• KOREAN JOURNAL OF CROP SCIENCE
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• v.3
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• pp.41-48
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• 1965

This study was aimed at knowing the magnitude of year variation in rice heading dates under the different seasonal cultures, and to estimate the heading date in advance. Using six rice varieties such as Kwansan, Suwon＃82, Suwon ＃144, Norin＃17, Yukoo＃132 and Paltal, the early, ordinary and late seasonal cultures had been carried out at Paddy Crop Division, Crop Experiment Station at Suwon for the six-year period 1959 to 1964. In addition the data of the standard rice cultures at the Provincial Offices of Rural Development for the 12-year period 1953 to 1954, were analyzed for the purpose of clarifying a relationship between variation of rice heading dates and some of meteorological data related to the locations and years. The results of this study are as follows: 1. Year variation of rice heading dates was as high as 14 to 21 days in the early seasonal culture and 7 to 14 days in the ordinary seasonal culture, while as low as one to seven days in the late seasonal culture which was the lowest among three cultures. The magnitude of variation depended greatly on variety, cultural season and location. 2. It was found out that there was a close negative correlation between the accumulated average air temperature for 40 days from 31 days after seeding and number of days to heading in the early seasonal culture. Accordingly, it was considered possible to predict the rice heading date through calculation of the accumulated average air temperature for the above period and then the linear regression(Y=a+bx). On the other hand, an estimation of the heading date in the late seasonal culture requires for the further studies. In the ordinary seasonal culture, no significant correlation between the accumulated average air temperature and number of days to heading was obtained in the six-year experiments conducted at Suwon. There was a varietal difference in relationship between the accumulated average air temperature for 70 days from seeding and number of days to heading in the standard cultures at the provincial offices of rural development. Some of varieties showed a significant correlation between two factors while the others didn't show any significant correlation. However, there was no regional difference in this relationship.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.53 no.4
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• pp.347-352
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• 2008

This study was carried out to estimate the quality of Jeonbuk-originated brand rice by comparing with other domestic brand rices and imported market rices. Rice variety, "Ilmi" was a major portion of brand rices in Jeonbuk region, and in few portion, there were variety-mixed brands, Shindongjin, Kosihikari, and Hitomebore. Comparing the ratio of head rice of high-quality Jeonbukoriginated brand rice with other domestic brand rices were not significantly different. Head rice ratio and mechanical taste values were not significantly different between high-quality Jeonbuk-originated brand rice and the other domestic brand rices. The contents of protein, moisture, amylose of rice were also not significantly different between them. The quality of high-quality Jeonbuk-originated brand rice was as good as that of other domestic brand rices and had not changed it by period. The foreign rice imported from United States, Chinese (involved parboiled), Thailand and the domestic rice cultivated in Jeonbuk province were investigated. There could get difference on the major component related to palatability of rice as country in this study. Comparing with foreign rices. protein content of domestic rice (6.1%) was similar with that of United States, lower than those of Chinese and Thailand. The head rice ratio of the domestic rice was 92%, which was similar with those of Unite State and Chinese but the Chinese parboiled rice was completely cracked during processing. The setback viscosity of domestic rice related to retrogradation was lower than those of the imported rice except United States. The Ad (Adhesiveness / H(Hardness) ratio was higher in the domestic and United States rice.

• Development and Reproduction
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• v.10 no.3
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• pp.159-168
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• 2006

Rodents and many other mammals have two chemosensory systems that mediate responses to pheromones, the main and accessory olfactory system, MOS and AOS, respectively. The chemosensory neurons associated with the MOS are located in the main olfactory epithelium, while those associated with the AOS are located in the vomeronasal organ(VNO). Pheromonal odorants access the lumen of the VNO via canals in the roof of the mouth, and are largely thought to be nonvolatile. The main pheromone receptor proteins consist of two superfamilies, V1Rs and V2Rs, that are structurally distinct and unrelated to the olfactory receptors expressed in the main olfactory epithelium. These two type of receptors are seven transmembrane domain G-protein coupled proteins(V1R with $G_{{\alpha}i2}$, V2R with $G_{0\;{\alpha}}$). V2Rs are co-expressed with nonclassical MHC Ib genes(M10 and other 8 M1 family proteins). Other important molecular component of VNO neuron is a TrpC2, a cation channel protein of transient receptor potential(TRP) family and thought to have a crucial role in signal transduction. There are four types of pheromones in mammalian chemical communication - primers, signalers, modulators and releasers. Responses to these chemosignals can vary substantially within and between individuals. This variability can stem from the modulating effects of steroid hormones and/or non-steroid factors such as neurotransmitters on olfactory processing. Such modulation frequently augments or facilitates the effects that prevailing social and environmental conditions have on the reproductive axis. The best example is the pregnancy block effect(Bruce effect), caused by testosterone-dependent major urinary proteins(MUPs) in male mouse urine. Intriguingly, mouse GnRH neurons receive pheromone signals from both odor and pheromone relays in the brain and may also receive common odor signals. Though it is quite controversial, recent studies reveal a complex interplay between reproduction and other functions in which GnRH neurons appear to integrate information from multiple sources and modulate a variety of brain functions.

• Archives of design research
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• v.19 no.2 s.64
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• pp.323-332
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• 2006

Information devices such as a cellular phone, smart phone, and PDA become smaller to such an extent that people put them into their pockets without any difficulties. This drastic miniaturization causes to deteriorate the readability of text-based contents. The morphological characteristics of size and proportion are supposed to have close relationships with the pocketability and text readability of mobile information devices. This research was aimed to investigate the optimal morphological characteristics to satisfy the two usability factors together. For this purpose, we conducted an controlled experiment, which was designed to evaluate the pocketability according to $size(4000mm^2/8000mm^2)$, proportion(1:1/2:1/3:1), and weight(100g/200g) of information devices as well as participants' pose and carrying method. In the case of male participants putting the models of information device into their pockets, 2:1 morphological proportion was preferred. On the other hand, the female participants carrying the models in their hands preferred 2:1 proportion$(size:4000mm^2{\times}2mm)$ and 3:1 proportion$(size:8000mm^2{\times}20mm)$. For the device in the size of $4000mm^2$, it was found that the weight of device has an significant effect on pocketability. In consequence, 2:1 proportion is optimal to achieve better pocketability. The second experiment was about how text readability is affected by size $(2000mm^2/4000mm^2/8000mm^2)$ and proportion(1:1/2:1/3:1) of information devices as well as interlinear space of displayed text(135%/200%). From this experiment result, it was found that reading speed was increased as line length increased. Regarding the subjective assessment on reading task, 2:1 proportion was strongly preferred. Based on these results, we suggest 2:l proportion as an optimal proportion that satisfy pocketability of mobile information devices and text readability displayed on the screen together. To apply these research outputs to a practical design work efficiently, it is important to take into account the fact that the space for input devices is also required in addition to a display screen.

• Journal of Nutrition and Health
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• v.50 no.1
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• pp.74-84
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• 2017

Purpose: In this study, factors of metabolic syndrome and nutritional status were examined according to gender and occupations using the 2013 Korea National Health and Nutrition Examination Survey (KNHANES). Methods: This study was conducted on 1,750 workers (male : 892, female : 858) aged between 30 and 64, who participated in a health survey, health examination, and nutrition survey using the 6th 2013 KNHANES. Occupations were classified into white collar and blue collar workers, and nutrient intake was analyzed using a food frequency questionnaire. Analysis of complex sample design data through SPSS 19.0 was used for analysis. Results: The prevalence rate of metabolic syndrome among blue collar (35.1%) was higher than that among white collar workers (26.8%) in male subjects (p < 0.05) as well as in blue collar (24.8%) compared to white collar workers (8.9%) in female subjects (p < 0.001). Intake frequency per week, considering one portion by food category, showed significant differences in cooked rice (p < 0.05) and bakeries and confectioneries (p < 0.05) in make workers as well as stew and casserole (p < 0.01) and fruits (p < 0.05) in female workers. With regard to nutrient intake by occupation and gender, white collar workers consumed a greater amount of nutrients (not including total energy intake) compared to blue collar workers in both male and female workers. With regard to nutrient adequacy ratio (NAR) and mean adequacy ratio (MAR) according to gender and occupation, white collar workers showed higher numbers than blue collar workers in both male and female subjects. Conclusions: This study examined the prevalence rates of metabolic syndrome and nutrient intake according to gender and occupation. In both male and female subjects, blue collar workers showed higher prevalence rates compared to white collar workers, and their diet quality was worse than white collar workers' diet quality. Considering this result, customized nutrition education according to gender and occupation should be provided to workers to prevent diseases.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.4
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• pp.280-292
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• 2017

Hail is not a frequently occurring weather event, and there are even fewer reports of hail damages to forest stands. Since the 2000s, an increase in hail incidence has been documented in Europe and the United States. In Korea, severe hails occurred in Jeollanam-do province on May 31 and in Gyeongsangbuk-do province on June 1, 2017. Hail size was ranged from 0.5 to 5.0 cm in diameter in Jeollanam-do, and from 1.5 to 3.0 cm in Gyeongsangbuk-do. This study was aimed to analyze the hail damages to forests by species and topography based on damage-categorized maps created by using drones and aerial photographs, and to analyze relationships of the damages with meteorological factors. The total damaged forest area was 1,163.1ha in Jeollanam-do, and 2,942.3ha in Gyeongsangbuk-do. Among the 'severe' damaged area 326.7ha, 91% was distributed in Jeollanam-do, and concentrated in the city of Hwasun which covers 57.2% of the total 'severe' damaged area. The most heavily damaged species was Korean red pine(Pinus densiflora S. & Z.) followed by P. rigida. Most broad-leaved trees species including oaks were recovered without any dead trees found. Liliodendron tulipifera was the most severely damaged in terms of the rate of 'severe' degree individuals which are needed to be checked whether they will die or be recovered. Cause of the death of pines was considered as the combination of physical damage caused by the hail and long-lasting drought with high air temperature that occurred before and after the hail event. No pathogens and insects were found which might have affected to tree deaths. We suggested a dieback mechanism of the pine trees damaged by hail and drought.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.29-45
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• 2015

Response modeling is a well-known research issue for those who have tried to get more superior performance in the capability of predicting the customers' response for the marketing promotion. The response model for customers would reduce the marketing cost by identifying prospective customers from very large customer database and predicting the purchasing intention of the selected customers while the promotion which is derived from an undifferentiated marketing strategy results in unnecessary cost. In addition, the big data environment has accelerated developing the response model with data mining techniques such as CBR, neural networks and support vector machines. And CBR is one of the most major tools in business because it is known as simple and robust to apply to the response model. However, CBR is an attractive data mining technique for data mining applications in business even though it hasn't shown high performance compared to other machine learning techniques. Thus many studies have tried to improve CBR and utilized in business data mining with the enhanced algorithms or the support of other techniques such as genetic algorithm, decision tree and AHP (Analytic Process Hierarchy). Ahn and Kim(2008) utilized logit, neural networks, CBR to predict that which customers would purchase the items promoted by marketing department and tried to optimized the number of k for k-nearest neighbor with genetic algorithm for the purpose of improving the performance of the integrated model. Hong and Park(2009) noted that the integrated approach with CBR for logit, neural networks, and Support Vector Machine (SVM) showed more improved prediction ability for response of customers to marketing promotion than each data mining models such as logit, neural networks, and SVM. This paper presented an approach to predict customers' response of marketing promotion with Case Based Reasoning. The proposed model was developed by applying different weights to each feature. We deployed logit model with a database including the promotion and the purchasing data of bath soap. After that, the coefficients were used to give different weights of CBR. We analyzed the performance of proposed weighted CBR based model compared to neural networks and pure CBR based model empirically and found that the proposed weighted CBR based model showed more superior performance than pure CBR model. Imbalanced data is a common problem to build data mining model to classify a class with real data such as bankruptcy prediction, intrusion detection, fraud detection, churn management, and response modeling. Imbalanced data means that the number of instance in one class is remarkably small or large compared to the number of instance in other classes. The classification model such as response modeling has a lot of trouble to recognize the pattern from data through learning because the model tends to ignore a small number of classes while classifying a large number of classes correctly. To resolve the problem caused from imbalanced data distribution, sampling method is one of the most representative approach. The sampling method could be categorized to under sampling and over sampling. However, CBR is not sensitive to data distribution because it doesn't learn from data unlike machine learning algorithm. In this study, we investigated the robustness of our proposed model while changing the ratio of response customers and nonresponse customers to the promotion program because the response customers for the suggested promotion is always a small part of nonresponse customers in the real world. We simulated the proposed model 100 times to validate the robustness with different ratio of response customers to response customers under the imbalanced data distribution. Finally, we found that our proposed CBR based model showed superior performance than compared models under the imbalanced data sets. Our study is expected to improve the performance of response model for the promotion program with CBR under imbalanced data distribution in the real world.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.99-120
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• 2010

Due to the wide spread of customers' frequent access of non face-to-face services, there have been many attempts to improve customer satisfaction using huge amounts of data accumulated throughnon face-to-face channels. Usually, a call center is regarded to be one of the most representative non-faced channels. Therefore, it is important that a call center has enough agents to offer high level customer satisfaction. However, managing too many agents would increase the operational costs of a call center by increasing labor costs. Therefore, predicting and calculating the appropriate size of human resources of a call center is one of the most critical success factors of call center management. For this reason, most call centers are currently establishing a department of WFM(Work Force Management) to estimate the appropriate number of agents and to direct much effort to predict the volume of inbound calls. In real world applications, inbound call prediction is usually performed based on the intuition and experience of a domain expert. In other words, a domain expert usually predicts the volume of calls by calculating the average call of some periods and adjusting the average according tohis/her subjective estimation. However, this kind of approach has radical limitations in that the result of prediction might be strongly affected by the expert's personal experience and competence. It is often the case that a domain expert may predict inbound calls quite differently from anotherif the two experts have mutually different opinions on selecting influential variables and priorities among the variables. Moreover, it is almost impossible to logically clarify the process of expert's subjective prediction. Currently, to overcome the limitations of subjective call prediction, most call centers are adopting a WFMS(Workforce Management System) package in which expert's best practices are systemized. With WFMS, a user can predict the volume of calls by calculating the average call of each day of the week, excluding some eventful days. However, WFMS costs too much capital during the early stage of system establishment. Moreover, it is hard to reflect new information ontothe system when some factors affecting the amount of calls have been changed. In this paper, we attempt to devise a new model for predicting inbound calls that is not only based on theoretical background but also easily applicable to real world applications. Our model was mainly developed by the interactive decision tree technique, one of the most popular techniques in data mining. Therefore, we expect that our model can predict inbound calls automatically based on historical data, and it can utilize expert's domain knowledge during the process of tree construction. To analyze the accuracy of our model, we performed intensive experiments on a real case of one of the largest car insurance companies in Korea. In the case study, the prediction accuracy of the devised two models and traditional WFMS are analyzed with respect to the various error rates allowable. The experiments reveal that our data mining-based two models outperform WFMS in terms of predicting the amount of accident calls and fault calls in most experimental situations examined.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.6
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• pp.4335-4347
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• 2015

The objective of this study was to investigate $PM_{10}$ and $CO_2$ concentrations in the classrooms of 286 elementary schools in Suwon, Ansan, and Hwaseong in the province of Gyeonggi between August 2008 and December 2012. By gaining an understanding of the environmental factors that influence these concentrations, this study also aimed to establish a management plan for indoor air quality in schools, which substantially affects the health of elementary students. When the schools were classified by region, no statistically significant difference in $PM_{10}$ concentration was observed. However, $PM_{10}$ concentration was relatively high in industrial areas and low in rural areas. No difference in $CO_2$ concentration was observed among the surveyed cities. Analysis of annual $PM_{10}$ concentration showed that the highest values for Suwon and Hwaseong occurred in 2008 and 2009, respectively (p<0.01). In the case of Ansan, the highest concentration occurred during 2009, but the difference was not significant compared to the other years. Analysis of the annual $CO_2$ concentration of each city shows no significant difference among the cities (p-value=0.366,0.730,0.210). According to a time series analysis of $PM_{10}$ and $CO_2$ by season, from autumn 2008 to winter 2012, $PM_{10}$ concentration was high during 2009, then it gradually decreased until 2012, and started to increase again. While no difference in annual $CO_2$ concentration was observed, the concentration had a tendency to be higher in spring and winter than in summer. By analyzing the relationship between $PM_{10}$ and $CO_2$ and the environmental factors (years of construction, average students of classroom, temperature, and humidity), it showed a significant negative correlation was found between $CO_2$ and the environmental temperature and humidity, at -0.329 and -0.188, respectively (p<0.01).

• Research in Plant Disease
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• v.14 no.1
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• pp.51-56
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• 2008

Powdery mildew of lettuce that is a newly reported disease became a threat to organic cultivation of lettuce in Korea since the disease caused by Podosphaera fusca resulted in a half of yield loss in heavily infected fields. To improve micro-environmental conditions around lettuce, ACF (air-circulation fan) was installed on inside roof of plastic house at 6 m intervals. The ACF increased 57% of lettuce yield and reduced 71.4% of lettuce seedling death. COY (cooking oil and yolk mixture) consisted of cooking oil 0.3% and egg yolk 0.08% reduced lettuce seedling death from 89.3% to 92.9% under the greenhouse. Seven-day interval spray of COY resulted in high control values of powdery mildew of lettuce ranging from 89.6% to 96.3%, which was comparable to a fungicide, Azoxystrobin. Lettuce yield was increased about two times compared to a non-treated conventional cultivation. Qualities of lettuce such as hardness and chlorophyll content were also improved by COY and ACF combination. Effect of COY on control of the disease was improved when $CaCO_3$ or $SiO_2$ 1,000 ppm was supplemented. Results indicated that the COY made of cooking oil such as canola emulsified with yolk was highly effective on control of powdery mildew of lettuce and suitable for organic agriculture, especially when combined with ACF.