• Korean Journal of Environmental Biology
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• v.40 no.4
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• pp.464-476
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• 2022

In recent years, macroalgal bloom occurs frequently in coastal oceans worldwide. It might be attributed to accelerating climate change. "Green tide" events caused by proliferation of green macroalgae (Ulva spp.) not only damage the local economy, but also harm coastal environments. These nuisance events have become common across several coastal regions of continents. In Korea, green tide incidences are readily seen throughout the year along the coastlines of Jeju Island, particularly the northeastern coast, since the 2000s. Ulva species are notorious to be difficult for morphology-based species identification due to their high degrees of phenotypic plasticity. In this study, to investigate temporal variation in Ulva community structure on Jeju Island between 2015 and 2020, chloroplast barcode tufA gene was sequenced and phylogenetically analyzed for 152 specimens from 24 sites. We found that Ulva ohnoi and Ulva pertusa known to be originated from subtropical regions were the most predominant all year round, suggesting that these two species contributed the most to local green tides in this region. While U. pertusa was relatively stable in frequency during 2015 to 2020, U. ohnoi increased 16% in frequency in 2020 (36.84%), which might be associated with rising sea surface temperature from which U. ohnoi could benefit. Two species (Ulva flexuosa, Ulva procera) of origins of Europe should be continuously monitored. The findings of this study provide valuable information and molecular genetic data of genus Ulva occurring in southern coasts of Korea, which will help mitigate negative influences of green tide events on Korea coast.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.655-667
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• 2023

Algal bloom outbreaks are frequently reported around the world, and serious water pollution problems arise every year in Korea. It is necessary to protect the aquatic ecosystem through continuous management and rapid response. Many studies using satellite images are being conducted to estimate the concentration of chlorophyll-a (Chl-a), an indicator of algal bloom occurrence. However, machine learning models have recently been used because it is difficult to accurately calculate Chl-a due to the spectral characteristics and atmospheric correction errors that change depending on the water system. It is necessary to consider the factors affecting algal bloom as well as the satellite spectral index. Therefore, this study constructed a dataset by considering water quality, hydrological and meteorological factors, and sentinel-2 images in combination. Representative ensemble models random forest and extreme gradient boosting (XGBoost) were used to predict the concentration of Chl-a in eight weirs located on the Nakdong river over the past five years. R-squared score (R²), root mean square errors (RMSE), and mean absolute errors (MAE) were used as model evaluation indicators, and it was confirmed that R² of XGBoost was 0.80, RMSE was 6.612, and MAE was 4.457. Shapley additive expansion analysis showed that water quality factors, suspended solids, biochemical oxygen demand, dissolved oxygen, and the band ratio using red edge bands were of high importance in both models. Various input data were confirmed to help improve model performance, and it seems that it can be applied to domestic and international algal bloom detection.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.2
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• pp.583-595
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• 2014

Currently, Korean transportation policies are aiming for increase of safety and environment-friendly and efficient operation, by avoiding construction and expansion of roads, and upgrading road alignments and facilities. This is revealed by that there have been 22 road expansion projects (30%) and 50 road improvement projects (70%) under the 3rd Five-Year Plan for National Highways ('11~'15), while there were 53 road expansion projects (71%) and 22 road improvement projects (29%) under the 2nd Five-Year Plan for National Highways. For more effective road improvement projects, there is a need of choosing projects after an objective and scientific safety assessment of each road, and assessing safety improvement depending on projects. This study is intended to develop a model for this road safety analysis and assessment. The major objective of this study is creating a road safety analysis and assessment model appropriate for Korean society, based on the HSM (Highway Safety Manual) of the U.S. In order to build up data for model development, the sections thought to have identical geometrical structure factors in 5 lines, Cheonbuk province, were divided as homogeneous sections, and representative values of geometric structures, facilities, traffic volume, climate conditions and land usage were collected from the 1,452 sections divided. In order to build up data for model development, the sections thought to have identical geometrical structure factors in 5 lines, Cheonbuk province, were divided as homogeneous sections, and representative values of geometric structures, facilities, traffic volume, climate conditions and land usage were collected from the 1,452 sections divided. The collected data was processed correlation analysis of each road element was implemented to see which factor had a big effect on traffic accidents. On the basis of these results, then, an accident model was established as a negative binomial regression model.Using the developed model, an Crash Modification Factor (CMF) which determines accident frequency changes depending on safety performance function (SPF) predicting the number of accident occurrence through traffic volume and road section expansion, road geometric structure and traffic properties, was extracted.

• Journal of Korean Society of Transportation
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• v.18 no.1
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• pp.75-85
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• 2000

In existing models in optimization, the crisp data improve has been used in the objective or constraints to derive the optimal solution, Besides, the subjective environments are eliminated because the complex and uncertain circumstances were regarded as Probable ambiguity, In other words those optimal solutions in the existing models could be the complete satisfactory solutions to the objective functions in the Process of application for industrial engineering methods to minimize risks of decision-making. As a result of those, decision-makers in location Problems couldn't face appropriately with the variation of demand as well as other variables and couldn't Provide the chance of wide selection because of the insufficient information. So under the circumstance. it has been to develop the model for the location and size decision problems of logistics facility in the use of the fuzzy theory in the intention of making the most reasonable decision in the Point of subjective view under ambiguous circumstances, in the foundation of the existing decision-making problems which must satisfy the constraints to optimize the objective function in strictly given conditions in this study. Introducing the Process used in this study after the establishment of a general mixed integer Programming(MIP) model based upon the result of existing studies to decide the location and size simultaneously, a fuzzy mixed integer Programming(FMIP) model has been developed in the use of fuzzy theory. And the general linear Programming software, LINDO 6.01 has been used to simulate, to evaluate the developed model with the examples and to judge of the appropriateness and adaptability of the model(FMIP) in the real world.

• Nuclear Medicine and Molecular Imaging
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• v.42 no.6
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• pp.469-477
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• 2008

Purpose: The goal of this paper is to present the design and performance of a position encoding circuit for $16{\times}16$ array of position sensitive multi-anode photomultiplier tube for small animal PET scanners. This circuit which reduces the number of readout channels from 256 to 4 channels is based on a charge division method utilizing a resistor array. Materials and Methods: The position encoding circuit was simulated with PSpice before fabrication. The position encoding circuit reads out the signals from H9500 flat panel PMTs (Hamamatsu Photonics K.K., Japan) on which $1.5{\times}1.5{\times}7.0\;mm^3$ $L_{0.9}GSO$ ($Lu_{1.8}Gd_{0.2}SiO_{5}:Ce$) crystals were mounted. For coincidence detection, two different PET modules were used. One PET module consisted of a $29{\times}29\;L_{0.9}GSO$ crystal layer, and the other PET module two $28{\times}28$ and $29{\times}29\;L_{0.9}GSO$ crystal layers which have relative offsets by half a crystal pitch in x- and y-directions. The crystal mapping algorithm was also developed to identify crystals. Results: Each crystal was clearly visible in flood images. The crystal identification capability was enhanced further by changing the values of resistors near the edge of the resistor array. Energy resolutions of individual crystal were about 11.6%(SD 1.6). The flood images were segmented well with the proposed crystal mapping algorithm. Conclusion: The position encoding circuit resulted in a clear separation of crystals and sufficient energy resolutions with H9500 flat-panel PMT and $L_{0.9}GSO$ crystals. This circuit is good enough for use in small animal PET scanners.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.43-57
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• 2012

To enhance the competitive advantage in a constantly changing business environment, an enterprise management must make the right decision in many business activities based on both internal and external information. Thus, providing accurate information plays a prominent role in management's decision making. Intuitively, historical data can provide a feasible estimate through the forecasting models. Therefore, if the service department can estimate the service quantity for the next period, the service department can then effectively control the inventory of service related resources such as human, parts, and other facilities. In addition, the production department can make load map for improving its product quality. Therefore, obtaining an accurate service forecast most likely appears to be critical to manufacturing companies. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average simulation. However, these methods are only efficient for data with are seasonal or cyclical. If the data are influenced by the special characteristics of product, they are not feasible. In our research, we propose a forecasting framework that predicts service demand of manufacturing organization by combining Case-based reasoning (CBR) and leveraging an unsupervised artificial neural network based clustering analysis (i.e., Self-Organizing Maps; SOM). We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the service forecasting domain. Our proposed approach has several appealing features : (1) We applied CBR and SOM in a new forecasting domain such as service demand forecasting. (2) We proposed our combined approach between CBR and SOM in order to overcome limitations of traditional statistical forecasting methods and We have developed a service forecasting tool based on the proposed approach using an unsupervised artificial neural network and Case-based reasoning. In this research, we conducted an empirical study on a real digital TV manufacturer (i.e., Company A). In addition, we have empirically evaluated the proposed approach and tool using real sales and service related data from digital TV manufacturer. In our empirical experiments, we intend to explore the performance of our proposed service forecasting framework when compared to the performances predicted by other two service forecasting methods; one is traditional CBR based forecasting model and the other is the existing service forecasting model used by Company A. We ran each service forecasting 144 times; each time, input data were randomly sampled for each service forecasting framework. To evaluate accuracy of forecasting results, we used Mean Absolute Percentage Error (MAPE) as primary performance measure in our experiments. We conducted one-way ANOVA test with the 144 measurements of MAPE for three different service forecasting approaches. For example, the F-ratio of MAPE for three different service forecasting approaches is 67.25 and the p-value is 0.000. This means that the difference between the MAPE of the three different service forecasting approaches is significant at the level of 0.000. Since there is a significant difference among the different service forecasting approaches, we conducted Tukey's HSD post hoc test to determine exactly which means of MAPE are significantly different from which other ones. In terms of MAPE, Tukey's HSD post hoc test grouped the three different service forecasting approaches into three different subsets in the following order: our proposed approach > traditional CBR-based service forecasting approach > the existing forecasting approach used by Company A. Consequently, our empirical experiments show that our proposed approach outperformed the traditional CBR based forecasting model and the existing service forecasting model used by Company A. The rest of this paper is organized as follows. Section 2 provides some research background information such as summary of CBR and SOM. Section 3 presents a hybrid service forecasting framework based on Case-based Reasoning and Self-Organizing Maps, while the empirical evaluation results are summarized in Section 4. Conclusion and future research directions are finally discussed in Section 5.

• Journal of Astronomy and Space Sciences
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• v.25 no.1
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• pp.33-42
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• 2008

By analyzing the observations from a number of ground- and space-based instruments, including ionosonde, magnetometers, and ACE interplanetary data, we examine the response of the ionospheric TEC over Korea during 2003 magnetic storms. We found that the variation of vertical TEC is correlated with the southward turning of the interplanetary magnetic field $B_z$. It is suggested that the electric fields produced by the dynamo process in the high-latitude region and the prompt penetration in the low- latitude region are responsible for TEC increases. During the June 16 event, dayside TEC values increase more than 15%. And the ionospheric F2-layer peak height (hmF2) was ${\sim}300km$ higher and the vertical $E{\times}B$ drift (estimated from ground-based magnetometer equatorial electrojet delta H) showed downward drift, which may be due to the ionospheric disturbance dynamo electric field produced by the large amount of energy dissipation into high-latitude regions. In contrast, during November 20 event, the nightside TEC increases may be due to the prompt penetration westward electric field. The ionospheric F2-layer peak height was below 200km and the vertical $E{\times}B$ drift showed downward drift. Also, a strong correlation is observed between enhanced vertical TEC and enhaaced interplanetary electric field. It is shown that, even though TEC increases are caused by the different processes, the electric field disturbances in the ionosphere play an important role in the variation of TEC over Korea.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.6
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• pp.652-657
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• 2018

Breeding control in a farm is a very important factor affecting milk productivity. Breeding management is important for the early detection of estrus, and reliable, automatic, more accurate, and faster monitoring of the timing of dairy cows is essential for farmers. This study measured the accuracy of estrus using the estrus indications, changes in activities, rumination activities, ruminal temperature, and pH. The biomedical information device S1 used in this study provided an estrus notice using the rumen temperature, pH, cow activities, and number of drinking estimations, which were inserted in the rumen through the oral route. The S2 device was used in the estrus notice for the rumen activities and cow activities. The data collected on the instrument were collected at intervals of 2 hours per day at the reference days (RD: -7~-3, +7~+ 3) +2), 7 days before insemination, and 7 days after insemination. The activities of the S1 device used in this paper increased with increasing number of insemination days (-1: $12.5{\pm}1.03/day$; 0: $12.9{\pm}1.73/day$) compared to the reference day (RD: $10.2{\pm}1.0/day$). The activities of the S2 device was also found to increase from the reference day to the insemination day (0: $63.0{\pm}3.66$) compared to the reference day (RD: $40.3{\pm}2.68$). The number of daily drinks in S1 decreased from the reference day (RD: $5.9{\pm}0.89/day$) to before the insemination day (-2: $5.6{\pm}0.98$; -1: $5.7{\pm}0.96$); +2: $6.0{\pm}0.73$). The number of daily drinks on the insemination day (0: $6.3{\pm}0.86$; +2: $6.0{\pm}0.73$) was similar to the reference day. The number of daily rumination in S2 decreased from the reference day (RD: $493.8{\pm}10.92$) to the insemination day (-1: $390.2{\pm}13.36$; 0: $354.1{\pm}16.71$).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.442-447
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• 2017

The purpose of this study was to establish norm-referenced criteria for the isokinetic strength of the elbow joint in Korean high school baseball players. Two hundred and one high school baseball players participated in this study, none of whom had any medical problem with their upper limbs. The elbow flexion/extension test was conducted four times at a speed of $60^{\circ}/sec$. The HUMAC NORM (CSMI, USA) system was used to obtain the values of the peak torque and peak torque per body weight. The results were presented as norm-referenced criterion valuesusing the 5-point scale of Cajori which consists of five stages (6.06%, 24.17%, 38.30%, 24.17%, and 6.06%). In the results of this study, the peak torques of the elbow (flexor and extensor?) at an angular velocity of $60^{\circ}/sec$ were $37.88{\pm}8.14Nm$ and $44.59{\pm}11.79Nm$, and the peak torque per body weight of the elbow (flexor and extensor?) were $50.06{\pm}8.66Nm$ and $58.28{\pm}12.84Nm$, respectively. The reference values of the peak torque and peak torque per body weight of the elbow flexor and extensor were setat an angular velocity of $60^{\circ}/sec$. On the basis of the results analyzed in this study, the following conclusions were drawn. There is a lack of proper studies on the elbow joint strength, even though the most common injury in baseball players occurs in the elbow joint. Therefore, we need to establish a standard muscle strength in order to prevent elbow joint injuries and improve their performance. The criteria for the peak torque and peak torque per body weight established here in will provide useful information for high school baseball players, baseball coaches, athletic trainers and sports injury rehabilitation specialists in injury recovery and return to rehabilitation, which can beutilized as objective clinical assessment data.

• Investigative Magnetic Resonance Imaging
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• v.4 no.2
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• pp.100-106
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• 2000

Purpose : To evaluate the usefulness of cerebral blood flow measurement applied to perfusion weighted image with short-scan time single shot gradient echo-planar technique in measuring cerebral blood volume(rCBV) of normal rabbits. Materials and methods : With 2.1-3.6 kg weighted rabbits, image is acquired when they are in supine position in children positioner. Perfusion weighted image is acquired to 44 seconds per 1 second successively. After 4 seconds later, Gd-DTPA 2ml are injected into int. jugular vein with 2 ml per second and normal saline is also injected after that. Same technique is applied 2 times per 30 minites in same rabbit. After Image is obtained in two part of cerebral cortex at vertex, convexity, in one of basal ganglia with choosing about $3-5{\textrm{mm}^2}$ areas. Curve of signal intensity changes in time sequence is drawn. After this images are transmitted by PC and software IDL, regional cerebral blood volume is measured with imaging processing program made by us. Results : With 22 of 24 rabbits, satisfactory 1-2 signal intensity versus time curve is made. Cerebral blood capacity and contrast media stay time (ST) is measured in two cerebral cortex and basal ganglia refering in parietal cerebral cortex. Mean focal cerebral blood flow capacity ratio in cortex was $0.97{\pm}0.35$ and in basal ganglia, $0.99{\pm}0.37$, mean contrast media stay time in cortex was $9.83{\pm}1.63$ sec and in basal gaiglia, $9.42{\pm}1.14$ sec, but there was no statistically significant difference between two areas ($\rho$=0.05). Conclusion : In cerebral cortex and basal ganglia, there is no difference in mean focal blood volume and mean contrast stay time. Therefore, PWI is useful in cerebral blood flow and early diagnosis, prognosis of cerebral ischemic disease. Hereafter, it is helpful in analysing cerebral blood flow changes with comparison difference in rCBV between normal tissue and ischemic tissue, and that with DWI finding in infarcted patient.