• Journal of Forest and Environmental Science
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• 제32권2호
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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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• 제28권2호
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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.

• 한국식물병리학회지
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• 제11권3호
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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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• 제33권1호
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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.

• 한국응용곤충학회지
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• 제58권3호
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• pp.239-249
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• 2019

본 연구는 북방농업지대에서 벼 해충의 지역 간 발생상황을 비교하기 위하여 곤충의 발육에 필요한 온도를 이용하여 발생 시기를 추정하는 방법으로 발생세대수나 발생 시기 등을 비교하였다. 벼 해충 6종(벼물바구미, 벼잎벌레, 흰등멸구, 벼멸구, 혹명나방, 멸강나방)에 대해 유효적산온도를 이용하여 발생 시기를 추정한 결과 월동해충은 지역에 따라 발생 시기에 차이가 있었으며, 동북방향으로 갈수록 발생시기가 늦어져, 북부고산이나 동해안북부에서는 발생시기가 가장 늦었다. 또한 해충의 발생시기가 6월부터 8월 사이에는 비래해충 1세대 성충 발생시기와 같이 지역 간 발생 시기에 차이가 적어 비슷한 시기에 발생하였으며, 기온이 낮아지는 8월부터 9월에 발생시기가 되면 지역 간 차이가 커서 벼멸구의 2세대 성충이 발생하지 못하거나, 흰등멸구, 혹명나방, 멸강나방 등의 2~3세대 성충의 발생이 안 되는 지역이 많아지고 있음을 알 수 있었다. 이러한 특징으로 보아 북방지역의 동북지역, 동해안북부, 북부내륙, 북부고산지역에서의 벼해충 발생은 적을 것으로 추정되며, 중부산간의 평강, 양덕을 제외한 동해안남부, 수양산 이남, 이북지역은 국내 경기, 강원북부지역과 비슷한 발생을 보일 것으로 추정되었다.

• 한국유기농업학회지
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• 제19권spc호
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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.

• 한국해안·해양공학회논문집
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• 제24권5호
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• pp.305-318
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• 2012

직립 케이슨 방파제에 대한 기존의 성능설계법은 임의의 시간 동안의 평균활동량을 산정하지만 허용활동량을 최초로 초과하는 사건의 발생확률(최초통과확률)은 계산하지 못한다. 설계자는 구조물이 최초로 피해를 입을 확률에 대한 정보를 구조물의 설계 단계뿐 아니라 관리 및 운영에서도 필요로 한다. 따라서 본 연구에서는 케이슨 활동의 최초통과확률을 산정하기 위해 확률과정에 기반한 시간의존 신뢰성 설계법을 개발하였다. 방파제의 활동을 일으키는 폭풍파는 발생 시간과 강도의 임의성의 특징이 있기 때문에 Poisson spike process를 사용하여 케이슨 활동을 정식화할 수 있다. 여기서 방파제의 활동을 일으키는 폭풍파의 발생률은 활동량분포함수와 폭풍파의 평균발생률로 표현된다. 성능설계법으로 모의된 이들은 설계변수들의 다변량 회귀함수로 나타내진다. 결과적으로 활동량분포함수와 폭풍파의 평균발생률은 유의파고, 케이슨 폭, 수심의 함수로 표현되어 케이슨 활동에 대한 최초통과확률을 손쉽게 산정할 수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권7호
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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.

• 생태와환경
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• 제50권4호
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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.

• 한국멀티미디어학회논문지
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• 제20권1호
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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.