• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.2
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• pp.13-27
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• 2019

This study shows the changes in the space created by the planning and leisure activities of Hangang River Park, focusing on the Yeouido portion of the Hangang River Park, which has the most users and the greatest degree of planning. The relationship between planning, behavior, and space changes are explained based on Giddens's Structural Theory. As research material, Hangang River Park plans and satellite photos were interpreted and newspaper articles were used to identifying the space changes and their causes, and a model of the space changes was derived through the application of the theory. The flow of space change in the Yeouido portion of the Hangang River Park due to planning and leisure activities is as follows. In the 1970s, the first sports spaces are made due to need from residents near the riverside, but huge plans for the utilization of the entire space were not realized. In the 1980s, leisure spaces were planned and developed through a comprehensive plan. Various sports spaces were built, but the environment of the spaces became a slum. In the 1990s, various leisure activities were revitalized due to the revision of the legal system, regulations on the usage of space, and space maintenance, and from the late 1990s, ecological issues arose along the Hangang River. In the 2000s, there was an overall space improvement project directed by two comprehensive plans, and cultural and ecological issues appeared in the Hangang River Park plans. However, actual leisure spaces were developed along with the promotion of large-scale activities. Regarding the structuration theory, elements of interaction, modality, and structure are the aspects of space changes in the Yeouido portion Hangang River Park. As the flow of the space change, the proportions of the comprehensive plan and the individual plans were similar. The comprehensive plan was influenced by the change of public businesses and the proliferation of large-scale activities. Individual plans were influenced by the user's activities and opinions. However, both plans were influenced by the users and suppliers. The leisure space of the Hangang River Park can be viewed as a social space, in terms of the structuring as a theory due to the user repeatedly changing the use of the space. The purpos of this study is to investigate the changes in the Hangang River Park space through planning and leisure activities. Through this study, we can understand the characteristics of the Hangang River Park in planning the leisure activity space.

• Journal of The Korean Society of Grassland and Forage Science
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• v.39 no.1
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• pp.45-52
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• 2019

This experiment was carried out to study the change of productivity and feed value in different types of hilly pasture. The pasture utilized in the experiment was placed on the experimental farm of Pyeongchang Campus of Seoul National University. Forage production type(FP; Orchardgrass 18 + Tall Fescue 12 + Timothy 5 + White clover 5 kg/ha) and Public farm type(PF: Orchardgrass 12 + Tall Fescue 18 + Timothy 5 + White clover 5 kg/ha) pasture were established in September 3, 2014 and utilized (cutting or grazing) four times every year. Growth characteristics, yield and forage quality were investigated for two years. Plant height of grasses was the highest in the $1^{st}$ cutting and legumes was in the $2^{nd}$ cutting. Dry matter (DM) content was highest at every the $1^{st}$ cut grasses significantly lower at the $2^{nd}$ harvest (p<0.05). However, there was no significant difference in the $2^{nd}$, $3^{rd}$ and $4^{th}$ harvest in 2016. In the botanical composition change, the portion of legume was gradually increased after pasture establishment and the ratio of weed and bare land was higher at $2^{nd}$ and $3^{rd}$ cutting, but it was decreased at $4^{th}$ harvest. There was no significant difference in 2016 of fresh yield between two farm types (p>0.05). The yield of dry matter showed similar trend of fresh yield and forage production type was higher than that of public farm type (p<0.05). The forage intake by livestock was 1,452 kg/ha in 2015 and 1,743 kg/ha in 2016. Pasture utilization ratio of public farm type pasture was highest in the $3^{rd}$ grazing time. Forage quality of pasture in relation to management type had not significant difference, but there was difference in harvest times. Crude protein (CP) was the lowest in the $1^{st}$ harvest and total digestible nutrient (TDN) was highest in the $1^{st}$ harvest and lowest in the $4^{th}$ harvest. Based on the above results, it is found that the establishment of pasture suitable for farm's situation is important for set up of Korean model of hilly pasture. Although the forage production type is superior on forage productivity, it is recommended that the results will be provided as basic data for management of public farm type in the future.

• Korean journal of applied entomology
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• v.57 no.4
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• pp.261-269
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• 2018

The cowpea aphid Aphis craccivora Koch (Hemiptera: Aphididae) is a polyphagous species with a worldwide distribution. We investigated the temperature effects on development periods of nymphs, and the longevity and fecundity of apterous female of A. craccivora. The study was conducted at six constant temperatures of 10.0, 15.0, 20.0, 25, 30.0, and $32.5^{\circ}C$. A. craccivora developed successfully from nymph to adult stage at all temperatures subjected. The developmental rate of A. craccivora increased as temperature increased. The lower developmental threshold (LT) and thermal constant (K) of A. craccivora nymph stage were estimated by linear regression as $5.3^{\circ}C$ and 128.4 degree-days (DD), respectively. Lower and higher threshold temperatures (TL, TH and TH-TL, respectively) were calculated by the Sharpe_Schoolfield_Ikemoto (SSI) model as $17.0^{\circ}C$, $34.6^{\circ}C$ and $17.5^{\circ}C$. Developmental completion of nymph stages was described using a three-parameter Weibull function. Life table parameters were estimated. The intrinsic rate of increase was highest at $25^{\circ}C$, while the net reproductive rate was highest at $20^{\circ}C$. Biological characteristics of A. craccivora populations from different geographic areas were discussed.

• Journal of Mushroom
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• v.17 no.3
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• pp.119-125
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• 2019

This study aims to report the results for the analysis of the growth environment by applying smart farm technology to "Chunchu No 2" farmers in order to develop an optimal growth model for precision cultivation of bottle-grown oyster mushrooms. The temperature, humidity, carbon dioxide concentration, and illumination data were collected and analyzed using an environmental sensor installed to obtain growth environment data from the oyster mushroom cultivator. Analysis of the collected temperature data revealed that the temperature at the time of granulation was $19.5^{\circ}C$ after scraping, and the mushroom was generated and maintained at about $21^{\circ}C$ until the bottle was flipped. When the fruiting body grew and approached harvest time, mushrooms were harvested while maintaining the temperature between $14^{\circ}C$ and $18^{\circ}C$. The humidity was maintained at almost 100% during the complete growth stage. Carbon dioxide concentration gradually increased until 3 days after the beginning of cultivation, and then increased rapidly to almost 5,500 ppm. From the 6th day, carbon dioxide concentration was gradually decreased through ventilation and was maintained at 1,600 ppm during harvest. Light intensity of 8 lux was irradiated up to day 6 after seeding, and growth was then continued while periodically irradiating 4 lux light. The fruiting body characteristics of "Chunchu No 2" cultivated in the farmhouse were as follows: pileus diameter of 26.5 mm and thickness of 4.9 mm, stipe thickness of 8.9 mm, and length of 68.7 mm. The fruiting body yield was 166.8 g/850 ml, and the individual weight was 12.8 g/10 units.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.221-238
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• 2019

Recently, companies and public institutions have been actively introducing chatbot services in the field of customer counseling and response. The introduction of the chatbot service not only brings labor cost savings to companies and organizations, but also enables rapid communication with customers. Advances in data analytics and artificial intelligence are driving the growth of these chatbot services. The current chatbot can understand users' questions and offer the most appropriate answers to questions through machine learning and deep learning. The advancement of chatbot core technologies such as NLP, NLU, and NLG has made it possible to understand words, understand paragraphs, understand meanings, and understand emotions. For this reason, the value of chatbots continues to rise. However, technology-oriented chatbots can be inconsistent with what users want inherently, so chatbots need to be addressed in the area of the user experience, not just in the area of technology. The Fourth Industrial Revolution represents the importance of the User Experience as well as the advancement of artificial intelligence, big data, cloud, and IoT technologies. The development of IT technology and the importance of user experience have provided people with a variety of environments and changed lifestyles. This means that experiences in interactions with people, services(products) and the environment become very important. Therefore, it is time to develop a user needs-based services(products) that can provide new experiences and values to people. This study proposes a chatbot development process based on user needs by applying the design thinking approach, a representative methodology in the field of user experience, to chatbot development. The process proposed in this study consists of four steps. The first step is 'setting up knowledge domain' to set up the chatbot's expertise. Accumulating the information corresponding to the configured domain and deriving the insight is the second step, 'Knowledge accumulation and Insight identification'. The third step is 'Opportunity Development and Prototyping'. It is going to start full-scale development at this stage. Finally, the 'User Feedback' step is to receive feedback from users on the developed prototype. This creates a "user needs-based service (product)" that meets the process's objectives. Beginning with the fact gathering through user observation, Perform the process of abstraction to derive insights and explore opportunities. Next, it is expected to develop a chatbot that meets the user's needs through the process of materializing to structure the desired information and providing the function that fits the user's mental model. In this study, we present the actual construction examples for the domestic cosmetics market to confirm the effectiveness of the proposed process. The reason why it chose the domestic cosmetics market as its case is because it shows strong characteristics of users' experiences, so it can quickly understand responses from users. This study has a theoretical implication in that it proposed a new chatbot development process by incorporating the design thinking methodology into the chatbot development process. This research is different from the existing chatbot development research in that it focuses on user experience, not technology. It also has practical implications in that companies or institutions propose realistic methods that can be applied immediately. In particular, the process proposed in this study can be accessed and utilized by anyone, since 'user needs-based chatbots' can be developed even if they are not experts. This study suggests that further studies are needed because only one field of study was conducted. In addition to the cosmetics market, additional research should be conducted in various fields in which the user experience appears, such as the smart phone and the automotive market. Through this, it will be able to be reborn as a general process necessary for 'development of chatbots centered on user experience, not technology centered'.

• Journal of the Korean Society for information Management
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• v.36 no.1
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• pp.137-168
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• 2019

This study measures and analyzes the university library user's sense of community, service quality assessment, user satisfaction and loyalty. In addition, the effect of the university library user's sense of community on university library user satisfaction and loyalty mediated by the assessment of the quality of service is investigated. On the basis of study result, to improve user satisfaction and user loyalty, the direction and implications of library development are presented. In order to achieve the purpose of the study, precedent research and literature were investigated, and the study model and hypothesis were established based on theoretical background. In order to verify the hypothesis, a total of 300 questionnaires were distributed to subject who had experience using the Central Library among undergraduate students at the C National University, and the final 282 sample was used for analysis. To analyze the differences depending on the general characteristics of the samples, It is the result of an independent sample t-test and one-way ANOVA. The results of the mediated effects analysis using the PROCESS macro-programs models 4 and 6 of Hayes for hypothesis testing are as follows. First, The university library user's sense of community (Service Benefits Perception and Satisfaction, Mutual sense of influence) effect the user satisfaction of university library mediated by service quality assessment at statistical significance. This showed that the higher the university library user's sense of community, the higher the service quality assessment, and the higher the user satisfaction level of university library. Second, The university library user's sense of community (Service Benefits Perception and Satisfaction, Mutual sense of influence) effect the user loyalty of university library mediated by service quality assessment and user satisfaction. This showed that the higher the university library user's sense of community, the higher the service quality assessment, the higher user satisfaction level of university library and the higher the user loyalty level of university library. The results of this study showed that the university library user's sense of community has a direct and indirect effect on enhancing user satisfaction and loyalty through the service quality assessment.

• Journal of Bio-Environment Control
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• v.28 no.2
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• pp.95-103
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• 2019

Temperature and relative humidity are important factors in crop cultivation and should be properly controlled for improving crop yield and quality. In order to control the environment accurately, we need to predict how the environment will change in the future. The objective of this study was to predict air temperature and relative humidity at a future time by using a multilayer perceptron (MLP). The data required to train MLP was collected every 10 min from Oct. 1, 2016 to Feb. 28, 2018 in an eight-span greenhouse ($1,032m^2$) cultivating mango (Mangifera indica cv. Irwin). The inputs for the MLP were greenhouse inside and outside environment data, and set-up and operating values of environment control devices. By using these data, the MLP was trained to predict the air temperature and relative humidity at a future time of 10 to 120 min. Considering typical four seasons in Korea, three-day data of the each season were compared as test data. The MLP was optimized with four hidden layers and 128 nodes for air temperature ($R^2=0.988$) and with four hidden layers and 64 nodes for relative humidity ($R^2=0.990$). Due to the characteristics of MLP, the accuracy decreased as the prediction time became longer. However, air temperature and relative humidity were properly predicted regardless of the environmental changes varied from season to season. For specific data such as spray irrigation, however, the numbers of trained data were too small, resulting in poor predictive accuracy. In this study, air temperature and relative humidity were appropriately predicted through optimization of MLP, but were limited to the experimental greenhouse. Therefore, it is necessary to collect more data from greenhouses at various places and modify the structure of neural network for generalization.

• Journal of Food Hygiene and Safety
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• v.34 no.2
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• pp.191-198
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• 2019

This study investigated the residual characteristics of bifenthrin and chlorothalonil in crown daisy and suggested pre-harvest residue limits (PHRLs) based on their dissipation patterns and biological half-lives. The samples for residue analysis were harvested at 0 (3 hr), 1, 3, 5, 7, 9, 11, 13, 15, 18, 22 and 26 days after treatment, and analyzed by $GC/{\mu}-ECD$ and TOF/MS. The limit of quantitation (LOQs) of bifenthrin and chlorothalonil were 0.0046 mg/kg and 0.0007 mg/kg, respectively. Recoveries ranged from $88.67{\pm}7.97%$ and $99.90{\pm}16.03%$, showing that this method is appropriate for the analysis of the pesticide residues in crown daisy. Being well within first order kinetics, the biological half-lives of the pesticide residues in crown daisy were 9.63 days for bifenthrin and 6.54 days for chlorothalonil. The PHRLs of bifenthrin and chlorothalonil were recommended as 11.70 mg/kg and 24.10 mg/kg for 26 days before harvest, respectively.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.175-197
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• 2021

Recently, with the development of deep learning technology, research on unstructured data analysis is being actively conducted, and it is showing remarkable results in various fields such as classification, summary, and generation. Among various text analysis fields, text classification is the most widely used technology in academia and industry. Text classification includes binary class classification with one label among two classes, multi-class classification with one label among several classes, and multi-label classification with multiple labels among several classes. In particular, multi-label classification requires a different training method from binary class classification and multi-class classification because of the characteristic of having multiple labels. In addition, since the number of labels to be predicted increases as the number of labels and classes increases, there is a limitation in that performance improvement is difficult due to an increase in prediction difficulty. To overcome these limitations, (i) compressing the initially given high-dimensional label space into a low-dimensional latent label space, (ii) after performing training to predict the compressed label, (iii) restoring the predicted label to the high-dimensional original label space, research on label embedding is being actively conducted. Typical label embedding techniques include Principal Label Space Transformation (PLST), Multi-Label Classification via Boolean Matrix Decomposition (MLC-BMaD), and Bayesian Multi-Label Compressed Sensing (BML-CS). However, since these techniques consider only the linear relationship between labels or compress the labels by random transformation, it is difficult to understand the non-linear relationship between labels, so there is a limitation in that it is not possible to create a latent label space sufficiently containing the information of the original label. Recently, there have been increasing attempts to improve performance by applying deep learning technology to label embedding. Label embedding using an autoencoder, a deep learning model that is effective for data compression and restoration, is representative. However, the traditional autoencoder-based label embedding has a limitation in that a large amount of information loss occurs when compressing a high-dimensional label space having a myriad of classes into a low-dimensional latent label space. This can be found in the gradient loss problem that occurs in the backpropagation process of learning. To solve this problem, skip connection was devised, and by adding the input of the layer to the output to prevent gradient loss during backpropagation, efficient learning is possible even when the layer is deep. Skip connection is mainly used for image feature extraction in convolutional neural networks, but studies using skip connection in autoencoder or label embedding process are still lacking. Therefore, in this study, we propose an autoencoder-based label embedding methodology in which skip connections are added to each of the encoder and decoder to form a low-dimensional latent label space that reflects the information of the high-dimensional label space well. In addition, the proposed methodology was applied to actual paper keywords to derive the high-dimensional keyword label space and the low-dimensional latent label space. Using this, we conducted an experiment to predict the compressed keyword vector existing in the latent label space from the paper abstract and to evaluate the multi-label classification by restoring the predicted keyword vector back to the original label space. As a result, the accuracy, precision, recall, and F1 score used as performance indicators showed far superior performance in multi-label classification based on the proposed methodology compared to traditional multi-label classification methods. This can be seen that the low-dimensional latent label space derived through the proposed methodology well reflected the information of the high-dimensional label space, which ultimately led to the improvement of the performance of the multi-label classification itself. In addition, the utility of the proposed methodology was identified by comparing the performance of the proposed methodology according to the domain characteristics and the number of dimensions of the latent label space.

• Journal of Korean Society of Forest Science
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• v.109 no.4
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• pp.477-483
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• 2020

We constructed a stand yield table for Chamaecyparis obtusa based on data from an actual forest. The previous stand yield table had a number of disadvantages because it was based on actual forest information. In the present study we used data from more than 200 sampling plots in a stand of Chamaecyparis obtusa. The analysis included theestimation, recovery and prediction of the distribution of values for diameter at breast height (DBH), and the result is a valuable process for the preparation ofstand yield tables. The DBH distribution model uses a Weibull function, and the site index (base age: 30 years), the standard for assessing forest productivity, was derived using the Chapman-Richards formula. Several estimation formulas for the preparation of the stand yield table were considered for the fitness index, and the optimal formula was chosen. The analysis shows that the site index is in the range of 10 to 18 in the Chamaecyparis obtusa stand. The estimated stand volume of each sample plot was found to have an accuracy of 62%. According to the residuals analysis, the stands showed even distribution around zero, which indicates that the results are useful in the field. Comparing the table constructed in this study to the existing stand yield table, we found that our table yielded comparatively higher values for growth. This is probably because the existing analysis data used a small amount of research data that did not properly reflect. We hope that the stand yield table of Chamaecyparis obtusa, a representative species of southern regions, will be widely used for forest management. As these forests stabilize and growth progresses, we plan to construct an additional yield table applicable to the production of developed stands.