• Proceedings of KOSOMES biannual meeting
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• 2005.05a
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• pp.7-12
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• 2005

A ship can be considered as a large human-machine system and the interaction between worker and system affects the work performed and its efficiency. Inside the bridge of a ship, there exist many auditory signals as well as visual signals. However, only a few studies have been performed related to human recognition to alarm systems in bridge. In this study, auditory icons and abstract sounds are compared to find more effective means of alarm systems. the study result shows tint auditory icons are recognized faster than abstract sounds. This result is expected to be used as a basic data for developing performance criteria of auditory display inside bridge and for designing integrated ship bridge alarm system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.179-185
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• 2020

Recently, in order to improve the performance of the Earthquake Early Warning System (EEWS) and to supplement the effects of earthquake disaster prevention in epicenters or near epicenters, development of on-site EEWS has been attempted. Unlike the national EEWS, which is used for earthquake disaster prevention by using seismic observation networks for earthquake research and observation, on-site EEWS aims at earthquake disaster prevention and therefore requires efficient design and evaluation in terms of performance and cost. At present, Korea lacks the necessary core technologies and operational know-how, including the use of existing EEWS design criteria and evaluation methods for the development of On-Site EEWS as well as EEWS. This study proposes hardware and software design directions and performance evaluation items and methods for seismic data collection, data processing, and analysis for localization of On-Site EEWS based on the seismic accelerometer requirements of the Seismic and Volcanic Disaster Response Act.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.67-77
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• 2023

This study represents an innovative research conducted in the smart farm environment, developing a deep learning-based disease and pest detection model and applying it to the Intelligent Internet of Things (IoT) platform to explore new possibilities in the implementation of digital agricultural environments. The core of the research was the integration of the latest ImageNet models such as Pseudo-Labeling, RegNet, EfficientNet, and preprocessing methods to detect various diseases and pests in complex agricultural environments with high accuracy. To this end, ensemble learning techniques were applied to maximize the accuracy and stability of the model, and the model was evaluated using various performance indicators such as mean Average Precision (mAP), precision, recall, accuracy, and box loss. Additionally, the SHAP framework was utilized to gain a deeper understanding of the model's prediction criteria, making the decision-making process more transparent. This analysis provided significant insights into how the model considers various variables to detect diseases and pests.

• Korean Journal of Soil Science and Fertilizer
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• v.51 no.2
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• pp.128-141
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• 2018

Industrial complex releasing huge amounts of dusts, fumes and wastewater containing heavy metal(loid)s could be a source of heavy metal(loid)s pollution in arable soil. Heavy metal(loid)s pollution in arable soil adversely affect crops safety, subsequently human being. Hence, it is important to accurately assess the heavy metal(loid)s pollution in soil using pollution indices. The objectives of this study are 1) to compare assessment methods of heavy metal(loid)s pollution in arable soils located near industrial complex in Gyeongsang provinces and 2) to determine the relationship between concentration of plant available heavy metal(loid)s and chemical properties of soil. Soil samples were collected from 85 sites of arable lands nearby 10 industrial complex in Gyeongsang provinces. The average total concentration of all heavy metal(loid)s of the studied soils was higher than that of Korean arable soils but did not exceed the warning criteria established by the Soil Environmental Conservation Act of Korea. Only six sites of arable soils for the total concentration of As, Cu and Ni exceeded the warning criteria (As: $25mg\;kg^{-1}$, Cu: $150mg\;kg^{-1}$, Ni: $100mg\;kg^{-1}$). The contamination factor (CF) and geoaccumulation index ($I_{geo}$) of the heavy metal(loid)s in arable soils varied among the sampling sites, and the average values of As and Cd were relatively higher than that of other metals. Results of integrated indices of As and Cd in arable soils located near industrial complex indicated that some arable soils were moderately or heavily polluted. The plant available concentration of heavy metal(loid)s was negatively related to the soil pH and negative charge of soil. Available Cd, Pb, and Zn concentrations had relatively high correlation coefficient with pH and negative charge of soil when compared with other heavy metal(loid)s. Based on the above results, it might be a good soil management to control pH with soil amendments such as lime and compost to reduce phytoavailability of heavy metal(loid)s in arable soil located near industrial complex.

• Journal of Korea Water Resources Association
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• v.56 no.10
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• pp.619-629
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• 2023

Recent intensification of climate change has led to an increase in damages caused by droughts. Currently, in Korea, the Standardized Precipitation Index (SPI) is used as a criterion to classify the intensity of droughts. Based on the accumulated precipitation over the past six months (SPI-6), meteorological drought intensities are classified into four categories: concern, caution, alert, and severe. However, there is a limitation in classifying drought intensity solely based on precipitation. To overcome the limitations of the meteorological drought warning criteria based on SPI, this study collected emergency water supply damage data from the National Drought Information Portal (NDIP) to classify drought intensity. Factors of SPI, such as precipitation, and factors used to calculate evapotranspiration, such as temperature and humidity, were indexed using min-max normalization. Coefficients for each factor were determined based on the Genetic Algorithm (GA). The drought intensity based on emergency water supply was used as the dependent variable, and the coefficients of each meteorological factor determined by GA were used as coefficients to derive a new Drought Severity Classification Index (DSCI). After deriving the DSCI, cumulative distribution functions were used to present intensity stage classification boundaries. It is anticipated that using the proposed DSCI in this study will allow for more accurate drought intensity classification than the traditional SPI, supporting decision-making for disaster management personnel.

• Journal of Korean Society of Forest Science
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• v.101 no.1
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• pp.28-35
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• 2012

Rainfall is widely recognized as a major landslide-triggering factor. Most of the latest landslides that occurred in South Korea were caused by short-duration heavy rainfall. However, the relationship between rainfall characteristics and landslide occurrence is poorly understood. To examine the effect of rainfall on landslide occurrence, cumulative rainfall(mm) and rainfall intensity(mm/hr) of serial rain and antecedent rainfall(mm) were analyzed for 18 landslide events that occurred in the southern and central regions of South Korea in June and July 2011. It was found that all of these landslides occurred by heavy rainfall for one or three days, with the rainfall intensity exceeding 30 mm/hr or with a cumulative rainfall of 200 mm. These plotted data are beyond the landslide warning criteria of Korea Forest Service and the critical line of landslide occurrence for Gyeongnam Province. It was also found that the time to landslide occurrence after rainfall start(T) was shortened with the increasing average rainfall intensity(ARI), showing an exponential-decay curve, and this relation can be expressed as "T = $94.569{\cdot}exp$($-0.068{\cdot}ARI$)($R^2$=0.64, p<0.001)". The findings in this study may provide important evidences for the landslide forecasting guidance service of Korea Forest Service as well as essential data for the establishment of non-structural measures such as a warning and evacuation system in the face of sediment disasters.

• Journal of Korea Water Resources Association
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• v.56 no.4
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• pp.261-272
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• 2023

In recent years, natural disasters such as heavy rainfall and typhoons have occurred more frequently, and their severity has increased due to climate change. The Korea Meteorological Administration (KMA) currently uses the same criteria for all regions in Korea for watch and warning based on the maximum cumulative rainfall with durations of 3-hour and 12-hour to reduce damage. However, KMA's criteria do not consider the regional characteristics of damages caused by heavy rainfall and typhoon events. In this regard, it is necessary to develop new criteria considering regional characteristics of damage and cumulative rainfalls in durations, establishing four stages: blue, yellow, orange, and red. A classification model, called DSCM (Disaster Severity Classification Model), for the four-stage disaster severity was developed using four machine learning models (Decision Tree, Support Vector Machine, Random Forest, and XGBoost). This study applied DSCM to local governments of Seoul, Incheon, and Gyeonggi Province province. To develop DSCM, we used data on rainfall, cumulative rainfall, maximum rainfalls for durations of 3-hour and 12-hour, and antecedent rainfall as independent variables, and a 4-class damage scale for heavy rain damage and typhoon damage for each local government as dependent variables. As a result, the Decision Tree model had the highest accuracy with an F1-Score of 0.56. We believe that this developed DSCM can help identify disaster risk at each stage and contribute to reducing damage through efficient disaster management for local governments based on specific events.

• Korean Journal of Soil Science and Fertilizer
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• v.47 no.1
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• pp.36-40
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• 2014

Korea's agricultural land is constantly being reduced. The reasons for this are due to the change of agricultural profitability and the policy conditions. The reduction of agricultural land in 2010 showed a decline trend by 14.4 % of paddy fields and 1.2% of uplands compared to areas from 2000. These reductions were mainly due to switch rice paddy fields into upland or greenhouse facility cultivation because of low profitability of rice products compared to farm products. In addition, the permit system of agricultural areas was relaxed in switching paddy fields and this accelerated the reduction of agricultural land. For this reason, more than 1% of agricultural land area has been reduced every year for last five years. Moreover, indiscreet fill and cover materials such as construction wastes were used in agricultural lands and caused land contamination which threatened foundation as sustainable agricultural lands. For these reasons, it is a desperate situation to conserve good agricultural lands. However, the standards of transported soils, filling soils and cutting soils in the Agricultural Land Act are qualitative and have a problem of causing complaints. Therefore, the following criteria (proposals) are proposed in the Agricultural Land Act; (1) Use the proper soils for crops (criterion), (2) Soil components and amounts should be proper as transported soils (range), and (3) Prohibiting usage of improper earth rocks or recycled aggregates in case of filling soils (kinds). The presented criteria (proposals) suggest following; (1) Use physio-chemically proper soils for crops (criterion), (2) In case of transported soils, i, exclude potential acid sulphate soils, ii, gravel content sould be less than 15%, and iii, Heavy metals and other contaminants should be less than the soil contamination warning limit from the Ministry of Environments, (3) In case of filling soils, 13 kinds of recycled wastes specified in the Wastes Control Act should not be used as filling soils, (4) Practice soil conservation technology in case of sloping areas, and (5) Follow proper fertilizer application standards for maturing paddy fields and uplands when cutting soils.

• Journal of the Korean Geosynthetics Society
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• v.17 no.4
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• pp.267-275
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• 2018

The dredged sediment management system was developed to have an objective, quantitative and scientific decision for the optimum removal time of dredged sediments behind debris barrier and was set up at the real site. The dredged sediment management system is designed and developed to directly measure the dredged sediments behind debris barrier in the field. This management system is composed of Data Acquisition System (DAS), Solar System and measurement units for measuring the weight of dredge sediments. The weight of dredged sediments, the water level and the rainfall are measured in real time using the monitoring sensors, and their data can be transmitted to the office through a wireless communication method. The monitoring sensors are composed of the rain gauge to measure rainfall, the load cell system to measure the weight of dredged sediments, and water level meter to measure the water level behind debris barrier. The management criteria of dredged sediments behind debris barrier was suggested by using the weight of dredged sediments. At first, the maximum weight of dredged sediments that could be deposited behind debris barrier was estimated. And then when 50%, 70% and 90% of the maximum dredged sediments weight were accumulated behind debris barrier, the management criteria were divided into phases of Outlooks, Watch and Warning, respectively. The weight of dredged sediments can be monitored by using the dredged sediment management system behind debris barrier in real time, and the condition of debris barrier and the removal time of dredged sediments can be decided based on monitoring results.

• Environmental Analysis Health and Toxicology
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• v.25 no.1
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• pp.19-26
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• 2010

Discharged materials from the point or non-point source are released into the sea, and as the results, marine environment is directly affected. We must estimate the impacts of contaminants to marine pollution rapidly and accurately. Therefore, it is needed on early warning system for appreciating marine environmental impacts, and required a bioassay to evaluate abnormal changes. A bioassay test was developed to examine the effects of heavy metal contaminants on the early life stages of the marine annimals. We have studied the effects of metals on early development of a sea urchin species, Strongylocentrotus intermedius. S. intermedius embryos were tested with six metals (Cu, Ag, Zn, Cd, Cr, Ni) and showed the highest sensitivity to Cu as well as the lowest sensitivity to Cd. The order of biological impact for metals was Cu>Ag>Ni>Zn>Cr>Cd. In accordance with the results, sea urchins embryos can provide biological criteria for seawater quality assessment. The sensitivity of developmental bioassay whith S. intermedius is at intermediate level among marine organisms commonly used in aquatic bioassays. And this sea urchin can be routinely employed as a test organism for ecotoxicity assays.