramiding of bakane R genes in rice breeding is a promising strategy having a high potential to mitigate the advert effects of bakanae disease. This study employed a gene pyramiding approach to develop bakanae disease resistant rice lines carrying qBK1, qFfR1 introduced from rice line MY299BK and cv. Nampyeong, respectively. The MY299BK carries qBK1 introduced from cv. Shingwang, which was found to have a high resistance compare to Nampyeong. In addition, the pyramiding effect of the qBK1 and qFfR1 resistance genes were investigated, and the presence or absence of these genes helped us investigate their interaction through bioassay method and MAS. Furthermore, the distribution of resistance in the population showed a biased distribution toward resistance in the F6:7 populutions. However, we could not confirm the accumulation effect of the resistance gene, but the difference between the two genes by the SN2 marker was confirmed. Therefore, the qBK1 gene harbored by MY299BK appears to be different from the qFfR1 carried by Nampyeong, suspected to possess a different bakanae disease resistant gene different from those found in MY299BK and Nampyeong.

• Journal of the Korean association of regional geographers
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• v.5 no.1
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• pp.101-120
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• 1999

The purpose of this study is to analyze the impact of agricultural polices on the change of regional structure based on the specialization during the productivism period. Analysis are carried on through the comparison of distribution in 1950s and 1997. Since the 1950s, governmental policy has played a leading role in shaping the pattern of farming in Great Britain. The range of British measures have also been employed in an attempt to improve the efficiency of agriculture and raise farm income. Three fairly distinct phase can be identified in the developing relationship between government policies and British agriculture in the postwar period. In the 1st phase, The Agricultural Act of 1947 laid the foundations for agricultural productivism in Great Britain until membership of the EC. This was to be achieved through the system of price support and guaranteed prices and the means of a series of grants and subsidies. Guaranteed prices encouraged farmenrs to intensify production and specialize in either cereal farming or milk-beef enterprise. The former favoured eastern areas, whereas the latter favoured western areas. Various grants and subsidies were made available to farmers during this period, again as a way of increasing efficiency and farm incomes. Many policies, such as Calf Subsidy and the Ploughing Grant, Hill cow and Hill Sheep Schemes and the Hill Farming and Livestock Rearing Grant was provided. Some of these policies favoured western uplands, whilst the others was biased towards the Lake District. Concentration of farms occured especially in near the London Metropolitan Area and south part of Scotland. In the 2nd stage after the membership of EC, very high guaranteed price created a relatively risk-free environment, so farmers intensified production and levels of self-sufficiency for most agriculture risen considerably. As farmers were being paid high prices for as much as they could produce, the policy favoured areas of larger-scale farming in eastern Britain. As a result of increasing regional disparities in agriculture, the CAP became more geographically sensitive in 1975 with the setting up of the Less Favoured Areas(LFAs). But they are biased towards the larger farms, because such farms have more crops and/or livestock, but small farms with low incomes are in most need of support. Specialization of cereals such wheat and barely was occured, but these two cereal crops have experienced rather different trend since 1950s. Under the CAP, farmers have been paid higher guaranteed prices for wheat than for barely because of the relative shortage of wheat in the EC. And more barely were cultivated as feedstuffs for livestock by home-grown cereals. In the 1950s dairying was already declining in what was to become the arable areas of southern and eastern England. By the mid-1980s, the pastral core had maintained its dominance, but the pastoral periphery had easily surpassed arable England as the second most important dairying district. Pig farming had become increasingly concentrated in intensive units in the main cereal areas of eastern England. These results show that the measure of agricultural policy induced the concentration and specialization implicitly. Measures for increasing demand, reducing supply or raising farm incomes are favoured by large scale farming. And price support induced specialization of farming. And technology for specialization are diffused and induced geographical specialization. This is the process of change of regional structure through the specialization.