• Journal of Forest and Environmental Science
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• v.32 no.2
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• pp.149-157
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• 2016

Understanding regional characteristics in forest fire occurrence is important to establish effective forest fire prevention policy in Korea. This study analyzed the characteristics of forest fires occurred in 16 administrative districts for recent 25 years (1990~2014) to examine regional characteristics in forest fire occurrence. Forest fire occurrence reflects regional characteristics depending on climatic factors as well as region's society-cultural factors. Results showed that the first cause of forest fire occurrence was carelessness by human activities throughout all administrative districts, however, the second cause depends on regional characteristics. As the results of forest fire occurrence period analyzed for 10 days, the most forest fires occurred in the southern region during January to March, while forest fires in the northern region occurred mostly during March to April. We classified forest fire occurrence patterns into three types (centralized: Gyeonggi-do, dispersal: Busan, horizontally distributed: Gyeongsangnam-do) by multi-temporal analysis for forest fire occurrence period.

• The Plant Pathology Journal
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• v.28 no.2
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• pp.172-184
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• 2012

An infection risk model for Phytophthora blight on chili pepper was developed to estimate the first date of disease occurrence in the field. The model consisted of three parts including estimation of zoosporangium formation, soil water content, and amount of active inoculum in soil. Daily weather data on air temperature, relative humidity and rainfall, and the soil texture data of local areas were used to estimate infection risk level that was quantified as the accumulated amount of active inoculum during the prior three days. Based on the analysis on 190 sets of weather and disease data, it was found that the threshold infection risk of 224 could be an appropriate criterion for determining the primary infection date. The 95% confidence interval for the difference between the estimated date of primary infection and the observed date of first disease occurrence was $8{\pm}3$ days. In the model validation tests, the observed dates of first disease occurrence were within the 95% confidence intervals of the estimated dates in the five out of six cases. The sensitivity analyses suggested that the model was more responsive to temperature and soil texture than relative humidity, rainfall, and transplanting date. The infection risk model could be implemented in practice to control Phytophthora blight in chili pepper fields.

• Korean Journal Plant Pathology
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• v.11 no.3
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• pp.224-229
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• 1995

Occurrence and incidences of major diseases of peach (Prunus persicae pv. vulgaris), leaf curl caused by Taphrina deformans, bacterial shot hole caused by Xanthomonas campestris pv. pruni, brown rot caused by Monilinia fructicola, and anthracnose caused by Glomerella cingulata in peach orchards in Cheongdo and Kyungsan areas of Gyeongbuk province, Korea, were investigated for four years from 1990 to 1993. In leaf curl and bacterial shot hole which mainly occurred on leaves, frist disease occurrences were dated from late April to early May. The maximum leaf curl incidence was dated in mid May, while dates of the maximum bacterial shot hole incidence varied from mid May to mid August depending on the years surveyed. In brown rot and anthracnose on fruit, the first disease occurrence dates ranged from early June to early August; however, the maximum disease incidences for both were invariably dated in late August. The disease incidences on the dates of the maximum incidences differed year by year, and the averages for the 4 years were 13.2%, 10.5%, 10.9% and 3.8% for leaf curl, bacterial shot hole, brown rot and anthracnose, respectively. Especially in the leaf curl disease, the first disease occurrence dates and the maximum disease incidences matched with the amounts of precipitation of rain up to April, suggesting that the disease occurrence may be related to the precipitation during the early season. The occurrence of leaf curl was somewhat higher in cultivar“Baekmi”than other cultivars. All of the major disease occurred more in hilly orchards than in plain ones.

• Animal Systematics, Evolution and Diversity
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• v.33 no.1
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• pp.37-44
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• 2017

The present census on freshwater bryozoans in the Han River, Geum River and in lentic water bodies in Gangwon Province revealed three gymnolaemate species. Two of them-Hislopia prolixa Hirose and Mawatari, 2011 and Victorella pavida Saville Kent, 1870 were recorded for the first time from South Korea. Paludicella articulata (Ehrenberg, 1831), on the other hand, had already been documented from a few sites since 1941. The bryozoans, all belonging to the order of Ctenostomata, were found on a variety of substrates in freshwater (H. prolixa and P. articulata) and brackish habitats (V. pavida). Hislopia prolixa had recently been established as a new species and this is the first record for an occurrence outside of Japan, where it had been newly described from Lake Biwa and nearby satellite lakes.

• Korean journal of applied entomology
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• v.58 no.3
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• pp.239-249
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• 2019

This study was carried out to compare on the time of occurrence of 6 major rice insect pests [Lissorhoptrus oryzophilus Kusche, Oulema oryzae Kuwayama, Sogatella furcifera (Horvath), Nilaparvata lugens Stal., Cnaphalocrocis medinalis (Guenee), Mythimna separata Walker] in northern part of the Korean peninsula. Using growing degree days of the insects, we evaluated the number of occurrence generations and the time of occurrence. Over-wintering insects such as L. oryzophilus and O. oryzae showed different occurrence periods in northern regions. The occurrence period of the first generation adults was later in northeast regions than in Korean middle regions and more later both in northern alpines and in northern parts of east sea. In addition, the first adults of S. furcifera, N. lugens, C. medinalis, and M. separata occurred between June and early August. However, from late August to September, these insects showed the different occurrence periods in northern regions. Especially, the second adults of N. lugens were not occurred and the second to third generation adults of S. furcifera, C. medinalis, and M. separata showed similar occurrence properties. Based on these properties, the occurrence of major rice insect pests will be less in northeast regions, northern regions of east sea, northern inlands, and northern alpines of the Korean peninsula. However, comparing with their occurrences in northern regions of Gyenonggi and Gangwon provinces, the rice insect pests may show similar occurrence pattern in mid-korean mountains except for pyunggang and yangduk regions as well as in the southern and northern regions of Suyang-san.

• Korean Journal of Organic Agriculture
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• v.19 no.spc
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• pp.13-16
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• 2011

The occurrence of major pest infestation was compared between conventional tea plantation and organic tea plantation at Sulloc tea garden in Dosun-dong, Seogwipo-si, Jeju-do from 2002 to 2009. Tetranychus kanzawai was observed a lot in the second year, but it waned from late June. There was not much difference between conventional farming and organic farming in terms of pest density. Empoasca onukii was infested in the second year of organic farming compared with conventional farming, which highlighted the fact that second year of organic farming requires a special care. Scirotothrips dorsalis was highly dense in the second and third year of conventional farming, but its occurrence was lowered when the farming technique was shifted to organic farming. The number of Homona magnanima peaked 4 times each year. In 2008, the first year of organic farming, saw high occurrence of 771.2 per trap per year. In 2009, the second year, the population per trap dropped to 80, showing a great variance depending on year. The occurrence of Caloptilia theivora peaked 5 times annually. In 2008, the first year of organic farming, an average of 2,779 pests per trap was found, and in the following year, 4,143 pests were observed. It showed that density rose in organic growing period.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.24 no.5
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• pp.305-318
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• 2012

Although the existing performance-based design method for the vertical breakwater evaluates an average sliding distance during an arbitrary time, it does not calculate the probability of the first occurrence of an event exceeding an allowable sliding distance(i.e. the first-passage probability). Designers need information about the probability that the structure is damaged for the first time for not only design but also maintenance and operation of the structure. Therefore, in this study, a time-dependent reliability design method based on a stochastic process is developed to evaluate the first-passage probability of caisson sliding. Caisson sliding can be formulated by the Poisson spike process because both occurrence time and intensity of severe waves causing caisson sliding are random processes. The occurrence rate of severe waves is expressed as a function of the distribution function of sliding distance and mean occurrence rate of severe waves. These values simulated by a performance-based design method are expressed as multivariate regression functions of design variables. As a result, because the distribution function of sliding distance and the mean occurrence rate of severe waves are expressed as functions of significant wave height, caisson width, and water depth, the first-passage probability of caisson sliding can be easily evaluated.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.7
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• pp.2736-2754
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• 2015

Android dominates the mobile operating system market, which stimulates the rapid spread of mobile malware. It is quite challenging to detect mobile malware. System call sequence analysis is widely used to identify malware. However, the malware detection accuracy of existing approaches is not satisfactory since they do not consider correlation of system calls in the sequence. In this paper, we propose a new scheme called Artificial Neural Networks (ANNs) on Co-occurrence Matrices Droid (ANNCMDroid), using co-occurrence matrices to mine correlation of system calls. Our key observation is that correlation of system calls is significantly different between malware and benign software, which can be accurately expressed by co-occurrence matrices, and ANNs can effectively identify anomaly in the co-occurrence matrices. Thus at first we calculate co-occurrence matrices from the system call sequences and then convert them into vectors. Finally, these vectors are fed into ANN to detect malware. We demonstrate the effectiveness of ANNCMDroid by real experiments. Experimental results show that only 4 applications among 594 evaluated benign applications are falsely detected as malware, and only 18 applications among 614 evaluated malicious applications are not detected. As a result, ANNCMDroid achieved an F-Score of 0.981878, which is much higher than other methods.

• Korean Journal of Ecology and Environment
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• v.50 no.4
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• pp.374-380
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• 2017

Pine wilt disease (PWD) is one of the hazardous pine tree diseases in whole world. In Korea, PWD has been spreading since it was first observed in Busan in 1988. Dispersion of PWD is mainly mediated by its vectors such as Japanese pine sawyer. In this study, we characterized environmental condition including meteorological factors, geographical factors, and land use factors influencing on the occurrence of PWD. The occurrence data of PWD were collected at 153 sites where were the initial occurrence sites of PWD in local government regions such as city, Gun, or Gu scale. We used Akaike Information Criterion (AIC) to evaluate the relative importance of environmental variables on the discrimination of occurrence or absence of PWD. The results showed that altitude, slope, and distance to road were the most influential factors on the occurrence of PWD, followed by distance to building. Finally, our study presented that human activities highly influenced on the long term dispersal of PWD.

• Journal of Korea Multimedia Society
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• v.20 no.1
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• pp.43-50
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• 2017

According to living environment, the number of deaths due to thyroid diseases increased. In this paper, we proposed an algorithm for recognizing a thyroid detection using texture analysis based on shape, gray level co-occurrence matrix and gray level run length matrix. First of all, we segmented the region of interest (ROI) using active contour model algorithm. Then, we applied a total of 18 features (5 first order descriptors, 10 Gray level co-occurrence matrix features(GLCM), 2 Gray level run length matrix features and shape feature) to each thyroid region of interest. The extracted features are used as statistical analysis. Our results show that first order statistics (Skewness, Entropy, Energy, Smoothness), GLCM (Correlation, Contrast, Energy, Entropy, Difference variance, Difference Entropy, Homogeneity, Maximum Probability, Sum average, Sum entropy), GLRLM features and shape feature helped to distinguish thyroid benign and malignant. This algorithm will be helpful to diagnose of thyroid nodule on ultrasound images.