• Korean Journal of Environmental Biology
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• v.22 no.3
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• pp.351-368
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• 2004

Following the previous experiments, a starvation experiment was conducted to determine the influence of feeding and starvation on the histological and biochemical changes, the morphormetric changes in the sectioned body and the morphometric changes in Rhynchocypris oxycephalus (Sauvage and Dabry). The influence of starvation on nutritional conditions of the histological changes of hepatocyte and intestinal epithelium as hepatosmatic index (HSI), protein, RNA and DNA concentrations of liver in R. oxycephalus was tested. Although the starved group showed higher concentrations of protein, DNA and RNA than the fed group, food deprivation resulted in a decrease in the HSI, hepatocyte nucleus size and nuclear height of the intestinal epithelium. The RNA - DNA ratio appears to be a useful index of nutritional status in R. oxycephalus and may be useful for determining if R. oxycephalus is in a period of rapid or slow growth at the time of sampling. Additionally, the data have been interpreted in detail and some biologically important relationships discussed. The effects of starvation on the morphometrical changes in sectioned body traits, condition factor, viscera index and dressing percentage were determined for evaluating nutritional conditions of R. oxycephalus. Starvation for nine weeks resulted in a decrease in most sectioned traits as well as in condition factor and viscera index (P<0.05). These findings suggest that nutritional parameters used in this study appear to be a useful index for nutritional status in this species. The data has been interpreted in detail and some important body sectioned values of interest to commercial growers discussed. A 75-day study was conducted to determine the effect of starvation on classical and truss parameters in R. oxycephalus. Truss dimensions of almost the entire head and trunk region as well as the abdomen were increased significantly through feeding or starvation (P<0.05). Truss dimensions of the caudal region generally decreased through feeding or starvation, particularly those dimensions at the hind part of the trunk. There were some significant decreases in classical dimensions of the head region during feeding, in relation to body depth characteristics in the trunk and caudal region during starvation, whereas there was only one decreasing classical dimension in the caudal region during feeding. The results of this study indicate that application of the truss network as a character set enforces classical coverage across the body form, discrimination among experimental groups thus being enhanced. Considering that the dimension of the lower part of the head and some truss and classical dimensions were least affected by feeding and starvation, these dimensions may then be useful as a taxonomical indicator to discriminate the species of Rhynchocypris sp. The value of trunk region dimensions with a large component of body depth in R. oxycephalus is most likely to be compromised by variability related to differences in feeding regimes of fish in different habitats.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.67-88
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• 2019

Webtoon is a Korean-style digital comics platform that distributes comics content produced using the characteristic elements of the Internet in a form that can be consumed online. With the recent rapid growth of the webtoon industry and the exponential increase in the supply of webtoon content, the need for effective webtoon content recommendation measures is growing. Webtoons are digital content products that combine pictorial, literary and digital elements. Therefore, webtoons stimulate consumer sentiment by making readers have fun and engaging and empathizing with the situations in which webtoons are produced. In this context, it can be expected that the sentiment that webtoons evoke to consumers will serve as an important criterion for consumers' choice of webtoons. However, there is a lack of research to improve webtoons' recommendation performance by utilizing consumer sentiment. This study is aimed at developing consumer sentiment pattern maps that can support effective recommendations of webtoon content, focusing on consumer sentiments that have not been fully discussed previously. Metadata and consumer sentiments data were collected for 200 works serviced on the Korean webtoon platform 'Naver Webtoon' to conduct this study. 488 sentiment terms were collected for 127 works, excluding those that did not meet the purpose of the analysis. Next, similar or duplicate terms were combined or abstracted in accordance with the bottom-up approach. As a result, we have built webtoons specialized sentiment-index, which are reduced to a total of 63 emotive adjectives. By performing exploratory factor analysis on the constructed sentiment-index, we have derived three important dimensions for classifying webtoon types. The exploratory factor analysis was performed through the Principal Component Analysis (PCA) using varimax factor rotation. The three dimensions were named 'Immersion', 'Touch' and 'Irritant' respectively. Based on this, K-Means clustering was performed and the entire webtoons were classified into four types. Each type was named 'Snack', 'Drama', 'Irritant', and 'Romance'. For each type of webtoon, we wrote webtoon-sentiment 2-Mode network graphs and looked at the characteristics of the sentiment pattern appearing for each type. In addition, through profiling analysis, we were able to derive meaningful strategic implications for each type of webtoon. First, The 'Snack' cluster is a collection of webtoons that are fast-paced and highly entertaining. Many consumers are interested in these webtoons, but they don't rate them well. Also, consumers mostly use simple expressions of sentiment when talking about these webtoons. Webtoons belonging to 'Snack' are expected to appeal to modern people who want to consume content easily and quickly during short travel time, such as commuting time. Secondly, webtoons belonging to 'Drama' are expected to evoke realistic and everyday sentiments rather than exaggerated and light comic ones. When consumers talk about webtoons belonging to a 'Drama' cluster in online, they are found to express a variety of sentiments. It is appropriate to establish an OSMU(One source multi-use) strategy to extend these webtoons to other content such as movies and TV series. Third, the sentiment pattern map of 'Irritant' shows the sentiments that discourage customer interest by stimulating discomfort. Webtoons that evoke these sentiments are hard to get public attention. Artists should pay attention to these sentiments that cause inconvenience to consumers in creating webtoons. Finally, Webtoons belonging to 'Romance' do not evoke a variety of consumer sentiments, but they are interpreted as touching consumers. They are expected to be consumed as 'healing content' targeted at consumers with high levels of stress or mental fatigue in their lives. The results of this study are meaningful in that it identifies the applicability of consumer sentiment in the areas of recommendation and classification of webtoons, and provides guidelines to help members of webtoons' ecosystem better understand consumers and formulate strategies.

• Journal of the Korean Institute of Landscape Architecture
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• v.39 no.1
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• pp.35-45
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• 2011

The landscape of Seoul was dynamically changed and developed with the rapid post-war economic growth. Seoul city designated a height regulation district to preserve and manage the city landscape and protect it from haphazard construction. The designation of a maximum height regulation district has obvious purpose and simple regulations which makes the implementation and management easy to apply yet the altitude restriction lacks an objective basis for its enforcement. Many studies have been done and the current uniform height regulation requires more objective and logical guidelines. This study selected the Bukhan Mountain area, a National Park designated to protect the environment, to present a new landscape height guideline to minimize environmental degradation and to harmonize the artificial and natural landscapes of the area. Document research was done to identify the regulation types(absolute height regulation, view line regulation, oblique line restriction regulation) and principles for height regulation district establishment, acknowledge the current status and issues of the Bukhan Mountain area's maximum height regulation district. Gangbuk-Gu was chosen as the site and survey was conducted on outstanding view points and view corridors of residents. From document research, an appropriate landscape height guideline was selected and applied to Gangbuk-Gu. According to the guideline, suitable heights for buildings were suggested. These were then applied to three-dimensional simulations and a final guideline was suggested.

• Asia pacific journal of information systems
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• v.19 no.4
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• pp.101-124
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• 2009

According to Wikipedia, virtual reality (VR) is defined as a technology that allows a user to interact with a computer-simulated environment. Due to a rapid growth in information technology (IT), the cost of virtual reality has been decreasing while the utility of virtual reality advertisements has dramatically increased. Nevertheless, only a few studies have investigated the effects of virtual reality advertisement on consumer behaviors. Therefore, the objective of this study is to empirically examine the effects of virtual reality advertisement. Compared to traditional online advertisements, virtual reality advertisement enables consumers to experience products realistically over the Internet by providing high media richness, interactivity, and telepresence (Suh and Lee, 2005). Advertisements with high media richness facilitate consumers' understanding of advertised products by providing them with a large amount and a high variety of information on the products. Interactivity also provides consumers with a high level of control over the computer-simulated environment in terms of their abilities to adjust the information according to their individual interests and concerns and to be active rather than passive in their engagement with the information (Pimentel and Teixera, 1994). Through high media richness and interactivity, virtual reality advertisements can generate compelling feelings of "telepresence" (Suh and Lee, 2005). Telepresence is a sense of being there in an environment by means of a communication medium (Steuer, 1992). Virtual reality advertisements enable consumers to create a perceptual illusion of being present and highly engaged in a simulated environment, while they are in reality physically present in another place (Biocca, 1997). Based on the characteristics of virtual reality advertisements, a research model has been proposed to explain consumer responses to the virtual reality advertisements. The proposed model includes two dimensions of consumer responses. One dimension is consumers' rational response, which is based on the Information Processing Theory. Based on the Information Processing Theory, product knowledge and perceived risk are selected as antecedents of intention to purchase. The other dimension is emotional response of consumers, which is based on the Attitude-Structure Theory. Based on the Attitude-Structure Theory, arousal, flow, and positive affect are selected as antecedents of intention to purchase. Because it has been criticized to have investigated only one of the two dimensions of consumer response in prior studies, our research model has been built so as to incorporate both dimensions. Based on the Attitude-Structure Theory, we hypothesized the path of consumers' emotional responses to a virtual reality advertisement: (H1) Arousal by the virtual reality advertisement increases flow; (H2) Flow increases positive affect; and (H3) Positive affect increases intension to purchase. In addition, we hypothesized the path of consumers' rational responses to the virtual reality advertisement based on the Information Processing Theory: (H4) Increased product knowledge through the virtual reality advertisement decreases perceived risk; and (H5) Perceived risk decreases intension to purchase. Based on literature of flow, we additionally hypothesized the relationship between flow and product knowledge: (H6) Flow increases product knowledge. To test the hypotheses, we conducted a free simulation experiment [Fromkin and Streufert, 1976] with 300 people. Subjects were asked to use the virtual reality advertisement of a cellular phone on the Internet and then answer questions about the variables. To check whether subjects fully experienced the virtual reality advertisement, they were asked to answer a quiz about the virtual reality advertisement itself. Responses of 26 subjects were dropped because of their incomplete answers. Responses of 274 subjects were used to test the hypotheses. It was found that all of six hypotheses are accepted. In addition, we found that consumers' emotional response has stronger impact on their intention to purchase than their rational response does. This study sheds much light into practical implications for both IS researchers and managers. First of all, while most of previous research has analyzed only one of the customers' rational and emotional responses, we theoretically incorporated and empirically examined both of the two sides. Second, we empirically showed that mediators such as arousal, flow, positive affect, product knowledge, and perceived risk play an important role between virtual reality advertisement and customer's intention to purchase. In addition, the findings of this study can provide a basis of practical strategies for managers. It was found that consumers' emotional response is stronger than their rational response. This result indicates that advertisements using virtual reality should focus on the emotional side, and that virtual reality can be served as an appropriate advertisement tool for fancy products that require their online advertisements to give an impetus to customers' emotion. Finally, even if this study examined the effects of virtual reality advertisement of cellular phone, its findings could be applied to other products that are suited for virtual experience. However, this research has some limitations. We were unable to control different kinds of consumers and different attributes of products on consumers' intention to purchase. It is, therefore, deemed important for future research to control the consumer and product types for more reliable results. In addition to the consumer and product attributes, other variables could affect consumers' intention to purchase. Thus, the future research needs to find ways t control other variables.

• Journal of The Korean Society of Grassland and Forage Science
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• v.10 no.3
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• pp.129-136
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• 1990

In the present report, two experiments were carried out with the purposes of knowing the differences of response among forage species to growing period and potassium level in culture solution, and investigating possible relation of the responses with occurence of grass tetany on grazing pasture. The results were as follows; (1) At 25 days after germination, fresh weight of top part as well as the sum of top and root parts of the forages increased rapidly. (2) Italian ryegrass was the highest in potassium (K) content but the lowest in magnesiurn(Mg) content among the three gramineous forages, while tall fescue showed the opposite result to it. And orchardgrass was intermediate of the two forage species (Experiment 1). (3) The K contents of forages generally increased, while Mg content became lower with the increase of K level in culture solution. The highest K contents of Italian ryegrass and orchardgrass were more than 3 times of the lowest values. The K contents of alfalfa and tall fescue increased in the narrower range. The decreases of Mg content of Italian ryegrass and orchardgrass were significant in the ranges of 5ppm to 25 or 50ppm KzO, while the content of the leguminous forages and tall fescue decreased up to 1000 level. (4) Fresh yield, water content and K content of the forages were significantly increased with the increase of K20 application levels up to 25 or 50ppm. (5) The K concentration of forage on a tissue water basis was higher at 50ppm than that at 5ppm $K_20$ level, especially for Italian ryegrass and orchardgrass with the value of 2.6times and 2.5times, respectively. However, the K concentration (tissue water) of leguminous forages increased gradually up to the level of lOOOppm (Experiment 2). It is suggested from the results that rapid changes of water content, Mg content and K concentration (tissue water) may occur to forage on a grazing pasture, when both growing period and K level in the soil affect the changes simultaneously. Under such conditions, plant water especially in Italian reyegrass and orchardgrass can function as toxic material to grazing ruminants.

• Journal for History of Mathematics
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• v.22 no.2
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• pp.27-52
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• 2009

This article discusses the contributions of the leader Oswald Veblen, who was the president of AMS during 1923-1924. In 2006, Korea ranked 12th in SCIE publications in mathematics, more than doubling its publications in less than 10 years, a successful model for a country with relatively short history of modern mathematical research. Now there are 192 four-year universities in Korea. Some 42 of these universities have Ph.D. granting graduate programs in mathematics and/or mathematical education in Korea. Rapid growth is observed over a broad spectrum including a phenomenal performance surge in International Mathematical Olympiad. Western mathematics was first introduced in Korea in the 17th century, but real significant mathematical contributions by Korean mathematicians in modern mathematics were not much known yet to the world. Surprisingly there is no Korean mathematician who could be found in MaC Tutor History Birthplace Map. We are at the time, to have a clear vision and leadership for the 21st century. Even with the above achievement, Korean mathematical community has had obstacles in funding. Many people thinks that mathematical research can be done without funding rather unlike other science subjects, even though they agree fundamental mathematical research is very important. We found that the experience of early American mathematical community can help us to give a vision and role model for Korean mathematical community. When we read the AMS Notice article 'The Vision, Insight, and Influence of Oswald Veblen' by Steve Batterson, it answers many of our questions on the development of American mathematics in early 20th century. We would like to share the story and analyze its meaning for the development of Korean Mathematics of 21st century.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.97-113
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• 2016

Due to the growth of internet data and the rapid development of internet technology, "big data" analysis is actively conducted to analyze enormous data for various purposes. Especially in recent years, a number of studies have been performed on the applications of text mining techniques in order to overcome the limitations of existing structured data analysis. Various studies on sentiment analysis, the part of text mining techniques, are actively studied to score opinions based on the distribution of polarity of words in documents. Usually, the sentiment analysis uses sentiment dictionary contains positivity and negativity of vocabularies. As a part of such studies, this study tries to construct sentiment dictionary which is customized to specific data domain. Using a common sentiment dictionary for sentiment analysis without considering data domain characteristic cannot reflect contextual expression only used in the specific data domain. So, we can expect using a modified sentiment dictionary customized to data domain can lead the improvement of sentiment analysis efficiency. Therefore, this study aims to suggest a way to construct customized dictionary to reflect characteristics of data domain. Especially, in this study, movie review data are divided by genre and construct genre-customized dictionaries. The performance of customized dictionary in sentiment analysis is compared with a common sentiment dictionary. In this study, IMDb data are chosen as the subject of analysis, and movie reviews are categorized by genre. Six genres in IMDb, 'action', 'animation', 'comedy', 'drama', 'horror', and 'sci-fi' are selected. Five highest ranking movies and five lowest ranking movies per genre are selected as training data set and two years' movie data from 2012 September 2012 to June 2014 are collected as test data set. Using SO-PMI (Semantic Orientation from Point-wise Mutual Information) technique, we build customized sentiment dictionary per genre and compare prediction accuracy on review rating. As a result of the analysis, the prediction using customized dictionaries improves prediction accuracy. The performance improvement is 2.82% in overall and is statistical significant. Especially, the customized dictionary on 'sci-fi' leads the highest accuracy improvement among six genres. Even though this study shows the usefulness of customized dictionaries in sentiment analysis, further studies are required to generalize the results. In this study, we only consider adjectives as additional terms in customized sentiment dictionary. Other part of text such as verb and adverb can be considered to improve sentiment analysis performance. Also, we need to apply customized sentiment dictionary to other domain such as product reviews.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.29-56
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• 2021

Recently, various types of products have been launched with the rapid growth of the e-commerce market. As a result, many users face information overload problems, which is time-consuming in the purchasing decision-making process. Therefore, the importance of a personalized recommendation service that can provide customized products and services to users is emerging. For example, global companies such as Netflix, Amazon, and Google have introduced personalized recommendation services to support users' purchasing decisions. Accordingly, the user's information search cost can reduce which can positively affect the company's sales increase. The existing personalized recommendation service research applied Collaborative Filtering (CF) technique predicts user preference mainly use quantified information. However, the recommendation performance may have decreased if only use quantitative information. To improve the problems of such existing studies, many studies using reviews to enhance recommendation performance. However, reviews contain factors that hinder purchasing decisions, such as advertising content, false comments, meaningless or irrelevant content. When providing recommendation service uses a review that includes these factors can lead to decrease recommendation performance. Therefore, we proposed a novel recommendation methodology through CNN-based review usefulness score prediction to improve these problems. The results show that the proposed methodology has better prediction performance than the recommendation method considering all existing preference ratings. In addition, the results suggest that can enhance the performance of traditional CF when the information on review usefulness reflects in the personalized recommendation service.

• 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 Intelligence and Information Systems
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• v.26 no.4
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• pp.67-86
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• 2020

Recommender Systems have been huge influence users and business more and more. Recently the importance of E-commerce has been reached rapid growth greatly in world-wide COVID-19 pandemic. Recommender system is the center of E-commerce lively. Top ranked E-commerce managers mentioned that recommender systems have a major influence on customer's purchase such as about 50% of Netflix, Amazon sales from their recommender systems. Most algorithms have been focused on improving accuracy of recommender system regardless of novelty, diversity, serendipity etc. Recommender systems with only high accuracy cannot satisfy business long-term profit because of generating sales polarization. In addition, customers do not experience enjoyment of shopping from only focusing accuracy recommender system because customer's preference is changed constantly. Therefore, recommender systems with various values need to be developed for user's high satisfaction. Reranking is the most useful methodology to realize diversity of recommender system. In this paper, diversity of recommender system is represented through constructing high similarity with users who have different preference using each user's purchased item's category algorithm. It is distinguished from past research approach which is changing the algorithm of recommender system without user's diversity preference level. We tried to discover user's diversity preference level and observed the results how the effect was different according to user's diversity preference level. In addition, graph-based recommender system was used to show diversity through user's network, not collaborative filtering. In this paper, Amazon Grocery and Gourmet Food data was used because the low-involvement product, such as habitual product, foods, low-priced goods etc., had high probability to show customer's diversity. First, a bipartite graph with users and items simultaneously is constructed to make graph-based recommender system. However, each users and items unipartite graph also need to be established to show diversity of recommender system. The weight of each unipartite graph has played crucial role changing Jaccard Distance of item's category. We can observe two important results from the user's unipartite network. First, the user's diversity preference level is observed from the network and second, dissimilar users can be discovered in the user's network. Through the research process, diversity of recommender system is presented highly with small accuracy loss and optimalization for higher accuracy is possible controlling diversity ratio. This paper has three important theoretical points. First, this research expands recommender system research for user's satisfaction with various values. Second, the graph-based recommender system is developed newly. Third, the evaluation indicator of diversity is made for diversity. In addition, recommender systems are useful for corporate profit practically and this paper has contribution on business closely. Above all, business long-term profit can be improved using recommender system with diversity and the recommender system can provide right service according to user's diversity level. Lastly, the corporate selling low-involvement products have great effect based on the results.