• Journal of the Korean Geosynthetics Society
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• v.22 no.1
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• pp.67-74
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• 2023

In order to monitor the stability of slopes, research on data-based slope failure prediction and early warning is increasing. However, most papers overlook the quality of data. Poor data quality can cause problems such as false alarms. Therefore, this paper proposes a two-step hybrid approach consisting of rules and machine learning models for quality control of data collected from slopes. The rule-based has the advantage of high accuracy and intuitive interpretation, and the machine learning model has the advantage of being able to derive patterns that cannot be explicitly expressed. The hybrid approach was able to take both of these advantages. Through a case study, the performance of using the two methods alone and the case of using the hybrid approach was compared, and the hybrid method was judged to have high performance. Therefore, it is judged that using a hybrid method is more appropriate than using the two methods alone for data quality control.

• Smart Media Journal
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• v.13 no.4
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• pp.48-56
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• 2024

In the livestock industry, detecting environmental outliers and predicting data are crucial tasks. Outliers in livestock environment data, typically gathered through time-series methods, can signal rapid changes in the environment and potential unexpected epidemics. Prompt detection and response to these outliers are essential to minimize stress in livestock and reduce economic losses for farmers by early detection of epidemic conditions. This study employs two methods to experiment and compare performances in setting thresholds that define outliers in livestock environment data outlier detection. The first method is an outlier detection using Mean Squared Error (MSE), and the second is an outlier detection using a Dynamic Threshold, which analyzes variability against the average value of previous data to identify outliers. The MSE-based method demonstrated a 94.98% accuracy rate, while the Dynamic Threshold method, which uses standard deviation, showed superior performance with 99.66% accuracy.

• Tunnel and Underground Space
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• v.15 no.2 s.55
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• pp.111-118
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• 2005

The area of investigation belongs to Okchon metamorphic zone and the fault fractured zone runs parallel to the tunnel direction. It causes the independent decline of tunnel face and the slackness of the tunnel surrounding base so, after all, the severe displacement has occurred within the tunnel. Accordingly, the TSP(Tunnel Seismic Prediction) survey has been performed to investigate the extent of fault fractured zone and to analize its characteristics. Also, we have analized the behavior causes by performing the tunnel face mapping and drilling investigation, and confirmed the position and scale of geological anomaly area and front fractured zone which influences tunnel excavation and supporting. Collected data analyzed ground layer condition through 3 dimensional modeling. Several variables included in the modeling were analyzed by geostastistics. The analysis of the modeling data shows that the belt of weathering by fault fractured zone is developing on the basis of the right side of tunnel and that is decreasing to the left side. The fault fractured zone was confirmed that it has strike, $N0\~5^{\circ}E$ dip NW, and it is consisted of large-scale fractured zone including several anomalies. The severe displacement in tunnel is probably caused by asymmetrical load that n generated by the crossing of discontinuity and the rock strength imbalance of tunnel's both side by fault fractured zone, and judge that need tunnel reinforcement method of grouting etc.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.6
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• pp.543-551
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• 2023

As climate change continues to prompt an increasing demand for advancements in disaster and safety management technologies to address abnormal high water temperatures, typhoons, floods, and droughts, sea surface temperature has emerged as a pivotal factor for swiftly assessing the impacts of summer harmful algal blooms in the seas surrounding Korean Peninsula and the formation and dissipation of cold water along the East Coast of Korea. Therefore, this study sought to gauge predictive performance by leveraging statistical methods and deep learning algorithms to harness sea surface temperature data effectively for marine anomaly research. The sea surface temperature data employed in the predictions spans from 2018 to 2022 and originates from the Heuksando Tidal Observatory. Both traditional statistical ARIMA methods and advanced deep learning models, including long short-term memory (LSTM) and gated recurrent unit (GRU), were employed. Furthermore, prediction performance was evaluated using the attention LSTM technique. The technique integrated an attention mechanism into the sequence-to-sequence (s2s), further augmenting the performance of LSTM. The results showed that the attention LSTM model outperformed the other models, signifying its superior predictive performance. Additionally, fine-tuning hyperparameters can improve sea surface temperature performance.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.1
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• pp.49-63
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• 2016

In this study, we analyzed the effects of regional hydrologic variability during warm season (June-September) in South Korea due to ENSO (El $Ni{\tilde{n}}o$-Southern Oscillation) pattern changes over the Tropical Pacific Ocean (TPO). We performed composite analysis (CA) and statistical significance test by Student's t-test using observed hydrologic data (such as, precipitation and streamflow) in the 113 sub-watershed areas over the 5-Major River basin, in South Korea. As a result of this study, during the warm-pool (WP) El $Ni{\tilde{n}}o$ year shows a significant increasing tendency than normal years. Particularly, during the cold-tongue (CT) El $Ni{\tilde{n}}o$ decaying years clearly decreasing tendency compared to the normal years was appeared. In addition, the La $Ni{\tilde{n}}a$ years tended to show a slightly increasing tendency and maintain the average year state. In addition, from the result of scatter plot of the percentage anomaly of hydrologic variables during warm season, it is possible to identify the linear increasing tendency. Also the center of the scatter plot shows during the WP El $Ni{\tilde{n}}o$ year (+17.93%, +26.99%), the CT El $Ni{\tilde{n}}a$ year (-8.20%, -15.73%), and the La $Ni{\tilde{n}}a$ year (+8.89%, +15.85%), respectively. This result shows a methodology of the tele-connection based long-range water resources prediction for reducing climate forecasting uncertainty, when occurs the abnormal SSTA (such as, El $Ni{\tilde{n}}o$ and La $Ni{\tilde{n}}a$) phenomenon in the TPO region. Furthermore, it can be a useful data for water managers and end-users to support long-range water-related policy making.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1255-1272
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• 2023

Satellite-based chlorophyll-a concentration, produced as a long-term time series, is crucial for global climate change research. The production of data without gaps through the merging of time-synthesized or multi-satellite data is essential. However, studies related to satellite-based chlorophyll-a concentration in the waters around the Korean Peninsula have mainly focused on evaluating seasonal characteristics or proposing algorithms suitable for research areas using a single ocean color sensor. In this study, a merging dataset of remote sensing reflectance from the geostationary sensor GOCI-II and polar-orbiting sensors (MODIS, VIIRS, OLCI) was utilized to achieve high spatial coverage of chlorophyll-a concentration in the waters around the Korean Peninsula. The spatial coverage in the results of this study increased by approximately 30% compared to polar-orbiting sensor data, effectively compensating for gaps caused by clouds. Additionally, we aimed to quantitatively assess accuracy through comparison with global chlorophyll-a composite data provided by Ocean Colour Climate Change Initiative (OC-CCI) and GlobColour, along with in-situ observation data. However, due to the limited number of in-situ observation data, we could not provide statistically significant results. Nevertheless, we observed a tendency for underestimation compared to global data. Furthermore, for the evaluation of practical applications in response to marine disasters such as red tides, we qualitatively compared our results with a case of a red tide in the East Sea in 2013. The results showed similarities to OC-CCI rather than standalone geostationary sensor results. Through this study, we plan to use the generated data for future research in artificial intelligence models for prediction and anomaly utilization. It is anticipated that the results will be beneficial for monitoring chlorophyll-a events in the coastal waters around Korea.

• Journal of Korean Tunnelling and Underground Space Association
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• v.16 no.2
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• pp.149-160
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• 2014

The objective of this study is the application of the harmony search (HS) algorithm and verification of the accuracy of inverse analysis to predict the location, thickness and electrical properties of anomalous zone ahead of tunnel face when utilizing the electrical resistivity survey using electrical resistivity of the ground. The relationship correlating the characteristic values of the anomalous zone with the electrical resistance values was derived using Gauss' laws and Ohm's laws. Inverse analysis program was developed to predict anomalous zone by using electrical resistivity based on HS algorithm. Electrical resistance measuring system is devised to obtain the electrical resistivity of the ground, and laboratory tests were performed on anomalies to verify the proposed HS algorithm. The test results show that the characteristics of the anomalies are predicted reasonably well resulting in less than 5% error when predicting the location and thickness of the anomaly.

• Journal of the Korean earth science society
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• v.31 no.4
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• pp.354-369
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• 2010

The synoptic and kinematic characteristics of a heavy rainfall that occurred in Gangneung region on 22 to 24 October 2006 were investigated using weather maps, infrared images, AWS observation data and NCEP global final analyses data. The total amount of rainfall observed in the region for the period was 316.5 mm, and the instanteneous maximum wind speed was $63.7m\;s^{-1}$. According to the analysis of weather maps, before the starting of the heavy rainfall, an extratropical low pressure system was developed in the middle region of the Korean Peninsula, and an inverted trough was formed in the northern region of the peninsula. In addition, a jet stream on the upper charts of 300 hPa was located over the Yellow Sea and the southern boundary of the peninsula. A cutoff low in the cyclonic shear side of the upper jet streak, which was linked to an anomaly of isentropic potential vorticity, was developed over the northwestern part of the peninsula. And there are analyzed potential vorticity and wind, time-height cross section of potential vorticity, vertical air motion, maximums of the divergence and convergence and vertical distribution of potential temperature in Gangneung region. The analyzed results of the synoptic conditions and kinematic processes strongly suggest that the tropopause folding made a significant role of initializing the heavy rainfall.

• Journal of the korean academy of Pediatric Dentistry
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• v.35 no.4
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• pp.718-724
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• 2008

Tooth impaction is a frequently observed eruption anomaly in pediatric dental practice. Young patients with impacted or unerupted teeth have more prediction for dentigerous cyst formation. Dentigerous cyst presents radiographic features, unilocular or multilocular radioluscency. Cysts occur most frequently in the premolar region except third molar. Dentigerous cysts can grow to a considerable size, and large cysts may be associated with a painless expansion of the bone in the involved area. Extensive lesions may result in facial asymmetry, osseous destruction, root resorption of proximal teeth and displacement of associated tooth. The nature of the causative tooth influences the type of surgical treatment required for the dentigerous cyst. If the cyst is associated with a supernumerary or wisdom tooth, complete enucleation of the cyst along with extraction of tooth may be the first treatment choice. Otherwise, preservation of the associated teeth should be considered to prevent a young patient from psychological and mental trauma because of the loss of tooth. We should consider the degree of tooth displacement, osseous destruction and growth pattern of oromaxillofacial area when planning treatment. Thus a proper and logical treatment planning can help a proper growth and development of oromaxillofacial area and can save the patient from a psychological and mental trauma. This report describes 4 cases of the management of impacted premolars and molars associated with dentigerous cysts in children.

• Journal of Energy Engineering
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• v.27 no.4
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• pp.103-110
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• 2018

In this paper, we introduce evaluation method of time series prediction model with new approach of Mean Absolute Percentage Error(hereafter MAPE) and Symmetric Mean Absolute Percentage Error(hereafter sMAPE). There are some problems using MAPE and sMAPE. First MAPE can't evaluate Zero observation of dataset. Moreover, when the observed value is very close to zero it evaluate heavier than other methods. Finally it evaluate different measure even same error between observations and predicted values. And sMAPE does different evaluations are made depending on whether the same error value is over-predicted or under-predicted. And it has different measurement according to the each sign, even if error is the same distance. These problems were solved by Maximum Mean Absolute Percentage Error(hereafter mMAPE). we used the absolute maximum of observed value as denominator instead of the observed value in MAPE, when the value is less than 1, removed denominator then solved the problem that the zero value is not defined. and were able to prevent heavier measurement problem. Also, if the absolute maximum of observed value is greater than 1, the evaluation values of mMAPE were compared with those of the other evaluations. With Beijing PM2.5 temperature data and our simulation data, we compared the evaluation values of mMAPE with other evaluations. And we proved that mMAPE can solve the problems that we mentioned.