• Korean Journal of Heritage: History & Science
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• v.46 no.3
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• pp.230-250
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• 2013

possessed by Dong-A University Museum is designated as Treasure No. 595, and has been known for a more exquisite, delicate and realistic expression and a colorful three-dimensional structure compared to the 'grass and insect painting' work and its value in art history. However, it has not been analyzed and studied in fabric craft despite it being an embroidered work. This study used scientific devices to examine and analyze the Screen's fabric, thread colors, and embroidery techniques to clarify its patterns and fabric craft characteristics for its value in the history of fabric craft. As a result, consists of eight sides and its subject matters and composition are similar to those of the general paintings of grass and insects. The patterns on each side of the 'grass and insect painting' include cucumber, cockscomb, day lily, balsam pear, gillyflower, watermelon, eggplant, and chrysanthemums from the first side. Among these flowers, the balsam pear is a special material not found in the existing paintings of grass and insect. The eighth side only has the chrysanthemums with no insects and reptiles, making it different from the typical forms of the paintings of grass and insect. The fabric of the Screen uses black that is not seen in other decorative embroideries to emphasize and maximize various colors of threads. The fabric used the weave structure of 5-end satin called Gong Dan [non-patterned satin]. The threads used extremely slightly twisted threads that are incidentally twisted. Some threads use one color, while other threads use two or mixed colors in combination for three-dimensional expressions. Because the threads are severely deterioration and faded, it is impossible to know the original colors, but the most frequently used colors are yellow to green and other colors remaining relatively prominently are blue, grown, and violet. The colors of day lily, gillyflower, and strawberries are currently remaining as reddish yellow, but it is anticipated that they were originally orange and red considering the existing paintings of grass and insects. The embroidery technique was mostly surface satin stitch to fill the surfaces. This shows the traditional women's wisdom to reduce the waste of color threads. Satin stitch is a relatively simple embroidery technique for decorating a surface, but it uses various color threads and divides the surfaces for combined vertical, horizontal, and diagonal stitches or for the combination of long and short stitches for various textures and the sense of volume. The bodies of insects use the combination of buttonhole stitch, outline stitch, and satin stitch for three-dimensional expressions, but the use of buttonhole stitch is particularly noticeable. In addition to that, decorative stitches were used to give volume to the leaves and surface pine needle stitches were done on the scouring rush to add more realistic texture. Decorative stitches were added on top of gillyflower, strawberries, and cucumbers for a more delicate touch. is valuable in the history of paintings and art and bears great importance in the history of Korean embroidery as it uses outstanding technique and colors of Korea to express the Shin Sa-im-dang's 'Grass and Insect Painting'.

• The Korean Journal of Nuclear Medicine Technology
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• v.23 no.1
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• pp.69-74
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• 2019

Purpose $^{18}F$-FDOPA using amino acid is particularly attractive for imaging of brain tumors because of the high uptake in tumor tissue and the low uptake in normal brain tissue. But, on the other hand, $^{18}F$-FDG is highly uptake in both tumor tissue and normal brain tissue. The purpose of study is to evaluate comparison of contrasts in $^{18}F$-FDOPA Brain PET/CT and $^{18}F$-FDG Brain PET/CT and to find out optimal scan time by analysis of variation in SUV with the passage of uptake time. Materials and Methods A region of interest of approximately $350mm^2$ at the center of the tumor and cerebellum in 12 patients ($51.4{\pm}12.8yrs$) who $^{18}F$-FDG Brain PET/CT and $^{18}F$-FDOPA Brain PET/CT were examined more than once each. The $SUV_{max}$ was measured, and the $SUV_{max}$ ratio (T/C ratio) of the tumor cerebellum was calculated. In the analysis of SUV, T/C ratio was calculated for each frame after dividing into 15 frames of 2 minutes each using List mode data in 25 patients ($49.{\pm}10.3yrs$). SPSS 21 was used to compare T/C ratio of $^{18}F$-FDOPA and T/C ratio of $^{18}F$-FDG. Results The T/C ratio of $^{18}F$-FDOPA Brain PET/CT was higher than the T/C ratio of $^{18}F$-FDG Brain, and show a significant difference according to a paired t-test(t=-5.214, p=0.000). As a result of analyzing changes in $SUV_{max}$ and T/C ratio, the peak point of $SUV_{max}$ was $5.6{\pm}2.9$ and appeared in the fourth frame (6 to 8 minutes), and the peak of T/C ratio also appeared in the fourth frame (6 to 8 minutes). Taking this into consideration and comparing the existing 10 to 30 minutes image and 6 to 26 minutes image, the $SUV_{max}$ and T/C ratio increased by 0.2 and 0.1 each, compared to the 10 to 30 minutes image for 6 to 26 minutes image. Conclusion From this study, $^{18}F$-FDOPA Brain PET/CT is effective when reading the image, because the T/C ratio of $^{18}F$-FDOPA Brain PET/CT was higher than T/C ratio of $^{18}F$-FDG Brain PET/CT. In addition, in the case of $^{18}F$-FDOPA Brain PET/CT, there was no difference between the existing 10 to 30 minutes image and 6 to 26 minutes image. Through continuous research, we can find possibility of shortening examination time in $^{18}F$-FDOPA Brain PET/CT. Also, we can help physician to accurate reading using additional scan data.

• The Korean Journal of Nuclear Medicine Technology
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• v.23 no.1
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• pp.35-39
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• 2019

Purpose Hepatitis B virus (hepatitis B virus, HBV) infection is a worldwide major public health problem and it is known as a major cause of chronic hepatitis, liver cirrhosis and liver cancer. And serologic tests of hepatitis B virus is essential for diagnosing and treating these diseases. In addition, with the development of molecular diagnostics, the detection of HBV DNA in serum diagnoses HBV infection and is recognized as an important indicator for the antiviral agent treatment response assessment. We performed HBeAg assay using Immunoradiometric assay (IRMA) and Chemiluminescent Microparticle Immunoassay (CMIA) in hepatitis B patients treated with antiviral agents. The detection rate of HBV DNA in serum was measured and compared by RT-PCR (Real Time - Polymerase Chain Reaction) method Materials and Methods HBeAg serum examination and HBV DNA quantification test were conducted on 270 hepatitis B patients undergoing anti-virus treatment after diagnosis of hepatitis B virus infection. Two serologic tests (IRMA, CMIA) with different detection principles were applied for the HBeAg serum test. Serum HBV DNA was quantitatively measured by real-time polymerase chain reaction (RT-PCR) using the Abbott m2000 System. Results The detection rate of HBeAg was 24.1% (65/270) for IRMA and 82.2% (222/270) for CMIA. Detection rate of serum HBV DNA by real-time RT-PCR is 29.3% (79/270). The measured amount of serum HBV DNA concentration is $4.8{\times}10^7{\pm}1.9{\times}10^8IU/mL$($mean{\pm}SD$). The minimum value is 16IU/mL, the maximum value is $1.0{\times}10^9IU/mL$, and the reference value for quantitative detection limit is 15IU/mL. The detection rates and concentrations of HBV DNA by group according to the results of HBeAg serological (IRMA, CMIA)tests were as follows. 1) Group I (IRMA negative, CMIA positive, N = 169), HBV DNA detection rate of 17.7% (30/169), $6.8{\times}10^5{\pm}1.9{\times}10^6IU/mL$ 2) Group II (IRMA positive, CMIA positive, N = 53), HBV DNA detection rate 62.3% (33/53), $1.1{\times}10^8{\pm}2.8{\times}10^8IU/mL$ 3) Group III (IRMA negative, CMIA negative, N = 36), HBV DNA detection rate 36.1% (13/36), $3.0{\times}10^5{\pm}1.1{\times}10^6IU/mL$ 4) Group IV(IRMA positive, CMIA negative, N = 12), HBV DNA detection rate 25% (3/12), $1.3{\times}10^3{\pm}1.1{\times}10^3IU/mL$ Conclusion HBeAg detection rate according to the serological test showed a large difference. This difference is considered for a number of reasons such as characteristics of the Ab used for assay kit and epitope, HBV of genotype. Detection rate and the concentration of the group-specific HBV DNA classified serologic results confirmed the high detection rate and the concentration in Group II (IRMA-positive, CMIA positive, N = 53).

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.161-177
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• 2019

In this paper, we study the performance improvement of the answer extraction in Question-Answering system by using sentence dependency parsing result. The Question-Answering (QA) system consists of query analysis, which is a method of analyzing the user's query, and answer extraction, which is a method to extract appropriate answers in the document. And various studies have been conducted on two methods. In order to improve the performance of answer extraction, it is necessary to accurately reflect the grammatical information of sentences. In Korean, because word order structure is free and omission of sentence components is frequent, dependency parsing is a good way to analyze Korean syntax. Therefore, in this study, we improved the performance of the answer extraction by adding the features generated by dependency parsing analysis to the inputs of the answer extraction model (Bidirectional LSTM-CRF). The process of generating the dependency graph embedding consists of the steps of generating the dependency graph from the dependency parsing result and learning the embedding of the graph. In this study, we compared the performance of the answer extraction model when inputting basic word features generated without the dependency parsing and the performance of the model when inputting the addition of the Eojeol tag feature and dependency graph embedding feature. Since dependency parsing is performed on a basic unit of an Eojeol, which is a component of sentences separated by a space, the tag information of the Eojeol can be obtained as a result of the dependency parsing. The Eojeol tag feature means the tag information of the Eojeol. The process of generating the dependency graph embedding consists of the steps of generating the dependency graph from the dependency parsing result and learning the embedding of the graph. From the dependency parsing result, a graph is generated from the Eojeol to the node, the dependency between the Eojeol to the edge, and the Eojeol tag to the node label. In this process, an undirected graph is generated or a directed graph is generated according to whether or not the dependency relation direction is considered. To obtain the embedding of the graph, we used Graph2Vec, which is a method of finding the embedding of the graph by the subgraphs constituting a graph. We can specify the maximum path length between nodes in the process of finding subgraphs of a graph. If the maximum path length between nodes is 1, graph embedding is generated only by direct dependency between Eojeol, and graph embedding is generated including indirect dependencies as the maximum path length between nodes becomes larger. In the experiment, the maximum path length between nodes is adjusted differently from 1 to 3 depending on whether direction of dependency is considered or not, and the performance of answer extraction is measured. Experimental results show that both Eojeol tag feature and dependency graph embedding feature improve the performance of answer extraction. In particular, considering the direction of the dependency relation and extracting the dependency graph generated with the maximum path length of 1 in the subgraph extraction process in Graph2Vec as the input of the model, the highest answer extraction performance was shown. As a result of these experiments, we concluded that it is better to take into account the direction of dependence and to consider only the direct connection rather than the indirect dependence between the words. The significance of this study is as follows. First, we improved the performance of answer extraction by adding features using dependency parsing results, taking into account the characteristics of Korean, which is free of word order structure and omission of sentence components. Second, we generated feature of dependency parsing result by learning - based graph embedding method without defining the pattern of dependency between Eojeol. Future research directions are as follows. In this study, the features generated as a result of the dependency parsing are applied only to the answer extraction model in order to grasp the meaning. However, in the future, if the performance is confirmed by applying the features to various natural language processing models such as sentiment analysis or name entity recognition, the validity of the features can be verified more accurately.

• Korean Journal of Heritage: History & Science
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• v.37
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• pp.371-405
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• 2004

International circulation of cultural assets involves numerous countries thereby making an approach based on international law essential to resolving this problem. Since the end of the $2^{nd}$ World War, as the value of cultural assets evolved from material value to moral and ethical values, with emphasis on establishing national identities, newly independent nations and former colonial states took issue with ownership of cultural assets which led to the need for international cooperation and statutory provisions for the return of cultural assets. UNESCO's 1954 "Convention for the Protection of Cultural Property in the Event of Armed Conflict" as preparatory measures for the protection of cultural assets, the 1970 "Convention on the Means of Prohibiting and Preventing the Illicit Import and Transfer of Ownership of Cultural Property" to regulate transfer of cultural assets, and the 1995 "Unidroit Convention on Stolen or Illegally Exported Cultural Objects" which required the return of illegally acquired cultural property are examples of international agreements established on illegal transfers of cultural assets. In addition, the UN agency UNESCO established the Division of Cultural Heritage to oversee cultural assets related matters, and the UN since its 1973 resolution 3187, has continued to demonstrate interest in protection of cultural assets. The resolution 3187 affirms the return of cultural assets to the country of origin, advises on preventing illegal transfers of works of art and cultural assets, advises cataloguing cultural assets within the respective countries and, conclusively, recommends becoming a member of UNESCO, composing a forum for international cooperation. Differences in defining cultural assets pose a limitation on international agreements. While the 1954 Convention states that cultural assets are not limited to movable property and includes immovable property, the 1970 Convention's objective of 'Prohibiting and preventing the illicit import, export and transfer of ownership of cultural property' effectively limits the subject to tangible movable cultural property. The 1995 Convention also has tangible movable cultural property as its subject. On this point, the two conventions demonstrate distinction from the 1954 Convention and the 1972 Convention that focuses on immovable cultural property and natural property. The disparity in defining cultural property is due to the object and purpose of the convention and does not reflect an inherent divergence. In the case of Korea, beginning with the 1866 French invasion, 36 years of Japanese colonial rule, military rule and period of economic development caused outflow of numerous cultural assets to foreign countries. Of course, it is neither possible nor necessary to have all of these cultural properties returned, but among those that have significant value in establishing cultural and historical identity or those that have been taken symbolically as a demonstration of occupational rule can cause issues in their return. In these cases, the 1954 Convention and the ratification of the first legislation must be actively considered. In the return of cultural property, if the illicit acquisition is the core issue, it is a simple matter of following the international accords, while if it rises to the level of diplomatic discussions, it will become a political issue. In that case, the country requesting the return must convince the counterpart country. Realizing a response to the earnest need for preventing illicit trading of cultural assets will require extensive national and civic societal efforts in the East Asian area to overcome its current deficiencies. The most effective way to prevent illicit trading of cultural property is rapid circulation of information between Interpol member countries, which will require development of an internet based communication system as well as more effective deployment of legislation to prevent trading of illicitly acquired cultural property, subscription to international conventions and cataloguing collections.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.24 no.2
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• pp.267-281
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• 2019

Energetic mesoscale eddies in the East Sea (ES) associated with strong mesoscale variability impacting circulation and environments were statistically characterized by analyzing satellite altimeter data collected during 1993-2017 and in-situ data obtained from four cruises conducted between 2015 and 2017. A total of 1,008 mesoscale eddies were detected, tracked, and identified and then classified into 27 groups characterized by mean lifetime (L, day), amplitude (H, m), radius (R, km), intensity per unit area (EI, $cm^2/s^2/km^2$), ellipticity (e), eddy kinetic energy (EKE, TJ), available potential energy (APE, TJ), and direction of movement. The center, boundary, and amplitude of mesoscale eddies identified from satellite altimeter data were compared to those from the in-situ observational data for the four cases, yielding uncertainties in the center position of 2-10 km, boundary position of 10-20 km, and amplitude of 0.6-5.9 cm. The mean L, H, R, EI, e, EKE, and APE of the ES mesoscale eddies during the total period are $95{\pm}104$ days, $3.5{\pm}1.5cm$, $39{\pm}6km$, $0.023{\pm}0.017cm^2/s^2/km^2$, $0.72{\pm}0.07$, $23{\pm}21TJ$, and $588{\pm}250TJ$, respectively. The ES mesoscale eddies tend to move following the mean surface current rather than propagating westward. The southern groups (south of the subpolar front) have a longer L, larger H, R, and higher EKE, APE; and stronger EI than those of the northern groups and tend to move a longer distance following surface currents. There are exceptions to the average characteristics, such as the quasi-stationary groups (the Wonsan Warm, Wonsan Cold, Western Japan Basin Warm, and Northern Subpolar Frontal Cold Eddy groups) and short-lived groups with a relatively larger H, higher EKE, and APE and stronger EI (the Yamato Coastal Warm, Central Yamato Warm, and Eastern Japan Basin Coastal Warm eddy groups). Small eddies in the northern ES hardly resolved using the satellite altimetry data only, were not identified here and discussed with potential over-estimations of the mean L, H, R, EI, EKE, and APE. This study suggests that the ES mesoscale eddies 1) include newly identified groups such as the Hokkaido and the Yamato Rise Warm Eddies in addition to relatively well-known groups (e.g., the Ulleung Warm and the Dok Cold Eddies); 2) have a shorter L; smaller H, R, and lower EKE; and stronger EI and higher APE than those of the global ocean, and move following surface currents rather than propagating westward; and 3) show large spatial inhomogeneity among groups.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.85-107
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• 2019

Online consumers browse products belonging to a particular product line or brand for purchase, or simply leave a wide range of navigation without making purchase. The research on the behavior and purchase of online consumers has been steadily progressed, and related services and applications based on behavior data of consumers have been developed in practice. In recent years, customization strategies and recommendation systems of consumers have been utilized due to the development of big data technology, and attempts are being made to optimize users' shopping experience. However, even in such an attempt, it is very unlikely that online consumers will actually be able to visit the website and switch to the purchase stage. This is because online consumers do not just visit the website to purchase products but use and browse the websites differently according to their shopping motives and purposes. Therefore, it is important to analyze various types of visits as well as visits to purchase, which is important for understanding the behaviors of online consumers. In this study, we explored the clustering analysis of session based on click stream data of e-commerce company in order to explain diversity and complexity of search behavior of online consumers and typified search behavior. For the analysis, we converted data points of more than 8 million pages units into visit units' sessions, resulting in a total of over 500,000 website visit sessions. For each visit session, 12 characteristics such as page view, duration, search diversity, and page type concentration were extracted for clustering analysis. Considering the size of the data set, we performed the analysis using the Mini-Batch K-means algorithm, which has advantages in terms of learning speed and efficiency while maintaining the clustering performance similar to that of the clustering algorithm K-means. The most optimized number of clusters was derived from four, and the differences in session unit characteristics and purchasing rates were identified for each cluster. The online consumer visits the website several times and learns about the product and decides the purchase. In order to analyze the purchasing process over several visits of the online consumer, we constructed the visiting sequence data of the consumer based on the navigation patterns in the web site derived clustering analysis. The visit sequence data includes a series of visiting sequences until one purchase is made, and the items constituting one sequence become cluster labels derived from the foregoing. We have separately established a sequence data for consumers who have made purchases and data on visits for consumers who have only explored products without making purchases during the same period of time. And then sequential pattern mining was applied to extract frequent patterns from each sequence data. The minimum support is set to 10%, and frequent patterns consist of a sequence of cluster labels. While there are common derived patterns in both sequence data, there are also frequent patterns derived only from one side of sequence data. We found that the consumers who made purchases through the comparative analysis of the extracted frequent patterns showed the visiting pattern to decide to purchase the product repeatedly while searching for the specific product. The implication of this study is that we analyze the search type of online consumers by using large - scale click stream data and analyze the patterns of them to explain the behavior of purchasing process with data-driven point. Most studies that typology of online consumers have focused on the characteristics of the type and what factors are key in distinguishing that type. In this study, we carried out an analysis to type the behavior of online consumers, and further analyzed what order the types could be organized into one another and become a series of search patterns. In addition, online retailers will be able to try to improve their purchasing conversion through marketing strategies and recommendations for various types of visit and will be able to evaluate the effect of the strategy through changes in consumers' visit patterns.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.179-196
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• 2019

Recently, the "Smart Consumer" has been emerging. He or she is increasingly inclined to search for and purchase products by taking into account personal judgment or expert reviews rather than by relying on information delivered through manufacturers' advertising. This is especially true when purchasing cosmetics. Because cosmetics act directly on the skin, consumers respond seriously to dangerous chemical elements they contain or to skin problems they may cause. Above all, cosmetics should fit well with the purchaser's skin type. In addition, changes in global cosmetics consumer trends make it necessary to study this field. The desire to find one's own individualized cosmetics is being revealed to consumers around the world and is known as "Finding the Holy Grail." Many consumers show a deep interest in customized cosmetics with the cultural boom known as "K-Beauty" (an aspect of "Han-Ryu"), the growth of personal grooming, and the emergence of "self-culture" that includes "self-beauty" and "self-interior." These trends have led to the explosive popularity of cosmetics made in Korea in the Chinese and Southeast Asian markets. In order to meet the customized cosmetics needs of consumers, cosmetics manufacturers and related companies are responding by concentrating on delivering premium services through the convergence of ICT(Information, Communication and Technology). Despite the evolution of companies' responses regarding market trends toward customized cosmetics, there is no "Intelligent Data Platform" that deals holistically with consumers' skin condition experience and thus attaches emotions to products and services. To find the Holy Grail of customized cosmetics, it is important to acquire and analyze consumer data on what they want in order to address their experiences and emotions. The emotions consumers are addressing when purchasing cosmetics varies by their age, sex, skin type, and specific skin issues and influences what price is considered reasonable. Therefore, it is necessary to classify emotions regarding cosmetics by individual consumer. Because of its importance, consumer emotion analysis has been used for both services and products. Given the trends identified above, we judge that consumer emotion analysis can be used in our study. Therefore, we collected and indexed data on consumers' emotions regarding their cosmetics experiences focusing on consumers' language. We crawled the cosmetics emotion data from SNS (blog and Twitter) according to sales ranking ($1^{st}$ to $99^{th}$), focusing on the ample/serum category. A total of 357 emotional adjectives were collected, and we combined and abstracted similar or duplicate emotional adjectives. We conducted a "Consumer Sentiment Journey" workshop to build a "Consumer Sentiment Dictionary," and this resulted in a total of 76 emotional adjectives regarding cosmetics consumer experience. Using these 76 emotional adjectives, we performed clustering with the Self-Organizing Map (SOM) method. As a result of the analysis, we derived eight final clusters of cosmetics consumer sentiments. Using the vector values of each node for each cluster, the characteristics of each cluster were derived based on the top ten most frequently appearing consumer sentiments. Different characteristics were found in consumer sentiments in each cluster. We also developed a cosmetics experience pattern map. The study results confirmed that recommendation and classification systems that consider consumer emotions and sentiments are needed because each consumer differs in what he or she pursues and prefers. Furthermore, this study reaffirms that the application of emotion and sentiment analysis can be extended to various fields other than cosmetics, and it implies that consumer insights can be derived using these methods. They can be used not only to build a specialized sentiment dictionary using scientific processes and "Design Thinking Methodology," but we also expect that these methods can help us to understand consumers' psychological reactions and cognitive behaviors. If this study is further developed, we believe that it will be able to provide solutions based on consumer experience, and therefore that it can be developed as an aspect of marketing intelligence.

• Journal of the Korean Institute of Landscape Architecture
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• v.46 no.6
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• pp.49-59
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• 2018

The purpose of this study was to analyze the importance and satisfaction of resources in the mouth of Nakdong River. A Pearson's chi-square test was performed in SPSS 24.0 for statistical analysis and the result of the study was summarized by three points. First, the results of importance analysis on resources in Nakdong estuary found that the importance of ecology resources was the highest with 27.1%, followed by landscape resources (18.5%), waterside leisure resources (6.5%), complex cultural resources (5.4%), and historic and cultural resources (3.3%). The probability values (p-value) of each group had shown significant differences depending on gender, age, and the location of the survey. For instance, women respondents reported a higher preference to ecology resources and complex cultural resources such as museums than men respondents as much as two times and three times, respectively. Meanwhile, men respondents showed a higher preference to waterside leisure resources in three times as much as women respondents. As for the analysis by age, the respondents in their 20s and 30s recorded a higher value than those in other age groups, and people in their 30s reported a higher preference to waterside leisure resources than those in different age groups by three times. Lastly, no significant differences were found in the preference analysis by occupation (p>.05). With regard to the results of satisfaction analysis, the average level of satisfaction on landscape resources was 6.01, and that of ecology resources and complex cultural resource were 5.65 and 5.15, respectively. Also, significant differences were found between landscape and ecology resources in the satisfaction analysis by age, landscape resources by age, ecology resources by region, and between landscape resources and ecology resources by occupation. The p-value of complex cultural resources was p=0.012, although the satisfaction level of landscape resources and ecology resources were reported to have no significant differences by age. As for the level of satisfaction in landscape resources, respondents in their 40s and 50s showed a high level of satisfaction. However, those in their 20s showed a relatively low level of satisfaction in the same category. The survey respondents living in Busan and South Gyeongsang Province and those living outside the regions revealed no significant differences in terms of satisfaction in landscape resources and complex cultural resources. However, the two same groups were found to show significant differences in the satisfaction analysis on ecology resources. In the satisfaction analysis of landscape resources and ecology resources by occupation, significant differences were found among college students, government employees, ordinary citizens, and expert groups. However, they showed no significant differences in the level of satisfaction to complex cultural resources. Third, the results of importance-satisfaction analysis on Nakdong estuary found that the average levels of satisfaction to landscape resources for each group of respondents who considered landscape, ecology, and cultural resources as important was 6.19, 6.08, and 5.67, respectively. Their levels of satisfaction on ecology resources were 5.95, 5.57, and 5.41 for each. Its correlation to the importance was insignificant. However, it was confirmed that the correlation to the level of satisfaction on complex cultural resources had a significant difference (p=0.025). In addition, the results of the analysis on 15 detailed items that was carried out with the aim to improving values and vitalizing resources in the mouth of Nakdong River found that respondents considered that the vitalization of eco-tourism (49.5%) and restoration of reed marsh (47.5%) were important. The results of detailed analysis revealed respondents' high awareness on the need of enhancing values on ecology resources. Also, improving infrastructure nearby the mouth, creating cycling routes, walkways, waterside leisure facilities, and others were considered as the requirements for the vitalization of Nakdong estuary.