• Journal of the Korean Society of Urban Environment
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• v.18 no.4
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• pp.547-555
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• 2018

In addition to North America and Europe, Korea is also responding to the toxic damage caused by the production and distribution of chemicals. Methods for assessing bio-toxicity of harmful substances have been widely introduced, but it is required of quantitative and speedy information for modeling. For 6 heavy metals, as zinc, copper, chrome, cadmium, mercury and lead, bio-toxicity assessment and kinetics model were constructed using Vibrio fischeri which is widely used luminous bacteria. The degree of luminescence activity and the toxicity of heavy metals were relative limunescence unit, RLU measured as by using a photomultiplier embedded device. The toxicity was assessed by the concentration levels giving under 20% lethality and lethal concentration, $EC_{50}$. In the results, the toxicity order were followed from mercury, lead, copper, chrome, zinc and cadmium. $EC_{{50},{\infty}}$ obtained by trends of $EC_{50}$ by time follows had highly linear agreement with main parameters of bio-toxicity modelling. The average error rates of the reproduced lethality obtained from DAM and TDM model on the basis of body residue, were 10.2% for mercury, lead, copper, chrome and 20.0 for the all 6 methals.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.2
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• pp.324-339
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• 2021

In this study, we determined the correlation between the wave characteristics and the change in the area of Haeundae Beach, conducted regression analysis between the wave characteristics and the change in beach area, and derived a formula for calculating the change in beach area. The change in beach area was calculated by applying the derived formula to wave observation data corresponding to a period of approximately 10 months, and the formula was subsequently validated by comparing the obtained results with the observed area. It is found that the error associated with the formula for calculating the change in beach area ranges from 1.5 m to 2.7 m based on the average beach width, and the correlation coefficient corresponding to the observed area ranges from 0.91 to 0.94. Furthermore, it is observed that the change in beach area is af ected by the wave direction in the western zone, wave height in the central zone, and wave height and wave period in the eastern zone. These results can contribute to understanding the impact of a coastal improvement project on the beach area fluctuation characteristics of Haeundae Beach and the ef ectiveness of such a coastal improvement project. By applying the aforementioned derived formula to highly accurate wave prediction data, the change in beach area can be calculated and incorporated for predicting significant long-term changes in beach areas. Furthermore, such a prediction can be considered as the basis for making decisions while establishing preemptive countermeasure policies to prevent coastal erosion.

• Journal of Korea Water Resources Association
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• v.54 no.5
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• pp.335-345
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• 2021

The one-dimensional solute transport models have been developed for recent decades to predict behavior and fate of solutes in rivers. Transient storage model (TSM) is the most popular model because of its simple conceptualization to consider the complexity of natural rivers. However, the TSM is highly dependent on its parameters which cannot be directly measured. In addition, the TSM interprets the late-time behavior of concentration curves in the shape of an exponential function, which has been evaluated as not suitable for actual solute behavior in natural rivers. In this study, we suggested a stochastic approach to the solute transport analysis. We delineated the model development and model application to a natural river, and compared the results of the proposed model to those of the TSM. To validate the proposed model, a tracer test was carried out in the 4.85 km reach of Gam Creek, one of the first-order tributaries of Nakdong River, South Korea. As a result of comparing the power-law slope of the tail of breakthrough curves, the simulation results from the stochastic storage model yielded the average error rate of 0.24, which is more accurate than the 14.03 and 1.87 from advection-dispersion model and TSM, respectively. This study demonstrated the appropriateness of the power-law residence time distribution to the hyporheic zone of the Gam Creek.

• Therapeutic Science for Rehabilitation
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• v.10 no.1
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• pp.105-114
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• 2021

Objective : The purpose of this study was to identify and compare the sex differences in episodic memory and spatial cognition in healthy young adults. Methods : Forty-eight undergraduates (male=24, female=24) were assessed for sex differences using the visual stimuli episodic memory task and the virtual reality-based spatial cognition task. The accuracy rates (%) for the What, Where, and When conditions of the episodic memory task and the average distance error (cm) for 10 trials of the spatial cognition task were analyzed. Results : There were no significant sex differences between the three conditions. The male participants showed a significantly higher performance on the spatial cognition task than the female participants Conclusion : The results of this study indicated that the sex differences in episodic memory could be altered by the test methods. Although episodic memory and spatial cognition mainly depend on the hippocampus, the sex-related differences between the two functions were inconsistent, suggesting that these two functions are independent.

• Journal of the Korean GEO-environmental Society
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• v.12 no.11
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• pp.71-77
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• 2011

Recently, non-destructive stress measurement method using magnetic anisotropy sensor has been applied to the construction site such as steel bridges and steel pipes. In addition, steel rib used in the tunnel construction site was found to be possible to measure the stress by non-destructive method. In this study, steel loading experiments using magnetic anisotropy sensor developed in Japan and strain gauges were conducted to derive stress sensitivity curve for domestic steel SS400. Also, additional steel loading experiments and numerical analysis were performed for evaluation of applicability for non-destructive stress measurement method using magnetic anisotropy sensor. As a result of this study, stress sensitivity curves for domestic steel SS400 were derived using output voltage measured by magnetic anisotropy sensor and average of stress measured by strain gauges depending on the measurement location. And as a result of comparing additional steel loading experiments with the numerical analysis, error level of magnetic anisotropy sensor is around 20MPa. When considering the level of the yield stress(245MPa) of steel, in case of using magnetic anisotropy sensor in order to determine the stress status of steel, it has sufficient accuracy in engineering. Especially, magnetic anisotropy sensor can easily identify the current state of stress which considers residual stress at steel structure that stress measurement sensor is not installed, so we found that magnetic anisotropy sensor can be applied at maintenance of steel structure conveniently.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.6
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• pp.57-65
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• 2018

Conventional RF signal-based indoor localization techniques such as BLE or Wi-Fi based fingerprinting method show considerable localization errors even in small-scale indoor environments due to unstable received signal strength(RSS) of RF signals. Therefore, it is difficult to apply the existing RF-based fingerprinting techniques to large-scale indoor environments such as airports and department stores. In this paper, instead of RF signal we use the geomagnetic sensor signal for indoor localization, whose signal strength is more stable than RF RSS. Although similar geomagnetic field values exist in indoor space, an object movement would experience a unique sequence of the geomagnetic field signals as the movement continues. We use a deep neural network model called the recurrent neural network (RNN), which is effective in recognizing time-varying sequences of sensor data, to track the user's location and movement path. To evaluate the performance of the proposed geomagnetic field based indoor positioning system (IPS), we constructed a magnetic field map for a campus testbed of about $94m{\times}26$ dimension and trained RNN using various potential movement paths and their location data extracted from the magnetic field map. By adjusting various hyperparameters, we could achieve an average localization error of 1.20 meters in the testbed.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.2
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• pp.122-133
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• 2021

Cultivar parameter calibration can be affected by the reliability of the input data to a crop growth model. In South Korea, two sets of weather stations, which are included in the automated synoptic observing system (ASOS) or the automatic weather system (AWS), are available for preparation of the weather input data. The objectives of this study were to estimate the cultivar parameter using those sets of weather data and to compare the uncertainty of these parameters. The cultivar parameters of CERES-Rice model for Shindongjin cultivar was calibrated using the weather data measured at the weather stations included in either ASO S or AWS. The observation data of crop growth and management at the experiment farms were retrieved from the report of new cultivar development and research published by Rural Development Administration. The weather stations were chosen to be the nearest neighbor to the experiment farms where crop data were collected. The Generalized Likelihood Uncertainty Estimation (GLUE) method was used to calibrate the cultivar parameters for 100 times, which resulted in the distribution of parameter values. O n average, the errors of the heading date decreased by one day when the weather input data were obtained from the weather stations included in AWS compared with ASO S. In particular, reduction of the estimation error was observed even when the distance between the experiment farm and the ASOS stations was about 15 km. These results suggest that the use of the AWS stations would improve the reliability and applicability of the crop growth models for decision support as well as parameter calibration.

• Journal of IKEEE
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• v.25 no.2
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• pp.388-398
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• 2021

This paper proposes a particle swarm optimization (PSO)-based peak shaving scheme using energy storage system (ESS) for electricity tariff reduction. The proposed scheme compares the actual load with the estimated load consumption, calculates the additional output power that the ESS needs to discharge additionally to reduce peak load, and adds the input. In addition, in order to compensate for the additional power, the process of allocating power to the determined point is performed, and an optimization that minimizes the average of the load expected at the active power allocations using PSO so that the allocated value does not affect the peak load. To investigated the performance of the proposed scheme, case study of small and large load prediction errors was conducted by reflecting actual load data and load prediction algorithm. As a result, when the proposed scheme is performed with the ESS charge and discharge control to reduce electricity tariff, even when the load prediction error is large, the peak load is successfully reduced, and the peak load reduction effect of 17.8% and electricity tariff reduction effect of 6.02% is shown.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.3
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• pp.57-67
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• 2021

A thorough administration of the arterial road network requires a continuous supply of updated and accurate information about the traffic that travels on the roads. One of the ways to effectively obtain the traffic volume and weight distribution of heavy vehicles is the BWIM technique, which is actively being studied. Unlike previous studies, this study was performed to develop a simplified Bridge Weigh-In-Motion (BWIM) algorithm that can easily estimate the axle spacing and weight of a traveling vehicle by utilizing the structural characteristics of the bridge. A short span RC T-beam bridge with no crossbeam installed was selected for the study, and then the strain response characteristics of bridge deck and girder was checked through preliminary field test. Based on the preliminary field test results, a simplified BWIM algorithm suitable for the bridge to be studied was derived. The validity and accuracy of the BWIM algorithm derived in this study were verified through field test. As a result of the verification test, the proposed BWIM algorithm can estimate the axle spacing and gross weight of the travelling vehicles with the average percent error of less than 3%.

• Journal of Korean Society on Water Environment
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• v.37 no.3
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• pp.217-228
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• 2021

This paper discusses a methodology where an integrated modelling framework is used to quantify the risk derived from anthropic activities on habitats and species. To achieve this purpose, a tool comprising the Delft3D and HABITAT model, was applied in the Yeongsan river. Delft3D effectively simulated the operational condition and flow of weirs in river. In accuracy evaluation of the Delft3D-FLOW, the Bias, Pbias, Mean Absolute Error (MAE), Nash-Sutcliffe Efficiency (NSE), and Index of Agreement (IOA) were used, and the result was evaluated as grade above 'Satisfactory'. The HABITAT calculated Habitat Suitability Value (HSV) for the following eight species: mammal, fish, aquatic plant, and benthic macroinvertebrate. An Area was defined as a suitable habitat if the HSV was larger than 0.5. HABITAT was judged accurately by measuring the Correct Classification rate (CCR) and the area under the ROC curve (AUC). For benthic macroinvertebrate, the CCR and AUC were 77% and 0.834, respectively, at thresholds of 0.017 and 4 inds/m² for HSV and individuals per unit area. This meant that the HABITAT model accurately predicted the appearance of the benthic macroinvertebrates by approximately 77% and that the probability of false alarms was also very low. As a result of evaluating the suitability of habitats, in the Yeongsan river, if the annual "lowest level" (Seungchon weir: 2.5 EL.m/ Juksan weir: -1.35 EL.m) was maintained, the average habitat improvement effect of 6.5%P compared to the 'reference' scenario was predicted. Consequently, it was demonstrated that the integrated modelling framework for habitat suitability assessment is able to support the remedy aquatic ecological management.