• Journal of Korean Society for Geospatial Information Science
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• v.18 no.1
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• pp.21-29
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• 2010

Nakdong Estuary Delta plays various roles of worldwide habitat for migratory birds and a sand supplier to Haewoondae Beach and Gwanganri, which are tourist attractions of Busan. In this study, long-term topographical changes of Nakdong Estuary (Jinwoo Islet, Sinja Islet, Doyodeung, Dadae Beach) coast were detected and interpreted. Through the analysis of 34 years' satellite images, it was found out that a part in between front side and back side of Jinwoo Islet increased, Sinja Islet was divided into two belts in 1970, and has formed an islet since the 1980s and extended westward. Due to the rapid development of small islets in front of Baekhabdeung since 1990s, Doyodeung formed in the late 1990s and is still growing. To make coastal map of Nakdong Estuary area, 13 images, of which the tide level was $99{\pm}13cm$, from the 112 Landsat images of the period from 1975 to 2009 were selected to section into water zone and land zone using NDV. And the rates of coastal line change such as MATLAB EPR(End Point Rate) and LRR(Linear Regression Rate) were calculated using DSAS 4.0(Digital Shoreline Analysis System). Through detecting topographical changes, EPR showed that the front(south) and back side(north) of Jinwoo Islet moved southward at -0.93~2.56m/yr, and changes in costal line and area of Jinwoo Islet were low and stable. The front and backside of Sinja Islet moved northward at 1~4m/yr, whereas the west side of Sinja Islet was stable at 2~3m/yr and east side of Sinja Islet moved northward at 10m/yr or faster. The front and back side of Doyodeung moved northward at 18~27m/yr, causing the increase of area, while the coastal line of Dadae Beach moved westward at 7m/yr, causing the expansion of the beach. LRR also demonstrated a similar trend to EPR. Although analysis of satellite images and GIS could enabled detection of topographical changes and quantitative analysis of natural phenomena, we found that continuous observation of natural phenomena and various analytical methods are required.

• Journal of Food Hygiene and Safety
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• v.32 no.4
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• pp.329-335
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• 2017

Analysis method was presented for the simultaneous determination of nine bisphenol A related compounds such as bisphenol A (BPA), phenol, p-tert-butylphenol, bisphenol A diglycidyl ether (BADGE), $BADGE{\cdot}2H_2O$, $BADGE{\cdot}2HCl$, bisphenol F diglycidyl ether (BFDGE), $BFDGE{\cdot}2H_2O$ and $BFDGE{\cdot}2HCl$ migrated from inner coatings of metal food cans by high performance liquid chromatography (HPLC) with fluorescence detection. The method was validated by examining the linearity of calibration curve, the limit of detection (LOD), the limit of quantification (LOQ), recovery and uncertainty. The migration tests of nine BPA related compounds were carried out with four food simulants; deionized water (DW), 4% acetic acid, 50% ethanol and n-heptane. There was not any compound detected in DW, 4% acetic acid and 50% ethanol at $60^{\circ}C$ for 30 min and n-heptane at $25^{\circ}C$ for 60 min. BPA and phenol were migrated into 4% acetic acid and 50% ethanol at $95^{\circ}C$ for 30 min. The concentrations were ranged from 0 to $10.77{\mu}g/L$ of BPA and from 0 to $2.35{\mu}g/L$ of phenol. Canned foodstuffs mostly have long-term shelf life. We investigated migration of nine BPA related compounds according to the variation in storage periods (0~90 days) and temperatures (4, 25 and $60^{\circ}C$). All compounds were not founded during 90 days at $4^{\circ}C$ and $25^{\circ}C$, respectively. However BPA and $BADGE{\cdot}2H_2O$ were founded in DW and 4% acetic acid at $60^{\circ}C$. The migration levels of BPA and $BADGE{\cdot}2H_2O$ were close to the value of LOQ, respectively and did not change significantly as storage period. It was founded from results that the migration of BPA related compounds from metal food cans was controlled to a safe level.

• Journal of Biomedical Engineering Research
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• v.25 no.1
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• pp.11-19
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• 2004

Stage 1 sleep provides important information regarding interpretation of nocturnal polysomnography, particularly sleep onset. It is a short transition period from wakeful consciousness to sleep. Lack of prominent sleep events characterizing stage 1 sleep is a major obstacle in automatic sleep stage scoring. In this study, we attempted to utilize simultaneous EEC and EOG processing and analyses to detect stage 1 sleep automatically. Relative powers of the alpha waves and the theta waves were calculated from spectral estimation. Either the relative power of alpha waves less than 50％ or the relative power of theta waves more than 23％ was regarded as stage 1 sleep. SEM (slow eye movement) was defined as the duration of both eye movement ranging from 1.5 to 4 seconds and regarded also as stage 1 sleep. If one of these three criteria was met, the epoch was regarded as stage 1 sleep. Results f ere compared to the manual rating results done by two polysomnography experts. Total of 169 epochs was analyzed. Agreement rate for stage 1 sleep between automatic detection and manual scoring was 79.3％ and Cohen's Kappa was 0.586 (p＜0.01). A significant portion (32％) of automatically detected stage 1 sleep included SEM. Generally, digitally-scored sleep s1aging shows the accuracy up to 70％. Considering potential difficulties in stage 1 sleep scoring, the accuracy of 79.3％ in this study seems to be robust enough. Simultaneous analysis of EOG provides differential value to the present study from previous oneswhich mainly depended on EEG analysis. The issue of close relationship between SEM and stage 1 sleep raised by Kinnariet at. remains to be a valid one in this study.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.213-225
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• 2010

Data mining has empowered the managers who are charge of the tasks in their company to present personalized and differentiated marketing programs to their customers with the rapid growth of information technology. Most studies on customer' response have focused on predicting whether they would respond or not for their marketing promotion as marketing managers have been eager to identify who would respond to their marketing promotion. So many studies utilizing data mining have tried to resolve the binary decision problems such as bankruptcy prediction, network intrusion detection, and fraud detection in credit card usages. The prediction of customer's response has been studied with similar methods mentioned above because the prediction of customer's response is a kind of dichotomous decision problem. In addition, a number of competitive data mining techniques such as neural networks, SVM(support vector machine), decision trees, logit, and genetic algorithms have been applied to the prediction of customer's response for marketing promotion. The marketing managers also have tried to classify their customers with quantitative measures such as recency, frequency, and monetary acquired from their transaction database. The measures mean that their customers came to purchase in recent or old days, how frequent in a period, and how much they spent once. Using segmented customers we proposed an approach that could enable to differentiate customers in the same rating among the segmented customers. Our approach employed support vector regression to forecast the purchase amount of customers for each customer rating. Our study used the sample that included 41,924 customers extracted from DMEF04 Data Set, who purchased at least once in the last two years. We classified customers from first rating to fifth rating based on the purchase amount after giving a marketing promotion. Here, we divided customers into first rating who has a large amount of purchase and fifth rating who are non-respondents for the promotion. Our proposed model forecasted the purchase amount of the customers in the same rating and the marketing managers could make a differentiated and personalized marketing program for each customer even though they were belong to the same rating. In addition, we proposed more efficient learning method by separating the learning samples. We employed two learning methods to compare the performance of proposed learning method with general learning method for SVRs. LMW (Learning Method using Whole data for purchasing customers) is a general learning method for forecasting the purchase amount of customers. And we proposed a method, LMS (Learning Method using Separated data for classification purchasing customers), that makes four different SVR models for each class of customers. To evaluate the performance of models, we calculated MAE (Mean Absolute Error) and MAPE (Mean Absolute Percent Error) for each model to predict the purchase amount of customers. In LMW, the overall performance was 0.670 MAPE and the best performance showed 0.327 MAPE. Generally, the performances of the proposed LMS model were analyzed as more superior compared to the performance of the LMW model. In LMS, we found that the best performance was 0.275 MAPE. The performance of LMS was higher than LMW in each class of customers. After comparing the performance of our proposed method LMS to LMW, our proposed model had more significant performance for forecasting the purchase amount of customers in each class. In addition, our approach will be useful for marketing managers when they need to customers for their promotion. Even if customers were belonging to same class, marketing managers could offer customers a differentiated and personalized marketing promotion.

• Korean journal of applied entomology
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• v.56 no.4
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• pp.377-385
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• 2017

Estimates of evolutionary sequence divergence and inference of a phylogenetic tree for eight delphacid planthopper species were based on the full-length nucleotide sequence of the internal transcribed spacer 2 (ITS2) region. Size of the ITS2 DNA sequence varied from 550 bp in Sogatella furcifera to 699 bp in Nilaparvata muiri. Nucleotide sequence distance ($d{\pm}S.E.$) was lowest between N. muiri and N. bakeri ($0.001{\pm}0.001$), and highest between Ecdelphax cervina and Stenocranus matsumurai ($0.579{\pm}0.021$). Sequence distance between N. lugens and other planthoppers ranged from $0.056{\pm}0.008$ (N. muiri) to $0.548{\pm}0.021$ (S. matsumurai). In the neighbor-joining phylogenetic tree, all planthoppers were clustered separately into a species group, except N. muiri and N. bakeri. The ITS2 nucleotide sequence of N. lugens was used to design four loop-mediated isothermal amplification (LAMP) primer sets (BPH-38, BPH-38-1, BPH-207, and BPH-92) for N. lugens species-specific detection. After the LAMP reaction of three rice planthoppers, N. lugens, S. furcifera, and Laodelphax striatellus, with the four LAMP primer sets for 60 min at $65^{\circ}C$, LAMP products were observed in the genomic DNA of N. lugens only. In the BPH-92 LAMP primer set, the fluorescence relative to that of the negative control differed according to the amount of DNA (0.1 ng, 10 ng, and 100 ng) and incubation duration (20 min, 30 min, 40 min, and 60 min). At $65^{\circ}C$ incubation, the difference was clearly observed after 40 min with 10 ng and100 ng, but with a 60-min incubation period, the minimum DNA needed was 0.1 ng. However, there was little difference in fluorescence among all DNA amounts tested with 20 or 30 min incubations.

• Parasites, Hosts and Diseases
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• v.33 no.3
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• pp.201-210
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• 1995

This study aims to assess the possible strain-dependent variations in detection of ToxopLosmn antigens and antibodies. The virulent RH strain or avirulent Beverley strain of T gondii were injected into mice, intraperitoneally, and their antigens, antibodies and parasites were identified from the blood or tissues: liver, brain and spleen by ELISA, Western blot and PCR. In mice infected with RH strain, circulating antigens and parasitemia were first detected from 2 days after infection, and ToxopIasma DNA were found in the blood, liver, brain and spleen from 3 days after infection. It was impossible to detect specific IgM and IgG antibodies to T gondij and any specific band was not found by Western blot. In mice infected with Beverley strain, circulating antigens were detected between day 10 and day 35. The Toxoplusma DNA was found in the blood and liver from day 15 until day 60, and in the brain from day 20. But Toxoplosma DNA in the spleen were mainly detected between day 10 and day 30. The IgM antibodies were first appeared on day 10 post-infection, and were noted obviously increased between day 15 and 25. The IgG antibodies were first detected on day 15, and showed progressively increased titers. The antibody binding bands were specific according to infection period. Sera from mice infected with Beverley strain reacted mainly with the antigen of 27.5-kDa and 32.5-kDa. In conclusion, mice infected with RH strain revealed Toxoplosma antigens strongly, but not antibodies. However. mice infected with Beverley strain revealed both the Toxoplasma antigens and antibodies. The present results showed that immune responses are different between avirulent and virulent T gonnii.

• Korean Journal of Remote Sensing
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• v.35 no.3
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• pp.415-431
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• 2019

The satellite-viewed cloudiness, a ratio of cloudy pixels to total pixels ($C_{sat,\;prev}$), inevitably differs from the "ground-viewed" cloudiness ($C_{grd}$) due to different viewpoints. Here we develop an algorithm to retrieve the satellite-viewed, but adjusted cloudiness to $C_{grd} (C_{sat,\;adj})$. The key process of the algorithm is to convert the cloudiness projected on the plane surface into the cloudiness on the celestial hemisphere from the observer. For this conversion, the supplementary satellite retrievals such as cloud detection and cloud top pressure are used as they provide locations of cloudy pixels and cloud base height information, respectively. The algorithm is tested for Himawari-8 level 1B data. The $C_{sat,\;adj}$ and $C_{sat,\;prev}$ are retrieved and validated with $C_{grd}$ of SYNOP station over Korea (22 stations) and China (724 stations) during only daytime for the first seven days of every month from July 2016 to June 2017. As results, the mean error of $C_{sat,\;adj}$ (0.61) is less that than that of $C_{sat,\;prev}$ (1.01). The percent of detection for 'Cloudy' scenario of $C_{sat,\;adj}$ (73%) is higher than that of $C_{sat,\;prev}$ (60%) The percent of correction, the accuracy, of $C_{sat,\;adj}$ is 61%, while that of $C_{sat,\;prev}$ is 55% for all seasons. For the December-January-February period when cloudy pixels are readily overestimated, the proportion of correction of $C_{sat,\;adj$ is 60%, while that of $C_{sat,\;prev}$ is 56%. Therefore, we conclude that the present algorithm can effectively get the satellite cloudiness near to the ground-viewed cloudiness.

• Korean Journal of Heritage: History & Science
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• v.54 no.1
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• pp.206-219
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• 2021

The warming of the climate is increasing the damage caused by termites to wooden buildings, cultural properties and houses. A group removal system can be installed around the building to detect and remove termite damage; however, if the site is not visited regularly, every one to two months, you cannot observe whether termites have spread within, and it is difficult to take prompt effective action. In addition, since the system is installed and operated in an exposed state for a long period of time, it may be ineffective or damaged, resulting in a loss of function. Furthermore if the system is installed near a cultural site, it may affect the aesthetic environment of the site. In this study, we created a detection system that uses wood, cellulose, magnets, and magnetic sensors to determine whether termites have entered the area. The data was then transferred to a low power LoRa Network which displayed the results without the necessity of visiting the site. The wood was made in the shape of a pile, and holes were made from the top to the bottom to make it easier for termites to enter and produce a cellulose sample. The cellulose sample was made in a cylindrical shape with a magnet wrapped in cellulose and inserted into the top of a hole in the wood. Then, the upper part of the wood pile was covered with a stopper to prevent foreign matter from entering. It also served to block external factors such as light and rainfall, and to create an environment where termites could add cellulose samples. When the cellulose was added by the termites, a space was created around the magnet, causing the magnet to either fall or tilt. The magnetic sensor inside the stopper was fixed on the top of the cellulose sample and measured the change in the distance between the magnet and the sensor according to the movement of the magnet. In outdoor experiments, 11 cellulose samples were inserted into the wood detection system and the termite inflow was confirmed through the movement of the magnet without visiting the site within 5 to 17 days. When making further improvements to the function and operation of the system it in the future, it is possible to confirm that termites have invaded without visiting the site. Then it is also possible to reduce damage and fruiting due to product exposure, and which would improve the condition and appearance of cultural properties.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.497-510
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• 2022

Agricultural reservoirs are essential structures for water supplies during dry period in the Korean peninsula, where water resources are temporally unequally distributed. For efficient water management, systematic and effective monitoring of medium-small reservoirs is required. Synthetic Aperture Radar (SAR) provides a way for continuous monitoring of those, with its capability of all-weather observation. This study aims to evaluate the applicability of SAR in monitoring medium-small reservoirs using Sentinel-1 (10 m resolution) and Capella X-SAR (1 m resolution), at Chari (CR), Galjeon (GJ), Dwitgol (DG) reservoirs located in Ulsan, Korea. Water detected results applying Z fuzzy function-based threshold (Z-thresh) and Chan-vese (CV), an object detection-based segmentation algorithm, are quantitatively evaluated using UAV-detected water boundary (UWB). Accuracy metrics from Z-thresh were 0.87, 0.89, 0.77 (at CR, GJ, DG, respectively) using Sentinel-1 and 0.78, 0.72, 0.81 using Capella, and improvements were observed when CV was applied (Sentinel-1: 0.94, 0.89, 0.84, Capella: 0.92, 0.89, 0.93). Boundaries of the waterbody detected from Capella agreed relatively well with UWB; however, false- and un-detections occurred from speckle noises, due to its high resolution. When masked with optical sensor-based supplementary images, improvements up to 13% were observed. More effective water resource management is expected to be possible with continuous monitoring of available water quantity, when more accurate and precise SAR-based water detection technique is developed.

• Journal of Food Hygiene and Safety
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• v.37 no.3
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• pp.159-165
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• 2022

In this study, heavy metals (lead, cadmium, and mercury) and shellfish poisoning toxins (diarrhetic shellfish poisoning toxins, amnesic shellfish poisoning toxins) were investigated in a total of 104 shellfishes. According to the analysis of heavy metals, lead (Pb) was detected in the range of 0.0177-0.5709 mg/kg, cadmium (Cd) was detected in the range of 0.0226-1.4602 mg/kg, and mercury (Hg) was detected in the range of 0.0015-0.0327 mg/kg. Levels of Pb, Cd, and Hg were acceptable by Korean standards. Okadaic acid (OA) and dinophysistoxin-1 (DTX-1) were investigated for monitoring of diarrhetic shellfish poisoning toxins and OA and DTX-1 were not detected. As a result of monitoring of amnesic shellfish poisoning toxins, domoic acid was detected in 5 of 104 samples and detection ratio was 4.8%. The detection period was found as follows; 1 case in January, 1 case in February, 1 case in May, 2 cases in September. These showed that continuous monitoring for the management of shellfish poisoning toxins and heavy metals is required. In addition, this study can be used as reference data to strengthen managing heavy metals in fishery products.