• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5B
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• pp.437-444
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• 2010

Soil moisture has been recognized as the essential parameter when understanding the complicated relationship between land surface and atmosphere in water and energy recycling system. It has been generally known that it is related with the temperature, wind, evaporation dependent on soil properties, transpiration due to vegetations and other constituents. There is, however, little research concerned about the relationship between soil moisture and these constitutes, thus it is needed to investigate it in detail. We estimated the soil moisture and then compared with field data using the hydrometerological data such as atmospheric temperature, specific humidity, and wind obtained from the Flux tower in Selmacheon, Korea. In the winter season, subterranean temperature showed highly positive correlation with soil moisture while it was negatively correlated from the spring to the fall. Estimation of seasonal soil moisture was compared with field measurements with the correlation of determination, R=0.82, 0.81, 0.82, and 0.96 for spring, summer, fall, and winter, respectively. Comprehensive relationship from this study can supply useful information about the downscaling of soil moisture with relatively large spatial resolutions, and will help to deepen the understanding of the water and energy recycling on the earth's surface.

• Journal of Korea Water Resources Association
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• v.56 no.5
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• pp.337-345
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• 2023

Monitoring river microplastics is a challenging task since it is a time-consuming and high-cost process. The use of a physical model to have a better understanding of river microplastics' behaviors can complement the challenging monitoring process. However, there have been very limited studies on modeling river microplastics. In this study, therefore, we evaluated the applicability of one commonly used river water quality model, i.e., the Water Quality Analysis Simulation Program (WASP), in simulating the microplastic concentration in the river environment. We simulated the microplastic concentration in the Anyangcheon stream using the WASP's biochemical oxygen demand (BOD) and suspended solid (SS) variables as possible surrogate variables for the microplastics. Simulation analyses indicate that the SS state variable performs better than the BOD state variable to mimic the observed concentrations of microplastics. This is because of the characteristics of each water quality parameter; the BOD variable, a biochemical indicator, is inappropriate for modeling the behaviors of microplastics, which have generally constant biochemical features. In contrast, the SS variable, which has similar physical behaviors, followed the observed patterns of the microplastic concentrations well. To build a more advanced and accurate model for simulating the microplastic concentration, comprehensive and long-term monitoring studies of the river microplastics under different environmental conditions are needed, and the unit of microplastic concentration should be carefully addressed before its modeling application.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5D
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• pp.443-451
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• 2010

This paper proposes the methodology about advisory safety speed based on real-time vehicular data collected from highway. The proposed model is useful information to drivers by appling seamless wireless communication and being collected from ECU(Engine Control Unit) equipment in every vehicle. Furthermore, this model also permits the use of realtime sensing data like as adverse weather and road-surface data. Here, the advisory safety speed is defined "the safety speed for drivers considering the time-dependent traffic condition and road-surface state parameter at uniform section", and the advisory safety speed model is developed by considering the parameters: inter-vehicles safe stopping distance, statistical vehicle speed, and real-time road-surface data. This model is evaluated by using the simulation technique for exploring the relationships between advisory safety speed and the dependent parameters like as traffic parameters(smooth condition and traffic jam), incident parameters(no-accident and accident) and road-surface parameters(dry, wet, snow). A simulation's results based on 12 scenarios show significant relationships and trends between 3 parameters and advisory safety speed. This model suggests that the advisory safety speed has more higher than average travel speed and is changeable by changing real-time incident states and road-surface states. The purpose of the research is to prove the new safety related services which are applicable in SMART Highway as traffic and IT convergence technology.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2020.08a
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• pp.55-55
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• 2020

This study investigated the growth and chlorophyll fluorescence reactions of three Ardisia genus grown under various indoor light intensity conditions with the aim of evaluating their suitability as indoor plants. Young seedlings of A. crispa (Thunb.) A.DC., A. pusilla DC., and A. japonica (Thunb.) Blume were used in the experiment. The plants were cultivated indoors for 10 weeks under different light intensities: 10, 50, 100, and 200 PPFD (μmol·m^-2·s^-1), and their growth was compared with that of plants cultivated in a greenhouse during the same period (mean value 236.8±20.4 PPFD at noon). Also, chlorophyll fluorescence analysis was investigated with a portable PAM fluorometer. The indoor plants were maintained at 12/12 h photoperiod, temperature at 25±1℃, and humidity at 55±3%. Irrigation frequency (once every three days) was the same for the indoors and the greenhouse. The results of growth in three Ardisia plants showed that almost all parameters except leaf number and chlorophyll content had similar levels regardless of light intensity. A. crispa and A. pusilla plants grown in 200 PPFD were investigated to have low chlorophyll contents. Meanwhile, chlorophyll fluorescence parameters differed based on light levels. In A. crispa, the Fv/Fm (0.77), DIo/RC (0.47) and Fm/Fo (4.77) parameters tended to be poor at 200 PPFD compared to those at other light intensities. Similarly, the DIo/RC, Fm/Fo, and Pi_Abs parameters of A. pusilla plant (200 PPFD) are 0.45, 4.48 and 2.42, respectively, which can be considered stress. The analysis of fluorescence in A. japonica showed that all parameters except ETo/RC had similar levels regardless of light intensity. The ETo/RC parameter was 0.49 and 0.72 in the control plants and plants 200 PPFD, respectively, which was lower than those in plants at other light intensities. Therefore, it seems that the relatively high light intensity acted as a stressor for Ardisia plants.

• Advanced Industrial SCIence
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• v.3 no.2
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• pp.8-16
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• 2024

This paper shows the system of drug classification, the goal of this is to foretell the apt drug for the patients based on their demographic and physiological traits. The dataset consists of various attributes like Age, Sex, BP (Blood Pressure), Cholesterol Level, and Na_to_K (Sodium to Potassium ratio), with the objective to determine the kind of drug being given. The models used in this paper are K-Nearest Neighbors (KNN), Logistic Regression and Random Forest. Further to fine-tune hyper parameters using 5-fold cross-validation, GridSearchCV was used and each model was trained and tested on the dataset. To assess the performance of each model both with and without hyper parameter tuning evaluation metrics like accuracy, confusion matrices, and classification reports were used and the accuracy of the models without GridSearchCV was 0.7, 0.875, 0.975 and with GridSearchCV was 0.75, 1.0, 0.975. According to GridSearchCV Logistic Regression is the most suitable model for drug classification among the three-model used followed by the K-Nearest Neighbors. Also, Na_to_K is an essential feature in predicting the outcome.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.3
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• pp.1-12
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• 2024

In this paper, we fine-tuned KoAlpaca, a large-scale Korean language model, and implemented a blog text generation system utilizing it. Blogs on social media platforms are widely used as a marketing tool for businesses. We constructed training data of positive reviews through emotion analysis and refinement of collected sponsored blog texts and applied QLoRA for the lightweight training of KoAlpaca. QLoRA is a fine-tuning approach that significantly reduces the memory usage required for training, with experiments in an environment with a parameter size of 12.8B showing up to a 58.8% decrease in memory usage compared to LoRA. To evaluate the generative performance of the fine-tuned model, texts generated from 100 inputs not included in the training data produced on average more than twice the number of words compared to the pre-trained model, with texts of positive sentiment also appearing more than twice as often. In a survey conducted for qualitative evaluation of generative performance, responses indicated that the fine-tuned model's generated outputs were more relevant to the given topics on average 77.5% of the time. This demonstrates that the positive review generation language model for sponsored content in this paper can enhance the efficiency of time management for content creation and ensure consistent marketing effects. However, to reduce the generation of content that deviates from the category of positive reviews due to elements of the pre-trained model, we plan to proceed with fine-tuning using the augmentation of training data.

• The Journal of the Acoustical Society of Korea
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• v.28 no.4
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• pp.392-400
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• 2009

In this paper, we propose an effective speech reinforcement technique base on ITU-T G.729A CS-ACELP codec under the near-end background noise environments. In general, since the intelligibility of the far-end speech for the near-end listener is significantly reduced under near-end noise environments, we require a far-end speech reinforcement approach to avoid this phenomena. In contrast to the conventional speech reinforcement algorithm, we reinforce the excitation signal of the codec's parameters received from the far-end speech signal based on the G.729A speech codec under various background noise environments. Specifically, we first estimate the excitation signal of ambient noise at the near-end through the encoder of the G.729A speech codec, reinforcing the excitation signal of the far-end speech transmitted from the far-end. we specially propose a novel approach to directly reinforce the excitation signal of far-end speech signal based on the decoder of the G.729A. The performance of the proposed algorithm is evaluated by the CCR (Comparison Category Rating) test of the method for subjective determination of transmission quality in ITU-T P.800 under various noise environments and shows better performances compared with conventional SNR Recovery methods.

• Korean Journal of Remote Sensing
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• v.40 no.4
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• pp.397-418
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• 2024

The Land Surface Temperature (LST) is a crucial parameter in identifying drought. It is essential to identify how LST can increase its accuracy, particularly in mountainous and hill areas. Increasing the LST accuracy can be achieved by applying early data processing in the correction phase, specifically in the context of topographic correction on the Lambertian model. Empirical evidence has demonstrated that this particular stage effectively enhances the process of identifying objects, especially within areas that lack direct illumination. Therefore, this research aims to examine the application of the Lambertian model in estimating LST using the Multi-Channel Method (MCM) across various physiographic regions. Lambertian model is a method that utilizes Lambertian reflectance and specifically addresses the radiance value obtained from Sun-Canopy-Sensor(SCS) and Cosine Correction measurements. Applying topographical adjustment to the LST outcome results in a notable augmentation in the dispersion of LST values. Nevertheless, the area physiography is also significant as the plains terrain tends to have an extreme LST value of ≥ 350 K. In mountainous and hilly terrains, the LST value often falls within the range of 310-325 K. The absence of topographic correction in LST results in varying values: 22 K for the plains area, 12-21 K for hilly and mountainous terrain, and 7-9 K for both plains and mountainous terrains. Furthermore, validation results indicate that employing the Lambertian model with SCS and Cosine Correction methods yields superior outcomes compared to processing without the Lambertian model, particularly in hilly and mountainous terrain. Conversely, in plain areas, the Lambertian model's application proves suboptimal. Additionally, the relationship between physiography and LST derived using the Lambertian model shows a high average R² value of 0.99. The lowest errors(K) and root mean square error values, approximately ±2 K and 0.54, respectively, were achieved using the Lambertian model with the SCS method. Based on the findings, this research concluded that the Lambertian model could increase LST values. These corrected values are often higher than the LST values obtained without the Lambertian model.

• Journal of Biomedical Engineering Research
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• v.25 no.4
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• pp.261-268
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• 2004

Osteoporosis is a clinical condition in which the amount of bone tissue is reduced and the likelihood of fracture is increased. It is known that the electrical property of the bone is related to its density, and, in particular, the electrical resistance of the bone decreases as the bone loss increases. This implies that the electrical property of bone may be an useful parameter to diagnose osteoporosis, provided that it can be readily measured. The study attempted to evaluate the electrical conductivity of bone using a technique of electrical impedance tomography (EIT). It nay not be easy in general to get an EIT for the bone due to the big difference (an order of 2) of electrical properties between the bone and the surrounding soft tissue. In the present study, we took an adaptive mesh regeneration technique originally developed for the detection of two phase boundaries and modified it to be able to reconstruct the electrical conductivity inside the boundary provided that the geometry of the boundary was given. Numerical simulation was carried out for a tibia phantom, circular cylindrical phantom (radius of 40 mm) inside of which there is an ellipsoidal homeogenous tibia bone (short and long radius are 17 mm and 15 mm, respectively) surrounded by the soft tissue. The bone was located in the 15 mm above from the center of the circular cross section of the phantom. The electrical conductivity of the soft tissue was set to be 4 mS/cm and varies from 0.01 to 1 ms/cm for the bone. The simulation considered measurement errors in order to look into its effects. The simulated results showed that, if the measurement error was maintained less than 5 %, the reconstructed electrical conductivity of the bone was within 10 % errors. The accuracy increased with the electrical conductivity of the bone, as expected. This indicates that the present technique provides more accurate information for osteoporotic bones. It should be noted that tile simulation is based on a simple two phase image for the bone and the surrounding soft tissue when its anatomical information is provided. Nevertheless, the study indicates the possibility that the EIT technique may be used as a new means to detect the bone loss leading to osteoporotic fractures.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.1
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• pp.13-17
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• 2010

Purpose: Partial volume effect (PVE) is the phenomenon to lower the accuracy of image due to low estimate, which is to occur from PET/CT 3D image acquisition. The more resolution is declined and the lesion is small, the more it causes a big error. So that it can influence the test result. Studied the optimum image reconstruction method by using variation of parameter, which can influence the PVE. Materials and Methods: It acquires the image in each size spheres which is injected $^{18}F$-FDG to hot site and background in the ratio 4:1 for 10 minutes by using NEMA 2001 IEC phantom in GE Discovey STE 16. The iterative reconstruction is used and gives variety to iteration 2-50 times, subset number 1-56. The analysis's fixed region of interest in detail part of image and compute % difference and signal to noise ratio (SNR) using $SUV_{max}$. Results: It's measured that $SUV_{max}$ of 10 mm spheres, which is changed subset number to 2, 5, 8, 20, 56 in fixed iteration to times, SNR is indicated 0.19, 0.30, 0.40, 0.48, 0.45. As well as each sphere's of total SNR is measured 2.73, 3.38, 3.64, 3.63, 3.38. Conclusion: In iteration 6th to 20th, it indicates similar value in % difference and SNR ($3.47{\pm}0.09$). Over 20th, it increases the phenomenon, which is placed low value on $SUV_{max}$ through the influence of noise. In addition, the identical iteration, it indicates that SNR is high value in 8th to 20th in variation of subset number. Therefore, to reduce partial volume effect of small lesion, it can be declined the partial volume effect in iteration 6 times, subset number 8~20 times, considering reconstruction time.