• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.21 no.2
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• pp.112-122
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• 1985

The purpose of this paper is to study the characteristics and vertical development of the sea breeze over Sacheon area which is located at Sacheon Bay, southern coastal area of Korean Peninsula. Also, the characteristics of the sea breeze over Sacheon area are compared with those over Kimhae and Pusan area. The results were as follows: the occurrence frequencies, 98.1 days for a year of the study area, are higher than those of Kimhae (56.8 days) and Pusan area (65.8 days). March shows the highest occurrence frequency (12.3%), and July shows the lowest (3.3%). The mean onset time of the sea-breeze over Sacheon area (13:24) is, except for summer season, earlier than that over Kimhae area (13:54) and the mean subsided time of the sea-breeze over Sacheon area (19:18) is earlier than that over Kimhae area (20:18). The mean duration (5.9 hrs.) of sea-breeze is, except for winter season, shorter than that over Kimhae area (6.5 hrs.). The mean speed of the sea-breeze over Sacheon area (5.8 kts) is, except for winter season, lower than that over Kimhae area (6.8kts). April shows the maximum speed (7.7kts), and December shows the minimum (4.8kts). When the sea-breeze has occurred, the depth of the sea-breeze grows higher and higher, and when subsided, it becomes lower and lower, and sometimes after is passed 21:00 (L. S. T.) there exists the sea-breeze above 1000 feet in altitude.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.4
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• pp.926-932
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• 2004

This study deals with the statistical analyses on the relationship between the red tide formation and the meteorological factors in the Korean coastal waters. From 1995 to 2002, the red tide was observed every year and the number of occurrences increased as well. The red tide mostly occurred in July, August, September and October. from multiple linear regression, the meteorological factors governing the mechanisms of the increase in the number of red tide occurrences are found to be a water temperature, rainfall, sunshine duration and wind velocity. But water temperature as the limited factor controlling the growth of phytoplankton (Cochlodinium polykrikoids) in 15∼$30^{\circ}c$. NO ＝ 8.089 - 0.319WT + 0.019RF + 0.141SD + 0.l19WV (R ＝ 0.897) in August NO = 7.531 - 0.327WT + 0.027RF + 0.208SD + 0.208WV (R ＝ 0.894) in September Here, NO is the number of occurrence for red tide, WT is water temperature, RF is rainfall, SD is sunshine duration and WV is wind velocity, respectively. The necessary times till the day of red tide occurrence verse the day when water temperature reaches $15^{\circ}c$ are 78∼104 days, then it should be divided the coastal waters into 4 areas by the comparison among the accumulated sunshine duration, water temperature and rainfall as follows； the South West Coast (SW), South Middle Coast (SM), South East Coast(SE) and East South Coast (ES). The coastal areas that red tide occurs were complicated and various by change of marine environments. Usually red tide with a high concentrations (individual number, cells/ml) appeared in SM and SE. It was found that the general situations for the frequencies of red tide formation are mainly concentrated to 24.5∼$25^{\circ}c$ (high water temperature) and eve. 1000 cells/ml (high individual number) such as the category of red tide warning.

• Ecology and Resilient Infrastructure
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• v.7 no.4
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• pp.374-387
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• 2020

This study was conducted to provide basic data for monitoring the trend of ecosystem change and establishing management plans for wetland protection areas by understanding the status of naturalized plants. In 21 wetland protection areas, 129 taxa, including 10 invasive alien species, were recorded. The naturalized plants appeared mostly as 71 taxa in the Chimsil wetland and were not observed in the Moojechineup and Sumeunmulbaengdui wetlands. Among the naturalized plants, 42 taxa (32.6%) originated from North America. Annual and biennial plants accounted for 68.2% (88 taxa). The frequencies of occurrence of naturalized plants growing in dry secondary grasses such as Erigeron annuus and Trifolium repens were high, and clonal plants that propagated by making stolons and struck roots accounted for 19.4% (25 taxa). The naturalized and urbanization indices showed positive correlations with location factors such as wetland, agricultural land, and used area. However, a negative correlation was found between altitude and forest. Therefore, a management plan that synthetically considers the occurrence frequency and growth characteristics of naturalized plants as well as the locational characteristics of wetland protection areas is required.

• Journal of Ecology and Environment
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• v.45 no.4
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• pp.203-217
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• 2021

Background: Sea turtles, which are globally endangered species, have been stranded and found as bycatch on the Korean shore recently. More studies on sea turtles in Korea are necessary to aid their conservation. To investigate the spatio-temporal occurrence patterns of sea turtles on the Korean shore, we recorded sampling locations and dates, identified species and sexes and measured sizes (maximum curved carapace length; CCL) of collected sea turtles from the year 2014 to 2020. For an analysis of diets through stomach contents, we identified the morphology of the remaining food and extracted DNA, followed by amplification, cloning, and sequencing. Results: A total of 62 stranded or bycaught sea turtle samples were collected from the Korean shores during the study period. There were 36 loggerhead turtles, which were the dominant species, followed by 19 green turtles, three hawksbill turtles, two olive ridley turtles, and two leatherback turtles. The highest numbers were collected in the year 2017 and during summer among the seasons. In terms of locations, most sea turtles were collected from the East Sea, especially from Pohang. Comparing the sizes of collected sea turtles according to species, the average CCL of loggerhead turtles was 79.8 cm, of green turtles was 73.5 cm, and of the relatively large leatherback turtle species was 126.2 cm. In most species, the proportion of females was higher than that of males and juveniles, and was more than 70% across all the species. Food remains were morphologically identified from 19 stomachs, mainly at class level. Seaweeds were abundant in stomachs of green turtles, and Bivalvia was the most detected food item in loggerhead turtles. Based on DNA analysis, food items from a total of 26 stomachs were identified to the species or genus level. The gulfweed, Sargassum thunbergii, and the kelp species, Saccharina japonica, were frequently detected from the stomachs of green turtles and the jellyfish, Cyanea nozakii, the swimming crab, Portunus trituberculatus, and kelps had high frequencies of occurrences in loggerhead turtles. Conclusions: Our findings support those of previous studies suggesting that sea turtles are steadily appearing in the Korean sea. In addition, we verified that fish and seaweed, which inhabit the Korean sea, are frequently detected in the stomach of sea turtles. Accordingly, there is a possibility that sea turtles use the Korean sea as feeding grounds and habitats. These results can serve as basic data for the conservation of globally endangered sea turtles.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.2
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• pp.85-101
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• 2013

In order to search for distribution characteristics on C4 plants at the paddy fields, uplands, orchard and roadside in South Korea, vascular plants were investigated. Flora investigation had been carried out from May 2002 to October 2006 at 241 plots. In the results of survey, the flora of these areas consist of 74 families, 231 genera and 352 species totally. The class frequencies were arranged by the order of Magnoliopsidae (255 species), Monocotyledoneae (89 species), Pteropsida (7 species) and Sphenopsida (1 species). The number of species in each investigated agricultural field types was 55 families with 203 species in paddy field, 49 families with 218 species in uplands, 44 families with 115 species in orchard and 48 families with 202 species in roadside respectiviely. Representative species compositions of these four agricultural field types were characterized by Artemisia princeps, Persicaria thunbergii in paddy field, Artemisia princeps, Erigeron annuus in upland and roadside, Commelina communis, Digitaria ciliaris in orchard, respectively. Therefore, indicative species in agricultural ecosystem was Artemisia princeps. Among the investigated 352 species, $C_4$ plants identified were 38 species, and the occurrence ratio of $C_4$ monocotyledonous plants were higher in paddy field, orchard and roadside than upland. Such differences in the occurrence ratio of $C_4$ plants under diverse agricultural field types reflect differences in environmental condition such as micro-climate, soil moisture under various agricultural fields. Dominant $C_4$ monocotyledonous plants were Digitaria ciliaris and Commelina communis, while $C_4$ dicotyledonous plants were Amaranthus mangostanus and Chenopodium album var. centrorubrum in agricultural fields. Naturalized plants were identified as 47 species and occurrence ratio were higher in upland and roadside than other agricultural field types. Among the investigated naturalized plants, $C_4$ plants were Amaranthus mangostanus and Amaranthus retroflexus. Distribution characteristics of representative $C_4$ plants in agricultural field types, revealed that the projected increase in temperature due to climate change may provide better conditions for the growth of $C_4$ plants. Thus, the necessity of long-term monitoring should be conducted on the diffusion of $C_4$ plants that may threaten influence agroecosystem in Korea.

• Asia pacific journal of information systems
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• v.18 no.2
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• pp.95-114
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• 2008

Recent interests in data mining result from the expansion of the amount of business data and the growing business needs for extracting valuable knowledge from the data and then utilizing it for decision making process. In particular, recent advances in association rule mining techniques enable us to acquire knowledge concerning sales patterns among individual items from the voluminous transactional data. Certainly, one of the major purposes of association rule mining is to utilize acquired knowledge in providing marketing strategies such as cross-selling, sales promotion, and shelf-space allocation. In spite of the potential applicability of association rule mining, unfortunately, it is not often the case that the marketing mix acquired from data mining leads to the realized profit. The main difficulty of mining-based profit realization can be found in the fact that tremendous numbers of patterns are discovered by the association rule mining. Due to the many patterns, data mining experts should perform additional mining of the results of initial mining in order to extract only actionable and profitable knowledge, which exhausts much time and costs. In the literature, a number of interestingness measures have been devised for estimating discovered patterns. Most of the measures can be directly calculated from what is known as a contingency table, which summarizes the sales frequencies of exclusive items or itemsets. A contingency table can provide brief insights into the relationship between two or more itemsets of concern. However, it is important to note that some useful information concerning sales transactions may be lost when a contingency table is constructed. For instance, information regarding the size of each market basket(i.e., the number of items in each transaction) cannot be described in a contingency table. It is natural that a larger basket has a tendency to consist of more sales patterns. Therefore, if two itemsets are sold together in a very large basket, it can be expected that the basket contains two or more patterns and that the two itemsets belong to mutually different patterns. Therefore, we should classify frequent itemset into two categories, inter-pattern co-occurrence and intra-pattern co-occurrence, and investigate the effect of the market basket size on the two categories. This notion implies that any interestingness measures for association rules should consider not only the total frequency of target itemsets but also the size of each basket. There have been many attempts on analyzing various interestingness measures in the literature. Most of them have conducted qualitative comparison among various measures. The studies proposed desirable properties of interestingness measures and then surveyed how many properties are obeyed by each measure. However, relatively few attentions have been made on evaluating how well the patterns discovered by each measure are regarded to be valuable in the real world. In this paper, attempts are made to propose two notions regarding association rule measures. First, a quantitative criterion for estimating accuracy of association rule measures is presented. According to this criterion, a measure can be considered to be accurate if it assigns high scores to meaningful patterns that actually exist and low scores to arbitrary patterns that co-occur by coincidence. Next, complementary measures are presented to improve the accuracy of traditional association rule measures. By adopting the factor of market basket size, the devised measures attempt to discriminate the co-occurrence of itemsets in a small basket from another co-occurrence in a large basket. Intensive computer simulations under various workloads were performed in order to analyze the accuracy of various interestingness measures including traditional measures and the proposed measures.

• Food Science of Animal Resources
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• v.36 no.3
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• pp.352-358
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• 2016

The aim of this study was to determine the prevalence of enterococci in cheese samples and to characterize their antimicrobial resistance profiles as well as the associated resistance genes. A total of 139 enterococci were isolated from 99 cheese samples, the isolates were identified as E. faecalis (61.2%), E. faecium (15.1%), E. gallinarum (12.9%), E. durans (5.0%), E. casseliflavis (2.9%) and E. avium (2.9%). The most frequent antimicrobial resistance observed in enterococci isolates was to lincomycin (88.5%), followed by kanamycin (84.2%), gentamycin (low level, 51.1%), rifampin (46.8%) and tetracycline (33.8%). Among the isolates, the frequencies of high level gentamycin and streptomycin resistant enterococci strains were 2.2% and 5.8%, respectively. Apart from the mentioned antibiotics, low levels of resistance to ciprofloxacin, erythromycin and chloramphenicol were found. Moreover no resistance was observed against penicillin and ampicillin. The antimicrobial resistance genes including tetM, tetL, ermB, cat, aph(3’)-IIIa, ant(6)-Ia and aac(6’)-Ieaph(2”)-Ia were found in enterococci from Turkish cheese samples. In the current study, we provided data for antibiotic resistance and the occurrence of resistance genes among enterococci. Regulatory and quality control programs for milk and other dairy products from farms to retail outlets has to be established and strengthened to monitor trends in antimicrobial resistance among emerging food borne pathogens in Turkey.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.1
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• pp.84.2-84.2
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• 2015

There are probabilistic forecast models for solar flare occurrence, which can be evaluated by various skill scores (e.g. accuracy, critical success index, heidek skill score, true skill score). Since these skill scores assume that two types of forecast errors (i.e. false alarm and miss) are equal or constant, which does not take into account different situations of users, they may be unrealistic. In this study, we make an evaluation of a probabilistic flare forecast model (Lee et al. 2012) which use sunspot groups and its area changes as a proxy of flux emergence. We calculate daily solar flare probabilities from 1996 to 2014 using this model. Overall frequencies are 61.08% (C), 22.83% (M), and 5.44% (X). The maximum probabilities computed by the model are 99.9% (C), 89.39% (M), and 25.45% (X), respectively. The skill scores are computed through contingency tables as a function of forecast probability, which corresponds to the maximum skill score depending on flare class and type of a skill score. For the critical success index widely used, the probability threshold values for contingency tables are 25% (C), 20% (M), and 4% (X). We use a value score with cost/loss ratio, relative importance between the two types of forecast errors. We find that the forecast model has an effective range of cost/loss ratio for each class flare: 0.15-0.83(C), 0.11-0.51(M), and 0.04-0.17(X), also depending on a lifetime of satellite. We expect that this study would provide a guideline to determine the probability threshold for space weather forecast.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.6
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• pp.3865-3869
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• 2013

Background: Cigarette per day (CPD) use is a key smoking behaviour indicator. It reflects smoking intensity which is directly proportional to the occurrence of tobacco induced cancers. Self reported CPD assessment in surveys may suffer from digit bias and under reporting. Estimates from such surveys could influence the policy decision for tobacco control efforts. In this context, this study aimed at identifying underlying factors of digit bias and its implications for Global Adult Tobacco Surveillance. Materials or Methods: Daily manufactured cigarette users CPD frequencies from Global Adult Tobacco Survey (GATS) - India data were analyzed. Adapted Whipple Index was estimated to assess digit bias and data quality of reported CPD frequency. Digit bias was quantified by considering reporting of '0' or '5' as the terminal digits in the CPD frequency. The factors influencing it were identified by bivariate and logistic regression analysis. Results: The mean and mode of CPD frequency was 6.7 and 10 respectively. Around 14.5%, 15.1% and 15.2% of daily smokers had reported their CPD frequency as 2, 5 and 10 respectively. Modified Whipple index was estimated to be 226.3 indicating poor data quality. Digit bias was observed in 38% of the daily smokers. Heavy smoking, urban residence, North, South, North- East region of India, less than primary, secondary or higher educated and fourth asset index quintile group were significantly associated with digit bias. Discussion: The present study highlighted poor quality of CPD frequency data in the GATS-India survey and need for its improvement. Modeling of digit preference and smoothing of the CPD frequency data is required to improve quality of data. Marketing of 10 cigarette sticks per pack may influence CPD frequency reporting, but this needs further examination. Exploring alternative methods to reduce digit bias in cross sectional surveys should be given priority.

• Journal of Korean Society of Disaster and Security
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• v.9 no.2
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• pp.15-21
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• 2016

According to the disaster statistics issued by the Ministry of Public Safety and Security, traffic accidents, fire, collapses and others are classified into twenty-three (23) categories. In the past, disasters were mainly caused by the influence of nature, such as typhoon or drought. On the other hand, as society has become city-centered, social disasters' types, frequencies and scales are becoming more diversified and ever-increasing. However, there are no specific criteria and assessment methods that can measure degrees of social disasters-related risks objectively. Therefore, this study targeted traffic accidents, fire and collapses from major social disasters, utilized data that are related to occurrence rate, scale of casualties and scale of property loss in past eight years, and calculated the disaster risk index using the distance (Euclidean distance) between two points on the 3D spatial coordinates, in order to make the objective assessment by social disaster type possible. These results will enable the objective evaluation of risk index of major social disaster to be used as the foundational data when building the national disaster management system.