• Journal of the Korean Geographical Society
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• v.51 no.5
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• pp.613-632
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• 2016

The recent diagnosis of the Anthropocene challenges public understanding of nature as a pure and singular entity removed from society, as the diagnosis confirms the earth-changing force of humans. In geography, the nature-society divide has been critically interrogated long before the diagnosis of the Anthropocene, developing several ways of theorizing nature-society relations. This paper introduces a new frontier for such theoretical endeavors: more-than-human geography. Inspired by the material and performative turn in geography and the social sciences around the 2000s, more-than-human geographers have sought to re-engage with the livingness of the world in the study of nature-society relations. Drawing on actor-network theory, non-representational theory (NRT) and vitalism, they have developed innovative ways of thinking about and relating to nature through the key concepts of 'nonhuman agency' and 'affect'. While more-than-human geography has been extensively debated and developed in recent Euro-American scholarship on cultural and economic geography, it has so far received limited attention in Korean geographical studies on nature. This paper aims to address this gap by discussing the key concepts and seminal work of more-than-human geography. I first outline four theoretical strands through which nature-society relations are perceived in geography. I then offer an overview of more-than-human geography, discussing its theoretical foundations and considering ontologies, epistemologies, politics and ethics associated with nature-society relations. Then, I compare more-than-human geography with political ecology, which is the mainstream critical approach in contemporary environmental social sciences. I would argue that more-than-human geography further challenges and develops political ecology through its heightened attention to the affective capacity of nonhumans and the methodological ethos of doing a careful political ecology. I conclude by reflecting on the implications of more-than-human geography for Korean studies on nature-society relations.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.159-172
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• 2010

The recommender system is one of the possible solutions to assist customers in finding the items they would like to purchase. To date, a variety of recommendation techniques have been developed. One of the most successful recommendation techniques is Collaborative Filtering (CF) that has been used in a number of different applications such as recommending Web pages, movies, music, articles and products. CF identifies customers whose tastes are similar to those of a given customer, and recommends items those customers have liked in the past. Numerous CF algorithms have been developed to increase the performance of recommender systems. Broadly, there are memory-based CF algorithms, model-based CF algorithms, and hybrid CF algorithms which combine CF with content-based techniques or other recommender systems. While many researchers have focused their efforts in improving CF performance, the theoretical justification of CF algorithms is lacking. That is, we do not know many things about how CF is done. Furthermore, the relative performances of CF algorithms are known to be domain and data dependent. It is very time-consuming and expensive to implement and launce a CF recommender system, and also the system unsuited for the given domain provides customers with poor quality recommendations that make them easily annoyed. Therefore, predicting the performances of CF algorithms in advance is practically important and needed. In this study, we propose an efficient approach to predict the performance of CF. Social Network Analysis (SNA) and Artificial Neural Network (ANN) are applied to develop our prediction model. CF can be modeled as a social network in which customers are nodes and purchase relationships between customers are links. SNA facilitates an exploration of the topological properties of the network structure that are implicit in data for CF recommendations. An ANN model is developed through an analysis of network topology, such as network density, inclusiveness, clustering coefficient, network centralization, and Krackhardt's efficiency. While network density, expressed as a proportion of the maximum possible number of links, captures the density of the whole network, the clustering coefficient captures the degree to which the overall network contains localized pockets of dense connectivity. Inclusiveness refers to the number of nodes which are included within the various connected parts of the social network. Centralization reflects the extent to which connections are concentrated in a small number of nodes rather than distributed equally among all nodes. Krackhardt's efficiency characterizes how dense the social network is beyond that barely needed to keep the social group even indirectly connected to one another. We use these social network measures as input variables of the ANN model. As an output variable, we use the recommendation accuracy measured by F1-measure. In order to evaluate the effectiveness of the ANN model, sales transaction data from H department store, one of the well-known department stores in Korea, was used. Total 396 experimental samples were gathered, and we used 40%, 40%, and 20% of them, for training, test, and validation, respectively. The 5-fold cross validation was also conducted to enhance the reliability of our experiments. The input variable measuring process consists of following three steps; analysis of customer similarities, construction of a social network, and analysis of social network patterns. We used Net Miner 3 and UCINET 6.0 for SNA, and Clementine 11.1 for ANN modeling. The experiments reported that the ANN model has 92.61% estimated accuracy and 0.0049 RMSE. Thus, we can know that our prediction model helps decide whether CF is useful for a given application with certain data characteristics.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.21-41
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• 2010

This paper proposes a system that can serve users with appropriate search results through real time filtering, and implemented adaptive user profiling based personalized information retrieval system(PIRS) using users' implicit feedbacks in order to deal with the problem of existing search systems such as Google or MSN that does not satisfy various user' personal search needs. One of the reasons that existing search systems hard to satisfy various user' personal needs is that it is not easy to recognize users' search intentions because of the uncertainty of search intentions. The uncertainty of search intentions means that users may want to different search results using the same query. For example, when a user inputs "java" query, the user may want to be retrieved "java" results as a computer programming language, a coffee of java, or a island of Indonesia. In other words, this uncertainty is due to ambiguity of search queries. Moreover, if the number of the used words for a query is fewer, this uncertainty will be more increased. Real-time filtering for search results returns only those results that belong to user-selected domain for a given query. Although it looks similar to a general directory search, it is different in that the search is executed for all web documents rather than sites, and each document in the search results is classified into the given domain in real time. By applying information filtering using real time directory classifying technology for search results to personalization, the number of delivering results to users is effectively decreased, and the satisfaction for the results is improved. In this paper, a user preference profile has a hierarchical structure, and consists of domains, used queries, and selected documents. Because the hierarchy structure of user preference profile can apply the context when users perfomed search, the structure is able to deal with the uncertainty of user intentions, when search is carried out, the intention may differ according to the context such as time or place for the same query. Furthermore, this structure is able to more effectively track web documents search behaviors of a user for each domain, and timely recognize the changes of user intentions. An IP address of each device was used to identify each user, and the user preference profile is continuously updated based on the observed user behaviors for search results. Also, we measured user satisfaction for search results by observing the user behaviors for the selected search result. Our proposed system automatically recognizes user preferences by using implicit feedbacks from users such as staying time on the selected search result and the exit condition from the page, and dynamically updates their preferences. Whenever search is performed by a user, our system finds the user preference profile for the given IP address, and if the file is not exist then a new user preference profile is created in the server, otherwise the file is updated with the transmitted information. If the file is not exist in the server, the system provides Google' results to users, and the reflection value is increased/decreased whenever user search. We carried out some experiments to evaluate the performance of adaptive user preference profile technique and real time filtering, and the results are satisfactory. According to our experimental results, participants are satisfied with average 4.7 documents in the top 10 search list by using adaptive user preference profile technique with real time filtering, and this result shows that our method outperforms Google's by 23.2%.

• Food Science and Preservation
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• v.20 no.4
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• pp.554-563
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• 2013

The changes in quality properties and nutritional components for two mugworts, namely, Artemisia capillaris Thumberg Artemisiae asiaticae Nakai fermented by Bacillus strains were characterized followed by rapid pattern analysis of volatile flavor compounds through the SAW-based electronic nose sensor in the GC system. After fermentation, the pH has remarkably decreased from 6.0~6.4 to 4.6~5.1 and there has been a slight change in the total soluble solids. The L (lightness) and b (yellowness) values in the Hunter's color system significantly decreased, whilst the a (redness) value increased via fermentation. The HPLC analysis demonstrated that the total amino acids increased in quantity and the essential amino acids were higher in the A. asiaticae Nakai than in the A. capillaris Thumberg, specially with high contents of glutamic and aspartic acid. After fermentation, the monounsaturated fatty acid increased in the A. asiaticae Nakai and the polyunsaturated fatty acids increased in the A. capillaris Thumberg. While the total polyphenol contents have not been affected by fermentation, the total sugar contents have dramatically decreased. Scopoletin, which is one of the most important index components in mugworts, was highly abundant in the A. capillaris Thumberg; however, it was not detected in the A. asiaticae Nakai. Small pieces of plant tissue in the surface microstructure were found in the fermented mugworts through the use of the scanning electron microscope (SEM). Volatile flavor compounds via electronic nose showed that the intensity of several peaks has increased and additional seven flavor peaks have been produced after fermentation. The VaporPrintTM images demonstrated a notable difference in flavors between the A. asiaticae Nakai and A. capillaris Thumberg, and the fermentation enabled the mugworts to produce subtle differences in flavor.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2003.05a
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• pp.181-186
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• 2003

The satellite navigation system is widely used for identifying a user's position regardless of weather or geographic conditions and also make effect on new technology of marine LBS(Location Based Service), which has the technology of geographic information such as the ENC. Generally, there are conceivable systems of marine LBS such as ECDIS, or ECS that use the ENC itself with powerful processor in installed type on ships bridge. Since the ENC is relatively heavy structure with dummy format for data transfer between different systems, we should reduce the ENC to small and compact size in order to use it in mobile platform. In this paper, we assumed that the mobile system like PDA, or Webpad can be used for small capability of mobile platform. However, the ENC should be updated periodically by update profile data produced by HO. If we would reduce the ENC without a consideration of update, we could not get newly updated data furthermore. As summary, we studied considerations for ENC reduction with update capability. It will make the ENC be useful in many mobile platforms for various applications.

• Journal of Life Science
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• v.23 no.11
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• pp.1325-1335
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• 2013

Working dogs, such as rescue dogs, military watch dogs, guide dogs, and search dogs, are selected by in-training examination of desired traits, including concentration, possessiveness, and boldness. In recent years, genetic information has been considered to be an important factor for the outstanding abilities of working dogs. To characterize the molecular features of the canine genes related to phenotypes for working dogs, we investigated the 24 previously reported genes (AR, BDNF, DAT, DBH, DGCR2, DRD4, MAOA, MAOB, SLC6A4, TH, TPH2, IFT88, KCNA3, TBR2, TRKB, ACE, GNB1, MSTN, PLCL1, SLC25A22, WFIKKN2, APOE, GRIN2B, and PIK3CG) that were categorized to personality, olfactory sense, and athletic/learning ability. We analyzed the chromosomal location, gene-gene interactions, Gene Ontology, and expression patterns of these genes using bioinformatic tools. In addition, variable numbers of tandem repeat (VNTR) or microsatellite (MS) polymorphism in the AR, MAOA, MAOB, TH, DAT, DBH, and DRD4 genes were reviewed. Taken together, we suggest that the genetic background of the canine genes associated with various working dog behaviors and skill performance attributes could be used for proper selection of superior working dogs.

• Journal of KIISE:Databases
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• v.28 no.4
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• pp.529-544
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• 2001

Prefetching is an effective method to minimize the number of roundtrips between the client and the server in database management systems. In this paper we propose new notions of the type-level access pattern and the type-level access locality and developed an efficient prefetchin policy based on the notions. The type-level access patterns is a sequence of attributes that are referenced in accessing the objects: the type-level access locality a phenomenon that regular and repetitive type-level access patterns exist. Existing prefetching methods are based on object-level or page-level access patterns, which consist of object0ids of page-ids of the objects accessed. However, the drawback of these methods is that they work only when exactly the same objects or pages are accessed repeatedly. In contrast, even though the same objects are not accessed repeatedly, our technique effectively prefetches objects if the same attributes are referenced repeatedly, i,e of there is type-level access locality. Many navigational applications in Object-Relational Database Management System(ORDBMs) have type-level access locality. Therefore our technique can be employed in ORDBMs to effectively reduce the number of roundtrips thereby significantly enhancing the performance. We have conducted extensive experiments in a prototype ORDBMS to show the effectiveness of our algorithm. Experimental results using the 007 benchmark and a real GIS application show that our technique provides orders of magnitude improvements in the roundtrips and several factors of improvements in overall performance over on-demand fetching and context-based prefetching, which a state-of the art prefetching method. These results indicate that our approach significantly and is a practical method that can be implemented in commercial ORDMSs.

• Journal of Korean Classical Literature and Education
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• no.35
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• pp.153-193
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• 2017

This study explores the creation and enjoyment of Kuwoonmong (九雲夢) using a reference system called the cultural imagination, which is related to the Yin-Yang (陰陽) and Wu Xing (五行). When Kim Manjung wrote Guwoonmong, he may have composed figures and events based on this imagination. In particular, when he designed the eight seonnyeo (팔선녀), he set the order such as Gap (甲), Eul (乙), Byeong (병), Jeong (丁), etc. and characterized them according to the celestial stem (天干). Thus it was easy to avoid overlapping of characters and to construct various stories and relationships between them. The table below shows the characters of Kuwoonmong corresponding to the celestial stem. In not only the individual person but also the narrative world, Kuwoonmon demonstrates Yin-Yang and Wu Xing's imagination. In this respect, Kuwoonmon can be considered a large symbol encompassing the abstract theory of Yin-Yang and Wu Xing. Of course, the writer, Kim, Manjung would not have tried to symbolize the principle intentionally. However, he was also present in the environment of the cultural imagination that has been formed over the years. The same is true for the contemporary recipients of Guwunmong. They would have had a pleasant experience applying the cultural imagination and strengthening their familiar world view and human view.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.42 no.2
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• pp.103-109
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• 2016

Efficacy of cosmetics has been mainly evaluated by qualitative and quantitative methods based on visual sense, tactile sense and skin structure until now. In this study, we suggested a novel evaluation method for skin status based on sound; measuring and analyzing the rubbing noise generated by applying cosmetics. First, the rubbing noise was measured at a close range by a high-sensitivity microphone in anechoic environment, and the noises were analyzed by 1/3 octave band analysis in frequency-domain. Three conditions, 1) before washing, 2) after washing and 3) after application of cosmetics, were compared. As a result, sound pressure level (SPL) of rubbing noise after washing was larger than that of before washing, and the SPL of rubbing noise after cosmetic application was the smallest. Furthermore, the energy of rubbing noise after application was higher than that of the before and after washing conditions in a low frequency band (lower than 2 kHz region). Conversely, the energy of rubbing noise after application was much lower than the others in a high-frequency band (upper than 2 kHz region). This change of energy distribution was described as a balloon-skin model. High SPL in the low frequency region after the cosmetic applications was due to the increase of "flexibility index", while SPL in the high frequency region significantly decreased because of the attenuation which is related to "softness index". Therefore, we developed two indices based on the spectrum-energy difference for evaluating skin conditions. This proposed method and indices were verified via skin flexibility and roughness measurement using cutometer and primos respectively. These results suggest that acoustic measurement of skin friction noise may be a new skin status evaluation method.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.5
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• pp.581-589
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• 2021

With the recent increase in the introduction of micro-electric vehicles in Korea, interest in micro-electric vehicle user satisfaction is increasing to revitalize related markets. In this paper, a basic study was conducted on the development of public services using micro-electric vehicle based on the constituent factors of user satisfaction. The survey includes: ① 'Analytic Hierarchy Process (AHP) for selecting the priority factors of user satisfaction of micro-electric vehicles', ② 'A survey of micro-electric vehicles image' to collect data in advance for providing users' preferences and transportation services for micro-electric vehicles, ③ In order to investigate the user satisfaction level of users who actually operated micro-electric vehicles, the order of 'user satisfaction survey of micro-electric vehicle drivers' was conducted. In the Analytic Hierarchy Process (AHP) analysis, it was found that users regarded as important in the order of 'user utilization data', 'vehicle movement data', and 'charging service data'. In the micro-electric vehicle image survey, users perceived micro-electric vehicles more positively in terms of "safety", 'durability', 'Ride comfort', 'design', 'MOOE (Maintenance and other operating expense)', and 'environment-friendly' when comparing micro-electric vehicles with electric motorcycles. In the survey on the user satisfaction of micro-electric vehicle drivers, the use of micro-electric vehicle did not directly affect work performance efficiency, and there was an experience of being disadvantaged on the road due to the size of the micro-electric vehicle, and driving in a cluster of micro-electric vehicle for outdoor advertisements. The city's public relations effect was great, but it was concerned about safety. In the future, based on the results of this study, we plan to build a user satisfaction structural equation model, preemptively discover feedback R&D for micro-electric vehicle utilization services in the public field, and actively seek to discover new public mobility support services.