• KOREAN JOURNAL OF CROP SCIENCE
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• v.25 no.1
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• pp.77-86
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• 1980

Asking to change the cropping patterns to save the labor and capitals in paddy rice cultivation, the study was intended to know the weed problems under the various possible cultural systems; namely, direct seeding (in broadcast and row), machine transplanting and hand transplanting. Under the conditions as weedy check plots, paddy yields were significantly variated among cropping systems, and the functions of panicle No. and spikelet No. to the yield were neglected, among others. However, the yield and yield components were narrowed among cropping systems, and the function of spikelets number per area was comparatively improved to the others.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.37 no.1
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• pp.23-32
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• 2019

Taking the boards and couplets of Changdeokgung Palace's Rear Garden as the research object, there were many studies about the humanistic interpretation of landscape elements, but there is no empirical study on Chinese visitors' landscape perception. Therefore, the purpose of this study is to find out how many Chinese visitors pay attention to the boards and couplets; If they are paid attention, how much they are understood and how helpful they are; Whether there is a difference in the perception of the boards and couplets in Buyongji and Ongnyucheon region. First, 97.5% of Chinese visitors read the boards of Changdeokgung Palace's Rear Garden, which proved that most Chinese visitors are highly aware of the boards and couplets because they are familiar with Chinese characters. Second, 'Chinese visitors who understanding of the boards and couplets' was shown to be significant value(0.00 < 0.05) and the average value was 3.39 > 2.97, indicating that the boards had a higher understood than the couplets. And 'Helpful of the boards and couplets in interpreting the entire landscape' was significant value(0.00 < 0.05) and the average was 3.85 > 3.37, indicating that the boards was more helpful than the couplets. Third, the results of the difference in the perception of the boards and couplets in Buyongji and Okryucheon region were that 'the board of Buyongjeong in Buyongji region' and 'the board of Soyojeong in Ongnyucheon region' are related to the surrounding landscape. Additionally, through practical interview, survey respondents(4 person) responded that understanding of the boards and couplets is closely related to their personal interesting orientations, educational background and experience. And the importance of the narrator's role was emphasized in appreciating the landscape by survey respondents.

• Science of Emotion and Sensibility
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• v.21 no.1
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• pp.59-70
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• 2018

With the breakthrough of speech recognition technology, conversational agents have become pervasive through smartphones and smart speakers. The recognition accuracy of speech recognition technology has developed to the level of human beings, but it still shows limitations on understanding the underlying meaning or intention of words, or understanding long conversation. Accordingly, the users experience various errors when interacting with the conversational agents, which may negatively affect the user experience. In addition, in the case of smart speakers with a voice as the main interface, the lack of feedback on system and transparency was reported as the main issue when the users using. Therefore, there is a strong need for research on how users can better understand the capability of the conversational agents and mitigate negative emotions in error situations. In this study, we applied social strategies, "forewarning" and "apology", to conversational agent and investigated how these strategies affect users' perceptions of the agent in breakdown situations. For the study, we created a series of demo videos of a user interacting with a conversational agent. After watching the demo videos, the participants were asked to evaluate how they liked and trusted the agent through an online survey. A total of 104 respondents were analyzed and found to be contrary to our expectation based on the literature study. The result showed that forewarning gave a negative impression to the user, especially the reliability of the agent. Also, apology in a breakdown situation did not affect the users' perceptions. In the following in-depth interviews, participants explained that they perceived the smart speaker as a machine rather than a human-like object, and for this reason, the social strategies did not work. These results show that the social strategies should be applied according to the perceptions that user has toward agents.

• Journal of Service Research and Studies
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• v.9 no.2
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• pp.55-76
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• 2019

This study conducted empirical analyses to investigate the factors affecting the intention to use smart home services. Based on the previous relevant studies, the characteristics of smart home service were found to influence on the intention to use smart home service, and four variables(ubiquitous connectivity, reliability, context awareness, and security) concerning the service characteristics could be derived. And referring to the technology acceptance model(TAM), the updated TAM, IS success model, and the theory of reasoned action(TRA), three variables such as perceived ease of use, perceived usefulness and subjective norm were also likely to affect the intention to use smart home service, and the user innovativeness was inferred to play a role of moderating variable. In order to examine the research model and the hypotheses which could describe the relationship of the above mentioned variables, this study surveyed 447 people who were currently using or would use the smart home services, and then tested the hypotheses for 436 valid responses. The results of hypotheses testing showed that reliability, context awareness, and security have a significant effect on perceived usefulness and on perceived ease of use. However, it was found that ubiquitous connectivity significantly affected perceived usefulness but did not affect perceived ease of use. And perceived ease of use, perceived usefulness and subjective norm had significant effect on the intention to use smart home services. Also, user innovativeness as moderating variable was found to significantly influence on the magnitude of the relationship between ubiquitous connectivity and perceived usefulness and on that between reliability and perceived ease of use. This can be interpreted as the findings implying that innovative smart home-service users are likely to feel the smart home-services more useful than ordinary users when the degree of ubiquitous connectivity is higher, and are likely to perceive the use of smart home-services to be easier than ordinary ones when the degree of reliability is higher.

• Sleep Medicine and Psychophysiology
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• v.26 no.1
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• pp.23-32
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• 2019

Objectives: Insomnia is not only the most common sleep-related disorder, but also is one of the most important. Knowledge of the comorbidities of insomnia is essential for proper treatment including pharmacological and non-pharmacological methods to prevent disease chronification. This study aimed to determine sleep clinic patients' knowledge of insomnia. Methods: This study recruited 44 patients (24 males and 20 females; mean age $54.11{\pm}16.30years$) from the sleep clinic at National Center for Mental Health. All subjects were asked to complete a self-report questionnaire about their reasons for visiting a sleep clinic and about their knowledge of treatment and comorbidities of insomnia. Results: The reasons for visiting the sleep clinic were insomnia symptoms of daytime sleepiness, irregular sleeping time, nightmares, snoring, and sleep apnea, in that order. Of the responders, 72.7% had a comorbidity of insomnia, and 22.7% showed high-risk alcohol use. In addition, 70.5% of responders chose pharmacological treatment of insomnia as the first option and reported collection of information about treatment of insomnia mainly from the internet and medical staff. More than half (52.3%) of the respondents reported that they had never heard about non-pharmacological treatments of insomnia such as cognitive behavioral treatment (CBT-I) or light therapy. The response rate about comorbidities of varied, with 75% of responders reporting knowledge of the relation between insomnia and depression, but only 38.6% stating awareness of the relation between insomnia and alcohol use disorder. Of the total responders, 68.2% were worried about hypnotics for insomnia treatment, and 70% were concerned about drug dependence. Conclusion: This study showed that patients at a sleep clinic had limited knowledge about insomnia. It is necessary to develop standardized insomnia treatment guidelines and educational handbooks for those suffering from insomnia. In addition, evaluation of alcohol use disorders is essential in the initial assessment of sleep disorders.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.221-241
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• 2018

Deep learning is getting attention recently. The deep learning technique which had been applied in competitions of the International Conference on Image Recognition Technology(ILSVR) and AlphaGo is Convolution Neural Network(CNN). CNN is characterized in that the input image is divided into small sections to recognize the partial features and combine them to recognize as a whole. Deep learning technologies are expected to bring a lot of changes in our lives, but until now, its applications have been limited to image recognition and natural language processing. The use of deep learning techniques for business problems is still an early research stage. If their performance is proved, they can be applied to traditional business problems such as future marketing response prediction, fraud transaction detection, bankruptcy prediction, and so on. So, it is a very meaningful experiment to diagnose the possibility of solving business problems using deep learning technologies based on the case of online shopping companies which have big data, are relatively easy to identify customer behavior and has high utilization values. Especially, in online shopping companies, the competition environment is rapidly changing and becoming more intense. Therefore, analysis of customer behavior for maximizing profit is becoming more and more important for online shopping companies. In this study, we propose 'CNN model of Heterogeneous Information Integration' using CNN as a way to improve the predictive power of customer behavior in online shopping enterprises. In order to propose a model that optimizes the performance, which is a model that learns from the convolution neural network of the multi-layer perceptron structure by combining structured and unstructured information, this model uses 'heterogeneous information integration', 'unstructured information vector conversion', 'multi-layer perceptron design', and evaluate the performance of each architecture, and confirm the proposed model based on the results. In addition, the target variables for predicting customer behavior are defined as six binary classification problems: re-purchaser, churn, frequent shopper, frequent refund shopper, high amount shopper, high discount shopper. In order to verify the usefulness of the proposed model, we conducted experiments using actual data of domestic specific online shopping company. This experiment uses actual transactions, customers, and VOC data of specific online shopping company in Korea. Data extraction criteria are defined for 47,947 customers who registered at least one VOC in January 2011 (1 month). The customer profiles of these customers, as well as a total of 19 months of trading data from September 2010 to March 2012, and VOCs posted for a month are used. The experiment of this study is divided into two stages. In the first step, we evaluate three architectures that affect the performance of the proposed model and select optimal parameters. We evaluate the performance with the proposed model. Experimental results show that the proposed model, which combines both structured and unstructured information, is superior compared to NBC(Naïve Bayes classification), SVM(Support vector machine), and ANN(Artificial neural network). Therefore, it is significant that the use of unstructured information contributes to predict customer behavior, and that CNN can be applied to solve business problems as well as image recognition and natural language processing problems. It can be confirmed through experiments that CNN is more effective in understanding and interpreting the meaning of context in text VOC data. And it is significant that the empirical research based on the actual data of the e-commerce company can extract very meaningful information from the VOC data written in the text format directly by the customer in the prediction of the customer behavior. Finally, through various experiments, it is possible to say that the proposed model provides useful information for the future research related to the parameter selection and its performance.

• Journal of Nutrition and Health
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• v.24 no.3
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• pp.230-242
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• 1991

This research was conducted on the 10 take-out boxed-lunches commercially prepared in the department stores. chain stores. and the public railroad trains in Korea. Sampling was conducted from February 1990 to March 1990. Nutritive values and sodium contents of the 10 boxed-lunch samples are summarized as follows : 1) The average weight(percentage) of the cooked rice and the side dishes were 304.6g(49.4) and 312.4(506%), respectively. The weight of these samples were significantly heavier than that of Japanese style boxed-lunches. 2) The average number of the side dishes was 12. The average numbers of food items classified by the five food groups were 6.1 in protein food group, 0.3 in calcium food group. 6.0 in vitamin and mineral food group. 1.5 in carbohydrate food group, and 1.5 in oil and fat food group. 3) They contained on the average 840.7kcal of energy, 38.9g of protein, 22.7g of fat, 120.4g of carbohydrate. 300.8mg of calcium. 410.8mg of phosphours, 6.61 mg of iron. 219.8 R.E. of vitamin A, 0.46mg of thiamin, 0.67mg of riboflavin, 10.5mg of niacin, 27.5mg of ascorbic acid. Thus. except vitamin t the content of all the nutrients were higher than the value of 1/3 of the RDA for adults. 4) The high priced group(group 2) had more protein, calcuim. iron and niacin contents than the cheaper group(group 1). Probably, it's because the group 2 had more animal foods than the group 1. 5) The average energy content per unit price(100 won) was 37.3kcal and the average protein content per unit price(100 won) was 1.64g. Korena style boxed-lunches had higher energy and protein contents per unit price than Japanese style, and the group 1 higher than the group 2. 6) The average energy Proportions of Protein, carbohydrate. and fat were 18.3%, 57.4%, and 24.3%, respectively. These proportions are good enough. 7) Frequency of cooking methods for the side dishes were found in the decreasing order : pan-frying, frying, braising, seasoning, kimchi, grilling, pickling, stir-frying, steaming and fermenting. Generally simple cooking methods were used, thus the menus were lack or varieties. 8) Frequency of colors for the side dishes were found in the decreasing order : red, brown. yellow, green, black, white. Too much red pepper was used. 9) The average capacity of the containers for the staples and the side dishes were 468.1ml and 590.6ml, respectively. And the containers could not keep the food items well seperated. 10) The average contensts of sodium and salt were 2.287mg and 5.76g, in the range of 1, 398mg to 3, 489mg and 3.53g to 8.80g, respectively. These are much higher values than the recommended amount of salt.