• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1B
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• pp.41-53
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• 2008

Unprecedented weather phenomena are occurring because of climate change: extreme heavy rains, heat waves, and severe rain storms after the rainy season. Recently, the frequency of these abnormal phenomena has increased. However, regular pattern or cycles cannot be found. Analysis of annual data or annual average data, which has been established a research method of climate change, should be applied to find frequency and tendencies of extreme climate events. In this paper, extreme indicators of precipitation and temperature marked by objectivity and consistency were established to analyze data collected by 66 observatories throughout Korea operated by the Meteorological Administration. To assess the statistical significance of the data, linear regression and Kendall-Tau method were applied for statistical diagnosis. The indicators were analyzed to find tendencies. The analysis revealed that an increase of precipitation along with a decrease of the number of rainy days. A seasonal trend was also found: precipitation rate and the heavy rainfall threshold increased to a greater extent in the summer(June-August) than in the winter (September-November). In the meanwhile, a tendency of temperature increase was more prominent in the winter (December-February) than in the summer (June-August). In general, this phenomenon was more widespread in inland areas than in coastal areas. Furthermore, the number of winter frost days diminished throughout Korea. As was mentioned in the literature, the progression of climate change has influenced the increase of temperature in the winter.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1B
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• pp.23-33
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• 2009

Climate change, abnormal weather, and unprecedented extreme weather events have appeared globally. Interest in their size, frequency, and changes in spatial distribution has been heightened. However, the events do not display regional or regular patterns or cycles. Therefore, it is difficult to carry out quantified evaluation of their frequency and tendency. For more objective evaluation of extreme weather events, this study proposed a rainfall extreme weather index (STARDEX, 2005). To compare the present and future spatio-temporal distribution of extreme weather events, each index was calculated from the past data collected from 66 observation points nationwide operated by Korea Meteorological Administration (KMA). Tendencies up to now have been analyzed. Then, using SRES B2 scenario and 2045s (2031-2050) data from YONU CGCM simulation were used to compute differences among each of future extreme weather event indices and their tendencies were spatially expressed.The results shows increased rainfall tendency in the East-West inland direction during the summer. In autumn, rainfall tendency increased in some parts of Gangwon-do and the south coast. In the meanwhile, the analysis of the duration of prolonged dry period, which can be contrasted with the occurrence of rainfall or its concentration, showed that the dryness tendency was more pronounced in autumn rather than summer. Geographically, the tendency was more remarkable in Jeju-do and areas near coastal areas.

• Korean Journal of Social Welfare Studies
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• v.41 no.3
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• pp.349-378
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• 2010

The Life-Course perspective is a theoretical orientation that views the life-course as the age structure embedded in social institutions and history and understands the life-course of individual and group in the contextual perspective. The life-course perspective studies were developed in Germany and North America. They study social and historical effects and the effect of institutions and the state on the life-course, the pathway of the work career and differences of labour outcomes, and the inequality that is developed in the life-course. In Korea, the life-course perspective studies were tried in various fields and cumulated. However, it didn't established as a theoretical orientation. For applying the life-course perspective to connect the individual life-course with social and historical event, I describe the historical location of individuals born between 1930 and 1979 and analyse the change of their transitions to adulthood exploratorily. On results, the extension of education made the structural change of their life-course, and in young cohort the timing of leaving school, entering workforce, marriage and childbirth was delayed and transitions were made in narrower spread. It means the standardization of the life-course as appears in modern society. The 1970s birth cohort has the differenciated life-course pattern, however I cannot verify that change because of the right censoring.

• Journal of Korea Water Resources Association
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• v.56 no.8
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• pp.471-484
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• 2023

Deep learning models based on generative adversarial neural networks are specialized in generating new information based on learned information. The deep generative models (DGMR) model developed by Google DeepMind is an generative adversarial neural network model that generates predictive radar images by learning complex patterns and relationships in large-scale radar image data. In this study, the DGMR model was trained using radar rainfall observation data from the Ministry of Environment, and rainfall prediction was performed using an generative adversarial neural network for a heavy rainfall case in August 2021, and the accuracy was compared with existing prediction techniques. The DGMR generally resembled the observed rainfall in terms of rainfall distribution in the first 60 minutes, but tended to predict a continuous development of rainfall in cases where strong rainfall occurred over the entire area. Statistical evaluation also showed that the DGMR method is an effective rainfall prediction method compared to other methods, with a critical success index of 0.57 to 0.79 and a mean absolute error of 0.57 to 1.36 mm in 1 hour advance prediction. However, the lack of diversity in the generated results sometimes reduces the prediction accuracy, so it is necessary to improve the diversity and to supplement it with rainfall data predicted by a physics-based numerical forecast model to improve the accuracy of the forecast for more than 2 hours in advance.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.12
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• pp.519-524
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• 2023

In hashing-based image retrieval, the hash code of a manipulated image is different from the original image, making it difficult to search for the same image. This paper proposes and evaluates a self-supervised deephashing model that generates perceptual hash codes from feature information such as texture, shape, and color of images. The comparison models are autoencoder-based variational inference models, but the encoder is designed with a fully connected layer, convolutional neural network, and transformer modules. The proposed model is a variational inference model that includes a SimAM module of extracting geometric patterns and positional relationships within images. The SimAM module can learn latent vectors highlighting objects or local regions through an energy function using the activation values of neurons and surrounding neurons. The proposed method is a representation learning model that can generate low-dimensional latent vectors from high-dimensional input images, and the latent vectors are binarized into distinguishable hash code. From the experimental results on public datasets such as CIFAR-10, ImageNet, and NUS-WIDE, the proposed model is superior to the comparative model and analyzed to have equivalent performance to the supervised learning-based deephashing model. The proposed model can be used in application systems that require low-dimensional representation of images, such as image search or copyright image determination.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.12 no.1
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• pp.24-31
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• 2007

Global fates of polychlorinated biphenyl(PCB) were investigated with a fugacity based multimedia transport and fate model, Globe-POP(persistent organic pollutant). The accumulation of PCB was directly affected by the emission patterns of PCB into the atmosphere and surface areas of environmental compartments. Partition coefficients and reaction rates also influenced on the accumulation patterns of PCB. The emission patterns of PCB in 10 climate zones were consistent for the past 70 years, while the contribution of PCB in high-latitude zones to the globe has increased by cold condensation. Considering the amounts of emission and accumulation of PCB, the North temperature zone is regarded as an important source and sink of PCB. Meanwhile, in spite of no significant sources, POPs accumulate in Antarctic environments mainly due to extremely low temperature. Finally we suggested that a global water balance accounting for snow/ice should be incorporated into multimedia environmental models for high-latitude zones and polar regions with the seasonal snow pack and/or permanent ice caps. The modified model will be useful to evaluate the influence of climate change on the fate of POPs.

• Phonetics and Speech Sciences
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• v.16 no.1
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• pp.33-40
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• 2024

This study investigated acoustic features in spectral moment analysis, comparing accurate articulations with distortions of alveolar fricatives such as dentalization, palatalization, and lateralization. A retrospective analysis was conducted on speech samples from 61 children (mean age: 5.6±1.5 years, 19 females, 42 males) using the Assessment of Phonology & Articulation for Children (APAC) and Urimal-test of Articulation and Phonology I (U-TAP I). Spectral moment analysis was applied to 169 speech samples. The results revealed that the center of gravity of accurate articulations was higher than that of palatalization, while palatalization was lower than dentalization. The variance of dentalization was higher than that of both accurate articulations and palatalization. The skewness of dentalization was higher than that of accurate articulations, and the skewness of palatalization was higher than that of accurate articulations. The kurtosis of palatalization was higher than that of both accurate articulations and dentalization. No significant differences were observed for the position of fricatives (initial, medial) and tense type (plain, tense) across all variables of spectral moment analysis for each distortion type. This study confirmed distinct patterns in center of gravity, variance, skewness, and kurtosis depending on the type of alveolar fricative distortion. The objective values provided in this study will serve as foundational data for diagnosing alveolar fricative distortions in children with speech sound disorders.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.1
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• pp.12-28
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• 2024

This study aims to identify the trend of changes in tourist floating population before and after COVID-19 in major tourist destinations in Jeju Island through spatial analysis. Seongsan-eup and Andeok-myeon in Jeju Island were selected as the research area, and the research period was set at 1 year before and 2 years after the COVID-19 outbreak. For the analysis, mobile floating population data was refined and processed to calculate floating population distribution and floating population increase/decrease data. This was converted into spatial data and an overlay analysis was performed with location data of major tourist attractions. As a result of the analysis, it was confirmed that the floating population of indoor tourist attractions and small facilities decreased immediately after COVID-19, and that in open coastal areas or large facilities, the floating population decreased less or actually increased. In conclusion, in tourism development, it is necessary to identify changes in floating population according to the characteristics of tourist facilities, and it is necessary to develop tourism facilities and strategies that can respond to risk situations such as pandemics when developing tourist destinations.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.4
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• pp.1-11
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• 2024

Bridges crack and become damaged due to age and external factors such as earthquakes, lack of maintenance, and weather conditions. With the number of aging bridge on the rise, lack of maintenance can lead to a decrease in safety, resulting in structural defects and collapse. To prevent these problems and reduce maintenance costs, a system that can monitor the condition of bridge and respond quickly is needed. To this end, existing research has proposed artificial intelligence model that use sensor data to identify the location and extent of cracks. However, existing research does not use data from actual bridge to determine the performance of the model, but rather creates the shape of the bridge through simulation to acquire data and use it for training, which does not reflect the actual bridge environment. In this paper, we propose a bridge safety determination edge AI model that detects bridge abnormalities based on artificial intelligence by utilizing acceleration data from bridge occurring in the field. To this end, we newly defined filtering rules for extracting valid data from acceleration data and constructed a model to apply them. We also evaluated the performance of the proposed bridge safety determination edge AI model based on data collected in the field. The results showed that the F1-Score was up to 0.9565, confirming that it is possible to determine safety using data from real bridge, and that rules that generate similar data patterns to real impact data perform better.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.7
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• pp.784-795
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• 2007

In this thesis, the Multi element antenna with wideband and enhanced gain characteristic is proposed to operate at both frequency range from 824 MHz to 896 11Hz for the CDMA and frequency range from 908.5 MHz to 914 MHz for the RFID band. The proposed antenna has tile size of $35{\times}15{\times}5mm^3$ in order to put it in the A model of S company and each element of the proposed antenna is folded to obtain the minimum size. To obtain the antenna with wideband and high gain characteristic, the radiator of the antenna is divided into 4 elements. As a result, bandwidth of the proposed antenna become broader and lower center frequency is appeared due to increased and lengthened current path. Moreover, the enhanced gain characteristic is verified because divided element structure that induct uniform current distribution can get increased antenna efficiency. To attain more uniform current distribution, modified structure of the feeding point that can deliver currents directly is designed. The antenna that alters the feeding structure has higher gain value. Each element is folded to increase the current paths considering the current directions to attain the miniaturization of the antenna. To measure the handset antenna, the handset case must be considered. Even though antenna is designed for predicted characteristic, the resonance frequency is shifted and antenna gain is deteriorated at predicted frequency while antenna is set in the handset case. 1.08 GHz of the resonant frequency is determined after frequency shift from 150 MHz to 200 MHz is confirmed and the maximum gain is measured as 3.1 dBi while antenna is not set in the handset. In case handset case is considered, the experimental results show that the impedance bandwidth for VSWR<2 is from 0.824 GHz to 0.936 GHz(110 MHz). This result appears that the proposed antenna can cover both CDMA and RFID band at once. The measured gain is from -3.4 dBi to -0.5 dBi and it has omni-directional pattern practically.