• Journal of Mushroom
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• v.13 no.3
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• pp.212-216
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• 2015

A new commercial strain "Mongdol" of oyster mushroom was developed by hyphal anastomosis. It was improved with hybridization between monokaryotic strain derived from Pleurotus ostreatus ASI 0627 and dikaryotic strain derived from P. ostreatus ASI 2929. The optimum temperature of mycelial growth and fruiting body development were $25{\sim}30^{\circ}C$ and $12{\sim}18^{\circ}C$, respectively. When two different media including PDA (potato dextrose agar medium) and MCM (mushroom complete medium) were compared, the mycelial growth of this mushroom was faster in MCM than in PDA. Similar result was observed with the control strain P. ostreatus ASI 2504. Analysis of the genetic characteristics of the new cultivar "Mongdol" showed a different DNA profile as that of the control strain ASI 2504, when RAPD (Random Amplified Polymorphic DNA) primer URP3 and URP6 were used. Fruiting body production per bottle was about 106 g using demonstration farms. The color of pileus was blackish gray and the stipe was long. Therefore, we expect that this new strain "Mongdol" will satisfy the consumer's demand for high quality mushrooms.

• Journal of agricultural medicine and community health
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• v.15 no.2
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• pp.97-106
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• 1990

1. Background Women's health and their involvement in health care are essential to health for everyone. If they are ignorant, malnourished or over-worked, the health &-their families as well as their own health will suffer. Women's health depends on broad considerations beyond medicine. Among other things, it depends upon their work in farming. their subordination to their families, their accepted roles, and poor hygiene with poorly equipped housing and environmental sanitation. 2. Objectives and Contents a. The health status of rural women : physical and mental complaints, experience of pesticides intoxication, Farmer's syndrome, experiences of reproductive health problems. b. participation in and attitudes towards housework and farming c. accessibility of medical care d. status of maternal health : fertility, family planning practice. induced abortion, and maternal care 3. Research method A nationwide field survey, based on stratified random sampling, was conducted during July, 1986. Revised Cornell Medical index(68 out of 195 items). Kawagai's Farmers Syndrome Scale, and self-developed structured questionnaires were used to rural farming wives(n=2.028). aged between 26-55. 4. Characteristics of the respondents mean age : 40.2 marital status : 90.8% married mean no. of household : 4.9 average years of education : 4.7 yrs. average income of household : \235,000 average years of residence in rural area : 36.4 yrs average Working hours(household and farming) : 11 hrs. 23 min 5. Health Status of rural women a. The average number of physical and mental symptoms were 12.4, 4.7, and the rate of complaints were 22.1%, 38.8% each. revealing complaints of mental symptomes higher than physical ones. b. 65.4% of rural women complained of more than 4 symptoms out of 9, indicating farmer's syndrome. 11.9 % experienced pesticide overdue syndrome c. 57.6% of respondents experienced women-specific health problems. d. Age and education of respondents were the variables which affect on the level of their health 6. Utilization of medical services a. The number of symptoms and complaints of respondents were dependent on the distance to where the health-care service is given b. Drug store was the most commonly utilized due to low price and the distance to reach. while nurse practitioners were well utilized when there were nurse practitioner's office in their villages. c. Rural women were internalized their subordination to husbands and children, revealing they are positive(93%) in health-care demand for-them but negative(30%) for themselves d. 33.0% of respondents were habitual drug users, 4.5% were smokers and 32.3% were alcohol drinkers. and 86.3% experienced induced-abortion. But most of them(77.6%) knew that those had negative effects on health. 7. Maternal Health Care a. Practice rate of contraception was 48.1% : female users were 90.9% in permanent and 89.6% in temporary contraception b. Induced abortions were taken mostly at hospital(86.3%), while health centers(4.7%), midwiferies(4.3%). and others(4.5%) including drug stores were listed a few. The repeated numbers of induced abortion seemed affected on the increasing numbers of symptoms and complaints. c. The first pre-natal check-up during first trimester was 41.8%, safe delivery rate was 15.6%, post-natal check-up during two months after delivery. Rural women had no enough rest after delivery revealing average days of rest from home work and farming 8.3 and 17.2. d. 86.6% practised breast feeding, showing younger and more educated mothers depending on artificial milk 8. Recommendations a. To lessen the multiple role over burden housing and sanitary conditions should be improved, and are needed farming machiner es for women and training on the use of them b. Health education should begin at primary school including health behavior and living environment. c. Women should be encouraged to become policy-makers as well as administrators in the field of women specific health affairs. d. Women's health indicators should be developed and women's health surveillance system too.

• Journal of Mushroom
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• v.15 no.3
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• pp.129-133
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• 2017

Oyster mushroom is a type of mushroom that is commonly cultivated and consumed in Korea. P. ostreatus 'Suhan' is a preferred cultivar for many mushroom farmers because it has a dark pileus and thick stipe. However, as it is very sensitive to environmental conditions, farmers consistently demand an alternative cultivar. To develop a new cultivar, the parental strains KMCC01680 ('Suhan') and KMCC00478 ('Gosol') were selected from various collected P. ostreatus strains by cultivating genetic resources. P. ostreatus 'Heuksol' was developed by the method of Mon-Mon crossing between monokaryotic strains derived from 'Suhan' and 'Gosol'. Thirty strains of 174 crossed strains were initially selected by cultivation experiments. After bulk cultivation tests, 'Heuksol' was selected. The nuclear DNA profile of 'Heuksol' was similar to those of the parental strains, 'Suhan' and 'Gosol', when RAPD (random amplified polymorphic DNA) primers and UPF (Universal PCR Fingerprinting) 2, 3, and 4 were used. The optimum temperature for mycelial growth was $30^{\circ}C$ for 'Heuksol', but medium-high temperatures were also appropriate, especially $13-20^{\circ}C$. The fruiting body production per bottle (1,100 mL) was approximately 140.8 g. When compared to the control strain 'Suhan', the thickness of the stipe of 'Heuksol' was greater than that of 'Suhan' (13.5 mm vs 9.4 mm). The pileus diameter of 'Heuksol' was similar to that of 'Suhan' and the pileus thickness of 'Heuksol' and 'Suhan' was 19.7 mm and 21.8 mm, respectively. 'Heuksol' had more a productive stipe number than 'Suhan' and the pileus of 'Heuksol' was dark gray, even at high temperatures. Therefore, it was suggested that this new cultivar, 'Heuksol', could provide an alternative to 'Suhan' and contribute to the profit of oyster mushroom farms.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.125-141
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• 2012

These days, the malicious attacks and hacks on the networked systems are dramatically increasing, and the patterns of them are changing rapidly. Consequently, it becomes more important to appropriately handle these malicious attacks and hacks, and there exist sufficient interests and demand in effective network security systems just like intrusion detection systems. Intrusion detection systems are the network security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. Conventional intrusion detection systems have generally been designed using the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. However, they cannot handle new or unknown patterns of the network attacks, although they perform very well under the normal situation. As a result, recent studies on intrusion detection systems use artificial intelligence techniques, which can proactively respond to the unknown threats. For a long time, researchers have adopted and tested various kinds of artificial intelligence techniques such as artificial neural networks, decision trees, and support vector machines to detect intrusions on the network. However, most of them have just applied these techniques singularly, even though combining the techniques may lead to better detection. With this reason, we propose a new integrated model for intrusion detection. Our model is designed to combine prediction results of four different binary classification models-logistic regression (LOGIT), decision trees (DT), artificial neural networks (ANN), and support vector machines (SVM), which may be complementary to each other. As a tool for finding optimal combining weights, genetic algorithms (GA) are used. Our proposed model is designed to be built in two steps. At the first step, the optimal integration model whose prediction error (i.e. erroneous classification rate) is the least is generated. After that, in the second step, it explores the optimal classification threshold for determining intrusions, which minimizes the total misclassification cost. To calculate the total misclassification cost of intrusion detection system, we need to understand its asymmetric error cost scheme. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, total misclassification cost is more affected by FNE rather than FPE. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 10,000 samples from them by using random sampling method. Also, we compared the results from our model with the results from single techniques to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell R4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on GA outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that the proposed model outperformed all the other comparative models in the total misclassification cost perspective. Consequently, it is expected that our study may contribute to build cost-effective intelligent intrusion detection systems.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1031-1042
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• 2023

In this study, a deep learning model was developed to predict the yield of cabbage and radish, one of the five major supply and demand management vegetables, using satellite images of Landsat 8. To predict the yield of cabbage and radish in Gangwon-do from 2015 to 2020, satellite images from June to September, the growing period of cabbage and radish, were used. Normalized difference vegetation index, enhanced vegetation index, lead area index, and land surface temperature were employed in this study as input data for the yield model. Crop yields can be effectively predicted using satellite images because satellites collect continuous spatiotemporal data on the global environment. Based on the model developed previous study, a model designed for input data was proposed in this study. Using time series satellite images, convolutional neural network, a deep learning model, was used to predict crop yield. Landsat 8 provides images every 16 days, but it is difficult to acquire images especially in summer due to the influence of weather such as clouds. As a result, yield prediction was conducted by splitting June to July into one part and August to September into two. Yield prediction was performed using a machine learning approach and reference models , and modeling performance was compared. The model's performance and early predictability were assessed using year-by-year cross-validation and early prediction. The findings of this study could be applied as basic studies to predict the yield of field crops in Korea.

• Tuberculosis and Respiratory Diseases
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• v.44 no.3
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• pp.592-600
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• 1997

Background : The level of imposed work of breathing (WOB) is important for patient-ventilator synchrony and during weaning from mechanical ventilation. Triggering methods and the sensitivity of demand system are important determining factors of the imposed WOB. Flow triggering method is available on several modern ventilator and is believed to impose less work to a patient-triggered breath than pressure triggering method. We intended to compare the level of imposed WOB on two different methods of triggering and also at different levels of sensitivities on each triggering method (0.7 L/min vs 2.0 L/min on flow triggering ; $-1\;cmH_2O$ vs $-2cm\;H_2O$ on pressure triggering). Methods : The subjects were 12 patients ($64.8{\pm}4.2\;yrs$) on mechanical ventilation and were stable in respiratory pattern on CPAP $3\;cmH_2O$. Four different triggering sensitivities were applied at random order. For determination of imposed WOB, tracheal end pressure was measured through the monitoring lumen of Hi-Lo Jet tracheal tube (Mallincrodt, New York, USA) using pneumotachograph/pressure transducer (CP-100 pulmonary monitor, Bicore, Irvine, CA, USA). Other data of respiratory mechanics were also obtained by CP-100 pulmonary monitor. Results : The imposed WOB was decreased by 37.5% during 0.7 L/min on flow triggering compared to $-2\;cmH_2O$ on pressure triggering and also decreased by 14% during $-1\;cmH_2O$ compared to $-2\;cmH_2O$ on pressure triggering (p < 0.05 in each). The PTP(Pressure Time Product) was also decreased significantly during 0.7 L/min on flow triggering and $-1\;cmH_2O$ on pressure triggering compared to $-2\;cmH_2O$ on pressure triggering (p < 0.05 in each). The proportions of imposed WOB in total WOB were ranged from 37% to 85% and no significant changes among different methods and sensitivities. The physiologic WOB showed no significant changes among different triggering methods and sensitivities. Conclusion : To reduce the imposed WOB, flow triggering with sensitivity of 0.7 L/min would be better method than pressure triggering with sensitivity of $-2\;cm\;H_2O$.