• Korean Journal of Heritage: History & Science
• /
• v.57 no.2
• /
• pp.52-78
• /
• 2024

This study analyzes the sculptural art of SeokhaSichan(石霞施讚, 1893-1958), a significant figure in modern Korean Buddhist art, to re-examine his contributions and standing in the history of Korean Buddhist art. Sichan expanded the boundaries of modern Korean Buddhist art by developing a unique style based on the traditional sculptural techniques he learned from his mentor, Wanho Nakhyeon (玩虎洛現, 1869~1933). This study explores Sichan's artistic development, focusing on his artistic characteristics and sculptural evolution. Sichan's early works are characterized by small sculptures modeled after the main Buddha of Seokguram Grotto and heavily influenced by his mentor, WanhoNakhyeon. In his later works, notable features include a sense of massive volume, larger scale, upright postures, integration of the Buddha statue with its pedestal, and decorative treatment of drapery. These changes are interpreted as Sichan's response to social changes and his reflection of inner contemplation and artistic exploration in his works. This study reveals the influences of Wanho Nakhyeon, collaborations with Toewon Woneil(退雲圓日, 1877~1939), interactions with patron Kim Jiseonghwa(金至誠華), and master-disciple relationship with successor Geumchun Seongpil(金春性必) through literature review and newly discovered works by Sichan. His works and his artistic evolution are pivotal milestones in the history of modern Korean Buddhist sculpture, demonstrating a unique integration of traditional and modern aesthetics. This study provides valuable insights into how Sichan's artistic legacy was inherited and developed by subsequent generations and offers crucial materials for the study of modern Korean Buddhist sculpture history.

• Journal of the Korean Society for information Management
• /
• v.41 no.3
• /
• pp.269-288
• /
• 2024

In the era of digital transformation, discussions about digital curation have become increasingly active not only in academia but also in various fields. The primary purpose of this study is to analyze the conceptual changes in digital curation over time, particularly by examining the definition statements related to digital curation as described in academic literature. To achieve this, academic research papers from 2009, when the term "digital curation" was first mentioned, to 2023 were collected, and definition statements that explained relevant concepts were extracted. Basic statistical analyses were conducted. Using DMR topic modeling and word networks, the relationships among keywords and the changes in their importance over time were examined, and a conceptual map of digital curation was made focusing on the main topics. The results revealed that the concept of digital curation is primarily centered around the themes of "data preservation," "traditional curator roles," and "product recommendation curation." Depending on the researchers' intentions for utilizing digital curation, the concept was expanded to include topics such as "content distribution and classification," "information usage," and "curation models." This study is significant in that it analyzed the concept of digital curation through definition statements reflecting the perspectives of researchers. Additionally, the study holds value in explicitly identifying changes in the concepts that researchers emphasize over time through the trends in topic prevalence.

• Journal of Intelligence and Information Systems
• /
• v.19 no.4
• /
• pp.55-79
• /
• 2013

In this paper, we propose a hybrid genetic algorithm (HGA) approach to effectively solve the reverse logistics network with centralized centers (RLNCC). For the proposed HGA approach, genetic algorithm (GA) is used as a main algorithm. For implementing GA, a new bit-string representation scheme using 0 and 1 values is suggested, which can easily make initial population of GA. As genetic operators, the elitist strategy in enlarged sampling space developed by Gen and Chang (1997), a new two-point crossover operator, and a new random mutation operator are used for selection, crossover and mutation, respectively. For hybrid concept of GA, an iterative hill climbing method (IHCM) developed by Michalewicz (1994) is inserted into HGA search loop. The IHCM is one of local search techniques and precisely explores the space converged by GA search. The RLNCC is composed of collection centers, remanufacturing centers, redistribution centers, and secondary markets in reverse logistics networks. Of the centers and secondary markets, only one collection center, remanufacturing center, redistribution center, and secondary market should be opened in reverse logistics networks. Some assumptions are considered for effectively implementing the RLNCC The RLNCC is represented by a mixed integer programming (MIP) model using indexes, parameters and decision variables. The objective function of the MIP model is to minimize the total cost which is consisted of transportation cost, fixed cost, and handling cost. The transportation cost is obtained by transporting the returned products between each centers and secondary markets. The fixed cost is calculated by opening or closing decision at each center and secondary markets. That is, if there are three collection centers (the opening costs of collection center 1 2, and 3 are 10.5, 12.1, 8.9, respectively), and the collection center 1 is opened and the remainders are all closed, then the fixed cost is 10.5. The handling cost means the cost of treating the products returned from customers at each center and secondary markets which are opened at each RLNCC stage. The RLNCC is solved by the proposed HGA approach. In numerical experiment, the proposed HGA and a conventional competing approach is compared with each other using various measures of performance. For the conventional competing approach, the GA approach by Yun (2013) is used. The GA approach has not any local search technique such as the IHCM proposed the HGA approach. As measures of performance, CPU time, optimal solution, and optimal setting are used. Two types of the RLNCC with different numbers of customers, collection centers, remanufacturing centers, redistribution centers and secondary markets are presented for comparing the performances of the HGA and GA approaches. The MIP models using the two types of the RLNCC are programmed by Visual Basic Version 6.0, and the computer implementing environment is the IBM compatible PC with 3.06Ghz CPU speed and 1GB RAM on Windows XP. The parameters used in the HGA and GA approaches are that the total number of generations is 10,000, population size 20, crossover rate 0.5, mutation rate 0.1, and the search range for the IHCM is 2.0. Total 20 iterations are made for eliminating the randomness of the searches of the HGA and GA approaches. With performance comparisons, network representations by opening/closing decision, and convergence processes using two types of the RLNCCs, the experimental result shows that the HGA has significantly better performance in terms of the optimal solution than the GA, though the GA is slightly quicker than the HGA in terms of the CPU time. Finally, it has been proved that the proposed HGA approach is more efficient than conventional GA approach in two types of the RLNCC since the former has a GA search process as well as a local search process for additional search scheme, while the latter has a GA search process alone. For a future study, much more large-sized RLNCCs will be tested for robustness of our approach.

• (The) Research of the performance art and culture
• /
• no.32
• /
• pp.71-106
• /
• 2016

This study analyzes the current work of the traditional theater around 'Back Parkcheomji(season2)' of theatre troupe 'Saninomou'. 'Back Parkcheomji(season2)' has proved that it is possible modernization while at the same time preserving the traditional theater. As a result, 'Back Parkcheomji(season2)' regained the spirit of contemporary social criticism and reality inherent in Kokdugaksinorum. The performance are beyond the traditional production method, which has created a new performance aspects. 'Back Parkcheomji(season2)' has created the puppets like this 'Kimga' 'Seweolho' 'Ryukbang' 'Chourani'. Traditional and creative dolls has criticized our modern society at the same stage. On the other hand, plays such as tightrope, Pungmul, Burna confirmed the spirit of Namsadangpae, and gave a dramatic fun. 'Back Parkcheomji(season2)' has dual stage. The dual stage will produce a magnificent spectacle, and has provided a variety of attractions. 'Back Parkcheomji(season2)' re-created the traditional theater of Namsadangpae in vivid contemporary version. The performance has made the opportunity to think again about the value of classical and allowed to recognize the new phase of classical theater.

• Korean Journal of Construction Engineering and Management
• /
• v.10 no.2
• /
• pp.65-74
• /
• 2009

It is expected that the number of apartment complexes in Korea that are over 20 years old will rapidly increase to more than 3,500,000. Consequently, the remodeling of these buildings is being revitalized throughout the country. Among the requirements for such remodeling, the expansion of parking lots has considerable weight. When enlarging a parking lot, the access route from an underground floor to the main building (i.e., the means of entry into the main building) determines the possibility of vertical enlargement for elevators, the size of the parking lot, the construction period, and construction expenses, etc. When enlarging an underground parking lot of an apartment complex, the access between the main building and the parking lot, as well as the inhabitants' requirements for entering the main building, are generally determined based on the designer's experience, rather than on the exact estimation of the peculiarity of the complex. In order to resolve such a problem, when enlarging an underground parking lot, a systematic and rational method is needed for selecting the means of entry into the main building. In this study, a selection model is derived for the method of selecting an access route into the main building when constructing an underground parking lot, in order to provide a reasonable decision-making process. A research method was investigated for determining the access route into the main building when enlarging a parking lot. On the basis of research carried out through in-depth interviews with experts, the characteristics for each means of entry into the main building were analyzed and the factors affecting the selection of the access route were deduced. The affecting factors selected were construction efficiency, convenience efficiency and economic efficiency. Weight values were then estimated for the selected affecting factors by applying the AHP method. Results showed that convenience efficiency, which gained the highest value, is the most important factor in selecting the means of entry into the main building. The most suitable means of entry into the main building was also suggested after estimating the applicability of the site by selecting complexes with remodeling possibility. This study will be applied as a reference for selecting the means of entry into the main building when constructing an underground parking lot particularly for older apartment complexes.

• Journal of the Korean association of regional geographers
• /
• v.7 no.3
• /
• pp.107-120
• /
• 2001

This study is concerned with providing a reliable procedure of calibrating a set of places specific distance parameters and with applying it to U.S. inter-State migration flows between 1985 and 1900. It attempts to conform to recent advances in quantitative geography that are characterized by an integration of ESDA(exploratory spatial data analysis) and local statistics. ESDA aims to detect the spatial clustering and heterogeneity by visualizing and exploring spatial patterns. A local statistic is defined as a statistically processed value given to each location as opposed to a global statistic that only captures an average trend across a whole study region. Whereas a global distance parameter estimates an averaged level of the friction of distance, place-specific distance parameters calibrate spatially varying effects of distance. It is presented that a poisson regression with an adequately specified design matrix yields a set of either origin-or destination-specific distance parameters. A case study demonstrates that the proposed model is a reliable device of measuring a spatial dimension of migration, and that place-specific distance parameters are spatially heterogeneous as well as spatially clustered.

• Spatial Information Research
• /
• v.11 no.3
• /
• pp.261-274
• /
• 2003

The effective probability-based tile pre-fetching algorithm and the collaborative cache replacement algorithm are able to reduce the response time for user's requests by transferring tiles which will be used in advance and determining tiles which should be removed from the restrictive cache space of a client based on the future access probabilities in Web GISs(Geographical Information Systems). The Web GISs have multi-level abstracted data for the quick response time when zoom-in and zoom-out queries are requested. But, the previous pre-fetching algorithm is applied on only two-dimensional pre-fetching space, and doesn't consider expanded pre-fetching space for multi-level abstracted data in Web GISs. In this thesis, a probability-based pre-fetching algorithm for multi-level abstracted in Web GISs was proposed. This algorithm expanded the previous two-dimensional pre-fetching space into three-dimensional one for pre-fetching tiles of the upper levels or lower levels. Moreover, we evaluated the effect of the proposed pre-fetching algorithm by using a simulation method. Through the experimental results, the response time for user requests was improved 1.8%∼21.6% on the average. Consequently, in Web GISs with multi-level abstracted data, the proposed pre-fetching algorithm and the collaborative cache replacement algorithm can reduce the response time for user requests substantially.

• Journal of Intelligence and Information Systems
• /
• v.23 no.4
• /
• pp.77-110
• /
• 2017

Recently, the diversification and individualization of consumption patterns through the web and mobile devices based on the Internet have been rapid. As this happens, the efficient operation of the offline store, which is a traditional distribution channel, has become more important. In order to raise both the sales and profits of stores, stores need to supply and sell the most attractive products to consumers in a timely manner. However, there is a lack of research on which SKUs, out of many products, can increase sales probability and reduce inventory costs. In particular, if a company sells products through multiple in-store stores across multiple locations, it would be helpful to increase sales and profitability of stores if SKUs appealing to customers are recommended. In this study, the recommender system (recommender system such as collaborative filtering and hybrid filtering), which has been used for personalization recommendation, is suggested by SKU recommendation method of a store unit of a distribution company that handles a homogeneous brand through a plurality of sales stores by country and region. We calculated the similarity of each store by using the purchase data of each store's handling items, filtering the collaboration according to the sales history of each store by each SKU, and finally recommending the individual SKU to the store. In addition, the store is classified into four clusters through PCA (Principal Component Analysis) and cluster analysis (Clustering) using the store profile data. The recommendation system is implemented by the hybrid filtering method that applies the collaborative filtering in each cluster and measured the performance of both methods based on actual sales data. Most of the existing recommendation systems have been studied by recommending items such as movies and music to the users. In practice, industrial applications have also become popular. In the meantime, there has been little research on recommending SKUs for each store by applying these recommendation systems, which have been mainly dealt with in the field of personalization services, to the store units of distributors handling similar brands. If the recommendation method of the existing recommendation methodology was 'the individual field', this study expanded the scope of the store beyond the individual domain through a plurality of sales stores by country and region and dealt with the store unit of the distribution company handling the same brand SKU while suggesting a recommendation method. In addition, if the existing recommendation system is limited to online, it is recommended to apply the data mining technique to develop an algorithm suitable for expanding to the store area rather than expanding the utilization range offline and analyzing based on the existing individual. The significance of the results of this study is that the personalization recommendation algorithm is applied to a plurality of sales outlets handling the same brand. A meaningful result is derived and a concrete methodology that can be constructed and used as a system for actual companies is proposed. It is also meaningful that this is the first attempt to expand the research area of the academic field related to the existing recommendation system, which was focused on the personalization domain, to a sales store of a company handling the same brand. From 05 to 03 in 2014, the number of stores' sales volume of the top 100 SKUs are limited to 52 SKUs by collaborative filtering and the hybrid filtering method SKU recommended. We compared the performance of the two recommendation methods by totaling the sales results. The reason for comparing the two recommendation methods is that the recommendation method of this study is defined as the reference model in which offline collaborative filtering is applied to demonstrate higher performance than the existing recommendation method. The results of this model are compared with the Hybrid filtering method, which is a model that reflects the characteristics of the offline store view. The proposed method showed a higher performance than the existing recommendation method. The proposed method was proved by using actual sales data of large Korean apparel companies. In this study, we propose a method to extend the recommendation system of the individual level to the group level and to efficiently approach it. In addition to the theoretical framework, which is of great value.

• Journal of the Korean Society of Food Science and Nutrition
• /
• v.44 no.9
• /
• pp.1388-1398
• /
• 2015

Quality Function Deployment (QFD) is the most complete and comprehensive method for translating what customers need from a product. This study utilized QFD to develop sauces made from Gochujang and to determine how to fulfill international customers' requirements. A customer survey and expert opinion survey were conducted from May 13 to August 22, 2014 and targeted 220 consumers and 20 experts in the U.S. and China. Finally, a total of 208 (190 consumers and 18 experts) useable data were selected. The top three customer requirements for Gochujang sauces were identified as fresh flavor (4.40), making better flavor (3.99), and cooking availability (3.90). Thirty-three engineering characteristics were developed. The results from the calculation of relative importance of engineering characteristics identified that 'cooking availability', 'free sample and food testing', 'unique concept', and 'development of brand' were the highest. The relative importance of engineering characteristics, correlation, and technical difficulties are ranked, and this result could contribute to the development Korean sauces based on customer needs and engineering characteristics.

• Korean Journal of Remote Sensing
• /
• v.31 no.5
• /
• pp.449-459
• /
• 2015

The conventional National Forest Inventory(NFI)-based forest carbon stock estimation method is suitable for national-scale estimation, but is not for regional-scale estimation due to the lack of NFI plots. In this study, for the purpose of regional-scale carbon stock estimation, we created grid-based forest carbon stock maps using spatial ancillary data and two types of up-scaling methods. Chungnam province was chosen to represent the study area and for which the $5^{th}$ NFI (2006~2009) data was collected. The first method (method 1) selects forest type map as ancillary data and uses regression model for forest carbon stock estimation, whereas the second method (method 2) uses satellite imagery and k-Nearest Neighbor(k-NN) algorithm. Additionally, in order to consider uncertainty effects, the final AGB carbon stock maps were generated by performing 200 iterative processes with Monte Carlo simulation. As a result, compared to the NFI-based estimation(21,136,911 tonC), the total carbon stock was over-estimated by method 1(22,948,151 tonC), but was under-estimated by method 2(19,750,315 tonC). In the paired T-test with 186 independent data, the average carbon stock estimation by the NFI-based method was statistically different from method2(p<0.01), but was not different from method1(p>0.01). In particular, by means of Monte Carlo simulation, it was found that the smoothing effect of k-NN algorithm and mis-registration error between NFI plots and satellite image can lead to large uncertainty in carbon stock estimation. Although method 1 was found suitable for carbon stock estimation of forest stands that feature heterogeneous trees in Korea, satellite-based method is still in demand to provide periodic estimates of un-investigated, large forest area. In these respects, future work will focus on spatial and temporal extent of study area and robust carbon stock estimation with various satellite images and estimation methods.